code: def validate_dtype_freq(
      dtype, freq: BaseOffsetT | timedelta | str | None
  ) -> BaseOffsetT:
      """
      If both a dtype and a freq are available, ensure they match.  If only
      dtype is available, extract the implied freq.
  
      Parameters
      ----------
      dtype : dtype
      freq : DateOffset or None
  
      Returns
      -------
      freq : DateOffset
  
      Raises
      ------
      ValueError : non-period dtype
      IncompatibleFrequency : mismatch between dtype and freq
      """
      if freq is not None:
          # error: Incompatible types in assignment (expression has type
          # "BaseOffset", variable has type "Union[BaseOffsetT, timedelta,
          # str, None]")
          freq = to_offset(freq)  # type: ignore[assignment]
  
      if dtype is not None:
          dtype = pandas_dtype(dtype)
          if not is_period_dtype(dtype):
              raise ValueError("dtype must be PeriodDtype")
          if freq is None:
              freq = dtype.freq
          elif freq != dtype.freq:
              raise IncompatibleFrequency(
                  "specified freq and dtype are different"
              )
      # error: Incompatible return value type (got "Union[BaseOffset, Any, None]",
      # expected "BaseOffset")
      return freq
  
imports: from __future__ import annotations
  from datetime import timedelta
  import operator
  from typing import TYPE_CHECKING, Any, Callable, Literal, Sequence, TypeVar, overload
  import numpy
  from pandas._libs import algos, lib
  from pandas._libs.arrays import NDArrayBacked
  from pandas._libs.tslibs import BaseOffset, NaT, NaTType, Timedelta, astype_overflowsafe, dt64arr_to_periodarr, get_unit_from_dtype, iNaT, parsing, period, to_offset
  from pandas._libs.tslibs.dtypes import FreqGroup
  from pandas._libs.tslibs.fields import isleapyear_arr
  from pandas._libs.tslibs.offsets import Tick, delta_to_tick
  from pandas._libs.tslibs.period import DIFFERENT_FREQ, IncompatibleFrequency, Period, get_period_field_arr, period_asfreq_arr
  from pandas._typing import AnyArrayLike, Dtype, NpDtype, npt
  from pandas.util._decorators import cache_readonly, doc
  from pandas.core.dtypes.common import ensure_object, is_datetime64_any_dtype, is_datetime64_dtype, is_dtype_equal, is_float_dtype, is_integer_dtype, is_period_dtype, pandas_dtype
  from pandas.core.dtypes.dtypes import PeriodDtype
  from pandas.core.dtypes.generic import ABCIndex, ABCPeriodIndex, ABCSeries, ABCTimedeltaArray
  from pandas.core.dtypes.missing import isna
  import pandas.core.algorithms
  from pandas.core.arrays import datetimelike
  import pandas.core.common
label_desc: Use image node_id 6 for calling a global function with example usage: validate_dtype_freq(dtype, freq) and returns: freq