code: def test_not_float_normalize(self):
      transform = GeneralizedRCNNTransform(
          300, 500, torch.zeros(3), torch.ones(3)
      )
      image = [torch.randint(0, 255, (3, 200, 300), dtype=torch.uint8)]
      targets = [{"boxes": torch.rand(3, 4)}]
      with pytest.raises(TypeError):
          out = transform(image, targets)
  
file_path: vision/test/test_models_detection_utils.py
imports: import copy
  import pytest
  import torch
  from common_utils import assert_equal
  from torchvision.models.detection import _utils, backbone_utils
  from torchvision.models.detection.transform import GeneralizedRCNNTransform
label_desc: Use image node_id 6 for calling the TestModelsDetectionUtils obj's underlying member method code with example usage: obj.test_not_float_normalize() without return types