entries_model
=============

.. py:function:: t3toolbox.fitting.entries_model(geometry, x, index, residual, regularizer = None)

   .. code-block:: python

      def entries_model(
              geometry,                            # MANIFOLD / COREWISE (or the UNIFORM_* twin for a uniform x)
              x:          typ.Union[t3.TuckerTensorTrain, ut3.UniformTuckerTensorTrain],   # the current point
              index:      NDArray,                 # int, shape=(d,)+W -- the grid points
              residual:   NDArray,                 # r = entries(x) − y, shape W+C
              regularizer: typ.Any = None,         # optional regularizer, e.g. optimizers.IdentityRegularizer(λ)
      ) -> typ.Union[GaussNewtonModel, UniformGaussNewtonModel]:


   The Gauss-Newton model of an all-modes ``entries`` least-squares objective at ``x``, on ``geometry``.

   Identical to :py:func:`apply_model` but the measurements are tensor **entries** at integer grid points
   ``index`` (shape ``(d,)+W``) rather than applies against probe vectors.