implemented for all pipelines (downloading, saving, running on a particular device, etc.). The pipeline also inherits the following loading and saving methods: load_textual_inversion() for loading textual inversion embeddings load_lora_weights() for loading LoRA weights save_lora_weights() for saving LoRA weights  generate_mask  < source > ( image: Union = None target_prompt: Union = None target_negative_prompt: Union = None target_prompt_embeds: Optional = None target_negative_prompt_embeds: Optional = None source_prompt: Union = None source_negative_prompt: Union = None source_prompt_embeds: Optional = None source_negative_prompt_embeds: Optional = None num_maps_per_mask: Optional = 10 mask_encode_strength: Optional = 0.5 mask_thresholding_ratio: Optional = 3.0 num_inference_steps: int = 50 guidance_scale: float = 7.5 generator: Union = None output_type: Optional = 'np' cross_attention_kwargs: Optional = None  ) → List[PIL.Image.Image] or np.array  Parameters   image (PIL.Image.Image) —