python人工智能tensorflow函数tf.get_variable使用方法

 def get_variable(name,
                  shape=None,
                  dtype=None,
                  initializer=None,
                  regularizer=None,
                  trainable=True,
                  collections=None,
                  caching_device=None,
                  partitioner=None,
                  validate_shape=True,
                  use_resource=None,
                  custom_getter=None):

 import tensorflow as tf;  
 import numpy as np;  
 #常量初始化器
 v1_cons = tf.get_variable('v1_cons', shape=[1,4], initializer=tf.constant_initializer())
 v2_cons = tf.get_variable('v2_cons', shape=[1,4], initializer=tf.constant_initializer(9))
 #正太分布初始化器
 v1_nor = tf.get_variable('v1_nor', shape=[1,4], initializer=tf.random_normal_initializer())
 v2_nor = tf.get_variable('v2_nor', shape=[1,4], initializer=tf.random_normal_initializer(mean=0, stddev=5, seed=0))#均值、方差、种子值
 #截断正态分布初始化器
 v1_trun = tf.get_variable('v1_trun', shape=[1,4], initializer=tf.truncated_normal_initializer())
 v2_trun = tf.get_variable('v2_trun', shape=[1,4], initializer=tf.truncated_normal_initializer(mean=0, stddev=5, seed=0))#均值、方差、种子值
 #均匀分布初始化器
 v1_uni = tf.get_variable('v1_uni', shape=[1,4], initializer=tf.random_uniform_initializer())
 v2_uni = tf.get_variable('v2_uni', shape=[1,4], initializer=tf.random_uniform_initializer(maxval=-1., minval=1., seed=0))#最大值、最小值、种子值
 with tf.Session() as sess:
     sess.run(tf.global_variables_initializer())
     print("常量初始化器v1_cons:",sess.run(v1_cons))
     print("常量初始化器v2_cons:",sess.run(v2_cons))
     print("正太分布初始化器v1_nor:",sess.run(v1_nor))
     print("正太分布初始化器v2_nor:",sess.run(v2_nor))
     print("截断正态分布初始化器v1_trun:",sess.run(v1_trun))
     print("截断正态分布初始化器v2_trun:",sess.run(v2_trun))
     print("均匀分布初始化器v1_uni:",sess.run(v1_uni))
     print("均匀分布初始化器v2_uni:",sess.run(v2_uni))

 常量初始化器v1_cons: [[0. 0. 0. 0.]]
 常量初始化器v2_cons: [[9. 9. 9. 9.]]
 正太分布初始化器v1_nor: [[-0.7286455  -0.03095582  1.6400269  -0.90134907]]
 正太分布初始化器v2_nor: [[-1.9957879 10.522196   0.8553612  2.7325907]]
 截断正态分布初始化器v1_trun: [[-0.52284956 -0.77045     1.9507815   0.96106136]]
 截断正态分布初始化器v2_trun: [[-1.9957879  0.8553612  2.7325907  2.1127698]]
 均匀分布初始化器v1_uni: [[0.5369104  0.05912018 0.1587832  0.2859378 ]]
 均匀分布初始化器v2_uni: [[ 0.79827476 -0.9403336  -0.69752836  0.9034374 ]]