code: def get_uncertain_point_coords_on_grid(uncertainty_map, num_points):
      """
      Find `num_points` most uncertain points from `uncertainty_map` grid.
  
      Args:
          uncertainty_map (Tensor): A tensor of shape (N, 1, H, W) that contains uncertainty
              values for a set of points on a regular H x W grid.
          num_points (int): The number of points P to select.
  
      Returns:
          point_indices (Tensor): A tensor of shape (N, P) that contains indices from
              [0, H x W) of the most uncertain points.
          point_coords (Tensor): A tensor of shape (N, P, 2) that contains [0, 1] x [0, 1] normalized
              coordinates of the most uncertain points from the H x W grid.
      """
      R, _, H, W = uncertainty_map.shape
      h_step = 1.0 / float(H)
      w_step = 1.0 / float(W)
  
      num_points = min(H * W, num_points)
      point_indices = torch.topk(
          uncertainty_map.view(R, H * W), k=num_points, dim=1
      )[1]
      point_coords = torch.zeros(
          R,
          num_points,
          2,
          dtype=torch.float,
          device=uncertainty_map.device,
      )
      point_coords[:, :, 0] = (
          w_step / 2.0 + (point_indices % W).to(torch.float) * w_step
      )
      point_coords[:, :, 1] = (
          h_step / 2.0 + (point_indices // W).to(torch.float) * h_step
      )
      return point_indices, point_coords
  
file_path: detectron2/projects/PointRend/point_rend/point_features.py
imports: import torch
  from torch.nn import functional
  from detectron2.layers import cat, shapes_to_tensor
  from detectron2.structures import BitMasks, Boxes
label_desc: Use image node_id 4 for calling a global function with example usage: get_uncertain_point_coords_on_grid(uncertainty_map, num_points) and returns: point_indices,  point_coords