refactor(yaml): Config ctc/cmvn/tokenizer in train.yaml

examples/aishell/NST/conf/train_conformer.yaml

@@ -28,12 +28,37 @@ decoder_conf:
     self_attention_dropout_rate: 0.0
     src_attention_dropout_rate: 0.0
 
+tokenizer: char
+tokenizer_conf:
+  symbol_table_path: 'data/dict/lang_char.txt'
+  split_with_space: false
+  bpe_path: null
+  non_lang_syms_path: null
+  is_multilingual: false
+  num_languages: 1
+  special_tokens:
+    <blank>: 0
+    <unk>: 1
+    <sos>: 2
+    <eos>: 2
+
+ctc: ctc
+ctc_conf:
+  ctc_blank_id: 0
+
+cmvn: global_cmvn
+cmvn_conf:
+  cmvn_file: 'data/train/global_cmvn'
+  is_json_cmvn: true
+
 # hybrid CTC/attention
+model: asr_model
 model_conf:
     ctc_weight: 0.3
     lsm_weight: 0.1     # label smoothing option
     length_normalized_loss: false
 
+dataset: asr
 dataset_conf:
     filter_conf:
         max_length: 1200

examples/aishell/NST/run_nst.sh

@@ -72,7 +72,6 @@ data_type=shard
 num_utts_per_shard=1000
 train_set=train
 train_config=conf/train_conformer.yaml
-cmvn=true
 average_checkpoint=true
 target_pt=80
 decode_checkpoint=$dir/$target_pt.pt
@@ -113,9 +112,6 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
   dist_backend="nccl"
   # the global_cmvn file need to be calculated by combining both supervised/unsupervised datasets,
   # and it should be positioned at data/${train_set}/global_cmvn .
-  cmvn_opts=
-  $cmvn && cp data/${train_set}/global_cmvn $dir/global_cmvn
-  $cmvn && cmvn_opts="--cmvn ${dir}/global_cmvn"
 
   # train.py rewrite $train_config to $dir/train.yaml with model input
   # and output dimension, and $dir/train.yaml will be used for inference
@@ -133,14 +129,12 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
       --train_engine ${train_engine} \
       --config $train_config \
       --data_type $data_type \
-      --symbol_table $dict \
       --train_data data/$train_set/$data_list \
       --cv_data data/dev/data.list \
       ${checkpoint:+--checkpoint $checkpoint} \
       --model_dir $dir \
       --ddp.dist_backend $dist_backend \
       --num_workers 1 \
-      $cmvn_opts \
       --pin_memory \
       --deepspeed_config ${deepspeed_config} \
       --deepspeed.save_states ${deepspeed_save_states}
@@ -190,7 +184,6 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
       --beam_size 10 \
       --batch_size 1 \
       --penalty 0.0 \
-      --dict $dict \
       --ctc_weight $ctc_weight \
       --reverse_weight $reverse_weight \
       --result_file $test_dir/text \
@@ -216,7 +209,6 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
       --beam_size 10 \
       --batch_size 1 \
       --penalty 0.0 \
-      --dict $dict \
       --ctc_weight $ctc_weight \
       --reverse_weight $reverse_weight \
       --result_file $dev_dir/text \
@@ -275,7 +267,6 @@ if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
     --beam_size 10 \
     --batch_size 1 \
     --penalty 0.0 \
-    --dict $dict \
     --ctc_weight $ctc_weight \
     --reverse_weight $reverse_weight \
     --result_file data/train/${dir_split}data_sublist${job_num}/${hypo_name} \

examples/aishell/rnnt/conf/conformer_rnnt.yaml

@@ -49,6 +49,29 @@ decoder_conf:
   self_attention_dropout_rate: 0.1
   src_attention_dropout_rate: 0.1
 
+tokenizer: char
+tokenizer_conf:
+  symbol_table_path: 'data/dict/lang_char.txt'
+  split_with_space: false
+  bpe_path: null
+  non_lang_syms_path: null
+  is_multilingual: false
+  num_languages: 1
+  special_tokens:
+    <blank>: 0
+    <unk>: 1
+    <sos>: 2
+    <eos>: 2
+
+ctc: ctc
+ctc_conf:
+  ctc_blank_id: 0
+
+cmvn: global_cmvn
+cmvn_conf:
+  cmvn_file: 'data/train/global_cmvn'
+  is_json_cmvn: true
+
 # hybrid transducer+ctc+attention
 model: transducer
 model_conf:
@@ -59,6 +82,7 @@ model_conf:
     length_normalized_loss: false
     reverse_weight: 0.3
 
+dataset: asr
 dataset_conf:
     filter_conf:
         max_length: 40960

examples/aishell/rnnt/conf/conformer_u2pp_rnnt.yaml

@@ -53,6 +53,29 @@ decoder_conf:
   self_attention_dropout_rate: 0.1
   src_attention_dropout_rate: 0.1
 
+tokenizer: char
+tokenizer_conf:
+  symbol_table_path: 'data/dict/lang_char.txt'
+  split_with_space: false
+  bpe_path: null
+  non_lang_syms_path: null
+  is_multilingual: false
+  num_languages: 1
+  special_tokens:
+    <blank>: 0
+    <unk>: 1
+    <sos>: 2
+    <eos>: 2
+
+ctc: ctc
+ctc_conf:
+  ctc_blank_id: 0
+
+cmvn: global_cmvn
+cmvn_conf:
+  cmvn_file: 'data/train/global_cmvn'
+  is_json_cmvn: true
+
 # hybrid transducer+ctc+attention
 model: transducer
 model_conf:
@@ -63,6 +86,7 @@ model_conf:
     length_normalized_loss: false
     reverse_weight: 0.3
 
+dataset: asr
 dataset_conf:
     filter_conf:
         max_length: 40960

examples/aishell/rnnt/conf/example_embedding_predictor.yaml

@@ -45,6 +45,29 @@ decoder_conf:
   self_attention_dropout_rate: 0.1
   src_attention_dropout_rate: 0.1
 
+tokenizer: char
+tokenizer_conf:
+  symbol_table_path: 'data/dict/lang_char.txt'
+  split_with_space: false
+  bpe_path: null
+  non_lang_syms_path: null
+  is_multilingual: false
+  num_languages: 1
+  special_tokens:
+    <blank>: 0
+    <unk>: 1
+    <sos>: 2
+    <eos>: 2
+
+ctc: ctc
+ctc_conf:
+  ctc_blank_id: 0
+
+cmvn: global_cmvn
+cmvn_conf:
+  cmvn_file: 'data/train/global_cmvn'
+  is_json_cmvn: true
+
 # hybrid transducer+ctc+attention
 model: transducer
 model_conf:
@@ -55,6 +78,7 @@ model_conf:
     length_normalized_loss: false
     reverse_weight: 0.3
 
+dataset: asr
 dataset_conf:
     filter_conf:
         max_length: 40960

examples/aishell/rnnt/run.sh

@@ -42,7 +42,6 @@ num_utts_per_shard=1000
 
 train_set=train
 train_config=conf/conformer_u2pp_rnnt.yaml
-cmvn=true
 dir=exp/conformer_rnnt
 checkpoint=
 
@@ -92,11 +91,10 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
   mkdir -p $(dirname $dict)
   echo "<blank> 0" > ${dict}  # 0 is for "blank" in CTC
   echo "<unk> 1"  >> ${dict}  # <unk> must be 1
+  echo "<sos/eos> 2" >> $dict
   tools/text2token.py -s 1 -n 1 data/train/text | cut -f 2- -d" " \
     | tr " " "\n" | sort | uniq | grep -a -v -e '^\s*$' | \
-    awk '{print $0 " " NR+1}' >> ${dict}
-  num_token=$(cat $dict | wc -l)
-  echo "<sos/eos> $num_token" >> $dict
+    awk '{print $0 " " NR+2}' >> ${dict}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
@@ -118,9 +116,6 @@ if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
   num_gpus=$(echo $CUDA_VISIBLE_DEVICES | awk -F "," '{print NF}')
   # Use "nccl" if it works, otherwise use "gloo"
   dist_backend="nccl"
-  cmvn_opts=
-  $cmvn && cp data/${train_set}/global_cmvn $dir
-  $cmvn && cmvn_opts="--cmvn ${dir}/global_cmvn"
 
   # train.py rewrite $train_config to $dir/train.yaml with model input
   # and output dimension, and $dir/train.yaml will be used for inference
@@ -137,14 +132,12 @@ if [ ${stage} -le 4 ] && [ ${stop_stage} -ge 4 ]; then
       --train_engine ${train_engine} \
       --config $train_config \
       --data_type $data_type \
-      --symbol_table $dict \
       --train_data data/$train_set/data.list \
       --cv_data data/dev/data.list \
       ${checkpoint:+--checkpoint $checkpoint} \
       --model_dir $dir \
       --ddp.dist_backend $dist_backend \
       --num_workers 1 \
-      $cmvn_opts \
       --pin_memory \
       --deepspeed_config ${deepspeed_config} \
       --deepspeed.save_states ${deepspeed_save_states}
@@ -183,7 +176,6 @@ if [ ${stage} -le 5 ] && [ ${stop_stage} -ge 5 ]; then
     --beam_size 10 \
     --batch_size 32 \
     --penalty 0.0 \
-    --dict $dict \
     --ctc_weight $rescore_ctc_weight \
     --transducer_weight $rescore_transducer_weight \
     --attn_weight $rescore_attn_weight \

examples/aishell/s0/conf/train_conformer.yaml

@@ -28,12 +28,37 @@ decoder_conf:
     self_attention_dropout_rate: 0.0
     src_attention_dropout_rate: 0.0
 
+tokenizer: char
+tokenizer_conf:
+  symbol_table_path: 'data/dict/lang_char.txt'
+  split_with_space: false
+  bpe_path: null
+  non_lang_syms_path: null
+  is_multilingual: false
+  num_languages: 1
+  special_tokens:
+    <blank>: 0
+    <unk>: 1
+    <sos>: 2
+    <eos>: 2
+
+ctc: ctc
+ctc_conf:
+  ctc_blank_id: 0
+
+cmvn: global_cmvn
+cmvn_conf:
+  cmvn_file: 'data/train/global_cmvn'
+  is_json_cmvn: true
+
 # hybrid CTC/attention
+model: asr_model
 model_conf:
     ctc_weight: 0.3
     lsm_weight: 0.1     # label smoothing option
     length_normalized_loss: false
 
+dataset: asr
 dataset_conf:
     filter_conf:
         max_length: 40960

examples/aishell/s0/conf/train_conformer_no_pos.yaml

@@ -28,12 +28,37 @@ decoder_conf:
     self_attention_dropout_rate: 0.0
     src_attention_dropout_rate: 0.0
 
+tokenizer: char
+tokenizer_conf:
+  symbol_table_path: 'data/dict/lang_char.txt'
+  split_with_space: false
+  bpe_path: null
+  non_lang_syms_path: null
+  is_multilingual: false
+  num_languages: 1
+  special_tokens:
+    <blank>: 0
+    <unk>: 1
+    <sos>: 2
+    <eos>: 2
+
+ctc: ctc
+ctc_conf:
+  ctc_blank_id: 0
+
+cmvn: global_cmvn
+cmvn_conf:
+  cmvn_file: 'data/train/global_cmvn'
+  is_json_cmvn: true
+
 # hybrid CTC/attention
+model: asr_model
 model_conf:
     ctc_weight: 0.3
     lsm_weight: 0.1     # label smoothing option
     length_normalized_loss: false
 
+dataset: asr
 dataset_conf:
     filter_conf:
         max_length: 40960

examples/aishell/s0/conf/train_ebranchformer.yaml

@@ -31,12 +31,37 @@ decoder_conf:
     self_attention_dropout_rate: 0.1
     src_attention_dropout_rate: 0.1
 
+tokenizer: char
+tokenizer_conf:
+  symbol_table_path: 'data/dict/lang_char.txt'
+  split_with_space: false
+  bpe_path: null
+  non_lang_syms_path: null
+  is_multilingual: false
+  num_languages: 1
+  special_tokens:
+    <blank>: 0
+    <unk>: 1
+    <sos>: 2
+    <eos>: 2
+
+ctc: ctc
+ctc_conf:
+  ctc_blank_id: 0
+
+cmvn: global_cmvn
+cmvn_conf:
+  cmvn_file: 'data/train/global_cmvn'
+  is_json_cmvn: true
+
 # hybrid CTC/attention
+model: asr_model
 model_conf:
     ctc_weight: 0.3
     lsm_weight: 0.1     # label smoothing option
     length_normalized_loss: false
 
+dataset: asr
 dataset_conf:
     filter_conf:
         max_length: 40960