Hi,
Suppose there is a case like this:
x1, x2, lb1, lb2 = dataloader.next
logits1 = model(x1)
logits2 = model(x2)
loss = criteria1(logits1, lb1) + criteria2(logits2, lb2)
...

The problem is that I need to update bn moving average status only on x1, and I do not need to update the moving average status on other forward computations. How could I do this with pytorch?