code: def video_batch(channels_first):
      """
      Video fixture of shape NFHWC and NCFHW.
      """
      test_input = np.stack(
          (np.zeros((3, 25, 4, 6)), np.ones((3, 25, 4, 6)))
      )
      if not channels_first:
          test_input = np.transpose(test_input, (0, 2, 3, 4, 1))
      test_output = test_input.copy()
      return test_input, test_output
  
file_path: adversarial-robustness-toolbox/tests/defences/preprocessor/test_video_compression_pytorch.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from art.defences.preprocessor import VideoCompressionPyTorch
  from tests.utils import ARTTestException
label_desc: Use image node_id 1 for calling a global function with example usage: video_batch(channels_first) and returns: test_input,  test_output