BP實現手寫數字識別(1)

import matplotlib as mplimport tensorflow as tffrom tensorflow.examples.tutorials.mnist import input_datamnist = input_data.read_data_sets("MNIST_data", one_hot=True)x = tf.placeholder('flost',[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= tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)init = tf.initialize_all_variables()with tf.Session() as sess:    sess.run(init)    for i in range(1000):        batch_xs, batch_ys = mnist.train.next_batch(100)        sess.run(train, 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}))