code: def test_GLM_throws_ArrayOutOfBoundException():
      nFold = 5
      fr = h2o.import_file(
          pyunit_utils.locate("bigdata/laptop/jira/christine.arff")
      )
      splitFrame = fr.split_frame(ratios=[0.05])
      glm = H2OGeneralizedLinearEstimator(
          family="binomial",
          nfolds=nFold,
          lambda_search=True,
          alpha=[0.0, 0.2, 0.4, 0.6, 0.8, 1.0],
      )
      glm.train(y=0, training_frame=splitFrame[0])
      assert (
          len(glm._model_json["output"]["cross_validation_models"])
          == nFold
      ), (
          "expected number of cross_validation_model: {0}.  Actual number of cross_validation: "
          "{1}".format(
              len(glm._model_json["output"]["cross_validation_models"]),
              nFold,
          )
      )
  
imports: import sys, os
  import h2o
  import h2o.exceptions
  from tests import pyunit_utils
  from h2o.estimators import H2OGeneralizedLinearEstimator
label_desc: Use image node_id 1 for calling a global function with example usage: test_GLM_throws_ArrayOutOfBoundException() without return types