code: def test_fit_mask(art_warning, get_pytorch_object_detector_mask):
      try:
          (
              object_detector,
              x_test,
              y_test,
          ) = get_pytorch_object_detector_mask
  
          # Compute loss before training
          loss1 = object_detector.compute_loss(x=x_test, y=y_test)
  
          # Train for one epoch
          object_detector.fit(x_test, y_test, nb_epochs=1)
  
          # Compute loss after training
          loss2 = object_detector.compute_loss(x=x_test, y=y_test)
  
          assert loss1 != loss2
  
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/estimators/object_detection/test_pytorch_object_detector.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from tests.utils import ARTTestException
label_desc: Use image node_id 4 for calling a global function with example usage: test_fit_mask(art_warning, get_pytorch_object_detector_mask) without return types