code: def setUp(self):
      self.initTestCase()
      x = np.random.uniform(0, 1, self.x_shape).astype("float64")
      gtbox = np.random.random(size=self.gtbox_shape).astype("float64")
      gtlabel = np.random.randint(
          0, self.class_num, self.gtbox_shape[:2]
      )
      gtmask = np.random.randint(0, 2, self.gtbox_shape[:2])
      gtbox = gtbox * gtmask[:, :, np.newaxis]
      gtlabel = gtlabel * gtmask
  
      gtscore = np.ones(self.gtbox_shape[:2]).astype("float64")
      if self.gtscore:
          gtscore = np.random.random(self.gtbox_shape[:2]).astype(
              "float64"
          )
  
      target = []
      for box, label, score in zip(gtbox, gtlabel, gtscore):
          target.append(
              gt2yolotarget(
                  box,
                  label,
                  score,
                  self.anchors,
                  self.anchor_mask,
                  self.class_num,
                  (self.h, self.w),
                  self.downsample_ratio,
              )
          )
  
      self.target = np.array(target).astype("float64")
  
      self.mask_anchors = []
      for i in self.anchor_mask:
          self.mask_anchors.extend(self.anchors[i])
      self.x = x
      self.gtbox = gtbox
      self.gtlabel = gtlabel
      self.gtscore = gtscore
  
imports: from __future__ import division
  import unittest
  import paddle
  import paddle.nn.functional
  import os
  import sys
  from ppdet.modeling.losses import YOLOv3Loss
  from ppdet.data.transform.op_helper import jaccard_overlap
  from ppdet.modeling.bbox_utils import iou_similarity
  import numpy
label_desc: Use image node_id 1 for calling the TestYolov3LossOp obj's underlying member method code with example usage: obj.setUp() without return types