#7135 mkl_malloc: failed to allocate memory,Traceback (most recent call last): File

183.158**8 Posted at: 1 hour ago

mkl_malloc: failed to allocate memory,Traceback (most recent call last):
File "videotrans\process\stt_faster.py", line 55, in _create_model
File "faster_whisper\transcribe.py", line 689, in init
RuntimeError: mkl_malloc: failed to allocate memory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "videotrans\process\stt_faster.py", line 55, in _create_model
File "faster_whisper\transcribe.py", line 689, in init
RuntimeError: mkl_malloc: failed to allocate memory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "videotrans\process\stt_faster.py", line 85, in faster_whisper
File "videotrans\process\stt_faster.py", line 74, in _create_model
File "videotrans\process\stt_faster.py", line 78, in _create_model
File "videotrans\process\stt_faster.py", line 55, in _create_model
File "faster_whisper\transcribe.py", line 689, in __ini
......
nit__.py", line 228, in run
File "videotrans\recognition\_base.py", line 97, in run
File "videotrans\recognition\_whisper.py", line 41, in _exec
File "videotrans\recognition\_whisper.py", line 130, in _faster
File "videotrans\configure\base.py", line 264, in _new_process
videotrans.configure.excepts.VideoTransError: mkl_malloc: failed to allocate memory,Traceback (most recent call last):
File "videotrans\process\stt_faster.py", line 55, in _create_model
File "faster_whisper\transcribe.py", line 689, in init
RuntimeError: mkl_malloc: failed to allocate memory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "videotrans\process\stt_faster.py", line 55, in _create_model
File "faster_whisper\transcribe.py", line 689, in init
RuntimeError: mkl_malloc: failed to allocate memory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "videotrans\process\stt_faster.py", line 85, in faster_whisper
File "videotrans\process\stt_faster.py", line 74, in _create_model
File "videotrans\process\stt_faster.py", line 78, in _create_model
File "videotrans\process\stt_faster.py", line 55, in _create_model
File "faster_whisper\transcribe.py", line 689, in init
RuntimeError: mkl_malloc: failed to allocate memory

cfg=[TaskCfgVTT]当前工作模式: 翻译视频 单视频模式
原始输入文件名: D:/AAA视频翻译/翻译测试 - 副本 (2) - 副本/1 (1).mp4,
输出结果保存到文件夹: D:/AAA视频翻译/翻译测试 - 副本 (2) - 副本/1 (1)-mp4,
临时文件夹: D://tmp/104112/fc565a39f0
未选 清理已存在
未启用CUDA加速
未选 降噪
语音识别:faster-whisper(内置), large-v3-turbo, 发音语言: 英语, 断句方式:默认断句
翻译渠道:Google(免费),原始语言:英语,目标语言:简体中文, 已选 发送完整字幕
配音渠道:Edge-TTS(免费), 角色:Yunyang(Male/CN), 配音语言:简体中文, 未选 二次语音识别
音量:+0%, 语速:+0%, 已选 音频加速, 未选 视频慢速
字幕: 不嵌入字幕
已选 分离人声与背景声, 已选 重新嵌入背景声, 背景音量0.8, 背景声音时长 短于 视频时长时: 拉长(降速播放),存在分离后的纯净人声文件,存在分离后的背景声音文件


=
system:Windows-10-10.0.26100-SP0
version:v4.12
frozen:True
language:zh_CN
root_dir:D:/

1 Replies

#1 DeepSeek reply at 1 hour ago

<mkl_malloc: failed to allocate memory 是因为系统在加载 faster-whisper large-v3-turbo 模型时内存分配失败,通常由物理内存不足、虚拟内存(页面文件)过小或同时运行的分离人声背景声任务占用了过多内存导致。

解决步骤如下:

  1. 关闭分离人声背景声:你当前同时勾选了“分离人声与背景声”,该操作基于CPU的onnx模型,会额外占用大量内存。如果无需保留背景声,请在“设置更多参数”中取消勾选“分离人声背景声”和“重新嵌入背景声”。
  2. 更换更小模型:当前使用的是 large-v3-turbo,需要约6GB显存或较多内存。请将语音识别模型改为 smallmedium,所需内存显著降低。
  3. 增大虚拟内存:进入系统设置 → 高级系统设置 → 性能 → 高级 → 虚拟内存,将页面文件大小设为“系统管理的大小”或手动设置为至少16GB。
  4. 关闭其他内存占用程序:在运行任务时关闭浏览器、其他大型软件等,释放可用内存。

如果以上方法仍无法解决,请确认系统物理内存是否低于8GB,建议升级内存或使用低配模型(如tiny)。

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