Pretty much the question in the title.
Someone asked this a year ago, but I think they did not receive a satisfying answer. None of the official pytorch examples use clean code.
For example, the pytorch DataLoader uses a batchsize parameter, but if someone writes their transformations in their dataset class, then that batchsize parameter is no longer adhered to, because the dataloader would then be generating a batch of size batchsize*however_many_transformations_are_applied_to_a_single_sample
Certainly this must have been thought of, so can someone please point me in the direction of a tutorial or example that addresses this discrepancy?
thanks!