block swap with no_grad context #1988
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What are the issues with multi-GPU block swapping? Would we want to distribute blocks to different devices? Or is it library specific? |
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with torch.no_grad()for block swap. Unfortunately block swapping doesn't work well with multi-GPU training, but it may solve the loss=NaN issue.