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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 generate_regular_range(start, end, periods, freq):
 """ Generate a range of dates with the spans between dates described by the given `freq` DateOffset. Parameters start : Timestamp or None first point of produced date range end : Timestamp or None last point of produced date range periods : int number of periods in produced date range freq : DateOffset describes space between dates in produced date range Returns ------- ndarray[np.int64] representing nanosecond unix timestamps """

    if isinstance(freq, Tick):
        stride = freq.nanos
        if periods is None:
            b = Timestamp(start).value
            # cannot just use e = Timestamp(end) + 1 because arange breaks when
            # stride is too large, see GH10887
            e = (b + (Timestamp(end).value - b) // stride * stride +
                 stride // 2 + 1)
            # end.tz == start.tz by this point due to _generate implementation
            tz = start.tz
        elif start is not None:
            b = Timestamp(start).value
            e = _generate_range_overflow_safe(b, periods, stride, side='start')
            tz = start.tz
        elif end is not None:
            e = Timestamp(end).value + stride
            b = _generate_range_overflow_safe(e, periods, stride, side='end')
            tz = end.tz
        else:
            raise ValueError("at least 'start' or 'end' should be specified "
                             "if a 'period' is given.")

        with np.errstate(over="raise"):
            # If the range is sufficiently large, np.arange may overflow
            #  and incorrectly return an empty array if not caught.
            try:
                values = np.arange(b, e, stride, dtype=np.int64)
            except FloatingPointError:
                xdr = [b]
                while xdr[-1] != e:
                    xdr.append(xdr[-1] + stride)
                values = np.array(xdr[:-1], dtype=np.int64)

    else:
        tz = None
        # start and end should have the same timezone by this point
        if start is not None:
            tz = start.tz
        elif end is not None:
            tz = end.tz

        xdr = generate_range(start=start, end=end,
                             periods=periods, offset=freq)

        values = np.array([x.value for x in xdr], dtype=np.int64)

    return values, tz