tensorflow tf.train.SummaryWriter()

报错：

AttributeError: module 'tensorflow.python.training.training' has no attribute 'FileWriter'

解决：
tensorflow 新版取消了tf.train.SummaryWriter()，换成使用tf.summary.FileWriter()
warning：

sess.run(tf.initialize_all_variables())  Use `tf.global_variables_initializer` instead.

解决：
tf.initialize_all_variables()换成tf.global_variables_initializer()
实例：

# -*- coding: utf-8 -*-"""Created on Mon Dec 25 19:53:43 2017@author: Administrator"""import matplotlib.pyplot as pltimport timeimport tensorflow as tfimport numpy as npdef add_layer(inputs,in_size,out_size,activation_function=None):    with tf.name_scope('layer'):        with tf.name_scope('weights'):            Weights=tf.Variable(tf.random_normal([in_size,out_size]),name='W')        with tf.name_scope('biases'):              biases=tf.Variable(tf.zeros([1,out_size])+0.1,name='b')        with tf.name_scope('Wx_plus_b'):            Wx_plus_b=tf.add(tf.matmul(inputs,Weights),biases)        if activation_function is None:            outputs=Wx_plus_b        else:            outputs=activation_function(Wx_plus_b)        return outputs#define placeholder for inputs to networkwith tf.name_scope('inputs'):    xs=tf.placeholder(tf.float32,[None,1],name='x_input')    ys=tf.placeholder(tf.float32,[None,1],name='y_input')#add hidden layerl1=add_layer(xs,1,10,activation_function=tf.nn.relu)#add output layerprediction=add_layer(l1,10,1,activation_function=None)#the error between prediction and real data loss=tf.reduce_mean(tf.reduce_sum(tf.square(ys-prediction),reduction_indices=[1]))with tf.name_scope('train'):    train_step=tf.train.GradientDescentOptimizer(0.1).minimize(loss)sess=tf.Session()writer=tf.summary.FileWriter("logs/",sess.graph)#important stepsess.run(tf.global_variables_initializer())