t3_sum
======

.. py:function:: t3toolbox.backend.t3_operations.t3_sum(x, axis = None)

   .. code-block:: python

      def t3_sum(
              x: typ.Tuple[
                  typ.Tuple[NDArray, ...],  # tucker_cores. len=d, elm_shape=stack_shape+(ni,Ni)
                  typ.Tuple[NDArray, ...],  # tt_cores.     len=d, elm_shape=stack_shape+(rLi,ni,rR(i+1))
              ],
              axis: typ.Union[int, typ.Sequence[int], None] = None,  # modes to sum (None -> all); negatives wrap
      ):  # -> T3 data tuple over the remaining modes, or a scalar NDArray (shape=stack_shape) if all modes summed


   Sum over axes of TuckerTensorTrain.