功能：tf.variable_scope可以让不同命名空间中的变量取相同的名字，无论tf.get_variable或者tf.Variable生成的变量
TensorFlow链接：https://tensorflow.google.cn/api_docs/python/tf/variable_scope?hl=en
举例：
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)
with tf.variable_scope("foo"):
v = tf.get_variable("v", [1])
with tf.variable_scope("foo", reuse=True):
v1 = tf.get_variable("v", [1])
assert v1 == v #不报错
功能：tf.name_scope具有类似的功能，但只限于tf.Variable生成的变量
TensorFlow链接：https://tensorflow.google.cn/api_docs/python/tf/name_scope?hl=en
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)
a1，a3会报错：ValueError: Variable a1 already exists, disallowed. Did you mean to set reuse=True or reuse=tf.AUTO_REUSE in VarScope? Originally defined at:
参考文献：
【1】tf.variable_scope和tf.name_scope的用法
tf.variable_scope和tf.name_scope
原文：https://www.cnblogs.com/nxf-rabbit75/p/11277076.html