assemble_tt_variation_jets_trs
==============================

.. py:function:: t3toolbox.backend.sampling_derivatives.assemble_tt_variation_jets_trs(sigma_tildes, tau_tildes, deta_tildes, xi_jets, mu_jets, nu_jets, trs, n_probe, sum_over_probes)

   .. code-block:: python

      def assemble_tt_variation_jets_trs(
              sigma_tildes:   typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+K+C+(rR(i+1),)
              tau_tildes:     typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+K+C+(rL(i+1),)
              deta_tildes:    typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+K+C+(nUi,)
              xi_jets:        typ.Sequence[NDArray],  # frame input jets, len=d, elm_shape=(2,)+W+C+(nUi,)
              mu_jets:        typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+C+(rLi,)
              nu_jets:        typ.Sequence[NDArray],  # len=d, elm_shape=(order+1,)+W+C+(rR(i+1),)
              trs:            NDArray,                # binomial tensor, shape=(order+1,order+1,order+1)
              n_probe:        int,                    # number of sample-stack (W) axes
              sum_over_probes: bool,
      ) -> typ.Tuple[NDArray, ...]:                   # dG_tildes. len=d, elm_shape=[W+]C+(rLi,nUi,rRi)


   Assemble TT-core variation gradients (the 3-edge, trs case): three order-less trs outer products
   ``mu (x) xi (x) sigma_tilde + tau_tilde (x) xi (x) nu + mu (x) deta_tilde (x) nu`` (the core-adjoints
   of the forward sigma / tau / deta contractions).