value_function.py 文件源码

def create_net(self, shape):
        hidden_size = 64
        print(shape)
        self.x = tf.placeholder(tf.float32, shape=[None, shape], name="x")
        self.y = tf.placeholder(tf.float32, shape=[None], name="y")

        weight_init = tf.random_uniform_initializer(-0.05, 0.05)
        bias_init = tf.constant_initializer(0)

        with tf.variable_scope("VF"):
            h1 = tf.nn.relu(fully_connected(self.x, shape, hidden_size, weight_init, bias_init, "h1"))
            h2 = tf.nn.relu(fully_connected(h1, hidden_size, hidden_size, weight_init, bias_init, "h2"))
            h3 = fully_connected(h2, hidden_size, 1, weight_init, bias_init, "h3")
        self.net = tf.reshape(h3, (-1,))
        l2 = tf.nn.l2_loss(self.net - self.y)
        self.train = tf.train.AdamOptimizer().minimize(l2)
        self.session.run(tf.initialize_all_variables())