code: def _init_test_generalized_rcnn_transform(self):
      min_size = 100
      max_size = 200
      image_mean = [0.485, 0.456, 0.406]
      image_std = [0.229, 0.224, 0.225]
      transform = GeneralizedRCNNTransform(
          min_size, max_size, image_mean, image_std
      )
      return transform
  
imports: import io
  from collections import OrderedDict
  from typing import List, Optional, Tuple
  import pytest
  import torch
  from common_utils import assert_equal, set_rng_seed
  from torchvision import models, ops
  from torchvision.models.detection.faster_rcnn import FastRCNNPredictor, TwoMLPHead
  from torchvision.models.detection.image_list import ImageList
  from torchvision.models.detection.roi_heads import RoIHeads
  from torchvision.models.detection.rpn import AnchorGenerator, RegionProposalNetwork, RPNHead
  from torchvision.models.detection.transform import GeneralizedRCNNTransform
  from torchvision.ops import _register_onnx_ops
label_desc: Use image node_id 13 for calling the TestONNXExporter obj's underlying member method code with example usage: obj._init_test_generalized_rcnn_transform() and returns: transform