import os
import tensorflow as tf


x = tf.constant(1.0, name='input')
w = tf.Variable(0.8, name='weight')
y = tf.multiply(w, x, name='output')
y_ = tf.constant(0.0,name='target')
loss = (y - y_)**2

train_step = tf.train.GradientDescentOptimizer(0.025).minimize(loss)

#1#writer = tf.summary.FileWriter("./logs/board111")
#2#summary_y = tf.summary.scalar('output', y)



with tf.Session() as sess:
   
    sess.run(tf.initialize_all_variables())
    for i in range(100):
        #3#summary_str = sess.run(summary_y)
        #4#writer.add_summary(summary_str, i)
        
        sess.run(train_step)
       


    
   
   #5# writer.close()

os.system('tensorboard --logdir=./logs/board111 --port 6006' )