Update pipeline.py

pipeline.py

@@ -561,16 +561,15 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
 
         # scale the initial noise by the standard deviation required by the scheduler
         latents = latents * self.scheduler.init_noise_sigma
-
-        # Apply motion and scale dynamics
+        
         for frame in range(num_frames):
-            x_offset = frame * x_velocity
-            y_offset = frame * y_velocity
+            x_offset = int(frame * x_velocity)  # Convert to int
+            y_offset = int(frame * y_velocity)  # Convert to int
             scale_factor = 1 + frame * scale_velocity
 
             # Apply offsets
-            latents[:, :, frame] = torch.roll(latents[:, :, frame], shifts=x_offset, dims=3)  # x direction
-            latents[:, :, frame] = torch.roll(latents[:, :, frame], shifts=y_offset, dims=2)  # y direction
+            latents[:, :, frame] = torch.roll(latents[:, :, frame], shifts=(x_offset,), dims=3)  # x direction
+            latents[:, :, frame] = torch.roll(latents[:, :, frame], shifts=(y_offset,), dims=2)  # y direction
 
             # Apply scaling - This is a simple approach and might not be ideal for all applications
             if scale_factor != 1: