-
Notifications
You must be signed in to change notification settings - Fork 0
/
neuron.py
23 lines (17 loc) · 699 Bytes
/
neuron.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
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='correct_value')
loss = tf.pow(y - y_, 2, name='loss')
train_step = tf.train.GradientDescentOptimizer(0.025).minimize(loss)
for value in [x,y,y_,w,loss]:
tf.summary.scalar(value.op.name, value)
summaries = tf.summary.merge_all()
sess = tf.Session()
summary_writer = tf.summary.FileWriter('log_simple_stats', sess.graph)
sess.run(tf.global_variables_initializer())
for i in range(1000):
print('before step {}, y is {}'.format(i, sess.run(y)))
summary_writer.add_summary(sess.run(summaries), i)
sess.run(train_step)