ubuntu version:16.04 LTS tensorflow version:1.1.0 python version:2.7.12
import numpy as np
import tensorflow as tf
# Model parameters
W = tf
.Variable([
.3], tf
.float32)
b = tf
.Variable([-
.3], tf
.float32)
# Model input and output
x = tf
.placeholder(tf
.float32)
linear_model = W *
x + b
y = tf
.placeholder(tf
.float32)
# loss
loss = tf
.reduce_sum(tf
.square(linear_model -
y))
# sum of the squares
# optimizer
optimizer = tf
.train.GradientDescentOptimizer(
0.01)
train = optimizer
.minimize(loss)
# training data
x_train = [
1,
2,
3,
4]
y_train = [
0,-
1,-
2,-
3]
# training loop
init = tf
.global_variables_initializer()
sess = tf
.Session()
sess
.run(init)
# reset values to wrong
for i
in range(
1000):
sess
.run(train, {
x:x_train,
y:y_train})
# evaluate training accuracy
curr_W, curr_b, curr_loss = sess
.run([W, b, loss], {
x:x_train,
y:y_train})
print(
"W: %s b: %s loss: %s"%(curr_W, curr_b, curr_loss))
运行结果：
W:
[-0.9999969] b:
[ 0.99999082] loss: 5
.69997e-11
tensorboard流程图
