import tensorflow as tf

            print("episodes %d" % len(episode_rewards))
            print("exploration %f" % exploration.value(t))
            print("learning_rate %f" % optimizer_spec.lr_schedule.value(t))
            mean_rew_summ = tf.Summary(value=[tf.Summary.Value(tag='mean_rew',simple_value=mean_episode_reward)])
            best_mean_rew_summ = tf.Summary(value=[tf.Summary.Value(tag='best_mean_rew',simple_value=best_mean_episode_reward)])
            writer.add_summary(mean_rew_summ, global_step=t)
