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I think I managed to fix the problem I was running into. The approach I had before didn't seem to take into account how Pytorch handled wrapping the Model class and distributing the necessary information to each forward function to perform the operations. I believe the trick to getting Pytorch to work was creating a custom function class inheriting from torch.autograd.

What I have, if I can look into it some more and fix some bugs, should be able to run with any number of GPUs while evenly distributing the image data, scored and classified arrays across them.

…nction to use within the model. The rest is probably fixing bugs
@lewismc
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lewismc commented Dec 2, 2019 via email

@lewismc
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lewismc commented Dec 3, 2019

Actually @Luner if your work incorporated into this PR?

@Luner
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Luner commented Dec 3, 2019

@lewismc It looks like this PR is utilizing the code from issue 192. This was when we changed everything to pytorch but did not implement the column by column approach. The runtime for issue 192 was closer to 50 minutes.

@lewismc lewismc reopened this Dec 3, 2019
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lewismc commented Dec 3, 2019

OK, we can rebase this once we've worked on #198

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4 participants