Update pipeline.py

pipeline.py

@@ -1059,10 +1059,6 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
                         noise_pred_uncond_sum[:, :, current_context_start : current_context_start + context_size, :, :] += noise_pred_uncond
                         noise_pred_text_sum[:, :, current_context_start : current_context_start + context_size, :, :] += noise_pred_text
                         latent_counter[current_context_start : current_context_start + context_size] += 1
-                        
-                        # print min and max values of noise_pred_uncond_sum and noise_pred_text_sum
-                        print(f"noise_pred_uncond_sum min: {noise_pred_uncond_sum.min()} max: {noise_pred_uncond_sum.max()}")
-                        print(f"noise_pred_text_sum min: {noise_pred_text_sum.min()} max: {noise_pred_text_sum.max()}")
 
                     # set the step index to the current batch
                     self.scheduler._step_index = i
@@ -1076,7 +1072,6 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
                     
                 # compute the previous noisy sample x_t -> x_t-1
                 latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample
-                print(f"latents min: {latents.min()} max: {latents.max()}")
                 
                 # call the callback, if provided
                 if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):