官網的解釋和例子實在是wast time，不用去看它了。

import tensorflow as tf


a1 = tf.get_variable(name='a1', shape=[1], initializer=tf.constant_initializer(1)) 


with tf.variable_scope('V1'):     
    a2 = tf.Variable(tf.random_normal(shape=[2,3], mean=0, stddev=1), name='a2') 
    
    
with tf.variable_scope('V2'): 
    a3 = tf.get_variable(name='a1', shape=[1], initializer=tf.constant_initializer(80)) 
    

print (a1.name)
print (a2.name)
print (a3.name)

    
with tf.Session() as sess: 
    sess.run(tf.global_variables_initializer())    
    print(sess.run(a1))
    print(sess.run(a2))
    print(sess.run(a3))
 

輸出結果可以看出，V1是範圍，變數名a2在V1範圍。變數名a1在V2範圍。後面的輸出value可以看出，此函式主要是用於name管理。然而此a1非彼a1，一般我們用的是tensor.Variable。

type(a1)
Out[2]: tensorflow.python.ops.variables.Variable

type(a3)
Out[3]: tensorflow.python.ops.variables.Variable