code: def test_params_are_correctly_passed_to_underlying_automl():
      estimator = H2OAutoMLEstimator(seed=seed)
      estimator.set_params(max_models=5, nfolds=0)
      estimator.project_name = "dummy"
      assert estimator.estimator is None
      estimator._make_estimator()  # normally done when calling `fit`
      aml = estimator.estimator
      assert aml
      assert aml.build_control["stopping_criteria"]["seed"] == seed
      assert aml.build_control["stopping_criteria"]["max_models"] == 5
      assert aml.build_control["nfolds"] == 0
      assert aml.build_control["project_name"] == "dummy"
  
file_path: h2o-3/h2o-py/tests/testdir_sklearn/pyunit_sklearn_params.py
imports: import os, sys
  from sklearn.pipeline import Pipeline
  from h2o.sklearn import H2OAutoMLEstimator, H2OGradientBoostingEstimator, H2OScaler, H2OPCA
  from tests import pyunit_utils
label_desc: Use image node_id 8 for calling a global function with example usage: test_params_are_correctly_passed_to_underlying_automl() without return types