code: def test_all_params_are_accessible_as_properties():
      pipeline = Pipeline(
          [
              ("standardize", H2OScaler(center=True, scale=False)),
              ("pca", H2OPCA(k=2, seed=seed)),
              (
                  "estimator",
                  H2OGradientBoostingEstimator(
                      ntrees=20, max_depth=5, seed=seed
                  ),
              ),
          ]
      )
      assert isinstance(pipeline.named_steps.standardize, H2OScaler)
      assert pipeline.named_steps.standardize.center is True
      assert pipeline.named_steps.standardize.scale is False
      assert isinstance(pipeline.named_steps.pca, H2OPCA)
      assert pipeline.named_steps.pca.k == 2
      assert pipeline.named_steps.pca.seed == seed
      assert isinstance(
          pipeline.named_steps.estimator, H2OGradientBoostingEstimator
      )
      assert pipeline.named_steps.estimator.ntrees == 20
      assert pipeline.named_steps.estimator.max_depth == 5
      assert pipeline.named_steps.estimator.seed == seed
      # also the ones that were not set explicitly
      assert pipeline.named_steps.pca.max_iterations is None
      assert pipeline.named_steps.estimator.learn_rate == 0.1
      assert (
          pipeline.named_steps.estimator.class_sampling_factors 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 3 for calling a global function with example usage: test_all_params_are_accessible_as_properties() without return types