test in latnent upcale

pipeline.py

@@ -872,25 +872,26 @@ class StableDiffusionLongPromptWeightingPipeline(StableDiffusionPipeline):
             # print(latent_model_input)
             print(latent_model_input.shape)
             # predict the noise residual
-            noise_pred = self.unet(latent_model_input, t,
+            upscale_noise_pred = self.unet(latent_model_input, t,
                                    encoder_hidden_states=text_embeddings).sample
             print("noise_pred")
             # print(noise_pred)
-            print(noise_pred.shape)
+            print(upscale_noise_pred.shape)
 
             print("perform guidance")
             # perform guidance
             if do_classifier_free_guidance:
-                noise_pred_uncond, noise_pred_text = noise_pred.chunk(2)
-                noise_pred = noise_pred_uncond + guidance_scale * \
+                noise_pred_uncond, noise_pred_text = upscale_noise_pred.chunk(
+                    2)
+                upscale_noise_pred = noise_pred_uncond + guidance_scale * \
                     (noise_pred_text - noise_pred_uncond)
             print("noise_pred after guidance")
-            print(noise_pred.shape)
-            
+            print(upscale_noise_pred.shape)
+
             print("compute the previous noisy sample")
             # compute the previous noisy sample x_t -> x_t-1
             upscale_latents = self.scheduler.step(
-                noise_pred, t, upscale_latents, **extra_step_kwargs).prev_sample
+                upscale_noise_pred, t, upscale_latents, **extra_step_kwargs).prev_sample
             print(upscale_latents.shape)
 
             print("compute mask")