+h+SSKJr SSKJrJrJr SSKrSSKr SSK J r \"SS\ 55r \"SS \ 55r g) ) dataclass)ListOptionalUnionN) BaseOutputc\rSrSr%Sr\\\RR\ R4\ S'\ \\ \ S'Srg)LEditsPPDiffusionPipelineOutput u Output class for LEdits++ Diffusion 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)`. nsfw_content_detected (`List[bool]`) List indicating whether the corresponding generated image contains “not-safe-for-work” (nsfw) content or `None` if safety checking could not be performed. imagesnsfw_content_detectedN)__name__ __module__ __qualname____firstlineno____doc__rrPILImagenpndarray__annotations__rbool__static_attributes__rg/home/james-whalen/.local/lib/python3.13/site-packages/diffusers/pipelines/ledits_pp/pipeline_output.pyr r s9  $syy'3 44#DJ//rr c\rSrSr%Sr\\\RR\ R4\ S'\\\RR\ R4\ S'Sr g)LEditsPPInversionPipelineOutputa  Output class for LEdits++ Diffusion pipelines. Args: input_images (`List[PIL.Image.Image]` or `np.ndarray`) List of the cropped and resized input images as PIL images of length `batch_size` or NumPy array of shape ` (batch_size, height, width, num_channels)`. vae_reconstruction_images (`List[PIL.Image.Image]` or `np.ndarray`) List of VAE reconstruction of all input images as PIL images of length `batch_size` or NumPy array of shape ` (batch_size, height, width, num_channels)`. r vae_reconstruction_imagesrN) rrrrrrrrrrrrrrrrrrsK  $syy'3 44$T#))//%:BJJ%FGGrr) dataclassesrtypingrrrnumpyr PIL.Imagerutilsrr rrrrr&sP!(( 0j0 0" HjH Hr