code: def test_partial_dependence_overwrite_labels(
      pyplot,
      clf_diabetes,
      diabetes,
      kind,
      line_kw,
      label,
  ):
      """Test that make sure that we can overwrite the label of the PDP plot"""
      disp = PartialDependenceDisplay.from_estimator(
          clf_diabetes,
          diabetes.data,
          [0, 2],
          grid_resolution=25,
          feature_names=diabetes.feature_names,
          kind=kind,
          line_kw=line_kw,
      )
  
      for ax in disp.axes_.ravel():
          if label is None:
              assert ax.get_legend() is None
          else:
              legend_text = ax.get_legend().get_texts()
              assert len(legend_text) == 1
              assert legend_text[0].get_text() == label
  
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 20 for calling a global function with example usage: test_partial_dependence_overwrite_labels(pyplot, clf_diabetes, diabetes, kind, line_kw, label) without return types