Hi everyone!
I am new in PyTorch and I constantly have to solve problems with memory.

Why does my data loader (for train) eat so much memory?
How can I care about memory when I use data loader for train/validation?
Is it necessary to point “volatile” in inputs and targets and it will help?
Should I use cuda.empty_cache() between two epochs? Or maybe any others?
I noticed that volatile flag has been removed in master. Why?

Thanks in advance!