code: def distance2bbox(points, distance, max_shape=None):
      """Decode distance prediction to bounding box.
      Args:
          points (Tensor): Shape (n, 2), [x, y].
          distance (Tensor): Distance from the given point to 4
              boundaries (left, top, right, bottom).
          max_shape (tuple): Shape of the image.
      Returns:
          Tensor: Decoded bboxes.
      """
      x1 = points[:, 0] - distance[:, 0]
      y1 = points[:, 1] - distance[:, 1]
      x2 = points[:, 0] + distance[:, 2]
      y2 = points[:, 1] + distance[:, 3]
      if max_shape is not None:
          x1 = x1.clip(min=0, max=max_shape[1])
          y1 = y1.clip(min=0, max=max_shape[0])
          x2 = x2.clip(min=0, max=max_shape[1])
          y2 = y2.clip(min=0, max=max_shape[0])
      return paddle.stack([x1, y1, x2, y2], -1)
  
imports: import math
  import paddle
  import numpy
label_desc: Use image node_id 18 for calling a global function with example usage: distance2bbox(points, distance, max_shape) and returns: paddle