code: def test_plot_partial_dependence_does_not_override_ylabel(
      pyplot, clf_diabetes, diabetes
  ):
      # Non-regression test to be sure to not override the ylabel if it has been
      # See https://github.com/scikit-learn/scikit-learn/issues/15772
      _, axes = pyplot.subplots(1, 2)
      axes[0].set_ylabel("Hello world")
      PartialDependenceDisplay.from_estimator(
          clf_diabetes, diabetes.data, [0, 1], ax=axes
      )
  
      assert axes[0].get_ylabel() == "Hello world"
      assert axes[1].get_ylabel() == "Partial dependence"
  
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 16 for calling a global function with example usage: test_plot_partial_dependence_does_not_override_ylabel(pyplot, clf_diabetes, diabetes) without return types