code: def test_passing_blending_frame_triggers_blending_mode():
      ds = prepare_data(blending=True)
      base_models = train_base_models(ds)
      se = train_stacked_ensemble(ds, base_models)
      assert se.stacking_strategy() == "blending"
      assert (
          se.model_performance().mse()
          == se.model_performance(ds.train).mse()
      )
  
file_path: h2o-3/h2o-py/tests/testdir_algos/stackedensemble/pyunit_stackedensemble_blending_frame.py
imports: import h2o
  import sys
  from h2o.estimators.random_forest import H2ORandomForestEstimator
  from h2o.estimators.gbm import H2OGradientBoostingEstimator
  from h2o.estimators.stackedensemble import H2OStackedEnsembleEstimator
  from tests import pyunit_utils
label_desc: Use image node_id 4 for calling a global function with example usage: test_passing_blending_frame_triggers_blending_mode() without return types