Update pipeline.py

pipeline.py

@@ -1109,12 +1109,12 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
             controlnet = self.controlnet._orig_mod if is_compiled_module(self.controlnet) else self.controlnet
 
             # align format for control guidance
+            control_end = control_guidance_end
             if not isinstance(control_guidance_start, list) and isinstance(control_guidance_end, list):
                 control_guidance_start = len(control_guidance_end) * [control_guidance_start]
             elif not isinstance(control_guidance_end, list) and isinstance(control_guidance_start, list):
                 control_guidance_end = len(control_guidance_start) * [control_guidance_end]
             elif not isinstance(control_guidance_start, list) and not isinstance(control_guidance_end, list):
-                control_end = control_guidance_end
                 mult = len(controlnet.nets) if isinstance(controlnet, MultiControlNetModel) else 1
                 control_guidance_start, control_guidance_end = (
                     mult * [control_guidance_start],
@@ -1418,8 +1418,6 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
                     # expand the latents if we are doing classifier free guidance
                     latent_model_input = torch.cat([current_context_latents] * 2) if do_classifier_free_guidance else current_context_latents
                     latent_model_input = self.scheduler.scale_model_input(latent_model_input, t)
-                    
-                    control_end_step = int(control_end*num_inference_steps)
 
                     if self.controlnet != None and i < int(control_end*num_inference_steps):