hmmm but for real data sets each of them will have their own data transforms e.g. their own mean, std to normalize the images. How do you deal with that? I’d assume this is dealt at the each data set level by giving them the right transforms when instantiating the data set pytorch object.
I think this: Concat image datasets with different size and number of channels answers my question. Which my suggestion was right.