Well, It’s not a matter of post-processing or speed up. In sample words:
I have ie 1000 files (dataset).
I want that my dataloader opens (ie) 2 of these files (randomly) and sum them. This sum is what i will feed the net with, so in the end my net will percive there are 1000/2 = 500 samples.  A batch have to be done of sums (but not raw files)
The matter is I don’t know what is the proper way to do this in pytorch. I can roughly emulate this behavior but I would like to know if pytorch framework is prepared to do this is a easy way.