Ë ¢Ùbiãó„—ddlmZddlmZmZddlZddlZddl Z ddl m Z eGd„de ««Z eGd„d e ««Z y) é)Ú dataclass)ÚListÚUnionNé)Ú BaseOutputcóh—eZdZUdZeeejjejfe d<y)ÚFluxPipelineOutputa Output class for Flux image generation pipelines. Args: images (`List[PIL.Image.Image]` or `torch.Tensor` or `np.ndarray`) List of denoised PIL images of length `batch_size` or numpy array or torch tensor of shape `(batch_size, height, width, num_channels)`. PIL images or numpy array present the denoised images of the diffusion pipeline. Torch tensors can represent either the denoised images or the intermediate latents ready to be passed to the decoder. ÚimagesN) Ú__name__Ú __module__Ú __qualname__Ú__doc__rrÚPILÚImageÚnpÚndarrayÚ__annotations__©óúc/home/cdr/jupyterlab/.venv/lib/python3.12/site-packages/diffusers/pipelines/flux/pipeline_output.pyr r s*…ñ ð $s—y‘y—‘Ñ'¨¯©Ð3Ñ 4Ô4rr cóN—eZdZUdZej ed<ej ed<y)ÚFluxPriorReduxPipelineOutputa[ Output class for Flux Prior Redux 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. Ú prompt_embedsÚpooled_prompt_embedsN)r r r rÚtorchÚTensorrrrrrrs…ñð—<‘<ÓØŸ,™,Ô&rr)Ú dataclassesrÚtypingrrÚnumpyrÚ PIL.ImagerrÚutilsrr rrrrúr"sMðÝ!ßãÛÛ åð ô 5˜ó 5ó ð 5ð ô ' :ó 'ó ñ 'r