Logout
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print("hello world")
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import tensorflow as tf
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#创建两个常量op
m1 = tf.constant([[3,3]])
m2 = tf.constant([[2],[3]])
#创建一个矩阵乘法op，把m1和m2传入
product = tf.matmul(m1,m2)
print(product)
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#第2—1课 ： 创建图，启动图
#定义一个会话，启动默认图
sess = tf.Session()
#调用sess的run方法来执行矩阵乘法op
#run(product)触发了图中3个op
result = sess.run(product)
print(result)
sess.close()
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with tf.Session() as sess:
#调用sess的run方法来执行矩阵乘法op
#run(product)触发了图中3个op
result = sess.run(product)
print(result)
#这里就不用关闭会话，系统自动关闭
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#第2—2课 ： 变量
x = tf.Variable([1,2])
a = tf.constant([3,3])
#增加一个减法op
sub = tf.subtract(x,a)
#增加一个加法op
add = tf.add(x,sub)
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
print(sess.run(sub))
print(sess.run(add))
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#创建一个变量初始化为0
state = tf.Variable(0,name='counter') #起名字
#创建一个op，作用是使state + 1
new_value = tf.add(state,1)
#赋值op
update = tf.assign(state,new_value)
#因为我们使用了变量，所以需要变量初始化
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
print(sess.run(state))
for _ in range(5):
sess.run(update)
print(sess.run(state))
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#第2—3课 ： Fetch and Feed
input1 = tf.constant(3.0)
input2 = tf.constant(2.0)
input3 = tf.constant(5.0)
add = tf.add(input1,input2)
mul = tf.multiply(input1,add)
#
with tf.Session() as sess:
result = sess.run([mul,add])#同时执行多个op
print(result)
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#Feed
#创建占位符
input1 = tf.placeholder(tf.float32)
input2 = tf.placeholder(tf.float32)
output = tf.multiply(input1,input2)
#运行op时才传入变量的值
with tf.Session() as sess:
#feed的数据以字典的形式传入
print(sess.run(output,feed_dict={input1:[8.],input2:[2.]}))
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