tensorflow 1.x practical tutorial (2) - simple variable operation

Target

This article aims to introduce the introductory knowledge points and practical examples of tensorflow. I hope that all novice students can be proficient in tensorflow related operations after learning.

simple variable operations

import tensorflow as tf
x = tf.Variable([9,10])
y = tf.constant([4,4])
sub = tf.subtract(x, y)
add = tf.add(x, y)
init = tf.global_variables_initializer() # 这里因为 graph 中有变量 x ，所以要有一个操作对 graph 中的变量进行初始化
with tf.Session() as sess:
    sess.run(init)
    print(sess.run([sub, add]))
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output result

[array([5, 6], dtype=int32), array([13, 14], dtype=int32)]
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Advanced - variable auto-increment

import tensorflow as tf
state = tf.Variable(0, name='state')
add = tf.add(state, 2) # 为 state 加 2
update = tf.assign(state, add) # 将变化之后的 add 赋值给 state 完成值的更新
init = tf.global_variables_initializer()
with tf.Session() as sess:
    sess.run(init)
    print(sess.run(state)) # 输出原始的 state 值
    for _ in range(3):
        sess.run(update) # update 操作中已经包含了加法和赋值两个操作
        print(sess.run(state)) # 输出变化之后的 state 值
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output result

0
2
4
6   
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Reference in this article

Reference for this article: blog.csdn.net/qq_19672707…