class_docstr: Base class for all cross-validators
  
  Implementations must define `_iter_test_masks` or `_iter_test_indices`.
docstr: Generates boolean masks corresponding to test sets.
  
  By default, delegates to _iter_test_indices(X, y, groups)
docstr_tok: ["Generates","boolean","masks","corresponding","to","test","sets",".","By","default",",","delegates","to","_iter_test_indices","(","X",",","y",",","groups",")"]
code: def _iter_test_masks(
      self, X=None, y=None, groups=None
  ):  # pragma: no cover
      """Generates boolean masks corresponding to test sets.
  
      By default, delegates to _iter_test_indices(X, y, groups)
      """
      for test_index in self._iter_test_indices(X, y, groups):
          test_mask = mt.zeros(_num_samples(X), dtype=bool)
          test_mask[test_index] = True
          yield test_mask
  
imports: import numbers
  from abc import ABCMeta, abstractmethod
  from itertools import chain
  from math import ceil, floor
  import numpy
  from ...core import ExecutableTuple
  from ...None import tensor
  from ...tensor.utils import check_random_state
  from ..utils import shuffle
  from ..utils.validation import indexable, _num_samples
label_desc: Use image node_id 2 for calling the BaseCrossValidator obj's underlying member method code with example usage: obj._iter_test_masks(X, y, groups) without return types