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Any progress for pytorch 1.5? #6
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Yup, I have pushed a branch named "pytorch-1.5" for the repo. Please pull the repo, do Let me know if it works! |
Thanks! And I'm confused about the 'func_copy' model. It seems that we need to use 2x GPU memory because of this implementation. Is there a more efficient way of implementing the backward method? |
Yes, that is a design choice due to PyTorch's nn.DataParallel. If you use only 1 GPU (i.e., no nn.DataParallel), then you are able to do the actual implicit differentiation all in the However, the weird thing we found was, once Indeed, once we are able to solve this issue, we will have much better memory efficiency than the ones reported in our paper. |
Thanks! I'm waiting for the better implementation! |
Hi, do you have any ideas for running the code for pytorch v1.5 with data parallel?
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