#7138 mkl_malloc: failed to allocate memory,Traceback (most recent call last): File

81.28**1 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
......
ile "videotrans\task\_stage_recogn.py", line 65, in recogn
File "videotrans\recognition\__init__.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/104488/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, 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


=
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

这是内存分配失败导致的错误,并非软件 bug。发生在 faster-whisper 模型初始化阶段,因为您选择了 large-v3 模型且未启用 CUDA 加速,模型需要在纯 CPU 环境下加载,会消耗大量物理内存(RAM),如果您的内存不足,就会触发 mkl_malloc: failed to allocate memory

请按以下顺序排查解决:

  1. 降低模型规模
    将语音识别渠道 faster-whisper(内置) 的模型从 large-v3 改为 large-v3-turbo(推荐,速度与精度兼顾)或更小的 mediumsmall。large-v3 基础运行需不低于 8GB 可用内存,纯 CPU 下要求更高。
  2. 释放系统内存
    关闭所有其他大型程序(浏览器、游戏、其他模型),确保有充足的物理内存。如果内存本身不足 8GB,请改用更小的模型。
  3. 检查模型文件是否完整
    若模型下载不完整也可能报错。可删除 软件目录/models/models--Systran--faster-whisper-large-v3 文件夹,重新启动软件让其自动完整下载,或参考文档手动下载。
  4. 启用 CUDA 加速(推荐)
    如果您有 NVIDIA 显卡且已配置 CUDA 12.8 及 cuDNN 9.x,请勾选主界面的 启用CUDA加速,将模型计算转移到显卡,大幅降低 CPU 内存压力并提升速度。若无 N 卡则忽略此步。
  5. 限制 CPU 任务数
    进入 菜单 → 工具 → 高级选项 → 通用设置,将 CPU同时任务数 设为 1,避免同时加载多个模型导致内存耗尽。
  6. 避免使用特殊路径
    您的文件路径中包含中文和空格,虽非本错误主因,但建议将视频移至纯英文数字路径(如 D:/test/1.mp4)以减少底层工具兼容问题。

请查阅相关文档:

若以上操作后仍然报错,请提供软件目录下 logs/ 文件夹中最新日志文件的内容,以便进一步分析。

Thinking...
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