tensorflow关于get

import tensorflow as tf
a = tf.get_variable('w1',[3,3],tf.float32,tf.ones_initializer())
b = tf.get_variable('w2',[3,3],tf.float32,tf.ones_initializer())
bb=a+b

c = tf.layers.dense(bb,5, activation=None,name='add') #获取网络层的输出只更改最后一维
g = tf.get_default_graph()

t = g.get_tensor_by_name('w1:0')
n = g.get_tensor_by_name('add:0') #获取网络层的输入
n1 = g.get_tensor_by_name('add/kernel:0') #获取网络层的权重

print(a)
print(t)

print(c)
print(n)
print(n1)


with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    print(sess.run(a))
    print(sess.run(t))

    print(sess.run(c))   #输出FC结果
    print(sess.run(n))   #打印add的输入
    print(sess.run(n1))  #打印add的权重
    print(n1.eval())      #tf.Tensor.eval()  功能：当默认的会话被指定之后可以通过其计算一个张量的取值。

    print(sess.run(tf.matmul(n,n1))) #   =c

 
##对应输出：

Tensor("w1:0", shape=(3, 3), dtype=float32_ref)
Tensor("add_1/BiasAdd:0", shape=(3, 5), dtype=float32)
Tensor("add:0", shape=(3, 3), dtype=float32)
Tensor("add/kernel:0", shape=(3, 5), dtype=float32_ref)


[[1. 1. 1.]
 [1. 1. 1.]
 [1. 1. 1.]]

[[1. 1. 1.]
 [1. 1. 1.]
 [1. 1. 1.]]

[[-1.3647698 -2.8054194 -1.7050204  3.338818   2.5336776]
 [-1.3647698 -2.8054194 -1.7050204  3.338818   2.5336776]
 [-1.3647698 -2.8054194 -1.7050204  3.338818   2.5336776]]

[[2. 2. 2.]
 [2. 2. 2.]
 [2. 2. 2.]]

[[-0.65962625 -0.769727    0.24005729  0.7080906   0.10090774]
 [ 0.29028767 -0.5869036  -0.6289141   0.6177673   0.43807036]
 [-0.31304634 -0.04607916 -0.4636534   0.3435511   0.72786075]]

[[-0.65962625 -0.769727    0.24005729  0.7080906   0.10090774]
 [ 0.29028767 -0.5869036  -0.6289141   0.6177673   0.43807036]
 [-0.31304634 -0.04607916 -0.4636534   0.3435511   0.72786075]]

[[-1.3647698 -2.8054194 -1.7050204  3.338818   2.5336776]
 [-1.3647698 -2.8054194 -1.7050204  3.338818   2.5336776]
 [-1.3647698 -2.8054194 -1.7050204  3.338818   2.5336776]]