Hello,
I working on a huge and complicated pytorch model to solve PDEs using torch geometric graphs and so on, I do computations on GPU RTX3090, but when I lunch the training I have memory error , I start searching, one of the thing I remarked is that when calculating error if I store it as a scalr instead of a tensor I use much less memory, but I convert it to a tensor just before calling backward() , but the problem is that in this case the training in starting but with no change from an epoch to an other.
here is the training loop:
an the epochs:
Is there a way to resolve this, remmeber my forst problem is cuda memory error.
thanks