code: def test_benign():
      training_data = h2o.import_file(
          pyunit_utils.locate("smalldata/gbm_test/BostonHousing.csv")
      )
      Y = 13
      X = list(range(13))
      check_warnings(
          "Wendy Wong and Nidhi Mehta", X, Y, 0, training_data
      )  # expect no warning here
  
      check_warnings(
          "Wendy / Wong / and / Nidhi / Mehta", X, Y, 1, training_data
      )  # bad model_id, expect one warning
      check_warnings(" test -  june/fifteenth ", X, Y, 1, training_data)
  
imports: from builtins import range
  import sys, os
  import h2o
  from h2o.estimators.glm import H2OGeneralizedLinearEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: test_benign() without return types