code: def assert_equal_z_values(
      back_coef,
      curr_coef,
      z_values_backward,
      coeff_backward,
      model_z_values,
      glm_coeff,
  ):
      for coeff in glm_coeff:
          backward_z_value = z_values_backward[
              coeff_backward.index(coeff)
          ]
          model_z_value = model_z_values[glm_coeff.index(coeff)]
          print(
              "for coeff: {0}, backward z-value: {1}, glm model z-value: {2}".format(
                  coeff, backward_z_value, model_z_value
              )
          )
          if backward_z_value == "NaN":
              assert math.isnan(model_z_value), (
                  "Expected z-value to be nan but is {0} for predictor"
                  " {1}".format(model_z_value, coeff)
              )
          else:
              if math.isnan(model_z_value):
                  assert (
                      False
                  ), "Expected z-value should not be nan for predictor {0}".format(
                      coeff
                  )
              else:
                  assert (
                      abs(backward_z_value - model_z_value) < 1e-12
                  ), (
                      "Expected z-value: {0}.  Actual z_value: {1}. They are very different."
                      "".format(backward_z_value, model_z_value)
                  )
  
file_path: h2o-3/h2o-py/tests/testdir_algos/modelselection/pyunit_PUBDEV_8675_modelselection_fail.py
imports: import sys
  import math
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.model_selection import H2OModelSelectionEstimator
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
label_desc: Use image node_id 6 for calling a global function with example usage: assert_equal_z_values(back_coef, curr_coef, z_values_backward, coeff_backward, model_z_values, glm_coeff) without return types