MNIST机器学习入门+tensorboard_mnist训练集tensorboard

代码如下：

#!/usr/bin/python
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(tf.float32, [None, 10])

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

train_step = tf.train.GradientDescentOptimizer(0.5).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(64)
  sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
  writer = tf.train.SummaryWriter("logs/",sess.graph)
  writer.close()
correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
accuracy = 
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