Tensorflow练手项目 - 使用DNN进行手写数字识别

首先书写如下的程序

#coding=utf-8
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
# number 1 to 10 data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)

def add_layer(inputs, in_size, out_size, activation_function=None ,):
    # add one more layer and return the output of this layer
    Weights = tf.Variable(tf.random_normal([in_size, out_size]))
    biases = tf.Variable(tf.zeros([1, out_size]) + 0.1 ,)
    Wx_plus_b = tf.matmul(inputs, Weights) + biases
    if activation_function is None:
        outputs = Wx_plus_b
    else:
        outputs = activation_function(Wx_plus_b ,)
    return outputs

def compute_accuracy(v_ys, y_pre):
    #global prediction
    #判断为1的位置是否相同
    correct_prediction = tf.equal(tf.argmax(y_pre ,1), tf.argmax(v_ys ,1))#
    accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
    return accuracy

# define placeholder for inputs to network
xs = tf.placeh