Why eval takes more memory?

vision
1

Memory is enough when i’m training the net, and i save the model.when i load the trained model and test, the code raise ‘out of memory’
train:batch_size=8. test:batch_size=1
i used eval() and ‘with torch.no_grad():’

In addition, I used 2 GPUs for training and testing in the code, but it only called one GPU’s memory when testing

2

Does your validation loop yield the OOM directly during the first iteration or after a few iterations?
Could you post a (small) code snippet, which shows how you are using the training and validation loop?

3

i have solved it,anyway,tks!!