Hi @ptrblck
Thank you for your quick response!
Can you please address to my specific problem? I read the comment you tagged me in but I have done all is written there. I’m using the Pytorch Dataloader (without any unnecessary for loops). How can I be sure what is the main cause of this problem? When I use htop in terminal all the six processors assigned to the mission are loaded with work but the GPU stays in ~600-700MB capacity regardless to the batch size (which increased to 2048 at the most). This is the reason why I suspect that the preprocess part is the bottleneck in this example.  Just to mention no augmentations where preformed only reading, normalizing and converting to tensor.