程序代码:

tensorMNIST.py

#coding = utf-8
import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("C:\\Users\\xiaoj\\Desktop\\MNIST_data",one_hot=True)x = tf.placeholder(tf.float32,[None,784])
W = tf.Variable(tf.zeros([784,10]))
b= tf.Variable(tf.zeros([10]))y = tf.nn.softmax(tf.matmul(x,W) + b )y_ = tf.placeholder("float",[None,10])
cross_entropy = -tf.reduce_sum(y_ * tf.log(y))train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)init = tf.global_variables_initializer()sess = tf.Session()
sess.run(init)for i in range(1,1000):batch_xs,batch_ys = mnist.train.next_batch(100)sess.run(train_step,feed_dict={x:batch_xs,y_:batch_ys})correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, 'float'))
print(sess.run(accuracy, feed_dict={x: mnist.test.images, y_: mnist.test.labels}))

运行结果:

准确率:91.64%

C:\Users\xiaoj\AppData\Local\Programs\Python\Python36\python.exe C:/Users/xiaoj/PycharmProjects/Exercise/tensorMnist.py
WARNING:tensorflow:From C:/Users/xiaoj/PycharmProjects/Exercise/tensorMnist.py:4: read_data_sets (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use alternatives such as official/mnist/dataset.py from tensorflow/models.
WARNING:tensorflow:From C:\Users\xiaoj\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:260: maybe_download (from tensorflow.contrib.learn.python.learn.datasets.base) is deprecated and will be removed in a future version.
Instructions for updating:
Please write your own downloading logic.
Extracting C:\Users\xiaoj\Desktop\MNIST_data\train-images-idx3-ubyte.gz
WARNING:tensorflow:From C:\Users\xiaoj\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:262: extract_images (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.data to implement this functionality.
WARNING:tensorflow:From C:\Users\xiaoj\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:267: extract_labels (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.data to implement this functionality.
Extracting C:\Users\xiaoj\Desktop\MNIST_data\train-labels-idx1-ubyte.gz
WARNING:tensorflow:From C:\Users\xiaoj\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:110: dense_to_one_hot (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use tf.one_hot on tensors.
Extracting C:\Users\xiaoj\Desktop\MNIST_data\t10k-images-idx3-ubyte.gz
Extracting C:\Users\xiaoj\Desktop\MNIST_data\t10k-labels-idx1-ubyte.gz
WARNING:tensorflow:From C:\Users\xiaoj\AppData\Local\Programs\Python\Python36\lib\site-packages\tensorflow\contrib\learn\python\learn\datasets\mnist.py:290: DataSet.__init__ (from tensorflow.contrib.learn.python.learn.datasets.mnist) is deprecated and will be removed in a future version.
Instructions for updating:
Please use alternatives such as official/mnist/dataset.py from tensorflow/models.
2019-01-29 16:46:57.465634: I T:\src\github\tensorflow\tensorflow\core\platform\cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
0.9164

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