code: def test_params_are_correctly_passed_to_underlying_transformer():
      pca = H2OPCA(seed=seed)
      pca.set_params(transform="demean", k=3)
      pca.model_id = "dummy"
      assert pca.estimator is None
      pca._make_estimator()  # normally done when calling `fit`
      assert pca.estimator
      parms = pca.estimator._parms
      assert parms["seed"] == seed
      assert parms["transform"] == "demean"
      assert parms["k"] == 3
      assert parms["model_id"] == "dummy"
      assert parms["max_iterations"] 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 6 for calling a global function with example usage: test_params_are_correctly_passed_to_underlying_transformer() without return types