How to fix this strange error: “RuntimeError: CUDA error: out of memory”

Question

I ran a code about the deep learning network,first I trained the network,and it works well,but this error occurs when running to the validate network.

I have five epoch,

Answer 1

1.. When you only perform validation not training,
you don't need to calculate gradients for forward and backward phase.
In that situation, your code can be located under

with torch.no_grad():
    ...
    net=Net()
    pred_for_validation=net(input)
    ...

Above code doesn't use GPU memory

2.. If you use += operator in your code,
it can accumulate gradient continuously in your gradient graph.
In that case, you need to use float() like following site
https://pytorch.org/docs/stable/notes/faq.html#my-model-reports-cuda-runtime-error-2-out-of-memory

Even if docs guides with float(), in case of me, item() also worked like

entire_loss=0.0
for i in range(100):
    one_loss=loss_function(prediction,label)
    entire_loss+=one_loss.item()

3.. If you use for loop in training code,
data can be sustained until entire for loop ends.
So, in that case, you can explicitly delete variables after performing optimizer.step()

for one_epoch in range(100):
    ...
    optimizer.step()
    del intermediate_variable1,intermediate_variable2,...