code: def _save_model(self, steps=0):
          
          for brain_name in self.trainers.keys():
              self.trainers[brain_name].save_model()
          self.logger.info('Saved Model')
docs: Saves current model to checkpoint folder.
          :param steps: Current number of steps in training process.
          :param saver: Tensorflow saver for session.