I built a convolutional autoencoder which consumes a variable size image dataset. For the dataloader, I used a custom collate_fn, but now I’m running into the problem that I can only load one image onto the GPU at a time. Since the bandwidth is really slow, I’m wondering if there is a way to load a list of pytorch tensors onto the GPU which have variable size? I know the maximum image size, so I have a fixed bound for the batch size, so this will never be a problem.