code: def test_kfold_indices(setup):
      # Check all indices are returned in the test folds
      X1 = np.ones(18)
      kf = KFold(3)
      check_cv_coverage(
          kf, X1, y=None, groups=None, expected_n_splits=3
      )
  
      # Check all indices are returned in the test folds even when equal-sized
      # folds are not possible
      X2 = np.ones(17)
      kf = KFold(3)
      check_cv_coverage(
          kf, X2, y=None, groups=None, expected_n_splits=3
      )
  
      # Check if get_n_splits returns the number of folds
      assert 5 == KFold(5).get_n_splits(X2)
  
imports: import itertools
  import numpy
  import pandas
  import pytest
  from ....None import dataframe
  from ....None import tensor
  from ....dataframe.core import DATAFRAME_TYPE
  from ....lib.sparse import SparseNDArray
  from ...utils.validation import _num_samples
  from ..None import train_test_split, KFold
label_desc: Use image node_id 12 for calling a global function with example usage: test_kfold_indices(setup) without return types