code: def test_wrong_model_pzvalues_stdErr():
      cars = h2o.import_file(
          path=pyunit_utils.locate("smalldata/junit/cars_20mpg.csv")
      )
      y = "economy_20mpg"
      predictors = [
          "displacement",
          "power",
          "weight",
          "acceleration",
          "year",
      ]
      cars[y] = cars[y].asfactor()
  
      h2oglm_compute_p_value = H2OGeneralizedLinearEstimator(
          family="binomial", seed=1234
      )
      h2oglm_compute_p_value.train(
          x=predictors, y=y, training_frame=cars
      )
  
      try:
          h2oglm_compute_p_value.coef_with_p_values()
      except ValueError as e:
          assert (
              "p-values, z-values and std_error are not found in model"
              in e.args[0]
          ), "Wrong error messages received."
  
imports: import sys
  import h2o
  from tests import pyunit_utils
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_wrong_model_pzvalues_stdErr() without return types