class_docstr: iou loss, see https://arxiv.org/abs/1908.03851
  loss = 1.0 - iou * iou
  Args:
      loss_weight (float): iou loss weight, default is 2.5
      max_height (int): max height of input to support random shape input
      max_width (int): max width of input to support random shape input
      ciou_term (bool): whether to add ciou_term
      loss_square (bool): whether to square the iou term
code: def __call__(self, pbox, gbox):
      iou = bbox_iou(
          pbox, gbox, giou=self.giou, diou=self.diou, ciou=self.ciou
      )
      if self.loss_square:
          loss_iou = 1 - iou * iou
      else:
          loss_iou = 1 - iou
  
      loss_iou = loss_iou * self.loss_weight
      return loss_iou
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import math
  import paddle
  from ppdet.core.workspace import register, serializable
  from ..bbox_utils import bbox_iou
label_desc: Use image node_id 2 for calling the IouLoss obj's underlying member method code with example usage: obj.__call__(pbox, gbox) and returns: loss_iou