code: def save_load_mode_with_cv():
      prostate = h2o.import_file(
          pyunit_utils.locate("smalldata/prostate/prostate.csv")
      )
      prostate["CAPSULE"] = prostate["CAPSULE"].asfactor()
  
      prostate_gbm = H2OGradientBoostingEstimator(
          nfolds=2, keep_cross_validation_predictions=True
      )
      prostate_gbm.train(
          x=["AGE", "RACE", "PSA", "DCAPS"],
          y="CAPSULE",
          training_frame=prostate,
      )
      path = pyunit_utils.locate("results")
  
      model_path = h2o.save_model(
          prostate_gbm,
          path=path,
          force=True,
          export_cross_validation_predictions=True,
      )
      assert os.path.isfile(
          model_path
      ), "Expected model artifact {0} to exist, but it does not.".format(
          model_path
      )
  
      h2o.remove_all()
  
      prostate_gbm_reloaded = h2o.load_model(model_path)
      assert isinstance(
          prostate_gbm_reloaded, H2OGradientBoostingEstimator
      ), "Expected H2OGradientBoostingEstimator, but got {0}".format(
          prostate_gbm_reloaded
      )
  
      holdout_frame_id = (
          prostate_gbm.cross_validation_holdout_predictions().frame_id
      )
      assert h2o.get_frame(holdout_frame_id) is not None
  
imports: import h2o
  import os
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 1 for calling a global function with example usage: save_load_mode_with_cv() without return types