Tensorflow学习--test1

import tensorflow as tf
import numpy as np

### create data ###
x_data = np.random.rand(100).astype(np.float32)
y_data = x_data * 0.1 + 0.3						# 实际y

### crate tensorflow structure start ###
Weights = tf.Variable(tf.random_uniform([1], -1.0, 1.0))
biases = tf.Variable(tf.zeros([1]))

y = Weights * x_data + biases					# 预测y

loss = tf.reduce_mean(tf.square(y - y_data))	# loss
optimizer = tf.train.GradientDescentOptimizer(0.5)
train = optimizer.minimize(loss)

init = tf.global_variables_initializer()
### crate tensorflow structure end ###

sess = tf.Session()
sess.run(init)  # Very important!

for step in range(201):
    sess.run(train)
    if step % 20 == 0:
        print(step, sess.run(Weights), sess.run(biases))