Fix bug with discriminator noise addition

It wasn't using the scale and was applying the noise to the
underlying state variable.

codes/models/steps/losses.py

@@ -137,10 +137,17 @@ class DiscriminatorGanLoss(ConfigurableLoss):
         fake = extract_params_from_state(self.opt['fake'], state)
         fake = [f.detach() for f in fake]
         if self.noise:
-            # An assumption is made that the first input to the discriminator is what we want to add noise to. If not,
-            # use a explicit formulation of adding noise (using an injector)
-            real[0] += torch.randn_like(real[0])
-            fake[0] += torch.randn_like(fake[0])
+            nreal = []
+            nfake = []
+            for i, t in enumerate(real):
+                if isinstance(t, torch.Tensor):
+                    nreal.append(t + torch.randn_like(t) * self.noise)
+                    nfake.append(fake[i] + torch.randn_like(t) * self.noise)
+                else:
+                    nreal.append(t)
+                    nfake.append(fake[i])
+            real = nreal
+            fake = nfake
         d_real = net(*real)
         d_fake = net(*fake)