utils/mytransforms.py [55:87]:
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        super().__init__()
        self.size = _setup_size(size, error_msg="Please provide only two dimensions (h, w) for size.")

        if not isinstance(scale, Sequence):
            raise TypeError("Scale should be a sequence")
        if not isinstance(ratio, Sequence):
            raise TypeError("Ratio should be a sequence")
        if (scale[0] > scale[1]) or (ratio[0] > ratio[1]):
            warnings.warn("Scale and ratio should be of kind (min, max)")

        self.interpolation = interpolation
        self.scale = scale
        self.ratio = ratio

    @staticmethod
    def get_params(
            img: Tensor, scale: List[float], ratio: List[float]
    ) -> Tuple[int, int, int, int]:
        """Get parameters for ``crop`` for a random sized crop, always centered

        Args:
            img (PIL Image or Tensor): Input image.
            scale (list): range of scale of the origin size cropped
            ratio (list): range of aspect ratio of the origin aspect ratio cropped

        Returns:
            tuple: params (i, j, h, w) to be passed to ``crop`` for a random
                sized crop.
        """
        width, height = F._get_image_size(img)
        area = height * width

        for _ in range(10):
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utils/mytransforms.py [143:165]:
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        super().__init__()
        self.size = _setup_size(size, error_msg="Please provide only two dimensions (h, w) for size.")

        if not isinstance(scale, Sequence):
            raise TypeError("Scale should be a sequence")
        if not isinstance(ratio, Sequence):
            raise TypeError("Ratio should be a sequence")
        if (scale[0] > scale[1]) or (ratio[0] > ratio[1]):
            warnings.warn("Scale and ratio should be of kind (min, max)")

        self.interpolation = interpolation
        self.scale = scale
        self.ratio = ratio

    @staticmethod
    def get_params(
            img: Tensor, scale: List[float], ratio: List[float]
    ) -> Tuple[int, int, int, int]:

        width, height = F._get_image_size(img)
        area = height * width

        for _ in range(10):
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