t3_tucker_weights_shared
========================

.. py:function:: t3toolbox.backend.sharing.t3_tucker_weights_shared(weights, sharing, rtol = 1e-09)

   .. code-block:: python

      def t3_tucker_weights_shared(
              weights:    typ.Tuple[
                  typ.Sequence[NDArray],  # tucker_weights. len=d,   elm_shape=stack_shape+(ni,)
                  typ.Sequence[NDArray],  # tt_weights.     len=d+1, elm_shape=stack_shape+(ri,)
              ],
              sharing:    typ.Sequence,   # len=d, static; one hashable group label per mode
              rtol:       float = 1e-9,   # relative tolerance on the Tucker-weight deviation
      ) -> NDArray:  # bool array, shape = stack_shape (scalar/0-d when unstacked)


   True (per stack element) where the Tucker weights are equal within every sharing group --
   the boolean form of :py:func:`t3_tucker_weights_sharing_residual`. A non-enforcing checker:
   absorbing group-UNEQUAL weights into a tied T3 is legitimate (it just unties the result --
   repair with :py:func:`t3_tie_tucker_factors` or re-enter with ``share`` if wanted).