import tensorflow as tf

        # Placeholders
        self.sess = tf.Session(config=config)
        self.s_dim, self.a_dim = env.observation_space.shape, env.action_space.shape[0]
        self.a_bound = (env.action_space.high - env.action_space.low) / 2
        self.actions = tf.placeholder(tf.float32, [None, self.a_dim], 'action')
        self.state = tf.placeholder(tf.float32, [None, self.s_dim[0]], 'state')
        self.advantage = tf.placeholder(tf.float32, [None, 1], 'advantage')
        self.rewards = tf.placeholder(tf.float32, [None, 1], 'discounted_r')
