diffusers/pipelines/animatediff/pipeline_output.py

from dataclasses import dataclass
from typing import List, Union

import numpy as np
import PIL.Image
import torch

from ...utils import BaseOutput


@dataclass
class AnimateDiffPipelineOutput(BaseOutput):
    r"""

     Output class for AnimateDiff pipelines.



     Args:

         frames (`torch.Tensor`, `np.ndarray`, or List[List[PIL.Image.Image]]):

             List of video outputs - It can be a nested list of length `batch_size,` with each sub-list containing

             denoised

     PIL image sequences of length `num_frames.` It can also be a NumPy array or Torch tensor of shape

    `(batch_size, num_frames, channels, height, width)`

    """

    frames: Union[torch.Tensor, np.ndarray, List[List[PIL.Image.Image]]]