code: def test_errors():
      from torch import hub
  
      from art.estimators.object_detection.pytorch_detection_transformer import (
          PyTorchDetectionTransformer,
      )
  
      model = hub.load(
          "facebookresearch/detr", "detr_resnet50", pretrained=True
      )
  
      with pytest.raises(ValueError):
          PyTorchDetectionTransformer(
              model=model,
              clip_values=(1, 2),
              attack_losses=("loss_ce", "loss_bbox", "loss_giou"),
          )
  
      with pytest.raises(ValueError):
          PyTorchDetectionTransformer(
              model=model,
              clip_values=(-1, 1),
              attack_losses=("loss_ce", "loss_bbox", "loss_giou"),
          )
  
      from art.defences.postprocessor.rounded import Rounded
  
      post_def = Rounded()
      with pytest.raises(ValueError):
          PyTorchDetectionTransformer(
              model=model,
              clip_values=(0, 1),
              attack_losses=("loss_ce", "loss_bbox", "loss_giou"),
              postprocessing_defences=post_def,
          )
  
file_path: adversarial-robustness-toolbox/tests/estimators/object_detection/test_pytorch_detection_transformer.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
label_desc: Use image node_id 4 for calling a global function with example usage: test_errors() without return types