import tensorflow as tf
import numpy as np
a = tf.Variable(0,dtype=tf.float32)
c = tf.assign_add(a,1)
#收集标量
#d是一次操作<class ‘tensorflow.python.framework.ops.Tensor’>
d = tf.summary.scalar(“loss”,a)
print(d)
#自动管理锁收集的标量,是一次操作
merged = tf.summary.merge_all()
print(type(merged))
print(merged)
init = tf.global_variables_initializer()
with tf.Session() as sess:
writer = tf.summary.FileWriter(“logs”,sess.graph)#将图存入到logs文件中
sess.run(init)
for i in range(100):
y=i*2
sess.run(tf.assign(a,y))#执行自加操作
print(sess.run(a))
#sess.run(d)#返回二进制对象,和summary是一样的
summary = sess.run(merged) #返回二进制对象
writer.add_summary(summary,i)#把二进制对象写入文件