Tensorflow基础1

变量OP 存储模型参数
存储持久化
可修改值
可指定被训练

变量需要显式初始化 才能运行值

def variable_demo():
    """
    变量的演示
    :return:
    """
    # 创建变量
    with tf.variable_scope("my_scope"):
        a = tf.Variable(initial_value=50)
        b = tf.Variable(initial_value=40)
    with tf.variable_scope("your_scope"):
        c = tf.add(a, b)
    print("a:\n", a)
    print("b:\n", b)
    print("c:\n", c)

    # 初始化变量
    init = tf.global_variables_initializer()

    # 开启会话
    with tf.Session() as sess:
        # 运行初始化
        sess.run(init)
        a_value, b_value, c_value = sess.run([a, b, c])
        print("a_value:\n", a_value)
        print("b_value:\n", b_value)
        print("c_value:\n", c_value)

    return None