code: def test_broadcastable_mean_std(art_warning):
      try:
          mean, std = broadcastable_mean_std(
              np.ones((1, 3, 20, 20)), np.ones(3), np.ones(3)
          )
          assert mean.shape == std.shape == (1, 3, 1, 1)
  
          mean, std = broadcastable_mean_std(
              np.ones((1, 3, 20, 20)),
              np.ones((1, 3, 1, 1)),
              np.ones((1, 3, 1, 1)),
          )
          assert mean.shape == std.shape == (1, 3, 1, 1)
      except ARTTestException as e:
          art_warning(e)
  
file_path: adversarial-robustness-toolbox/tests/preprocessing/test_standardisation_mean_std.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from art.preprocessing.standardisation_mean_std import StandardisationMeanStd, StandardisationMeanStdPyTorch, StandardisationMeanStdTensorFlow
  from art.preprocessing.standardisation_mean_std.utils import broadcastable_mean_std
  from tests.utils import ARTTestException
label_desc: Use image node_id 2 for calling a global function with example usage: test_broadcastable_mean_std(art_warning) without return types