lispc

from __future__ import print_function
import os 
os.environ["CUDA_VISIBLE_DEVICES"]=''
import time
import threading
import numpy as np 
import tensorflow as tf
queue_size = 10
queue_shape = [6, 200, 200, 3]
cluster_spec_config = {'train': ['localhost:22222', 'localhost:23333']}

lispc

import tensorflow as tf 
import time 
from datetime import datetime 
import numpy as np

FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_bool('cluster', False, '')

def log(obj):
    print datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3], obj

lispc

class Solution {
public:
    int pw(int a,int b){
        if(b==0){
            return 1;
        }
        int half = pw(a,b/2);
        return half*half*(b%2?a:1);
    }
    int canCompleteCircuit(vector<int> &gas, vector<int> &cost) {

lispc

#include<iostream>
#include<string>
#include<fstream>
#include<cstdlib>
#include<cstring>
#include<vector>
#include<utility>
#include<unistd.h>
#include<algorithm>
using namespace std;

lispc

var descriptionDisplayLimit = 200;
var ids = [];
var simly = Simly.getInstance();
templateFunc = swig.compile($("#src_item_template").html());
function load_log(){
    $.ajax({
        url: "/simly/api/get_feedback_log",
        dataType: "json",
        data: {uname:getLoginInfo().username},
        success:function(res){