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Hi, the bottleneck is that our inputs has variable length since we use sparse CNN. So if we are going to support multi-gpu training, we need to padding correctly I guess, or try to use distributed data parallel so that each GPU use a different process and set the batch size on each gpu still to be 1.
It seems that hplflownet now only support single gpu training, so how to modify it for using multi-gpu training?
thanks.
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