Hi,
I am doing some GAN research and I am running into a problem with memory efficiency.
My both networks together have a size of around 50 MB. However, training with batches of size 3 already uses all of my GPU memory, i.e. 12 GB. The input consists of 512 x 512 images concatenated with some binary masks. I am aware that autograd needs to keep track of additional things for the backward pass, but it just seems a little bit too much for me.
I couldn’t find any useful memory efficiency tips, so any advice would be appreciated.
Thanks!