TensorFlow保存读取数据

保存数据

import tensorflow as tf

# 声明两个变量
v1 = tf.Variable(tf.random_normal([1, 2]), name="v1")  #1*2的矩阵
v2 = tf.Variable(tf.random_normal([2, 3]), name="v2")  #2*3的矩阵
init_op = tf.global_variables_initializer() # 初始化全部变量
saver = tf.train.Saver() #保存
with tf.Session() as sess:
    sess.run(init_op)

    print("v1:", sess.run(v1)) # 打印v1、v2的值一会读取之后对比
    print("v2:", sess.run(v2))
    saver_path = saver.save(sess, "path\\model.ckpt")  # 将模型保存到save/model.ckpt文件
    print("Model saved in file:", saver_path)

读取数据

import tensorflow as tf

# 使用和保存模型代码中一样的方式来声明变量
v1 = tf.Variable(tf.random_normal([1, 2]), name="v1")
v2 = tf.Variable(tf.random_normal([2, 3]), name="v2")
saver = tf.train.Saver() 
with tf.Session() as sess:
    saver.restore(sess, "path\\model.ckpt")

    print("v1:", sess.run(v1)) # 打印v1、v2的值和之前的进行对比
    print("v2:", sess.run(v2))
    print("Model Restored")