def METHOD_NAME(arg, unit=None, errors="raise", name=None):
    """Convert a list of objects to a timedelta index object."""
    if isinstance(arg, (list, tuple)) or not hasattr(arg, "dtype"):
        # This is needed only to ensure that in the case where we end up
        #  returning arg (errors == "ignore"), and where the input is a
        #  generator, we return a useful list-like instead of a
        #  used-up generator
        arg = np.array(list(arg), dtype=object)
    try:
        td64arr = sequence_to_td64ns(arg, unit=unit, errors=errors, copy=False)[0]
    except ValueError:
        if errors == "ignore":
            return arg
        else:
            # This else-block accounts for the cases when errors='raise'
            # and errors='coerce'. If errors == 'raise', these errors
            # should be raised. If errors == 'coerce', we shouldn't
            # expect any errors to be raised, since all parsing errors
            # cause coercion to pd.NaT. However, if an error / bug is
            # introduced that causes an Exception to be raised, we would
            # like to surface it.
            raise
    from pandas import TimedeltaIndex
    value = TimedeltaIndex(td64arr, unit="ns", name=name)
    return value