github地址https://github.com/fz861062923/TensorFlow
#建立‘计算图’
import tensorflow as tf
x=tf.constant(2,name='x')#建立常量,有点像C
y=tf.Variable(x+5,name='y')#建立变量
#执行‘计算图’
with tf.Session() as sess:
init=tf.global_variables_initializer()#初始化global变量
sess.run(init)
print('x=',sess.run(x))
print('y=',sess.run(y))
x= 2
y= 7
x
正如这个名字一样,hold on,hold on,告诉计算机等等在把值传给你,嘻嘻嘻嘻
a=tf.placeholder('int32')
b=tf.placeholder('int32')
c=tf.multiply(a,b)
with tf.Session() as sess:
init=tf.global_variables_initializer()
sess.run(init)
print('c=',sess.run(c,feed_dict={a:6,b:7}))
c= 42
正如其名,可视化已经建立的计算图
#承接上面的session
#下面代码将显示在tensorboard的数据写在log文件中
tf.summary.merge_all()#将显示在board的数据整合
train_writer=tf.summary.FileWriter('log/c',sess.graph)#写入log文件中
ts_x=tf.Variable([0.4,0.2,0.4])
with tf.Session() as sess:
init=tf.global_variables_initializer()
sess.run(init)
x=sess.run(ts_x)
print(x)
[0.4 0.2 0.4]
x.shape
(3,)
ts_x=tf.Variable([[0.4,0.2,0.4]])
with tf.Session() as sess:
init=tf.global_variables_initializer()
sess.run(init)
x=sess.run(ts_x)
print(x)
[[0.4 0.2 0.4]]
x.shape
(1, 3)
ts_x=tf.Variable([[0.4,0.2],
[0.3,0.4],
[-0.5,0.2]])
with tf.Session() as sess:
init=tf.global_variables_initializer()
sess.run(init)
x=sess.run(ts_x)
print(x)
[[ 0.4 0.2]
[ 0.3 0.4]
[-0.5 0.2]]
x.shape
(3, 2)
x=tf.Variable([[1.,1.,1.]])
w=tf.Variable([[-0.1,-0.2],
[-0.3,0.4],
[0.5,0.6]])
xw=tf.matmul(x,w)
with tf.Session() as sess:
init=tf.global_variables_initializer()
sess.run(init)
print(sess.run(xw))
[[0.09999999 0.8 ]]
x=tf.Variable([[1.,1.,1.]])
w=tf.Variable([[-0.1,-0.2],
[-0.3,0.4],
[0.5,0.6]])
b=tf.Variable([[0.1,0.2]])
xwb=tf.matmul(x,w)+b
with tf.Session() as sess:
init=tf.global_variables_initializer()
sess.run(init)
print(sess.run(xwb))
[[0.19999999 1. ]]