code: def change_order(bboxes):
      """Change bounding box encoding order.
  
      TensorFlow works with the (y_min, x_min, y_max, x_max) order while we work
      with the (x_min, y_min, x_max, y_min).
  
      While both encoding options have its advantages and disadvantages we
      decided to use the (x_min, y_min, x_max, y_min), forcing use to switch to
      TensorFlow's every time we want to use a std function that handles bounding
      boxes.
  
      Args:
          bboxes: A Tensor of shape (total_bboxes, 4)
  
      Returns:
          bboxes: A Tensor of shape (total_bboxes, 4) with the order swaped.
      """
      with tf.name_scope("BoundingBoxTransform/change_order"):
          first_min, second_min, first_max, second_max = tf.unstack(
              bboxes, axis=1
          )
          bboxes = tf.stack(
              [second_min, first_min, second_max, first_max], axis=1
          )
          return bboxes
  
imports: import tensorflow
label_desc: Use image node_id 5 for calling a global function with example usage: change_order(bboxes) and returns: bboxes