code: def test_partial_dependence_pipeline():
      # check that the partial dependence support pipeline
      iris = load_iris()
  
      scaler = StandardScaler()
      clf = DummyClassifier(random_state=42)
      pipe = make_pipeline(scaler, clf)
  
      clf.fit(scaler.fit_transform(iris.data), iris.target)
      pipe.fit(iris.data, iris.target)
  
      features = 0
      pdp_pipe = partial_dependence(
          pipe,
          iris.data,
          features=[features],
          grid_resolution=10,
          kind="average",
      )
      pdp_clf = partial_dependence(
          clf,
          scaler.transform(iris.data),
          features=[features],
          grid_resolution=10,
          kind="average",
      )
      assert_allclose(pdp_pipe["average"], pdp_clf["average"])
      assert_allclose(
          pdp_pipe["grid_values"][0],
          pdp_clf["grid_values"][0] * scaler.scale_[features]
          + scaler.mean_[features],
      )
  
imports: import warnings
  import numpy
  import pytest
  import sklearn
  from sklearn.base import BaseEstimator, ClassifierMixin, clone, is_regressor
  from sklearn.cluster import KMeans
  from sklearn.compose import make_column_transformer
  from sklearn.datasets import load_iris, make_classification, make_regression
  from sklearn.dummy import DummyClassifier
  from sklearn.ensemble import GradientBoostingClassifier, GradientBoostingRegressor, HistGradientBoostingClassifier, HistGradientBoostingRegressor, RandomForestRegressor
  from sklearn.exceptions import NotFittedError
  from sklearn.inspection import partial_dependence
  from sklearn.inspection._partial_dependence import _grid_from_X, _partial_dependence_brute, _partial_dependence_recursion
  from sklearn.linear_model import LinearRegression, LogisticRegression, MultiTaskLasso
  from sklearn.metrics import r2_score
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import PolynomialFeatures, RobustScaler, StandardScaler, scale
  from sklearn.tree import DecisionTreeRegressor
  from sklearn.tree.tests.test_tree import assert_is_subtree
  from sklearn.utils import _IS_32BIT
  from sklearn.utils._testing import assert_allclose, assert_array_equal
  from sklearn.utils.validation import check_random_state
label_desc: Use image node_id 18 for calling a global function with example usage: test_partial_dependence_pipeline() without return types