kinoko3

import numpy as np
import tensorflow as tf

files = tf.train.match_filenames_once("train.tfrecord")

filename_queue = tf.train.string_input_producer(files, shuffle=False)

reader = tf.TFRecordReader()

_, serialized_example = reader.read(filename_queue)

kinoko3

import pymongo

SERVER = '120.79.9.80'
PORT = 27017
DB_NAME = 'ex-rank'
COLLECTION = 'rank'

client = pymongo.MongoClient(SERVER, PORT)
db = client[DB_NAME]

kinoko3

import tensorflow as tf
state = tf.Variable(0, name='test')     # 变量

one = tf.constant(1)    # 张量

new_value = tf.add(state, one)

update = tf.assign(state, new_value)    #更新 new_value 替换state

init = tf.global_variables_initializer()

kinoko3

import numpy as np
import matplotlib.pyplot as plt
#y=2 * (x1) + (x2) + 3 
rate = 0.001
x_train = np.array([    [1, 2],    [2, 1],    [2, 3],    [3, 5],    [1, 3],    [4, 2],    [7, 3],    [4, 5],    [11, 3],    [8, 7]    ])
y_train = np.array([7, 8, 10, 14, 8, 13, 20, 16, 28, 26])
x_test  = np.array([    [1, 4],    [2, 2],    [2, 5],    [5, 3],    [1, 5],    [4, 1]    ])

a = np.random.normal()
b = np.random.normal()

kinoko3

#include <algorithm>
#include <iostream>
using namespace std;

// 使用搜索前先排序
int main(){
	int A[10] = {1,1,2,3,4,5,6,10,9,15};
	int *pos;
	int idx;
  bool h;

kinoko3

import requests
from concurrent import futures
import pymongo
from lxml import etree
import datetime
MAX_WORKERS = 8


def get(url):
    session = requests.session()