code: def test_forward_runs(self):
      loader = TorchImageLoader(
          resize=True, normalize=True, device="cuda:0"
      )
      backbone = ResnetBackbone().to(device="cuda:0")
      backbone.eval()
      detector = FasterRcnnRegionDetector().to(device="cuda:0")
      detector.eval()
  
      image_path = (
          self.FIXTURES_ROOT
          / "data"
          / "images"
          / "COCO_train2014_000000458752.jpg"
      )
  
      images, sizes = loader([image_path, image_path])
      image_features = backbone(images, sizes)
      del backbone
      detections = detector(images, sizes, image_features)
      del detector
  
      assert len(detections.features) == 2
      assert len(detections.boxes) == 2
      assert len(detections.class_probs) == 2
      assert len(detections.class_labels) == 2
  
      assert detections.features[0].shape[0] >= 1
      assert detections.features[0].shape[1] == 1024
      assert (
          detections.features[0].shape[0]
          == detections.boxes[0].shape[0]
          == detections.class_probs[0].shape[0]
          == detections.class_labels[0].shape[0]
      )
  
      # Okay, cool, so far so good. Now let's make sure the output we got
      # actually matches exactly what we would get using the full pipeline
      # directly from torchvision.
      raw_loader = TorchImageLoader(
          resize=False, normalize=False, device="cuda:0"
      )
      image, _ = raw_loader(image_path)
      model = torchvision.models.detection.fasterrcnn_resnet50_fpn(
          pretrained=True
      ).to("cuda:0")
      model.eval()
      result = model([image, image])
      # We can't compare the boxes directly because the boxes here are post-processed
      # back to reference the original un-resized image. But we can compare
      # the labels and scores. They should match exactly.
      assert (result[0]["labels"] == detections.class_labels[0]).all()
      assert (result[0]["scores"] == detections.class_probs[0]).all()
  
file_path: allennlp/tests/modules/vision/region_detector_test.py
imports: import torchvision
  from allennlp.common.testing import AllenNlpTestCase, requires_gpu
  from allennlp.data.image_loader import TorchImageLoader
  from allennlp.modules.vision.grid_embedder import ResnetBackbone
  from allennlp.modules.vision.region_detector import FasterRcnnRegionDetector
label_desc: Use image node_id 1 for calling the TestFasterRcnnRegionDetector obj's underlying member method code with example usage: obj.test_forward_runs() without return types