Dear Kushajveer,
Thank you for your response.
I know how to use broadcasting; that isn’t my question.
My question is, what is the preferred way to write a transform (e.g. the transforms in torchvision that are passed to dataset constructors) such that it operates on a batch of inputs at a time.
It seems that the convention is to apply the transform within the __getitem__() function of the dataset class, but doing it this way means it can’t be parallel.