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Running
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Zero
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from dataclasses import dataclass
from typing import List, Union
import numpy as np
import PIL.Image
import torch
from diffusers.utils import BaseOutput
@dataclass
class HunyuanVideoPipelineOutput(BaseOutput):
r"""
Output class for HunyuanVideo 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
@dataclass
class HunyuanVideoFramepackPipelineOutput(BaseOutput):
r"""
Output class for HunyuanVideo 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)`. Or, a list of torch tensors where each tensor
corresponds to a latent that decodes to multiple frames.
"""
frames: Union[torch.Tensor, np.ndarray, List[List[PIL.Image.Image]], List[torch.Tensor]]
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