def score(self, data, data_ref, graph=None):
        """Compute the reconstruction loss over the test set.

        Parameters
        ----------

        data : array_like
            Data to reconstruct.

        data_ref : array_like
            Reference data.

        Returns
        -------

        float: Mean error.
        """
        g = graph if graph is not None else self.tf_graph

        with g.as_default():
            with tf.Session() as self.tf_session:
                self.tf_saver.restore(self.tf_session, self.model_path)
                feed = {
                    self.input_data: data,
                    self.input_labels: data_ref,
                    self.keep_prob: 1
                }
                return self.cost.eval(feed)
Compute the reconstruction loss over the test set.

        Parameters
        ----------

        data : array_like
            Data to reconstruct.

        data_ref : array_like
            Reference data.

        Returns
        -------

        float: Mean error.