code: def image_batch(request):
      """
      Create image fixture of shape NFHWC and NCFHW.
      """
      channels_first = request.param
      test_input = np.ones((2, 3, 32, 32))
      if not channels_first:
          test_input = np.transpose(test_input, (0, 2, 3, 1))
      test_mean = [0] * 3
      test_std = [1] * 3
      test_output = test_input.copy()
      return test_input, test_output, test_mean, test_std
  
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 1 for calling a global function with example usage: image_batch(request) and returns: test_input,  test_output,  test_mean,  test_std