def resize(
        self,
        image: np.ndarray,
        size: Dict[str, int],
        crop_pct: float,
        resample: PILImageResampling = PILImageResampling.BICUBIC,
        data_format: Optional[Union[str, ChannelDimension]] = None,
        input_data_format: Optional[Union[str, ChannelDimension]] = None,
        **kwargs,
    ) -> np.ndarray:
        """
        Resize an image.

        Args:
            image (`np.ndarray`):
                Image to resize.
            size (`Dict[str, int]`):
                Dictionary of the form `{"shortest_edge": int}`, specifying the size of the output image. If
                `size["shortest_edge"]` >= 384 image is resized to `(size["shortest_edge"], size["shortest_edge"])`.
                Otherwise, the smaller edge of the image will be matched to `int(size["shortest_edge"] / crop_pct)`,
                after which the image is cropped to `(size["shortest_edge"], size["shortest_edge"])`.
            crop_pct (`float`):
                Percentage of the image to crop. Only has an effect if size < 384.
            resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BICUBIC`):
                Resampling filter to use when resizing the image.
            data_format (`str` or `ChannelDimension`, *optional*):
                The channel dimension format of the image. If not provided, it will be the same as the input image.
            input_data_format (`ChannelDimension` or `str`, *optional*):
                The channel dimension format of the input image. If not provided, it will be inferred from the input
                image.
        """
        size = get_size_dict(size, default_to_square=False)
        if "shortest_edge" not in size:
            raise ValueError(f"Size dictionary must contain 'shortest_edge' key. Got {size.keys()}")
        shortest_edge = size["shortest_edge"]

        if shortest_edge < 384:
            # maintain same ratio, resizing shortest edge to shortest_edge/crop_pct
            resize_shortest_edge = int(shortest_edge / crop_pct)
            resize_size = get_resize_output_image_size(
                image, size=resize_shortest_edge, default_to_square=False, input_data_format=input_data_format
            )
            image = resize(
                image=image,
                size=resize_size,
                resample=resample,
                data_format=data_format,
                input_data_format=input_data_format,
                **kwargs,
            )
            # then crop to (shortest_edge, shortest_edge)
            return center_crop(
                image=image,
                size=(shortest_edge, shortest_edge),
                data_format=data_format,
                input_data_format=input_data_format,
                **kwargs,
            )
        else:
            # warping (no cropping) when evaluated at 384 or larger
            return resize(
                image,
                size=(shortest_edge, shortest_edge),
                resample=resample,
                data_format=data_format,
                input_data_format=input_data_format,
                **kwargs,
            )

        Resize an image.

        Args:
            image (`np.ndarray`):
                Image to resize.
            size (`Dict[str, int]`):
                Dictionary of the form `{"shortest_edge": int}`, specifying the size of the output image. If
                `size["shortest_edge"]` >= 384 image is resized to `(size["shortest_edge"], size["shortest_edge"])`.
                Otherwise, the smaller edge of the image will be matched to `int(size["shortest_edge"] / crop_pct)`,
                after which the image is cropped to `(size["shortest_edge"], size["shortest_edge"])`.
            crop_pct (`float`):
                Percentage of the image to crop. Only has an effect if size < 384.
            resample (`PILImageResampling`, *optional*, defaults to `PILImageResampling.BICUBIC`):
                Resampling filter to use when resizing the image.
            data_format (`str` or `ChannelDimension`, *optional*):
                The channel dimension format of the image. If not provided, it will be the same as the input image.
            input_data_format (`ChannelDimension` or `str`, *optional*):
                The channel dimension format of the input image. If not provided, it will be inferred from the input
                image.
        
dpkd/transformers/src/transformers/models/convnext/image_processing_convnext.py