human
Complete the below
def _stata_elapsed_date_to_datetime_vec(dates, fmt):

    ''''Convert from SIF to datetime. http://www.stata.com/help.cgi?datetime
    Parameters
    dates : Series
    The Stata Internal Format date to convert to datetime according to fmt
    fmt : str
    The format to convert to. Can be, tc, td, tw, tm, tq, th, ty
    Returns
    Returns
    converted : Series
    The converted dates
    Examples
    >>> import pandas as pd
    >>> dates = pd.Series([52])
    >>> _stata_elapsed_date_to_datetime_vec(dates , "%tw")
    0   1961-01-01
    dtype: datetime64[ns]
    Notes
    datetime/c - tc
    milliseconds since 01jan1960 00:00:00.000, assuming 86,400 s/day
    datetime/C - tC - NOT IMPLEMENTED
    milliseconds since 01jan1960 00:00:00.000, adjusted for leap seconds
    date - td
    days since 01jan1960 (01jan1960 = 0)
    weekly date - tw
    weeks since 1960w1
    This assumes 52 weeks in a year, then adds 7 * remainder of the weeks.
    The datetime value is the start of the week in terms of days in the
    year, not ISO calendar weeks.
    monthly date - tm
    months since 1960m1
    quarterly date - tq
    quarters since 1960q1
    half-yearly date - th
    half-years since 1960h1 yearly
    date - ty
    years since 0000
    If you don\'t have pandas with datetime support, then you can\'t do
    milliseconds accurately.'
    '''

What is a the Python program you requested?
assistant
#Here is the Python program you requested.
    (MIN_YEAR, MAX_YEAR) = (Timestamp.min.year, Timestamp.max.year)
    MAX_DAY_DELTA = (Timestamp.max - datetime.datetime(1960, 1, 1)).days
    MIN_DAY_DELTA = (Timestamp.min - datetime.datetime(1960, 1, 1)).days
    MIN_MS_DELTA = (((MIN_DAY_DELTA * 24) * 3600) * 1000)
    MAX_MS_DELTA = (((MAX_DAY_DELTA * 24) * 3600) * 1000)
    def convert_year_month_safe(year, month):
        '\n                                Convert    year    and    month    to    datetimes,    using    pandas    vectorized    versions\n                                when    the    date    range    falls    within    the    range    supported    by    pandas.        Other\n                                wise    it    falls    back    to    a    slower    but    more    robust    method    using    datetime.\n                                '
        if ((year.max() < MAX_YEAR) and (year.min() > MIN_YEAR)):
            return to_datetime(((100 * year) + month), format='%Y%m')
        else:
            index = getattr(year, 'index', None)
            return Series([datetime.datetime(y, m, 1) for (y, m) in zip(year, month)], index=index)
    def convert_year_days_safe(year, days):
        '\n                                Converts    year    (e.g.    1999)    and    days    since    the    start    of    the    year    to    a\n                                datetime    or    datetime64    Series\n                                '
        if ((year.max() < (MAX_YEAR - 1)) and (year.min() > MIN_YEAR)):
            return (to_datetime(year, format='%Y') + to_timedelta(days, unit='d'))
        else:
            index = getattr(year, 'index', None)
            value = [(datetime.datetime(y, 1, 1) + relativedelta(days=int(d))) for (y, d) in zip(year, days)]
            return Series(value, index=index)
    def convert_delta_safe(base, deltas, unit):
        '\n                                Convert    base    dates    and    deltas    to    datetimes,    using    pandas    vectorized\n                                versions    if    the...