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import tensorflow as tfa_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，该函数保证其辖域中的操作必须要在该函数所传递的参数中的操作完成后再进行    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)

输出：

Add:  12

import tensorflow as tfa_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)输出：Add:  3Add_with_dependency:  12

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