Tensorflow name_scope和variable_scope的区别

为了研究一下tensorflow的name_scope和variable_scope到底有啥区别，我对Variable和Summary对象分别试验了这两种scope。直接上代码：

1.对Variable先加name_scope，再加variable_scope

import tensorflow as tf

with tf.name_scope('ns1'):          #name_scope
    v1 = tf.get_variable('v1', shape=(1,))
with tf.variable_scope('vs1'):  #variable_scope
        v2 = tf.get_variable('v2', shape=(1,))

v1v2_coll = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES,scope='ns1') #[]
v2_coll = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES,scope='vs1')   #'vs1/v2:0'
#name_scope对变量无效， 'vs1/v2:0'的prefix里没有'ns1/'

2.对Variable先加variable_scope，再加name_scope

with tf.variable_scope('vs2'):      #variable_scope
    v1 = tf.get_variable('v1', shape=(1,))
with tf.name_scope('ns2'):      #name_scope
        v2 = tf.get_variable('v2', shape=(1,))

v1v2_coll = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES,scope='vs2') #'vs2/v1:0'
v2_coll = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES,scope='ns2')   #[]
#name_scope对变量无效， 'vs2/v1:0'的prefix里没有'ns2/'

3.对Summary先加name_scope，再加variable_scope

with tf.name_scope('ns3'):          #name_scope
    tf.summary.histogram('sum_ns', tf.convert_to_tensor([1]))
with tf.variable_scope('vs3'):  #variable_scope
        tf.summary.histogram('sum_nsvs', tf.convert_to_tensor([1]))

sum_ns_coll = tf.get_collection(tf.GraphKeys.SUMMARIES,scope='ns3')
#'ns3/sum_ns:0', 'ns3/vs3/sum_vs:0'
sum_nsvs_coll = tf.get_collection(tf.GraphKeys.SUMMARIES,scope='ns3/vs3')
#'ns3/vs3/sum_nsvs:0'

4.对Summary先加variable_scope，再加name_scope

with tf.variable_scope('vs4'):      #variable_scope
    tf.summary.histogram('sum_vs', tf.convert_to_tensor([1]))
with tf.name_scope('ns4'):      #name_scope
        tf.summary.histogram('sum_ns', tf.convert_to_tensor([1]))

sum_vs_coll = tf.get_collection(tf.GraphKeys.SUMMARIES,scope='vs4')
#'vs4/sum_vs:0', 'vs4/ns4/sum_ns:0'
sum_vsns_coll = tf.get_collection(tf.GraphKeys.SUMMARIES,scope='vs4/ns4')
#'vs4/ns4/sum_ns:0'