code: def testMaskRCNNFPN_with_postproc(self):
      def inference_func(model, image):
          inputs = [
              {
                  "image": image,
                  "height": image.shape[1],
                  "width": image.shape[2],
              }
          ]
          return model.inference(inputs, do_postprocess=True)[0][
              "instances"
          ]
  
      self._test_model(
          "COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml",
          inference_func,
      )
  
imports: import copy
  import glob
  import json
  import os
  import random
  import tempfile
  import unittest
  import zipfile
  import torch
  from torch import Tensor, nn
  from detectron2 import model_zoo
  from detectron2.config import get_cfg
  from detectron2.config.instantiate import dump_dataclass, instantiate
  from detectron2.export import dump_torchscript_IR, scripting_with_instances
  from detectron2.export.flatten import TracingAdapter, flatten_to_tuple
  from detectron2.export.torchscript_patch import patch_builtin_len
  from detectron2.layers import ShapeSpec
  from detectron2.modeling import build_backbone
  from detectron2.modeling.postprocessing import detector_postprocess
  from detectron2.modeling.roi_heads import KRCNNConvDeconvUpsampleHead
  from detectron2.structures import Boxes, Instances
  from detectron2.utils.env import TORCH_VERSION
  from detectron2.utils.testing import assert_instances_allclose, convert_scripted_instances, get_sample_coco_image, random_boxes, reload_script_model, skipIfOnCPUCI
label_desc: Use image node_id 2 for calling the TestTracing obj's underlying member method code with example usage: obj.testMaskRCNNFPN_with_postproc() and returns: model