code: def test_params_are_correctly_passed_to_underlying_estimator():
      estimator = H2OGradientBoostingEstimator(seed=seed)
      estimator.set_params(max_depth=10, learn_rate=0.5)
      estimator.model_id = "dummy"
      assert estimator.estimator is None
      estimator._make_estimator()  # normally done when calling `fit`
      real_estimator = estimator.estimator
      assert real_estimator
      parms = real_estimator._parms
      assert real_estimator.seed == parms["seed"] == seed
      assert real_estimator.max_depth == parms["max_depth"] == 10
      assert real_estimator.learn_rate == parms["learn_rate"] == 0.5
      assert real_estimator._id == parms["model_id"] == "dummy"
      assert (
          real_estimator.training_frame
          == parms["training_frame"]
          is None
      )
  
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 7 for calling a global function with example usage: test_params_are_correctly_passed_to_underlying_estimator() without return types