import tensorflow as tf

#定义三行四列的零矩阵

tf.zeros([3,4])

#定义两行三列的全1矩阵

tf.ones([2,3])

#定义常量

tensor = tf.constant([1,2,3,4,5,6,7])

#定义两行三列全为-1的矩阵

tensor = tf.constant(-1.0.shape=[2,3])

#[10 11 12]

tf.linspace(10.0,12.0,3,name="linespace")

tf.range(start,end,delta)

#构造两行三列的均值为mean，方差为stddev的符合正态分布的矩阵

norm = tf.random_normal([2,3],mean=-1,stddev=4)

#洗牌操作

c = tf.constant([[1,2],[3,4],[5,6]])

shuff = tf.random_shuffle(c)

sess = tf.Session()
 print(sess.run(norm))
 print(sess.run(shuff))

#赋个初始值

state = tf.Variable(0)

#初始值加1

new_value = tf.add(state, tf.constant(1))

#更新

update = tf.assign(state, new_value)

with tf.Session() as sess:

   sess.run(tf.global_variables_initializer())

   print(sess.run(state))

   for _ in range(3):

        sess.run(update)

        print(sess.run(state))

#numpy向tensorflow转换

import numpy as np

a = np.zeros((3,3))

ta = tf.convert_to_tensor(a)

with tf.Session() as sess:

  print(sess.run(ta))

#tensorflow中的placeholder

input1 = tf.placeholder(tf.float32)

input2 = tf.placeholder(tf.float32)

output = tf.multiply(input1,input2)

with tf.Session() as sess:

    print(sess.run([output],feed_dict={input1:[7.],input2:[2.]}))