#5477 cfg=TaskCfgSTT(uuid='6f1ee0d9fa', name='D:/张建光/姜胡说/2021年/@姜胡说_20201008_我Z核心的底层方法之一_建议多看几遍_刻意练习_值....mp4', dirname='D:/张建

语音识别阶段出错[Qwen-ASR(本地内置)] CUDA out of memory. Tried to allocate 24.00 MiB. GPU 0 has a total capacity of 4.00 GiB of which 0 bytes is free. Of the allocated memory 3.42 GiB is allocated by PyTorch, and 37.81 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables):Traceback (most recent call last):
File "videotrans\process\stt_fun.py", line 544, in qwen3asr_fun
File "D:\download\pyVideoTrans\_internal\qwen_asr\inference\qwen3_asr.py", line 206, in from_pretrained

model = AutoModel.from_pretrained(pretrained_model_name_or_path, **kwargs)

File "transformers\models\auto\auto_factory.py", line 604, in from_pretrained

return model_class.from_pretrained(

File "transformers\modeling_utils.py", line 277, in _wrapper

return func(*args, **kwarg

......
allocated by PyTorch, and 37.81 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

Traceback (most recent call last):

File "videotrans\task\job.py", line 35, in run

File "videotrans\task\job.py", line 100, in process_task

File "videotrans\task\speech2text.py", line 97, in recogn

File "videotrans\recognition\__init__.py", line 191, in run

File "videotrans\recognition\_base.py", line 90, in run

File "videotrans\recognition\_qwenasrlocal.py", line 45, in _exec

File "videotrans\configure\base.py", line 272, in _new_process

videotrans.configure.excepts.VideoTransError: CUDA out of memory. Tried to allocate 24.00 MiB. GPU 0 has a total capacity of 4.00 GiB of which 0 bytes is free. Of the allocated memory 3.42 GiB is allocated by PyTorch, and 37.81 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables):Traceback (most recent call last):
File "videotrans\process\stt_fun.py", line 544, in qwen3asr_fun
File "D:\download\pyVideoTrans\_internal\qwen_asr\inference\qwen3_asr.py", line 206, in from_pretrained

model = AutoModel.from_pretrained(pretrained_model_name_or_path, **kwargs)

File "transformers\models\auto\auto_factory.py", line 604, in from_pretrained

return model_class.from_pretrained(

File "transformers\modeling_utils.py", line 277, in _wrapper

return func(*args, **kwargs)

File "transformers\modeling_utils.py", line 5048, in from_pretrained

) = cls._load_pretrained_model(

File "transformers\modeling_utils.py", line 5468, in _load_pretrained_model

_error_msgs, disk_offload_index = load_shard_file(args)

File "transformers\modeling_utils.py", line 843, in load_shard_file

disk_offload_index = _load_state_dict_into_meta_model(

File "torch\utils\_contextlib.py", line 116, in decorate_context

return func(*args, **kwargs)

File "transformers\modeling_utils.py", line 750, in _load_state_dict_into_meta_model

param = param.to(casting_dtype)

torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 24.00 MiB. GPU 0 has a total capacity of 4.00 GiB of which 0 bytes is free. Of the allocated memory 3.42 GiB is allocated by PyTorch, and 37.81 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
cfg=TaskCfgSTT(uuid='6f1ee0d9fa', name='D:/张建光/姜胡说/2021年/@姜胡说_20201008_我Z核心的底层方法之一_建议多看几遍_刻意练习_值....mp4', dirname='D:/张建光/姜胡说/2021年', noextname='@姜胡说_20201008_我Z核心的底层方法之一_建议多看几遍_刻意练习_值...', basename='@姜胡说_20201008_我Z核心的底层方法之一_建议多看几遍_刻意练习_值....mp4', ext='mp4', target_dir='D:/download/pyVideoTrans/output/recogn', cache_folder='D:/download/pyVideoTrans/tmp/10384/6f1ee0d9fa', is_cuda=True, source_language=None, source_language_code=None, source_sub=None, source_wav=None, source_wav_output=None, target_language=None, target_language_code=None, target_sub='D:/download/pyVideoTrans/output/recogn/@姜胡说_20201008_我Z核心的底层方法之一_建议多看几遍_刻意练习_值....srt', target_wav=None, target_wav_output=None, detect_language='zh-cn', recogn_type=2, model_name='1.7B', shibie_audio='D:/download/pyVideoTrans/tmp/10384/6f1ee0d9fa/@姜胡说_20201008_我Z核心的底层方法之一_建议多看几遍_刻意练习_值...-1782386957.9285924.wav', remove_noise=False, enable_diariz=False, nums_diariz=0, rephrase=0, fix_punc=0)