prop_f = torch.empty([b,c,h,w], device='cuda', requires_grad = False)

prop_f is a tensor that I created , so in theory, it is a leaf.
after that,
prop_f[bb,:, hh, ww] = product

I use prop_f to store some important intermedian variable tensor that are in the computation graph.
So, after that, is prop_f requires grad now?   and could prop_f backward grad when loss.backward()
PS. loss is the loss of the whole model