F:\workspace\Fun-ASR.venv\Scripts\python.exe F:\workspace\Fun-ASR\demo1.py
funasr version: 1.3.1.
Check update of funasr, and it would cost few times. You may disable it by set disable_update=True in AutoModel
You are using the latest version of funasr-1.3.1
Downloading Model from https://www.modelscope.cn to directory: C:\Users\Administrator.cache\modelscope\hub\models\FunAudioLLM\Fun-ASR-Nano-2512
WARNING:root:trust_remote_code: True
Loading remote code successfully: ./model.py
rtf_avg: 0.429: 100%|██████████| 1/1 [02:06<00:00, 126.67s/it]
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funasr version: 1.3.1.
Check update of funasr, and it would cost few times. You may disable it by set disable_update=True in AutoModel
You are using the latest version of funasr-1.3.1
Downloading Model from https://www.modelscope.cn to directory: C:\Users\Administrator.cache\modelscope\hub\models\FunAudioLLM\Fun-ASR-Nano-2512
Loading remote code successfully: ./model.py
WARNING:root:trust_remote_code: True
Downloading Model from https://www.modelscope.cn to directory: C:\Users\Administrator.cache\modelscope\hub\models\iic\speech_fsmn_vad_zh-cn-16k-common-pytorch
WARNING:root:trust_remote_code: False
rtf_avg: 0.135: 100%|██████████| 1/1 [00:07<00:00, 7.46s/it]
0%| | 0/1 [00:00<?, ?it/s]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:01<00:00, 1.05s/it]
{'load_data': '0.000', 'extract_feat': '0.057', 'forward': '1.051', 'batch_size': '1', 'rtf': '1.752'}, : 100%|██████████| 1/1 [00:01<00:00, 1.05s/it]
rtf_avg: 1.752: 100%|██████████| 1/1 [00:01<00:00, 1.05s/it]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:00<00:00, 1.51it/s]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.661', 'batch_size': '1', 'rtf': '0.648'}, : 100%|██████████| 1/1 [00:00<00:00, 1.51it/s]
rtf_avg: 0.648: 100%|██████████| 1/1 [00:00<00:00, 1.51it/s]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:00<00:00, 2.16it/s]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.464', 'batch_size': '1', 'rtf': '0.407'}, : 100%|██████████| 1/1 [00:00<00:00, 2.16it/s]
rtf_avg: 0.407: 100%|██████████| 1/1 [00:00<00:00, 2.16it/s]
0%| | 0/1 [00:00<?, ?it/s]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.655', 'batch_size': '1', 'rtf': '0.575'}, : 100%|██████████| 1/1 [00:00<00:00, 1.53it/s]
rtf_avg: 0.575: 100%|██████████| 1/1 [00:00<00:00, 1.52it/s]
0%| | 0/1 [00:00<?, ?it/s]
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{'load_data': '0.000', 'extract_feat': '0.001', 'forward': '0.647', 'batch_size': '1', 'rtf': '0.514'}, : 100%|██████████| 1/1 [00:00<00:00, 1.54it/s]
rtf_avg: 0.514: 100%|██████████| 1/1 [00:00<00:00, 1.54it/s]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:00<00:00, 1.30it/s]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.769', 'batch_size': '1', 'rtf': '0.583'}, : 100%|██████████| 1/1 [00:00<00:00, 1.30it/s]
rtf_avg: 0.583: 100%|██████████| 1/1 [00:00<00:00, 1.30it/s]
0%| | 0/1 [00:00<?, ?it/s]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.889', 'batch_size': '1', 'rtf': '0.674'}, : 100%|██████████| 1/1 [00:00<00:00, 1.12it/s]
rtf_avg: 0.674: 100%|██████████| 1/1 [00:00<00:00, 1.12it/s]
0%| | 0/1 [00:00<?, ?it/s]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.761', 'batch_size': '1', 'rtf': '0.552'}, : 100%|██████████| 1/1 [00:00<00:00, 1.31it/s]
rtf_avg: 0.552: 100%|██████████| 1/1 [00:00<00:00, 1.31it/s]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:00<00:00, 1.11it/s]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.897', 'batch_size': '1', 'rtf': '0.623'}, : 100%|██████████| 1/1 [00:00<00:00, 1.11it/s]
rtf_avg: 0.623: 100%|██████████| 1/1 [00:00<00:00, 1.11it/s]
0%| | 0/1 [00:00<?, ?it/s]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.092', 'batch_size': '1', 'rtf': '0.758'}, : 100%|██████████| 1/1 [00:01<00:00, 1.09s/it]
rtf_avg: 0.758: 100%|██████████| 1/1 [00:01<00:00, 1.09s/it]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.756', 'batch_size': '1', 'rtf': '0.504'}, : 100%|██████████| 1/1 [00:00<00:00, 1.32it/s]
rtf_avg: 0.504: 100%|██████████| 1/1 [00:00<00:00, 1.32it/s]
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100%|██████████| 1/1 [00:01<00:00, 1.14s/it]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.137', 'batch_size': '1', 'rtf': '0.702'}, : 100%|██████████| 1/1 [00:01<00:00, 1.14s/it]
rtf_avg: 0.702: 100%|██████████| 1/1 [00:01<00:00, 1.14s/it]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.885', 'batch_size': '1', 'rtf': '0.546'}, : 100%|██████████| 1/1 [00:00<00:00, 1.13it/s]
rtf_avg: 0.546: 100%|██████████| 1/1 [00:00<00:00, 1.13it/s]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.885', 'batch_size': '1', 'rtf': '0.547'}, : 100%|██████████| 1/1 [00:00<00:00, 1.13it/s]
rtf_avg: 0.547: 100%|██████████| 1/1 [00:00<00:00, 1.13it/s]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.232', 'batch_size': '1', 'rtf': '0.622'}, : 100%|██████████| 1/1 [00:01<00:00, 1.23s/it]
rtf_avg: 0.622: 100%|██████████| 1/1 [00:01<00:00, 1.23s/it]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:01<00:00, 1.29s/it]
{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '1.286', 'batch_size': '1', 'rtf': '0.649'}, : 100%|██████████| 1/1 [00:01<00:00, 1.29s/it]
rtf_avg: 0.649: 100%|██████████| 1/1 [00:01<00:00, 1.29s/it]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:00<00:00, 1.25it/s]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '0.798', 'batch_size': '1', 'rtf': '0.403'}, : 100%|██████████| 1/1 [00:00<00:00, 1.25it/s]
rtf_avg: 0.403: 100%|██████████| 1/1 [00:00<00:00, 1.25it/s]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:01<00:00, 1.11s/it]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.106', 'batch_size': '1', 'rtf': '0.527'}, : 100%|██████████| 1/1 [00:01<00:00, 1.11s/it]
rtf_avg: 0.527: 100%|██████████| 1/1 [00:01<00:00, 1.11s/it]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:01<00:00, 1.08s/it]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.079', 'batch_size': '1', 'rtf': '0.500'}, : 100%|██████████| 1/1 [00:01<00:00, 1.08s/it]
rtf_avg: 0.500: 100%|██████████| 1/1 [00:01<00:00, 1.08s/it]
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100%|██████████| 1/1 [00:01<00:00, 1.33s/it]
{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '1.331', 'batch_size': '1', 'rtf': '0.528'}, : 100%|██████████| 1/1 [00:01<00:00, 1.33s/it]
rtf_avg: 0.528: 100%|██████████| 1/1 [00:01<00:00, 1.33s/it]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.175', 'batch_size': '1', 'rtf': '0.455'}, : 100%|██████████| 1/1 [00:01<00:00, 1.17s/it]
rtf_avg: 0.455: 100%|██████████| 1/1 [00:01<00:00, 1.18s/it]
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{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '1.379', 'batch_size': '1', 'rtf': '0.522'}, : 100%|██████████| 1/1 [00:01<00:00, 1.38s/it]
rtf_avg: 0.522: 100%|██████████| 1/1 [00:01<00:00, 1.38s/it]
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100%|██████████| 1/1 [00:01<00:00, 1.43s/it]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.434', 'batch_size': '1', 'rtf': '0.520'}, : 100%|██████████| 1/1 [00:01<00:00, 1.43s/it]
rtf_avg: 0.520: 100%|██████████| 1/1 [00:01<00:00, 1.43s/it]
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{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.502', 'batch_size': '1', 'rtf': '0.491'}, : 100%|██████████| 1/1 [00:01<00:00, 1.50s/it]
rtf_avg: 0.491: 100%|██████████| 1/1 [00:01<00:00, 1.50s/it]
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100%|██████████| 1/1 [00:01<00:00, 1.67s/it]
{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '1.672', 'batch_size': '1', 'rtf': '0.546'}, : 100%|██████████| 1/1 [00:01<00:00, 1.67s/it]
rtf_avg: 0.546: 100%|██████████| 1/1 [00:01<00:00, 1.67s/it]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:01<00:00, 1.79s/it]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '1.787', 'batch_size': '1', 'rtf': '0.573'}, : 100%|██████████| 1/1 [00:01<00:00, 1.79s/it]
rtf_avg: 0.573: 100%|██████████| 1/1 [00:01<00:00, 1.79s/it]
0%| | 0/1 [00:00<?, ?it/s]
100%|██████████| 1/1 [00:01<00:00, 1.38s/it]
{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '1.375', 'batch_size': '1', 'rtf': '0.441'}, : 100%|██████████| 1/1 [00:01<00:00, 1.38s/it]
rtf_avg: 0.441: 100%|██████████| 1/1 [00:01<00:00, 1.38s/it]
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100%|██████████| 1/1 [00:02<00:00, 2.14s/it]
{'load_data': '0.000', 'extract_feat': '0.002', 'forward': '2.136', 'batch_size': '1', 'rtf': '0.672'}, : 100%|██████████| 1/1 [00:02<00:00, 2.14s/it]
rtf_avg: 0.672: 100%|██████████| 1/1 [00:02<00:00, 2.14s/it]
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{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '1.837', 'batch_size': '1', 'rtf': '0.547'}, : 100%|██████████| 1/1 [00:01<00:00, 1.84s/it]
rtf_avg: 0.547: 100%|██████████| 1/1 [00:01<00:00, 1.84s/it]
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{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '1.586', 'batch_size': '1', 'rtf': '0.401'}, : 100%|██████████| 1/1 [00:01<00:00, 1.59s/it]
rtf_avg: 0.401: 100%|██████████| 1/1 [00:01<00:00, 1.59s/it]
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{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '2.100', 'batch_size': '1', 'rtf': '0.515'}, : 100%|██████████| 1/1 [00:02<00:00, 2.10s/it]
rtf_avg: 0.515: 100%|██████████| 1/1 [00:02<00:00, 2.10s/it]
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{'load_data': '0.000', 'extract_feat': '0.003', 'forward': '1.825', 'batch_size': '1', 'rtf': '0.395'}, : 100%|██████████| 1/1 [00:01<00:00, 1.83s/it]
rtf_avg: 0.395: 100%|██████████| 1/1 [00:01<00:00, 1.83s/it]
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{'load_data': '0.000', 'extract_feat': '0.004', 'forward': '1.939', 'batch_size': '1', 'rtf': '0.399'}, : 100%|██████████| 1/1 [00:01<00:00, 1.94s/it]
rtf_avg: 0.399: 100%|██████████| 1/1 [00:01<00:00, 1.94s/it]
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{'load_data': '0.000', 'extract_feat': '0.006', 'forward': '1.749', 'batch_size': '1', 'rtf': '0.307'}, : 100%|██████████| 1/1 [00:01<00:00, 1.75s/it]
rtf_avg: 0.307: 100%|██████████| 1/1 [00:01<00:00, 1.75s/it]
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{'load_data': '0.000', 'extract_feat': '0.004', 'forward': '2.810', 'batch_size': '1', 'rtf': '0.459'}, : 100%|██████████| 1/1 [00:02<00:00, 2.81s/it]
rtf_avg: 0.459: 100%|██████████| 1/1 [00:02<00:00, 2.81s/it]
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{'load_data': '0.000', 'extract_feat': '0.005', 'forward': '2.428', 'batch_size': '1', 'rtf': '0.385'}, : 100%|██████████| 1/1 [00:02<00:00, 2.43s/it]
rtf_avg: 0.385: 100%|██████████| 1/1 [00:02<00:00, 2.43s/it]
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{'load_data': '0.000', 'extract_feat': '0.004', 'forward': '2.432', 'batch_size': '1', 'rtf': '0.375'}, : 100%|██████████| 1/1 [00:02<00:00, 2.43s/it]
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{'load_data': '0.000', 'extract_feat': '0.005', 'forward': '3.151', 'batch_size': '1', 'rtf': '0.453'}, : 100%|██████████| 1/1 [00:03<00:00, 3.15s/it]
rtf_avg: 0.453: 100%|██████████| 1/1 [00:03<00:00, 3.15s/it]
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{'load_data': '0.000', 'extract_feat': '0.005', 'forward': '2.764', 'batch_size': '1', 'rtf': '0.390'}, : 100%|██████████| 1/1 [00:02<00:00, 2.76s/it]
rtf_avg: 0.390: 100%|██████████| 1/1 [00:02<00:00, 2.76s/it]
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{'load_data': '0.000', 'extract_feat': '0.005', 'forward': '2.748', 'batch_size': '1', 'rtf': '0.372'}, : 100%|██████████| 1/1 [00:02<00:00, 2.75s/it]
rtf_avg: 0.372: 100%|██████████| 1/1 [00:02<00:00, 2.75s/it]
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{'load_data': '0.000', 'extract_feat': '0.007', 'forward': '3.024', 'batch_size': '1', 'rtf': '0.368'}, : 100%|██████████| 1/1 [00:03<00:00, 3.02s/it]
rtf_avg: 0.368: 100%|██████████| 1/1 [00:03<00:00, 3.02s/it]
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{'load_data': '0.000', 'extract_feat': '0.005', 'forward': '4.105', 'batch_size': '1', 'rtf': '0.444'}, : 100%|██████████| 1/1 [00:04<00:00, 4.11s/it]
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rtf_avg: 0.417: 100%|██████████| 1/1 [00:06<00:00, 6.70s/it]
Traceback (most recent call last):
File "F:\workspace\Fun-ASR\demo1.py", line 56, in
main()
File "F:\workspace\Fun-ASR\demo1.py", line 50, in main
res = model.generate(input=[wav_path], cache={}, batch_size=1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "F:\workspace\Fun-ASR.venv\Lib\site-packages\funasr\auto\auto_model.py", line 329, in generate
return self.inference_with_vad(
^^^^^^^^^^^^^^^^^^^^^^^^
File "F:\workspace\Fun-ASR.venv\Lib\site-packages\funasr\auto\auto_model.py", line 558, in inference_with_vad
t[0] += vadsegments[j][0]
~^^^
KeyError: 0
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进程已结束，退出代码为 1
F:\workspace\Fun-ASR.venv\Scripts\python.exe F:\workspace\Fun-ASR\demo1.py
funasr version: 1.3.1.
Check update of funasr, and it would cost few times. You may disable it by set
disable_update=Truein AutoModelYou are using the latest version of funasr-1.3.1
Downloading Model from https://www.modelscope.cn to directory: C:\Users\Administrator.cache\modelscope\hub\models\FunAudioLLM\Fun-ASR-Nano-2512
WARNING:root:trust_remote_code: True
Loading remote code successfully: ./model.py
rtf_avg: 0.429: 100%|██████████| 1/1 [02:06<00:00, 126.67s/it]
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funasr version: 1.3.1.
Check update of funasr, and it would cost few times. You may disable it by set
disable_update=Truein AutoModelYou are using the latest version of funasr-1.3.1
Downloading Model from https://www.modelscope.cn to directory: C:\Users\Administrator.cache\modelscope\hub\models\FunAudioLLM\Fun-ASR-Nano-2512
Loading remote code successfully: ./model.py
WARNING:root:trust_remote_code: True
Downloading Model from https://www.modelscope.cn to directory: C:\Users\Administrator.cache\modelscope\hub\models\iic\speech_fsmn_vad_zh-cn-16k-common-pytorch
WARNING:root:trust_remote_code: False
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rtf_avg: 0.417: 100%|██████████| 1/1 [00:06<00:00, 6.70s/it]
Traceback (most recent call last):
File "F:\workspace\Fun-ASR\demo1.py", line 56, in
main()
File "F:\workspace\Fun-ASR\demo1.py", line 50, in main
res = model.generate(input=[wav_path], cache={}, batch_size=1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "F:\workspace\Fun-ASR.venv\Lib\site-packages\funasr\auto\auto_model.py", line 329, in generate
return self.inference_with_vad(
^^^^^^^^^^^^^^^^^^^^^^^^
File "F:\workspace\Fun-ASR.venv\Lib\site-packages\funasr\auto\auto_model.py", line 558, in inference_with_vad
t[0] += vadsegments[j][0]
~^^^
KeyError: 0
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进程已结束，退出代码为 1