From 1cca7562552ac99f381903b1bee1cac21e39efeb Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 16 三月 2023 11:38:02 +0800
Subject: [PATCH] Merge pull request #240 from alibaba-damo-academy/dev_wjm
---
egs/aishell/data2vec_transformer_finetune/run.sh | 2
funasr/torch_utils/load_pretrained_model.py | 10 +-
egs/aishell/paraformerbert/run.sh | 2
funasr/train/trainer.py | 36 ++++----
egs/callhome/diarization/sond/unit_test.py | 8 +-
egs/alimeeting/diarization/sond/infer_alimeeting_test.py | 2
egs/aishell/conformer/run.sh | 2
egs/aishell/transformer/run.sh | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/README.md | 2
funasr/bin/asr_inference_paraformer.py | 2
funasr/bin/asr_inference_uniasr_vad.py | 2
egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py | 2
funasr/bin/asr_inference_paraformer_vad_punc.py | 2
egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py | 2
funasr/bin/sond_inference.py | 2
funasr/bin/asr_inference_mfcca.py | 2
egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md | 2
funasr/tasks/diar.py | 2
funasr/tasks/abs_task.py | 8 +-
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/README.md | 2
egs/aishell/data2vec_paraformer_finetune/run.sh | 2
funasr/bin/asr_inference_uniasr.py | 2
funasr/bin/asr_inference.py | 2
egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md | 2
egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/README.md | 2
funasr/bin/eend_ola_inference.py | 2
egs/aishell2/paraformer/run.sh | 2
egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/README.md | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/infer_after_finetune.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer_after_finetune.py | 2
funasr/bin/asr_inference_rnnt.py | 2
egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-8k-common-vocab8358-tensorflow1/infer_after_finetune.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer_after_finetune.py | 2
egs/aishell2/paraformerbert/run.sh | 2
egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/infer_after_finetune.py | 2
funasr/main_funcs/pack_funcs.py | 4
egs/alimeeting/diarization/sond/unit_test.py | 8 +-
egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/infer_after_finetune.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/README.md | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer_after_finetune.py | 2
egs/aishell2/transformerLM/run.sh | 2
funasr/tasks/sv.py | 2
egs/mars/sd/local_run.sh | 2
funasr/bin/diar_inference_launch.py | 2
funasr/tasks/asr.py | 4
egs/aishell2/conformer/run.sh | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/README.md | 2
egs/alimeeting/diarization/sond/run.sh | 6
egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell1-vocab8404-pytorch/infer_after_finetune.py | 2
egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell2-vocab8404-pytorch/infer_after_finetune.py | 2
egs/aishell2/transformer/run.sh | 2
funasr/main_funcs/average_nbest_models.py | 18 ++--
egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/README.md | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/README.md | 3
egs/aishell/paraformer/run.sh | 2
funasr/bin/sv_inference.py | 4
egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/infer_after_finetune.py | 2
egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/infer_after_finetune.py | 2
58 files changed, 102 insertions(+), 101 deletions(-)
diff --git a/egs/aishell/conformer/run.sh b/egs/aishell/conformer/run.sh
index 41db45d..09ddab8 100755
--- a/egs/aishell/conformer/run.sh
+++ b/egs/aishell/conformer/run.sh
@@ -52,7 +52,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
diff --git a/egs/aishell/data2vec_paraformer_finetune/run.sh b/egs/aishell/data2vec_paraformer_finetune/run.sh
index cada164..d033ce2 100755
--- a/egs/aishell/data2vec_paraformer_finetune/run.sh
+++ b/egs/aishell/data2vec_paraformer_finetune/run.sh
@@ -55,7 +55,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer_noctc_1best.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
diff --git a/egs/aishell/data2vec_transformer_finetune/run.sh b/egs/aishell/data2vec_transformer_finetune/run.sh
index 7ab8626..26222e6 100755
--- a/egs/aishell/data2vec_transformer_finetune/run.sh
+++ b/egs/aishell/data2vec_transformer_finetune/run.sh
@@ -55,7 +55,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml
-inference_asr_model=valid.cer_ctc.ave_10best.pth
+inference_asr_model=valid.cer_ctc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
diff --git a/egs/aishell/paraformer/run.sh b/egs/aishell/paraformer/run.sh
index 2b0f144..53b5f90 100755
--- a/egs/aishell/paraformer/run.sh
+++ b/egs/aishell/paraformer/run.sh
@@ -52,7 +52,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer_noctc_1best.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
diff --git a/egs/aishell/paraformerbert/run.sh b/egs/aishell/paraformerbert/run.sh
index 96310ab..2487eac 100755
--- a/egs/aishell/paraformerbert/run.sh
+++ b/egs/aishell/paraformerbert/run.sh
@@ -56,7 +56,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer_noctc_1best.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
diff --git a/egs/aishell/transformer/run.sh b/egs/aishell/transformer/run.sh
index 4c307b0..f66a338 100755
--- a/egs/aishell/transformer/run.sh
+++ b/egs/aishell/transformer/run.sh
@@ -52,7 +52,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
diff --git a/egs/aishell2/conformer/run.sh b/egs/aishell2/conformer/run.sh
index bd6d81e..f9ea69a 100755
--- a/egs/aishell2/conformer/run.sh
+++ b/egs/aishell2/conformer/run.sh
@@ -54,7 +54,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, e.g., gpuid_list=2,3, the same as training stage by default
diff --git a/egs/aishell2/paraformer/run.sh b/egs/aishell2/paraformer/run.sh
index 2b7d841..e1ea4fe 100755
--- a/egs/aishell2/paraformer/run.sh
+++ b/egs/aishell2/paraformer/run.sh
@@ -54,7 +54,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer_noctc_1best.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, e.g., gpuid_list=2,3, the same as training stage by default
diff --git a/egs/aishell2/paraformerbert/run.sh b/egs/aishell2/paraformerbert/run.sh
index d0407d4..239a7e3 100755
--- a/egs/aishell2/paraformerbert/run.sh
+++ b/egs/aishell2/paraformerbert/run.sh
@@ -58,7 +58,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer_noctc_1best.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, e.g., gpuid_list=2,3, the same as training stage by default
diff --git a/egs/aishell2/transformer/run.sh b/egs/aishell2/transformer/run.sh
index a5a14ec..6f2dd4d 100755
--- a/egs/aishell2/transformer/run.sh
+++ b/egs/aishell2/transformer/run.sh
@@ -54,7 +54,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, e.g., gpuid_list=2,3, the same as training stage by default
diff --git a/egs/aishell2/transformerLM/run.sh b/egs/aishell2/transformerLM/run.sh
index 28e3762..9e7a713 100755
--- a/egs/aishell2/transformerLM/run.sh
+++ b/egs/aishell2/transformerLM/run.sh
@@ -34,7 +34,7 @@
tag=exp1
model_dir="baseline_$(basename "${lm_config}" .yaml)_${lang}_${token_type}_${tag}"
lm_exp=${exp_dir}/exp/${model_dir}
-inference_lm=valid.loss.ave.pth # Language model path for decoding.
+inference_lm=valid.loss.ave.pb # Language model path for decoding.
stage=0
stop_stage=3
diff --git a/egs/alimeeting/diarization/sond/infer_alimeeting_test.py b/egs/alimeeting/diarization/sond/infer_alimeeting_test.py
index 0988f5d..b4d534b 100644
--- a/egs/alimeeting/diarization/sond/infer_alimeeting_test.py
+++ b/egs/alimeeting/diarization/sond/infer_alimeeting_test.py
@@ -4,7 +4,7 @@
def main():
diar_config_path = sys.argv[1] if len(sys.argv) > 1 else "sond_fbank.yaml"
- diar_model_path = sys.argv[2] if len(sys.argv) > 2 else "sond.pth"
+ diar_model_path = sys.argv[2] if len(sys.argv) > 2 else "sond.pb"
output_dir = sys.argv[3] if len(sys.argv) > 3 else "./outputs"
data_path_and_name_and_type = [
("data/test_rmsil/feats.scp", "speech", "kaldi_ark"),
diff --git a/egs/alimeeting/diarization/sond/run.sh b/egs/alimeeting/diarization/sond/run.sh
index 7e9a7f7..19ae40c 100644
--- a/egs/alimeeting/diarization/sond/run.sh
+++ b/egs/alimeeting/diarization/sond/run.sh
@@ -17,9 +17,9 @@
echo "Downloading Pre-trained model..."
git clone https://www.modelscope.cn/damo/speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch.git
git clone https://www.modelscope.cn/damo/speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch.git
- ln -s speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pth ./sv.pth
+ ln -s speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.pb ./sv.pb
cp speech_xvector_sv-zh-cn-cnceleb-16k-spk3465-pytorch/sv.yaml ./sv.yaml
- ln -s speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch/sond.pth ./sond.pth
+ ln -s speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch/sond.pb ./sond.pb
cp speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch/sond_fbank.yaml ./sond_fbank.yaml
cp speech_diarization_sond-zh-cn-alimeeting-16k-n16k4-pytorch/sond.yaml ./sond.yaml
echo "Done."
@@ -30,7 +30,7 @@
if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ]; then
echo "Calculating diarization results..."
- python infer_alimeeting_test.py sond_fbank.yaml sond.pth outputs
+ python infer_alimeeting_test.py sond_fbank.yaml sond.pb outputs
python local/convert_label_to_rttm.py \
outputs/labels.txt \
data/test_rmsil/raw_rmsil_map.scp \
diff --git a/egs/alimeeting/diarization/sond/unit_test.py b/egs/alimeeting/diarization/sond/unit_test.py
index 84a4247..0f40ab2 100644
--- a/egs/alimeeting/diarization/sond/unit_test.py
+++ b/egs/alimeeting/diarization/sond/unit_test.py
@@ -4,7 +4,7 @@
def test_fbank_cpu_infer():
diar_config_path = "config_fbank.yaml"
- diar_model_path = "sond.pth"
+ diar_model_path = "sond.pb"
output_dir = "./outputs"
data_path_and_name_and_type = [
("data/unit_test/test_feats.scp", "speech", "kaldi_ark"),
@@ -24,7 +24,7 @@
def test_fbank_gpu_infer():
diar_config_path = "config_fbank.yaml"
- diar_model_path = "sond.pth"
+ diar_model_path = "sond.pb"
output_dir = "./outputs"
data_path_and_name_and_type = [
("data/unit_test/test_feats.scp", "speech", "kaldi_ark"),
@@ -45,7 +45,7 @@
def test_wav_gpu_infer():
diar_config_path = "config.yaml"
- diar_model_path = "sond.pth"
+ diar_model_path = "sond.pb"
output_dir = "./outputs"
data_path_and_name_and_type = [
("data/unit_test/test_wav.scp", "speech", "sound"),
@@ -66,7 +66,7 @@
def test_without_profile_gpu_infer():
diar_config_path = "config.yaml"
- diar_model_path = "sond.pth"
+ diar_model_path = "sond.pb"
output_dir = "./outputs"
raw_inputs = [[
"data/unit_test/raw_inputs/record.wav",
diff --git a/egs/callhome/diarization/sond/unit_test.py b/egs/callhome/diarization/sond/unit_test.py
index 519ac56..a48eda1 100644
--- a/egs/callhome/diarization/sond/unit_test.py
+++ b/egs/callhome/diarization/sond/unit_test.py
@@ -4,7 +4,7 @@
def test_fbank_cpu_infer():
diar_config_path = "sond_fbank.yaml"
- diar_model_path = "sond.pth"
+ diar_model_path = "sond.pb"
output_dir = "./outputs"
data_path_and_name_and_type = [
("data/unit_test/test_feats.scp", "speech", "kaldi_ark"),
@@ -24,7 +24,7 @@
def test_fbank_gpu_infer():
diar_config_path = "sond_fbank.yaml"
- diar_model_path = "sond.pth"
+ diar_model_path = "sond.pb"
output_dir = "./outputs"
data_path_and_name_and_type = [
("data/unit_test/test_feats.scp", "speech", "kaldi_ark"),
@@ -45,7 +45,7 @@
def test_wav_gpu_infer():
diar_config_path = "config.yaml"
- diar_model_path = "sond.pth"
+ diar_model_path = "sond.pb"
output_dir = "./outputs"
data_path_and_name_and_type = [
("data/unit_test/test_wav.scp", "speech", "sound"),
@@ -66,7 +66,7 @@
def test_without_profile_gpu_infer():
diar_config_path = "config.yaml"
- diar_model_path = "sond.pth"
+ diar_model_path = "sond.pb"
output_dir = "./outputs"
raw_inputs = [[
"data/unit_test/raw_inputs/record.wav",
diff --git a/egs/mars/sd/local_run.sh b/egs/mars/sd/local_run.sh
index 3b319f4..4516e9f 100755
--- a/egs/mars/sd/local_run.sh
+++ b/egs/mars/sd/local_run.sh
@@ -49,7 +49,7 @@
model_dir="baseline_$(basename "${asr_config}" .yaml)_${feats_type}_${lang}_${token_type}_${tag}"
inference_config=conf/decode_asr_transformer.yaml
-inference_asr_model=valid.acc.ave_10best.pth
+inference_asr_model=valid.acc.ave_10best.pb
# you can set gpu num for decoding here
gpuid_list=$CUDA_VISIBLE_DEVICES # set gpus for decoding, the same as training stage by default
diff --git a/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/README.md b/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/README.md
index c2e4354..053986d 100644
--- a/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/README.md
+++ b/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/README.md
@@ -41,7 +41,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed~~~~
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/infer_after_finetune.py b/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/infer_after_finetune.py
index 56c282c..b326067 100644
--- a/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/infer_after_finetune.py
+++ b/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-paraformer-zh-cn-aishell2-16k/infer_after_finetune.py
@@ -48,5 +48,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "valid.cer_ctc.ave.pth"
+ params["decoding_model_name"] = "valid.cer_ctc.ave.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/README.md b/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/README.md
index c2e4354..053986d 100644
--- a/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/README.md
+++ b/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/README.md
@@ -41,7 +41,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed~~~~
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/infer_after_finetune.py b/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/infer_after_finetune.py
index e163999..2f038a8 100644
--- a/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/infer_after_finetune.py
+++ b/egs_modelscope/asr/data2vec/speech_data2vec_pretrain-zh-cn-aishell2-16k-pytorch/infer_after_finetune.py
@@ -48,5 +48,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "valid.cer_ctc.ave.pth"
+ params["decoding_model_name"] = "valid.cer_ctc.ave.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/README.md b/egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/README.md
index 9097e7a..16aeada 100644
--- a/egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/README.md
+++ b/egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/README.md
@@ -41,7 +41,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/infer_after_finetune.py b/egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/infer_after_finetune.py
index e714a3d..333b66a 100755
--- a/egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/infer_after_finetune.py
+++ b/egs_modelscope/asr/mfcca/speech_mfcca_asr-zh-cn-16k-alimeeting-vocab4950/infer_after_finetune.py
@@ -63,5 +63,5 @@
params["required_files"] = ["feats_stats.npz", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./example_data/validation"
- params["decoding_model_name"] = "valid.acc.ave.pth"
+ params["decoding_model_name"] = "valid.acc.ave.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell1-vocab8404-pytorch/infer_after_finetune.py b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell1-vocab8404-pytorch/infer_after_finetune.py
index 6c34ed0..f1f29fa 100644
--- a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell1-vocab8404-pytorch/infer_after_finetune.py
+++ b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell1-vocab8404-pytorch/infer_after_finetune.py
@@ -49,5 +49,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "valid.acc.ave_10best.pth"
+ params["decoding_model_name"] = "valid.acc.ave_10best.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell2-vocab8404-pytorch/infer_after_finetune.py b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell2-vocab8404-pytorch/infer_after_finetune.py
index 6140bb7..8cb537b 100644
--- a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell2-vocab8404-pytorch/infer_after_finetune.py
+++ b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-aishell2-vocab8404-pytorch/infer_after_finetune.py
@@ -49,5 +49,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "valid.acc.ave_10best.pth"
+ params["decoding_model_name"] = "valid.acc.ave_10best.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
index dfd509d..b68f1e9 100644
--- a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
+++ b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
@@ -41,7 +41,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py
index 94393ec..f26f237 100644
--- a/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py
+++ b/egs_modelscope/asr/paraformer/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py
@@ -49,5 +49,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "valid.acc.ave_10best.pth"
+ params["decoding_model_name"] = "valid.acc.ave_10best.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-8k-common-vocab8358-tensorflow1/infer_after_finetune.py b/egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-8k-common-vocab8358-tensorflow1/infer_after_finetune.py
index 96102cc..726009d 100644
--- a/egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-8k-common-vocab8358-tensorflow1/infer_after_finetune.py
+++ b/egs_modelscope/asr/paraformer/speech_paraformer_asr_nat-zh-cn-8k-common-vocab8358-tensorflow1/infer_after_finetune.py
@@ -49,5 +49,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "valid.acc.ave_10best.pth"
+ params["decoding_model_name"] = "valid.acc.ave_10best.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/README.md b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/README.md
index dfd509d..b68f1e9 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/README.md
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/README.md
@@ -41,7 +41,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer_after_finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer_after_finetune.py
index d91a40a..6593f4e 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer_after_finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-offline/infer_after_finetune.py
@@ -50,5 +50,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "20epoch.pth"
+ params["decoding_model_name"] = "20epoch.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/README.md b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/README.md
index dfd509d..b68f1e9 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/README.md
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/README.md
@@ -41,7 +41,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer_after_finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer_after_finetune.py
index f9fb0db..f067c81 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer_after_finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-fa-16k-common-vocab1257-pytorch-online/infer_after_finetune.py
@@ -50,5 +50,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "20epoch.pth"
+ params["decoding_model_name"] = "20epoch.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/README.md b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/README.md
index dd947d3..9a84f9b 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/README.md
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/README.md
@@ -41,7 +41,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/infer_after_finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/infer_after_finetune.py
index 030c2e2..d4df29e 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/infer_after_finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-minnan-16k-common-vocab3825/infer_after_finetune.py
@@ -50,5 +50,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "20epoch.pth"
+ params["decoding_model_name"] = "20epoch.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/README.md b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/README.md
index dd947d3..9a84f9b 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/README.md
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/README.md
@@ -41,7 +41,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer_after_finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer_after_finetune.py
index 3b39a16..861fefb 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer_after_finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-offline/infer_after_finetune.py
@@ -49,5 +49,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "20epoch.pth"
+ params["decoding_model_name"] = "20epoch.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/README.md b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/README.md
index dd947d3..eff933e 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/README.md
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/README.md
@@ -41,7 +41,8 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave
+ .pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/infer_after_finetune.py b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/infer_after_finetune.py
index 4860cf7..d73cae2 100644
--- a/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/infer_after_finetune.py
+++ b/egs_modelscope/asr/uniasr/speech_UniASR_asr_2pass-zh-cn-8k-common-vocab3445-pytorch-online/infer_after_finetune.py
@@ -49,5 +49,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "20epoch.pth"
+ params["decoding_model_name"] = "20epoch.pb"
modelscope_infer_after_finetune(params)
diff --git a/egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md b/egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
index 1094bb5..94144ef 100644
--- a/egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
+++ b/egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/README.md
@@ -34,7 +34,7 @@
- Modify inference related parameters in `infer_after_finetune.py`
- <strong>output_dir:</strong> # result dir
- <strong>data_dir:</strong> # the dataset dir needs to include `test/wav.scp`. If `test/text` is also exists, CER will be computed
- - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pth`
+ - <strong>decoding_model_name:</strong> # set the checkpoint name for decoding, e.g., `valid.cer_ctc.ave.pb`
- Then you can run the pipeline to finetune with:
```python
diff --git a/egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py b/egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py
index 5f171b4..3712cb8 100644
--- a/egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py
+++ b/egs_modelscope/asr_vad_punc/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch/infer_after_finetune.py
@@ -53,5 +53,5 @@
params["required_files"] = ["am.mvn", "decoding.yaml", "configuration.json", "punc/punc.pb", "punc/punc.yaml", "vad/vad.mvn", "vad/vad.pb", "vad/vad.yaml"]
params["output_dir"] = "./checkpoint"
params["data_dir"] = "./data/test"
- params["decoding_model_name"] = "valid.acc.ave_10best.pth"
+ params["decoding_model_name"] = "valid.acc.ave_10best.pb"
modelscope_infer_after_finetune(params)
diff --git a/funasr/bin/asr_inference.py b/funasr/bin/asr_inference.py
index 318d3d7..f3b4d56 100644
--- a/funasr/bin/asr_inference.py
+++ b/funasr/bin/asr_inference.py
@@ -52,7 +52,7 @@
Examples:
>>> import soundfile
- >>> speech2text = Speech2Text("asr_config.yml", "asr.pth")
+ >>> speech2text = Speech2Text("asr_config.yml", "asr.pb")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2text(audio)
[(text, token, token_int, hypothesis object), ...]
diff --git a/funasr/bin/asr_inference_mfcca.py b/funasr/bin/asr_inference_mfcca.py
index 4176ba6..888d4d2 100644
--- a/funasr/bin/asr_inference_mfcca.py
+++ b/funasr/bin/asr_inference_mfcca.py
@@ -55,7 +55,7 @@
Examples:
>>> import soundfile
- >>> speech2text = Speech2Text("asr_config.yml", "asr.pth")
+ >>> speech2text = Speech2Text("asr_config.yml", "asr.pb")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2text(audio)
[(text, token, token_int, hypothesis object), ...]
diff --git a/funasr/bin/asr_inference_paraformer.py b/funasr/bin/asr_inference_paraformer.py
index 6413d92..e45e575 100644
--- a/funasr/bin/asr_inference_paraformer.py
+++ b/funasr/bin/asr_inference_paraformer.py
@@ -50,7 +50,7 @@
Examples:
>>> import soundfile
- >>> speech2text = Speech2Text("asr_config.yml", "asr.pth")
+ >>> speech2text = Speech2Text("asr_config.yml", "asr.pb")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2text(audio)
[(text, token, token_int, hypothesis object), ...]
diff --git a/funasr/bin/asr_inference_paraformer_vad_punc.py b/funasr/bin/asr_inference_paraformer_vad_punc.py
index a0e7b47..3f57751 100644
--- a/funasr/bin/asr_inference_paraformer_vad_punc.py
+++ b/funasr/bin/asr_inference_paraformer_vad_punc.py
@@ -58,7 +58,7 @@
Examples:
>>> import soundfile
- >>> speech2text = Speech2Text("asr_config.yml", "asr.pth")
+ >>> speech2text = Speech2Text("asr_config.yml", "asr.pb")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2text(audio)
[(text, token, token_int, hypothesis object), ...]
diff --git a/funasr/bin/asr_inference_rnnt.py b/funasr/bin/asr_inference_rnnt.py
index 6cd7061..4a9ff0b 100644
--- a/funasr/bin/asr_inference_rnnt.py
+++ b/funasr/bin/asr_inference_rnnt.py
@@ -49,7 +49,7 @@
Examples:
>>> import soundfile
- >>> speech2text = Speech2Text("asr_config.yml", "asr.pth")
+ >>> speech2text = Speech2Text("asr_config.yml", "asr.pb")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2text(audio)
[(text, token, token_int, hypothesis object), ...]
diff --git a/funasr/bin/asr_inference_uniasr.py b/funasr/bin/asr_inference_uniasr.py
index 8b31fad..ac71538 100644
--- a/funasr/bin/asr_inference_uniasr.py
+++ b/funasr/bin/asr_inference_uniasr.py
@@ -46,7 +46,7 @@
Examples:
>>> import soundfile
- >>> speech2text = Speech2Text("asr_config.yml", "asr.pth")
+ >>> speech2text = Speech2Text("asr_config.yml", "asr.pb")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2text(audio)
[(text, token, token_int, hypothesis object), ...]
diff --git a/funasr/bin/asr_inference_uniasr_vad.py b/funasr/bin/asr_inference_uniasr_vad.py
index e5815df..7cb889b 100644
--- a/funasr/bin/asr_inference_uniasr_vad.py
+++ b/funasr/bin/asr_inference_uniasr_vad.py
@@ -46,7 +46,7 @@
Examples:
>>> import soundfile
- >>> speech2text = Speech2Text("asr_config.yml", "asr.pth")
+ >>> speech2text = Speech2Text("asr_config.yml", "asr.pb")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2text(audio)
[(text, token, token_int, hypothesis object), ...]
diff --git a/funasr/bin/diar_inference_launch.py b/funasr/bin/diar_inference_launch.py
index 70bb947..85e4518 100755
--- a/funasr/bin/diar_inference_launch.py
+++ b/funasr/bin/diar_inference_launch.py
@@ -133,7 +133,7 @@
param_dict = {
"extract_profile": True,
"sv_train_config": "sv.yaml",
- "sv_model_file": "sv.pth",
+ "sv_model_file": "sv.pb",
}
if "param_dict" in kwargs and kwargs["param_dict"] is not None:
for key in param_dict:
diff --git a/funasr/bin/eend_ola_inference.py b/funasr/bin/eend_ola_inference.py
index bc29fa2..01d3f29 100755
--- a/funasr/bin/eend_ola_inference.py
+++ b/funasr/bin/eend_ola_inference.py
@@ -35,7 +35,7 @@
Examples:
>>> import soundfile
>>> import numpy as np
- >>> speech2diar = Speech2Diarization("diar_sond_config.yml", "diar_sond.pth")
+ >>> speech2diar = Speech2Diarization("diar_sond_config.yml", "diar_sond.pb")
>>> profile = np.load("profiles.npy")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2diar(audio, profile)
diff --git a/funasr/bin/sond_inference.py b/funasr/bin/sond_inference.py
index ab6d26f..936dc21 100755
--- a/funasr/bin/sond_inference.py
+++ b/funasr/bin/sond_inference.py
@@ -42,7 +42,7 @@
Examples:
>>> import soundfile
>>> import numpy as np
- >>> speech2diar = Speech2Diarization("diar_sond_config.yml", "diar_sond.pth")
+ >>> speech2diar = Speech2Diarization("diar_sond_config.yml", "diar_sond.pb")
>>> profile = np.load("profiles.npy")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2diar(audio, profile)
diff --git a/funasr/bin/sv_inference.py b/funasr/bin/sv_inference.py
index a78bccd..7e63bbd 100755
--- a/funasr/bin/sv_inference.py
+++ b/funasr/bin/sv_inference.py
@@ -36,7 +36,7 @@
Examples:
>>> import soundfile
- >>> speech2xvector = Speech2Xvector("sv_config.yml", "sv.pth")
+ >>> speech2xvector = Speech2Xvector("sv_config.yml", "sv.pb")
>>> audio, rate = soundfile.read("speech.wav")
>>> speech2xvector(audio)
[(text, token, token_int, hypothesis object), ...]
@@ -169,7 +169,7 @@
log_level: Union[int, str] = "INFO",
key_file: Optional[str] = None,
sv_train_config: Optional[str] = "sv.yaml",
- sv_model_file: Optional[str] = "sv.pth",
+ sv_model_file: Optional[str] = "sv.pb",
model_tag: Optional[str] = None,
allow_variable_data_keys: bool = True,
streaming: bool = False,
diff --git a/funasr/main_funcs/average_nbest_models.py b/funasr/main_funcs/average_nbest_models.py
index 53f9568..d8df949 100644
--- a/funasr/main_funcs/average_nbest_models.py
+++ b/funasr/main_funcs/average_nbest_models.py
@@ -66,13 +66,13 @@
elif n == 1:
# The averaged model is same as the best model
e, _ = epoch_and_values[0]
- op = output_dir / f"{e}epoch.pth"
- sym_op = output_dir / f"{ph}.{cr}.ave_1best.{suffix}pth"
+ op = output_dir / f"{e}epoch.pb"
+ sym_op = output_dir / f"{ph}.{cr}.ave_1best.{suffix}pb"
if sym_op.is_symlink() or sym_op.exists():
sym_op.unlink()
sym_op.symlink_to(op.name)
else:
- op = output_dir / f"{ph}.{cr}.ave_{n}best.{suffix}pth"
+ op = output_dir / f"{ph}.{cr}.ave_{n}best.{suffix}pb"
logging.info(
f"Averaging {n}best models: " f'criterion="{ph}.{cr}": {op}'
)
@@ -83,12 +83,12 @@
if e not in _loaded:
if oss_bucket is None:
_loaded[e] = torch.load(
- output_dir / f"{e}epoch.pth",
+ output_dir / f"{e}epoch.pb",
map_location="cpu",
)
else:
buffer = BytesIO(
- oss_bucket.get_object(os.path.join(pai_output_dir, f"{e}epoch.pth")).read())
+ oss_bucket.get_object(os.path.join(pai_output_dir, f"{e}epoch.pb")).read())
_loaded[e] = torch.load(buffer)
states = _loaded[e]
@@ -115,13 +115,13 @@
else:
buffer = BytesIO()
torch.save(avg, buffer)
- oss_bucket.put_object(os.path.join(pai_output_dir, f"{ph}.{cr}.ave_{n}best.{suffix}pth"),
+ oss_bucket.put_object(os.path.join(pai_output_dir, f"{ph}.{cr}.ave_{n}best.{suffix}pb"),
buffer.getvalue())
- # 3. *.*.ave.pth is a symlink to the max ave model
+ # 3. *.*.ave.pb is a symlink to the max ave model
if oss_bucket is None:
- op = output_dir / f"{ph}.{cr}.ave_{max(_nbests)}best.{suffix}pth"
- sym_op = output_dir / f"{ph}.{cr}.ave.{suffix}pth"
+ op = output_dir / f"{ph}.{cr}.ave_{max(_nbests)}best.{suffix}pb"
+ sym_op = output_dir / f"{ph}.{cr}.ave.{suffix}pb"
if sym_op.is_symlink() or sym_op.exists():
sym_op.unlink()
sym_op.symlink_to(op.name)
diff --git a/funasr/main_funcs/pack_funcs.py b/funasr/main_funcs/pack_funcs.py
index ffa807e..fe365d8 100644
--- a/funasr/main_funcs/pack_funcs.py
+++ b/funasr/main_funcs/pack_funcs.py
@@ -191,12 +191,12 @@
Examples:
tarfile:
- model.pth
+ model.pb
some1.file
some2.file
>>> unpack("tarfile", "out")
- {'asr_model_file': 'out/model.pth'}
+ {'asr_model_file': 'out/model.pb'}
"""
input_archive = Path(input_archive)
outpath = Path(outpath)
diff --git a/funasr/tasks/abs_task.py b/funasr/tasks/abs_task.py
index e0884ce..3f20b4f 100644
--- a/funasr/tasks/abs_task.py
+++ b/funasr/tasks/abs_task.py
@@ -639,12 +639,12 @@
"and exclude_keys excludes keys of model states for the initialization."
"e.g.\n"
" # Load all parameters"
- " --init_param some/where/model.pth\n"
+ " --init_param some/where/model.pb\n"
" # Load only decoder parameters"
- " --init_param some/where/model.pth:decoder:decoder\n"
+ " --init_param some/where/model.pb:decoder:decoder\n"
" # Load only decoder parameters excluding decoder.embed"
- " --init_param some/where/model.pth:decoder:decoder:decoder.embed\n"
- " --init_param some/where/model.pth:decoder:decoder:decoder.embed\n",
+ " --init_param some/where/model.pb:decoder:decoder:decoder.embed\n"
+ " --init_param some/where/model.pb:decoder:decoder:decoder.embed\n",
)
group.add_argument(
"--ignore_init_mismatch",
diff --git a/funasr/tasks/asr.py b/funasr/tasks/asr.py
index 36499a2..e151473 100644
--- a/funasr/tasks/asr.py
+++ b/funasr/tasks/asr.py
@@ -826,7 +826,7 @@
if "model.ckpt-" in model_name or ".bin" in model_name:
model_name_pth = os.path.join(model_dir, model_name.replace('.bin',
'.pb')) if ".bin" in model_name else os.path.join(
- model_dir, "{}.pth".format(model_name))
+ model_dir, "{}.pb".format(model_name))
if os.path.exists(model_name_pth):
logging.info("model_file is load from pth: {}".format(model_name_pth))
model_dict = torch.load(model_name_pth, map_location=device)
@@ -1073,7 +1073,7 @@
if "model.ckpt-" in model_name or ".bin" in model_name:
model_name_pth = os.path.join(model_dir, model_name.replace('.bin',
'.pb')) if ".bin" in model_name else os.path.join(
- model_dir, "{}.pth".format(model_name))
+ model_dir, "{}.pb".format(model_name))
if os.path.exists(model_name_pth):
logging.info("model_file is load from pth: {}".format(model_name_pth))
model_dict = torch.load(model_name_pth, map_location=device)
diff --git a/funasr/tasks/diar.py b/funasr/tasks/diar.py
index 6962915..9875f6a 100644
--- a/funasr/tasks/diar.py
+++ b/funasr/tasks/diar.py
@@ -553,7 +553,7 @@
if ".bin" in model_name:
model_name_pth = os.path.join(model_dir, model_name.replace('.bin', '.pb'))
else:
- model_name_pth = os.path.join(model_dir, "{}.pth".format(model_name))
+ model_name_pth = os.path.join(model_dir, "{}.pb".format(model_name))
if os.path.exists(model_name_pth):
logging.info("model_file is load from pth: {}".format(model_name_pth))
model_dict = torch.load(model_name_pth, map_location=device)
diff --git a/funasr/tasks/sv.py b/funasr/tasks/sv.py
index 1b08c4d..bef5dc5 100644
--- a/funasr/tasks/sv.py
+++ b/funasr/tasks/sv.py
@@ -501,7 +501,7 @@
if ".bin" in model_name:
model_name_pth = os.path.join(model_dir, model_name.replace('.bin', '.pb'))
else:
- model_name_pth = os.path.join(model_dir, "{}.pth".format(model_name))
+ model_name_pth = os.path.join(model_dir, "{}.pb".format(model_name))
if os.path.exists(model_name_pth):
logging.info("model_file is load from pth: {}".format(model_name_pth))
model_dict = torch.load(model_name_pth, map_location=device)
diff --git a/funasr/torch_utils/load_pretrained_model.py b/funasr/torch_utils/load_pretrained_model.py
index 8e3f05e..e9b18cd 100644
--- a/funasr/torch_utils/load_pretrained_model.py
+++ b/funasr/torch_utils/load_pretrained_model.py
@@ -52,13 +52,13 @@
init_param: <file_path>:<src_key>:<dst_key>:<exclude_Keys>
Examples:
- >>> load_pretrained_model("somewhere/model.pth", model)
- >>> load_pretrained_model("somewhere/model.pth:decoder:decoder", model)
- >>> load_pretrained_model("somewhere/model.pth:decoder:decoder:", model)
+ >>> load_pretrained_model("somewhere/model.pb", model)
+ >>> load_pretrained_model("somewhere/model.pb:decoder:decoder", model)
+ >>> load_pretrained_model("somewhere/model.pb:decoder:decoder:", model)
>>> load_pretrained_model(
- ... "somewhere/model.pth:decoder:decoder:decoder.embed", model
+ ... "somewhere/model.pb:decoder:decoder:decoder.embed", model
... )
- >>> load_pretrained_model("somewhere/decoder.pth::decoder", model)
+ >>> load_pretrained_model("somewhere/decoder.pb::decoder", model)
"""
sps = init_param.split(":", 4)
if len(sps) == 4:
diff --git a/funasr/train/trainer.py b/funasr/train/trainer.py
index 50bce47..efe2009 100644
--- a/funasr/train/trainer.py
+++ b/funasr/train/trainer.py
@@ -205,9 +205,9 @@
else:
scaler = None
- if trainer_options.resume and (output_dir / "checkpoint.pth").exists():
+ if trainer_options.resume and (output_dir / "checkpoint.pb").exists():
cls.resume(
- checkpoint=output_dir / "checkpoint.pth",
+ checkpoint=output_dir / "checkpoint.pb",
model=model,
optimizers=optimizers,
schedulers=schedulers,
@@ -361,7 +361,7 @@
},
buffer,
)
- trainer_options.oss_bucket.put_object(os.path.join(trainer_options.output_dir, "checkpoint.pth"), buffer.getvalue())
+ trainer_options.oss_bucket.put_object(os.path.join(trainer_options.output_dir, "checkpoint.pb"), buffer.getvalue())
else:
torch.save(
{
@@ -374,7 +374,7 @@
],
"scaler": scaler.state_dict() if scaler is not None else None,
},
- output_dir / "checkpoint.pth",
+ output_dir / "checkpoint.pb",
)
# 5. Save and log the model and update the link to the best model
@@ -382,22 +382,22 @@
buffer = BytesIO()
torch.save(model.state_dict(), buffer)
trainer_options.oss_bucket.put_object(os.path.join(trainer_options.output_dir,
- f"{iepoch}epoch.pth"),buffer.getvalue())
+ f"{iepoch}epoch.pb"),buffer.getvalue())
else:
- torch.save(model.state_dict(), output_dir / f"{iepoch}epoch.pth")
+ torch.save(model.state_dict(), output_dir / f"{iepoch}epoch.pb")
- # Creates a sym link latest.pth -> {iepoch}epoch.pth
+ # Creates a sym link latest.pb -> {iepoch}epoch.pb
if trainer_options.use_pai:
- p = os.path.join(trainer_options.output_dir, "latest.pth")
+ p = os.path.join(trainer_options.output_dir, "latest.pb")
if trainer_options.oss_bucket.object_exists(p):
trainer_options.oss_bucket.delete_object(p)
trainer_options.oss_bucket.copy_object(trainer_options.oss_bucket.bucket_name,
- os.path.join(trainer_options.output_dir, f"{iepoch}epoch.pth"), p)
+ os.path.join(trainer_options.output_dir, f"{iepoch}epoch.pb"), p)
else:
- p = output_dir / "latest.pth"
+ p = output_dir / "latest.pb"
if p.is_symlink() or p.exists():
p.unlink()
- p.symlink_to(f"{iepoch}epoch.pth")
+ p.symlink_to(f"{iepoch}epoch.pb")
_improved = []
for _phase, k, _mode in trainer_options.best_model_criterion:
@@ -407,16 +407,16 @@
# Creates sym links if it's the best result
if best_epoch == iepoch:
if trainer_options.use_pai:
- p = os.path.join(trainer_options.output_dir, f"{_phase}.{k}.best.pth")
+ p = os.path.join(trainer_options.output_dir, f"{_phase}.{k}.best.pb")
if trainer_options.oss_bucket.object_exists(p):
trainer_options.oss_bucket.delete_object(p)
trainer_options.oss_bucket.copy_object(trainer_options.oss_bucket.bucket_name,
- os.path.join(trainer_options.output_dir, f"{iepoch}epoch.pth"),p)
+ os.path.join(trainer_options.output_dir, f"{iepoch}epoch.pb"),p)
else:
- p = output_dir / f"{_phase}.{k}.best.pth"
+ p = output_dir / f"{_phase}.{k}.best.pb"
if p.is_symlink() or p.exists():
p.unlink()
- p.symlink_to(f"{iepoch}epoch.pth")
+ p.symlink_to(f"{iepoch}epoch.pb")
_improved.append(f"{_phase}.{k}")
if len(_improved) == 0:
logging.info("There are no improvements in this epoch")
@@ -438,7 +438,7 @@
type="model",
metadata={"improved": _improved},
)
- artifact.add_file(str(output_dir / f"{iepoch}epoch.pth"))
+ artifact.add_file(str(output_dir / f"{iepoch}epoch.pb"))
aliases = [
f"epoch-{iepoch}",
"best" if best_epoch == iepoch else "",
@@ -473,12 +473,12 @@
for e in range(1, iepoch):
if trainer_options.use_pai:
- p = os.path.join(trainer_options.output_dir, f"{e}epoch.pth")
+ p = os.path.join(trainer_options.output_dir, f"{e}epoch.pb")
if trainer_options.oss_bucket.object_exists(p) and e not in nbests:
trainer_options.oss_bucket.delete_object(p)
_removed.append(str(p))
else:
- p = output_dir / f"{e}epoch.pth"
+ p = output_dir / f"{e}epoch.pb"
if p.exists() and e not in nbests:
p.unlink()
_removed.append(str(p))
--
Gitblit v1.9.1