Comments (6)
I chose option D(CPU mode) in the installer for reference.
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Ok, I think I finally figured it out. Oulala. So what's happening is that one-click-installer installs latest pytorch in this case:
conda install -y -k pytorch torchvision torchaudio cpuonly git -c pytorch
However, since other packages like to be picky with pytorch, there are many torch==2.0.0 version selectors in the installations happening after that to prevent it from being reinstalled. It works on NVidia installs, but does the opposite on everything else.
The manual fix is to run that command again (after each update):
conda install -y -k pytorch torchvision torchaudio cpuonly git -c pytorch
But now that I know the problem I might be able to find a fix.
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In my case the manual fix needed the additional flag --force-reinstall to actually get the correct versions since it thought it had already installed the packages but for a completely fresh install it might not. once that was done in the conda environment it worked.
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Thanks for letting me know. Right now the only fix I imagine is to just automatically reinstall at the end. It will make the install slower but it's already time consuming, so I think I will do it that way for now.
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Ok, I added that to the update.py so that if there's no CUDA it attempts to reinstall pytorch with
conda install --force-reinstall -y -k pytorch torchvision torchaudio cpuonly git -c pytorch
command.
I will close this issue, please reopen if needed.
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