RuntimeError: cuDNN error: CUDNN_ STATUS_ EXECUTION_ FAILED
The error is in cuda:10.0 Pytorch: 1.2 problems in the training model under the GPU server environment, error prompt Cudnn status execution failed
The problem with this error is that CUDA’s version does not correspond to pytorch’s version, resulting in CUDA’s failure to speed up model training and execute at the same time.
When downloading pytorch, we need to correctly download the corresponding relationship between pytorch and CUDA version on the official website. In the local training model, my environment is CUDA 10.0 and pytorch 1.9. Therefore, reinstall pytorch version 1.9 in the server and run successfully.
Performance: CUDA’s version does not correspond to pytorch’s version. The most obvious performance is that when running the program, the video memory does not change. When the normally loaded data and model enter the video memory, the video memory will increase significantly, while when the version does not correspond, the video memory does not change significantly. At the same time, the program will be very slow when loading the model, and even the model cannot be loaded into the video memory for 20 minutes.
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