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from dataclasses import dataclass
import torch
from diffusers.utils import BaseOutput
@dataclass
class LTX2PipelineOutput(BaseOutput):
r"""
Output class for LTX 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)`.
audio (`torch.Tensor`, `np.ndarray`):
TODO
"""
frames: torch.Tensor
audio: torch.Tensor