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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 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)