code: def _validate_date_like_dtype(dtype):
      """
      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
                   the frequency provided is too specific)
      """
  
      try:
          typ = np.datetime_data(dtype)[0]
      except ValueError as e:
          raise TypeError("{error}".format(error=e))
      if typ != "generic" and typ != "ns":
          msg = "{name!r} is too specific of a frequency, try passing {type!r}"
          raise ValueError(
              msg.format(name=dtype.name, type=dtype.type.__name__)
          )
  
imports: import warnings
  import numpy
  from pandas._libs import algos, lib
  from pandas._libs.tslibs import conversion
  from pandas.compat import PY3, PY36, string_types
  from pandas.core.dtypes.dtypes import CategoricalDtype, DatetimeTZDtype, ExtensionDtype, IntervalDtype, PandasExtensionDtype, PeriodDtype, registry
  from pandas.core.dtypes.generic import ABCCategorical, ABCDateOffset, ABCDatetimeIndex, ABCIndexClass, ABCPeriodArray, ABCPeriodIndex, ABCSeries
  from pandas.core.dtypes.inference import is_array_like, is_bool, is_complex, 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, is_string_like
label_desc: Use image node_id 50 for calling a global function with example usage: _validate_date_like_dtype(dtype) without return types