code: def score(self, data, data_ref, graph=None):
          
          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)
docs: 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.