code: def test_infogram_personal_loan():
      """
      Simple Perosnal loan test to check that when wrong thresholds are specified, warnings should be
      generated.
      :return:
      """
      fr = h2o.import_file(
          path=pyunit_utils.locate(
              "smalldata/admissibleml_test/Bank_Personal_Loan_Modelling.csv"
          )
      )
      target = "Personal Loan"
      fr[target] = fr[target].asfactor()
      x = [
          "Experience",
          "Income",
          "Family",
          "CCAvg",
          "Education",
          "Mortgage",
          "Securities Account",
          "CD Account",
          "Online",
          "CreditCard",
      ]
      with pyunit_utils.catch_warnings() as ws:
          infogram_model = H2OInfogram(
              seed=12345,
              protected_columns=["Age", "ZIP Code"],
              top_n_features=len(x),
              net_information_threshold=0.2,
              total_information_threshold=0.2,
          )
          infogram_model.train(x=x, y=target, training_frame=fr)
          assert (
              len(ws) == 2
          ), "Expected two warnings but received {0} warnings instead.".format(
              len(ws)
          )
          assert pyunit_utils.contains_warning(
              ws, "information_threshold for fair infogram runs."
          )
  
imports: import os
  import sys
  import h2o
  from h2o.estimators.infogram import H2OInfogram
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_infogram_personal_loan() without return types