code: def get_point_coords_wrt_box(boxes_coords, point_coords):
      """
      Convert image-level absolute coordinates to box-normalized [0, 1] x [0, 1] point cooordinates.
      Args:
          boxes_coords (Tensor): A tensor of shape (R, 4) that contains bounding boxes.
              coordinates.
          point_coords (Tensor): A tensor of shape (R, P, 2) that contains
              image-normalized coordinates of P sampled points.
      Returns:
          point_coords_wrt_box (Tensor): A tensor of shape (R, P, 2) that contains
              [0, 1] x [0, 1] box-normalized coordinates of the P sampled points.
      """
      with torch.no_grad():
          point_coords_wrt_box = point_coords.clone()
          point_coords_wrt_box[:, :, 0] -= boxes_coords[:, None, 0]
          point_coords_wrt_box[:, :, 1] -= boxes_coords[:, None, 1]
          point_coords_wrt_box[:, :, 0] = point_coords_wrt_box[
              :, :, 0
          ] / (boxes_coords[:, None, 2] - boxes_coords[:, None, 0])
          point_coords_wrt_box[:, :, 1] = point_coords_wrt_box[
              :, :, 1
          ] / (boxes_coords[:, None, 3] - boxes_coords[:, None, 1])
      return point_coords_wrt_box
  
label_desc: Use image node_id 2 for calling a global function with example usage: get_point_coords_wrt_box(boxes_coords, point_coords) and returns: point_coords_wrt_box