def objects_to_td64ns(data, unit="<STR_LIT>", errors="<STR_LIT>"):
<EOL>values = np.array(data, dtype=np.object_, copy=False)<EOL>result = array_to_timedelta64(values,<EOL>unit=unit, errors=errors)<EOL>return result.view('<STR_LIT>')<EOL>
Convert a object-dtyped or string-dtyped array into an
timedelta64[ns]-dtyped array.

Parameters
----------
data : ndarray or Index
unit : str, default "ns"
    The timedelta unit to treat integers as multiples of.
errors : {"raise", "coerce", "ignore"}, default "raise"
    How to handle elements that cannot be converted to timedelta64[ns].
    See ``pandas.to_timedelta`` for details.

Returns
-------
numpy.ndarray : timedelta64[ns] array converted from data

Raises
------
ValueError : Data cannot be converted to timedelta64[ns].

Notes
-----
Unlike `pandas.to_timedelta`, if setting `errors=ignore` will not cause
errors to be ignored; they are caught and subsequently ignored at a
higher level.