run_agent.py 文件源码

def run_agent(save_path, T, game_name):
    with tf.Session() as sess:
        agent = Agent(session=sess, observation_shape=(210,160,3),
        action_size=3,
        optimizer=tf.train.AdamOptimizer(1e-4))

        # Create a saver, and only keep 2 checkpoints.
        saver = tf.train.Saver()

        saver.restore(sess, save_path + '-' + str(T))

        play(agent, game_name)

        return sess, agent