Hi, i am working on a dynamic models, using pytorch. For each sample, matrix multiplication or softmax has different shapes.For example, in a batch, the shape of input is (16X128) and for another sample it s (24X128). This leads to attention map/softmax/matmul with different length of input, like (64X16) and (64X24) / and matmul like (64X16) X .... "/>

Mar 04, 2020 · Data parallelism refers to using multiple GPUs to increase the number of examples processed simultaneously. For example, if a batch size of 256 fits on one GPU, you can use data parallelism to increase the batch size to 512 by using two GPUs, and Pytorch will automatically assign ~256 examples to one GPU and ~256 examples to the other GPU.. Feb 24, 2021 · To implement dataloaders on a custom dataset we need to override the following two subclass functions: The _len_ () function: returns the size of the dataset. The _getitem_ () function: returns a sample of the given index from the dataset. Python3. import torch. from torch.utils.data import Dataset.. Sampler class, i.e. they are passed to a PyTorch Dataloader. The purpose of samplers is to determine how batches should be formed. This is also where any offline pair or. "/>.

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