code: def assert_deciles(
      xsegments: Optional[List[np.ndarray]] = None,
      expected_xdeciles: Optional[np.ndarray] = None,
      ysegments: Optional[List[np.ndarray]] = None,
      expected_ydeciles: Optional[np.ndarray] = None,
  ):
      """Checks the deciles on the x-axis."""
      if (xsegments is not None) and (expected_xdeciles is not None):
          xdeciles = np.array([segment[0, 0] for segment in xsegments])
          assert np.allclose(xdeciles, expected_xdeciles[1:-1])
  
      if (ysegments is not None) and (expected_ydeciles is not None):
          ydeciles = np.array([segment[0, 1] for segment in ysegments])
          assert np.allclose(ydeciles, expected_ydeciles[1:-1])
  
imports: import re
  import sys
  from copy import deepcopy
  from typing import Dict, List, Optional, Tuple, Union
  from packaging import version
  import matplotlib.pyplot
  import numpy
  import pandas
  import pytest
  from pytest_lazyfixture import lazy_fixture
  from sklearn.base import BaseEstimator
  from sklearn.datasets import make_classification
  from sklearn.ensemble import GradientBoostingClassifier
  from sklearn.exceptions import NotFittedError
  from sklearn.inspection import partial_dependence
  from sklearn.model_selection import train_test_split
  from sklearn.multioutput import MultiOutputClassifier
  from sklearn.pipeline import Pipeline
  from sklearn.utils import Bunch, shuffle
  import sklearn
  from alibi.api.defaults import DEFAULT_DATA_PD, DEFAULT_META_PD
  from alibi.api.interfaces import Explanation
  from alibi.explainers import PartialDependence, TreePartialDependence, plot_pd
  from alibi.explainers.partial_dependence import _plot_one_pd_cat, _plot_one_pd_num, _plot_two_pd_cat_cat, _plot_two_pd_num_cat, _plot_two_pd_num_num, _process_pd_ice, _sample_ice
label_desc: Use image node_id 21 for calling a global function with example usage: assert_deciles(xsegments, expected_xdeciles, ysegments, expected_ydeciles) without return types