Fix merge

pipeline_glide.py

@@ -895,13 +895,17 @@ class GLIDE(DiffusionPipeline):
                 noise_residual, pred_variance = torch.split(model_output, 3, dim=1)
 
             # 2. predict previous mean of image x_t-1
-            pred_prev_image = self.upscale_noise_scheduler.step(noise_residual, image, t, num_inference_steps_upscale, eta)
+            pred_prev_image = self.upscale_noise_scheduler.step(
+                noise_residual, image, t, num_inference_steps_upscale, eta
+            )
 
             # 3. optionally sample variance
             variance = 0
             if eta > 0:
                 noise = torch.randn(image.shape, generator=generator).to(image.device)
-                variance = self.upscale_noise_scheduler.get_variance(t, num_inference_steps_upscale).sqrt() * eta * noise
+                variance = (
+                    self.upscale_noise_scheduler.get_variance(t, num_inference_steps_upscale).sqrt() * eta * noise
+                )
 
             # 4. set current image to prev_image: x_t -> x_t-1
             image = pred_prev_image + variance