| | from dataclasses import dataclass |
| |
|
| | import torch |
| |
|
| | from diffusers.utils import BaseOutput |
| |
|
| |
|
| | @dataclass |
| | class LTXPipelineOutput(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)`. |
| | """ |
| |
|
| | frames: torch.Tensor |
| |
|