Update pipeline.py

pipeline.py

@@ -778,15 +778,16 @@ class AnimateDiffPipeline(DiffusionPipeline, TextualInversionLoaderMixin, IPAdap
             num_digits = output_path.count('#')  # count the number of '#' characters
             frame_format = output_path.replace('#' * num_digits, '{:0' + str(num_digits) + 'd}')
             
-            for start_idx in range(0, num_frames, output_batch_size):
-                end_idx = min(start_idx + output_batch_size, num_frames)
-                video_tensor = self.decode_latents(latents[:, :, start_idx:end_idx, :, :])
+            for batch in range((num_frames + output_batch_size - 1) // output_batch_size):
+                start_id = batch * output_batch_size
+                end_id = min((batch + 1) * output_batch_size, num_frames)
+                video_tensor = self.decode_latents(latents[:, :, start_id:end_id, :, :])
                 video = tensor2vid(video_tensor, self.image_processor, output_type=output_type)
-
-                for batch_idx, frame_batch in enumerate(video[0][0]):
-                    for frame_idx, frame in enumerate(frame_batch):
-                        frame_number = start_idx + batch_idx * len(frame_batch[0][0]) + frame_idx
-                        frame.save(frame_format.format(frame_number))
+                frame_list = video[0][0]
+                print("frame_list type", type(frame_list))
+                for f_id, frame in enumerate(frame_list):
+                    frame_number = start_id + f_id
+                    frame.save(frame_format.format(frame_number))
             return output_path
             
         # Post-processing