Extract feature maps from intermediate layers without modifying forward()

[smth]

There are many examples in this thread:

Why cant I see .grad of an intermediate variable?

Hi! I am loving this framework… Since Im a noob, I am probably not getting something, but I am wondering why I cant get the gradient of an intermediate variable with .grad? Here is an example of what I mean: xx = Variable(torch.randn(1,1), requires_grad = True) yy = 3*xx zz = yy**2 zz.backward() xx.grad # This is ok yy.grad # This gives 0! zz.grad # This should give 1! So I get the correct result for xx.grad, but why does yy.grad show 0, as does zz.grad? How can I get the yy.grad value in t…

Also a search will give you a few more examples:

https://discuss.pytorch.org/search?q=register_hook