Problem.objective
=================

.. py:method:: t3toolbox.backend.optimizers.Problem.objective(x_cores, sample=None, data=None)

   .. code-block:: python

      def objective(self, x_cores: Tangent, sample=None, data=None):


   ``½‖S(x)-data‖²`` (+ ``ρ(x)`` if regularized) on the full data (``sample=None``) or an explicit
   minibatch; no frame sweep (cheap -- for the line search / the full-batch stop signal). The reg term
   reads ``x_cores`` directly, so on the manifold it assumes ``x_cores`` is left-orthogonal (true for a
   retraction output -- the line-search points; ``dev/regularization_design.md`` §4a).