extras-tweaks: autoformat changed lines

        while len(self) > self._max_size:

            self.popitem(last=False)

cached_images: LruCache = LruCache(max_size=5)

    else:

        outpath = opts.outdir_samples or opts.outdir_extras_samples

    # Extra operation definitions

    def run_gfpgan(image: Image.Image, info: str) -> Tuple[Image.Image, str]:

        restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))

        res = Image.fromarray(restored_img)

        info += f"CodeFormer w: {round(codeformer_weight, 2)}, CodeFormer visibility:{round(codeformer_visibility, 2)}\n"

        return (res, info)

    def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop):

        upscaler = shared.sd_upscalers[scaler_index]

        res = upscaler.scaler.upscale(image, resize, upscaler.data_path)

    def run_upscalers_blend(params: List[UpscaleParams], image: Image.Image, info: str) -> Tuple[Image.Image, str]:

        blended_result: Image.Image = None

        for upscaler in params:

            upscale_args = (upscaler.upscaler_idx, upscaling_resize, resize_mode, upscaling_resize_w, upscaling_resize_h, upscaling_crop)

            upscale_args = (upscaler.upscaler_idx, upscaling_resize, resize_mode,

                            upscaling_resize_w, upscaling_resize_h, upscaling_crop)

            cache_key = LruCache.Key(image_hash=hash(np.array(image.getdata()).tobytes()),

                                     info_hash=hash(info),

                                     args_hash=hash(upscale_args + (upscaler.blend_alpha,)))

    extras_ops: List[Callable] = (upscale_ops + facefix_ops) if upscale_first else (facefix_ops + upscale_ops)

    for image, image_name in zip(imageArr, imageNameArr):

        if image is None:

            return outputs, "Please select an input image.", ''