Is it possible for the following updates happen?
for loop:
  y1 = nn.Module.sigmoid(x)
  y_list.append(y1.data[0][0])
prob = nn.Module.Softmax(y_list)
choices = prob.Multinomial()

and then:
autograd.backward(choices, [None for _ in choices])
I wanna backpropagate like that, but I got the following error:
RuntimeError: there are no graph nodes that require computing gradients
I think that y_list.append is the reason for that error, (graph is broken?)  is that right? If not, then why?
Thanks a lot
update: I misunderstood with .data , now I’ve solved it.