code: def objects_to_td64ns(data, unit="ns", errors="raise"):
      
      # coerce Index to np.ndarray, converting string-dtype if necessary
      values = np.array(data, dtype=np.object_, copy=False)
  
      result = array_to_timedelta64(values,
                                    unit=unit, errors=errors)
      return result.view('timedelta64[ns]')
docs: 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.