用tensorflow构建两层简单神经网络（全连接）

中国大学Mooc 北京大学 人工智能实践：Tensorflow笔记(week3)

#coding:utf-8
#两层简单神经网络（全连接）

import tensorflow as tf

#定义输入和参数
#用placeholder实现输入定义（sess.run中喂一组数据）
x = tf.placeholder(tf.float32, shape = (None, 2))
w1 = tf.Variable(tf.random_normal([2, 3], stddev = 1, seed = 1))
w2 = tf.Variable(tf.random_normal([3, 1], stddev = 1, seed = 1))

#定义向前传播过程
a = tf.matmul(x, w1)
y = tf.matmul(a, w2)


#用会话计算结果
with tf.Session() as sess:
    init_op = tf.global_variables_initializer()
    sess.run(init_op)
    print("the result of this exercise is \n", sess.run(y, feed_dict = {x:[[0.7, 0.5], [0.2, 0.3], [0.3, 0.4], [0.4, 0.5]]}))
    print("w1\n", sess.run(w1))
    print("w2\n", sess.run(w2))