The Problem: Unable to Find PyTorch Version for CUDA 12.2
If you are encountering the error message "RuntimeError: The detected CUDA version (12.2) mismatches the version that was used to compile PyTorch (11.7)", it indicates an incompatibility between the CUDA driver and the PyTorch version you are using. This may occur if you have installed CUDA driver 12.2 but cannot find the corresponding PyTorch version.
The Solution: Exploring Available Options
To resolve this issue, here are a few possible solutions you can consider:
Solution 1: Using an NGC Container
One option is to use an NGC Container, which provides a pre-configured environment with the required CUDA drivers and PyTorch libraries. You can find PyTorch containers for various CUDA versions on the NVIDIA GPU Cloud (NGC) catalog. Visit https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch to explore the available containers and choose the one compatible with CUDA 12.2.
Solution 2: Downgrading to CUDA 12.1 and Installing the Nightly PyTorch Version
Another potential solution is to downgrade your CUDA driver to version 12.1. You can find the CUDA 12.1 PyTorch nightly version at https://download.pytorch.org/whl/nightly/cu121. Please note that you may need to update the required driver version for CUDA 12.1. Install the nightly version of PyTorch compatible with CUDA 12.1 using the provided link and see if the compatibility issue is resolved.
Solution 3: Downgrading to a Stable CUDA Version
If the above solutions don’t work for you, consider downgrading your CUDA driver to a more stable version, such as CUDA 10.2. PyTorch version 1.5 is known to work well with PyTorch for CUDA 10.2. Ensure that you update your NVIDIA driver accordingly. You can find the CUDA 10.2 PyTorch version at https://pytorch.org/get-started/previous-versions/.
Conclusion
If you are unable to find the PyTorch version for CUDA 12.2, try exploring NGC containers, downgrading to CUDA 12.1, or downgrading to a stable CUDA version such as 10.2. Ensure compatibility between CUDA driver and PyTorch version to resolve compatibility issues. Remember to update your NVIDIA driver accordingly to avoid further conflicts.
