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-8 -*-import tensorflow as tffrom tensorflow.examples.tutorials.mnist import input_datamnist = input_data.read_data_sets("E:/testdata/MNIST/", one_hot=True)x = tf.placeholder("float", [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.global_variables_initializer()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}))

注：研究了一下数据流向，画了张图