I have a GPU and CUDA installed in Windows 10 but Pytorch's torch.cuda.is_available() returns false; how can I correct this?

  • 1 year ago
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If torch.cuda.is_available() in PyTorch is returning False even though you have a GPU and CUDA installed on your Windows 10 system, there are a few potential reasons for this issue. Here are some steps you can take to troubleshoot and resolve the problem:

  1. Verify GPU and CUDA installation: Make sure that your GPU drivers and CUDA toolkit are correctly installed on your Windows 10 system. Ensure that you have the compatible versions of CUDA and GPU drivers for your specific GPU model.

  2. Check CUDA toolkit installation path: Ensure that the CUDA installation path is correctly set in the system environment variables. The CUDA_PATH environment variable should point to the CUDA installation directory, which typically contains the bin, lib, and include folders.

  3. Check PyTorch version: Ensure that you are using a PyTorch version that is compatible with your GPU and CUDA installation. Some older versions of PyTorch may not support the latest CUDA versions or GPU architectures. Consider upgrading to the latest stable version of PyTorch.

  4. Verify CUDA runtime compatibility: Check if the CUDA runtime version matches the version supported by the installed GPU drivers. In some cases, there may be a compatibility mismatch between the CUDA runtime version and the GPU driver version. Ensure that you have the correct versions installed.

  5. Restart the system: Try restarting your Windows 10 system after installing CUDA and GPU drivers. Sometimes, a restart can help the system recognize the GPU and CUDA availability correctly.

  6. Check GPU visibility in other applications: Verify that your GPU is functioning correctly by checking if it is visible in other GPU-accelerated applications or frameworks like TensorFlow or CUDA samples. If other applications can detect the GPU, it indicates that the issue might be specific to PyTorch.

  7. Reinstall PyTorch: If none of the above steps resolve the issue, you can try uninstalling and reinstalling PyTorch. Ensure that you follow the correct installation instructions specific to your GPU and CUDA configuration.

By following these steps, you should be able to troubleshoot and resolve the issue with torch.cuda.is_available() returning False in PyTorch.