tensorflow function Feature Highlights

tf.add_to_collection（） tf.get_collection() tf.add_n()

tf.add_to_collection: the variables into a set, a list of the many variables into 

tf.get_collection: Remove all the variables from a binding, the list is a 

tf.add_n: a list of things are combined sequentially 

example: 

Import tensorflow TF AS;   
Import numpy AS NP;   
Import matplotlib.pyplot AS PLT;   
 
V1 = tf.get_variable (name = 'V1', Shape = [. 1], initializer of tf.constant_initializer = (0)) 
tf.add_to_collection ( 'Loss', V1) 
V2 = tf.get_variable (name = 'V2', Shape = [. 1], = tf.constant_initializer initializer of (2)) 
tf.add_to_collection ( 'Loss', V2) 
 
with tf.Session () AS Sess: 
	Sess. RUN (tf.initialize_all_variables ()) 
	Print tf.get_collection ( 'Loss') 
	Print sess.run (tf.add_n (tf.get_collection ( 'Loss'))) 
output:
[<tensorflow.python.ops.variables.Variable object at 0x7f6b5d700c50>, <tensorflow.python.ops.variables.Variable object at 0x7f6b5d700c90>]
[ 2.]