code: def is_datetime64_any_dtype(arr_or_dtype) -> bool:
      """
      Check whether the provided array or dtype is of the datetime64 dtype.
  
      Parameters
      ----------
      arr_or_dtype : array-like or dtype
          The array or dtype to check.
  
      Returns
      -------
      bool
          Whether or not the array or dtype is of the datetime64 dtype.
  
      Examples
      --------
      >>> from pandas.api.types import is_datetime64_any_dtype
      >>> from pandas.core.dtypes.dtypes import DatetimeTZDtype
      >>> is_datetime64_any_dtype(str)
      False
      >>> is_datetime64_any_dtype(int)
      False
      >>> is_datetime64_any_dtype(np.datetime64)  # can be tz-naive
      True
      >>> is_datetime64_any_dtype(DatetimeTZDtype("ns", "US/Eastern"))
      True
      >>> is_datetime64_any_dtype(np.array(['a', 'b']))
      False
      >>> is_datetime64_any_dtype(np.array([1, 2]))
      False
      >>> is_datetime64_any_dtype(np.array([], dtype="datetime64[ns]"))
      True
      >>> is_datetime64_any_dtype(pd.DatetimeIndex([1, 2, 3], dtype="datetime64[ns]"))
      True
      """
      if isinstance(arr_or_dtype, (np.dtype, ExtensionDtype)):
          # GH#33400 fastpath for dtype object
          return arr_or_dtype.kind == "M"
  
      if arr_or_dtype is None:
          return False
  
      try:
          tipo = _get_dtype(arr_or_dtype)
      except TypeError:
          return False
      return lib.is_np_dtype(tipo, "M") or isinstance(
          tipo, DatetimeTZDtype
      )
  
imports: from __future__ import annotations
  from typing import TYPE_CHECKING, Any, Callable
  import warnings
  import numpy
  from pandas._libs import Interval, Period, algos, lib
  from pandas._libs.tslibs import conversion
  from pandas.util._exceptions import find_stack_level
  from pandas.core.dtypes.base import _registry
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PeriodDtype, SparseDtype
  from pandas.core.dtypes.generic import ABCIndex
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, is_dataclass, is_decimal, is_dict_like, is_file_like, is_float, is_hashable, is_integer, is_interval, is_iterator, is_list_like, is_named_tuple, is_nested_list_like, is_number, is_re, is_re_compilable, is_scalar, is_sequence
label_desc: Use image node_id 21 for calling a global function with example usage: is_datetime64_any_dtype(arr_or_dtype) and returns: unknown, unknown, False, False