code: def test_rpn(self):
      set_rng_seed(0)
  
      class RPNModule(torch.nn.Module):
          def __init__(self_module):
              super().__init__()
              self_module.rpn = self._init_test_rpn()
  
          def forward(self_module, images, features):
              images = ImageList(images, [i.shape[-2:] for i in images])
              return self_module.rpn(images, features)
  
      images = torch.rand(2, 3, 150, 150)
      features = self.get_features(images)
      images2 = torch.rand(2, 3, 80, 80)
      test_features = self.get_features(images2)
  
      model = RPNModule()
      model.eval()
      model(images, features)
  
      self.run_model(
          model,
          [(images, features), (images2, test_features)],
          input_names=[
              "input1",
              "input2",
              "input3",
              "input4",
              "input5",
              "input6",
          ],
          dynamic_axes={
              "input1": [0, 1, 2, 3],
              "input2": [0, 1, 2, 3],
              "input3": [0, 1, 2, 3],
              "input4": [0, 1, 2, 3],
              "input5": [0, 1, 2, 3],
              "input6": [0, 1, 2, 3],
          },
      )
  
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 17 for calling the TestONNXExporter obj's underlying member method code with example usage: obj.test_rpn() and returns: self_module