ut3_apply
=========

.. py:function:: t3toolbox.backend.ut3_sampling.ut3_apply(data, vecs)

   .. code-block:: python

      def ut3_apply(
              data: UT3Data,
              vecs: typ.Sequence[NDArray],  # len=d, ith elm_shape=vec_stack+(Ni,)
      ) -> NDArray:                         # shape=vec_stack+stack_shape


   Contract a uniform Tucker tensor train with vectors in all modes (shares
   ``apply.t3_apply``). Vectors are zero-padded to ``N``.