code: def test_partial_dependence_kind_list(
      pyplot,
      clf_diabetes,
      diabetes,
  ):
      """Check that we can provide a list of strings to kind parameter."""
      matplotlib = pytest.importorskip("matplotlib")
  
      disp = PartialDependenceDisplay.from_estimator(
          clf_diabetes,
          diabetes.data,
          features=[0, 2, (1, 2)],
          grid_resolution=20,
          kind=["both", "both", "average"],
      )
  
      for idx in [0, 1]:
          assert all(
              [
                  isinstance(line, matplotlib.lines.Line2D)
                  for line in disp.lines_[0, idx].ravel()
              ]
          )
          assert disp.contours_[0, idx] is None
  
      assert disp.contours_[0, 2] is not None
      assert all([line is None for line in disp.lines_[0, 2].ravel()])
  
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose
  from scipy.stats.mstats import mquantiles
  from sklearn.compose import make_column_transformer
  from sklearn.datasets import load_diabetes, load_iris, make_classification, make_regression
  from sklearn.ensemble import GradientBoostingClassifier, GradientBoostingRegressor
  from sklearn.inspection import PartialDependenceDisplay
  from sklearn.linear_model import LinearRegression
  from sklearn.pipeline import make_pipeline
  from sklearn.preprocessing import OneHotEncoder
  from sklearn.utils._testing import _convert_container
label_desc: Use image node_id 24 for calling a global function with example usage: test_partial_dependence_kind_list(pyplot, clf_diabetes, diabetes) without return types