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from dataclasses import dataclass |
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import torch |
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from diffusers.utils import BaseOutput |
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@dataclass |
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class MochiPipelineOutput(BaseOutput): |
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r""" |
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Output class for Mochi pipelines. |
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Args: |
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frames (`torch.Tensor`, `np.ndarray`, or List[List[PIL.Image.Image]]): |
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List of video outputs - It can be a nested list of length `batch_size,` with each sub-list containing |
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denoised PIL image sequences of length `num_frames.` It can also be a NumPy array or Torch tensor of shape |
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`(batch_size, num_frames, channels, height, width)`. |
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""" |
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frames: torch.Tensor |
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