python人工智能tensorflow函数tf.get_collection使用方法_python_

 def get_collection(key, scope=None) Wrapper for Graph.get_collection() using the default graph. See tf.Graph.get_collection for more details. Args: key: The key for the collection. For example, the `GraphKeys` class contains many standard names for collections. scope: (Optional.) If supplied, the resulting list is filtered to include only items whose `name` attribute matches using `re.match`. Items without a `name` attribute are never returned if a scope is supplied and the choice or `re.match` means that a `scope` without special tokens filters by prefix. Returns: The list of values in the collection with the given `name`, or an empty list if no value has been added to that collection. The list contains the values in the order under which they were collected. 

 import tensorflow as tf; import numpy as np; c1 = ['c1', tf.GraphKeys.GLOBAL_VARIABLES] v1 = tf.get_variable('v1', [1], initializer=tf.constant_initializer(1),collections=c1) v2 = tf.get_variable('v2', [1], initializer=tf.constant_initializer(2)) tf.add_to_collection('c2', v2) with tf.Session() as sess: sess.run(tf.global_variables_initializer()) print(tf.get_collection('c1')) print(tf.get_collection('c2')) 

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