off by one

diffusion.py

@@ -195,7 +195,7 @@ class GaussianDiffusion:
       for t in it:
         temp_image = self.denormalize_image(torch.clip(x, -1, 1)).clone().squeeze(0)
         if cb is not None:
-          cb(temp_image, 1-t/(self.noise_steps-1))
+          cb(temp_image, 1-t/(self.noise_steps+1))
         image_versions.append(self.denormalize_image(torch.clip(x, -1, 1)).clone().squeeze(0))
         
         if x0 is not None and t > 80: