I have a model that I would like to parallelize so that inference would be much faster. The input vector that I have to this network is at one point 195xHxW. My network then reshapes it -1x3xHxW, which should normally work (65x3xHxW). But because DataParallel wraps the network it divides the 195xHxW tensor into n pieces, where n is the amount of gpus. However, when dividing the tensor it does it in such a way that the last tensor can no longer be reshaped. Is there a way to get DataParallel to work with the model so that the tensor can still be properly reshaped?