Add decoding logs.

log/beam_search/log-decode-epoch-42-avg-11-beam-4-2022-03-12-10-40-40

@@ -0,0 +1,233 @@
+2022-03-12 10:40:40,428 INFO [decode.py:425] Decoding started
+2022-03-12 10:40:40,428 INFO [decode.py:431] Device: cuda:0
+2022-03-12 10:40:40,430 INFO [decode.py:440] {'feature_dim': 80, 'subsampling_factor': 4, 'attention_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'vgg_frontend': False, 'embedding_dim': 512, 'env_info': {'k2-version': '1.13', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '5ee082ea55f50e8bd42203ba266945ea5a236ab8', 'k2-git-date': 'Sun Feb 27 09:00:48 2022', 'lhotse-version': '1.0.0.dev+missing.version.file', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'modified-beam-search-for-pruned-rnnt', 'icefall-git-sha1': 'ad62981-dirty', 'icefall-git-date': 'Fri Mar 4 15:38:23 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-pruned-rnnt', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-rnnt-ali/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-rnnt-ali/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0307202051-57dc848959-8tmmp', 'IP address': '10.177.24.138'}, 'epoch': 42, 'avg': 11, 'exp_dir': PosixPath('pruned_transducer_stateless/exp'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'decoding_method': 'beam_search', 'beam_size': 4, 'context_size': 2, 'max_sym_per_frame': 3, 'full_libri': True, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 100, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless/exp/beam_search'), 'suffix': 'epoch-42-avg-11-beam-4', 'blank_id': 0, 'vocab_size': 500}
+2022-03-12 10:40:40,431 INFO [decode.py:442] About to create model
+2022-03-12 10:40:40,914 INFO [decode.py:453] averaging ['pruned_transducer_stateless/exp/epoch-32.pt', 'pruned_transducer_stateless/exp/epoch-33.pt', 'pruned_transducer_stateless/exp/epoch-34.pt', 'pruned_transducer_stateless/exp/epoch-35.pt', 'pruned_transducer_stateless/exp/epoch-36.pt', 'pruned_transducer_stateless/exp/epoch-37.pt', 'pruned_transducer_stateless/exp/epoch-38.pt', 'pruned_transducer_stateless/exp/epoch-39.pt', 'pruned_transducer_stateless/exp/epoch-40.pt', 'pruned_transducer_stateless/exp/epoch-41.pt', 'pruned_transducer_stateless/exp/epoch-42.pt']
+2022-03-12 10:40:52,342 INFO [decode.py:462] Number of model parameters: 84514780
+2022-03-12 10:40:52,342 INFO [asr_datamodule.py:379] About to get test-clean cuts
+2022-03-12 10:40:52,454 INFO [asr_datamodule.py:384] About to get test-other cuts
+2022-03-12 10:41:03,367 INFO [decode.py:350] batch 0/?, cuts processed until now is 20
+2022-03-12 10:41:24,590 INFO [decode.py:350] batch 2/?, cuts processed until now is 64
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+2022-03-12 11:26:44,050 INFO [decode.py:367] The transcripts are stored in pruned_transducer_stateless/exp/beam_search/recogs-test-clean-beam_4-epoch-42-avg-11-beam-4.txt
+2022-03-12 11:26:44,122 INFO [utils.py:406] [test-clean-beam_4] %WER 2.57% [1352 / 52576, 148 ins, 96 del, 1108 sub ]
+2022-03-12 11:26:44,290 INFO [decode.py:380] Wrote detailed error stats to pruned_transducer_stateless/exp/beam_search/errs-test-clean-beam_4-epoch-42-avg-11-beam-4.txt
+2022-03-12 11:26:44,290 INFO [decode.py:397] 
+For test-clean, WER of different settings are:
+beam_4	2.57	best for test-clean
+
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+2022-03-12 11:56:50,212 INFO [decode.py:350] batch 174/?, cuts processed until now is 2698
+2022-03-12 11:57:12,133 INFO [decode.py:350] batch 176/?, cuts processed until now is 2721
+2022-03-12 11:57:33,733 INFO [decode.py:350] batch 178/?, cuts processed until now is 2737
+2022-03-12 11:57:48,955 INFO [decode.py:350] batch 180/?, cuts processed until now is 2758
+2022-03-12 11:58:10,384 INFO [decode.py:350] batch 182/?, cuts processed until now is 2770
+2022-03-12 11:58:31,137 INFO [decode.py:350] batch 184/?, cuts processed until now is 2786
+2022-03-12 11:58:51,057 INFO [decode.py:350] batch 186/?, cuts processed until now is 2805
+2022-03-12 11:59:11,045 INFO [decode.py:350] batch 188/?, cuts processed until now is 2817
+2022-03-12 11:59:22,444 INFO [decode.py:350] batch 190/?, cuts processed until now is 2825
+2022-03-12 11:59:40,563 INFO [decode.py:350] batch 192/?, cuts processed until now is 2843
+2022-03-12 12:00:03,480 INFO [decode.py:350] batch 194/?, cuts processed until now is 2857
+2022-03-12 12:00:25,593 INFO [decode.py:350] batch 196/?, cuts processed until now is 2871
+2022-03-12 12:00:47,356 INFO [decode.py:350] batch 198/?, cuts processed until now is 2885
+2022-03-12 12:01:08,797 INFO [decode.py:350] batch 200/?, cuts processed until now is 2899
+2022-03-12 12:01:29,826 INFO [decode.py:350] batch 202/?, cuts processed until now is 2913
+2022-03-12 12:01:50,130 INFO [decode.py:350] batch 204/?, cuts processed until now is 2927
+2022-03-12 12:02:07,524 INFO [decode.py:350] batch 206/?, cuts processed until now is 2939
+2022-03-12 12:02:07,603 INFO [decode.py:367] The transcripts are stored in pruned_transducer_stateless/exp/beam_search/recogs-test-other-beam_4-epoch-42-avg-11-beam-4.txt
+2022-03-12 12:02:07,674 INFO [utils.py:406] [test-other-beam_4] %WER 6.27% [3282 / 52343, 340 ins, 284 del, 2658 sub ]
+2022-03-12 12:02:07,845 INFO [decode.py:380] Wrote detailed error stats to pruned_transducer_stateless/exp/beam_search/errs-test-other-beam_4-epoch-42-avg-11-beam-4.txt
+2022-03-12 12:02:07,846 INFO [decode.py:397] 
+For test-other, WER of different settings are:
+beam_4	6.27	best for test-other
+
+2022-03-12 12:02:07,846 INFO [decode.py:489] Done!

log/log-decode-epoch-42-avg-11-beam-4-2022-03-12-10-30-00

@@ -0,0 +1,233 @@
+2022-03-12 10:30:00,617 INFO [decode.py:425] Decoding started
+2022-03-12 10:30:00,618 INFO [decode.py:431] Device: cuda:0
+2022-03-12 10:30:00,620 INFO [decode.py:440] {'feature_dim': 80, 'subsampling_factor': 4, 'attention_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'vgg_frontend': False, 'embedding_dim': 512, 'env_info': {'k2-version': '1.13', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '5ee082ea55f50e8bd42203ba266945ea5a236ab8', 'k2-git-date': 'Sun Feb 27 09:00:48 2022', 'lhotse-version': '1.0.0.dev+missing.version.file', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'master', 'icefall-git-sha1': 'ad62981-dirty', 'icefall-git-date': 'Fri Mar 4 15:38:23 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-pruned-rnnt', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-rnnt-ali/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-rnnt-ali/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0307202051-57dc848959-8tmmp', 'IP address': '10.177.24.138'}, 'epoch': 42, 'avg': 11, 'exp_dir': PosixPath('pruned_transducer_stateless/exp'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'decoding_method': 'modified_beam_search', 'beam_size': 4, 'context_size': 2, 'max_sym_per_frame': 3, 'full_libri': True, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 100, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless/exp/modified_beam_search'), 'suffix': 'epoch-42-avg-11-beam-4', 'blank_id': 0, 'vocab_size': 500}
+2022-03-12 10:30:00,620 INFO [decode.py:442] About to create model
+2022-03-12 10:30:01,108 INFO [decode.py:453] averaging ['pruned_transducer_stateless/exp/epoch-32.pt', 'pruned_transducer_stateless/exp/epoch-33.pt', 'pruned_transducer_stateless/exp/epoch-34.pt', 'pruned_transducer_stateless/exp/epoch-35.pt', 'pruned_transducer_stateless/exp/epoch-36.pt', 'pruned_transducer_stateless/exp/epoch-37.pt', 'pruned_transducer_stateless/exp/epoch-38.pt', 'pruned_transducer_stateless/exp/epoch-39.pt', 'pruned_transducer_stateless/exp/epoch-40.pt', 'pruned_transducer_stateless/exp/epoch-41.pt', 'pruned_transducer_stateless/exp/epoch-42.pt']
+2022-03-12 10:31:05,568 INFO [decode.py:462] Number of model parameters: 84514780
+2022-03-12 10:31:05,568 INFO [asr_datamodule.py:379] About to get test-clean cuts
+2022-03-12 10:31:05,674 INFO [asr_datamodule.py:384] About to get test-other cuts
+2022-03-12 10:31:07,304 INFO [decode.py:350] batch 0/?, cuts processed until now is 20
+2022-03-12 10:31:09,999 INFO [decode.py:350] batch 2/?, cuts processed until now is 64
+2022-03-12 10:31:12,557 INFO [decode.py:350] batch 4/?, cuts processed until now is 81
+2022-03-12 10:31:15,273 INFO [decode.py:350] batch 6/?, cuts processed until now is 121
+2022-03-12 10:31:17,751 INFO [decode.py:350] batch 8/?, cuts processed until now is 133
+2022-03-12 10:31:20,345 INFO [decode.py:350] batch 10/?, cuts processed until now is 168
+2022-03-12 10:31:22,776 INFO [decode.py:350] batch 12/?, cuts processed until now is 202
+2022-03-12 10:31:25,630 INFO [decode.py:350] batch 14/?, cuts processed until now is 217
+2022-03-12 10:31:28,361 INFO [decode.py:350] batch 16/?, cuts processed until now is 241
+2022-03-12 10:31:31,053 INFO [decode.py:350] batch 18/?, cuts processed until now is 267
+2022-03-12 10:31:33,895 INFO [decode.py:350] batch 20/?, cuts processed until now is 281
+2022-03-12 10:31:36,556 INFO [decode.py:350] batch 22/?, cuts processed until now is 325
+2022-03-12 10:31:39,266 INFO [decode.py:350] batch 24/?, cuts processed until now is 349
+2022-03-12 10:31:42,002 INFO [decode.py:350] batch 26/?, cuts processed until now is 366
+2022-03-12 10:31:44,658 INFO [decode.py:350] batch 28/?, cuts processed until now is 389
+2022-03-12 10:31:47,343 INFO [decode.py:350] batch 30/?, cuts processed until now is 410
+2022-03-12 10:31:49,978 INFO [decode.py:350] batch 32/?, cuts processed until now is 442
+2022-03-12 10:31:52,706 INFO [decode.py:350] batch 34/?, cuts processed until now is 474
+2022-03-12 10:31:55,376 INFO [decode.py:350] batch 36/?, cuts processed until now is 498
+2022-03-12 10:31:58,068 INFO [decode.py:350] batch 38/?, cuts processed until now is 514
+2022-03-12 10:32:00,767 INFO [decode.py:350] batch 40/?, cuts processed until now is 524
+2022-03-12 10:32:03,375 INFO [decode.py:350] batch 42/?, cuts processed until now is 564
+2022-03-12 10:32:06,063 INFO [decode.py:350] batch 44/?, cuts processed until now is 621
+2022-03-12 10:32:08,650 INFO [decode.py:350] batch 46/?, cuts processed until now is 633
+2022-03-12 10:32:11,191 INFO [decode.py:350] batch 48/?, cuts processed until now is 648
+2022-03-12 10:32:13,816 INFO [decode.py:350] batch 50/?, cuts processed until now is 662
+2022-03-12 10:32:16,366 INFO [decode.py:350] batch 52/?, cuts processed until now is 680
+2022-03-12 10:32:19,001 INFO [decode.py:350] batch 54/?, cuts processed until now is 708
+2022-03-12 10:32:21,489 INFO [decode.py:350] batch 56/?, cuts processed until now is 736
+2022-03-12 10:32:24,073 INFO [decode.py:350] batch 58/?, cuts processed until now is 752
+2022-03-12 10:32:26,740 INFO [decode.py:350] batch 60/?, cuts processed until now is 819
+2022-03-12 10:32:29,371 INFO [decode.py:350] batch 62/?, cuts processed until now is 843
+2022-03-12 10:32:31,988 INFO [decode.py:350] batch 64/?, cuts processed until now is 850
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+2022-03-12 10:32:37,252 INFO [decode.py:350] batch 68/?, cuts processed until now is 932
+2022-03-12 10:32:40,042 INFO [decode.py:350] batch 70/?, cuts processed until now is 957
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+2022-03-12 10:32:45,387 INFO [decode.py:350] batch 74/?, cuts processed until now is 1064
+2022-03-12 10:32:48,040 INFO [decode.py:350] batch 76/?, cuts processed until now is 1077
+2022-03-12 10:32:50,715 INFO [decode.py:350] batch 78/?, cuts processed until now is 1114
+2022-03-12 10:32:53,371 INFO [decode.py:350] batch 80/?, cuts processed until now is 1141
+2022-03-12 10:32:55,971 INFO [decode.py:350] batch 82/?, cuts processed until now is 1172
+2022-03-12 10:32:58,656 INFO [decode.py:350] batch 84/?, cuts processed until now is 1180
+2022-03-12 10:33:01,267 INFO [decode.py:350] batch 86/?, cuts processed until now is 1199
+2022-03-12 10:33:03,862 INFO [decode.py:350] batch 88/?, cuts processed until now is 1228
+2022-03-12 10:33:06,534 INFO [decode.py:350] batch 90/?, cuts processed until now is 1245
+2022-03-12 10:33:09,131 INFO [decode.py:350] batch 92/?, cuts processed until now is 1267
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+2022-03-12 10:33:14,401 INFO [decode.py:350] batch 96/?, cuts processed until now is 1363
+2022-03-12 10:33:15,898 INFO [decode.py:350] batch 98/?, cuts processed until now is 1378
+2022-03-12 10:33:18,584 INFO [decode.py:350] batch 100/?, cuts processed until now is 1406
+2022-03-12 10:33:21,186 INFO [decode.py:350] batch 102/?, cuts processed until now is 1420
+2022-03-12 10:33:23,830 INFO [decode.py:350] batch 104/?, cuts processed until now is 1445
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+2022-03-12 10:33:29,314 INFO [decode.py:350] batch 108/?, cuts processed until now is 1494
+2022-03-12 10:33:32,034 INFO [decode.py:350] batch 110/?, cuts processed until now is 1547
+2022-03-12 10:33:34,782 INFO [decode.py:350] batch 112/?, cuts processed until now is 1582
+2022-03-12 10:33:37,434 INFO [decode.py:350] batch 114/?, cuts processed until now is 1615
+2022-03-12 10:33:40,191 INFO [decode.py:350] batch 116/?, cuts processed until now is 1636
+2022-03-12 10:33:42,738 INFO [decode.py:350] batch 118/?, cuts processed until now is 1655
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+2022-03-12 10:34:41,123 INFO [decode.py:350] batch 162/?, cuts processed until now is 2274
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+2022-03-12 10:34:46,550 INFO [decode.py:350] batch 166/?, cuts processed until now is 2327
+2022-03-12 10:34:49,185 INFO [decode.py:350] batch 168/?, cuts processed until now is 2351
+2022-03-12 10:34:51,840 INFO [decode.py:350] batch 170/?, cuts processed until now is 2364
+2022-03-12 10:34:54,516 INFO [decode.py:350] batch 172/?, cuts processed until now is 2374
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+2022-03-12 10:35:01,466 INFO [decode.py:350] batch 178/?, cuts processed until now is 2427
+2022-03-12 10:35:04,016 INFO [decode.py:350] batch 180/?, cuts processed until now is 2440
+2022-03-12 10:35:06,622 INFO [decode.py:350] batch 182/?, cuts processed until now is 2456
+2022-03-12 10:35:09,103 INFO [decode.py:350] batch 184/?, cuts processed until now is 2466
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+2022-03-12 10:35:13,211 INFO [decode.py:350] batch 188/?, cuts processed until now is 2492
+2022-03-12 10:35:15,029 INFO [decode.py:350] batch 190/?, cuts processed until now is 2502
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+2022-03-12 10:35:30,485 INFO [decode.py:350] batch 202/?, cuts processed until now is 2575
+2022-03-12 10:35:33,081 INFO [decode.py:350] batch 204/?, cuts processed until now is 2587
+2022-03-12 10:35:35,665 INFO [decode.py:350] batch 206/?, cuts processed until now is 2599
+2022-03-12 10:35:38,217 INFO [decode.py:350] batch 208/?, cuts processed until now is 2611
+2022-03-12 10:35:40,107 INFO [decode.py:350] batch 210/?, cuts processed until now is 2620
+2022-03-12 10:35:40,177 INFO [decode.py:367] The transcripts are stored in pruned_transducer_stateless/exp/modified_beam_search/recogs-test-clean-beam_4-epoch-42-avg-11-beam-4.txt
+2022-03-12 10:35:40,245 INFO [utils.py:406] [test-clean-beam_4] %WER 2.56% [1347 / 52576, 147 ins, 94 del, 1106 sub ]
+2022-03-12 10:35:40,410 INFO [decode.py:380] Wrote detailed error stats to pruned_transducer_stateless/exp/modified_beam_search/errs-test-clean-beam_4-epoch-42-avg-11-beam-4.txt
+2022-03-12 10:35:40,411 INFO [decode.py:397] 
+For test-clean, WER of different settings are:
+beam_4	2.56	best for test-clean
+
+2022-03-12 10:35:41,914 INFO [decode.py:350] batch 0/?, cuts processed until now is 23
+2022-03-12 10:35:44,619 INFO [decode.py:350] batch 2/?, cuts processed until now is 71
+2022-03-12 10:35:47,392 INFO [decode.py:350] batch 4/?, cuts processed until now is 92
+2022-03-12 10:35:49,999 INFO [decode.py:350] batch 6/?, cuts processed until now is 134
+2022-03-12 10:35:52,776 INFO [decode.py:350] batch 8/?, cuts processed until now is 150
+2022-03-12 10:35:55,455 INFO [decode.py:350] batch 10/?, cuts processed until now is 190
+2022-03-12 10:35:57,864 INFO [decode.py:350] batch 12/?, cuts processed until now is 225
+2022-03-12 10:36:00,236 INFO [decode.py:350] batch 14/?, cuts processed until now is 240
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+2022-03-12 10:38:16,280 INFO [decode.py:350] batch 116/?, cuts processed until now is 1872
+2022-03-12 10:38:18,933 INFO [decode.py:350] batch 118/?, cuts processed until now is 1894
+2022-03-12 10:38:21,658 INFO [decode.py:350] batch 120/?, cuts processed until now is 1938
+2022-03-12 10:38:24,364 INFO [decode.py:350] batch 122/?, cuts processed until now is 1968
+2022-03-12 10:38:27,049 INFO [decode.py:350] batch 124/?, cuts processed until now is 1982
+2022-03-12 10:38:29,798 INFO [decode.py:350] batch 126/?, cuts processed until now is 2007
+2022-03-12 10:38:32,492 INFO [decode.py:350] batch 128/?, cuts processed until now is 2037
+2022-03-12 10:38:35,185 INFO [decode.py:350] batch 130/?, cuts processed until now is 2105
+2022-03-12 10:38:37,860 INFO [decode.py:350] batch 132/?, cuts processed until now is 2152
+2022-03-12 10:38:40,479 INFO [decode.py:350] batch 134/?, cuts processed until now is 2172
+2022-03-12 10:38:43,171 INFO [decode.py:350] batch 136/?, cuts processed until now is 2206
+2022-03-12 10:38:45,889 INFO [decode.py:350] batch 138/?, cuts processed until now is 2228
+2022-03-12 10:38:48,438 INFO [decode.py:350] batch 140/?, cuts processed until now is 2238
+2022-03-12 10:38:51,098 INFO [decode.py:350] batch 142/?, cuts processed until now is 2290
+2022-03-12 10:38:53,686 INFO [decode.py:350] batch 144/?, cuts processed until now is 2321
+2022-03-12 10:38:55,595 INFO [decode.py:350] batch 146/?, cuts processed until now is 2353
+2022-03-12 10:38:58,263 INFO [decode.py:350] batch 148/?, cuts processed until now is 2410
+2022-03-12 10:39:00,714 INFO [decode.py:350] batch 150/?, cuts processed until now is 2420
+2022-03-12 10:39:03,395 INFO [decode.py:350] batch 152/?, cuts processed until now is 2456
+2022-03-12 10:39:05,919 INFO [decode.py:350] batch 154/?, cuts processed until now is 2479
+2022-03-12 10:39:08,477 INFO [decode.py:350] batch 156/?, cuts processed until now is 2496
+2022-03-12 10:39:10,151 INFO [decode.py:350] batch 158/?, cuts processed until now is 2513
+2022-03-12 10:39:12,895 INFO [decode.py:350] batch 160/?, cuts processed until now is 2531
+2022-03-12 10:39:15,488 INFO [decode.py:350] batch 162/?, cuts processed until now is 2555
+2022-03-12 10:39:18,177 INFO [decode.py:350] batch 164/?, cuts processed until now is 2587
+2022-03-12 10:39:20,766 INFO [decode.py:350] batch 166/?, cuts processed until now is 2621
+2022-03-12 10:39:23,468 INFO [decode.py:350] batch 168/?, cuts processed until now is 2650
+2022-03-12 10:39:25,192 INFO [decode.py:350] batch 170/?, cuts processed until now is 2661
+2022-03-12 10:39:27,946 INFO [decode.py:350] batch 172/?, cuts processed until now is 2673
+2022-03-12 10:39:30,669 INFO [decode.py:350] batch 174/?, cuts processed until now is 2698
+2022-03-12 10:39:33,397 INFO [decode.py:350] batch 176/?, cuts processed until now is 2721
+2022-03-12 10:39:36,081 INFO [decode.py:350] batch 178/?, cuts processed until now is 2737
+2022-03-12 10:39:38,022 INFO [decode.py:350] batch 180/?, cuts processed until now is 2758
+2022-03-12 10:39:40,679 INFO [decode.py:350] batch 182/?, cuts processed until now is 2770
+2022-03-12 10:39:43,284 INFO [decode.py:350] batch 184/?, cuts processed until now is 2786
+2022-03-12 10:39:45,808 INFO [decode.py:350] batch 186/?, cuts processed until now is 2805
+2022-03-12 10:39:48,348 INFO [decode.py:350] batch 188/?, cuts processed until now is 2817
+2022-03-12 10:39:49,783 INFO [decode.py:350] batch 190/?, cuts processed until now is 2825
+2022-03-12 10:39:52,078 INFO [decode.py:350] batch 192/?, cuts processed until now is 2843
+2022-03-12 10:39:54,939 INFO [decode.py:350] batch 194/?, cuts processed until now is 2857
+2022-03-12 10:39:57,738 INFO [decode.py:350] batch 196/?, cuts processed until now is 2871
+2022-03-12 10:40:00,481 INFO [decode.py:350] batch 198/?, cuts processed until now is 2885
+2022-03-12 10:40:03,163 INFO [decode.py:350] batch 200/?, cuts processed until now is 2899
+2022-03-12 10:40:05,796 INFO [decode.py:350] batch 202/?, cuts processed until now is 2913
+2022-03-12 10:40:08,403 INFO [decode.py:350] batch 204/?, cuts processed until now is 2927
+2022-03-12 10:40:10,658 INFO [decode.py:350] batch 206/?, cuts processed until now is 2939
+2022-03-12 10:40:10,729 INFO [decode.py:367] The transcripts are stored in pruned_transducer_stateless/exp/modified_beam_search/recogs-test-other-beam_4-epoch-42-avg-11-beam-4.txt
+2022-03-12 10:40:10,806 INFO [utils.py:406] [test-other-beam_4] %WER 6.27% [3282 / 52343, 333 ins, 289 del, 2660 sub ]
+2022-03-12 10:40:11,006 INFO [decode.py:380] Wrote detailed error stats to pruned_transducer_stateless/exp/modified_beam_search/errs-test-other-beam_4-epoch-42-avg-11-beam-4.txt
+2022-03-12 10:40:11,007 INFO [decode.py:397] 
+For test-other, WER of different settings are:
+beam_4	6.27	best for test-other
+
+2022-03-12 10:40:11,007 INFO [decode.py:489] Done!

log/log-decode-epoch-42-avg-11-context-2-max-sym-per-frame-1-2022-03-12-10-50-03

@@ -0,0 +1,29 @@
+2022-03-12 10:50:03,877 INFO [decode.py:425] Decoding started
+2022-03-12 10:50:03,877 INFO [decode.py:431] Device: cuda:0
+2022-03-12 10:50:03,879 INFO [decode.py:440] {'feature_dim': 80, 'subsampling_factor': 4, 'attention_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'vgg_frontend': False, 'embedding_dim': 512, 'env_info': {'k2-version': '1.13', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '5ee082ea55f50e8bd42203ba266945ea5a236ab8', 'k2-git-date': 'Sun Feb 27 09:00:48 2022', 'lhotse-version': '1.0.0.dev+missing.version.file', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'modified-beam-search-for-pruned-rnnt', 'icefall-git-sha1': 'bd033de-clean', 'icefall-git-date': 'Sat Mar 12 10:42:25 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-pruned-rnnt', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-rnnt-ali/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-rnnt-ali/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0307202051-57dc848959-8tmmp', 'IP address': '10.177.24.138'}, 'epoch': 42, 'avg': 11, 'exp_dir': PosixPath('pruned_transducer_stateless/exp'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'decoding_method': 'greedy_search', 'beam_size': 4, 'context_size': 2, 'max_sym_per_frame': 1, 'full_libri': True, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 100, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless/exp/greedy_search'), 'suffix': 'epoch-42-avg-11-context-2-max-sym-per-frame-1', 'blank_id': 0, 'vocab_size': 500}
+2022-03-12 10:50:03,879 INFO [decode.py:442] About to create model
+2022-03-12 10:50:04,362 INFO [decode.py:453] averaging ['pruned_transducer_stateless/exp/epoch-32.pt', 'pruned_transducer_stateless/exp/epoch-33.pt', 'pruned_transducer_stateless/exp/epoch-34.pt', 'pruned_transducer_stateless/exp/epoch-35.pt', 'pruned_transducer_stateless/exp/epoch-36.pt', 'pruned_transducer_stateless/exp/epoch-37.pt', 'pruned_transducer_stateless/exp/epoch-38.pt', 'pruned_transducer_stateless/exp/epoch-39.pt', 'pruned_transducer_stateless/exp/epoch-40.pt', 'pruned_transducer_stateless/exp/epoch-41.pt', 'pruned_transducer_stateless/exp/epoch-42.pt']
+2022-03-12 10:50:16,152 INFO [decode.py:462] Number of model parameters: 84514780
+2022-03-12 10:50:16,152 INFO [asr_datamodule.py:379] About to get test-clean cuts
+2022-03-12 10:50:16,254 INFO [asr_datamodule.py:384] About to get test-other cuts
+2022-03-12 10:50:17,332 INFO [decode.py:350] batch 0/?, cuts processed until now is 20
+2022-03-12 10:51:34,592 INFO [decode.py:350] batch 100/?, cuts processed until now is 1406
+2022-03-12 10:52:50,773 INFO [decode.py:350] batch 200/?, cuts processed until now is 2563
+2022-03-12 10:52:57,884 INFO [decode.py:367] The transcripts are stored in pruned_transducer_stateless/exp/greedy_search/recogs-test-clean-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-1.txt
+2022-03-12 10:52:57,952 INFO [utils.py:406] [test-clean-greedy_search] %WER 2.62% [1380 / 52576, 147 ins, 117 del, 1116 sub ]
+2022-03-12 10:52:58,118 INFO [decode.py:380] Wrote detailed error stats to pruned_transducer_stateless/exp/greedy_search/errs-test-clean-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-1.txt
+2022-03-12 10:52:58,119 INFO [decode.py:397] 
+For test-clean, WER of different settings are:
+greedy_search	2.62	best for test-clean
+
+2022-03-12 10:52:59,060 INFO [decode.py:350] batch 0/?, cuts processed until now is 23
+2022-03-12 10:54:17,250 INFO [decode.py:350] batch 100/?, cuts processed until now is 1614
+2022-03-12 10:55:33,934 INFO [decode.py:350] batch 200/?, cuts processed until now is 2899
+2022-03-12 10:55:38,381 INFO [decode.py:367] The transcripts are stored in pruned_transducer_stateless/exp/greedy_search/recogs-test-other-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-1.txt
+2022-03-12 10:55:38,454 INFO [utils.py:406] [test-other-greedy_search] %WER 6.37% [3333 / 52343, 324 ins, 330 del, 2679 sub ]
+2022-03-12 10:55:38,628 INFO [decode.py:380] Wrote detailed error stats to pruned_transducer_stateless/exp/greedy_search/errs-test-other-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-1.txt
+2022-03-12 10:55:38,629 INFO [decode.py:397] 
+For test-other, WER of different settings are:
+greedy_search	6.37	best for test-other
+
+2022-03-12 10:55:38,629 INFO [decode.py:489] Done!

log/log-decode-epoch-42-avg-11-context-2-max-sym-per-frame-2-2022-03-12-10-56-46

@@ -0,0 +1,29 @@
+2022-03-12 10:56:46,784 INFO [decode.py:425] Decoding started
+2022-03-12 10:56:46,784 INFO [decode.py:431] Device: cuda:0
+2022-03-12 10:56:46,786 INFO [decode.py:440] {'feature_dim': 80, 'subsampling_factor': 4, 'attention_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'vgg_frontend': False, 'embedding_dim': 512, 'env_info': {'k2-version': '1.13', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '5ee082ea55f50e8bd42203ba266945ea5a236ab8', 'k2-git-date': 'Sun Feb 27 09:00:48 2022', 'lhotse-version': '1.0.0.dev+missing.version.file', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'modified-beam-search-for-pruned-rnnt', 'icefall-git-sha1': 'bd033de-clean', 'icefall-git-date': 'Sat Mar 12 10:42:25 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-pruned-rnnt', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-rnnt-ali/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-rnnt-ali/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0307202051-57dc848959-8tmmp', 'IP address': '10.177.24.138'}, 'epoch': 42, 'avg': 11, 'exp_dir': PosixPath('pruned_transducer_stateless/exp'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'decoding_method': 'greedy_search', 'beam_size': 4, 'context_size': 2, 'max_sym_per_frame': 2, 'full_libri': True, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 100, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless/exp/greedy_search'), 'suffix': 'epoch-42-avg-11-context-2-max-sym-per-frame-2', 'blank_id': 0, 'vocab_size': 500}
+2022-03-12 10:56:46,786 INFO [decode.py:442] About to create model
+2022-03-12 10:56:47,289 INFO [decode.py:453] averaging ['pruned_transducer_stateless/exp/epoch-32.pt', 'pruned_transducer_stateless/exp/epoch-33.pt', 'pruned_transducer_stateless/exp/epoch-34.pt', 'pruned_transducer_stateless/exp/epoch-35.pt', 'pruned_transducer_stateless/exp/epoch-36.pt', 'pruned_transducer_stateless/exp/epoch-37.pt', 'pruned_transducer_stateless/exp/epoch-38.pt', 'pruned_transducer_stateless/exp/epoch-39.pt', 'pruned_transducer_stateless/exp/epoch-40.pt', 'pruned_transducer_stateless/exp/epoch-41.pt', 'pruned_transducer_stateless/exp/epoch-42.pt']
+2022-03-12 10:57:53,821 INFO [decode.py:462] Number of model parameters: 84514780
+2022-03-12 10:57:53,822 INFO [asr_datamodule.py:379] About to get test-clean cuts
+2022-03-12 10:57:53,952 INFO [asr_datamodule.py:384] About to get test-other cuts
+2022-03-12 10:57:55,219 INFO [decode.py:350] batch 0/?, cuts processed until now is 20
+2022-03-12 10:59:24,003 INFO [decode.py:350] batch 100/?, cuts processed until now is 1406
+2022-03-12 11:00:51,007 INFO [decode.py:350] batch 200/?, cuts processed until now is 2563
+2022-03-12 11:00:59,257 INFO [decode.py:367] The transcripts are stored in pruned_transducer_stateless/exp/greedy_search/recogs-test-clean-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-2.txt
+2022-03-12 11:00:59,331 INFO [utils.py:406] [test-clean-greedy_search] %WER 2.62% [1380 / 52576, 147 ins, 115 del, 1118 sub ]
+2022-03-12 11:00:59,498 INFO [decode.py:380] Wrote detailed error stats to pruned_transducer_stateless/exp/greedy_search/errs-test-clean-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-2.txt
+2022-03-12 11:00:59,499 INFO [decode.py:397] 
+For test-clean, WER of different settings are:
+greedy_search	2.62	best for test-clean
+
+2022-03-12 11:01:00,615 INFO [decode.py:350] batch 0/?, cuts processed until now is 23
+2022-03-12 11:02:28,395 INFO [decode.py:350] batch 100/?, cuts processed until now is 1614
+2022-03-12 11:03:52,897 INFO [decode.py:350] batch 200/?, cuts processed until now is 2899
+2022-03-12 11:03:57,774 INFO [decode.py:367] The transcripts are stored in pruned_transducer_stateless/exp/greedy_search/recogs-test-other-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-2.txt
+2022-03-12 11:03:57,863 INFO [utils.py:406] [test-other-greedy_search] %WER 6.37% [3334 / 52343, 326 ins, 326 del, 2682 sub ]
+2022-03-12 11:03:58,039 INFO [decode.py:380] Wrote detailed error stats to pruned_transducer_stateless/exp/greedy_search/errs-test-other-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-2.txt
+2022-03-12 11:03:58,040 INFO [decode.py:397] 
+For test-other, WER of different settings are:
+greedy_search	6.37	best for test-other
+
+2022-03-12 11:03:58,040 INFO [decode.py:489] Done!

log/log-decode-epoch-42-avg-11-context-2-max-sym-per-frame-3-2022-03-11-18-36-33

@@ -0,0 +1,29 @@
+2022-03-11 18:36:33,290 INFO [decode.py:405] Decoding started
+2022-03-11 18:36:33,290 INFO [decode.py:411] Device: cuda:0
+2022-03-11 18:36:33,292 INFO [decode.py:420] {'feature_dim': 80, 'subsampling_factor': 4, 'attention_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'vgg_frontend': False, 'embedding_dim': 512, 'env_info': {'k2-version': '1.13', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': '5ee082ea55f50e8bd42203ba266945ea5a236ab8', 'k2-git-date': 'Sun Feb 27 09:00:48 2022', 'lhotse-version': '1.0.0.dev+missing.version.file', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'master', 'icefall-git-sha1': 'ad62981-clean', 'icefall-git-date': 'Fri Mar 4 15:38:23 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-pruned-rnnt', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-rnnt-ali/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-rnnt-ali/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-3-0307202051-57dc848959-8tmmp', 'IP address': '10.177.24.138'}, 'epoch': 42, 'avg': 11, 'exp_dir': PosixPath('pruned_transducer_stateless/exp'), 'bpe_model': 'data/lang_bpe_500/bpe.model', 'decoding_method': 'greedy_search', 'beam_size': 4, 'context_size': 2, 'max_sym_per_frame': 3, 'full_libri': True, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 100, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless/exp/greedy_search'), 'suffix': 'epoch-42-avg-11-context-2-max-sym-per-frame-3', 'blank_id': 0, 'vocab_size': 500}
+2022-03-11 18:36:33,292 INFO [decode.py:422] About to create model
+2022-03-11 18:36:33,827 INFO [decode.py:433] averaging ['pruned_transducer_stateless/exp/epoch-32.pt', 'pruned_transducer_stateless/exp/epoch-33.pt', 'pruned_transducer_stateless/exp/epoch-34.pt', 'pruned_transducer_stateless/exp/epoch-35.pt', 'pruned_transducer_stateless/exp/epoch-36.pt', 'pruned_transducer_stateless/exp/epoch-37.pt', 'pruned_transducer_stateless/exp/epoch-38.pt', 'pruned_transducer_stateless/exp/epoch-39.pt', 'pruned_transducer_stateless/exp/epoch-40.pt', 'pruned_transducer_stateless/exp/epoch-41.pt', 'pruned_transducer_stateless/exp/epoch-42.pt']
+2022-03-11 18:36:48,445 INFO [decode.py:442] Number of model parameters: 84514780
+2022-03-11 18:36:48,445 INFO [asr_datamodule.py:379] About to get test-clean cuts
+2022-03-11 18:36:48,545 INFO [asr_datamodule.py:384] About to get test-other cuts
+2022-03-11 18:36:50,037 INFO [decode.py:334] batch 0/?, cuts processed until now is 20
+2022-03-11 18:38:27,402 INFO [decode.py:334] batch 100/?, cuts processed until now is 1406
+2022-03-11 18:40:10,870 INFO [decode.py:334] batch 200/?, cuts processed until now is 2563
+2022-03-11 18:40:20,541 INFO [decode.py:351] The transcripts are stored in pruned_transducer_stateless/exp/greedy_search/recogs-test-clean-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-3.txt
+2022-03-11 18:40:20,607 INFO [utils.py:406] [test-clean-greedy_search] %WER 2.62% [1380 / 52576, 147 ins, 115 del, 1118 sub ]
+2022-03-11 18:40:20,807 INFO [decode.py:364] Wrote detailed error stats to pruned_transducer_stateless/exp/greedy_search/errs-test-clean-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-3.txt
+2022-03-11 18:40:20,808 INFO [decode.py:381] 
+For test-clean, WER of different settings are:
+greedy_search	2.62	best for test-clean
+
+2022-03-11 18:40:22,118 INFO [decode.py:334] batch 0/?, cuts processed until now is 23
+2022-03-11 18:42:07,004 INFO [decode.py:334] batch 100/?, cuts processed until now is 1614
+2022-03-11 18:43:49,356 INFO [decode.py:334] batch 200/?, cuts processed until now is 2899
+2022-03-11 18:43:55,246 INFO [decode.py:351] The transcripts are stored in pruned_transducer_stateless/exp/greedy_search/recogs-test-other-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-3.txt
+2022-03-11 18:43:55,319 INFO [utils.py:406] [test-other-greedy_search] %WER 6.37% [3334 / 52343, 326 ins, 326 del, 2682 sub ]
+2022-03-11 18:43:55,499 INFO [decode.py:364] Wrote detailed error stats to pruned_transducer_stateless/exp/greedy_search/errs-test-other-greedy_search-epoch-42-avg-11-context-2-max-sym-per-frame-3.txt
+2022-03-11 18:43:55,502 INFO [decode.py:381] 
+For test-other, WER of different settings are:
+greedy_search	6.37	best for test-other
+
+2022-03-11 18:43:55,502 INFO [decode.py:469] Done!