Update diffusion.py

diffusion.py

@@ -86,8 +86,8 @@ class Diffusion_cond:
                     print('The sampler {} is not implemented'.format(sampling_mode))
                     break
         model.train() # it goes back to training mode
-        # x = (x.clamp(-1, 1) + 1) / 2 # to be in [-1, 1], the plus 1 and the division by 2 is to bring back values to [0, 1]
-        # x = (x * 255).type(torch.uint8) # to bring in valid pixel range
+        x = (x.clamp(-1, 1) + 1) / 2 # to be in [-1, 1], the plus 1 and the division by 2 is to bring back values to [0, 1]
+        x = (x * 255).type(torch.uint8) # to bring in valid pixel range
         return x
 
 mse = nn.MSELoss()