In distributeddataparallel, when local batch-size is 64 (i.e. torch.utils.data.DataLoader(batch_size=64) and torch.utils.data.distributed.DistributedSampler() is used), assume there are N processes totally in ddp (N processes distirbute in one node or more than one node). Is the forward-backward process in ddp similar to the forward-backward process in a single gpu using 64×N batch-size inputs?