log/fast_beam_search_nbest_oracle/log-decode-epoch-10-avg-2-beam-20.0-max-contexts-8-max-states-64-2022-07-18-19-25-34

2022-07-18 19:25:34,655 INFO [decode.py:590] Decoding started
2022-07-18 19:25:34,655 INFO [decode.py:596] Device: cuda:0
2022-07-18 19:25:36,083 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
2022-07-18 19:25:36,182 INFO [decode.py:607] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 10, 'log_interval': 1, 'reset_interval': 200, 'feature_dim': 80, 'subsampling_factor': 4, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'decoder_dim': 512, 'joiner_dim': 512, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.5.0.dev+git.7cce647.dirty', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'add-LG-decoding-method-for-pruned-rnnt2', 'icefall-git-sha1': 'ffca1ae-dirty', 'icefall-git-date': 'Fri Jul 15 10:32:54 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.5.0.dev0+git.7cce647.dirty-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-7-0616225511-78bf4545d8-tv52r', 'IP address': '10.177.77.9'}, 'epoch': 10, 'batch': None, 'avg': 2, 'avg_last_n': 0, 'exp_dir': PosixPath('pruned_transducer_stateless2/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search_nbest_oracle', 'beam_size': 4, 'beam': 20.0, 'max_contexts': 8, 'max_states': 64, 'context_size': 2, 'max_sym_per_frame': 1, 'num_paths': 200, 'nbest_scale': 0.5, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 600, 'bucketing_sampler': True, 'num_buckets': 300, '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, 'training_subset': 'L', 'res_dir': PosixPath('pruned_transducer_stateless2/exp/fast_beam_search_nbest_oracle'), 'suffix': 'epoch-10-avg-2-beam-20.0-max-contexts-8-max-states-64', 'blank_id': 0, 'vocab_size': 5537}
2022-07-18 19:25:36,183 INFO [decode.py:609] About to create model
2022-07-18 19:25:36,805 INFO [decode.py:630] averaging ['pruned_transducer_stateless2/exp/epoch-9.pt', 'pruned_transducer_stateless2/exp/epoch-10.pt']
2022-07-18 19:25:43,292 INFO [decode.py:654] Number of model parameters: 88978927
2022-07-18 19:25:43,297 INFO [asr_datamodule.py:347] About to create dev dataset
2022-07-18 19:25:47,699 INFO [asr_datamodule.py:368] About to create dev dataloader
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2022-07-18 19:30:45,881 INFO [decode.py:524] The transcripts are stored in pruned_transducer_stateless2/exp/fast_beam_search_nbest_oracle/recogs-DEV-beam_size_4-epoch-10-avg-2-beam-20.0-max-contexts-8-max-states-64.txt
2022-07-18 19:30:46,356 INFO [utils.py:410] [DEV-beam_size_4] %WER 6.88% [22750 / 330498, 8267 ins, 5375 del, 9108 sub ]
2022-07-18 19:30:47,745 INFO [decode.py:537] Wrote detailed error stats to pruned_transducer_stateless2/exp/fast_beam_search_nbest_oracle/errs-DEV-beam_size_4-epoch-10-avg-2-beam-20.0-max-contexts-8-max-states-64.txt
2022-07-18 19:30:47,746 INFO [decode.py:554] 
For DEV, WER of different settings are:
beam_size_4	6.88	best for DEV

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2022-07-18 19:37:07,155 INFO [decode.py:524] The transcripts are stored in pruned_transducer_stateless2/exp/fast_beam_search_nbest_oracle/recogs-TEST_NET-beam_size_4-epoch-10-avg-2-beam-20.0-max-contexts-8-max-states-64.txt
2022-07-18 19:37:07,766 INFO [utils.py:410] [TEST_NET-beam_size_4] %WER 7.18% [29851 / 415747, 10875 ins, 4279 del, 14697 sub ]
2022-07-18 19:37:09,353 INFO [decode.py:537] Wrote detailed error stats to pruned_transducer_stateless2/exp/fast_beam_search_nbest_oracle/errs-TEST_NET-beam_size_4-epoch-10-avg-2-beam-20.0-max-contexts-8-max-states-64.txt
2022-07-18 19:37:09,354 INFO [decode.py:554] 
For TEST_NET, WER of different settings are:
beam_size_4	7.18	best for TEST_NET

2022-07-18 19:37:16,407 INFO [decode.py:507] batch 0/?, cuts processed until now is 56
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2022-07-18 19:41:38,721 INFO [decode.py:507] batch 114/?, cuts processed until now is 8370
2022-07-18 19:41:39,274 INFO [decode.py:524] The transcripts are stored in pruned_transducer_stateless2/exp/fast_beam_search_nbest_oracle/recogs-TEST_MEETING-beam_size_4-epoch-10-avg-2-beam-20.0-max-contexts-8-max-states-64.txt
2022-07-18 19:41:39,582 INFO [utils.py:410] [TEST_MEETING-beam_size_4] %WER 11.77% [25932 / 220385, 7948 ins, 7275 del, 10709 sub ]
2022-07-18 19:41:40,405 INFO [decode.py:537] Wrote detailed error stats to pruned_transducer_stateless2/exp/fast_beam_search_nbest_oracle/errs-TEST_MEETING-beam_size_4-epoch-10-avg-2-beam-20.0-max-contexts-8-max-states-64.txt
2022-07-18 19:41:40,406 INFO [decode.py:554] 
For TEST_MEETING, WER of different settings are:
beam_size_4	11.77	best for TEST_MEETING

2022-07-18 19:41:40,406 INFO [decode.py:754] Done!