'Builds a beam search based training loop for this component.
The default implementation builds a dummy graph and raises a
TensorFlow runtime exception to indicate that structured training
is not implemented.
Args:
state: MasterState from the \'AdvanceMaster\' op that advances the
underlying master to this component.
network_states: dictionary of component NetworkState objects.
Returns:
(handle, cost, correct, total) -- These are TF ops corresponding
to the final handle after unrolling, the total cost, and the
total number of actions. Since the number of correctly predicted
actions is not applicable in the structured training setting, a
dummy value should returned.'

def build_structured_training(self, state, network_states):

    del network_states
    with tf.control_dependencies([tf.Assert(False, ['Not    implemented.'])]):
        handle = tf.identity(state.handle)
    cost = tf.constant(0.0)
    (correct, total) = (tf.constant(0), tf.constant(0))
    return (handle, cost, correct, total)
