minst数据集怎么跑

方法一：命令行跑程序 参考http://blog.csdn.net/zhuiqiuk/article/details/52993544

（我用的python3，注意print的语法）

 

方法二：用IDE跑

将下好的mnist数据集拷贝到pycharm中,文件夹命名为MNIST_data

再创建一个python脚本，代码如下

import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("./MNIST_data/", one_hot=True)


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}))

 

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