update m2met2 (#543)

* update m2met2

* update doc

docs/m2met2/_build/html/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: a62852d90c3e533904d811bbf85f977d
+config: 160d25833895e2f6c62a4c315cacc3b9
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/m2met2_cn/_build/html/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 06d9c1d4093817b45b9d4df7ab350eaf
+config: a4d4595bd4f85adbedc556dc23e6150a
 tags: 645f666f9bcd5a90fca523b33c5a78b7

egs/alimeeting/sa-asr/asr_local.sh

@@ -1153,10 +1153,10 @@ if ! "${skip_train}"; then
         mkdir -p ${sa_asr_exp}/log
         INIT_FILE=${sa_asr_exp}/ddp_init
         
-        if [ ! -f "exp/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pb" ]; then
+        if [ ! -f "exp/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pth" ]; then
             # download xvector extractor model file
             python local/download_xvector_model.py exp
-            log "Successfully download the pretrained xvector extractor to exp/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pb"
+            log "Successfully download the pretrained xvector extractor to exp/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pth"
         fi
         
         if [ -f $INIT_FILE ];then
@@ -1195,8 +1195,8 @@ if ! "${skip_train}"; then
                     --init_param "${asr_exp}/valid.acc.ave.pb:decoder.decoders.3:decoder.decoder4.2" \
                     --init_param "${asr_exp}/valid.acc.ave.pb:decoder.decoders.4:decoder.decoder4.3" \
                     --init_param "${asr_exp}/valid.acc.ave.pb:decoder.decoders.5:decoder.decoder4.4" \
-                    --init_param "exp/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pb:encoder:spk_encoder"   \
-                    --init_param "exp/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pb:decoder:spk_encoder:decoder.output_dense"   \
+                    --init_param "exp/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pth:encoder:spk_encoder"   \
+                    --init_param "exp/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pth:decoder:spk_encoder:decoder.output_dense"   \
                     --valid_data_path_and_name_and_type "${_asr_valid_dir}/${_scp},speech,${_type}" \
                     --valid_data_path_and_name_and_type "${_asr_valid_dir}/text,text,text" \
                     --valid_data_path_and_name_and_type "${_asr_valid_dir}/oracle_profile_nopadding.scp,profile,npy" \

egs/alimeeting/sa-asr/conf/train_asr_conformer.yaml

@@ -4,6 +4,7 @@ frontend_conf:
     n_fft: 400
     win_length: 400
     hop_length: 160
+    use_channel: 0
     
 # encoder related
 encoder: conformer

egs/alimeeting/sa-asr/conf/train_sa_asr_conformer.yaml

@@ -4,6 +4,7 @@ frontend_conf:
     n_fft: 400
     win_length: 400
     hop_length: 160
+    use_channel: 0
 
 # encoder related
 asr_encoder: conformer

funasr/bin/asr_train.py

@@ -46,7 +46,8 @@ if __name__ == '__main__':
     args = parse_args()
 
     # setup local gpu_id
-    os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_id)
+    if args.ngpu > 0:
+        os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_id)
 
     # DDP settings
     if args.ngpu > 1:
@@ -57,9 +58,9 @@ if __name__ == '__main__':
 
     # re-compute batch size: when dataset type is small
     if args.dataset_type == "small":
-        if args.batch_size is not None:
+        if args.batch_size is not None and args.ngpu > 0:
             args.batch_size = args.batch_size * args.ngpu
-        if args.batch_bins is not None:
+        if args.batch_bins is not None and args.ngpu > 0:
             args.batch_bins = args.batch_bins * args.ngpu
 
     main(args=args)