Update pipeline.py

pipeline.py

@@ -691,12 +691,7 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
                 shape = shape
                 # shape = (1,) + shape[1:]
                 # ignore init latents for batch model
-                latents = [
-                    torch.randn(
-                        shape, generator=generator[i], device=rand_device, dtype=dtype
-                    )
-                    for i in range(batch_size)
-                ]
+                latents = [torch.randn(shape, generator=generator[i], device=rand_device, dtype=dtype)for i in range(batch_size)]
                 latents = torch.cat(latents, dim=0).to(device)
             else:
                 if init_latents is not None:
@@ -943,7 +938,7 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
         #     y_velocity=y_velocity,
         #     scale_velocity=scale_velocity,
         # )
-        _,latents = self.prepare_correlated_latents(
+        latents, init_latents = self.prepare_correlated_latents(
             init_image,
             init_image_strength,
             init_noise_correlation,
@@ -956,6 +951,8 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
             device,
             generator,
         )
+        print(type(latents), hasattr(latents, 'shape') and latents.shape)
+
 
         # 6. Prepare extra step kwargs. TODO: Logic should ideally just be moved out of the pipeline
         extra_step_kwargs = self.prepare_extra_step_kwargs(generator, eta)