Update pipeline.py

pipeline.py

@@ -143,12 +143,10 @@ def tensor2vid(video: torch.Tensor, processor, output_type="np"):
 
     return outputs
 
-
 @dataclass
 class AnimateDiffPipelineOutput(BaseOutput):
     frames: Union[torch.Tensor, np.ndarray]
 
-
 class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdapterMixin, LoraLoaderMixin):
     r"""
     Pipeline for text-to-video generation.
@@ -200,29 +198,17 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
         super().__init__()
         unet = UNetMotionModel.from_unet2d(unet, motion_adapter)
 
-        if controlnet is None:
-            self.register_modules(
-                vae=vae,
-                text_encoder=text_encoder,
-                tokenizer=tokenizer,
-                unet=unet,
-                motion_adapter=motion_adapter,
-                scheduler=scheduler,
-                feature_extractor=feature_extractor,
-                image_encoder=image_encoder,
-            )
-        else:
-            self.register_modules(
-                vae=vae,
-                text_encoder=text_encoder,
-                tokenizer=tokenizer,
-                unet=unet,
-                motion_adapter=motion_adapter,
-                controlnet=controlnet,
-                scheduler=scheduler,
-                feature_extractor=feature_extractor,
-                image_encoder=image_encoder,
-            )
+        self.register_modules(
+            vae=vae,
+            text_encoder=text_encoder,
+            tokenizer=tokenizer,
+            unet=unet,
+            motion_adapter=motion_adapter,
+            controlnet=controlnet,
+            scheduler=scheduler,
+            feature_extractor=feature_extractor,
+            image_encoder=image_encoder,
+        )
         self.vae_scale_factor = 2 ** (len(self.vae.config.block_out_channels) - 1)
         self.image_processor = VaeImageProcessor(vae_scale_factor=self.vae_scale_factor)
         self.control_image_processor = VaeImageProcessor(