test change return

pipeline.py

@@ -1151,7 +1151,7 @@ class StableDiffusionLongPromptWeightingPipeline(StableDiffusionPipeline):
                         negative_prompt: Optional[Union[str, List[str]]] = None,
                         height: int = 512,
                         width: int = 512,
-                        num_inference_steps: int = 50,
+                        num_inference_steps: int = 20,
                         num_inference_steps_upscale: int = 20,
                         guidance_scale: float = 7.5,
                         strength: float = 0.6,
@@ -1186,22 +1186,22 @@ class StableDiffusionLongPromptWeightingPipeline(StableDiffusionPipeline):
         )
         image_tensor = torch.from_numpy(image.images[0])
 
-        resized_image = torch.nn.functional.interpolate(
-            image_tensor, size=(int(height*resize_scale), int(width*resize_scale)))
-
-        highres_image = self.__call__(prompt=prompt,
-                                      negative_prompt=negative_prompt,
-                                      image=resized_image,
-                                      num_inference_steps=num_inference_steps,
-                                      guidance_scale=guidance_scale,
-                                      strength=strength,
-                                      num_images_per_prompt=num_images_per_prompt,
-                                      eta=eta,
-                                      generator=generator,
-                                      max_embeddings_multiples=max_embeddings_multiples,
-                                      output_type=output_type,
-                                      return_dict=return_dict,
-                                      callback=callback,
-                                      is_cancelled_callback=is_cancelled_callback,
-                                      callback_steps=callback_steps,)
-        return highres_image
+        # resized_image = torch.nn.functional.interpolate(
+        #     image_tensor, size=(int(height*resize_scale), int(width*resize_scale)))
+
+        # highres_image = self.__call__(prompt=prompt,
+        #                               negative_prompt=negative_prompt,
+        #                               image=resized_image,
+        #                               num_inference_steps=num_inference_steps_upscale,
+        #                               guidance_scale=guidance_scale,
+        #                               strength=strength,
+        #                               num_images_per_prompt=num_images_per_prompt,
+        #                               eta=eta,
+        #                               generator=generator,
+        #                               max_embeddings_multiples=max_embeddings_multiples,
+        #                               output_type=output_type,
+        #                               return_dict=return_dict,
+        #                               callback=callback,
+        #                               is_cancelled_callback=is_cancelled_callback,
+        #                               callback_steps=callback_steps,)
+        return image