I am going through the DCGAN tutorials tutorials.
One question I have is how do you turn off the gradient history tracking for discriminator when you are training the generator. In the tutorial, it is not turned off as shown below.
... # this part trains generator netG.zero_grad() label.fill_(real_label) # fake labels are real for generator cost # Since we just updated D, perform another forward pass of all-fake batch through D output = netD(fake).view(-1) # Calculate G's loss based on this output errG = criterion(output, label) # Calculate gradients for G errG.backward() ...
I see the grad tracking is turned off for generator when training the discriminator by calling detach on fake image. But not the other way around. Thanks in advance for your help