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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def dt64arr_to_periodarr(data, freq, tz=None):
 """ Convert an datetime-like array to values Period ordinals. Parameters data : Union[Series[datetime64[ns]], DatetimeIndex, ndarray[datetime64ns]] freq : Optional[Union[str, Tick]] Must match the `freq` on the `data` if `data` is a DatetimeIndex or Series. tz : Optional[tzinfo] Returns ------- ordinals : ndarray[int] freq : Tick The frequencey extracted from the Series or DatetimeIndex if that's used. """

    if data.dtype != np.dtype('M8[ns]'):
        raise ValueError('Wrong dtype: {dtype}'.format(dtype=data.dtype))

    if freq is None:
        if isinstance(data, ABCIndexClass):
            data, freq = data._values, data.freq
        elif isinstance(data, ABCSeries):
            data, freq = data._values, data.dt.freq

    freq = Period._maybe_convert_freq(freq)

    if isinstance(data, (ABCIndexClass, ABCSeries)):
        data = data._values

    base, mult = libfrequencies.get_freq_code(freq)
    return libperiod.dt64arr_to_periodarr(data.view('i8'), base, tz), freq