def _restore_slim(self, variables):
        """ Restore from tf-slim file (usually a ImageNet pre-trained model). """
        variables_to_restore = self.get_variables_in_checkpoint_file(self.flags['RESTORE_SLIM_FILE'])
        variables_to_restore = {self.name_in_checkpoint(v): v for v in variables if (self.name_in_checkpoint(v) in variables_to_restore)}
        if variables_to_restore is []:
            print('Check the SLIM checkpoint filename. No model variables matched the checkpoint variables.')
            exit()
        saver = tf.train.Saver(variables_to_restore)
        saver.restore(self.sess, self.flags['RESTORE_SLIM_FILE'])
        print("Model restored from %s" % self.flags['RESTORE_SLIM_FILE'])
Restore from tf-slim file (usually a ImageNet pre-trained model).