o ۷i@sTddlmZddlZddlZddlmZeGdddeZeGdddeZ dS) ) dataclassN) BaseOutputc@s8eZdZUdZeejjejBe d<ee dBe d<dS)LEditsPPDiffusionPipelineOutputu 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. imagesNnsfw_content_detected) __name__ __module__ __qualname____doc__listPILImagenpndarray__annotations__boolrrc/home/ubuntu/vllm_env/lib/python3.10/site-packages/diffusers/pipelines/ledits_pp/pipeline_output.pyr s  rc@s>eZdZUdZeejjejBe d<eejjejBe d<dS)LEditsPPInversionPipelineOutputa0 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)`. rvae_reconstruction_imagesN) rr r r r r rrrrrrrrrs  r) dataclassesrnumpyr PIL.Imager utilsrrrrrrrs