【深度学习】环境搭建ubuntu22.04

清华官网的conda源
https://mirrors.tuna.tsinghua.edu.cn/help/anaconda/
安装torch
conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
2.2.2
在这里插入图片描述
conda install 指引看这里:
ref:https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#package-manager-metas
invidia toolkit的指引在这里,看起来,driver和toolkit合二为一了,一步到位。
https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=22.04&target_type=deb_network
cudann安装:https://docs.nvidia.com/deeplearning/cudnn/installation/linux.html

报错:https://forums.developer.nvidia.com/t/verify-cudnn-install-failed/167220
(base) justin@justin-System-Product-Name:/usr/src/cudnn_samples_v9/mnistCUDNN$ sudo make
CUDA_VERSION is 12040
Linking agains cublasLt = true
CUDA VERSION: 12040
TARGET ARCH: x86_64
HOST_ARCH: x86_64
TARGET OS: linux
SMS: 50 53 60 61 62 70 72 75 80 86 87 90
test.c:1:10: fatal error: FreeImage.h: No such file or directory
1 | #include “FreeImage.h”

解决方案:https://forums.developer.nvidia.com/t/verify-cudnn-install-failed/167220/4

cudnn测试通过,它被安装在了src下。cp一份sample到home下:


(base) justin@justin-System-Product-Name:~/cudnn_samples_v9/mnistCUDNN$ ./mnistCUDNN
Executing: mnistCUDNN
cudnnGetVersion() : 90000 , CUDNN_VERSION from cudnn.h : 90000 (9.0.0)
Host compiler version : GCC 11.4.0There are 1 CUDA capable devices on your machine :
device 0 : sms 128  Capabilities 8.9, SmClock 2520.0 Mhz, MemSize (Mb) 24188, MemClock 10501.0 Mhz, Ecc=0, boardGroupID=0
Using device 0Testing single precision
Loading binary file data/conv1.bin
Loading binary file data/conv1.bias.bin
Loading binary file data/conv2.bin
Loading binary file data/conv2.bias.bin
Loading binary file data/ip1.bin
Loading binary file data/ip1.bias.bin
Loading binary file data/ip2.bin
Loading binary file data/ip2.bias.bin
Loading image data/one_28x28.pgm
Performing forward propagation ...
Testing cudnnGetConvolutionForwardAlgorithm_v7 ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: -1.000000 time requiring 178432 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: -1.000000 time requiring 184784 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: -1.000000 time requiring 2057744 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.015360 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.017408 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.037728 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.106496 time requiring 178432 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.242464 time requiring 184784 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.287936 time requiring 2057744 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnGetConvolutionForwardAlgorithm_v7 ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: -1.000000 time requiring 128848 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: -1.000000 time requiring 1433120 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: -1.000000 time requiring 2450080 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: -1.000000 time requiring 4656640 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.028672 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.045024 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.104768 time requiring 128848 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.116736 time requiring 1433120 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.136192 time requiring 4656640 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.209152 time requiring 2450080 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Resulting weights from Softmax:
0.0000000 0.9999399 0.0000000 0.0000000 0.0000561 0.0000000 0.0000012 0.0000017 0.0000010 0.0000000
Loading image data/three_28x28.pgm
Performing forward propagation ...
Testing cudnnGetConvolutionForwardAlgorithm_v7 ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: -1.000000 time requiring 178432 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: -1.000000 time requiring 184784 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: -1.000000 time requiring 2057744 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.011488 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.013312 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.014336 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.024576 time requiring 184784 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.024576 time requiring 178432 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.028512 time requiring 2057744 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnGetConvolutionForwardAlgorithm_v7 ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: -1.000000 time requiring 128848 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: -1.000000 time requiring 1433120 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: -1.000000 time requiring 2450080 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: -1.000000 time requiring 4656640 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.023552 time requiring 2450080 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.026624 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.029600 time requiring 4656640 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.037536 time requiring 1433120 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.044032 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.049152 time requiring 128848 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Resulting weights from Softmax:
0.0000000 0.0000000 0.0000000 0.9999288 0.0000000 0.0000711 0.0000000 0.0000000 0.0000000 0.0000000
Loading image data/five_28x28.pgm
Performing forward propagation ...
Resulting weights from Softmax:
0.0000000 0.0000008 0.0000000 0.0000002 0.0000000 0.9999820 0.0000154 0.0000000 0.0000012 0.0000006Result of classification: 1 3 5Test passed!Testing half precision (math in single precision)
Loading binary file data/conv1.bin
Loading binary file data/conv1.bias.bin
Loading binary file data/conv2.bin
Loading binary file data/conv2.bias.bin
Loading binary file data/ip1.bin
Loading binary file data/ip1.bias.bin
Loading binary file data/ip2.bin
Loading binary file data/ip2.bias.bin
Loading image data/one_28x28.pgm
Performing forward propagation ...
Testing cudnnGetConvolutionForwardAlgorithm_v7 ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: -1.000000 time requiring 178432 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: -1.000000 time requiring 184784 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: -1.000000 time requiring 2057744 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.008096 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.011104 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.011264 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.030464 time requiring 184784 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.030720 time requiring 2057744 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.031488 time requiring 178432 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnGetConvolutionForwardAlgorithm_v7 ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: -1.000000 time requiring 1433120 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: -1.000000 time requiring 4656640 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: -1.000000 time requiring 2450080 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.037696 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.041056 time requiring 2450080 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.048128 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.053248 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.055296 time requiring 1433120 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.057344 time requiring 4656640 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Resulting weights from Softmax:
0.0000001 1.0000000 0.0000001 0.0000000 0.0000563 0.0000001 0.0000012 0.0000017 0.0000010 0.0000001
Loading image data/three_28x28.pgm
Performing forward propagation ...
Testing cudnnGetConvolutionForwardAlgorithm_v7 ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: -1.000000 time requiring 178432 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: -1.000000 time requiring 184784 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: -1.000000 time requiring 2057744 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.010240 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.012544 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.014336 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.025600 time requiring 178432 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.026656 time requiring 184784 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.032448 time requiring 2057744 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnGetConvolutionForwardAlgorithm_v7 ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: -1.000000 time requiring 1433120 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: -1.000000 time requiring 4656640 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: -1.000000 time requiring 2450080 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Testing cudnnFindConvolutionForwardAlgorithm ...
^^^^ CUDNN_STATUS_SUCCESS for Algo 4: 0.022368 time requiring 2450080 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 5: 0.027648 time requiring 4656640 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 0: 0.030720 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 7: 0.034816 time requiring 1433120 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 1: 0.037984 time requiring 0 memory
^^^^ CUDNN_STATUS_SUCCESS for Algo 2: 0.041984 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 6: -1.000000 time requiring 0 memory
^^^^ CUDNN_STATUS_NOT_SUPPORTED for Algo 3: -1.000000 time requiring 0 memory
Resulting weights from Softmax:
0.0000000 0.0000000 0.0000000 1.0000000 0.0000000 0.0000714 0.0000000 0.0000000 0.0000000 0.0000000
Loading image data/five_28x28.pgm
Performing forward propagation ...
Resulting weights from Softmax:
0.0000000 0.0000008 0.0000000 0.0000002 0.0000000 1.0000000 0.0000154 0.0000000 0.0000012 0.0000006Result of classification: 1 3 5Test passed!

(base) justin@justin-System-Product-Name:/usr/src$ locate cudnn_version.h
/usr/include/cudnn_version.h
(base) justin@justin-System-Product-Name:/usr/src$

ref:https://blog.csdn.net/qq_42406643/article/details/109545766

本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如若转载,请注明出处:http://www.mzph.cn/news/801525.shtml

如若内容造成侵权/违法违规/事实不符,请联系多彩编程网进行投诉反馈email:809451989@qq.com,一经查实,立即删除!

相关文章

Leetcode面试经典150_Q14最长公共前缀

题目: 编写一个函数来查找字符串数组中的最长公共前缀。如果不存在公共前缀,返回空字符串 ""。 思路A:横向/纵向扫描 Python: class Solution:def longestCommonPrefix(self, strs: List[str]) -> str:s "…

微软edge浏览器上网、下载速度慢,如何解决??

🏆本文收录于「Bug调优」专栏,主要记录项目实战过程中的Bug之前因后果及提供真实有效的解决方案,希望能够助你一臂之力,帮你早日登顶实现财富自由🚀;同时,欢迎大家关注&&收藏&&…

【Spring】一问详解什么是Spring IoC和DI

目录 一、IoC & DI入门1.1、Spring1.1.1、什么是容器1.1.2、什么是IoC 1.2、IoC介绍1.2.1、传统程序开发1.2.2、问题分析1.2.3、问题解决1.2.4、 IoC优势 1.3、Bean的作用域1.4、DI介绍 二、IoC详解2.1、Bean的存储2.1.1、类注解的使用2.1.2、获取bean对象的其他方式2.1.3、…

【Linux 命令】内核、驱动调试手段总结

文章目录 1. printk2. strace3. Itrace4. ptrace5. ftrace6. 动态打印7. perf8. devmem9. demsg参考: 1. printk **printk()**是 Linux 内核中最广为人知的函数之一。它是我们打印消息的标准工具,通常也是追踪和调试的最基本方法。 虽然 printk() 是基…

element问题总结之el-table使用fixed中 header换行后固定行错位问题/固定列下陷问题

固定列下陷问题 效果图问题描述解决方案1、为table添加ref2、调用节点重新自适应方法doLayout3、在操作表头的时候触发的函数header-dragend绑定doLayout方法4、成功解决 效果图 问题描述 在使用el-table的fixed中,发现如果header拖拽文本折行的时候会出现下陷 解…

【大数据】大数据概论与Hadoop

目录 1.大数据概述 1.1.大数据的概念 1.2.大数据的应用场景 1.3.大数据的关键技术 1.4.大数据的计算模式 1.5.大数据和云计算的关系 1.6.物联网 2.Hadoop 2.1.核心架构 2.2.版本演进 2.3.生态圈的全量结构 1.大数据概述 1.1.大数据的概念 大数据即字面意思&#x…

SRIO学习(3)使用SRIO IP核进行设计

文章目录 前言一、设计框图二、模块介绍三、上板验证 前言 本文将通过使用SRIO IP核实现数据通信,重点在于打通数据链路,具体的协议内容设计并非重点,打通了链路大家自己根据设计需求来即可。 一、设计框图 看了前面高速接口的一些设计&am…

探索算力(云计算、人工智能、边缘计算等):数字时代的引擎

引言 在数字时代,算力是一种至关重要的资源,它是推动科技创新、驱动经济发展的关键引擎之一。简而言之,算力即计算能力,是计算机系统在单位时间内完成的计算任务数量或计算复杂度的度量。随着科技的不断发展和应用范围的不断扩大…

流式密集视频字幕

流式密集视频字幕 摘要1 IntroductionRelated Work3 Streaming Dense Video Captioning Streaming Dense Video Captioning 摘要 对于一个密集视频字幕生成模型,预测在视频中时间上定位的字幕,理想情况下应该能够处理长的输入视频,预测丰富、…

C语言 | Leetcoce C语言题解之第18题四数之和

题目: 题解: int comp(const void* a, const void* b) {return *(int*)a - *(int*)b; }int** fourSum(int* nums, int numsSize, int target, int* returnSize, int** returnColumnSizes) {int** quadruplets malloc(sizeof(int*) * 1001);*returnSize…

企业版ChatGPT用户激增至60万;百度文心一言推出个性化声音定制功能

🦉 AI新闻 🚀 企业版ChatGPT用户激增至60万 摘要:OpenAI首席运营官Brad Lightcap在接受采访时透露,企业版ChatGPT的注册用户已超60万,相较2024年1月的15万用户,短短三个月内增长了300%。这一版本自2023年…

C++11新特性(2) ——动态内存和智能指针从入门到入坑

动态内存与智能指针 动态内存的使用十分容易出现问题(内存泄漏/非法内存),而智能指针能更安全、容易的使用动态内存,因为他负责自动释放所指向的对象,并且在出现异常时,也会自动释放。 两种智能指针&#…

《springcloud alibaba》 四 seata安装以及使用

目录 准备调整db配置准备创建数据库 seata配置nacos配置confi.txt下载向nacos推送配置的脚本 启动seata新建项目order-seata项目 订单项目数据库脚本pom.xmlapplication.yml启动类实体类dao类service类controller类feign类mapper类 stock-seata 库存项目数据库脚本pom.xmlappli…

STM32学习和实践笔记(5):时钟树

STM32一共有4个时钟源。外部时钟高低速各一个,内部时钟高低速各一个。 外部高速时钟是:4-16MHZ的HSE OSC。HS表示高速high speed. E表示外部的external。开发板该处安装的8M晶振。 外部低速时钟是:32.768KHz的LSI OSC。LS表示高速low speed…

为说阿拉伯语的国家进行游戏本地化

阿拉伯语是由超过4亿人使用的语言,并且是二十多个国家的官方语言。进入这些国家的市场并非易事——虽然他们共享一种通用语言,但每个国家都有自己独特的文化,有自己的禁忌和对审查的处理方式。这就是为什么视频游戏公司长期以来都远离阿拉伯语…

Qt QML的插件(Qt Quick 2 Extension Plugin)方法

Qt Quick的插件方法 序言环境前置注意概念——Qt Quick插件的相关知识插件里的qml文件模块名的相关知识模块名本身注意事项模块名版本注意事项 以示例来说明创建插件qmltypes的生成qmltypes的可能性失效 插件的编码注意1、插件模块版本控制2、pro里的注意 调用插件插件信息输入…

华为手机 鸿蒙系统 或者安卓系统的百度网盘下载的文件保存在手机什么位置如何查看

华为手机 鸿蒙系统 或者安卓系统的百度网盘下载的文件保存在手机什么位置如何查看 连接电脑后一般在这里位置 计算机\Mate 20 Pro (UD)\内部存储\Download\BaiduNetdisk 也就是用usb(数据线,不是充电线,要四心的 )连接手机后,打…

计算机网络——40各个层次的安全性

各个层次的安全性 安全电子邮件 Alice需要发送机密的报文m给Bob Alice 产生随机的对称秘钥, K s K_s Ks​使用 K s K_s Ks​对报文进行加密(为了效率)对 K s K_s Ks​使用Bob的公钥进行加密发送 K s ( m ) K_s(m) Ks​(m)和 K B ( K S ) K…

uniapp如何配置后使用uni.chooseLocation等地图位置api

在uniapp中想要使用uni.getLocation、uni.chooseLocation ……api的时候我们需要在小程序就开启配置,不然无法使用。 第一步:首先找到manifest.json 第二步:点击源码视图 第三步:在 mp-weixin 加入下面代码 "permission&…

Paper Digest | GPT-RE:基于大语言模型针对关系抽取的上下文学习

持续分享 SPG 及 SPG LLM 双驱架构应用相关进展 1、动机 在很多自然语言处理任务中,上下文学习的性能已经媲美甚至超过了全资源微调的方法。但是,其在关系抽取任务上的性能却不尽如人意。以 GPT-3 为例,一些基于 GPT-3 的上下文学习抽取方…