# -*- coding:utf-8 -*-

import tensorflow as tf

import os

config = tf.ConfigProto()

config.gpu_options.allow_growth = True

sess = tf.Session(config=config)

"""TensorBoard 简单例子。

tf.summary.scalar('var_name', var) # 记录标量的变化

tf.summary.histogram('vec_name', vec) # 记录向量或者矩阵，tensor的数值分布变化。

merged = tf.summary.merge_all() # 把所有的记录并把他们写到 log_dir 中

train_writer = tf.summary.FileWriter(FLAGS.log_dir + '/train', sess.graph) # 保存位置

运行完后，在命令行中输入 tensorboard --logdir=log_dir_path

"""

tf.app.flags.DEFINE_string('log_dir', 'summary/graph/', 'log saving path')

FLAGS = tf.app.flags.FLAGS

if os.path.exists(FLAGS.log_dir):

os.rmdir(FLAGS.log_dir)

os.makedirs(FLAGS.log_dir)

print 'created log_dir path'

with tf.name_scope('add_example'):

a = tf.Variable(tf.truncated_normal([100, 1], mean=0.5, stddev=0.5), name='var_a')

tf.summary.histogram('a_hist', a)

b = tf.Variable(tf.truncated_normal([100, 1], mean=-0.5, stddev=1.0), name='var_b')

tf.summary.histogram('b_hist', b)

increase_b = tf.assign(b, b + 0.05)

c = tf.add(a, b)

tf.summary.histogram('c_hist', c)

c_mean = tf.reduce_mean(c)

tf.summary.scalar('c_mean', c_mean)

merged = tf.summary.merge_all()

writer = tf.summary.FileWriter(FLAGS.log_dir + 'add_example', sess.graph)

def main(_):

sess.run(tf.global_variables_initializer())

for step in xrange(500):

sess.run([merged, increase_b]) # 每步改变一次 b 的值

summary = sess.run(merged)

writer.add_summary(summary, step)

writer.close()

if __name__ == '__main__':

tf.app.run()