(pyenv3) [root@bsyocr server]# python nlp/run.py > nlp/log.txt
/opt/pyenv3/lib64/python3.6/site-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: The NVIDIA driver on your system is too old (found version 10010). Please update your GPU driver by downloading and installing a new version from the URL: http://www.nvidia.com/Download/index.aspx Alternatively, go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver. (Triggered internally at /pytorch/c10/cuda/CUDAFunctions.cpp:109.)
return torch._C._cuda_getDeviceCount() > 0
38185it [00:52, 734.24it/s]
4242it [00:05, 791.65it/s]
4707it [00:06, 781.75it/s]
/opt/server/pytorch_pretrained/optimization.py:275: UserWarning: This overload of add_ is deprecated:
add_(Number alpha, Tensor other)
Consider using one of the following signatures instead:
add_(Tensor other, *, Number alpha) (Triggered internally at /pytorch/torch/csrc/utils/python_arg_parser.cpp:1005.)
next_m.mul_(beta1).add_(1 - beta1, grad)
参考
1 解决思路(不盲目升级cuda,调整pytorch版本)
https://www.zhihu.com/question/309583980
2 cuda 与 pytorch对应关系
https://blog.youkuaiyun.com/kellyroslyn/article/details/109668001
本文探讨了如何在遇到CUDA版本过旧的PyTorch警告时,避免盲目升级CUDA,而是提供了解决思路,包括调整PyTorch版本建议。同时,介绍了CUDA与PyTorch之间的对应关系,以帮助读者更好地理解两者在深度学习中的配合。
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