1.安装

sudo pip  install --index http://pypi.douban.com/simple --trusted-host pypi.douban.com tensorflow

2.mnist_softmax.py脚本

#!/usr/local/python

from tensorflow.examples.tutorials.mnist import input_data

mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

import tensorflow as tf

x = tf.placeholder(tf.float32, [None, 784])

W = tf.Variable(tf.zeros([784, 10]))

b = tf.Variable(tf.zeros([10]))

y = tf.nn.softmax(tf.matmul(x, W) + b)

y_ = tf.placeholder(tf.float32, [None, 10])

#train

cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1]))

train_step = tf.train.GradientDescentOptimizer(0.05).minimize(cross_entropy)

sess = tf.InteractiveSession()

tf.global_variables_initializer().run()

for _ in range(1000):

      batch_xs, batch_ys = mnist.train.next_batch(100)

      sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})

#Evaluating

correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))

accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))

print(sess.run(accuracy, feed_dict={x: mnist.test.images, y_: mnist.test.labels}))

3.运行demo

从http://yann.lecun.com/exdb/mnist/下载mnist数据放到tensorflow/examples/tutorials/mnist/MNIST_data;在tensorflow/examples/tutorials/mnist/运行mnist_softmax.py