1.从tensorflow的example改编

2.源码

import numpy as np
import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data

#one_host = True，把类标记转换成向量，比如类标记是3，就转换成[0,0,0,1,0...0]
mnist = input_data.read_data_sets('/tmp/data', one_hot=True)

#训练集和测试集
Xtrain, Ytrain = mnist.train.next_batch(5000)
Xtest, Ytest = mnist.test.next_batch(200)

#建图
xtrain = tf.placeholder('float', [None, 784])
xtest = tf.placeholder('float', [784])

distance = tf.reduce_sum(tf.abs(xtrain-xtest), reduction_indices=1)
pred = tf.argmin(distance, 0)

with tf.Session() as session:
    accuracy = 0
    for i in range(len(Xtest)):
        # dis = session.run(distance, feed_dict={xtrain:Xtrain, xtest:tt})
        p = session.run(pred, feed_dict={xtrain:Xtrain, xtest:Xtest[i]})
        if np.argmax(Ytest[i]) == np.argmax(Ytrain[p]):
            accuracy += 1./len(Xtest)

    print(accuracy)