def xywh2xyxy(xywh: "torch.Tensor") -> "torch.Tensor":
        """
        Convert the representation from xywh format yo xyxy format.

        :param xyhw: An n by 4 boxes store the information in xyhw format
                     where [x ,y, w h] is [center_x, center_y, width, height]
        :return: The n by 4 boxes in xyxy format
                 where [x1, y1, x2, y2] is [top_left_x, top_left_y, bottom_right_x,  bottom_right_y]
        """
        xyxy = xywh.clone()
        xyxy[:, 0] = xywh[:, 0] - xywh[:, 2] / 2
        xyxy[:, 1] = xywh[:, 1] - xywh[:, 3] / 2
        xyxy[:, 2] = xywh[:, 0] + xywh[:, 2] / 2
        xyxy[:, 3] = xywh[:, 1] + xywh[:, 3] / 2
        return xyxy

        Convert the representation from xywh format yo xyxy format.

        :param xyhw: An n by 4 boxes store the information in xyhw format
                     where [x ,y, w h] is [center_x, center_y, width, height]
        :return: The n by 4 boxes in xyxy format
                 where [x1, y1, x2, y2] is [top_left_x, top_left_y, bottom_right_x,  bottom_right_y]
        
art/attacks/evasion/overload/overload.py