code: def _max_error(arrays1, arrays2):
      """Computes maximum elementwise gap between two lists of ndarrays.
  
      Computes the maximum elementwise gap between two lists with the same length,
      of arrays with the same shape.
  
      Args:
        arrays1: a lists of np.ndarrays.
        arrays2: a lists of np.ndarrays of the same shape as arrays1.
  
      Returns:
        The maximum elementwise absolute difference between the two lists of arrays.
      """
      error = 0
      for array1, array2 in zip(arrays1, arrays2):
          if (
              array1.size or array2.size
          ):  # Handle zero size ndarrays correctly
              error = np.maximum(error, np.fabs(array1 - array2).max())
      return error
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import warnings
  from absl import flags
  from absl.testing import parameterized
  import numpy
  from six.moves import zip
  import tensorflow
  from tensorflow_graphics.util import tfg_flags
label_desc: Use image node_id 1 for calling a global function with example usage: _max_error(arrays1, arrays2) and returns: error