Tensorflow minist单层感知机

测试集准确率才86%. 官方文档有92%，奇怪了

from tensorflow.examples.tutorials.mnist import input_data
import tensorflow as tf

def load_data():
    mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
    return mnist

def build_model():
    x = tf.placeholder("float", shape=[None, 784])
    y_ = tf.placeholder("float", shape=[None, 10])
    W = tf.Variable(tf.zeros([784,10]))
    b = tf.Variable(tf.zeros([10]))
    y = tf.nn.softmax(tf.matmul(x,W) + b)
    return x,y_,y


def main():
    mnist = load_data()
    x,y_,y = build_model()
    cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1]))
    train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)
    sess = tf.InteractiveSession()
    sess.run(tf.initialize_all_variables())
    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, tf.float32))
    print(sess.run(accuracy, feed_dict={x: mnist.test.images, y_: mnist.test.labels}))

if __name__ == '__main__':
    main()