<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[Jean的博客]]></title><description><![CDATA[奋斗+追求=做最好的自己]]></description><link>https://blog.youkuaiyun.com/Jean001100</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; Jean001100]]></copyright><item><title><![CDATA[Knowledge graph, Freebase, Wikidata三大知识图谱]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/119191096</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/119191096</guid><author>Jean001100</author><pubDate>Thu, 29 Jul 2021 16:09:14 +0800</pubDate><description><![CDATA[知识图谱本质上是一种语义网络，其节点代表实体或者概念，边代表实体/概念之间的各种语义关系。

Knowledge Graph：


]]></description><category></category></item><item><title><![CDATA[pytorch调试代码遇到常见错误类型]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/107393169</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/107393169</guid><author>Jean001100</author><pubDate>Thu, 16 Jul 2020 20:49:10 +0800</pubDate><description><![CDATA[1. 代码运行遇见以下报错内容：

RuntimeError: cublas runtime error : library not initialized at /opt/conda/conda-bld/pytorch_1549627089062/work/aten/src/THC/THCGeneral.cpp:250
	RuntimeError: merge_sort: failed to synchronize: device-side assert triggere
以上错误是某个变量的索引超出边界]]></description><category></category></item><item><title><![CDATA[ubuntu系统外连接两个显示器设置]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/107347574</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/107347574</guid><author>Jean001100</author><pubDate>Tue, 14 Jul 2020 21:31:14 +0800</pubDate><description><![CDATA[1.打开终端，输入


xrandr

查看显示器情况，是否连接两个显示器，一个是笔记本显示器，比如：DP-4；另一个是外接的HDMI显示器HDMI-0

2.设置主屏幕


xrandr --output DP-4 --auto --primary

--auto表示自动设置分辨率

--primary表示设置为主屏幕

3.扩展屏幕模式


xrandr --output HDMI-0 --right-of DP-4 --auto

--right-of表示右侧拓展
...]]></description><category></category></item><item><title><![CDATA[关于依存句法的一些知识]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/107070736</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/107070736</guid><author>Jean001100</author><pubDate>Wed, 01 Jul 2020 19:48:45 +0800</pubDate><description><![CDATA[https://www.youkuaiyun.com/gather_2b/Mtjagg4sNzIxLWJsb2cO0O0O.html



mantchs.com/2020/02/18/Introduction-NLP/sentence_parser/


]]></description><category></category></item><item><title><![CDATA[%d,%c,%s,%x各代表什么]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106854506</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106854506</guid><author>Jean001100</author><pubDate>Fri, 19 Jun 2020 13:24:03 +0800</pubDate><description><![CDATA[转换说明符
   %a(%A)   浮点数、十六进制数字和p-(P-)记数法(C99)
   %c       字符
   %d       有符号十进制整数
   %f       浮点数(包括float和doulbe)
   %e(%E)   浮点数指数输出[e-(E-)记数法]
   %g(%G)   浮点数不显无意义的零"0"
   %i       有符号十进制整数(与%d相同)
   ...]]></description><category></category></item><item><title><![CDATA[正则表达式+re.findall+re.match]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106850095</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106850095</guid><author>Jean001100</author><pubDate>Fri, 19 Jun 2020 10:14:04 +0800</pubDate><description><![CDATA[1.正则化表达式

常用的元字符:

代码
			说明
		.
			匹配除换行符以外的任意字符
		\w
			匹配字符或数字或下划线或汉字等
		\s
			匹配任意的空白符，包括空格，制表符（tab），换行符，中文全角空格等
		\d
			匹配数字
		\b
			匹配单词的开始或结束
		^
			匹配字符串的开始
		$
			匹配字符串的结束
		常用的限定词：

代码/语法
			说明
		*
			重复零次或更多次
		+
			重复一次或更多次
		?
			重复零次或一次
		{n}
]]></description><category></category></item><item><title><![CDATA[非root用戶import torch遇到ImportError: libmkl_intel_lp64.so: cannot open shared object file: No such file]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106613553</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106613553</guid><author>Jean001100</author><pubDate>Mon, 08 Jun 2020 10:35:22 +0800</pubDate><description><![CDATA[解決方法：

1. 搜索該文件路徑


find /home/usename -name libmkl_intel_lp64.so

如果這個文件存在，則顯示路徑：

/home/usename/anaconda3/lib/libmkl_intel_lp64.so

2. 將搜索出來的路徑添加到環境變量中


vi /home/usename/.bashrc

export LD_LIBRARY_PATH=/home/usename/anaconda3/lib:$LD_LIBRARY_PATH

3. 更新]]></description><category></category></item><item><title><![CDATA[使用pytorch版本scibert环境配置与使用]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106530518</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106530518</guid><author>Jean001100</author><pubDate>Wed, 03 Jun 2020 18:46:41 +0800</pubDate><description><![CDATA[1.环境配置：python3.6

conda install pytorch=1.3.1

pip install --upgrade pip

pip install transformers

详细见https://github.com/huggingface/transformers

sudo apt-get install git

pip install -r requirements.txt

pip install --upgrade .

详细见https://github.com/a.]]></description><category></category></item><item><title><![CDATA[ubuntu18.04安装，nvidia安装，cuda安装，cudnn安装]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106439342</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106439342</guid><author>Jean001100</author><pubDate>Sat, 30 May 2020 12:14:40 +0800</pubDate><description><![CDATA[1.ubuntu18.04安装

用刻好的U盘启动盘安装ubuntu18,04，按照推荐步骤一步一步走。

2.nvidia安装

找到Software&amp;Updates，先更换aliyun源，然后在Additional Drivers中安装nvidia驱动，选择第一个（proprietary，tested）进行安装。

3.cuda安装

下载cuda10.0，选择runfile(local)这个文件下载，见链接https://developer.nvidia.com/cuda-10.0-downl]]></description><category></category></item><item><title><![CDATA[ubuntu安装并开启ssh服务]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106436740</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106436740</guid><author>Jean001100</author><pubDate>Sat, 30 May 2020 08:57:34 +0800</pubDate><description><![CDATA[1.安装ssh

终端窗口，命令行输入：


sudo apt-get install openssh-server

2.查看ssh服务是否启动

终端窗口，命令行输入：


sudo ps -e | grep ssh

如果有sshd，说明ssh服务已经启动，如果没用启动，输入一下命令行：


sudo service ssh start

3.查看ubuntu的IP地址

终端窗口，命令行输入：


sudo ifconfig


...]]></description><category></category></item><item><title><![CDATA[en_core_web_md安装与使用]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106203318</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106203318</guid><author>Jean001100</author><pubDate>Mon, 18 May 2020 22:44:19 +0800</pubDate><description><![CDATA[安装

1. spacy 安装：


conda install spacy

2. en库安装：


python -m spacy download en

3. en_core_web_md库安装：


python -m spacy download en_core_web_md

使用


import spacy
import en_core_web_md

nlp = en_core_web_md.load()
sentence = 'I love learning. I like knowl]]></description><category></category></item><item><title><![CDATA[远程服务器linux系统非root安装jdk1.8+与环境配置]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106035918</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106035918</guid><author>Jean001100</author><pubDate>Sun, 10 May 2020 14:53:34 +0800</pubDate><description><![CDATA[1.下载jdk1.8+

下载jdk-8u251-linux-x64.tar.gz，见链接https://www.oracle.com/java/technologies/javase-jdk8-downloads.html

2.解压jdk压缩包（路径没有要求）

放到服务器自己的目录下，在当前目录进行解压缩


tar -zxvf jdk-8u251-linux-x64.tar.gz

3.配置环境


vi ~/.bash_profile

export JAVA_HOME=/home1/wh/cen]]></description><category></category></item><item><title><![CDATA[conda install遇到Segmentation fault错误]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106031806</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106031806</guid><author>Jean001100</author><pubDate>Sun, 10 May 2020 09:11:50 +0800</pubDate><description><![CDATA[出错原因：

可能是之前安装的时候网络不好导致中途中断，从而存在于本地缓存中，但是并不完整。

解决方案：


conda clean -a 


删除所有的缓存。

另外，为了避免网络不良导致的中断，建设使用国内的镜像源下载。
...]]></description><category></category></item><item><title><![CDATA[远程服务器ubuntu16.04操作系统非root安装cuda10.02和cudnn7.6.5]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/106016806</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/106016806</guid><author>Jean001100</author><pubDate>Sat, 09 May 2020 14:18:17 +0800</pubDate><description><![CDATA[1. 安装cuda10.02

下载cuda10.02，选择runfile(local)这个文件下载，见链接https://developer.nvidia.com/cuda-downloads?target_os=Linux&amp;target_arch=x86_64&amp;target_distro=Ubuntu&amp;target_version=1604&amp;target_type=runfilelocal

然后命令行执行如下操作：


chmod +xcuda_10.2.89_440.]]></description><category></category></item><item><title><![CDATA[API calls]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/82947162</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/82947162</guid><author>Jean001100</author><pubDate>Fri, 05 Oct 2018 21:23:44 +0800</pubDate><description><![CDATA[API calls：API接口调用。

API（Application Programming Interface,应用程序编程接口）是一些预先定义的函数，目的是提供应用程序与开发人员基于某软件或硬件得以访问一组例程的能力，而又无需访问源码，或理解内部工作机制的细节。

程序功能远程过程调用（RPC）：通过作用在共享数据缓存器上的过程（或任务）实现程序间的通信。标准查询语言（SQL）：是标准的访问...]]></description><category></category></item><item><title><![CDATA[Anaconda简介]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/82184557</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/82184557</guid><author>Jean001100</author><pubDate>Wed, 29 Aug 2018 15:53:45 +0800</pubDate><description><![CDATA[Anaconda 是专门为了方便使用 Python 进行数据科学研究而建立的一组软件包，涵盖了数据科学领域常见的 Python 库，并且自带了专门用来解决软件环境依赖问题的 conda 包管理系统。主要是提供了包管理与环境管理的功能，可以很方便地解决多版本python并存、切换以及各种第三方包安装问题。Anaconda利用工具/命令conda来进行package和environment的管理，并且...]]></description><category></category></item><item><title><![CDATA[安装AllenNLP遇到的问题和解决方法]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/82182022</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/82182022</guid><author>Jean001100</author><pubDate>Wed, 29 Aug 2018 14:16:16 +0800</pubDate><description><![CDATA[AllenNLP的安装过程：

详细见官网安装教程https://github.com/allenai/allennlp/blob/v0.5.0/README.md#installing-using-docker

操作系统windows10

安装环境python3.6.2

命令行安装pip install allennlp

遇到的问题：

1.error: Microsoft Visual...]]></description><category></category></item><item><title><![CDATA[NLP学习资料]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/82149589</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/82149589</guid><author>Jean001100</author><pubDate>Tue, 28 Aug 2018 16:06:12 +0800</pubDate><description><![CDATA[NLP参考资源

自然语言处理（Natural Language Processing）是深度学习的主要应用领域之一。

1. 教程

CS224d: Deep Learning for Natural Language Processing

http://cs224d.stanford.edu/

CS224d课程的课件

http://web.stanford.edu/class/cs224...]]></description><category></category></item><item><title><![CDATA[windows 安装 pytorch 0.4.0]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/81877678</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/81877678</guid><author>Jean001100</author><pubDate>Mon, 20 Aug 2018 20:56:42 +0800</pubDate><description><![CDATA[转载https://blog.youkuaiyun.com/xiangxianghehe/article/details/80103095

2018年4月25日，PyTorch 官方发布 0.4.0 版本，该版本的PyTorch 有多项重大更新，其中最重要的改进是支持 Windows系统。Windows用户能直接通过conda、pip和源码编译三种方式来安装Pytorch，不过需要强调Windows下的Py...]]></description><category></category></item><item><title><![CDATA[CPU和GPU]]></title><link>https://blog.youkuaiyun.com/Jean001100/article/details/81877192</link><guid>https://blog.youkuaiyun.com/Jean001100/article/details/81877192</guid><author>Jean001100</author><pubDate>Mon, 20 Aug 2018 20:22:09 +0800</pubDate><description><![CDATA[CPU, Central Processing Unit  中央处理器

中央处理器（CPU，Central Processing Unit）是一块超大规模的集成电路，是一台计算机的运算核心和控制核心。它的功能主要是解释计算机指令以及处理计算机软件中的数据。

中央处理器主要包括运算器（算术逻辑运算单元，ALU，Arithmetic Logic Unit）和高速缓冲存储器（Cache）及实现它们之...]]></description><category></category></item></channel></rss>