环境:python 3 , tensorflow 1.1
"""
python 3
tensorflow 1.1
"""
import tensorflow
as tf
import numpy
as np
tf.set_random_seed(
100)
np.random.seed(
100)
x = np.linspace(-
1,
1,
100)[:,np.newaxis]
noise = np.random.normal(
0,
0.1,x.shape)
y = np.power(x,
3) + noise
with tf.variable_scope(
'inputs'):
xs = tf.placeholder(tf.float32,x.shape,name=
'x')
ys = tf.placeholder(tf.float32,y.shape,name=
'y')
with tf.variable_scope(
'neural_network'):
l1 = tf.layers.dense(xs,
10,tf.nn.relu,name=
'hidden_layer')
output = tf.layers.dense(l1,
1,name=
'output_layer')
tf.summary.histogram(
'layer1',l1)
tf.summary.histogram(
'output',output)
loss = tf.losses.mean_squared_error(y,output,scope=
'loss')
train = tf.train.GradientDescentOptimizer(learning_rate=
0.5).minimize(loss)
tf.summary.scalar(
'loss',loss)
with tf.Session()
as sess:
init = tf.global_variables_initializer()
sess.run(init)
merged = tf.summary.merge_all()
writer = tf.summary.FileWriter(
'./tensorflow1.1_logs',sess.graph)
for step
in range(
100):
_,result = sess.run([train,merged],feed_dict={xs:x,ys:y})
writer.add_summary(result,step)
运行结果