| 2026-01-14 00:19:21 | INFO | espnet3 | === ESPnet3 run started: 2026-01-14T00:19:21.364830 === |
| 2026-01-14 00:19:21 | INFO | espnet3 | Command: /data/user_data/msomeki/espnet3/.venv/bin/python3 run.py --stages create_dataset train_tokenizer collect_stats train infer measure --train_config conf/train.yaml --infer_config conf/infer.yaml --measure_config conf/measure.yaml |
| 2026-01-14 00:19:21 | INFO | espnet3 | Python: 3.11.13 (main, Aug 18 2025, 19:19:13) [Clang 20.1.4 ] |
| 2026-01-14 00:19:21 | INFO | espnet3 | Working directory: /home/msomeki/00_systems/espnet3/egs3/mini_an4/asr |
| 2026-01-14 00:19:21 | INFO | espnet3 | train config: /home/msomeki/00_systems/espnet3/egs3/mini_an4/asr/conf/train_asr_rnn_data_aug_debug.yaml |
| 2026-01-14 00:19:21 | INFO | espnet3 | infer config: /home/msomeki/00_systems/espnet3/egs3/mini_an4/asr/conf/infer.yaml |
| 2026-01-14 00:19:21 | INFO | espnet3 | measure config: /home/msomeki/00_systems/espnet3/egs3/mini_an4/asr/conf/measure.yaml |
| 2026-01-14 00:19:21 | INFO | espnet3 | Git: commit=8509faad9811b58d5024f29fb9d68ffb026b5e73, short_commit=8509faad9, branch=espnet3/recipe/asr_ls100, worktree=dirty |
| 2026-01-14 00:19:21 | INFO | espnet3 | Cluster env: |
| OMPI_MCA_plm_slurm_args=--external-launcher |
| SLURM_CLUSTER_NAME=babel |
| SLURM_CONF=/var/spool/slurmd/conf-cache/slurm.conf |
| SLURM_CPUS_ON_NODE=1 |
| SLURM_CPUS_PER_TASK=1 |
| SLURM_CPU_BIND=quiet,mask_cpu:0x0000000000010000 |
| SLURM_CPU_BIND_LIST=0x0000000000010000 |
| SLURM_CPU_BIND_TYPE=mask_cpu: |
| SLURM_CPU_BIND_VERBOSE=quiet |
| SLURM_DISTRIBUTION=cyclic,pack |
| SLURM_GTIDS=0 |
| SLURM_JOBID=6122041 |
| SLURM_JOB_ACCOUNT=swatanab |
| SLURM_JOB_CPUS_PER_NODE=1 |
| SLURM_JOB_END_TIME=1768401875 |
| SLURM_JOB_GID=2709140 |
| SLURM_JOB_GROUP=msomeki |
| SLURM_JOB_ID=6122041 |
| SLURM_JOB_NAME=bash |
| SLURM_JOB_NODELIST=babel-o9-16 |
| SLURM_JOB_NUM_NODES=1 |
| SLURM_JOB_PARTITION=debug |
| SLURM_JOB_QOS=debug_qos |
| SLURM_JOB_START_TIME=1768358675 |
| SLURM_JOB_UID=2709140 |
| SLURM_JOB_USER=msomeki |
| SLURM_LAUNCH_NODE_IPADDR=172.16.1.2 |
| SLURM_LOCALID=0 |
| SLURM_MEM_PER_NODE=4096 |
| SLURM_NNODES=1 |
| SLURM_NODEID=0 |
| SLURM_NODELIST=babel-o9-16 |
| SLURM_NPROCS=1 |
| SLURM_NTASKS=1 |
| SLURM_NTASKS_PER_NODE=1 |
| SLURM_PRIO_PROCESS=0 |
| SLURM_PROCID=0 |
| SLURM_PTY_PORT=40465 |
| SLURM_PTY_WIN_COL=112 |
| SLURM_PTY_WIN_ROW=61 |
| SLURM_SCRIPT_CONTEXT=prolog_task |
| SLURM_SRUN_COMM_HOST=172.16.1.2 |
| SLURM_SRUN_COMM_PORT=33789 |
| SLURM_STEPID=0 |
| SLURM_STEP_ID=0 |
| SLURM_STEP_LAUNCHER_PORT=33789 |
| SLURM_STEP_NODELIST=babel-o9-16 |
| SLURM_STEP_NUM_NODES=1 |
| SLURM_STEP_NUM_TASKS=1 |
| SLURM_STEP_TASKS_PER_NODE=1 |
| SLURM_SUBMIT_DIR=/home/msomeki/00_systems/espnet3 |
| SLURM_SUBMIT_HOST=login1 |
| SLURM_TASKS_PER_NODE=1 |
| SLURM_TASK_PID=3334910 |
| SLURM_TOPOLOGY_ADDR=babel-o9-16 |
| SLURM_TOPOLOGY_ADDR_PATTERN=node |
| SLURM_TRES_PER_TASK=cpu=1 |
| SLURM_UMASK=0027 |
| 2026-01-14 00:19:21 | INFO | espnet3 | Runtime env: |
| LD_LIBRARY_PATH=/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64:/home/msomeki/00_systems/espnet3/tools/espeak-ng/lib:/home/msomeki/00_systems/espnet3/tools/lib:/home/msomeki/00_systems/espnet3/tools/lib64: |
| PATH=/home/msomeki/00_systems/espnet3/tools/ffmpeg-release:/home/msomeki/00_systems/espnet3/tools/festival/bin:/home/msomeki/00_systems/espnet3/tools/MBROLA/Bin:/home/msomeki/00_systems/espnet3/tools/espeak-ng/bin:/home/msomeki/00_systems/espnet3/tools/BeamformIt:/home/msomeki/00_systems/espnet3/tools/kenlm/build/bin:/home/msomeki/00_systems/espnet3/tools/PESQ/P862_annex_A_2005_CD/source:/home/msomeki/00_systems/espnet3/tools/nkf/nkf-2.1.4:/home/msomeki/00_systems/espnet3/tools/moses/scripts/tokenizer:/home/msomeki/00_systems/espnet3/tools/moses/scripts/generic:/home/msomeki/00_systems/espnet3/tools/tools/moses/scripts/recaser:/home/msomeki/00_systems/espnet3/tools/moses/scripts/training:/home/msomeki/00_systems/espnet3/tools/mwerSegmenter:/home/msomeki/00_systems/espnet3/tools/sctk/bin:/home/msomeki/00_systems/espnet3/tools/sph2pipe:/home/msomeki/00_systems/espnet3/tools/sentencepiece_commands:/data/user_data/msomeki/espnet3/.venv/bin:/home/msomeki/.pixi/bin:/home/msomeki/local/bin:/home/msomeki/utils:/usr/share/Modules/bin:/home/msomeki/00_systems/espnet3/tools/ffmpeg-release:/home/msomeki/00_systems/espnet3/tools/festival/bin:/home/msomeki/00_systems/espnet3/tools/MBROLA/Bin:/home/msomeki/00_systems/espnet3/tools/espeak-ng/bin:/home/msomeki/00_systems/espnet3/tools/BeamformIt:/home/msomeki/00_systems/espnet3/tools/kenlm/build/bin:/home/msomeki/00_systems/espnet3/tools/PESQ/P862_annex_A_2005_CD/source:/home/msomeki/00_systems/espnet3/tools/nkf/nkf-2.1.4:/home/msomeki/00_systems/espnet3/tools/moses/scripts/tokenizer:/home/msomeki/00_systems/espnet3/tools/moses/scripts/generic:/home/msomeki/00_systems/espnet3/tools/tools/moses/scripts/recaser:/home/msomeki/00_systems/espnet3/tools/moses/scripts/training:/home/msomeki/00_systems/espnet3/tools/mwerSegmenter:/home/msomeki/00_systems/espnet3/tools/sctk/bin:/home/msomeki/00_systems/espnet3/tools/sph2pipe:/home/msomeki/00_systems/espnet3/tools/sentencepiece_commands:/home/msomeki/00_systems/espnet3/tools/ffmpeg-release:/home/msomeki/00_systems/espnet3/tools/festival/bin:/home/msomeki/00_systems/espnet3/tools/MBROLA/Bin:/home/msomeki/00_systems/espnet3/tools/espeak-ng/bin:/home/msomeki/00_systems/espnet3/tools/BeamformIt:/home/msomeki/00_systems/espnet3/tools/kenlm/build/bin:/home/msomeki/00_systems/espnet3/tools/PESQ/P862_annex_A_2005_CD/source:/home/msomeki/00_systems/espnet3/tools/nkf/nkf-2.1.4:/home/msomeki/00_systems/espnet3/tools/moses/scripts/tokenizer:/home/msomeki/00_systems/espnet3/tools/moses/scripts/generic:/home/msomeki/00_systems/espnet3/tools/tools/moses/scripts/recaser:/home/msomeki/00_systems/espnet3/tools/moses/scripts/training:/home/msomeki/00_systems/espnet3/tools/mwerSegmenter:/home/msomeki/00_systems/espnet3/tools/sctk/bin:/home/msomeki/00_systems/espnet3/tools/sph2pipe:/home/msomeki/00_systems/espnet3/tools/sentencepiece_commands:/home/msomeki/.pixi/bin:/home/msomeki/local/bin:/home/msomeki/utils:/home/msomeki/.local/bin:/home/msomeki/bin:/usr/local/bin:/usr/bin:/usr/local/sbin:/usr/sbin |
| PYTHONPATH=/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:../../../:../../TEMPLATE/asr:/home/msomeki/00_systems/espnet3/egs3/mini_an4/asr:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:../../../:../../TEMPLATE/asr:/home/msomeki/00_systems/espnet3/egs3/mini_an4/asr:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:../../../:../../TEMPLATE/asr:/home/msomeki/00_systems/espnet3/egs3/mini_an4/asr:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:../../../:../../TEMPLATE/asr:/home/msomeki/00_systems/espnet3/egs3/mini_an4/asr:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:../../../:../../TEMPLATE/asr:/home/msomeki/00_systems/espnet3/egs3/mini_an4/asr:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:../../../:../../TEMPLATE/asr:/home/msomeki/00_systems/espnet3/egs3/mini_an4/asr:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models:../../../:../../TEMPLATE/asr:/home/msomeki/00_systems/espnet3/egs3/mini_an4/asr:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3:/home/msomeki/00_systems/espnet3/tools/RawNet/python/RawNet3/models: |
| 2026-01-14 00:19:21 | INFO | espnet3 | Train config content: |
| num_device: 1 |
| num_nodes: 1 |
| task: espnet3.systems.asr.task.ASRTask |
| recipe_dir: . |
| data_dir: ./data |
| exp_tag: train_asr_rnn_data_aug_debug |
| exp_dir: ./exp/train_asr_rnn_data_aug_debug |
| stats_dir: ./exp/stats |
| decode_dir: ./exp/train_asr_rnn_data_aug_debug/decode |
| dataset_dir: ./data/mini_an4 |
| create_dataset: |
| func: src.create_dataset.create_dataset |
| dataset_dir: ./data/mini_an4 |
| archive_path: ./../../egs2/mini_an4/asr1/downloads.tar.gz |
| dataset: |
| _target_: espnet3.components.data.data_organizer.DataOrganizer |
| train: |
| - name: train_nodev |
| dataset: |
| _target_: src.dataset.MiniAN4Dataset |
| manifest_path: ./data/mini_an4/manifest/train_nodev.tsv |
| valid: |
| - name: train_dev |
| dataset: |
| _target_: src.dataset.MiniAN4Dataset |
| manifest_path: ./data/mini_an4/manifest/train_dev.tsv |
| preprocessor: |
| _target_: espnet2.train.preprocessor.CommonPreprocessor |
| _convert_: all |
| fs: 16000 |
| train: true |
| data_aug_effects: |
| - - 0.1 |
| - contrast |
| - enhancement_amount: 75.0 |
| - - 0.1 |
| - highpass |
| - cutoff_freq: 5000 |
| Q: 0.707 |
| - - 0.1 |
| - equalization |
| - center_freq: 1000 |
| gain: 0 |
| Q: 0.707 |
| - - 0.1 |
| - - - 0.3 |
| - speed_perturb |
| - factor: 0.9 |
| - - 0.3 |
| - speed_perturb |
| - factor: 1.1 |
| - - 0.3 |
| - speed_perturb |
| - factor: 1.3 |
| data_aug_num: |
| - 1 |
| - 4 |
| data_aug_prob: 1.0 |
| token_type: bpe |
| token_list: ./data/bpe_30/tokens.txt |
| bpemodel: ./data/bpe_30/bpe.model |
| parallel: |
| env: local |
| n_workers: 1 |
| options: {} |
| dataloader: |
| collate_fn: |
| _target_: espnet2.train.collate_fn.CommonCollateFn |
| int_pad_value: -1 |
| train: |
| multiple_iterator: false |
| num_shards: 1 |
| iter_factory: |
| _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory |
| shuffle: true |
| collate_fn: |
| _target_: espnet2.train.collate_fn.CommonCollateFn |
| int_pad_value: -1 |
| num_workers: 0 |
| batches: |
| type: sorted |
| shape_files: |
| - ./exp/stats/train/feats_shape |
| batch_size: 2 |
| batch_bins: 200000 |
| valid: |
| multiple_iterator: false |
| num_shards: 1 |
| iter_factory: |
| _target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory |
| shuffle: false |
| collate_fn: |
| _target_: espnet2.train.collate_fn.CommonCollateFn |
| int_pad_value: -1 |
| batches: |
| type: sorted |
| shape_files: |
| - ./exp/stats/valid/feats_shape |
| batch_size: 2 |
| batch_bins: 200000 |
| optim: |
| _target_: torch.optim.Adam |
| lr: 0.001 |
| weight_decay: 0.0 |
| scheduler: |
| _target_: torch.optim.lr_scheduler.ReduceLROnPlateau |
| mode: min |
| factor: 0.5 |
| patience: 1 |
| val_scheduler_criterion: valid/loss |
| best_model_criterion: |
| - - valid/acc |
| - 1 |
| - max |
| trainer: |
| devices: 1 |
| num_nodes: 1 |
| accumulate_grad_batches: 1 |
| check_val_every_n_epoch: 1 |
| gradient_clip_val: 1.0 |
| log_every_n_steps: 1 |
| max_epochs: 1 |
| limit_train_batches: 1 |
| limit_val_batches: 1 |
| precision: 32 |
| reload_dataloaders_every_n_epochs: 1 |
| use_distributed_sampler: false |
| tokenizer: |
| vocab_size: 30 |
| character_coverage: 1.0 |
| model_type: bpe |
| save_path: ./data/bpe_30 |
| text_builder: |
| func: src.tokenizer.gather_training_text |
| manifest_path: ./data/mini_an4/manifest/train_nodev.tsv |
| model: |
| vocab_size: 30 |
| token_list: ./data/bpe_30/tokens.txt |
| encoder: vgg_rnn |
| encoder_conf: |
| num_layers: 1 |
| hidden_size: 2 |
| output_size: 2 |
| decoder: rnn |
| decoder_conf: |
| hidden_size: 2 |
| model_conf: |
| ctc_weight: 0.3 |
| lsm_weight: 0.1 |
| length_normalized_loss: false |
| frontend: default |
| frontend_conf: |
| n_fft: 512 |
| win_length: 400 |
| hop_length: 160 |
|
|
| 2026-01-14 00:19:21 | INFO | espnet3 | Infer config content: |
| num_device: 1 |
| num_nodes: 1 |
| recipe_dir: . |
| data_dir: ./data |
| exp_tag: train_asr_rnn_data_aug_debug |
| exp_dir: ./exp/train_asr_rnn_data_aug_debug |
| stats_dir: ./exp/stats |
| decode_dir: ./exp/train_asr_rnn_data_aug_debug/decode |
| dataset_dir: ./data/mini_an4 |
| dataset: |
| _target_: espnet3.components.data.data_organizer.DataOrganizer |
| test: |
| - name: test |
| dataset: |
| _target_: src.dataset.MiniAN4Dataset |
| manifest_path: ./data/mini_an4/manifest/test.tsv |
| parallel: |
| env: local |
| n_workers: 1 |
| model: |
| _target_: espnet2.bin.asr_inference.Speech2Text |
| asr_train_config: ./exp/train_asr_rnn_data_aug_debug/config.yaml |
| asr_model_file: ./exp/train_asr_rnn_data_aug_debug/last.ckpt |
| beam_size: 1 |
| ctc_weight: 0.3 |
| tokenizer: |
| vocab_size: 30 |
| character_coverage: 1.0 |
| model_type: bpe |
| save_path: ./data/bpe_30 |
|
|
| 2026-01-14 00:19:21 | INFO | espnet3 | Measure config content: |
| recipe_dir: . |
| data_dir: ./data |
| exp_tag: train_asr_rnn_data_aug_debug |
| exp_dir: ./exp/train_asr_rnn_data_aug_debug |
| stats_dir: ./exp/stats |
| decode_dir: ./exp/train_asr_rnn_data_aug_debug/decode |
| dataset_dir: ./data/mini_an4 |
| dataset: |
| _target_: espnet3.components.data.data_organizer.DataOrganizer |
| test: |
| - name: test |
| dataset: |
| _target_: src.dataset.MiniAN4Dataset |
| manifest_path: ./data/mini_an4/manifest/test.tsv |
| metrics: |
| - metric: |
| _target_: espnet3.systems.asr.metrics.wer.WER |
| clean_types: null |
| - metric: |
| _target_: espnet3.systems.asr.metrics.cer.CER |
| clean_types: null |
|
|
| 2026-01-14 00:19:21 | INFO | espnet3 | === [START] stage: train === |
| 2026-01-14 00:19:21 | INFO | espnet3.systems.asr.system | ASRSystem.train(): starting training process |
| 2026-01-14 00:19:21 | INFO | espnet3.systems.base.system | Training start | exp_dir=./exp/train_asr_rnn_data_aug_debug model=<unknown> |
| 2026-01-14 00:19:22 | INFO | root | Vocabulary size: 30 |
| 2026-01-14 00:19:22 | INFO | espnet3.systems.base.train | Model: |
| ESPnetASRModel( |
| (frontend): DefaultFrontend( |
| (stft): Stft(n_fft=512, win_length=400, hop_length=160, center=True, normalized=False, onesided=True) |
| (frontend): Frontend() |
| (logmel): LogMel(sr=16000, n_fft=512, n_mels=80, fmin=0, fmax=8000.0, htk=False) |
| ) |
| (normalize): UtteranceMVN(norm_means=True, norm_vars=False) |
| (encoder): VGGRNNEncoder( |
| (enc): ModuleList( |
| (0): VGG2L( |
| (conv1_1): Conv2d(1, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) |
| (conv1_2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) |
| (conv2_1): Conv2d(64, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) |
| (conv2_2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1)) |
| ) |
| (1): RNNP( |
| (birnn0): LSTM(2560, 2, batch_first=True, bidirectional=True) |
| (bt0): Linear(in_features=4, out_features=2, bias=True) |
| ) |
| ) |
| ) |
| (decoder): RNNDecoder( |
| (embed): Embedding(30, 2) |
| (dropout_emb): Dropout(p=0.0, inplace=False) |
| (decoder): ModuleList( |
| (0): LSTMCell(4, 2) |
| ) |
| (dropout_dec): ModuleList( |
| (0): Dropout(p=0.0, inplace=False) |
| ) |
| (output): Linear(in_features=2, out_features=30, bias=True) |
| (att_list): ModuleList( |
| (0): AttLoc( |
| (mlp_enc): Linear(in_features=2, out_features=320, bias=True) |
| (mlp_dec): Linear(in_features=2, out_features=320, bias=False) |
| (mlp_att): Linear(in_features=10, out_features=320, bias=False) |
| (loc_conv): Conv2d(1, 10, kernel_size=(1, 201), stride=(1, 1), padding=(0, 100), bias=False) |
| (gvec): Linear(in_features=320, out_features=1, bias=True) |
| ) |
| ) |
| ) |
| (criterion_att): LabelSmoothingLoss( |
| (criterion): KLDivLoss() |
| ) |
| (ctc): CTC( |
| (ctc_lo): Linear(in_features=2, out_features=30, bias=True) |
| (ctc_loss): CTCLoss() |
| ) |
| ) |
| 2026-01-14 00:19:22 | WARNING | py.warnings | /data/user_data/msomeki/espnet3/.venv/lib/python3.11/site-packages/lightning/fabric/plugins/environments/slurm.py:204: The `srun` command is available on your system but is not used. HINT: If your intention is to run Lightning on SLURM, prepend your python command with `srun` like so: srun python3 run.py --stages create_dataset train_tokenizer coll ... |
|
|
| 2026-01-14 00:19:22 | INFO | lightning.pytorch.utilities.rank_zero | GPU available: False, used: False |
| 2026-01-14 00:19:22 | INFO | lightning.pytorch.utilities.rank_zero | TPU available: False, using: 0 TPU cores |
| 2026-01-14 00:19:22 | INFO | lightning.pytorch.utilities.rank_zero | `Trainer(limit_train_batches=1)` was configured so 1 batch per epoch will be used. |
| 2026-01-14 00:19:22 | INFO | lightning.pytorch.utilities.rank_zero | `Trainer(limit_val_batches=1)` was configured so 1 batch will be used. |
| 2026-01-14 00:19:22 | WARNING | py.warnings | /data/user_data/msomeki/espnet3/.venv/lib/python3.11/site-packages/lightning/pytorch/callbacks/model_checkpoint.py:881: Checkpoint directory /home/msomeki/00_systems/espnet3/egs3/mini_an4/asr/exp/train_asr_rnn_data_aug_debug exists and is not empty. |
|
|
| 2026-01-14 00:19:22 | INFO | lightning.pytorch.callbacks.model_summary | |
| | Name | Type | Params | Mode | FLOPs |
| --------------------------------------------------------- |
| 0 | model | ESPnetASRModel | 307 K | train | 0 |
| --------------------------------------------------------- |
| 307 K Trainable params |
| 0 Non-trainable params |
| 307 K Total params |
| 1.230 Total estimated model params size (MB) |
| 35 Modules in train mode |
| 1 Modules in eval mode |
| 0 Total Flops |
| 2026-01-14 00:19:22 | WARNING | py.warnings | /home/msomeki/00_systems/espnet3/espnet2/asr/espnet_model.py:402: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead. |
| with autocast(self.autocast_frontend, dtype=autocast_type): |
|
|
| 2026-01-14 00:19:22 | WARNING | root | Using make_pad_mask with a list of lengths is not tracable. If you try to trace this function with type(lengths) == list, please change the type of lengths to torch.LongTensor. |
| 2026-01-14 00:19:22 | WARNING | root | Using make_pad_mask with a list of lengths is not tracable. If you try to trace this function with type(lengths) == list, please change the type of lengths to torch.LongTensor. |
| 2026-01-14 00:19:22 | WARNING | py.warnings | /data/user_data/msomeki/espnet3/.venv/lib/python3.11/site-packages/lightning/pytorch/loops/fit_loop.py:534: Found 1 module(s) in eval mode at the start of training. This may lead to unexpected behavior during training. If this is intentional, you can ignore this warning. |
|
|
| 2026-01-14 00:19:22 | WARNING | root | Using make_pad_mask with a list of lengths is not tracable. If you try to trace this function with type(lengths) == list, please change the type of lengths to torch.LongTensor. |
| 2026-01-14 00:19:23 | WARNING | root | Using make_pad_mask with a list of lengths is not tracable. If you try to trace this function with type(lengths) == list, please change the type of lengths to torch.LongTensor. |
| 2026-01-14 00:19:23 | WARNING | root | Using make_pad_mask with a list of lengths is not tracable. If you try to trace this function with type(lengths) == list, please change the type of lengths to torch.LongTensor. |
| 2026-01-14 00:19:23 | WARNING | root | Using make_pad_mask with a list of lengths is not tracable. If you try to trace this function with type(lengths) == list, please change the type of lengths to torch.LongTensor. |
| 2026-01-14 00:19:23 | INFO | lightning.pytorch.utilities.rank_zero | `Trainer.fit` stopped: `max_epochs=1` reached. |
| 2026-01-14 00:19:23 | INFO | espnet3.systems.base.train | Training finished in 1.46s | exp_dir=./exp/train_asr_rnn_data_aug_debug model=None |
| 2026-01-14 00:19:23 | INFO | espnet3 | === [DONE] stage: train (1.47s) === |
|
|
