Tensorflow name_scope和variable_scope的区别

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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 tfwith 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'

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