TensorFlow MNIST案例代码

看了极客学院官方中文版http://wiki.jikexueyuan.com/index.php/project/tensorflow-zh/tutorials/mnist_beginners.html的翻译之后所得，我用的是TensorFlow的GPU版本，GPU型号是NVIDIA M40

from __future__ import absolute_import

from __future__ import division

from __future__ import print_function

import gzip

import os

import tempfile

import numpy

from six.moves import urllib

from six.moves import xrange

import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data

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

# from tensorflow.contrib.learn.python.learn.datasets.mnist import read_data_sets

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("float", [None, 10])

cross_entropy = -tf.reduce_sum(y_*tf.log(y))

train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)

init = tf.initialize_all_variables()

sess =tf.Session()

sess.run(init)

for i in range(1000):

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

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

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

accuracy = tf.reduce_mean(tf.cast(correct_prediction,"float"))

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