code: def test_scorefunc_multilabel():
      # Test whether k-best and percentiles works with multilabels with chi2.
  
      X = np.array([[10000, 9999, 0], [100, 9999, 0], [1000, 99, 0]])
      y = [[1, 1], [0, 1], [1, 0]]
  
      Xt = SelectKBest(chi2, k=2).fit_transform(X, y)
      assert Xt.shape == (3, 2)
      assert 0 not in Xt
  
      Xt = SelectPercentile(chi2, percentile=67).fit_transform(X, y)
      assert Xt.shape == (3, 2)
      assert 0 not in Xt
  
imports: import itertools
  import warnings
  import numpy
  import pytest
  from numpy.testing import assert_allclose
  from scipy import sparse, stats
  from sklearn.datasets import load_iris, make_classification, make_regression
  from sklearn.feature_selection import GenericUnivariateSelect, SelectFdr, SelectFpr, SelectFwe, SelectKBest, SelectPercentile, chi2, f_classif, f_oneway, f_regression, mutual_info_classif, mutual_info_regression, r_regression
  from sklearn.utils import safe_mask
  from sklearn.utils._testing import _convert_container, assert_almost_equal, assert_array_almost_equal, assert_array_equal, ignore_warnings
  from sklearn.utils.fixes import CSR_CONTAINERS
label_desc: Use image node_id 28 for calling a global function with example usage: test_scorefunc_multilabel() without return types