code: def test_forward_negative_sample_frcnn(self, name):
      model = torchvision.models.get_model(
          name,
          weights=None,
          weights_backbone=None,
          num_classes=2,
          min_size=100,
          max_size=100,
      )
  
      images, targets = self._make_empty_sample()
      loss_dict = model(images, targets)
  
      assert_equal(loss_dict["loss_box_reg"], torch.tensor(0.0))
      assert_equal(loss_dict["loss_rpn_box_reg"], torch.tensor(0.0))
  
file_path: vision/test/test_models_detection_negative_samples.py
imports: import pytest
  import torch
  import torchvision.models
  from common_utils import assert_equal
  from torchvision.models.detection.faster_rcnn import FastRCNNPredictor, TwoMLPHead
  from torchvision.models.detection.roi_heads import RoIHeads
  from torchvision.models.detection.rpn import AnchorGenerator, RegionProposalNetwork, RPNHead
  from torchvision.ops import MultiScaleRoIAlign
label_desc: Use image node_id 4 for calling the TestModelsDetectionNegativeSamples obj's underlying member method code with example usage: obj.test_forward_negative_sample_frcnn(name) without return types