TensorFlow学习笔记(二)-- MNIST机器学习入门程序学习

时间:2024-09-01 00:03:32

此程序被称为TF的 Hello World,19行代码,给人感觉很简单。
第一遍看的时候,不到半个小时,就把程序看完了。
感觉有点囫囵吞枣的意思,没理解透彻。
现在回过头来看,感觉还可以从中学到更多东西。

# -*- coding:utf- -*-

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets("E:/testdata/MNIST/", one_hot=True)
x = tf.placeholder("float", [None, ])
W = tf.Variable(tf.zeros([, ]))
b = tf.Variable(tf.zeros([]))
y = tf.nn.softmax(tf.matmul(x, W) + b)
y_ = tf.placeholder("float", [None, ])
cross_entropy = -tf.reduce_sum(y_ * tf.log(y))
train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)
init = tf.global_variables_initializer()
sess = tf.Session()
sess.run(init)
for i in range():
batch_xs, batch_ys = mnist.train.next_batch()
sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
correct_prediction = tf.equal(tf.argmax(y, ), tf.argmax(y_, ))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
print(sess.run(accuracy, feed_dict={x: mnist.test.images, y_: mnist.test.labels}))

注:研究了一下数据流向,画了张图

TensorFlow学习笔记(二)-- MNIST机器学习入门程序学习