Update pipeline.py

pipeline.py

@@ -1189,7 +1189,7 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
             # to avoid doing two forward passes
             if do_classifier_free_guidance:
                 # concatenate negative prompt embeddings with prompt embeddings on a new dimension after the first batch dimension
-                single_prompt_embeds = torch.stack([single_negative_prompt_embeds, single_prompt_embeds], dim=1)
+                single_prompt_embeds = torch.stack([single_negative_prompt_embeds, single_prompt_embeds], dim=0)
     
             prompt_embeds_list.append(single_prompt_embeds)
             
@@ -1437,6 +1437,8 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
                     context_position = current_context_indexes[0] % context_size
                     current_prompt_index =  int(context_position / (context_size / num_prompts))
                     
+                    # print shape
+                    print(prompt_embeds_list[current_prompt_index].shape)
                     # print min and max values of the current prompt embed
                     print("avg", torch.mean(prompt_embeds_list[current_prompt_index][1]))