inference_audio_tagging/log-decode-iter-224000-avg-2-use-averaged-model-2024-08-17-12-48-01

2024-08-17 12:48:01,618 INFO [inference_audio_tagging.py:316] Evaluation started
2024-08-17 12:48:01,618 INFO [inference_audio_tagging.py:318] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 0, 'log_interval': 50, 'reset_interval': 200, 'valid_interval': 3000, 'feature_dim': 80, 'subsampling_factor': 4, 'warm_step': 2000, 'env_info': {'k2-version': '1.24.3', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'e400fa3b456faf8afe0ee5bfe572946b4921a3db', 'k2-git-date': 'Sat Jul 15 04:21:50 2023', 'lhotse-version': '1.16.0', 'torch-version': '2.0.1+cu117', 'torch-cuda-available': True, 'torch-cuda-version': '11.7', 'python-version': '3.9', 'icefall-git-branch': 'multi_KD_with_wenet', 'icefall-git-sha1': '0d2af1df-clean', 'icefall-git-date': 'Wed Aug 14 17:27:16 2024', 'icefall-path': '/xy/mnt/yangxiaoyu/workspace/icefall_multi_KD', 'k2-path': '/root/anaconda3/lib/python3.9/site-packages/k2/__init__.py', 'lhotse-path': '/root/anaconda3/lib/python3.9/site-packages/lhotse/__init__.py', 'hostname': 'NGK_xiaoyu'}, 'epoch': 30, 'iter': 224000, 'avg': 2, 'use_averaged_model': True, 'exp_dir': PosixPath('multi_KD/exp_causal1_delta6KD_LS1_5fold+wenetspech0_0fold+as_unbalanced1+vox_1_vox2_base_lr_0.045_use_beats_1_scale_1.0_use_ecapa_1_layer_2_scale_10.0_1_scale_1.0_specaug0_musan0_with_task_ID_stop_early1_share_asr1_md1500_amp_bf16'), 'trained_with_distillation': True, 'trained_with_multitask': False, 'freeze_encoder': False, 'num_events': 527, 'eval_subset': 'eval', 'vocab_size': 500, 'blank_id': 0, 'context_size': 2, 'do_audio_tagging': True, 'use_encoder_projection': True, 'encoder_projection_dim': 2560, 'freezing_encoder_layer_index': '-1', 'freeze_encoder_steps': -1, 'save_logits': False, 'num_encoder_layers': '2,2,3,4,3,2', 'downsampling_factor': '1,2,4,8,4,2', 'feedforward_dim': '512,768,1024,1536,1024,768', 'num_heads': '4,4,4,8,4,4', 'encoder_dim': '192,256,384,512,384,256', 'query_head_dim': '32', 'value_head_dim': '12', 'pos_head_dim': '4', 'pos_dim': 48, 'encoder_unmasked_dim': '192,192,256,256,256,192', 'cnn_module_kernel': '31,31,15,15,15,31', 'decoder_dim': 512, 'joiner_dim': 512, 'causal': False, 'chunk_size': '32', 'left_context_frames': '256', 'use_transducer': True, 'use_ctc': False, 'speaker_input_idx': 2, 'whisper_dim': 1280, 'use_task_id': False, 'num_codebooks': 32, 'mvq_kd_layer_idx': -1, 'use_subsampled_output': True, 'delta_t': 0, 'full_libri': True, 'mini_libri': False, 'use_libriheavy': False, 'libriheavy_subset': 'small', 'use_librispeech': False, 'use_wenetspeech': False, 'use_audioset': False, 'audioset_subset': 'balanced', 'use_voxceleb': False, 'voxceleb_subset': 'vox1', 'use_fma': False, 'fma_subset': 'large', 'manifest_dir': PosixPath('data/fbank_LS_Vox_AS_fma'), 'max_duration': 300, 'bucketing_sampler': True, 'num_buckets': 30, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'drop_last': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'enable_audioset': False, 'use_musan_separately': False, 'input_strategy': 'PrecomputedFeatures', 'drop_features': False, 'return_audio': False, 'use_beats': True, 'use_ecapa': False, 'use_whisper': True, 'whisper_mvq': False, 'beats_ckpt': 'data/models/BEATs/BEATs_iter3_plus_AS2M_finetuned_on_AS2M_cpt2.pt', 'whisper_version': 'small.en', 'use_mert': False, 'lm_vocab_size': 500, 'lm_epoch': 7, 'lm_avg': 1, 'lm_exp_dir': None, 'rnn_lm_embedding_dim': 2048, 'rnn_lm_hidden_dim': 2048, 'rnn_lm_num_layers': 3, 'rnn_lm_tie_weights': True, 'transformer_lm_exp_dir': None, 'transformer_lm_dim_feedforward': 2048, 'transformer_lm_encoder_dim': 768, 'transformer_lm_embedding_dim': 768, 'transformer_lm_nhead': 8, 'transformer_lm_num_layers': 16, 'transformer_lm_tie_weights': True, 'res_dir': PosixPath('multi_KD/exp_causal1_delta6KD_LS1_5fold+wenetspech0_0fold+as_unbalanced1+vox_1_vox2_base_lr_0.045_use_beats_1_scale_1.0_use_ecapa_1_layer_2_scale_10.0_1_scale_1.0_specaug0_musan0_with_task_ID_stop_early1_share_asr1_md1500_amp_bf16/inference_audio_tagging'), 'suffix': 'iter-224000-avg-2-use-averaged-model'}
2024-08-17 12:48:01,618 INFO [inference_audio_tagging.py:324] About to create model
2024-08-17 12:48:01,966 INFO [inference_audio_tagging.py:384] Calculating the averaged model over iteration checkpoints from multi_KD/exp_causal1_delta6KD_LS1_5fold+wenetspech0_0fold+as_unbalanced1+vox_1_vox2_base_lr_0.045_use_beats_1_scale_1.0_use_ecapa_1_layer_2_scale_10.0_1_scale_1.0_specaug0_musan0_with_task_ID_stop_early1_share_asr1_md1500_amp_bf16/checkpoint-216000.pt (excluded) to multi_KD/exp_causal1_delta6KD_LS1_5fold+wenetspech0_0fold+as_unbalanced1+vox_1_vox2_base_lr_0.045_use_beats_1_scale_1.0_use_ecapa_1_layer_2_scale_10.0_1_scale_1.0_specaug0_musan0_with_task_ID_stop_early1_share_asr1_md1500_amp_bf16/checkpoint-224000.pt
2024-08-17 12:48:05,206 INFO [inference_audio_tagging.py:421] Number of model parameters: 65577734
2024-08-17 12:48:05,206 INFO [kd_datamodule.py:912] About to get the audioset eval cuts.
2024-08-17 12:48:05,253 INFO [kd_datamodule.py:570] About to create dev dataset
2024-08-17 12:48:05,664 INFO [kd_datamodule.py:591] About to create dev dataloader
2024-08-17 12:48:11,858 INFO [inference_audio_tagging.py:286] Processed 60 cuts already.
2024-08-17 12:48:19,317 INFO [inference_audio_tagging.py:286] Processed 660 cuts already.
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2024-08-17 12:48:33,866 INFO [inference_audio_tagging.py:286] Processed 1860 cuts already.
2024-08-17 12:48:40,924 INFO [inference_audio_tagging.py:286] Processed 2460 cuts already.
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2024-08-17 12:49:00,564 INFO [inference_audio_tagging.py:286] Processed 4260 cuts already.
2024-08-17 12:49:02,476 INFO [zipformer.py:1877] name=None, attn_weights_entropy = tensor([4.2148, 2.8000, 3.8232, 4.1030], device='cuda:0')
2024-08-17 12:49:06,932 INFO [inference_audio_tagging.py:286] Processed 4860 cuts already.
2024-08-17 12:49:08,285 INFO [zipformer.py:1877] name=None, attn_weights_entropy = tensor([5.9429, 5.7100, 5.8488, 5.9095], device='cuda:0')
2024-08-17 12:49:13,280 INFO [inference_audio_tagging.py:286] Processed 5460 cuts already.
2024-08-17 12:49:20,088 INFO [inference_audio_tagging.py:286] Processed 6060 cuts already.
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2024-08-17 12:49:40,057 INFO [inference_audio_tagging.py:286] Processed 7860 cuts already.
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2024-08-17 12:50:05,083 INFO [inference_audio_tagging.py:286] Processed 10260 cuts already.
2024-08-17 12:50:06,261 INFO [zipformer.py:1877] name=None, attn_weights_entropy = tensor([5.8057, 5.5924, 5.9777, 5.9412], device='cuda:0')
2024-08-17 12:50:07,625 INFO [zipformer.py:1877] name=None, attn_weights_entropy = tensor([4.7783, 4.0281, 4.8420, 4.0611], device='cuda:0')
2024-08-17 12:50:11,477 INFO [inference_audio_tagging.py:286] Processed 10860 cuts already.
2024-08-17 12:50:17,910 INFO [inference_audio_tagging.py:286] Processed 11460 cuts already.
2024-08-17 12:50:24,172 INFO [inference_audio_tagging.py:286] Processed 12060 cuts already.
2024-08-17 12:50:28,935 INFO [zipformer.py:1877] name=None, attn_weights_entropy = tensor([3.8829, 3.4486, 3.6587, 2.9680, 3.7674, 3.2865, 3.6840, 3.7479],
       device='cuda:0')
2024-08-17 12:50:30,309 INFO [inference_audio_tagging.py:286] Processed 12660 cuts already.
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2024-08-17 12:50:45,167 INFO [zipformer.py:1877] name=None, attn_weights_entropy = tensor([4.2130, 2.8556, 3.8183, 4.1412], device='cuda:0')
2024-08-17 12:50:47,648 INFO [zipformer.py:1877] name=None, attn_weights_entropy = tensor([0.0018, 0.1121, 0.0003, 0.0496, 0.0003, 0.2586, 0.0050, 0.1315],
       device='cuda:0')
2024-08-17 12:50:48,883 INFO [inference_audio_tagging.py:286] Processed 14460 cuts already.
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2024-08-17 12:50:55,751 INFO [inference_audio_tagging.py:287] Finish collecting audio logits
2024-08-17 12:50:57,161 INFO [inference_audio_tagging.py:454] mAP for audioset eval is: 0.007296872691144849
2024-08-17 12:50:57,161 INFO [inference_audio_tagging.py:456] Done