Add model files

README.md

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+---
+tags:
+- espnet
+- audio
+- automatic-speech-recognition
+language: en
+datasets:
+- sinhala
+license: cc-by-4.0
+---
+## ESPnet2 ASR pretrained model 
+### `espnet/Karthik_sinhala_asr_train_asr_transformer`
+
+This model was trained by Karthik using sinhala/asr1 recipe in [espnet](https://github.com/espnet/espnet/).
+### Demo: How to use in ESPnet2
+```python
+# coming soon
+```
+### Citing ESPnet
+```BibTex
+@inproceedings{watanabe2018espnet,
+  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson {Enrique Yalta Soplin} and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
+  title={{ESPnet}: End-to-End Speech Processing Toolkit},
+  year={2018},
+  booktitle={Proceedings of Interspeech},
+  pages={2207--2211},
+  doi={10.21437/Interspeech.2018-1456},
+  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
+}
+```
+or arXiv:
+```bibtex
+@misc{watanabe2018espnet,
+      title={ESPnet: End-to-End Speech Processing Toolkit}, 
+      author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Enrique Yalta Soplin and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
+      year={2018},
+      eprint={1804.00015},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```

exp/asr_stats_raw_en_word/logdir/q/stats.log

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+Submitted batch job 6473470

exp/asr_stats_raw_en_word/logdir/q/stats.sh

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+#!/bin/bash
+cd /ocean/projects/cis210027p/ganesank/karthik_new/espnet/egs2/dstc2/asr2
+. ./path.sh
+( echo '#' Running on `hostname`
+  echo '#' Started at `date`
+  set | grep SLURM | while read line; do echo "# $line"; done
+  echo -n '# '; cat <<EOF
+python3 -m espnet2.bin.asr_train --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.${SLURM_ARRAY_TASK_ID}.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.${SLURM_ARRAY_TASK_ID}.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.${SLURM_ARRAY_TASK_ID} --config conf/train_asr.yaml --frontend_conf fs=16k 
+EOF
+) >exp/asr_stats_raw_en_word/logdir/stats.$SLURM_ARRAY_TASK_ID.log
+if [ "$CUDA_VISIBLE_DEVICES" == "NoDevFiles" ]; then
+  ( echo CUDA_VISIBLE_DEVICES set to NoDevFiles, unsetting it... 
+  )>>exp/asr_stats_raw_en_word/logdir/stats.$SLURM_ARRAY_TASK_ID.log
+  unset CUDA_VISIBLE_DEVICES
+fi
+time1=`date +"%s"`
+ ( python3 -m espnet2.bin.asr_train --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.${SLURM_ARRAY_TASK_ID}.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.${SLURM_ARRAY_TASK_ID}.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.${SLURM_ARRAY_TASK_ID} --config conf/train_asr.yaml --frontend_conf fs=16k  ) &>>exp/asr_stats_raw_en_word/logdir/stats.$SLURM_ARRAY_TASK_ID.log
+ret=$?
+sync || true
+time2=`date +"%s"`
+echo '#' Accounting: begin_time=$time1 >>exp/asr_stats_raw_en_word/logdir/stats.$SLURM_ARRAY_TASK_ID.log
+echo '#' Accounting: end_time=$time2 >>exp/asr_stats_raw_en_word/logdir/stats.$SLURM_ARRAY_TASK_ID.log
+echo '#' Accounting: time=$(($time2-$time1)) threads=1 >>exp/asr_stats_raw_en_word/logdir/stats.$SLURM_ARRAY_TASK_ID.log
+echo '#' Finished at `date` with status $ret >>exp/asr_stats_raw_en_word/logdir/stats.$SLURM_ARRAY_TASK_ID.log
+[ $ret -eq 137 ] && exit 100;
+touch exp/asr_stats_raw_en_word/logdir/q/done.1251580.$SLURM_ARRAY_TASK_ID
+exit $[$ret ? 1 : 0]
+## submitted with:
+# sbatch --export=PATH  -p RM-shared --time 10:00:00  --open-mode=append -e exp/asr_stats_raw_en_word/logdir/q/stats.log -o exp/asr_stats_raw_en_word/logdir/q/stats.log --array 1-32 /ocean/projects/cis210027p/ganesank/karthik_new/espnet/egs2/dstc2/asr2/exp/asr_stats_raw_en_word/logdir/q/stats.sh >>exp/asr_stats_raw_en_word/logdir/q/stats.log 2>&1

exp/asr_stats_raw_en_word/logdir/stats.1.log

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+# Running on r226.ib.bridges2.psc.edu
+# Started at Mon Jan 31 02:19:48 EST 2022
+# SLURMD_NODENAME=r226
+# SLURM_ARRAY_JOB_ID=6473470
+# SLURM_ARRAY_TASK_COUNT=32
+# SLURM_ARRAY_TASK_ID=1
+# SLURM_ARRAY_TASK_MAX=32
+# SLURM_ARRAY_TASK_MIN=1
+# SLURM_ARRAY_TASK_STEP=1
+# SLURM_CLUSTER_NAME=bridges2
+# SLURM_CONF=/var/spool/slurm/d/conf-cache/slurm.conf
+# SLURM_CPUS_ON_NODE=1
+# SLURM_EXPORT_ENV=PATH
+# SLURM_GET_USER_ENV=1
+# SLURM_GTIDS=0
+# SLURM_JOBID=6473472
+# SLURM_JOB_ACCOUNT=cis210027p
+# SLURM_JOB_CPUS_PER_NODE=1
+# SLURM_JOB_GID=24886
+# SLURM_JOB_ID=6473472
+# SLURM_JOB_NAME=stats.sh
+# SLURM_JOB_NODELIST=r226
+# SLURM_JOB_NUM_NODES=1
+# SLURM_JOB_PARTITION=RM-shared
+# SLURM_JOB_QOS=rm
+# SLURM_JOB_UID=82326
+# SLURM_JOB_USER=ganesank
+# SLURM_LOCALID=0
+# SLURM_MEM_PER_CPU=2000
+# SLURM_NNODES=1
+# SLURM_NODEID=0
+# SLURM_NODELIST=r226
+# SLURM_NODE_ALIASES='(null)'
+# SLURM_OPEN_MODE=a
+# SLURM_PRIO_PROCESS=0
+# SLURM_PROCID=0
+# SLURM_SUBMIT_DIR=/ocean/projects/cis210027p/ganesank/karthik_new/espnet/egs2/dstc2/asr2
+# SLURM_SUBMIT_HOST=br012.ib.bridges2.psc.edu
+# SLURM_TASKS_PER_NODE=1
+# SLURM_TASK_PID=37159
+# SLURM_TOPOLOGY_ADDR=r226
+# SLURM_TOPOLOGY_ADDR_PATTERN=node
+# SLURM_WORKING_CLUSTER=bridges2:br003:6814:9216:109
+# python3 -m espnet2.bin.asr_train --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.1.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.1.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.1 --config conf/train_asr.yaml --frontend_conf fs=16k 
+/ocean/projects/cis210027p/ganesank/karthik_new/espnet/tools/venv/bin/python3 /ocean/projects/cis210027p/ganesank/karthik_new/espnet/espnet2/bin/asr_train.py --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.1.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.1.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.1 --config conf/train_asr.yaml --frontend_conf fs=16k
+[r226] 2022-01-31 02:20:59,156 (asr:382) INFO: Vocabulary size: 613
+[r226] 2022-01-31 02:21:00,083 (abs_task:1132) INFO: pytorch.version=1.8.1+cu102, cuda.available=False, cudnn.version=7605, cudnn.benchmark=False, cudnn.deterministic=True
+[r226] 2022-01-31 02:21:00,090 (abs_task:1133) INFO: Model structure:
+ESPnetASRModel(
+  (frontend): DefaultFrontend(
+    (stft): Stft(n_fft=512, win_length=512, hop_length=128, 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)
+  )
+  (specaug): SpecAug(
+    (time_warp): TimeWarp(window=5, mode=bicubic)
+    (freq_mask): MaskAlongAxis(mask_width_range=[0, 30], num_mask=2, axis=freq)
+    (time_mask): MaskAlongAxis(mask_width_range=[0, 40], num_mask=2, axis=time)
+  )
+  (normalize): UtteranceMVN(norm_means=True, norm_vars=False)
+  (encoder): TransformerEncoder(
+    (embed): Conv2dSubsampling(
+      (conv): Sequential(
+        (0): Conv2d(1, 256, kernel_size=(3, 3), stride=(2, 2))
+        (1): ReLU()
+        (2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2))
+        (3): ReLU()
+      )
+      (out): Sequential(
+        (0): Linear(in_features=4864, out_features=256, bias=True)
+        (1): PositionalEncoding(
+          (dropout): Dropout(p=0.1, inplace=False)
+        )
+      )
+    )
+    (encoders): MultiSequential(
+      (0): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (1): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (2): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (3): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (4): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (5): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (6): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (7): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (8): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (9): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (10): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (11): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (after_norm): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+  )
+  (decoder): TransformerDecoder(
+    (embed): Sequential(
+      (0): Embedding(613, 256)
+      (1): PositionalEncoding(
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (after_norm): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+    (output_layer): Linear(in_features=256, out_features=613, bias=True)
+    (decoders): MultiSequential(
+      (0): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (1): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (2): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (3): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (4): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (5): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+  )
+  (ctc): CTC(
+    (ctc_lo): Linear(in_features=256, out_features=613, bias=True)
+    (ctc_loss): CTCLoss()
+  )
+  (criterion_att): LabelSmoothingLoss(
+    (criterion): KLDivLoss()
+  )
+)
+
+Model summary:
+    Class Name: ESPnetASRModel
+    Total Number of model parameters: 27.56 M
+    Number of trainable parameters: 27.56 M (100.0%)
+    Size: 110.26 MB
+    Type: torch.float32
+[r226] 2022-01-31 02:21:00,090 (abs_task:1136) INFO: Optimizer:
+Adam (
+Parameter Group 0
+    amsgrad: False
+    betas: (0.9, 0.999)
+    eps: 1e-08
+    initial_lr: 0.0002
+    lr: 8e-09
+    weight_decay: 0
+)
+[r226] 2022-01-31 02:21:00,090 (abs_task:1137) INFO: Scheduler: WarmupLR(warmup_steps=25000)
+[r226] 2022-01-31 02:21:00,092 (abs_task:1146) INFO: Saving the configuration in exp/asr_stats_raw_en_word/logdir/stats.1/config.yaml
+[r226] 2022-01-31 02:21:00,121 (abs_task:1157) INFO: Namespace(config='conf/train_asr.yaml', print_config=False, log_level='INFO', dry_run=False, iterator_type='sequence', output_dir='exp/asr_stats_raw_en_word/logdir/stats.1', ngpu=0, seed=0, num_workers=1, num_att_plot=3, dist_backend='nccl', dist_init_method='env://', dist_world_size=None, dist_rank=None, local_rank=None, dist_master_addr=None, dist_master_port=None, dist_launcher=None, multiprocessing_distributed=False, unused_parameters=False, sharded_ddp=False, cudnn_enabled=True, cudnn_benchmark=False, cudnn_deterministic=True, collect_stats=True, write_collected_feats=False, max_epoch=20, patience=None, val_scheduler_criterion=('valid', 'loss'), early_stopping_criterion=('valid', 'loss', 'min'), best_model_criterion=[('train', 'loss', 'min'), ('valid', 'loss', 'min'), ('train', 'acc', 'max'), ('valid', 'acc', 'max')], keep_nbest_models=5, grad_clip=5.0, grad_clip_type=2.0, grad_noise=False, accum_grad=1, no_forward_run=False, resume=False, train_dtype='float32', use_amp=False, log_interval=None, use_tensorboard=True, use_wandb=False, wandb_project=None, wandb_id=None, wandb_entity=None, wandb_name=None, wandb_model_log_interval=-1, detect_anomaly=False, pretrain_path=None, init_param=[], ignore_init_mismatch=False, freeze_param=[], num_iters_per_epoch=None, batch_size=20, valid_batch_size=None, batch_bins=1000000, valid_batch_bins=None, train_shape_file=['exp/asr_stats_raw_en_word/logdir/train.1.scp'], valid_shape_file=['exp/asr_stats_raw_en_word/logdir/valid.1.scp'], batch_type='folded', valid_batch_type=None, fold_length=[], sort_in_batch='descending', sort_batch='descending', multiple_iterator=False, chunk_length=500, chunk_shift_ratio=0.5, num_cache_chunks=1024, train_data_path_and_name_and_type=[('dump/raw/train/wav.scp', 'speech', 'sound'), ('dump/raw/train/text', 'text', 'text')], valid_data_path_and_name_and_type=[('dump/raw/valid/wav.scp', 'speech', 'sound'), ('dump/raw/valid/text', 'text', 'text')], allow_variable_data_keys=False, max_cache_size=0.0, max_cache_fd=32, valid_max_cache_size=None, optim='adam', optim_conf={'lr': 0.0002}, scheduler='warmuplr', scheduler_conf={'warmup_steps': 25000}, token_list=['<blank>', '<unk>', '<utt>', '<sep>', 'bye', 'the', 'food', 'you', 'thank', 'thankyou', 'good', 'request-phone', 'number', 'phone', 'request-addr', 'address', 'restaurant', 'of', 'i', 'what', 'is', 'a', 'in', 'town', 'reqalts', 'part', 'inform-this-dontcare', 'for', 'and', 'looking', 'im', 'whats', 'about', 'inform-pricerange-moderate', 'dont', 'that', 'care', 'affirm', 'cheap', 'inform-pricerange-cheap', 'south', 'inform-area-south', 'how', 'serves', 'have', 'moderately', 'yes', 'priced', 'expensive', 'north', 'any', 'inform-pricerange-expensive', 'can', 'request-postcode', 'anything', 'else', 'inform-area-north', 'code', 'post', 'it', 'price', 'west', 'inform-area-west', 'east', 'type', 'inform-area-east', 'range', 'there', 'request-food', 'okay', 'oriental', 'goodbye', 'european', 'request-pricerange', 'area', 'want', 'an', 'inform-food-indian', 'indian', 'matter', 'doesnt', 'uh', 'thai', 'serve', 'request-area', 'inform-food-thai', 'inform-food-asian', 'asian', 'chinese', 'like', 'inform-area-centre', 'find', 'inform-food-chinese', 'inform-food-italian', 'italian', 'negate', 'center', 'no', 'moderate', 'please', 'get', 'to', 'their', 'inform-food-european', 'serving', 'may', 'inform-area-dontcare', 'do', 'korean', 'spanish', 'inform-food-spanish', 'vietnamese', 'inform-food-vietnamese', 'inform-food-korean', 'id', 'could', 'american', 'british', 'inform-food-british', 'kind', 'need', 'inform-food-turkish', 'turkish', 'um', 'inform-food-portuguese', 'gastropub', 'portuguese', 'does', 'inform-food-gastropub', 'inform-food-french', 'french', 'would', 'inform-food-mediterranean', 'mediterranean', 'they', 'modern', 'hello', 'inform-food-modern', 'noise', 'inform-pricerange-dontcare', 'its', 'inform-food-international', 'international', 'me', 'should', 'inform-food-north', 'repeat', 'right', 'give', 'inform-food-seafood', 'inform-food-japanese', 'japanese', 'jamaican', 'inform-food-jamaican', 'inform-food-creative', 'creative', 'are', 'inform-food-mexican', 'mexican', 'telephone', 'another', 'one', 'hungarian', 'ah', 'something', 'inform-food-dontcare', 'inform-food-cantonese', 'cantonese', 'inform-food-cuban', 'cuban', 'inform-food-hungarian', 'hi', 'breath', 'sea', 'yea', 'am', 'inform-food-traditional', 'traditional', 'caribbean', 'restaurants', 'ack', 'inform-food-world', 'world', 'with', 'inform-food-caribbean', 'barbecue', 'inform-food-corsica', 'corsica', 'inform-food-lebanese', 'lebanese', 'be', 'inform-food-basque', 'postcode', 'inform-food-romanian', 'romanian', 'inform-food-greek', 'greek', 'inform-food-barbeque', 'inform-food-african', 'african', 'side', 'other', 'pan', 'inform-food-english', 'english', 'inform-food-danish', 'danish', 'venue', 'inform-food-malaysian', 'australian', 'inform-food-unusual', 'unusual', 'inform-food-moroccan', 'inform-food-kosher', 'kosher', 'thats', 'inform-food-scandinavian', 'inform-food-afghan', 'afghan', 'inform-food-polynesian', 'polynesian', 'bout', 'inform-food-german', 'german', 'not', 'inform-food-vegetarian', 'inform-food-persian', 'persian', 'scandinavian', 'basque', 'inform-food-belgian', 'malaysian', 'inform-food-australian', 'moroccan', 'christmas', 'inform-food-catalan', 'inform-food-canapes', 'vegetarian', 'on', 'swedish', 'inform-food-irish', 'irish', 'canapes', 'inform-food-christmas', 'catalan', 'inform-food-venetian', 'inform-food-swedish', 'where', 'inform-food-tuscan', 'tuscan', 'inform-food-eritrean', 'venetian', 'inform-food-steakhouse', 'fusion', 'unintelligible', 'inform-food-bistro', 'bistro', 'yeah', 'alright', 'inform-food-swiss', 'swiss', 'inform-food-singaporean', 'seafood', 'know', 'confirm-pricerange-expensive', 'confirm-pricerange-moderate', 'next', 'oh', 'inform-food-brazilian', 'brazilian', 'inform-food-scottish', 'scottish', 'inform-food-fusion', 'inform-food-russian', 'russian', 'singaporean', 'kay', 'fine', 'inform-food-welsh', 'welsh', 'over', 'belgium', 'belgian', 'great', 'addre', 'inform-food-crossover', 'cool', 'steakhouse', 'confirm-food-chinese', 'inform-food-austrian', 'austrian', 'inform-food-polish', 'polish', 'again', 'centre', 'then', 'ok', 'halal', 'steak', 'back', 'thanks', 'inform-food-indonesian', 'indonesian', 'correct', 'well', 'confirm-area-centre', 'confirm-area-north', 'inform-food-halal', 'see', 'welcome', 'house', 'postal', 'pri', 'more', 'anywhere', 'central', 'crossover', 'much', 'very', 'located', 'my', 'confirm-pricerange-cheap', 'restart', 'start', 'go', 'just', 'iam', 'confirm-food-thai', 'confirm-food-korean', 'city', 'as', 'wok', 'option', 'was', 'two', 'your', 'confirm-food-gastropub', 'time', 'chiquito', 'inform-name-prezzo', 'prezzo', 'fuck', 'prices', 'reqmore', 'bask', 'different', 'cambridge', 'turkiesh', 'show', 'chineese', 'confirm-area-east', 'rest', 'request-name', 'name', 'try', 'sorry', 'foo', 'ye', 'ser', 'sells', 'change', 'confirm-food-hungarian', 'eritrean', 'but', 'eartrain', 'options', 'location', 'served', 'cross', 'k', 'inform-name-chiquito', 'bar', 'tv_noise', 'confirm-food-canapes', 'day', 'parts', 'malyasian', 'airitran', 'so', 'new', 'at', 'confirm-food-indian', 'confirm-food-portuguese', 'place', 'tell', 'though', 'choice', 'awesome', 'stop', 'inform-food-australasian', 'portugese', 'missing', 'sock', 'deny-name-golden', 'golden', 'park', 'tur', 'vinci', 'pizzeria', 'endonesian', 'needs', 'deny-food-korean', 'confirm-area-west', 't', 'trying', 'dear', 'thatll', 'excellent', 'baskaye', 'confirm-food-basque', 'p', 'if', 'india', 'some', 'ran', 'moroccon', 'confirm-food-european', 'hut', 'all', 'airatarin', 'canope', 'tailand', 'vanessa', 'earatrain', 'shit', 'ts', 'confirm-food-steakhouse', 'cantonates', 'vegitarian', 'knocking', 'signaporian', 'mail', 'foods', 'got', 'us', 'lets', 'f', 'medium', 'un', 'downtown', 'portugeuse', 'venues', 'talking', 'nymber', 'every', 'this', 'moron', 'says', 'sucks', 'itailian', 'chinses', 'elses', 'request-signature', 'special', 'restaurnt', 'confirm-food-fusion', 'spensive', 'scandinavia', 'gastro', 'pub', 'anyone', 'deny-food-chinese', 'res', 'derately', 'down', 'fancy', 'wha', 'alternative', 'confirm-food-mediterranean', 'confirm-food-caribbean', 'first', 'least', 'bart', 'selection', 'finally', 'somewhere', 'ko', 'sounds', 'said', 'eat', 'huh', 'searching', 's', 'wrong', 'cute', 'ffood', 'earetree', 'earatree', 'confirm-food-modern', 'confirm-food-christmas', 'long', 'class', 'restauran', 'turk', 'deny-name-the', 'beside', 'yourself', 'hate', 'signaporean', 'restuarant', 'did', 'inform-name-da', 'da', 'only', 'int', 'inform-name-bloomsbury', 'bloomsbury', 'inaudible', 'scandanavian', 'done', 'confirm-food-indonesian', 'cancun', 'gasper', 'o', 'meant', 'plea', 'halo', 'inner', 'confirm-food-swedish', 'confirm-food-asian', 'wanna', 'catalanian', 'darling', 'canape', 'baskey', 'indians', 'bat', 'europ', 'now', 'canopy', 'restaraunt', 'medterranean', 'cant', 'deosnt', 'ostro', 'addrss', 'damn', 'deny-name-hk', 'hk', 'signapore', 'probably', 'ly', 'moderat', 'modereate', 'let', 'zip', 'spani', 'adddress', 'ori', 'euorpean', 'confirm-food-seafood', 'mistakes', 'ooh', 'confirm-food-spanish', 'worth', 'mediteranian', 'music', 'others', 'b', 'types', 'thing', 'fish', 'besides', 'confirm-food-halal', 'inform-name-pizza', 'pizza', 'ever', 'surprise', 'ones', 'train', 'arotrian', 'modertley', 'calling', 'minuet', 'york', 'sh', 'cost', 'confirm-area-south', 'bristish', 'confirm-food-british', 'loo', 'think', 'medetanian', 'wheres', 'his', 'confirm-food-turkish', 'inform-name-restaurant', 'euro', 'wondering', 'theres', 'afternoon', 'sure', 'might', 'umh', 'deny-food-vietnamese', 'art', 'rerestaurant', 'vietna', 'ne', 'take', 'modreately', 'air', 'tran', 'crosstalk', 'mind', 'ya', 'god', 'really', 'believe', 'confirm-food-italian', 'confirm-food-jamaican', 'preference', '<sos/eos>'], init=None, input_size=None, ctc_conf={'dropout_rate': 0.0, 'ctc_type': 'builtin', 'reduce': True, 'ignore_nan_grad': True}, model_conf={'ctc_weight': 0.5, 'ignore_id': -1, 'lsm_weight': 0.0, 'length_normalized_loss': False, 'report_cer': True, 'report_wer': True, 'sym_space': '<space>', 'sym_blank': '<blank>', 'extract_feats_in_collect_stats': True}, use_preprocessor=True, token_type='word', bpemodel=None, non_linguistic_symbols=None, cleaner=None, g2p=None, speech_volume_normalize=None, rir_scp=None, rir_apply_prob=1.0, noise_scp=None, noise_apply_prob=1.0, noise_db_range='13_15', frontend='default', frontend_conf={'fs': '16k'}, specaug='specaug', specaug_conf={'apply_time_warp': True, 'time_warp_window': 5, 'time_warp_mode': 'bicubic', 'apply_freq_mask': True, 'freq_mask_width_range': [0, 30], 'num_freq_mask': 2, 'apply_time_mask': True, 'time_mask_width_range': [0, 40], 'num_time_mask': 2}, normalize='utterance_mvn', normalize_conf={}, preencoder=None, preencoder_conf={}, encoder='transformer', encoder_conf={'output_size': 256, 'attention_heads': 4, 'linear_units': 2048, 'num_blocks': 12, 'dropout_rate': 0.1, 'positional_dropout_rate': 0.1, 'attention_dropout_rate': 0.0, 'input_layer': 'conv2d', 'normalize_before': True}, postencoder=None, postencoder_conf={}, decoder='transformer', decoder_conf={'attention_heads': 4, 'linear_units': 2048, 'num_blocks': 6, 'dropout_rate': 0.1, 'positional_dropout_rate': 0.1, 'self_attention_dropout_rate': 0.0, 'src_attention_dropout_rate': 0.0}, required=['output_dir', 'token_list'], version='0.10.3a3', distributed=False)
+# Accounting: begin_time=1643613588
+# Accounting: end_time=1643613668
+# Accounting: time=80 threads=1
+# Finished at Mon Jan 31 02:21:08 EST 2022 with status 0

exp/asr_stats_raw_en_word/logdir/stats.1/config.yaml

@@ -0,0 +1,804 @@
+config: conf/train_asr.yaml
+print_config: false
+log_level: INFO
+dry_run: false
+iterator_type: sequence
+output_dir: exp/asr_stats_raw_en_word/logdir/stats.1
+ngpu: 0
+seed: 0
+num_workers: 1
+num_att_plot: 3
+dist_backend: nccl
+dist_init_method: env://
+dist_world_size: null
+dist_rank: null
+local_rank: null
+dist_master_addr: null
+dist_master_port: null
+dist_launcher: null
+multiprocessing_distributed: false
+unused_parameters: false
+sharded_ddp: false
+cudnn_enabled: true
+cudnn_benchmark: false
+cudnn_deterministic: true
+collect_stats: true
+write_collected_feats: false
+max_epoch: 20
+patience: null
+val_scheduler_criterion:
+- valid
+- loss
+early_stopping_criterion:
+- valid
+- loss
+- min
+best_model_criterion:
+-   - train
+    - loss
+    - min
+-   - valid
+    - loss
+    - min
+-   - train
+    - acc
+    - max
+-   - valid
+    - acc
+    - max
+keep_nbest_models: 5
+grad_clip: 5.0
+grad_clip_type: 2.0
+grad_noise: false
+accum_grad: 1
+no_forward_run: false
+resume: false
+train_dtype: float32
+use_amp: false
+log_interval: null
+use_tensorboard: true
+use_wandb: false
+wandb_project: null
+wandb_id: null
+wandb_entity: null
+wandb_name: null
+wandb_model_log_interval: -1
+detect_anomaly: false
+pretrain_path: null
+init_param: []
+ignore_init_mismatch: false
+freeze_param: []
+num_iters_per_epoch: null
+batch_size: 20
+valid_batch_size: null
+batch_bins: 1000000
+valid_batch_bins: null
+train_shape_file:
+- exp/asr_stats_raw_en_word/logdir/train.1.scp
+valid_shape_file:
+- exp/asr_stats_raw_en_word/logdir/valid.1.scp
+batch_type: folded
+valid_batch_type: null
+fold_length: []
+sort_in_batch: descending
+sort_batch: descending
+multiple_iterator: false
+chunk_length: 500
+chunk_shift_ratio: 0.5
+num_cache_chunks: 1024
+train_data_path_and_name_and_type:
+-   - dump/raw/train/wav.scp
+    - speech
+    - sound
+-   - dump/raw/train/text
+    - text
+    - text
+valid_data_path_and_name_and_type:
+-   - dump/raw/valid/wav.scp
+    - speech
+    - sound
+-   - dump/raw/valid/text
+    - text
+    - text
+allow_variable_data_keys: false
+max_cache_size: 0.0
+max_cache_fd: 32
+valid_max_cache_size: null
+optim: adam
+optim_conf:
+    lr: 0.0002
+scheduler: warmuplr
+scheduler_conf:
+    warmup_steps: 25000
+token_list:
+- <blank>
+- <unk>
+- <utt>
+- <sep>
+- bye
+- the
+- food
+- you
+- thank
+- thankyou
+- good
+- request-phone
+- number
+- phone
+- request-addr
+- address
+- restaurant
+- of
+- i
+- what
+- is
+- a
+- in
+- town
+- reqalts
+- part
+- inform-this-dontcare
+- for
+- and
+- looking
+- im
+- whats
+- about
+- inform-pricerange-moderate
+- dont
+- that
+- care
+- affirm
+- cheap
+- inform-pricerange-cheap
+- south
+- inform-area-south
+- how
+- serves
+- have
+- moderately
+- 'yes'
+- priced
+- expensive
+- north
+- any
+- inform-pricerange-expensive
+- can
+- request-postcode
+- anything
+- else
+- inform-area-north
+- code
+- post
+- it
+- price
+- west
+- inform-area-west
+- east
+- type
+- inform-area-east
+- range
+- there
+- request-food
+- okay
+- oriental
+- goodbye
+- european
+- request-pricerange
+- area
+- want
+- an
+- inform-food-indian
+- indian
+- matter
+- doesnt
+- uh
+- thai
+- serve
+- request-area
+- inform-food-thai
+- inform-food-asian
+- asian
+- chinese
+- like
+- inform-area-centre
+- find
+- inform-food-chinese
+- inform-food-italian
+- italian
+- negate
+- center
+- 'no'
+- moderate
+- please
+- get
+- to
+- their
+- inform-food-european
+- serving
+- may
+- inform-area-dontcare
+- do
+- korean
+- spanish
+- inform-food-spanish
+- vietnamese
+- inform-food-vietnamese
+- inform-food-korean
+- id
+- could
+- american
+- british
+- inform-food-british
+- kind
+- need
+- inform-food-turkish
+- turkish
+- um
+- inform-food-portuguese
+- gastropub
+- portuguese
+- does
+- inform-food-gastropub
+- inform-food-french
+- french
+- would
+- inform-food-mediterranean
+- mediterranean
+- they
+- modern
+- hello
+- inform-food-modern
+- noise
+- inform-pricerange-dontcare
+- its
+- inform-food-international
+- international
+- me
+- should
+- inform-food-north
+- repeat
+- right
+- give
+- inform-food-seafood
+- inform-food-japanese
+- japanese
+- jamaican
+- inform-food-jamaican
+- inform-food-creative
+- creative
+- are
+- inform-food-mexican
+- mexican
+- telephone
+- another
+- one
+- hungarian
+- ah
+- something
+- inform-food-dontcare
+- inform-food-cantonese
+- cantonese
+- inform-food-cuban
+- cuban
+- inform-food-hungarian
+- hi
+- breath
+- sea
+- yea
+- am
+- inform-food-traditional
+- traditional
+- caribbean
+- restaurants
+- ack
+- inform-food-world
+- world
+- with
+- inform-food-caribbean
+- barbecue
+- inform-food-corsica
+- corsica
+- inform-food-lebanese
+- lebanese
+- be
+- inform-food-basque
+- postcode
+- inform-food-romanian
+- romanian
+- inform-food-greek
+- greek
+- inform-food-barbeque
+- inform-food-african
+- african
+- side
+- other
+- pan
+- inform-food-english
+- english
+- inform-food-danish
+- danish
+- venue
+- inform-food-malaysian
+- australian
+- inform-food-unusual
+- unusual
+- inform-food-moroccan
+- inform-food-kosher
+- kosher
+- thats
+- inform-food-scandinavian
+- inform-food-afghan
+- afghan
+- inform-food-polynesian
+- polynesian
+- bout
+- inform-food-german
+- german
+- not
+- inform-food-vegetarian
+- inform-food-persian
+- persian
+- scandinavian
+- basque
+- inform-food-belgian
+- malaysian
+- inform-food-australian
+- moroccan
+- christmas
+- inform-food-catalan
+- inform-food-canapes
+- vegetarian
+- 'on'
+- swedish
+- inform-food-irish
+- irish
+- canapes
+- inform-food-christmas
+- catalan
+- inform-food-venetian
+- inform-food-swedish
+- where
+- inform-food-tuscan
+- tuscan
+- inform-food-eritrean
+- venetian
+- inform-food-steakhouse
+- fusion
+- unintelligible
+- inform-food-bistro
+- bistro
+- yeah
+- alright
+- inform-food-swiss
+- swiss
+- inform-food-singaporean
+- seafood
+- know
+- confirm-pricerange-expensive
+- confirm-pricerange-moderate
+- next
+- oh
+- inform-food-brazilian
+- brazilian
+- inform-food-scottish
+- scottish
+- inform-food-fusion
+- inform-food-russian
+- russian
+- singaporean
+- kay
+- fine
+- inform-food-welsh
+- welsh
+- over
+- belgium
+- belgian
+- great
+- addre
+- inform-food-crossover
+- cool
+- steakhouse
+- confirm-food-chinese
+- inform-food-austrian
+- austrian
+- inform-food-polish
+- polish
+- again
+- centre
+- then
+- ok
+- halal
+- steak
+- back
+- thanks
+- inform-food-indonesian
+- indonesian
+- correct
+- well
+- confirm-area-centre
+- confirm-area-north
+- inform-food-halal
+- see
+- welcome
+- house
+- postal
+- pri
+- more
+- anywhere
+- central
+- crossover
+- much
+- very
+- located
+- my
+- confirm-pricerange-cheap
+- restart
+- start
+- go
+- just
+- iam
+- confirm-food-thai
+- confirm-food-korean
+- city
+- as
+- wok
+- option
+- was
+- two
+- your
+- confirm-food-gastropub
+- time
+- chiquito
+- inform-name-prezzo
+- prezzo
+- fuck
+- prices
+- reqmore
+- bask
+- different
+- cambridge
+- turkiesh
+- show
+- chineese
+- confirm-area-east
+- rest
+- request-name
+- name
+- try
+- sorry
+- foo
+- ye
+- ser
+- sells
+- change
+- confirm-food-hungarian
+- eritrean
+- but
+- eartrain
+- options
+- location
+- served
+- cross
+- k
+- inform-name-chiquito
+- bar
+- tv_noise
+- confirm-food-canapes
+- day
+- parts
+- malyasian
+- airitran
+- so
+- new
+- at
+- confirm-food-indian
+- confirm-food-portuguese
+- place
+- tell
+- though
+- choice
+- awesome
+- stop
+- inform-food-australasian
+- portugese
+- missing
+- sock
+- deny-name-golden
+- golden
+- park
+- tur
+- vinci
+- pizzeria
+- endonesian
+- needs
+- deny-food-korean
+- confirm-area-west
+- t
+- trying
+- dear
+- thatll
+- excellent
+- baskaye
+- confirm-food-basque
+- p
+- if
+- india
+- some
+- ran
+- moroccon
+- confirm-food-european
+- hut
+- all
+- airatarin
+- canope
+- tailand
+- vanessa
+- earatrain
+- shit
+- ts
+- confirm-food-steakhouse
+- cantonates
+- vegitarian
+- knocking
+- signaporian
+- mail
+- foods
+- got
+- us
+- lets
+- f
+- medium
+- un
+- downtown
+- portugeuse
+- venues
+- talking
+- nymber
+- every
+- this
+- moron
+- says
+- sucks
+- itailian
+- chinses
+- elses
+- request-signature
+- special
+- restaurnt
+- confirm-food-fusion
+- spensive
+- scandinavia
+- gastro
+- pub
+- anyone
+- deny-food-chinese
+- res
+- derately
+- down
+- fancy
+- wha
+- alternative
+- confirm-food-mediterranean
+- confirm-food-caribbean
+- first
+- least
+- bart
+- selection
+- finally
+- somewhere
+- ko
+- sounds
+- said
+- eat
+- huh
+- searching
+- s
+- wrong
+- cute
+- ffood
+- earetree
+- earatree
+- confirm-food-modern
+- confirm-food-christmas
+- long
+- class
+- restauran
+- turk
+- deny-name-the
+- beside
+- yourself
+- hate
+- signaporean
+- restuarant
+- did
+- inform-name-da
+- da
+- only
+- int
+- inform-name-bloomsbury
+- bloomsbury
+- inaudible
+- scandanavian
+- done
+- confirm-food-indonesian
+- cancun
+- gasper
+- o
+- meant
+- plea
+- halo
+- inner
+- confirm-food-swedish
+- confirm-food-asian
+- wanna
+- catalanian
+- darling
+- canape
+- baskey
+- indians
+- bat
+- europ
+- now
+- canopy
+- restaraunt
+- medterranean
+- cant
+- deosnt
+- ostro
+- addrss
+- damn
+- deny-name-hk
+- hk
+- signapore
+- probably
+- ly
+- moderat
+- modereate
+- let
+- zip
+- spani
+- adddress
+- ori
+- euorpean
+- confirm-food-seafood
+- mistakes
+- ooh
+- confirm-food-spanish
+- worth
+- mediteranian
+- music
+- others
+- b
+- types
+- thing
+- fish
+- besides
+- confirm-food-halal
+- inform-name-pizza
+- pizza
+- ever
+- surprise
+- ones
+- train
+- arotrian
+- modertley
+- calling
+- minuet
+- york
+- sh
+- cost
+- confirm-area-south
+- bristish
+- confirm-food-british
+- loo
+- think
+- medetanian
+- wheres
+- his
+- confirm-food-turkish
+- inform-name-restaurant
+- euro
+- wondering
+- theres
+- afternoon
+- sure
+- might
+- umh
+- deny-food-vietnamese
+- art
+- rerestaurant
+- vietna
+- ne
+- take
+- modreately
+- air
+- tran
+- crosstalk
+- mind
+- ya
+- god
+- really
+- believe
+- confirm-food-italian
+- confirm-food-jamaican
+- preference
+- <sos/eos>
+init: null
+input_size: null
+ctc_conf:
+    dropout_rate: 0.0
+    ctc_type: builtin
+    reduce: true
+    ignore_nan_grad: true
+model_conf:
+    ctc_weight: 0.5
+    ignore_id: -1
+    lsm_weight: 0.0
+    length_normalized_loss: false
+    report_cer: true
+    report_wer: true
+    sym_space: <space>
+    sym_blank: <blank>
+    extract_feats_in_collect_stats: true
+use_preprocessor: true
+token_type: word
+bpemodel: null
+non_linguistic_symbols: null
+cleaner: null
+g2p: null
+speech_volume_normalize: null
+rir_scp: null
+rir_apply_prob: 1.0
+noise_scp: null
+noise_apply_prob: 1.0
+noise_db_range: '13_15'
+frontend: default
+frontend_conf:
+    fs: 16k
+specaug: specaug
+specaug_conf:
+    apply_time_warp: true
+    time_warp_window: 5
+    time_warp_mode: bicubic
+    apply_freq_mask: true
+    freq_mask_width_range:
+    - 0
+    - 30
+    num_freq_mask: 2
+    apply_time_mask: true
+    time_mask_width_range:
+    - 0
+    - 40
+    num_time_mask: 2
+normalize: utterance_mvn
+normalize_conf: {}
+preencoder: null
+preencoder_conf: {}
+encoder: transformer
+encoder_conf:
+    output_size: 256
+    attention_heads: 4
+    linear_units: 2048
+    num_blocks: 12
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    attention_dropout_rate: 0.0
+    input_layer: conv2d
+    normalize_before: true
+postencoder: null
+postencoder_conf: {}
+decoder: transformer
+decoder_conf:
+    attention_heads: 4
+    linear_units: 2048
+    num_blocks: 6
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    self_attention_dropout_rate: 0.0
+    src_attention_dropout_rate: 0.0
+required:
+- output_dir
+- token_list
+version: 0.10.3a3
+distributed: false

exp/asr_stats_raw_en_word/logdir/stats.1/train/batch_keys

@@ -0,0 +1,2 @@
+speech
+text

exp/asr_stats_raw_en_word/logdir/stats.1/train/speech_shape

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exp/asr_stats_raw_en_word/logdir/stats.10.log

@@ -0,0 +1,495 @@
+# Running on r207.ib.bridges2.psc.edu
+# Started at Mon Jan 31 02:19:57 EST 2022
+# SLURMD_NODENAME=r207
+# SLURM_ARRAY_JOB_ID=6473470
+# SLURM_ARRAY_TASK_COUNT=32
+# SLURM_ARRAY_TASK_ID=10
+# SLURM_ARRAY_TASK_MAX=32
+# SLURM_ARRAY_TASK_MIN=1
+# SLURM_ARRAY_TASK_STEP=1
+# SLURM_CLUSTER_NAME=bridges2
+# SLURM_CONF=/var/spool/slurm/d/conf-cache/slurm.conf
+# SLURM_CPUS_ON_NODE=1
+# SLURM_EXPORT_ENV=PATH
+# SLURM_GET_USER_ENV=1
+# SLURM_GTIDS=0
+# SLURM_JOBID=6473481
+# SLURM_JOB_ACCOUNT=cis210027p
+# SLURM_JOB_CPUS_PER_NODE=1
+# SLURM_JOB_GID=24886
+# SLURM_JOB_ID=6473481
+# SLURM_JOB_NAME=stats.sh
+# SLURM_JOB_NODELIST=r207
+# SLURM_JOB_NUM_NODES=1
+# SLURM_JOB_PARTITION=RM-shared
+# SLURM_JOB_QOS=rm
+# SLURM_JOB_UID=82326
+# SLURM_JOB_USER=ganesank
+# SLURM_LOCALID=0
+# SLURM_MEM_PER_CPU=2000
+# SLURM_NNODES=1
+# SLURM_NODEID=0
+# SLURM_NODELIST=r207
+# SLURM_NODE_ALIASES='(null)'
+# SLURM_OPEN_MODE=a
+# SLURM_PRIO_PROCESS=0
+# SLURM_PROCID=0
+# SLURM_SUBMIT_DIR=/ocean/projects/cis210027p/ganesank/karthik_new/espnet/egs2/dstc2/asr2
+# SLURM_SUBMIT_HOST=br012.ib.bridges2.psc.edu
+# SLURM_TASKS_PER_NODE=1
+# SLURM_TASK_PID=75946
+# SLURM_TOPOLOGY_ADDR=r207
+# SLURM_TOPOLOGY_ADDR_PATTERN=node
+# SLURM_WORKING_CLUSTER=bridges2:br003:6814:9216:109
+# python3 -m espnet2.bin.asr_train --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.10.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.10.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.10 --config conf/train_asr.yaml --frontend_conf fs=16k 
+/ocean/projects/cis210027p/ganesank/karthik_new/espnet/tools/venv/bin/python3 /ocean/projects/cis210027p/ganesank/karthik_new/espnet/espnet2/bin/asr_train.py --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.10.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.10.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.10 --config conf/train_asr.yaml --frontend_conf fs=16k
+[r207] 2022-01-31 02:20:59,157 (asr:382) INFO: Vocabulary size: 613
+[r207] 2022-01-31 02:21:00,040 (abs_task:1132) INFO: pytorch.version=1.8.1+cu102, cuda.available=False, cudnn.version=7605, cudnn.benchmark=False, cudnn.deterministic=True
+[r207] 2022-01-31 02:21:00,047 (abs_task:1133) INFO: Model structure:
+ESPnetASRModel(
+  (frontend): DefaultFrontend(
+    (stft): Stft(n_fft=512, win_length=512, hop_length=128, 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)
+  )
+  (specaug): SpecAug(
+    (time_warp): TimeWarp(window=5, mode=bicubic)
+    (freq_mask): MaskAlongAxis(mask_width_range=[0, 30], num_mask=2, axis=freq)
+    (time_mask): MaskAlongAxis(mask_width_range=[0, 40], num_mask=2, axis=time)
+  )
+  (normalize): UtteranceMVN(norm_means=True, norm_vars=False)
+  (encoder): TransformerEncoder(
+    (embed): Conv2dSubsampling(
+      (conv): Sequential(
+        (0): Conv2d(1, 256, kernel_size=(3, 3), stride=(2, 2))
+        (1): ReLU()
+        (2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2))
+        (3): ReLU()
+      )
+      (out): Sequential(
+        (0): Linear(in_features=4864, out_features=256, bias=True)
+        (1): PositionalEncoding(
+          (dropout): Dropout(p=0.1, inplace=False)
+        )
+      )
+    )
+    (encoders): MultiSequential(
+      (0): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (1): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (2): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (3): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (4): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (5): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (6): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (7): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (8): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (9): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (10): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (11): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (after_norm): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+  )
+  (decoder): TransformerDecoder(
+    (embed): Sequential(
+      (0): Embedding(613, 256)
+      (1): PositionalEncoding(
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (after_norm): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+    (output_layer): Linear(in_features=256, out_features=613, bias=True)
+    (decoders): MultiSequential(
+      (0): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (1): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (2): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (3): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (4): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (5): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+  )
+  (ctc): CTC(
+    (ctc_lo): Linear(in_features=256, out_features=613, bias=True)
+    (ctc_loss): CTCLoss()
+  )
+  (criterion_att): LabelSmoothingLoss(
+    (criterion): KLDivLoss()
+  )
+)
+
+Model summary:
+    Class Name: ESPnetASRModel
+    Total Number of model parameters: 27.56 M
+    Number of trainable parameters: 27.56 M (100.0%)
+    Size: 110.26 MB
+    Type: torch.float32
+[r207] 2022-01-31 02:21:00,047 (abs_task:1136) INFO: Optimizer:
+Adam (
+Parameter Group 0
+    amsgrad: False
+    betas: (0.9, 0.999)
+    eps: 1e-08
+    initial_lr: 0.0002
+    lr: 8e-09
+    weight_decay: 0
+)
+[r207] 2022-01-31 02:21:00,047 (abs_task:1137) INFO: Scheduler: WarmupLR(warmup_steps=25000)
+[r207] 2022-01-31 02:21:00,048 (abs_task:1146) INFO: Saving the configuration in exp/asr_stats_raw_en_word/logdir/stats.10/config.yaml
+[r207] 2022-01-31 02:21:00,075 (abs_task:1157) INFO: Namespace(config='conf/train_asr.yaml', print_config=False, log_level='INFO', dry_run=False, iterator_type='sequence', output_dir='exp/asr_stats_raw_en_word/logdir/stats.10', ngpu=0, seed=0, num_workers=1, num_att_plot=3, dist_backend='nccl', dist_init_method='env://', dist_world_size=None, dist_rank=None, local_rank=None, dist_master_addr=None, dist_master_port=None, dist_launcher=None, multiprocessing_distributed=False, unused_parameters=False, sharded_ddp=False, cudnn_enabled=True, cudnn_benchmark=False, cudnn_deterministic=True, collect_stats=True, write_collected_feats=False, max_epoch=20, patience=None, val_scheduler_criterion=('valid', 'loss'), early_stopping_criterion=('valid', 'loss', 'min'), best_model_criterion=[('train', 'loss', 'min'), ('valid', 'loss', 'min'), ('train', 'acc', 'max'), ('valid', 'acc', 'max')], keep_nbest_models=5, grad_clip=5.0, grad_clip_type=2.0, grad_noise=False, accum_grad=1, no_forward_run=False, resume=False, train_dtype='float32', use_amp=False, log_interval=None, use_tensorboard=True, use_wandb=False, wandb_project=None, wandb_id=None, wandb_entity=None, wandb_name=None, wandb_model_log_interval=-1, detect_anomaly=False, pretrain_path=None, init_param=[], ignore_init_mismatch=False, freeze_param=[], num_iters_per_epoch=None, batch_size=20, valid_batch_size=None, batch_bins=1000000, valid_batch_bins=None, train_shape_file=['exp/asr_stats_raw_en_word/logdir/train.10.scp'], valid_shape_file=['exp/asr_stats_raw_en_word/logdir/valid.10.scp'], batch_type='folded', valid_batch_type=None, fold_length=[], sort_in_batch='descending', sort_batch='descending', multiple_iterator=False, chunk_length=500, chunk_shift_ratio=0.5, num_cache_chunks=1024, train_data_path_and_name_and_type=[('dump/raw/train/wav.scp', 'speech', 'sound'), ('dump/raw/train/text', 'text', 'text')], valid_data_path_and_name_and_type=[('dump/raw/valid/wav.scp', 'speech', 'sound'), ('dump/raw/valid/text', 'text', 'text')], allow_variable_data_keys=False, max_cache_size=0.0, max_cache_fd=32, valid_max_cache_size=None, optim='adam', optim_conf={'lr': 0.0002}, scheduler='warmuplr', scheduler_conf={'warmup_steps': 25000}, token_list=['<blank>', '<unk>', '<utt>', '<sep>', 'bye', 'the', 'food', 'you', 'thank', 'thankyou', 'good', 'request-phone', 'number', 'phone', 'request-addr', 'address', 'restaurant', 'of', 'i', 'what', 'is', 'a', 'in', 'town', 'reqalts', 'part', 'inform-this-dontcare', 'for', 'and', 'looking', 'im', 'whats', 'about', 'inform-pricerange-moderate', 'dont', 'that', 'care', 'affirm', 'cheap', 'inform-pricerange-cheap', 'south', 'inform-area-south', 'how', 'serves', 'have', 'moderately', 'yes', 'priced', 'expensive', 'north', 'any', 'inform-pricerange-expensive', 'can', 'request-postcode', 'anything', 'else', 'inform-area-north', 'code', 'post', 'it', 'price', 'west', 'inform-area-west', 'east', 'type', 'inform-area-east', 'range', 'there', 'request-food', 'okay', 'oriental', 'goodbye', 'european', 'request-pricerange', 'area', 'want', 'an', 'inform-food-indian', 'indian', 'matter', 'doesnt', 'uh', 'thai', 'serve', 'request-area', 'inform-food-thai', 'inform-food-asian', 'asian', 'chinese', 'like', 'inform-area-centre', 'find', 'inform-food-chinese', 'inform-food-italian', 'italian', 'negate', 'center', 'no', 'moderate', 'please', 'get', 'to', 'their', 'inform-food-european', 'serving', 'may', 'inform-area-dontcare', 'do', 'korean', 'spanish', 'inform-food-spanish', 'vietnamese', 'inform-food-vietnamese', 'inform-food-korean', 'id', 'could', 'american', 'british', 'inform-food-british', 'kind', 'need', 'inform-food-turkish', 'turkish', 'um', 'inform-food-portuguese', 'gastropub', 'portuguese', 'does', 'inform-food-gastropub', 'inform-food-french', 'french', 'would', 'inform-food-mediterranean', 'mediterranean', 'they', 'modern', 'hello', 'inform-food-modern', 'noise', 'inform-pricerange-dontcare', 'its', 'inform-food-international', 'international', 'me', 'should', 'inform-food-north', 'repeat', 'right', 'give', 'inform-food-seafood', 'inform-food-japanese', 'japanese', 'jamaican', 'inform-food-jamaican', 'inform-food-creative', 'creative', 'are', 'inform-food-mexican', 'mexican', 'telephone', 'another', 'one', 'hungarian', 'ah', 'something', 'inform-food-dontcare', 'inform-food-cantonese', 'cantonese', 'inform-food-cuban', 'cuban', 'inform-food-hungarian', 'hi', 'breath', 'sea', 'yea', 'am', 'inform-food-traditional', 'traditional', 'caribbean', 'restaurants', 'ack', 'inform-food-world', 'world', 'with', 'inform-food-caribbean', 'barbecue', 'inform-food-corsica', 'corsica', 'inform-food-lebanese', 'lebanese', 'be', 'inform-food-basque', 'postcode', 'inform-food-romanian', 'romanian', 'inform-food-greek', 'greek', 'inform-food-barbeque', 'inform-food-african', 'african', 'side', 'other', 'pan', 'inform-food-english', 'english', 'inform-food-danish', 'danish', 'venue', 'inform-food-malaysian', 'australian', 'inform-food-unusual', 'unusual', 'inform-food-moroccan', 'inform-food-kosher', 'kosher', 'thats', 'inform-food-scandinavian', 'inform-food-afghan', 'afghan', 'inform-food-polynesian', 'polynesian', 'bout', 'inform-food-german', 'german', 'not', 'inform-food-vegetarian', 'inform-food-persian', 'persian', 'scandinavian', 'basque', 'inform-food-belgian', 'malaysian', 'inform-food-australian', 'moroccan', 'christmas', 'inform-food-catalan', 'inform-food-canapes', 'vegetarian', 'on', 'swedish', 'inform-food-irish', 'irish', 'canapes', 'inform-food-christmas', 'catalan', 'inform-food-venetian', 'inform-food-swedish', 'where', 'inform-food-tuscan', 'tuscan', 'inform-food-eritrean', 'venetian', 'inform-food-steakhouse', 'fusion', 'unintelligible', 'inform-food-bistro', 'bistro', 'yeah', 'alright', 'inform-food-swiss', 'swiss', 'inform-food-singaporean', 'seafood', 'know', 'confirm-pricerange-expensive', 'confirm-pricerange-moderate', 'next', 'oh', 'inform-food-brazilian', 'brazilian', 'inform-food-scottish', 'scottish', 'inform-food-fusion', 'inform-food-russian', 'russian', 'singaporean', 'kay', 'fine', 'inform-food-welsh', 'welsh', 'over', 'belgium', 'belgian', 'great', 'addre', 'inform-food-crossover', 'cool', 'steakhouse', 'confirm-food-chinese', 'inform-food-austrian', 'austrian', 'inform-food-polish', 'polish', 'again', 'centre', 'then', 'ok', 'halal', 'steak', 'back', 'thanks', 'inform-food-indonesian', 'indonesian', 'correct', 'well', 'confirm-area-centre', 'confirm-area-north', 'inform-food-halal', 'see', 'welcome', 'house', 'postal', 'pri', 'more', 'anywhere', 'central', 'crossover', 'much', 'very', 'located', 'my', 'confirm-pricerange-cheap', 'restart', 'start', 'go', 'just', 'iam', 'confirm-food-thai', 'confirm-food-korean', 'city', 'as', 'wok', 'option', 'was', 'two', 'your', 'confirm-food-gastropub', 'time', 'chiquito', 'inform-name-prezzo', 'prezzo', 'fuck', 'prices', 'reqmore', 'bask', 'different', 'cambridge', 'turkiesh', 'show', 'chineese', 'confirm-area-east', 'rest', 'request-name', 'name', 'try', 'sorry', 'foo', 'ye', 'ser', 'sells', 'change', 'confirm-food-hungarian', 'eritrean', 'but', 'eartrain', 'options', 'location', 'served', 'cross', 'k', 'inform-name-chiquito', 'bar', 'tv_noise', 'confirm-food-canapes', 'day', 'parts', 'malyasian', 'airitran', 'so', 'new', 'at', 'confirm-food-indian', 'confirm-food-portuguese', 'place', 'tell', 'though', 'choice', 'awesome', 'stop', 'inform-food-australasian', 'portugese', 'missing', 'sock', 'deny-name-golden', 'golden', 'park', 'tur', 'vinci', 'pizzeria', 'endonesian', 'needs', 'deny-food-korean', 'confirm-area-west', 't', 'trying', 'dear', 'thatll', 'excellent', 'baskaye', 'confirm-food-basque', 'p', 'if', 'india', 'some', 'ran', 'moroccon', 'confirm-food-european', 'hut', 'all', 'airatarin', 'canope', 'tailand', 'vanessa', 'earatrain', 'shit', 'ts', 'confirm-food-steakhouse', 'cantonates', 'vegitarian', 'knocking', 'signaporian', 'mail', 'foods', 'got', 'us', 'lets', 'f', 'medium', 'un', 'downtown', 'portugeuse', 'venues', 'talking', 'nymber', 'every', 'this', 'moron', 'says', 'sucks', 'itailian', 'chinses', 'elses', 'request-signature', 'special', 'restaurnt', 'confirm-food-fusion', 'spensive', 'scandinavia', 'gastro', 'pub', 'anyone', 'deny-food-chinese', 'res', 'derately', 'down', 'fancy', 'wha', 'alternative', 'confirm-food-mediterranean', 'confirm-food-caribbean', 'first', 'least', 'bart', 'selection', 'finally', 'somewhere', 'ko', 'sounds', 'said', 'eat', 'huh', 'searching', 's', 'wrong', 'cute', 'ffood', 'earetree', 'earatree', 'confirm-food-modern', 'confirm-food-christmas', 'long', 'class', 'restauran', 'turk', 'deny-name-the', 'beside', 'yourself', 'hate', 'signaporean', 'restuarant', 'did', 'inform-name-da', 'da', 'only', 'int', 'inform-name-bloomsbury', 'bloomsbury', 'inaudible', 'scandanavian', 'done', 'confirm-food-indonesian', 'cancun', 'gasper', 'o', 'meant', 'plea', 'halo', 'inner', 'confirm-food-swedish', 'confirm-food-asian', 'wanna', 'catalanian', 'darling', 'canape', 'baskey', 'indians', 'bat', 'europ', 'now', 'canopy', 'restaraunt', 'medterranean', 'cant', 'deosnt', 'ostro', 'addrss', 'damn', 'deny-name-hk', 'hk', 'signapore', 'probably', 'ly', 'moderat', 'modereate', 'let', 'zip', 'spani', 'adddress', 'ori', 'euorpean', 'confirm-food-seafood', 'mistakes', 'ooh', 'confirm-food-spanish', 'worth', 'mediteranian', 'music', 'others', 'b', 'types', 'thing', 'fish', 'besides', 'confirm-food-halal', 'inform-name-pizza', 'pizza', 'ever', 'surprise', 'ones', 'train', 'arotrian', 'modertley', 'calling', 'minuet', 'york', 'sh', 'cost', 'confirm-area-south', 'bristish', 'confirm-food-british', 'loo', 'think', 'medetanian', 'wheres', 'his', 'confirm-food-turkish', 'inform-name-restaurant', 'euro', 'wondering', 'theres', 'afternoon', 'sure', 'might', 'umh', 'deny-food-vietnamese', 'art', 'rerestaurant', 'vietna', 'ne', 'take', 'modreately', 'air', 'tran', 'crosstalk', 'mind', 'ya', 'god', 'really', 'believe', 'confirm-food-italian', 'confirm-food-jamaican', 'preference', '<sos/eos>'], init=None, input_size=None, ctc_conf={'dropout_rate': 0.0, 'ctc_type': 'builtin', 'reduce': True, 'ignore_nan_grad': True}, model_conf={'ctc_weight': 0.5, 'ignore_id': -1, 'lsm_weight': 0.0, 'length_normalized_loss': False, 'report_cer': True, 'report_wer': True, 'sym_space': '<space>', 'sym_blank': '<blank>', 'extract_feats_in_collect_stats': True}, use_preprocessor=True, token_type='word', bpemodel=None, non_linguistic_symbols=None, cleaner=None, g2p=None, speech_volume_normalize=None, rir_scp=None, rir_apply_prob=1.0, noise_scp=None, noise_apply_prob=1.0, noise_db_range='13_15', frontend='default', frontend_conf={'fs': '16k'}, specaug='specaug', specaug_conf={'apply_time_warp': True, 'time_warp_window': 5, 'time_warp_mode': 'bicubic', 'apply_freq_mask': True, 'freq_mask_width_range': [0, 30], 'num_freq_mask': 2, 'apply_time_mask': True, 'time_mask_width_range': [0, 40], 'num_time_mask': 2}, normalize='utterance_mvn', normalize_conf={}, preencoder=None, preencoder_conf={}, encoder='transformer', encoder_conf={'output_size': 256, 'attention_heads': 4, 'linear_units': 2048, 'num_blocks': 12, 'dropout_rate': 0.1, 'positional_dropout_rate': 0.1, 'attention_dropout_rate': 0.0, 'input_layer': 'conv2d', 'normalize_before': True}, postencoder=None, postencoder_conf={}, decoder='transformer', decoder_conf={'attention_heads': 4, 'linear_units': 2048, 'num_blocks': 6, 'dropout_rate': 0.1, 'positional_dropout_rate': 0.1, 'self_attention_dropout_rate': 0.0, 'src_attention_dropout_rate': 0.0}, required=['output_dir', 'token_list'], version='0.10.3a3', distributed=False)
+# Accounting: begin_time=1643613597
+# Accounting: end_time=1643613668
+# Accounting: time=71 threads=1
+# Finished at Mon Jan 31 02:21:08 EST 2022 with status 0

exp/asr_stats_raw_en_word/logdir/stats.10/config.yaml

@@ -0,0 +1,804 @@
+config: conf/train_asr.yaml
+print_config: false
+log_level: INFO
+dry_run: false
+iterator_type: sequence
+output_dir: exp/asr_stats_raw_en_word/logdir/stats.10
+ngpu: 0
+seed: 0
+num_workers: 1
+num_att_plot: 3
+dist_backend: nccl
+dist_init_method: env://
+dist_world_size: null
+dist_rank: null
+local_rank: null
+dist_master_addr: null
+dist_master_port: null
+dist_launcher: null
+multiprocessing_distributed: false
+unused_parameters: false
+sharded_ddp: false
+cudnn_enabled: true
+cudnn_benchmark: false
+cudnn_deterministic: true
+collect_stats: true
+write_collected_feats: false
+max_epoch: 20
+patience: null
+val_scheduler_criterion:
+- valid
+- loss
+early_stopping_criterion:
+- valid
+- loss
+- min
+best_model_criterion:
+-   - train
+    - loss
+    - min
+-   - valid
+    - loss
+    - min
+-   - train
+    - acc
+    - max
+-   - valid
+    - acc
+    - max
+keep_nbest_models: 5
+grad_clip: 5.0
+grad_clip_type: 2.0
+grad_noise: false
+accum_grad: 1
+no_forward_run: false
+resume: false
+train_dtype: float32
+use_amp: false
+log_interval: null
+use_tensorboard: true
+use_wandb: false
+wandb_project: null
+wandb_id: null
+wandb_entity: null
+wandb_name: null
+wandb_model_log_interval: -1
+detect_anomaly: false
+pretrain_path: null
+init_param: []
+ignore_init_mismatch: false
+freeze_param: []
+num_iters_per_epoch: null
+batch_size: 20
+valid_batch_size: null
+batch_bins: 1000000
+valid_batch_bins: null
+train_shape_file:
+- exp/asr_stats_raw_en_word/logdir/train.10.scp
+valid_shape_file:
+- exp/asr_stats_raw_en_word/logdir/valid.10.scp
+batch_type: folded
+valid_batch_type: null
+fold_length: []
+sort_in_batch: descending
+sort_batch: descending
+multiple_iterator: false
+chunk_length: 500
+chunk_shift_ratio: 0.5
+num_cache_chunks: 1024
+train_data_path_and_name_and_type:
+-   - dump/raw/train/wav.scp
+    - speech
+    - sound
+-   - dump/raw/train/text
+    - text
+    - text
+valid_data_path_and_name_and_type:
+-   - dump/raw/valid/wav.scp
+    - speech
+    - sound
+-   - dump/raw/valid/text
+    - text
+    - text
+allow_variable_data_keys: false
+max_cache_size: 0.0
+max_cache_fd: 32
+valid_max_cache_size: null
+optim: adam
+optim_conf:
+    lr: 0.0002
+scheduler: warmuplr
+scheduler_conf:
+    warmup_steps: 25000
+token_list:
+- <blank>
+- <unk>
+- <utt>
+- <sep>
+- bye
+- the
+- food
+- you
+- thank
+- thankyou
+- good
+- request-phone
+- number
+- phone
+- request-addr
+- address
+- restaurant
+- of
+- i
+- what
+- is
+- a
+- in
+- town
+- reqalts
+- part
+- inform-this-dontcare
+- for
+- and
+- looking
+- im
+- whats
+- about
+- inform-pricerange-moderate
+- dont
+- that
+- care
+- affirm
+- cheap
+- inform-pricerange-cheap
+- south
+- inform-area-south
+- how
+- serves
+- have
+- moderately
+- 'yes'
+- priced
+- expensive
+- north
+- any
+- inform-pricerange-expensive
+- can
+- request-postcode
+- anything
+- else
+- inform-area-north
+- code
+- post
+- it
+- price
+- west
+- inform-area-west
+- east
+- type
+- inform-area-east
+- range
+- there
+- request-food
+- okay
+- oriental
+- goodbye
+- european
+- request-pricerange
+- area
+- want
+- an
+- inform-food-indian
+- indian
+- matter
+- doesnt
+- uh
+- thai
+- serve
+- request-area
+- inform-food-thai
+- inform-food-asian
+- asian
+- chinese
+- like
+- inform-area-centre
+- find
+- inform-food-chinese
+- inform-food-italian
+- italian
+- negate
+- center
+- 'no'
+- moderate
+- please
+- get
+- to
+- their
+- inform-food-european
+- serving
+- may
+- inform-area-dontcare
+- do
+- korean
+- spanish
+- inform-food-spanish
+- vietnamese
+- inform-food-vietnamese
+- inform-food-korean
+- id
+- could
+- american
+- british
+- inform-food-british
+- kind
+- need
+- inform-food-turkish
+- turkish
+- um
+- inform-food-portuguese
+- gastropub
+- portuguese
+- does
+- inform-food-gastropub
+- inform-food-french
+- french
+- would
+- inform-food-mediterranean
+- mediterranean
+- they
+- modern
+- hello
+- inform-food-modern
+- noise
+- inform-pricerange-dontcare
+- its
+- inform-food-international
+- international
+- me
+- should
+- inform-food-north
+- repeat
+- right
+- give
+- inform-food-seafood
+- inform-food-japanese
+- japanese
+- jamaican
+- inform-food-jamaican
+- inform-food-creative
+- creative
+- are
+- inform-food-mexican
+- mexican
+- telephone
+- another
+- one
+- hungarian
+- ah
+- something
+- inform-food-dontcare
+- inform-food-cantonese
+- cantonese
+- inform-food-cuban
+- cuban
+- inform-food-hungarian
+- hi
+- breath
+- sea
+- yea
+- am
+- inform-food-traditional
+- traditional
+- caribbean
+- restaurants
+- ack
+- inform-food-world
+- world
+- with
+- inform-food-caribbean
+- barbecue
+- inform-food-corsica
+- corsica
+- inform-food-lebanese
+- lebanese
+- be
+- inform-food-basque
+- postcode
+- inform-food-romanian
+- romanian
+- inform-food-greek
+- greek
+- inform-food-barbeque
+- inform-food-african
+- african
+- side
+- other
+- pan
+- inform-food-english
+- english
+- inform-food-danish
+- danish
+- venue
+- inform-food-malaysian
+- australian
+- inform-food-unusual
+- unusual
+- inform-food-moroccan
+- inform-food-kosher
+- kosher
+- thats
+- inform-food-scandinavian
+- inform-food-afghan
+- afghan
+- inform-food-polynesian
+- polynesian
+- bout
+- inform-food-german
+- german
+- not
+- inform-food-vegetarian
+- inform-food-persian
+- persian
+- scandinavian
+- basque
+- inform-food-belgian
+- malaysian
+- inform-food-australian
+- moroccan
+- christmas
+- inform-food-catalan
+- inform-food-canapes
+- vegetarian
+- 'on'
+- swedish
+- inform-food-irish
+- irish
+- canapes
+- inform-food-christmas
+- catalan
+- inform-food-venetian
+- inform-food-swedish
+- where
+- inform-food-tuscan
+- tuscan
+- inform-food-eritrean
+- venetian
+- inform-food-steakhouse
+- fusion
+- unintelligible
+- inform-food-bistro
+- bistro
+- yeah
+- alright
+- inform-food-swiss
+- swiss
+- inform-food-singaporean
+- seafood
+- know
+- confirm-pricerange-expensive
+- confirm-pricerange-moderate
+- next
+- oh
+- inform-food-brazilian
+- brazilian
+- inform-food-scottish
+- scottish
+- inform-food-fusion
+- inform-food-russian
+- russian
+- singaporean
+- kay
+- fine
+- inform-food-welsh
+- welsh
+- over
+- belgium
+- belgian
+- great
+- addre
+- inform-food-crossover
+- cool
+- steakhouse
+- confirm-food-chinese
+- inform-food-austrian
+- austrian
+- inform-food-polish
+- polish
+- again
+- centre
+- then
+- ok
+- halal
+- steak
+- back
+- thanks
+- inform-food-indonesian
+- indonesian
+- correct
+- well
+- confirm-area-centre
+- confirm-area-north
+- inform-food-halal
+- see
+- welcome
+- house
+- postal
+- pri
+- more
+- anywhere
+- central
+- crossover
+- much
+- very
+- located
+- my
+- confirm-pricerange-cheap
+- restart
+- start
+- go
+- just
+- iam
+- confirm-food-thai
+- confirm-food-korean
+- city
+- as
+- wok
+- option
+- was
+- two
+- your
+- confirm-food-gastropub
+- time
+- chiquito
+- inform-name-prezzo
+- prezzo
+- fuck
+- prices
+- reqmore
+- bask
+- different
+- cambridge
+- turkiesh
+- show
+- chineese
+- confirm-area-east
+- rest
+- request-name
+- name
+- try
+- sorry
+- foo
+- ye
+- ser
+- sells
+- change
+- confirm-food-hungarian
+- eritrean
+- but
+- eartrain
+- options
+- location
+- served
+- cross
+- k
+- inform-name-chiquito
+- bar
+- tv_noise
+- confirm-food-canapes
+- day
+- parts
+- malyasian
+- airitran
+- so
+- new
+- at
+- confirm-food-indian
+- confirm-food-portuguese
+- place
+- tell
+- though
+- choice
+- awesome
+- stop
+- inform-food-australasian
+- portugese
+- missing
+- sock
+- deny-name-golden
+- golden
+- park
+- tur
+- vinci
+- pizzeria
+- endonesian
+- needs
+- deny-food-korean
+- confirm-area-west
+- t
+- trying
+- dear
+- thatll
+- excellent
+- baskaye
+- confirm-food-basque
+- p
+- if
+- india
+- some
+- ran
+- moroccon
+- confirm-food-european
+- hut
+- all
+- airatarin
+- canope
+- tailand
+- vanessa
+- earatrain
+- shit
+- ts
+- confirm-food-steakhouse
+- cantonates
+- vegitarian
+- knocking
+- signaporian
+- mail
+- foods
+- got
+- us
+- lets
+- f
+- medium
+- un
+- downtown
+- portugeuse
+- venues
+- talking
+- nymber
+- every
+- this
+- moron
+- says
+- sucks
+- itailian
+- chinses
+- elses
+- request-signature
+- special
+- restaurnt
+- confirm-food-fusion
+- spensive
+- scandinavia
+- gastro
+- pub
+- anyone
+- deny-food-chinese
+- res
+- derately
+- down
+- fancy
+- wha
+- alternative
+- confirm-food-mediterranean
+- confirm-food-caribbean
+- first
+- least
+- bart
+- selection
+- finally
+- somewhere
+- ko
+- sounds
+- said
+- eat
+- huh
+- searching
+- s
+- wrong
+- cute
+- ffood
+- earetree
+- earatree
+- confirm-food-modern
+- confirm-food-christmas
+- long
+- class
+- restauran
+- turk
+- deny-name-the
+- beside
+- yourself
+- hate
+- signaporean
+- restuarant
+- did
+- inform-name-da
+- da
+- only
+- int
+- inform-name-bloomsbury
+- bloomsbury
+- inaudible
+- scandanavian
+- done
+- confirm-food-indonesian
+- cancun
+- gasper
+- o
+- meant
+- plea
+- halo
+- inner
+- confirm-food-swedish
+- confirm-food-asian
+- wanna
+- catalanian
+- darling
+- canape
+- baskey
+- indians
+- bat
+- europ
+- now
+- canopy
+- restaraunt
+- medterranean
+- cant
+- deosnt
+- ostro
+- addrss
+- damn
+- deny-name-hk
+- hk
+- signapore
+- probably
+- ly
+- moderat
+- modereate
+- let
+- zip
+- spani
+- adddress
+- ori
+- euorpean
+- confirm-food-seafood
+- mistakes
+- ooh
+- confirm-food-spanish
+- worth
+- mediteranian
+- music
+- others
+- b
+- types
+- thing
+- fish
+- besides
+- confirm-food-halal
+- inform-name-pizza
+- pizza
+- ever
+- surprise
+- ones
+- train
+- arotrian
+- modertley
+- calling
+- minuet
+- york
+- sh
+- cost
+- confirm-area-south
+- bristish
+- confirm-food-british
+- loo
+- think
+- medetanian
+- wheres
+- his
+- confirm-food-turkish
+- inform-name-restaurant
+- euro
+- wondering
+- theres
+- afternoon
+- sure
+- might
+- umh
+- deny-food-vietnamese
+- art
+- rerestaurant
+- vietna
+- ne
+- take
+- modreately
+- air
+- tran
+- crosstalk
+- mind
+- ya
+- god
+- really
+- believe
+- confirm-food-italian
+- confirm-food-jamaican
+- preference
+- <sos/eos>
+init: null
+input_size: null
+ctc_conf:
+    dropout_rate: 0.0
+    ctc_type: builtin
+    reduce: true
+    ignore_nan_grad: true
+model_conf:
+    ctc_weight: 0.5
+    ignore_id: -1
+    lsm_weight: 0.0
+    length_normalized_loss: false
+    report_cer: true
+    report_wer: true
+    sym_space: <space>
+    sym_blank: <blank>
+    extract_feats_in_collect_stats: true
+use_preprocessor: true
+token_type: word
+bpemodel: null
+non_linguistic_symbols: null
+cleaner: null
+g2p: null
+speech_volume_normalize: null
+rir_scp: null
+rir_apply_prob: 1.0
+noise_scp: null
+noise_apply_prob: 1.0
+noise_db_range: '13_15'
+frontend: default
+frontend_conf:
+    fs: 16k
+specaug: specaug
+specaug_conf:
+    apply_time_warp: true
+    time_warp_window: 5
+    time_warp_mode: bicubic
+    apply_freq_mask: true
+    freq_mask_width_range:
+    - 0
+    - 30
+    num_freq_mask: 2
+    apply_time_mask: true
+    time_mask_width_range:
+    - 0
+    - 40
+    num_time_mask: 2
+normalize: utterance_mvn
+normalize_conf: {}
+preencoder: null
+preencoder_conf: {}
+encoder: transformer
+encoder_conf:
+    output_size: 256
+    attention_heads: 4
+    linear_units: 2048
+    num_blocks: 12
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    attention_dropout_rate: 0.0
+    input_layer: conv2d
+    normalize_before: true
+postencoder: null
+postencoder_conf: {}
+decoder: transformer
+decoder_conf:
+    attention_heads: 4
+    linear_units: 2048
+    num_blocks: 6
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    self_attention_dropout_rate: 0.0
+    src_attention_dropout_rate: 0.0
+required:
+- output_dir
+- token_list
+version: 0.10.3a3
+distributed: false

exp/asr_stats_raw_en_word/logdir/stats.10/train/batch_keys

@@ -0,0 +1,2 @@
+speech
+text

exp/asr_stats_raw_en_word/logdir/stats.10/train/speech_shape

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exp/asr_stats_raw_en_word/logdir/stats.11.log

@@ -0,0 +1,495 @@
+# Running on r207.ib.bridges2.psc.edu
+# Started at Mon Jan 31 02:20:05 EST 2022
+# SLURMD_NODENAME=r207
+# SLURM_ARRAY_JOB_ID=6473470
+# SLURM_ARRAY_TASK_COUNT=32
+# SLURM_ARRAY_TASK_ID=11
+# SLURM_ARRAY_TASK_MAX=32
+# SLURM_ARRAY_TASK_MIN=1
+# SLURM_ARRAY_TASK_STEP=1
+# SLURM_CLUSTER_NAME=bridges2
+# SLURM_CONF=/var/spool/slurm/d/conf-cache/slurm.conf
+# SLURM_CPUS_ON_NODE=1
+# SLURM_EXPORT_ENV=PATH
+# SLURM_GET_USER_ENV=1
+# SLURM_GTIDS=0
+# SLURM_JOBID=6473482
+# SLURM_JOB_ACCOUNT=cis210027p
+# SLURM_JOB_CPUS_PER_NODE=1
+# SLURM_JOB_GID=24886
+# SLURM_JOB_ID=6473482
+# SLURM_JOB_NAME=stats.sh
+# SLURM_JOB_NODELIST=r207
+# SLURM_JOB_NUM_NODES=1
+# SLURM_JOB_PARTITION=RM-shared
+# SLURM_JOB_QOS=rm
+# SLURM_JOB_UID=82326
+# SLURM_JOB_USER=ganesank
+# SLURM_LOCALID=0
+# SLURM_MEM_PER_CPU=2000
+# SLURM_NNODES=1
+# SLURM_NODEID=0
+# SLURM_NODELIST=r207
+# SLURM_NODE_ALIASES='(null)'
+# SLURM_OPEN_MODE=a
+# SLURM_PRIO_PROCESS=0
+# SLURM_PROCID=0
+# SLURM_SUBMIT_DIR=/ocean/projects/cis210027p/ganesank/karthik_new/espnet/egs2/dstc2/asr2
+# SLURM_SUBMIT_HOST=br012.ib.bridges2.psc.edu
+# SLURM_TASKS_PER_NODE=1
+# SLURM_TASK_PID=76347
+# SLURM_TOPOLOGY_ADDR=r207
+# SLURM_TOPOLOGY_ADDR_PATTERN=node
+# SLURM_WORKING_CLUSTER=bridges2:br003:6814:9216:109
+# python3 -m espnet2.bin.asr_train --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.11.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.11.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.11 --config conf/train_asr.yaml --frontend_conf fs=16k 
+/ocean/projects/cis210027p/ganesank/karthik_new/espnet/tools/venv/bin/python3 /ocean/projects/cis210027p/ganesank/karthik_new/espnet/espnet2/bin/asr_train.py --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.11.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.11.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.11 --config conf/train_asr.yaml --frontend_conf fs=16k
+[r207] 2022-01-31 02:20:59,157 (asr:382) INFO: Vocabulary size: 613
+[r207] 2022-01-31 02:21:00,040 (abs_task:1132) INFO: pytorch.version=1.8.1+cu102, cuda.available=False, cudnn.version=7605, cudnn.benchmark=False, cudnn.deterministic=True
+[r207] 2022-01-31 02:21:00,047 (abs_task:1133) INFO: Model structure:
+ESPnetASRModel(
+  (frontend): DefaultFrontend(
+    (stft): Stft(n_fft=512, win_length=512, hop_length=128, 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)
+  )
+  (specaug): SpecAug(
+    (time_warp): TimeWarp(window=5, mode=bicubic)
+    (freq_mask): MaskAlongAxis(mask_width_range=[0, 30], num_mask=2, axis=freq)
+    (time_mask): MaskAlongAxis(mask_width_range=[0, 40], num_mask=2, axis=time)
+  )
+  (normalize): UtteranceMVN(norm_means=True, norm_vars=False)
+  (encoder): TransformerEncoder(
+    (embed): Conv2dSubsampling(
+      (conv): Sequential(
+        (0): Conv2d(1, 256, kernel_size=(3, 3), stride=(2, 2))
+        (1): ReLU()
+        (2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2))
+        (3): ReLU()
+      )
+      (out): Sequential(
+        (0): Linear(in_features=4864, out_features=256, bias=True)
+        (1): PositionalEncoding(
+          (dropout): Dropout(p=0.1, inplace=False)
+        )
+      )
+    )
+    (encoders): MultiSequential(
+      (0): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (1): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (2): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (3): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (4): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (5): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (6): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (7): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (8): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (9): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (10): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (11): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (after_norm): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+  )
+  (decoder): TransformerDecoder(
+    (embed): Sequential(
+      (0): Embedding(613, 256)
+      (1): PositionalEncoding(
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (after_norm): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+    (output_layer): Linear(in_features=256, out_features=613, bias=True)
+    (decoders): MultiSequential(
+      (0): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (1): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (2): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (3): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (4): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (5): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+  )
+  (ctc): CTC(
+    (ctc_lo): Linear(in_features=256, out_features=613, bias=True)
+    (ctc_loss): CTCLoss()
+  )
+  (criterion_att): LabelSmoothingLoss(
+    (criterion): KLDivLoss()
+  )
+)
+
+Model summary:
+    Class Name: ESPnetASRModel
+    Total Number of model parameters: 27.56 M
+    Number of trainable parameters: 27.56 M (100.0%)
+    Size: 110.26 MB
+    Type: torch.float32
+[r207] 2022-01-31 02:21:00,047 (abs_task:1136) INFO: Optimizer:
+Adam (
+Parameter Group 0
+    amsgrad: False
+    betas: (0.9, 0.999)
+    eps: 1e-08
+    initial_lr: 0.0002
+    lr: 8e-09
+    weight_decay: 0
+)
+[r207] 2022-01-31 02:21:00,047 (abs_task:1137) INFO: Scheduler: WarmupLR(warmup_steps=25000)
+[r207] 2022-01-31 02:21:00,048 (abs_task:1146) INFO: Saving the configuration in exp/asr_stats_raw_en_word/logdir/stats.11/config.yaml
+[r207] 2022-01-31 02:21:00,075 (abs_task:1157) INFO: Namespace(config='conf/train_asr.yaml', print_config=False, log_level='INFO', dry_run=False, iterator_type='sequence', output_dir='exp/asr_stats_raw_en_word/logdir/stats.11', ngpu=0, seed=0, num_workers=1, num_att_plot=3, dist_backend='nccl', dist_init_method='env://', dist_world_size=None, dist_rank=None, local_rank=None, dist_master_addr=None, dist_master_port=None, dist_launcher=None, multiprocessing_distributed=False, unused_parameters=False, sharded_ddp=False, cudnn_enabled=True, cudnn_benchmark=False, cudnn_deterministic=True, collect_stats=True, write_collected_feats=False, max_epoch=20, patience=None, val_scheduler_criterion=('valid', 'loss'), early_stopping_criterion=('valid', 'loss', 'min'), best_model_criterion=[('train', 'loss', 'min'), ('valid', 'loss', 'min'), ('train', 'acc', 'max'), ('valid', 'acc', 'max')], keep_nbest_models=5, grad_clip=5.0, grad_clip_type=2.0, grad_noise=False, accum_grad=1, no_forward_run=False, resume=False, train_dtype='float32', use_amp=False, log_interval=None, use_tensorboard=True, use_wandb=False, wandb_project=None, wandb_id=None, wandb_entity=None, wandb_name=None, wandb_model_log_interval=-1, detect_anomaly=False, pretrain_path=None, init_param=[], ignore_init_mismatch=False, freeze_param=[], num_iters_per_epoch=None, batch_size=20, valid_batch_size=None, batch_bins=1000000, valid_batch_bins=None, train_shape_file=['exp/asr_stats_raw_en_word/logdir/train.11.scp'], valid_shape_file=['exp/asr_stats_raw_en_word/logdir/valid.11.scp'], batch_type='folded', valid_batch_type=None, fold_length=[], sort_in_batch='descending', sort_batch='descending', multiple_iterator=False, chunk_length=500, chunk_shift_ratio=0.5, num_cache_chunks=1024, train_data_path_and_name_and_type=[('dump/raw/train/wav.scp', 'speech', 'sound'), ('dump/raw/train/text', 'text', 'text')], valid_data_path_and_name_and_type=[('dump/raw/valid/wav.scp', 'speech', 'sound'), ('dump/raw/valid/text', 'text', 'text')], allow_variable_data_keys=False, max_cache_size=0.0, max_cache_fd=32, valid_max_cache_size=None, optim='adam', optim_conf={'lr': 0.0002}, scheduler='warmuplr', scheduler_conf={'warmup_steps': 25000}, token_list=['<blank>', '<unk>', '<utt>', '<sep>', 'bye', 'the', 'food', 'you', 'thank', 'thankyou', 'good', 'request-phone', 'number', 'phone', 'request-addr', 'address', 'restaurant', 'of', 'i', 'what', 'is', 'a', 'in', 'town', 'reqalts', 'part', 'inform-this-dontcare', 'for', 'and', 'looking', 'im', 'whats', 'about', 'inform-pricerange-moderate', 'dont', 'that', 'care', 'affirm', 'cheap', 'inform-pricerange-cheap', 'south', 'inform-area-south', 'how', 'serves', 'have', 'moderately', 'yes', 'priced', 'expensive', 'north', 'any', 'inform-pricerange-expensive', 'can', 'request-postcode', 'anything', 'else', 'inform-area-north', 'code', 'post', 'it', 'price', 'west', 'inform-area-west', 'east', 'type', 'inform-area-east', 'range', 'there', 'request-food', 'okay', 'oriental', 'goodbye', 'european', 'request-pricerange', 'area', 'want', 'an', 'inform-food-indian', 'indian', 'matter', 'doesnt', 'uh', 'thai', 'serve', 'request-area', 'inform-food-thai', 'inform-food-asian', 'asian', 'chinese', 'like', 'inform-area-centre', 'find', 'inform-food-chinese', 'inform-food-italian', 'italian', 'negate', 'center', 'no', 'moderate', 'please', 'get', 'to', 'their', 'inform-food-european', 'serving', 'may', 'inform-area-dontcare', 'do', 'korean', 'spanish', 'inform-food-spanish', 'vietnamese', 'inform-food-vietnamese', 'inform-food-korean', 'id', 'could', 'american', 'british', 'inform-food-british', 'kind', 'need', 'inform-food-turkish', 'turkish', 'um', 'inform-food-portuguese', 'gastropub', 'portuguese', 'does', 'inform-food-gastropub', 'inform-food-french', 'french', 'would', 'inform-food-mediterranean', 'mediterranean', 'they', 'modern', 'hello', 'inform-food-modern', 'noise', 'inform-pricerange-dontcare', 'its', 'inform-food-international', 'international', 'me', 'should', 'inform-food-north', 'repeat', 'right', 'give', 'inform-food-seafood', 'inform-food-japanese', 'japanese', 'jamaican', 'inform-food-jamaican', 'inform-food-creative', 'creative', 'are', 'inform-food-mexican', 'mexican', 'telephone', 'another', 'one', 'hungarian', 'ah', 'something', 'inform-food-dontcare', 'inform-food-cantonese', 'cantonese', 'inform-food-cuban', 'cuban', 'inform-food-hungarian', 'hi', 'breath', 'sea', 'yea', 'am', 'inform-food-traditional', 'traditional', 'caribbean', 'restaurants', 'ack', 'inform-food-world', 'world', 'with', 'inform-food-caribbean', 'barbecue', 'inform-food-corsica', 'corsica', 'inform-food-lebanese', 'lebanese', 'be', 'inform-food-basque', 'postcode', 'inform-food-romanian', 'romanian', 'inform-food-greek', 'greek', 'inform-food-barbeque', 'inform-food-african', 'african', 'side', 'other', 'pan', 'inform-food-english', 'english', 'inform-food-danish', 'danish', 'venue', 'inform-food-malaysian', 'australian', 'inform-food-unusual', 'unusual', 'inform-food-moroccan', 'inform-food-kosher', 'kosher', 'thats', 'inform-food-scandinavian', 'inform-food-afghan', 'afghan', 'inform-food-polynesian', 'polynesian', 'bout', 'inform-food-german', 'german', 'not', 'inform-food-vegetarian', 'inform-food-persian', 'persian', 'scandinavian', 'basque', 'inform-food-belgian', 'malaysian', 'inform-food-australian', 'moroccan', 'christmas', 'inform-food-catalan', 'inform-food-canapes', 'vegetarian', 'on', 'swedish', 'inform-food-irish', 'irish', 'canapes', 'inform-food-christmas', 'catalan', 'inform-food-venetian', 'inform-food-swedish', 'where', 'inform-food-tuscan', 'tuscan', 'inform-food-eritrean', 'venetian', 'inform-food-steakhouse', 'fusion', 'unintelligible', 'inform-food-bistro', 'bistro', 'yeah', 'alright', 'inform-food-swiss', 'swiss', 'inform-food-singaporean', 'seafood', 'know', 'confirm-pricerange-expensive', 'confirm-pricerange-moderate', 'next', 'oh', 'inform-food-brazilian', 'brazilian', 'inform-food-scottish', 'scottish', 'inform-food-fusion', 'inform-food-russian', 'russian', 'singaporean', 'kay', 'fine', 'inform-food-welsh', 'welsh', 'over', 'belgium', 'belgian', 'great', 'addre', 'inform-food-crossover', 'cool', 'steakhouse', 'confirm-food-chinese', 'inform-food-austrian', 'austrian', 'inform-food-polish', 'polish', 'again', 'centre', 'then', 'ok', 'halal', 'steak', 'back', 'thanks', 'inform-food-indonesian', 'indonesian', 'correct', 'well', 'confirm-area-centre', 'confirm-area-north', 'inform-food-halal', 'see', 'welcome', 'house', 'postal', 'pri', 'more', 'anywhere', 'central', 'crossover', 'much', 'very', 'located', 'my', 'confirm-pricerange-cheap', 'restart', 'start', 'go', 'just', 'iam', 'confirm-food-thai', 'confirm-food-korean', 'city', 'as', 'wok', 'option', 'was', 'two', 'your', 'confirm-food-gastropub', 'time', 'chiquito', 'inform-name-prezzo', 'prezzo', 'fuck', 'prices', 'reqmore', 'bask', 'different', 'cambridge', 'turkiesh', 'show', 'chineese', 'confirm-area-east', 'rest', 'request-name', 'name', 'try', 'sorry', 'foo', 'ye', 'ser', 'sells', 'change', 'confirm-food-hungarian', 'eritrean', 'but', 'eartrain', 'options', 'location', 'served', 'cross', 'k', 'inform-name-chiquito', 'bar', 'tv_noise', 'confirm-food-canapes', 'day', 'parts', 'malyasian', 'airitran', 'so', 'new', 'at', 'confirm-food-indian', 'confirm-food-portuguese', 'place', 'tell', 'though', 'choice', 'awesome', 'stop', 'inform-food-australasian', 'portugese', 'missing', 'sock', 'deny-name-golden', 'golden', 'park', 'tur', 'vinci', 'pizzeria', 'endonesian', 'needs', 'deny-food-korean', 'confirm-area-west', 't', 'trying', 'dear', 'thatll', 'excellent', 'baskaye', 'confirm-food-basque', 'p', 'if', 'india', 'some', 'ran', 'moroccon', 'confirm-food-european', 'hut', 'all', 'airatarin', 'canope', 'tailand', 'vanessa', 'earatrain', 'shit', 'ts', 'confirm-food-steakhouse', 'cantonates', 'vegitarian', 'knocking', 'signaporian', 'mail', 'foods', 'got', 'us', 'lets', 'f', 'medium', 'un', 'downtown', 'portugeuse', 'venues', 'talking', 'nymber', 'every', 'this', 'moron', 'says', 'sucks', 'itailian', 'chinses', 'elses', 'request-signature', 'special', 'restaurnt', 'confirm-food-fusion', 'spensive', 'scandinavia', 'gastro', 'pub', 'anyone', 'deny-food-chinese', 'res', 'derately', 'down', 'fancy', 'wha', 'alternative', 'confirm-food-mediterranean', 'confirm-food-caribbean', 'first', 'least', 'bart', 'selection', 'finally', 'somewhere', 'ko', 'sounds', 'said', 'eat', 'huh', 'searching', 's', 'wrong', 'cute', 'ffood', 'earetree', 'earatree', 'confirm-food-modern', 'confirm-food-christmas', 'long', 'class', 'restauran', 'turk', 'deny-name-the', 'beside', 'yourself', 'hate', 'signaporean', 'restuarant', 'did', 'inform-name-da', 'da', 'only', 'int', 'inform-name-bloomsbury', 'bloomsbury', 'inaudible', 'scandanavian', 'done', 'confirm-food-indonesian', 'cancun', 'gasper', 'o', 'meant', 'plea', 'halo', 'inner', 'confirm-food-swedish', 'confirm-food-asian', 'wanna', 'catalanian', 'darling', 'canape', 'baskey', 'indians', 'bat', 'europ', 'now', 'canopy', 'restaraunt', 'medterranean', 'cant', 'deosnt', 'ostro', 'addrss', 'damn', 'deny-name-hk', 'hk', 'signapore', 'probably', 'ly', 'moderat', 'modereate', 'let', 'zip', 'spani', 'adddress', 'ori', 'euorpean', 'confirm-food-seafood', 'mistakes', 'ooh', 'confirm-food-spanish', 'worth', 'mediteranian', 'music', 'others', 'b', 'types', 'thing', 'fish', 'besides', 'confirm-food-halal', 'inform-name-pizza', 'pizza', 'ever', 'surprise', 'ones', 'train', 'arotrian', 'modertley', 'calling', 'minuet', 'york', 'sh', 'cost', 'confirm-area-south', 'bristish', 'confirm-food-british', 'loo', 'think', 'medetanian', 'wheres', 'his', 'confirm-food-turkish', 'inform-name-restaurant', 'euro', 'wondering', 'theres', 'afternoon', 'sure', 'might', 'umh', 'deny-food-vietnamese', 'art', 'rerestaurant', 'vietna', 'ne', 'take', 'modreately', 'air', 'tran', 'crosstalk', 'mind', 'ya', 'god', 'really', 'believe', 'confirm-food-italian', 'confirm-food-jamaican', 'preference', '<sos/eos>'], init=None, input_size=None, ctc_conf={'dropout_rate': 0.0, 'ctc_type': 'builtin', 'reduce': True, 'ignore_nan_grad': True}, model_conf={'ctc_weight': 0.5, 'ignore_id': -1, 'lsm_weight': 0.0, 'length_normalized_loss': False, 'report_cer': True, 'report_wer': True, 'sym_space': '<space>', 'sym_blank': '<blank>', 'extract_feats_in_collect_stats': True}, use_preprocessor=True, token_type='word', bpemodel=None, non_linguistic_symbols=None, cleaner=None, g2p=None, speech_volume_normalize=None, rir_scp=None, rir_apply_prob=1.0, noise_scp=None, noise_apply_prob=1.0, noise_db_range='13_15', frontend='default', frontend_conf={'fs': '16k'}, specaug='specaug', specaug_conf={'apply_time_warp': True, 'time_warp_window': 5, 'time_warp_mode': 'bicubic', 'apply_freq_mask': True, 'freq_mask_width_range': [0, 30], 'num_freq_mask': 2, 'apply_time_mask': True, 'time_mask_width_range': [0, 40], 'num_time_mask': 2}, normalize='utterance_mvn', normalize_conf={}, preencoder=None, preencoder_conf={}, encoder='transformer', encoder_conf={'output_size': 256, 'attention_heads': 4, 'linear_units': 2048, 'num_blocks': 12, 'dropout_rate': 0.1, 'positional_dropout_rate': 0.1, 'attention_dropout_rate': 0.0, 'input_layer': 'conv2d', 'normalize_before': True}, postencoder=None, postencoder_conf={}, decoder='transformer', decoder_conf={'attention_heads': 4, 'linear_units': 2048, 'num_blocks': 6, 'dropout_rate': 0.1, 'positional_dropout_rate': 0.1, 'self_attention_dropout_rate': 0.0, 'src_attention_dropout_rate': 0.0}, required=['output_dir', 'token_list'], version='0.10.3a3', distributed=False)
+# Accounting: begin_time=1643613605
+# Accounting: end_time=1643613668
+# Accounting: time=63 threads=1
+# Finished at Mon Jan 31 02:21:08 EST 2022 with status 0

exp/asr_stats_raw_en_word/logdir/stats.11/config.yaml

@@ -0,0 +1,804 @@
+config: conf/train_asr.yaml
+print_config: false
+log_level: INFO
+dry_run: false
+iterator_type: sequence
+output_dir: exp/asr_stats_raw_en_word/logdir/stats.11
+ngpu: 0
+seed: 0
+num_workers: 1
+num_att_plot: 3
+dist_backend: nccl
+dist_init_method: env://
+dist_world_size: null
+dist_rank: null
+local_rank: null
+dist_master_addr: null
+dist_master_port: null
+dist_launcher: null
+multiprocessing_distributed: false
+unused_parameters: false
+sharded_ddp: false
+cudnn_enabled: true
+cudnn_benchmark: false
+cudnn_deterministic: true
+collect_stats: true
+write_collected_feats: false
+max_epoch: 20
+patience: null
+val_scheduler_criterion:
+- valid
+- loss
+early_stopping_criterion:
+- valid
+- loss
+- min
+best_model_criterion:
+-   - train
+    - loss
+    - min
+-   - valid
+    - loss
+    - min
+-   - train
+    - acc
+    - max
+-   - valid
+    - acc
+    - max
+keep_nbest_models: 5
+grad_clip: 5.0
+grad_clip_type: 2.0
+grad_noise: false
+accum_grad: 1
+no_forward_run: false
+resume: false
+train_dtype: float32
+use_amp: false
+log_interval: null
+use_tensorboard: true
+use_wandb: false
+wandb_project: null
+wandb_id: null
+wandb_entity: null
+wandb_name: null
+wandb_model_log_interval: -1
+detect_anomaly: false
+pretrain_path: null
+init_param: []
+ignore_init_mismatch: false
+freeze_param: []
+num_iters_per_epoch: null
+batch_size: 20
+valid_batch_size: null
+batch_bins: 1000000
+valid_batch_bins: null
+train_shape_file:
+- exp/asr_stats_raw_en_word/logdir/train.11.scp
+valid_shape_file:
+- exp/asr_stats_raw_en_word/logdir/valid.11.scp
+batch_type: folded
+valid_batch_type: null
+fold_length: []
+sort_in_batch: descending
+sort_batch: descending
+multiple_iterator: false
+chunk_length: 500
+chunk_shift_ratio: 0.5
+num_cache_chunks: 1024
+train_data_path_and_name_and_type:
+-   - dump/raw/train/wav.scp
+    - speech
+    - sound
+-   - dump/raw/train/text
+    - text
+    - text
+valid_data_path_and_name_and_type:
+-   - dump/raw/valid/wav.scp
+    - speech
+    - sound
+-   - dump/raw/valid/text
+    - text
+    - text
+allow_variable_data_keys: false
+max_cache_size: 0.0
+max_cache_fd: 32
+valid_max_cache_size: null
+optim: adam
+optim_conf:
+    lr: 0.0002
+scheduler: warmuplr
+scheduler_conf:
+    warmup_steps: 25000
+token_list:
+- <blank>
+- <unk>
+- <utt>
+- <sep>
+- bye
+- the
+- food
+- you
+- thank
+- thankyou
+- good
+- request-phone
+- number
+- phone
+- request-addr
+- address
+- restaurant
+- of
+- i
+- what
+- is
+- a
+- in
+- town
+- reqalts
+- part
+- inform-this-dontcare
+- for
+- and
+- looking
+- im
+- whats
+- about
+- inform-pricerange-moderate
+- dont
+- that
+- care
+- affirm
+- cheap
+- inform-pricerange-cheap
+- south
+- inform-area-south
+- how
+- serves
+- have
+- moderately
+- 'yes'
+- priced
+- expensive
+- north
+- any
+- inform-pricerange-expensive
+- can
+- request-postcode
+- anything
+- else
+- inform-area-north
+- code
+- post
+- it
+- price
+- west
+- inform-area-west
+- east
+- type
+- inform-area-east
+- range
+- there
+- request-food
+- okay
+- oriental
+- goodbye
+- european
+- request-pricerange
+- area
+- want
+- an
+- inform-food-indian
+- indian
+- matter
+- doesnt
+- uh
+- thai
+- serve
+- request-area
+- inform-food-thai
+- inform-food-asian
+- asian
+- chinese
+- like
+- inform-area-centre
+- find
+- inform-food-chinese
+- inform-food-italian
+- italian
+- negate
+- center
+- 'no'
+- moderate
+- please
+- get
+- to
+- their
+- inform-food-european
+- serving
+- may
+- inform-area-dontcare
+- do
+- korean
+- spanish
+- inform-food-spanish
+- vietnamese
+- inform-food-vietnamese
+- inform-food-korean
+- id
+- could
+- american
+- british
+- inform-food-british
+- kind
+- need
+- inform-food-turkish
+- turkish
+- um
+- inform-food-portuguese
+- gastropub
+- portuguese
+- does
+- inform-food-gastropub
+- inform-food-french
+- french
+- would
+- inform-food-mediterranean
+- mediterranean
+- they
+- modern
+- hello
+- inform-food-modern
+- noise
+- inform-pricerange-dontcare
+- its
+- inform-food-international
+- international
+- me
+- should
+- inform-food-north
+- repeat
+- right
+- give
+- inform-food-seafood
+- inform-food-japanese
+- japanese
+- jamaican
+- inform-food-jamaican
+- inform-food-creative
+- creative
+- are
+- inform-food-mexican
+- mexican
+- telephone
+- another
+- one
+- hungarian
+- ah
+- something
+- inform-food-dontcare
+- inform-food-cantonese
+- cantonese
+- inform-food-cuban
+- cuban
+- inform-food-hungarian
+- hi
+- breath
+- sea
+- yea
+- am
+- inform-food-traditional
+- traditional
+- caribbean
+- restaurants
+- ack
+- inform-food-world
+- world
+- with
+- inform-food-caribbean
+- barbecue
+- inform-food-corsica
+- corsica
+- inform-food-lebanese
+- lebanese
+- be
+- inform-food-basque
+- postcode
+- inform-food-romanian
+- romanian
+- inform-food-greek
+- greek
+- inform-food-barbeque
+- inform-food-african
+- african
+- side
+- other
+- pan
+- inform-food-english
+- english
+- inform-food-danish
+- danish
+- venue
+- inform-food-malaysian
+- australian
+- inform-food-unusual
+- unusual
+- inform-food-moroccan
+- inform-food-kosher
+- kosher
+- thats
+- inform-food-scandinavian
+- inform-food-afghan
+- afghan
+- inform-food-polynesian
+- polynesian
+- bout
+- inform-food-german
+- german
+- not
+- inform-food-vegetarian
+- inform-food-persian
+- persian
+- scandinavian
+- basque
+- inform-food-belgian
+- malaysian
+- inform-food-australian
+- moroccan
+- christmas
+- inform-food-catalan
+- inform-food-canapes
+- vegetarian
+- 'on'
+- swedish
+- inform-food-irish
+- irish
+- canapes
+- inform-food-christmas
+- catalan
+- inform-food-venetian
+- inform-food-swedish
+- where
+- inform-food-tuscan
+- tuscan
+- inform-food-eritrean
+- venetian
+- inform-food-steakhouse
+- fusion
+- unintelligible
+- inform-food-bistro
+- bistro
+- yeah
+- alright
+- inform-food-swiss
+- swiss
+- inform-food-singaporean
+- seafood
+- know
+- confirm-pricerange-expensive
+- confirm-pricerange-moderate
+- next
+- oh
+- inform-food-brazilian
+- brazilian
+- inform-food-scottish
+- scottish
+- inform-food-fusion
+- inform-food-russian
+- russian
+- singaporean
+- kay
+- fine
+- inform-food-welsh
+- welsh
+- over
+- belgium
+- belgian
+- great
+- addre
+- inform-food-crossover
+- cool
+- steakhouse
+- confirm-food-chinese
+- inform-food-austrian
+- austrian
+- inform-food-polish
+- polish
+- again
+- centre
+- then
+- ok
+- halal
+- steak
+- back
+- thanks
+- inform-food-indonesian
+- indonesian
+- correct
+- well
+- confirm-area-centre
+- confirm-area-north
+- inform-food-halal
+- see
+- welcome
+- house
+- postal
+- pri
+- more
+- anywhere
+- central
+- crossover
+- much
+- very
+- located
+- my
+- confirm-pricerange-cheap
+- restart
+- start
+- go
+- just
+- iam
+- confirm-food-thai
+- confirm-food-korean
+- city
+- as
+- wok
+- option
+- was
+- two
+- your
+- confirm-food-gastropub
+- time
+- chiquito
+- inform-name-prezzo
+- prezzo
+- fuck
+- prices
+- reqmore
+- bask
+- different
+- cambridge
+- turkiesh
+- show
+- chineese
+- confirm-area-east
+- rest
+- request-name
+- name
+- try
+- sorry
+- foo
+- ye
+- ser
+- sells
+- change
+- confirm-food-hungarian
+- eritrean
+- but
+- eartrain
+- options
+- location
+- served
+- cross
+- k
+- inform-name-chiquito
+- bar
+- tv_noise
+- confirm-food-canapes
+- day
+- parts
+- malyasian
+- airitran
+- so
+- new
+- at
+- confirm-food-indian
+- confirm-food-portuguese
+- place
+- tell
+- though
+- choice
+- awesome
+- stop
+- inform-food-australasian
+- portugese
+- missing
+- sock
+- deny-name-golden
+- golden
+- park
+- tur
+- vinci
+- pizzeria
+- endonesian
+- needs
+- deny-food-korean
+- confirm-area-west
+- t
+- trying
+- dear
+- thatll
+- excellent
+- baskaye
+- confirm-food-basque
+- p
+- if
+- india
+- some
+- ran
+- moroccon
+- confirm-food-european
+- hut
+- all
+- airatarin
+- canope
+- tailand
+- vanessa
+- earatrain
+- shit
+- ts
+- confirm-food-steakhouse
+- cantonates
+- vegitarian
+- knocking
+- signaporian
+- mail
+- foods
+- got
+- us
+- lets
+- f
+- medium
+- un
+- downtown
+- portugeuse
+- venues
+- talking
+- nymber
+- every
+- this
+- moron
+- says
+- sucks
+- itailian
+- chinses
+- elses
+- request-signature
+- special
+- restaurnt
+- confirm-food-fusion
+- spensive
+- scandinavia
+- gastro
+- pub
+- anyone
+- deny-food-chinese
+- res
+- derately
+- down
+- fancy
+- wha
+- alternative
+- confirm-food-mediterranean
+- confirm-food-caribbean
+- first
+- least
+- bart
+- selection
+- finally
+- somewhere
+- ko
+- sounds
+- said
+- eat
+- huh
+- searching
+- s
+- wrong
+- cute
+- ffood
+- earetree
+- earatree
+- confirm-food-modern
+- confirm-food-christmas
+- long
+- class
+- restauran
+- turk
+- deny-name-the
+- beside
+- yourself
+- hate
+- signaporean
+- restuarant
+- did
+- inform-name-da
+- da
+- only
+- int
+- inform-name-bloomsbury
+- bloomsbury
+- inaudible
+- scandanavian
+- done
+- confirm-food-indonesian
+- cancun
+- gasper
+- o
+- meant
+- plea
+- halo
+- inner
+- confirm-food-swedish
+- confirm-food-asian
+- wanna
+- catalanian
+- darling
+- canape
+- baskey
+- indians
+- bat
+- europ
+- now
+- canopy
+- restaraunt
+- medterranean
+- cant
+- deosnt
+- ostro
+- addrss
+- damn
+- deny-name-hk
+- hk
+- signapore
+- probably
+- ly
+- moderat
+- modereate
+- let
+- zip
+- spani
+- adddress
+- ori
+- euorpean
+- confirm-food-seafood
+- mistakes
+- ooh
+- confirm-food-spanish
+- worth
+- mediteranian
+- music
+- others
+- b
+- types
+- thing
+- fish
+- besides
+- confirm-food-halal
+- inform-name-pizza
+- pizza
+- ever
+- surprise
+- ones
+- train
+- arotrian
+- modertley
+- calling
+- minuet
+- york
+- sh
+- cost
+- confirm-area-south
+- bristish
+- confirm-food-british
+- loo
+- think
+- medetanian
+- wheres
+- his
+- confirm-food-turkish
+- inform-name-restaurant
+- euro
+- wondering
+- theres
+- afternoon
+- sure
+- might
+- umh
+- deny-food-vietnamese
+- art
+- rerestaurant
+- vietna
+- ne
+- take
+- modreately
+- air
+- tran
+- crosstalk
+- mind
+- ya
+- god
+- really
+- believe
+- confirm-food-italian
+- confirm-food-jamaican
+- preference
+- <sos/eos>
+init: null
+input_size: null
+ctc_conf:
+    dropout_rate: 0.0
+    ctc_type: builtin
+    reduce: true
+    ignore_nan_grad: true
+model_conf:
+    ctc_weight: 0.5
+    ignore_id: -1
+    lsm_weight: 0.0
+    length_normalized_loss: false
+    report_cer: true
+    report_wer: true
+    sym_space: <space>
+    sym_blank: <blank>
+    extract_feats_in_collect_stats: true
+use_preprocessor: true
+token_type: word
+bpemodel: null
+non_linguistic_symbols: null
+cleaner: null
+g2p: null
+speech_volume_normalize: null
+rir_scp: null
+rir_apply_prob: 1.0
+noise_scp: null
+noise_apply_prob: 1.0
+noise_db_range: '13_15'
+frontend: default
+frontend_conf:
+    fs: 16k
+specaug: specaug
+specaug_conf:
+    apply_time_warp: true
+    time_warp_window: 5
+    time_warp_mode: bicubic
+    apply_freq_mask: true
+    freq_mask_width_range:
+    - 0
+    - 30
+    num_freq_mask: 2
+    apply_time_mask: true
+    time_mask_width_range:
+    - 0
+    - 40
+    num_time_mask: 2
+normalize: utterance_mvn
+normalize_conf: {}
+preencoder: null
+preencoder_conf: {}
+encoder: transformer
+encoder_conf:
+    output_size: 256
+    attention_heads: 4
+    linear_units: 2048
+    num_blocks: 12
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    attention_dropout_rate: 0.0
+    input_layer: conv2d
+    normalize_before: true
+postencoder: null
+postencoder_conf: {}
+decoder: transformer
+decoder_conf:
+    attention_heads: 4
+    linear_units: 2048
+    num_blocks: 6
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    self_attention_dropout_rate: 0.0
+    src_attention_dropout_rate: 0.0
+required:
+- output_dir
+- token_list
+version: 0.10.3a3
+distributed: false

exp/asr_stats_raw_en_word/logdir/stats.11/train/batch_keys

@@ -0,0 +1,2 @@
+speech
+text

exp/asr_stats_raw_en_word/logdir/stats.11/train/speech_shape

@@ -0,0 +1,340 @@
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exp/asr_stats_raw_en_word/logdir/stats.12.log

@@ -0,0 +1,495 @@
+# Running on r248.ib.bridges2.psc.edu
+# Started at Mon Jan 31 02:19:48 EST 2022
+# SLURMD_NODENAME=r248
+# SLURM_ARRAY_JOB_ID=6473470
+# SLURM_ARRAY_TASK_COUNT=32
+# SLURM_ARRAY_TASK_ID=12
+# SLURM_ARRAY_TASK_MAX=32
+# SLURM_ARRAY_TASK_MIN=1
+# SLURM_ARRAY_TASK_STEP=1
+# SLURM_CLUSTER_NAME=bridges2
+# SLURM_CONF=/var/spool/slurm/d/conf-cache/slurm.conf
+# SLURM_CPUS_ON_NODE=1
+# SLURM_EXPORT_ENV=PATH
+# SLURM_GET_USER_ENV=1
+# SLURM_GTIDS=0
+# SLURM_JOBID=6473483
+# SLURM_JOB_ACCOUNT=cis210027p
+# SLURM_JOB_CPUS_PER_NODE=1
+# SLURM_JOB_GID=24886
+# SLURM_JOB_ID=6473483
+# SLURM_JOB_NAME=stats.sh
+# SLURM_JOB_NODELIST=r248
+# SLURM_JOB_NUM_NODES=1
+# SLURM_JOB_PARTITION=RM-shared
+# SLURM_JOB_QOS=rm
+# SLURM_JOB_UID=82326
+# SLURM_JOB_USER=ganesank
+# SLURM_LOCALID=0
+# SLURM_MEM_PER_CPU=2000
+# SLURM_NNODES=1
+# SLURM_NODEID=0
+# SLURM_NODELIST=r248
+# SLURM_NODE_ALIASES='(null)'
+# SLURM_OPEN_MODE=a
+# SLURM_PRIO_PROCESS=0
+# SLURM_PROCID=0
+# SLURM_SUBMIT_DIR=/ocean/projects/cis210027p/ganesank/karthik_new/espnet/egs2/dstc2/asr2
+# SLURM_SUBMIT_HOST=br012.ib.bridges2.psc.edu
+# SLURM_TASKS_PER_NODE=1
+# SLURM_TASK_PID=95132
+# SLURM_TOPOLOGY_ADDR=r248
+# SLURM_TOPOLOGY_ADDR_PATTERN=node
+# SLURM_WORKING_CLUSTER=bridges2:br003:6814:9216:109
+# python3 -m espnet2.bin.asr_train --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.12.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.12.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.12 --config conf/train_asr.yaml --frontend_conf fs=16k 
+/ocean/projects/cis210027p/ganesank/karthik_new/espnet/tools/venv/bin/python3 /ocean/projects/cis210027p/ganesank/karthik_new/espnet/espnet2/bin/asr_train.py --collect_stats true --use_preprocessor true --bpemodel none --token_type word --token_list data/en_token_list/word/tokens.txt --non_linguistic_symbols none --cleaner none --g2p none --train_data_path_and_name_and_type dump/raw/train/wav.scp,speech,sound --train_data_path_and_name_and_type dump/raw/train/text,text,text --valid_data_path_and_name_and_type dump/raw/valid/wav.scp,speech,sound --valid_data_path_and_name_and_type dump/raw/valid/text,text,text --train_shape_file exp/asr_stats_raw_en_word/logdir/train.12.scp --valid_shape_file exp/asr_stats_raw_en_word/logdir/valid.12.scp --output_dir exp/asr_stats_raw_en_word/logdir/stats.12 --config conf/train_asr.yaml --frontend_conf fs=16k
+[r248] 2022-01-31 02:20:59,181 (asr:382) INFO: Vocabulary size: 613
+[r248] 2022-01-31 02:21:00,050 (abs_task:1132) INFO: pytorch.version=1.8.1+cu102, cuda.available=False, cudnn.version=7605, cudnn.benchmark=False, cudnn.deterministic=True
+[r248] 2022-01-31 02:21:00,056 (abs_task:1133) INFO: Model structure:
+ESPnetASRModel(
+  (frontend): DefaultFrontend(
+    (stft): Stft(n_fft=512, win_length=512, hop_length=128, 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)
+  )
+  (specaug): SpecAug(
+    (time_warp): TimeWarp(window=5, mode=bicubic)
+    (freq_mask): MaskAlongAxis(mask_width_range=[0, 30], num_mask=2, axis=freq)
+    (time_mask): MaskAlongAxis(mask_width_range=[0, 40], num_mask=2, axis=time)
+  )
+  (normalize): UtteranceMVN(norm_means=True, norm_vars=False)
+  (encoder): TransformerEncoder(
+    (embed): Conv2dSubsampling(
+      (conv): Sequential(
+        (0): Conv2d(1, 256, kernel_size=(3, 3), stride=(2, 2))
+        (1): ReLU()
+        (2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2))
+        (3): ReLU()
+      )
+      (out): Sequential(
+        (0): Linear(in_features=4864, out_features=256, bias=True)
+        (1): PositionalEncoding(
+          (dropout): Dropout(p=0.1, inplace=False)
+        )
+      )
+    )
+    (encoders): MultiSequential(
+      (0): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (1): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (2): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (3): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (4): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (5): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (6): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (7): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (8): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (9): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (10): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (11): EncoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (after_norm): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+  )
+  (decoder): TransformerDecoder(
+    (embed): Sequential(
+      (0): Embedding(613, 256)
+      (1): PositionalEncoding(
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+    (after_norm): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+    (output_layer): Linear(in_features=256, out_features=613, bias=True)
+    (decoders): MultiSequential(
+      (0): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (1): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (2): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (3): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (4): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+      (5): DecoderLayer(
+        (self_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (src_attn): MultiHeadedAttention(
+          (linear_q): Linear(in_features=256, out_features=256, bias=True)
+          (linear_k): Linear(in_features=256, out_features=256, bias=True)
+          (linear_v): Linear(in_features=256, out_features=256, bias=True)
+          (linear_out): Linear(in_features=256, out_features=256, bias=True)
+          (dropout): Dropout(p=0.0, inplace=False)
+        )
+        (feed_forward): PositionwiseFeedForward(
+          (w_1): Linear(in_features=256, out_features=2048, bias=True)
+          (w_2): Linear(in_features=2048, out_features=256, bias=True)
+          (dropout): Dropout(p=0.1, inplace=False)
+          (activation): ReLU()
+        )
+        (norm1): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm2): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (norm3): LayerNorm((256,), eps=1e-12, elementwise_affine=True)
+        (dropout): Dropout(p=0.1, inplace=False)
+      )
+    )
+  )
+  (ctc): CTC(
+    (ctc_lo): Linear(in_features=256, out_features=613, bias=True)
+    (ctc_loss): CTCLoss()
+  )
+  (criterion_att): LabelSmoothingLoss(
+    (criterion): KLDivLoss()
+  )
+)
+
+Model summary:
+    Class Name: ESPnetASRModel
+    Total Number of model parameters: 27.56 M
+    Number of trainable parameters: 27.56 M (100.0%)
+    Size: 110.26 MB
+    Type: torch.float32
+[r248] 2022-01-31 02:21:00,057 (abs_task:1136) INFO: Optimizer:
+Adam (
+Parameter Group 0
+    amsgrad: False
+    betas: (0.9, 0.999)
+    eps: 1e-08
+    initial_lr: 0.0002
+    lr: 8e-09
+    weight_decay: 0
+)
+[r248] 2022-01-31 02:21:00,057 (abs_task:1137) INFO: Scheduler: WarmupLR(warmup_steps=25000)
+[r248] 2022-01-31 02:21:00,058 (abs_task:1146) INFO: Saving the configuration in exp/asr_stats_raw_en_word/logdir/stats.12/config.yaml
+[r248] 2022-01-31 02:21:00,085 (abs_task:1157) INFO: Namespace(config='conf/train_asr.yaml', print_config=False, log_level='INFO', dry_run=False, iterator_type='sequence', output_dir='exp/asr_stats_raw_en_word/logdir/stats.12', ngpu=0, seed=0, num_workers=1, num_att_plot=3, dist_backend='nccl', dist_init_method='env://', dist_world_size=None, dist_rank=None, local_rank=None, dist_master_addr=None, dist_master_port=None, dist_launcher=None, multiprocessing_distributed=False, unused_parameters=False, sharded_ddp=False, cudnn_enabled=True, cudnn_benchmark=False, cudnn_deterministic=True, collect_stats=True, write_collected_feats=False, max_epoch=20, patience=None, val_scheduler_criterion=('valid', 'loss'), early_stopping_criterion=('valid', 'loss', 'min'), best_model_criterion=[('train', 'loss', 'min'), ('valid', 'loss', 'min'), ('train', 'acc', 'max'), ('valid', 'acc', 'max')], keep_nbest_models=5, grad_clip=5.0, grad_clip_type=2.0, grad_noise=False, accum_grad=1, no_forward_run=False, resume=False, train_dtype='float32', use_amp=False, log_interval=None, use_tensorboard=True, use_wandb=False, wandb_project=None, wandb_id=None, wandb_entity=None, wandb_name=None, wandb_model_log_interval=-1, detect_anomaly=False, pretrain_path=None, init_param=[], ignore_init_mismatch=False, freeze_param=[], num_iters_per_epoch=None, batch_size=20, valid_batch_size=None, batch_bins=1000000, valid_batch_bins=None, train_shape_file=['exp/asr_stats_raw_en_word/logdir/train.12.scp'], valid_shape_file=['exp/asr_stats_raw_en_word/logdir/valid.12.scp'], batch_type='folded', valid_batch_type=None, fold_length=[], sort_in_batch='descending', sort_batch='descending', multiple_iterator=False, chunk_length=500, chunk_shift_ratio=0.5, num_cache_chunks=1024, train_data_path_and_name_and_type=[('dump/raw/train/wav.scp', 'speech', 'sound'), ('dump/raw/train/text', 'text', 'text')], valid_data_path_and_name_and_type=[('dump/raw/valid/wav.scp', 'speech', 'sound'), ('dump/raw/valid/text', 'text', 'text')], allow_variable_data_keys=False, max_cache_size=0.0, max_cache_fd=32, valid_max_cache_size=None, optim='adam', optim_conf={'lr': 0.0002}, scheduler='warmuplr', scheduler_conf={'warmup_steps': 25000}, token_list=['<blank>', '<unk>', '<utt>', '<sep>', 'bye', 'the', 'food', 'you', 'thank', 'thankyou', 'good', 'request-phone', 'number', 'phone', 'request-addr', 'address', 'restaurant', 'of', 'i', 'what', 'is', 'a', 'in', 'town', 'reqalts', 'part', 'inform-this-dontcare', 'for', 'and', 'looking', 'im', 'whats', 'about', 'inform-pricerange-moderate', 'dont', 'that', 'care', 'affirm', 'cheap', 'inform-pricerange-cheap', 'south', 'inform-area-south', 'how', 'serves', 'have', 'moderately', 'yes', 'priced', 'expensive', 'north', 'any', 'inform-pricerange-expensive', 'can', 'request-postcode', 'anything', 'else', 'inform-area-north', 'code', 'post', 'it', 'price', 'west', 'inform-area-west', 'east', 'type', 'inform-area-east', 'range', 'there', 'request-food', 'okay', 'oriental', 'goodbye', 'european', 'request-pricerange', 'area', 'want', 'an', 'inform-food-indian', 'indian', 'matter', 'doesnt', 'uh', 'thai', 'serve', 'request-area', 'inform-food-thai', 'inform-food-asian', 'asian', 'chinese', 'like', 'inform-area-centre', 'find', 'inform-food-chinese', 'inform-food-italian', 'italian', 'negate', 'center', 'no', 'moderate', 'please', 'get', 'to', 'their', 'inform-food-european', 'serving', 'may', 'inform-area-dontcare', 'do', 'korean', 'spanish', 'inform-food-spanish', 'vietnamese', 'inform-food-vietnamese', 'inform-food-korean', 'id', 'could', 'american', 'british', 'inform-food-british', 'kind', 'need', 'inform-food-turkish', 'turkish', 'um', 'inform-food-portuguese', 'gastropub', 'portuguese', 'does', 'inform-food-gastropub', 'inform-food-french', 'french', 'would', 'inform-food-mediterranean', 'mediterranean', 'they', 'modern', 'hello', 'inform-food-modern', 'noise', 'inform-pricerange-dontcare', 'its', 'inform-food-international', 'international', 'me', 'should', 'inform-food-north', 'repeat', 'right', 'give', 'inform-food-seafood', 'inform-food-japanese', 'japanese', 'jamaican', 'inform-food-jamaican', 'inform-food-creative', 'creative', 'are', 'inform-food-mexican', 'mexican', 'telephone', 'another', 'one', 'hungarian', 'ah', 'something', 'inform-food-dontcare', 'inform-food-cantonese', 'cantonese', 'inform-food-cuban', 'cuban', 'inform-food-hungarian', 'hi', 'breath', 'sea', 'yea', 'am', 'inform-food-traditional', 'traditional', 'caribbean', 'restaurants', 'ack', 'inform-food-world', 'world', 'with', 'inform-food-caribbean', 'barbecue', 'inform-food-corsica', 'corsica', 'inform-food-lebanese', 'lebanese', 'be', 'inform-food-basque', 'postcode', 'inform-food-romanian', 'romanian', 'inform-food-greek', 'greek', 'inform-food-barbeque', 'inform-food-african', 'african', 'side', 'other', 'pan', 'inform-food-english', 'english', 'inform-food-danish', 'danish', 'venue', 'inform-food-malaysian', 'australian', 'inform-food-unusual', 'unusual', 'inform-food-moroccan', 'inform-food-kosher', 'kosher', 'thats', 'inform-food-scandinavian', 'inform-food-afghan', 'afghan', 'inform-food-polynesian', 'polynesian', 'bout', 'inform-food-german', 'german', 'not', 'inform-food-vegetarian', 'inform-food-persian', 'persian', 'scandinavian', 'basque', 'inform-food-belgian', 'malaysian', 'inform-food-australian', 'moroccan', 'christmas', 'inform-food-catalan', 'inform-food-canapes', 'vegetarian', 'on', 'swedish', 'inform-food-irish', 'irish', 'canapes', 'inform-food-christmas', 'catalan', 'inform-food-venetian', 'inform-food-swedish', 'where', 'inform-food-tuscan', 'tuscan', 'inform-food-eritrean', 'venetian', 'inform-food-steakhouse', 'fusion', 'unintelligible', 'inform-food-bistro', 'bistro', 'yeah', 'alright', 'inform-food-swiss', 'swiss', 'inform-food-singaporean', 'seafood', 'know', 'confirm-pricerange-expensive', 'confirm-pricerange-moderate', 'next', 'oh', 'inform-food-brazilian', 'brazilian', 'inform-food-scottish', 'scottish', 'inform-food-fusion', 'inform-food-russian', 'russian', 'singaporean', 'kay', 'fine', 'inform-food-welsh', 'welsh', 'over', 'belgium', 'belgian', 'great', 'addre', 'inform-food-crossover', 'cool', 'steakhouse', 'confirm-food-chinese', 'inform-food-austrian', 'austrian', 'inform-food-polish', 'polish', 'again', 'centre', 'then', 'ok', 'halal', 'steak', 'back', 'thanks', 'inform-food-indonesian', 'indonesian', 'correct', 'well', 'confirm-area-centre', 'confirm-area-north', 'inform-food-halal', 'see', 'welcome', 'house', 'postal', 'pri', 'more', 'anywhere', 'central', 'crossover', 'much', 'very', 'located', 'my', 'confirm-pricerange-cheap', 'restart', 'start', 'go', 'just', 'iam', 'confirm-food-thai', 'confirm-food-korean', 'city', 'as', 'wok', 'option', 'was', 'two', 'your', 'confirm-food-gastropub', 'time', 'chiquito', 'inform-name-prezzo', 'prezzo', 'fuck', 'prices', 'reqmore', 'bask', 'different', 'cambridge', 'turkiesh', 'show', 'chineese', 'confirm-area-east', 'rest', 'request-name', 'name', 'try', 'sorry', 'foo', 'ye', 'ser', 'sells', 'change', 'confirm-food-hungarian', 'eritrean', 'but', 'eartrain', 'options', 'location', 'served', 'cross', 'k', 'inform-name-chiquito', 'bar', 'tv_noise', 'confirm-food-canapes', 'day', 'parts', 'malyasian', 'airitran', 'so', 'new', 'at', 'confirm-food-indian', 'confirm-food-portuguese', 'place', 'tell', 'though', 'choice', 'awesome', 'stop', 'inform-food-australasian', 'portugese', 'missing', 'sock', 'deny-name-golden', 'golden', 'park', 'tur', 'vinci', 'pizzeria', 'endonesian', 'needs', 'deny-food-korean', 'confirm-area-west', 't', 'trying', 'dear', 'thatll', 'excellent', 'baskaye', 'confirm-food-basque', 'p', 'if', 'india', 'some', 'ran', 'moroccon', 'confirm-food-european', 'hut', 'all', 'airatarin', 'canope', 'tailand', 'vanessa', 'earatrain', 'shit', 'ts', 'confirm-food-steakhouse', 'cantonates', 'vegitarian', 'knocking', 'signaporian', 'mail', 'foods', 'got', 'us', 'lets', 'f', 'medium', 'un', 'downtown', 'portugeuse', 'venues', 'talking', 'nymber', 'every', 'this', 'moron', 'says', 'sucks', 'itailian', 'chinses', 'elses', 'request-signature', 'special', 'restaurnt', 'confirm-food-fusion', 'spensive', 'scandinavia', 'gastro', 'pub', 'anyone', 'deny-food-chinese', 'res', 'derately', 'down', 'fancy', 'wha', 'alternative', 'confirm-food-mediterranean', 'confirm-food-caribbean', 'first', 'least', 'bart', 'selection', 'finally', 'somewhere', 'ko', 'sounds', 'said', 'eat', 'huh', 'searching', 's', 'wrong', 'cute', 'ffood', 'earetree', 'earatree', 'confirm-food-modern', 'confirm-food-christmas', 'long', 'class', 'restauran', 'turk', 'deny-name-the', 'beside', 'yourself', 'hate', 'signaporean', 'restuarant', 'did', 'inform-name-da', 'da', 'only', 'int', 'inform-name-bloomsbury', 'bloomsbury', 'inaudible', 'scandanavian', 'done', 'confirm-food-indonesian', 'cancun', 'gasper', 'o', 'meant', 'plea', 'halo', 'inner', 'confirm-food-swedish', 'confirm-food-asian', 'wanna', 'catalanian', 'darling', 'canape', 'baskey', 'indians', 'bat', 'europ', 'now', 'canopy', 'restaraunt', 'medterranean', 'cant', 'deosnt', 'ostro', 'addrss', 'damn', 'deny-name-hk', 'hk', 'signapore', 'probably', 'ly', 'moderat', 'modereate', 'let', 'zip', 'spani', 'adddress', 'ori', 'euorpean', 'confirm-food-seafood', 'mistakes', 'ooh', 'confirm-food-spanish', 'worth', 'mediteranian', 'music', 'others', 'b', 'types', 'thing', 'fish', 'besides', 'confirm-food-halal', 'inform-name-pizza', 'pizza', 'ever', 'surprise', 'ones', 'train', 'arotrian', 'modertley', 'calling', 'minuet', 'york', 'sh', 'cost', 'confirm-area-south', 'bristish', 'confirm-food-british', 'loo', 'think', 'medetanian', 'wheres', 'his', 'confirm-food-turkish', 'inform-name-restaurant', 'euro', 'wondering', 'theres', 'afternoon', 'sure', 'might', 'umh', 'deny-food-vietnamese', 'art', 'rerestaurant', 'vietna', 'ne', 'take', 'modreately', 'air', 'tran', 'crosstalk', 'mind', 'ya', 'god', 'really', 'believe', 'confirm-food-italian', 'confirm-food-jamaican', 'preference', '<sos/eos>'], init=None, input_size=None, ctc_conf={'dropout_rate': 0.0, 'ctc_type': 'builtin', 'reduce': True, 'ignore_nan_grad': True}, model_conf={'ctc_weight': 0.5, 'ignore_id': -1, 'lsm_weight': 0.0, 'length_normalized_loss': False, 'report_cer': True, 'report_wer': True, 'sym_space': '<space>', 'sym_blank': '<blank>', 'extract_feats_in_collect_stats': True}, use_preprocessor=True, token_type='word', bpemodel=None, non_linguistic_symbols=None, cleaner=None, g2p=None, speech_volume_normalize=None, rir_scp=None, rir_apply_prob=1.0, noise_scp=None, noise_apply_prob=1.0, noise_db_range='13_15', frontend='default', frontend_conf={'fs': '16k'}, specaug='specaug', specaug_conf={'apply_time_warp': True, 'time_warp_window': 5, 'time_warp_mode': 'bicubic', 'apply_freq_mask': True, 'freq_mask_width_range': [0, 30], 'num_freq_mask': 2, 'apply_time_mask': True, 'time_mask_width_range': [0, 40], 'num_time_mask': 2}, normalize='utterance_mvn', normalize_conf={}, preencoder=None, preencoder_conf={}, encoder='transformer', encoder_conf={'output_size': 256, 'attention_heads': 4, 'linear_units': 2048, 'num_blocks': 12, 'dropout_rate': 0.1, 'positional_dropout_rate': 0.1, 'attention_dropout_rate': 0.0, 'input_layer': 'conv2d', 'normalize_before': True}, postencoder=None, postencoder_conf={}, decoder='transformer', decoder_conf={'attention_heads': 4, 'linear_units': 2048, 'num_blocks': 6, 'dropout_rate': 0.1, 'positional_dropout_rate': 0.1, 'self_attention_dropout_rate': 0.0, 'src_attention_dropout_rate': 0.0}, required=['output_dir', 'token_list'], version='0.10.3a3', distributed=False)
+# Accounting: begin_time=1643613588
+# Accounting: end_time=1643613668
+# Accounting: time=80 threads=1
+# Finished at Mon Jan 31 02:21:08 EST 2022 with status 0

exp/asr_stats_raw_en_word/logdir/stats.12/config.yaml

@@ -0,0 +1,804 @@
+config: conf/train_asr.yaml
+print_config: false
+log_level: INFO
+dry_run: false
+iterator_type: sequence
+output_dir: exp/asr_stats_raw_en_word/logdir/stats.12
+ngpu: 0
+seed: 0
+num_workers: 1
+num_att_plot: 3
+dist_backend: nccl
+dist_init_method: env://
+dist_world_size: null
+dist_rank: null
+local_rank: null
+dist_master_addr: null
+dist_master_port: null
+dist_launcher: null
+multiprocessing_distributed: false
+unused_parameters: false
+sharded_ddp: false
+cudnn_enabled: true
+cudnn_benchmark: false
+cudnn_deterministic: true
+collect_stats: true
+write_collected_feats: false
+max_epoch: 20
+patience: null
+val_scheduler_criterion:
+- valid
+- loss
+early_stopping_criterion:
+- valid
+- loss
+- min
+best_model_criterion:
+-   - train
+    - loss
+    - min
+-   - valid
+    - loss
+    - min
+-   - train
+    - acc
+    - max
+-   - valid
+    - acc
+    - max
+keep_nbest_models: 5
+grad_clip: 5.0
+grad_clip_type: 2.0
+grad_noise: false
+accum_grad: 1
+no_forward_run: false
+resume: false
+train_dtype: float32
+use_amp: false
+log_interval: null
+use_tensorboard: true
+use_wandb: false
+wandb_project: null
+wandb_id: null
+wandb_entity: null
+wandb_name: null
+wandb_model_log_interval: -1
+detect_anomaly: false
+pretrain_path: null
+init_param: []
+ignore_init_mismatch: false
+freeze_param: []
+num_iters_per_epoch: null
+batch_size: 20
+valid_batch_size: null
+batch_bins: 1000000
+valid_batch_bins: null
+train_shape_file:
+- exp/asr_stats_raw_en_word/logdir/train.12.scp
+valid_shape_file:
+- exp/asr_stats_raw_en_word/logdir/valid.12.scp
+batch_type: folded
+valid_batch_type: null
+fold_length: []
+sort_in_batch: descending
+sort_batch: descending
+multiple_iterator: false
+chunk_length: 500
+chunk_shift_ratio: 0.5
+num_cache_chunks: 1024
+train_data_path_and_name_and_type:
+-   - dump/raw/train/wav.scp
+    - speech
+    - sound
+-   - dump/raw/train/text
+    - text
+    - text
+valid_data_path_and_name_and_type:
+-   - dump/raw/valid/wav.scp
+    - speech
+    - sound
+-   - dump/raw/valid/text
+    - text
+    - text
+allow_variable_data_keys: false
+max_cache_size: 0.0
+max_cache_fd: 32
+valid_max_cache_size: null
+optim: adam
+optim_conf:
+    lr: 0.0002
+scheduler: warmuplr
+scheduler_conf:
+    warmup_steps: 25000
+token_list:
+- <blank>
+- <unk>
+- <utt>
+- <sep>
+- bye
+- the
+- food
+- you
+- thank
+- thankyou
+- good
+- request-phone
+- number
+- phone
+- request-addr
+- address
+- restaurant
+- of
+- i
+- what
+- is
+- a
+- in
+- town
+- reqalts
+- part
+- inform-this-dontcare
+- for
+- and
+- looking
+- im
+- whats
+- about
+- inform-pricerange-moderate
+- dont
+- that
+- care
+- affirm
+- cheap
+- inform-pricerange-cheap
+- south
+- inform-area-south
+- how
+- serves
+- have
+- moderately
+- 'yes'
+- priced
+- expensive
+- north
+- any
+- inform-pricerange-expensive
+- can
+- request-postcode
+- anything
+- else
+- inform-area-north
+- code
+- post
+- it
+- price
+- west
+- inform-area-west
+- east
+- type
+- inform-area-east
+- range
+- there
+- request-food
+- okay
+- oriental
+- goodbye
+- european
+- request-pricerange
+- area
+- want
+- an
+- inform-food-indian
+- indian
+- matter
+- doesnt
+- uh
+- thai
+- serve
+- request-area
+- inform-food-thai
+- inform-food-asian
+- asian
+- chinese
+- like
+- inform-area-centre
+- find
+- inform-food-chinese
+- inform-food-italian
+- italian
+- negate
+- center
+- 'no'
+- moderate
+- please
+- get
+- to
+- their
+- inform-food-european
+- serving
+- may
+- inform-area-dontcare
+- do
+- korean
+- spanish
+- inform-food-spanish
+- vietnamese
+- inform-food-vietnamese
+- inform-food-korean
+- id
+- could
+- american
+- british
+- inform-food-british
+- kind
+- need
+- inform-food-turkish
+- turkish
+- um
+- inform-food-portuguese
+- gastropub
+- portuguese
+- does
+- inform-food-gastropub
+- inform-food-french
+- french
+- would
+- inform-food-mediterranean
+- mediterranean
+- they
+- modern
+- hello
+- inform-food-modern
+- noise
+- inform-pricerange-dontcare
+- its
+- inform-food-international
+- international
+- me
+- should
+- inform-food-north
+- repeat
+- right
+- give
+- inform-food-seafood
+- inform-food-japanese
+- japanese
+- jamaican
+- inform-food-jamaican
+- inform-food-creative
+- creative
+- are
+- inform-food-mexican
+- mexican
+- telephone
+- another
+- one
+- hungarian
+- ah
+- something
+- inform-food-dontcare
+- inform-food-cantonese
+- cantonese
+- inform-food-cuban
+- cuban
+- inform-food-hungarian
+- hi
+- breath
+- sea
+- yea
+- am
+- inform-food-traditional
+- traditional
+- caribbean
+- restaurants
+- ack
+- inform-food-world
+- world
+- with
+- inform-food-caribbean
+- barbecue
+- inform-food-corsica
+- corsica
+- inform-food-lebanese
+- lebanese
+- be
+- inform-food-basque
+- postcode
+- inform-food-romanian
+- romanian
+- inform-food-greek
+- greek
+- inform-food-barbeque
+- inform-food-african
+- african
+- side
+- other
+- pan
+- inform-food-english
+- english
+- inform-food-danish
+- danish
+- venue
+- inform-food-malaysian
+- australian
+- inform-food-unusual
+- unusual
+- inform-food-moroccan
+- inform-food-kosher
+- kosher
+- thats
+- inform-food-scandinavian
+- inform-food-afghan
+- afghan
+- inform-food-polynesian
+- polynesian
+- bout
+- inform-food-german
+- german
+- not
+- inform-food-vegetarian
+- inform-food-persian
+- persian
+- scandinavian
+- basque
+- inform-food-belgian
+- malaysian
+- inform-food-australian
+- moroccan
+- christmas
+- inform-food-catalan
+- inform-food-canapes
+- vegetarian
+- 'on'
+- swedish
+- inform-food-irish
+- irish
+- canapes
+- inform-food-christmas
+- catalan
+- inform-food-venetian
+- inform-food-swedish
+- where
+- inform-food-tuscan
+- tuscan
+- inform-food-eritrean
+- venetian
+- inform-food-steakhouse
+- fusion
+- unintelligible
+- inform-food-bistro
+- bistro
+- yeah
+- alright
+- inform-food-swiss
+- swiss
+- inform-food-singaporean
+- seafood
+- know
+- confirm-pricerange-expensive
+- confirm-pricerange-moderate
+- next
+- oh
+- inform-food-brazilian
+- brazilian
+- inform-food-scottish
+- scottish
+- inform-food-fusion
+- inform-food-russian
+- russian
+- singaporean
+- kay
+- fine
+- inform-food-welsh
+- welsh
+- over
+- belgium
+- belgian
+- great
+- addre
+- inform-food-crossover
+- cool
+- steakhouse
+- confirm-food-chinese
+- inform-food-austrian
+- austrian
+- inform-food-polish
+- polish
+- again
+- centre
+- then
+- ok
+- halal
+- steak
+- back
+- thanks
+- inform-food-indonesian
+- indonesian
+- correct
+- well
+- confirm-area-centre
+- confirm-area-north
+- inform-food-halal
+- see
+- welcome
+- house
+- postal
+- pri
+- more
+- anywhere
+- central
+- crossover
+- much
+- very
+- located
+- my
+- confirm-pricerange-cheap
+- restart
+- start
+- go
+- just
+- iam
+- confirm-food-thai
+- confirm-food-korean
+- city
+- as
+- wok
+- option
+- was
+- two
+- your
+- confirm-food-gastropub
+- time
+- chiquito
+- inform-name-prezzo
+- prezzo
+- fuck
+- prices
+- reqmore
+- bask
+- different
+- cambridge
+- turkiesh
+- show
+- chineese
+- confirm-area-east
+- rest
+- request-name
+- name
+- try
+- sorry
+- foo
+- ye
+- ser
+- sells
+- change
+- confirm-food-hungarian
+- eritrean
+- but
+- eartrain
+- options
+- location
+- served
+- cross
+- k
+- inform-name-chiquito
+- bar
+- tv_noise
+- confirm-food-canapes
+- day
+- parts
+- malyasian
+- airitran
+- so
+- new
+- at
+- confirm-food-indian
+- confirm-food-portuguese
+- place
+- tell
+- though
+- choice
+- awesome
+- stop
+- inform-food-australasian
+- portugese
+- missing
+- sock
+- deny-name-golden
+- golden
+- park
+- tur
+- vinci
+- pizzeria
+- endonesian
+- needs
+- deny-food-korean
+- confirm-area-west
+- t
+- trying
+- dear
+- thatll
+- excellent
+- baskaye
+- confirm-food-basque
+- p
+- if
+- india
+- some
+- ran
+- moroccon
+- confirm-food-european
+- hut
+- all
+- airatarin
+- canope
+- tailand
+- vanessa
+- earatrain
+- shit
+- ts
+- confirm-food-steakhouse
+- cantonates
+- vegitarian
+- knocking
+- signaporian
+- mail
+- foods
+- got
+- us
+- lets
+- f
+- medium
+- un
+- downtown
+- portugeuse
+- venues
+- talking
+- nymber
+- every
+- this
+- moron
+- says
+- sucks
+- itailian
+- chinses
+- elses
+- request-signature
+- special
+- restaurnt
+- confirm-food-fusion
+- spensive
+- scandinavia
+- gastro
+- pub
+- anyone
+- deny-food-chinese
+- res
+- derately
+- down
+- fancy
+- wha
+- alternative
+- confirm-food-mediterranean
+- confirm-food-caribbean
+- first
+- least
+- bart
+- selection
+- finally
+- somewhere
+- ko
+- sounds
+- said
+- eat
+- huh
+- searching
+- s
+- wrong
+- cute
+- ffood
+- earetree
+- earatree
+- confirm-food-modern
+- confirm-food-christmas
+- long
+- class
+- restauran
+- turk
+- deny-name-the
+- beside
+- yourself
+- hate
+- signaporean
+- restuarant
+- did
+- inform-name-da
+- da
+- only
+- int
+- inform-name-bloomsbury
+- bloomsbury
+- inaudible
+- scandanavian
+- done
+- confirm-food-indonesian
+- cancun
+- gasper
+- o
+- meant
+- plea
+- halo
+- inner
+- confirm-food-swedish
+- confirm-food-asian
+- wanna
+- catalanian
+- darling
+- canape
+- baskey
+- indians
+- bat
+- europ
+- now
+- canopy
+- restaraunt
+- medterranean
+- cant
+- deosnt
+- ostro
+- addrss
+- damn
+- deny-name-hk
+- hk
+- signapore
+- probably
+- ly
+- moderat
+- modereate
+- let
+- zip
+- spani
+- adddress
+- ori
+- euorpean
+- confirm-food-seafood
+- mistakes
+- ooh
+- confirm-food-spanish
+- worth
+- mediteranian
+- music
+- others
+- b
+- types
+- thing
+- fish
+- besides
+- confirm-food-halal
+- inform-name-pizza
+- pizza
+- ever
+- surprise
+- ones
+- train
+- arotrian
+- modertley
+- calling
+- minuet
+- york
+- sh
+- cost
+- confirm-area-south
+- bristish
+- confirm-food-british
+- loo
+- think
+- medetanian
+- wheres
+- his
+- confirm-food-turkish
+- inform-name-restaurant
+- euro
+- wondering
+- theres
+- afternoon
+- sure
+- might
+- umh
+- deny-food-vietnamese
+- art
+- rerestaurant
+- vietna
+- ne
+- take
+- modreately
+- air
+- tran
+- crosstalk
+- mind
+- ya
+- god
+- really
+- believe
+- confirm-food-italian
+- confirm-food-jamaican
+- preference
+- <sos/eos>
+init: null
+input_size: null
+ctc_conf:
+    dropout_rate: 0.0
+    ctc_type: builtin
+    reduce: true
+    ignore_nan_grad: true
+model_conf:
+    ctc_weight: 0.5
+    ignore_id: -1
+    lsm_weight: 0.0
+    length_normalized_loss: false
+    report_cer: true
+    report_wer: true
+    sym_space: <space>
+    sym_blank: <blank>
+    extract_feats_in_collect_stats: true
+use_preprocessor: true
+token_type: word
+bpemodel: null
+non_linguistic_symbols: null
+cleaner: null
+g2p: null
+speech_volume_normalize: null
+rir_scp: null
+rir_apply_prob: 1.0
+noise_scp: null
+noise_apply_prob: 1.0
+noise_db_range: '13_15'
+frontend: default
+frontend_conf:
+    fs: 16k
+specaug: specaug
+specaug_conf:
+    apply_time_warp: true
+    time_warp_window: 5
+    time_warp_mode: bicubic
+    apply_freq_mask: true
+    freq_mask_width_range:
+    - 0
+    - 30
+    num_freq_mask: 2
+    apply_time_mask: true
+    time_mask_width_range:
+    - 0
+    - 40
+    num_time_mask: 2
+normalize: utterance_mvn
+normalize_conf: {}
+preencoder: null
+preencoder_conf: {}
+encoder: transformer
+encoder_conf:
+    output_size: 256
+    attention_heads: 4
+    linear_units: 2048
+    num_blocks: 12
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    attention_dropout_rate: 0.0
+    input_layer: conv2d
+    normalize_before: true
+postencoder: null
+postencoder_conf: {}
+decoder: transformer
+decoder_conf:
+    attention_heads: 4
+    linear_units: 2048
+    num_blocks: 6
+    dropout_rate: 0.1
+    positional_dropout_rate: 0.1
+    self_attention_dropout_rate: 0.0
+    src_attention_dropout_rate: 0.0
+required:
+- output_dir
+- token_list
+version: 0.10.3a3
+distributed: false

exp/asr_stats_raw_en_word/logdir/stats.12/train/batch_keys

@@ -0,0 +1,2 @@
+speech
+text