将模型保存为pb
import tensorflow as tf
from tensorflow.python.framework import graph_util
logdir='output/'
with tf.variable_scope('conv'):
w=tf.get_variable('w',[2,2],tf.float32,initializer=tf.ran
不管是用VS开发的基于.NET的WebService，还是用<em>Java</em>开发的WebService，还是用<em>PB</em>本身开发的.NET
Web Service，<em>PB</em><em>调用</em>WebService的原理是一样的，都是通过WSDL访问WebServices.具体步骤有三：
1.编写WebService
2.创建<em>PB</em> Web Service Proxy
3.创建<em>PB</em> Web Service Client
1
from __future__ import print_function
import keras
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2...
<em>PB</em> 通过 PostRul
一 创建Standard Class对象 type为"internetresult" n_ir
forward
global type n_ir from internetresult
end type
end forward
global type n_ir from internetresult
end type
global n_ir n_ir
t
