UT3Weights.is_consistent_with
=============================

.. py:method:: t3toolbox.uniform_tucker_tensor_train.UT3Weights.is_consistent_with(x)

   .. code-block:: python

      def is_consistent_with(self, x: 'UniformTuckerTensorTrain') -> bool:


   True iff these weights can be absorbed into ``x`` (non-raising).

   Requires that the padded shapes fit **and that the edge masks are equal**.

   The mask equality is the real content, and it is a check ragged does not need: ragged catches a
   rank mismatch as an einsum shape error (a length-``n`` weight vector against a rank-``n`` core),
   but uniform pads both to the common ``(n, r)``, so a mismatch is invisible to the shapes and would
   silently corrupt -- a weight whose mask calls slot ``i`` padding carries a canonical zero there,
   and absorbing it would **zero a real slot** of ``x``. The same precondition uniform adds to
   variation add/sub (``docs/uniform_masks_vs_ranks.md``).