TensorFlow tf.control_dependencies

import tensorflow as tf
a_1 = tf.Variable(1)
b_1 = tf.Variable(2)
update_op1 = tf.assign(a_1, 10)
add = tf.add(a_1, b_1)

a_2 = tf.Variable(1)
b_2 = tf.Variable(2)
update_op2 = tf.assign(a_2, 10)
with tf.control_dependencies([update_op1,update_op2]):#tf.control_dependencies，該函數保證其轄域中的操作必須要在該函數所傳遞的參數中的操作完成後再進行
    add_with_dependencies = tf.add(a_2, a_1)

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    ans_1, ans_2 = sess.run([add, add_with_dependencies])
    print("Add: ", ans_1)
    print("Add_with_dependency: ", ans_2)

輸出：

Add:  12
Add_with_dependency:  20

import tensorflow as tf
a_1 = tf.Variable(1)
b_1 = tf.Variable(2)
update_op = tf.assign(a_1, 10)
add = tf.add(a_1, b_1)

a_2 = tf.Variable(1)
b_2 = tf.Variable(2)
update_op = tf.assign(a_2, 10)
with tf.control_dependencies([update_op]):
    add_with_dependencies = tf.add(a_2, b_2)

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    ans_1, ans_2 = sess.run([add, add_with_dependencies])
    print("Add: ", ans_1)
    print("Add_with_dependency: ", ans_2)

輸出：
Add:  3
Add_with_dependency:  12