import tensorflow as tf

        self.v = DenseLayer(1, False, tf.nn.relu, initializers=self._initializers,
                                            regularizers=self._regularizers, name='OutputVector')
        self.score = tf.squeeze(self.v(self._cur_user * self._cur_item))
        negative_output = tf.squeeze(self.v(self._cur_user * self._cur_item_negative))
        tf.add_to_collection(GraphKeys.PREDICTION, self.score)
        self.loss = LossLayer()(self.score, negative_output)
        self._optimizer = OptimizerLayer(self.config.optimizer, clip=5.0,
                                         params={})
