>>> pipe.vae.enable_xformers_memory_efficient_attention(attention_op=None)  disable_xformers_memory_efficient_attention  < source > ( )    Disable memory efficient attention from xFormers.  class diffusers.AmusedInpaintPipeline  < source > ( vqvae: VQModel tokenizer: CLIPTokenizer text_encoder: CLIPTextModelWithProjection transformer: UVit2DModel scheduler: AmusedScheduler  )     __call__  < source > ( prompt: Union = None image: Union = None mask_image: Union = None strength: float = 1.0 num_inference_steps: int = 12 guidance_scale: float = 10.0 negative_prompt: Union = None num_images_per_prompt: Optional = 1 generator: Optional = None prompt_embeds: Optional = None encoder_hidden_states: Optional = None negative_prompt_embeds: Optional = None negative_encoder_hidden_states: Optional = None output_type = 'pil' return_dict: bool = True callback: Optional = None callback_steps: int = 1 cross_attention_kwargs: Optional = None micro_conditioning_aesthetic_score: int = 6 micro_conditioning_crop_coord: Tuple = (0, 0) temperature: Union = (2, 0)  ) → ImagePipelineOutput or tuple  Parameters   prompt (str or List[str], optional) —