TensorFlow学习笔记（二十） tensorflow实现简单三层网络

代码：

import tensorflow as tf

w1= tf.Variable(tf.random_normal([2, 3], stddev=1, seed=1))
w2= tf.Variable(tf.random_normal([3, 1], stddev=1, seed=1))
x = tf.constant([[0.7, 0.9]])  

a = tf.matmul(x, w1)
y = tf.matmul(a, w2)

sess = tf.Session()
sess.run(w1.initializer)  
sess.run(w2.initializer)  
print(sess.run(y))  
sess.close()

结果：

[[ 3.95757794]]

对上面代码修改一下,

1. 如果使用placeholder，则这样写

x = tf.placeholder(tf.float32, shape=(1, 2), name="input")
a = tf.matmul(x, w1)
y = tf.matmul(a, w2)
sess = tf.Session()
init_op = tf.global_variables_initializer()  
sess.run(init_op)
print(sess.run(y, feed_dict={x: [[0.7,0.9]]}))

2. 如果有多个输入值X，则用placeholder这样定义：

x = tf.placeholder(tf.float32, shape=(3, 2), name="input")
a = tf.matmul(x, w1)
y = tf.matmul(a, w2)

sess = tf.Session()
#使用tf.global_variables_initializer()来初始化所有的变量
init_op = tf.global_variables_initializer()  
sess.run(init_op)
print(sess.run(y, feed_dict={x: [[0.7,0.9],[0.1,0.4],[0.5,0.8]]}))