| 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) === | |