pytorch config_error ai_generated true

RuntimeError: 尝试在 CUDA 设备上反序列化对象，但 torch.cuda.is_available() 为 False。如果你在仅 CPU 的机器上运行，请使用 torch.load 并设置 map_location=torch.device('cpu') 将存储映射到 CPU。

RuntimeError: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map the storages to the CPU.

ID: pytorch/model-save-load-device-mismatch

其他格式: JSON · Markdown 中文 · English
90%修复率
87%置信度
1证据数
2023-04-12首次发现

版本兼容性

版本状态引入弃用备注
1.10 active — — —
1.11 active — — —
1.12 active — — —
1.13 active — — —
2.0 active — — —
2.1 active — — —
2.2 active — — —
2.3 active — — —

根因分析

将在 GPU 机器上保存的模型检查点加载到仅 CPU 的机器上，而未指定 map_location，导致 PyTorch 尝试在非 CUDA 系统上加载 CUDA 张量。

English

Loading a model checkpoint that was saved on a GPU machine onto a CPU-only machine without specifying map_location, causing PyTorch to try to load CUDA tensors on a non-CUDA system.

generic

官方文档

https://pytorch.org/docs/stable/generated/torch.load.html

解决方案

  1. Use torch.load with map_location=torch.device('cpu') to load the checkpoint onto CPU, then move the model to the desired device afterward.
  2. Alternatively, use map_location='cpu' directly as a string argument.

无效尝试

常见但无效的做法:

  1. 80% 失败

    This doesn't address the device mismatch; the model still expects CUDA.

  2. 90% 失败

    This just changes the file path but doesn't fix the loading device.