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The dataset generation failed
Error code: DatasetGenerationError
Exception: ArrowNotImplementedError
Message: Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
Traceback: Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 583, in write_table
self._build_writer(inferred_schema=pa_table.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2029, in _prepare_split_single
num_examples, num_bytes = writer.finalize()
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 602, in finalize
self._build_writer(self.schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 404, in _build_writer
self.pa_writer = self._WRITER_CLASS(self.stream, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/pyarrow/parquet/core.py", line 1010, in __init__
self.writer = _parquet.ParquetWriter(
File "pyarrow/_parquet.pyx", line 2157, in pyarrow._parquet.ParquetWriter.__cinit__
File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
pyarrow.lib.ArrowNotImplementedError: Cannot write struct type 'model_kwargs' with no child field to Parquet. Consider adding a dummy child field.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1396, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1045, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1029, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1124, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1884, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2040, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
config
dict | report
dict | name
string | backend
dict | scenario
dict | launcher
dict | environment
dict | load
dict | forward
dict |
|---|---|---|---|---|---|---|---|---|
{
"name": "test_api_push_to_hub_mixin",
"backend": {
"name": "pytorch",
"version": "2.4.1+cpu",
"_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
"task": "fill-mask",
"library": "transformers",
"model_type": "bert",
"model": "google-bert/bert-base-uncased",
"processor": "google-bert/bert-base-uncased",
"device": "cpu",
"device_ids": null,
"seed": 42,
"inter_op_num_threads": null,
"intra_op_num_threads": null,
"model_kwargs": {},
"processor_kwargs": {},
"no_weights": false,
"device_map": null,
"torch_dtype": null,
"eval_mode": true,
"to_bettertransformer": false,
"low_cpu_mem_usage": null,
"attn_implementation": null,
"cache_implementation": null,
"autocast_enabled": false,
"autocast_dtype": null,
"torch_compile": false,
"torch_compile_target": "forward",
"torch_compile_config": {},
"quantization_scheme": null,
"quantization_config": {},
"deepspeed_inference": false,
"deepspeed_inference_config": {},
"peft_type": null,
"peft_config": {}
},
"scenario": {
"name": "inference",
"_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario",
"iterations": 1,
"duration": 1,
"warmup_runs": 1,
"input_shapes": {
"batch_size": 2,
"num_choices": 2,
"sequence_length": 16
},
"new_tokens": null,
"memory": true,
"latency": true,
"energy": false,
"forward_kwargs": {},
"generate_kwargs": {},
"call_kwargs": {}
},
"launcher": {
"name": "process",
"_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
"device_isolation": false,
"device_isolation_action": null,
"numactl": false,
"numactl_kwargs": {},
"start_method": "spawn"
},
"environment": {
"cpu": " AMD EPYC 7763 64-Core Processor",
"cpu_count": 4,
"cpu_ram_mb": 16766.7712,
"system": "Linux",
"machine": "x86_64",
"platform": "Linux-6.8.0-1014-azure-x86_64-with-glibc2.35",
"processor": "x86_64",
"python_version": "3.12.6",
"optimum_benchmark_version": "0.4.0",
"optimum_benchmark_commit": "96dfb7e6bb8c002c5fbc444701732aa424c1a4c3",
"transformers_version": "4.44.2",
"transformers_commit": null,
"accelerate_version": "0.34.2",
"accelerate_commit": null,
"diffusers_version": "0.30.3",
"diffusers_commit": null,
"optimum_version": null,
"optimum_commit": null,
"timm_version": "1.0.9",
"timm_commit": null,
"peft_version": null,
"peft_commit": null
}
} | {
"load": {
"memory": {
"unit": "MB",
"max_ram": 560.320512,
"max_global_vram": null,
"max_process_vram": null,
"max_reserved": null,
"max_allocated": null
},
"latency": {
"unit": "s",
"count": 1,
"total": 4.99940361900002,
"mean": 4.99940361900002,
"stdev": 0,
"p50": 4.99940361900002,
"p90": 4.99940361900002,
"p95": 4.99940361900002,
"p99": 4.99940361900002,
"values": [
4.99940361900002
]
},
"throughput": null,
"energy": null,
"efficiency": null
},
"forward": {
"memory": {
"unit": "MB",
"max_ram": 925.179904,
"max_global_vram": null,
"max_process_vram": null,
"max_reserved": null,
"max_allocated": null
},
"latency": {
"unit": "s",
"count": 9,
"total": 1.0341356900000278,
"mean": 0.11490396555555865,
"stdev": 0.047665139223444654,
"p50": 0.08221962499999336,
"p90": 0.18869181039999033,
"p95": 0.18920222520000038,
"p99": 0.18961055704000843,
"values": [
0.18971264000001042,
0.18843660299998533,
0.16717282300001557,
0.08303271600001949,
0.08221962499999336,
0.08086178499999619,
0.08091067600000201,
0.08038774800002102,
0.08140107399998442
]
},
"throughput": {
"unit": "samples/s",
"value": 17.4058396534013
},
"energy": null,
"efficiency": null
}
} | null | null | null | null | null | null | null |
null | null | test_api_push_to_hub_mixin | {
"name": "pytorch",
"version": "2.4.1+cpu",
"_target_": "optimum_benchmark.backends.pytorch.backend.PyTorchBackend",
"task": "fill-mask",
"library": "transformers",
"model_type": "bert",
"model": "google-bert/bert-base-uncased",
"processor": "google-bert/bert-base-uncased",
"device": "cpu",
"device_ids": null,
"seed": 42,
"inter_op_num_threads": null,
"intra_op_num_threads": null,
"model_kwargs": {},
"processor_kwargs": {},
"no_weights": false,
"device_map": null,
"torch_dtype": null,
"eval_mode": true,
"to_bettertransformer": false,
"low_cpu_mem_usage": null,
"attn_implementation": null,
"cache_implementation": null,
"autocast_enabled": false,
"autocast_dtype": null,
"torch_compile": false,
"torch_compile_target": "forward",
"torch_compile_config": {},
"quantization_scheme": null,
"quantization_config": {},
"deepspeed_inference": false,
"deepspeed_inference_config": {},
"peft_type": null,
"peft_config": {}
} | {
"name": "inference",
"_target_": "optimum_benchmark.scenarios.inference.scenario.InferenceScenario",
"iterations": 1,
"duration": 1,
"warmup_runs": 1,
"input_shapes": {
"batch_size": 2,
"num_choices": 2,
"sequence_length": 16
},
"new_tokens": null,
"memory": true,
"latency": true,
"energy": false,
"forward_kwargs": {},
"generate_kwargs": {},
"call_kwargs": {}
} | {
"name": "process",
"_target_": "optimum_benchmark.launchers.process.launcher.ProcessLauncher",
"device_isolation": false,
"device_isolation_action": null,
"numactl": false,
"numactl_kwargs": {},
"start_method": "spawn"
} | {
"cpu": " AMD EPYC 7763 64-Core Processor",
"cpu_count": 4,
"cpu_ram_mb": 16766.7712,
"system": "Linux",
"machine": "x86_64",
"platform": "Linux-6.8.0-1014-azure-x86_64-with-glibc2.35",
"processor": "x86_64",
"python_version": "3.12.6",
"optimum_benchmark_version": "0.4.0",
"optimum_benchmark_commit": "96dfb7e6bb8c002c5fbc444701732aa424c1a4c3",
"transformers_version": "4.44.2",
"transformers_commit": null,
"accelerate_version": "0.34.2",
"accelerate_commit": null,
"diffusers_version": "0.30.3",
"diffusers_commit": null,
"optimum_version": null,
"optimum_commit": null,
"timm_version": "1.0.9",
"timm_commit": null,
"peft_version": null,
"peft_commit": null
} | null | null |
null | null | null | null | null | null | null | {
"memory": {
"unit": "MB",
"max_ram": 560.320512,
"max_global_vram": null,
"max_process_vram": null,
"max_reserved": null,
"max_allocated": null
},
"latency": {
"unit": "s",
"count": 1,
"total": 4.99940361900002,
"mean": 4.99940361900002,
"stdev": 0,
"p50": 4.99940361900002,
"p90": 4.99940361900002,
"p95": 4.99940361900002,
"p99": 4.99940361900002,
"values": [
4.99940361900002
]
},
"throughput": null,
"energy": null,
"efficiency": null
} | {
"memory": {
"unit": "MB",
"max_ram": 925.179904,
"max_global_vram": null,
"max_process_vram": null,
"max_reserved": null,
"max_allocated": null
},
"latency": {
"unit": "s",
"count": 9,
"total": 1.0341356900000278,
"mean": 0.11490396555555865,
"stdev": 0.047665139223444654,
"p50": 0.08221962499999336,
"p90": 0.18869181039999033,
"p95": 0.18920222520000038,
"p99": 0.18961055704000843,
"values": [
0.18971264000001042,
0.18843660299998533,
0.16717282300001557,
0.08303271600001949,
0.08221962499999336,
0.08086178499999619,
0.08091067600000201,
0.08038774800002102,
0.08140107399998442
]
},
"throughput": {
"unit": "samples/s",
"value": 17.4058396534013
},
"energy": null,
"efficiency": null
} |
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