In pytorch, I want to save the output in every epoch for late caculation. But it leads to OUT OF MEMORY ERROR after several epochs. The code is like below:
L=[]
optimizer.zero_grad()
for i, (input, target) in enumerate(train_loader):
output = model(input)
L.append(output)
*** updata my model to minimize a loss function. List L will be used here.
I know the reason is because pytorch save all computation graphs from every epoch. But the loss function can only be calculated after obtaining all of the prediction results
Is there a way I can train my model?
are you training on a GPU?
If so, you could move it main memory like