Reported by a user (@kenza-bouzid) here:

When using num_workers>1 and pin_memory=True, training time increases exponentially over epochs


I had profiled/timed all intermediate steps, and found out that GridPatch was the guilty one

So I timed all intermediate step in the tranform

It turned out that the operation that was taking too long was a memory allocation by np.array

I eventually fixed it by setting pin_memory=False,
which I explain by cuda memory allocation being more expensive as it has to be allocated from the pinned memory

Note that I am dealing with particularly large slides ~50kx50k

Any thoughts on this?