def img2img(
        self,
        prompt: str = None,
        prompt_2: Optional[str] = None,
        image: Optional[PipelineImageInput] = None,
        height: Optional[int] = None,
        width: Optional[int] = None,
        strength: float = 0.8,
        num_inference_steps: int = 50,
        timesteps: List[int] = None,
        denoising_start: Optional[float] = None,
        denoising_end: Optional[float] = None,
        guidance_scale: float = 5.0,
        negative_prompt: Optional[str] = None,
        negative_prompt_2: Optional[str] = None,
        num_images_per_prompt: Optional[int] = 1,
        eta: float = 0.0,
        generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None,
        latents: Optional[torch.Tensor] = None,
        ip_adapter_image: Optional[PipelineImageInput] = None,
        prompt_embeds: Optional[torch.Tensor] = None,
        negative_prompt_embeds: Optional[torch.Tensor] = None,
        pooled_prompt_embeds: Optional[torch.Tensor] = None,
        negative_pooled_prompt_embeds: Optional[torch.Tensor] = None,
        output_type: Optional[str] = "pil",
        return_dict: bool = True,
        cross_attention_kwargs: Optional[Dict[str, Any]] = None,
        guidance_rescale: float = 0.0,
        original_size: Optional[Tuple[int, int]] = None,
        crops_coords_top_left: Tuple[int, int] = (0, 0),
        target_size: Optional[Tuple[int, int]] = None,
        clip_skip: Optional[int] = None,
        callback_on_step_end: Optional[Callable[[int, int, Dict], None]] = None,
        callback_on_step_end_tensor_inputs: List[str] = ["latents"],
        **kwargs,
    ):
        r"""
        Function invoked when calling pipeline for image-to-image.

        Refer to the documentation of the `__call__` method for parameter descriptions.
        """
        return self.__call__(
            prompt=prompt,
            prompt_2=prompt_2,
            image=image,
            height=height,
            width=width,
            strength=strength,
            num_inference_steps=num_inference_steps,
            timesteps=timesteps,
            denoising_start=denoising_start,
            denoising_end=denoising_end,
            guidance_scale=guidance_scale,
            negative_prompt=negative_prompt,
            negative_prompt_2=negative_prompt_2,
            num_images_per_prompt=num_images_per_prompt,
            eta=eta,
            generator=generator,
            latents=latents,
            ip_adapter_image=ip_adapter_image,
            prompt_embeds=prompt_embeds,
            negative_prompt_embeds=negative_prompt_embeds,
            pooled_prompt_embeds=pooled_prompt_embeds,
            negative_pooled_prompt_embeds=negative_pooled_prompt_embeds,
            output_type=output_type,
            return_dict=return_dict,
            cross_attention_kwargs=cross_attention_kwargs,
            guidance_rescale=guidance_rescale,
            original_size=original_size,
            crops_coords_top_left=crops_coords_top_left,
            target_size=target_size,
            clip_skip=clip_skip,
            callback_on_step_end=callback_on_step_end,
            callback_on_step_end_tensor_inputs=callback_on_step_end_tensor_inputs,
            **kwargs,
        )

        Function invoked when calling pipeline for image-to-image.

        Refer to the documentation of the `__call__` method for parameter descriptions.
        
examples/community/lpw_stable_diffusion_xl.py