无论tf.get_variable或者tf.Variable生成的变量，tf.variable_scope可以让不同命名空间中的变量取相同的名字。tf.name_scope具有类似的功能，但只限于tf.Variable生成的变量。
import tensorflow as tf;
import numpy as np;
import matplotlib.pyplot as plt;
with tf.variable_scope('V1'):
a1 = tf.get_variable(name='a1', shape=[1], initializer=tf.constant_initializer(1))
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(1))
a4 = tf.Variable(tf.random_normal(shape=[2,3], mean=0, stddev=1), name='a2')
with tf.Session() as sess:
sess.run(tf.initialize_all_variables())
print a1.name
print a2.name
print a3.name
print a4.name
输出：
V1/a1:0
V1/a2:0
V2/a1:0
V2/a2:0
import tensorflow as tf;
import numpy as np;
import matplotlib.pyplot as plt;
with tf.name_scope('V1'):
a1 = tf.get_variable(name='a1', shape=[1], initializer=tf.constant_initializer(1))
a2 = tf.Variable(tf.random_normal(shape=[2,3], mean=0, stddev=1), name='a2')
with tf.name_scope('V2'):
a3 = tf.get_variable(name='a1', shape=[1], initializer=tf.constant_initializer(1))
a4 = tf.Variable(tf.random_normal(shape=[2,3], mean=0, stddev=1), name='a2')
with tf.Session() as sess:
sess.run(tf.initialize_all_variables())
print a1.name
print a2.name
print a3.name
print a4.name
由于使用的是tf.name_scope，并且在该命名空间中包含了两种创建变量的方法，而tf.name_scope仅对tf.Variable生效，所以会报错：
报错：Variable a1 already exists, disallowed. Did you mean to set reuse=True in VarScope?
import tensorflow as tf;
import numpy as np;
import matplotlib.pyplot as plt;
with tf.name_scope('V1'):
# a1 = tf.get_variable(name='a1', shape=[1], initializer=tf.constant_initializer(1))
a2 = tf.Variable(tf.random_normal(shape=[2,3], mean=0, stddev=1), name='a2')
with tf.name_scope('V2'):
# a3 = tf.get_variable(name='a1', shape=[1], initializer=tf.constant_initializer(1))
a4 = tf.Variable(tf.random_normal(shape=[2,3], mean=0, stddev=1), name='a2')
with tf.Session() as sess:
sess.run(tf.initialize_all_variables())
# print a1.name
print a2.name
# print a3.name
print a4.name
输出：
V1/a2:0
V2/a2:0
