o Û·i™ã@shddlmZddlZddlZddlZddlmZm Z e e ƒZ eGdd„deƒƒZ eGdd„deƒƒZ dS)é)Ú dataclassN)Ú BaseOutputÚ get_loggerc@seZdZUdZejed<dS)ÚCosmosPipelineOutputaà 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)`. ÚframesN)Ú__name__Ú __module__Ú __qualname__Ú__doc__ÚtorchÚTensorÚ__annotations__©rrú`/home/ubuntu/vllm_env/lib/python3.10/site-packages/diffusers/pipelines/cosmos/pipeline_output.pyr s  rc@s(eZdZUdZeejjejBe d<dS)ÚCosmosImagePipelineOutputa^ 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. ÚimagesN) rrr r ÚlistÚPILÚImageÚnpÚndarrayr rrrrrs  r)Ú dataclassesrÚnumpyrÚ PIL.Imagerr Údiffusers.utilsrrrÚloggerrrrrrrÚs