Update pipeline.py

pipeline.py

@@ -1070,7 +1070,7 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
                     noise_pred = noise_pred_uncond + guidance_scale * (noise_pred_text - noise_pred_uncond)
                 
                 # compute the previous noisy sample x_t -> x_t-1
-                current_context_latents = self.scheduler.step(noise_pred, t, current_context_latents, **extra_step_kwargs).prev_sample
+                latents = self.scheduler.step(noise_pred, t, latents, **extra_step_kwargs).prev_sample
                 
                 # call the callback, if provided
                 if i == len(timesteps) - 1 or ((i + 1) > num_warmup_steps and (i + 1) % self.scheduler.order == 0):
@@ -1079,7 +1079,7 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
                         callback(i, t, None)
                 
                 # shuffle rotate latent images by step places, wrapping around the last 2 to the start
-                latents = torch.cat([current_context_latents[:, :, -step:, :, :], current_context_latents[:, :, :-step, :, :]], dim=2)
+                latents = torch.cat([latents[:, :, -step:, :, :], latents[:, :, :-step, :, :]], dim=2)
         
         if output_type == "latent":
             return AnimateDiffPipelineOutput(frames=latents)