libtorch 加载 pytorch 模块进行预测示例 void mat2tensor(const char * path, torch::Tensor &output) { //读取图片 cv::Mat img = cv::imread(path); if (img.empty()) { printf("load image failed!"); system("pause"); } //调整大小 cv::resize(img, img, { 224,2

经过两天的折腾,一个对c++和机器学习库的安装都一知半解的人终于在反复安装中,成功的将shark库安装好了,小小纪念一下,多亏了卡门的热心帮忙. shark的安装主要分为以下几个部分: (1)下载 shark,cmake,和boost 从这个网页里面可以找到这三项的下载地方http://image.diku.dk/shark/sphinx_pages/build/html/rest_sources/getting_started/installation.html 同时,这个也是shark安装指

题 Today, Wet Shark is given n integers. Using any of these integers no more than once, Wet Shark wants to get maximum possible even (divisible by 2) sum. Please, calculate this value for Wet Shark. Note, that if Wet Shark uses no integers from the n 

题 There are n sharks who grow flowers for Wet Shark. They are all sitting around the table, such that sharks i andi + 1 are neighbours for all i from 1 to n - 1. Sharks n and 1 are neighbours too. Each shark will grow some number of flowers si. For i

Shark是构建在Spark和Hive基础之上的数据仓库. 目前,Shark已经完成学术使命,终止开发,但其架构和原理仍具有借鉴意义. 它提供了能够查询Hive中所存储数据的一套SQL接口,兼容现有的Hive QL语法. 这样,熟悉Hive QL或者SQL的用户可以基于Shark进行快速的Ad-Hoc. Reporting等类型的SQL查询. Shark底层复用Hive的解析器. 优化器以及元数据存储和序列化接口. Shark会将Hive QL编译转化为一组Spark任务,进行分布式运算.

  环境:shark(0.11分支编译)+spark 0.8+hive 0.11(编译)+hadoop 2.00 cdh4.4 用sharkserver的方式执行一段时间后,通过kit-b8连接到kit-b5的sharkserver上,执行时报以下错误: Hive history file=/tmp/hadoop/hive_job_log_hadoop_48828@kit-b8_201402180950_254775764.txt 5.118: [GC 262656K->24086K(10055

1.部署环境 OS:Red Hat Enterprise Linux Server release 6.4 (Santiago) Hadoop:Hadoop 2.4.1 Hive:0.11.0 JDK:1.7.0_60 Python:2.6.6(spark集群需要python2.6以上,否则无法在spark集群上运行py) Spark:0.9.1(最新版是1.1.0) Shark:0.9.1(目前最新的版本,但是只能够兼容到spark-0.9.1,见shark 0.9.1 release) Zo

C. Wet Shark and Flowers time limit per test 2 seconds memory limit per test 256 megabytes input standard input output standard output There are n sharks who grow flowers for Wet Shark. They are all sitting around the table, such that sharks i and i 

B. Wet Shark and Bishops time limit per test 2 seconds memory limit per test 256 megabytes input standard input output standard output Today, Wet Shark is given n bishops on a 1000 by 1000 grid. Both rows and columns of the grid are numbered from 1 t

A. Wet Shark and Odd and Even time limit per test 2 seconds memory limit per test 256 megabytes input standard input output standard output Today, Wet Shark is given n integers. Using any of these integers no more than once, Wet Shark wants to get ma

一.Shark简单介绍 Shark是基于Spark与Hive之上的一种SQL查询引擎,官网的架构图及性能測试图例如以下:(Ps:本人也做了一个性能測试见Shark性能測试报告) 我们涉及到了2个依赖组件,1是Apache Spark, 另外一个是AMPLAB的Hive0.11. 这里注意版本号的选择.一定要选择官方的推荐版本号: Spark0.91 + AMPLAB Hive0.11 + Shark0.91 一定要自己编译好它们,适用于自己的集群. 二.Shark集群搭建 1. 搭建Spark集

最近因为项目需要,看了看机器学习方面的东西.Google一番,发现Shark正是朕需要的东西.于是准备按官方文档来使用它了.但是官方文档只有怎么生成静态库,并没有在QT里引用的sample. 废话不多说,直接上步骤: 首先,环境:  Ubuntu 16.04,Qt5.7,shark 3.1.3 在开始编译安装shark之前,先安装其所依赖的其他组件: sudo apt-get install cmake cmake-curses-gui libatlas-base-dev libboost-al

Codeforces Codeforces Round #484 (Div. 2) D. Shark 题目连接: http://codeforces.com/contest/982/problem/D Description For long time scientists study the behavior of sharks. Sharks, as many other species, alternate short movements in a certain location and

环境 Ubuntu -18.04.1, opencv3.4.0 ,  python 3.6,  cmake 3.5.0, pytorch 1.0. pytorch官网下载对应版本:https://pytorch.org/. libtorch库的安装参考:https://pytorch.org/cppdocs/installing.html. example代码下载:https://github.com/iamhankai/cpp-pytorch. 具体流程和example代码中的一样,先在tra

http://blog.csdn.net/pelick/article/details/11964291 Shark简介 Shark即Hive on Spark,本质上是通过Hive的HQL解析,把HQL翻译成Spark上的RDD操作,然后通过Hive的metadata获取数据库里的表信息,实际HDFS上的数据和文件,会由Shark获取并放到Spark上运算.Shark的特点就是快,完全兼容Hive,且可以在shell模式下使用rdd2sql()这样的API,把HQL得到的结果集,继续在scal

B. Wet Shark and Bishops time limit per test: 2 seconds memory limit per test: 256 megabytes input: standard input output: standard output Today, Wet Shark is given n bishops on a 1000 by 1000 grid. Both rows and columns of the grid are numbered from

题目链接: http://codeforces.com/problemset/problem/621/E E. Wet Shark and Blocks time limit per test2 secondsmemory limit per test256 megabytes 问题描述 There are b blocks of digits. Each one consisting of the same n digits, which are given to you in the inp

如何使用 libtorch 实现 AlexNet 网络? 按照图片上流程写即可.输入的图片大小必须 227x227 3 通道彩色图片 // Define a new Module. struct Net : torch::nn::Module { Net() { conv1 = torch::nn::Conv2d(torch::nn::Conv2dOptions(3, 96, { 11,11 }).stride({4,4})); conv2 = torch::nn::Conv2d(torch::

如何使用 libtorch 实现 LeNet 网络? LeNet 网络论文地址: http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf

如何在 windows 配置 libtorch c++ 前端库? 下载 pytorch 已经编译好的库: 此库不带 gpu,主要方便演示.支持 win7 win10 系统. 下载地址:https://download.pytorch.org/libtorch/cpu/libtorch-win-shared-with-deps-latest.zip 1. cmake 配置 1.1 新建 CMakeLists.txt 并添加以下内容: # 设置 cmake 版本限制 cmake_minimum_re