code: def vectorized_is_element(array, choices):
      """
      Check if each element of ``array`` is in choices.
  
      Parameters
      ----------
      array : np.ndarray
      choices : object
          Object implementing __contains__.
  
      Returns
      -------
      was_element : np.ndarray[bool]
          Array indicating whether each element of ``array`` was in ``choices``.
      """
      return vectorize(choices.__contains__, otypes=[bool])(array)
  
imports: from collections import OrderedDict
  from datetime import datetime
  from distutils.version import StrictVersion
  from warnings import catch_warnings, filterwarnings
  import six
  import numpy
  from numpy import array_equal, broadcast, busday_count, datetime64, diff, dtype, empty, flatnonzero, hstack, isnan, nan, vectorize, where
  from numpy.lib.stride_tricks import as_strided
  from toolz import flip
label_desc: Use image node_id 15 for calling a global function with example usage: vectorized_is_element(array, choices) and returns: vectorize