code: def _validate_date_like_dtype(dtype) -> None:
      """
      Check whether the dtype is a date-like dtype. Raises an error if invalid.
  
      Parameters
      ----------
      dtype : dtype, type
          The dtype to check.
  
      Raises
      ------
      TypeError : The dtype could not be casted to a date-like dtype.
      ValueError : The dtype is an illegal date-like dtype (e.g. the
                   frequency provided is too specific)
      """
      try:
          typ = np.datetime_data(dtype)[0]
      except ValueError as e:
          raise TypeError(e) from e
      if typ not in ["generic", "ns"]:
          raise ValueError(
              f"{repr(dtype.name)} is too specific of a frequency, "
              f"try passing {repr(dtype.type.__name__)}"
          )
  
imports: from __future__ import annotations
  from typing import Any, Callable
  import warnings
  import numpy
  from pandas._libs import Interval, Period, algos, lib
  from pandas._libs.tslibs import conversion
  from pandas._typing import ArrayLike, DtypeObj
  from pandas.core.dtypes.base import _registry
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PeriodDtype
  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 42 for calling a global function with example usage: _validate_date_like_dtype(dtype) without return types