Update pipeline.py

pipeline.py

@@ -1036,8 +1036,6 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
                 
         context_indexes = context_scheduler(context_size, overlap, step, num_frames, len(timesteps))
         
-        print(f"Context indexes: {context_indexes}")
-        
         # Denoising loop
         num_warmup_steps = len(timesteps) - num_inference_steps * self.scheduler.order
         with self.progress_bar(total=len(timesteps)) as progress_bar:
@@ -1079,13 +1077,19 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
 
                     # set the step index to the current batch
                     self.scheduler._step_index = i
-                    
+                
+                print("latent_counter", latent_counter)
+                print("current_context_indexes", current_context_indexes)
+                
                 # perform guidance
                 if do_classifier_free_guidance:
                     latent_counter = latent_counter.reshape(1, 1, num_frames, 1, 1)
                     noise_pred_uncond = noise_pred_uncond_sum / latent_counter
                     noise_pred_text = noise_pred_text_sum / latent_counter
                     noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
+                
+                # print min and max
+                print("noise_pred: ", noise_pred.min(), noise_pred.max())
                     
                 # compute the previous noisy sample x_t -> x_t-1
                 latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample