Tensorflow学习

Posted simplekinght

tags:

篇首语:本文由小常识网(cha138.com)小编为大家整理,主要介绍了Tensorflow学习相关的知识,希望对你有一定的参考价值。

 

不知道应该写些什么,所以先空着??

import os
os.environ[TF_CPP_MIN_LOG_LEVEL] = 2
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
#import tensorflow.examples.tutorials.mnist.input_data as input_data

def add_layer(inputs,in_size,out_size,activation_function=None):
    Weights = tf.Variable(tf.random_normal([in_size,out_size]))
    biases = tf.Variable(tf.zeros([1,out_size])+0.1)
    Wx_plus_b = tf.matmul(inputs,Weights)+biases
    if activation_function is None:
        outputs = Wx_plus_b
    else:
        outputs = activation_function(Wx_plus_b)
    return  outputs

x_data = np.linspace(-1,1,300)[:,np.newaxis]
noise = np.random.normal(0,0.05,x_data.shape)
y_data = np.square(x_data)-0.5+noise
xs = tf.placeholder(tf.float32,[None,1])
ys = tf.placeholder(tf.float32,[None,1])
l1 = add_layer(xs,1,10,activation_function=tf.nn.relu)
predition = add_layer(l1,10,1,activation_function=None)

loss = tf.reduce_mean(tf.reduce_sum(tf.square(ys-predition),reduction_indices=[1]))
train_step = tf.train.GradientDescentOptimizer(0.1).minimize(loss)

init = tf.global_variables_initializer()
sess = tf.Session()
sess.run(init)

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.scatter(x_data, y_data)
plt.ion()
plt.show()

for i in range(1000):
    sess.run(train_step,feed_dict={xs:x_data,ys:y_data})
    if i %50 ==0:
        try:
            ax.lines.remove(lines[0])
        except Exception:
            pass
        predition_value = sess.run(predition,feed_dict={xs:x_data})
        lines = ax.plot(x_data,predition_value,r-,lw=5)
        plt.pause(0.1)
        print(sess.run(loss,feed_dict={xs:x_data,ys:y_data}))

 

以上是关于Tensorflow学习的主要内容,如果未能解决你的问题,请参考以下文章

《Tensorflow实战Google深度学习框架》PDF一套四本+源代码_高清_完整

TensorFlow.js:那两个张量相等吗?

学习《TensorFlow实战Google深度学习框架 (第2版) 》中文PDF和代码

学习TF:《TensorFlow技术解析与实战》PDF+代码

TensorFlow DNNRegressor实现深度学习的代码

Tensorflow学习笔记---2--DCGAN代码学习