run_siloz.py 文件源码

def run(settings):
    recreate_subdirectory_structure(settings)
    tf.reset_default_graph()

    with tf.device("/cpu:0"):
        global_step = tf.Variable(0, dtype=tf.int32, name='global_episodes', trainable=False)
        optimizer = tf.train.AdamOptimizer(learning_rate=settings["lr"])
        global_network = ACNetwork('global', None)

        num_agents = 1
        agents = []
        envs = []
        for i in range(num_agents):
            if settings["game"] == '11arms':
                this_env = ElevenArms()
            else:
                this_env = TwoArms(settings["game"])
            envs.append(this_env)

        for i in range(num_agents):
            agents.append(Agent(envs[i], i, optimizer, global_step, settings))
        saver = tf.train.Saver(max_to_keep=5)

    with tf.Session() as sess:
        coord = tf.train.Coordinator()
        if FLAGS.resume:
            if FLAGS.hypertune:
                ckpt = tf.train.get_checkpoint_state(settings["checkpoint_dir"])
            else:
                ckpt = tf.train.get_checkpoint_state(settings["load_from"])
            print("Loading Model from {}".format(ckpt.model_checkpoint_path))
            saver.restore(sess, ckpt.model_checkpoint_path)
        else:
            sess.run(tf.global_variables_initializer())

        agent_threads = []
        for agent in agents:
            agent_play = lambda: agent.play(sess, coord, saver)
            thread = threading.Thread(target=agent_play)
            thread.start()
            agent_threads.append(thread)
        coord.join(agent_threads)