code: def _is_int(a):
      """Determine whether the values of `a` are of type `numpy.int`
  
      Parameters
      ----------
      a: Array-like
          Array, whose values' types will be checked
  
      Returns
      -------
      Boolean
          True if the `dtype` of the values of `a` == `numpy.int`. Else, False
  
      Examples
      --------
      >>> assert _is_int(np.array([0, 1, 2, 3]))
      >>> assert _is_int(pd.DataFrame([0, 1], [2, 3]))
      >>> assert not _is_int(np.array([0.0, 1.1, 2.2, 3.3]))
      >>> assert not _is_int(pd.DataFrame([0.0, 1.1], [2.2, 3.3]))"""
      try:
          return a.values.dtype == np.int
      except AttributeError:
          return a.dtype == np.int
  
imports: from collections import OrderedDict
  from contextlib import suppress
  import numpy
  import pandas
  from typing import Dict, Iterable, List, Tuple, Union
  from sklearn import metrics
  from sklearn.utils.multiclass import type_of_target, unique_labels
label_desc: Use image node_id 3 for calling a global function with example usage: _is_int(a) and returns: unknown, unknown