+hSSKJr SSKJrJr SSKrSSKrSSK r SSK J r J r \ "\ 5r\"SS\ 55r\"SS\ 55rg) ) dataclass)ListUnionN) BaseOutput get_loggerc8\rSrSr%Sr\R \S'Srg)CosmosPipelineOutputa Output class for Cosmos any-to-world/video 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)`. framesN) __name__ __module__ __qualname____firstlineno____doc__torchTensor__annotations____static_attributes__r d/home/james-whalen/.local/lib/python3.13/site-packages/diffusers/pipelines/cosmos/pipeline_output.pyr r s LLrr cp\rSrSr%Sr\\\RR\ R4\ S'Sr g)CosmosImagePipelineOutputaF Output class for Cosmos any-to-image pipelines. Args: images (`List[PIL.Image.Image]` or `np.ndarray`) List of denoised PIL images of length `batch_size` or numpy array of shape `(batch_size, height, width, num_channels)`. PIL images or numpy array present the denoised images of the diffusion pipeline. imagesr N) r rrrrrrPILImagenpndarrayrrr rrrrs* $syy'3 44rr) dataclassesrtypingrrnumpyr PIL.Imagerrdiffusers.utilsrrr loggerr rr rrr&sY! 2 H   :     5 5  5r