import numpy as np

import tensorflow as tf

#build a graph

print("build a graph")

#生产变量tensor

a=tf.constant([[1,2],[3,4]])

b=tf.constant([[1,1],[0,1]])

#获取tensor的数据类型和张量维度

print("a.dtype",a.dtype)

print(a.get_shape())

print("type of a:",type(a))

#基本的数据运算

c=tf.matmul(a,b)

d=tf.subtract(a,b)

e=tf.add(a,b)

print("a:",a)

print("b:",b)

#construct a 'Session' to excute the graph

sess=tf.Session()

# Execute the graph and store the value that `c` represents in `result`.

print("excuted in Session")

result_a=sess.run(a)

result_a2=a.eval(session=sess)

print("result_a:\n",result_a)

print("result_a2:\n",result_a2)

result_b=sess.run(b)

print("result_b:\n",result_b)

result_c=sess.run(c)

print("result_c:\n",result_c)

result_d=sess.run(d)

print("result_d:\n",result_d)

result_e=sess.run(e)

print("result_e:\n",result_e)