ubuntu系统各种问题解决方案

修复grub2

https://www.howtogeek.com/114884/how-to-repair-grub2-when-ubuntu-wont-boot/

安装N卡驱动

https://blog.csdn.net/xunan003/article/details/81665835

ubuntu出现了内部错误

sudo rm -rf /var/crash

dpkg：警告：无法找到软件包 XXXX 问题

sudo dpkg --configure -a
dpkg -l | grep ^ii | awk ‘{print $2}’ | grep -v XXX | xargs
sudo aptitude reinstall

ubuntu18.04开机键鼠不可用，重启无效解决方法

1.排除硬件问题（进入windows系统看看是否可用，或尝试打开BIOS界面）
2.非硬件问题：重启按下ESC进入grub引导界面
3.选择ubuntu高级选项（ubuntu Advanced Options）
4.选择(Recovery mode)的选项
5.选择Network，并选择yes
6.选择Drop to root shell prompt，并点"Enter"
7.输入mount -o rw,remount /
8.输入apt install xserver-xorg-input-all（需要联网）
9.完成后输入sudo reboot重启电脑

18.04安装搜狗拼音

https://blog.csdn.net/fx_yzjy101/article/details/80243710

ubuntu 软件包换源

https://www.cnblogs.com/tlz888/p/9569234.html

安装gcc

sudo apt-get update
sudo apt-get install build-essential

python升级

https://www.cnblogs.com/yjlch1016/p/8641910.html

python

https://blog.csdn.net/Test_tju/article/details/86603160

pip装包换源

https://blog.csdn.net/moshiyaofei/article/details/86529216

github提速

https://www.ipaddress.com/查询github.com和github.global.ssl.fastly.net的ip地址
sudo vim /etc/hosts
把两个网址及其ip地址按照 "ip地址 网址"的形式添加到文件末尾

github项目卸载（以glog为例）

sudo rm -rf /usr/local/include/glog/
sudo rm -rf /usr/local/lib/libglog*

出现ImportError: No module named ‘pip._internal’

强制重新安装pip
https://blog.csdn.net/youlaqian/article/details/81410700

安装CUDA

sudo dpkg -i cuda-repo-ubuntu1604<<>>
sudo apt-key add /var/cuda-repo-<<>>/7fa2af80.pub
sudo apt-get update
sudo apt-get install cuda
(安装多个版本的cuda,第二个版本之后需要指定版本)sudo apt-get install cuda-10-0

https://blog.csdn.net/wf19930209/article/details/81879514
https://blog.csdn.net/wanzhen4330/article/details/81699769

安装完成加入~/.bashrc
export LD_LIBRARY_PATH=$L{D}_{L}IBRAR{Y}_{P}ATH:/usr/local/cuda-10.0/lib64exportPATH=$PATH:/usr/local/cuda-10.0/bin
export CUDA_HOME=$CUDA_HOME:/usr/local/cuda-10.0

更换默认cuda版本

https://blog.csdn.net/ksws0292756/article/details/80120561
sudo rm -rf cuda
sudo ln -s /usr/local/cuda- /usr/local/cuda

安装cudnn

download (need a nvidia account)
https://developer.nvidia.com/rdp/cudnn-archive
https://blog.csdn.net/wanzhen4330/article/details/81699769

如果cudnn的文件形式是solitairetheme8，执行
cp cudnn--linux-x64-v.solitairetheme8 cudnn--linux-x64-v.tgz
tar -xvf cudnn-8.0-linux-x64-v5.1.tgz

安装pycharm

官网上下载
在/usr/share/applications/下创建一个Pycharm.desktop，键入以下内容：

[Desktop Entry]
Version=1.0
Type=Application
Name=Pycharm
Icon=/home/syq/pycharm-community-2019.2/bin/pycharm.png
Exec=sh /home/syq/pycharm-community-2019.2/bin/pycharm.sh
MimeType=application/x-py;
Name[en_Us]=pycharm

保存，复制到桌面

安装tensorflow

https://tensorflow.google.cn/install/gpu

安装pytorch

https://pytorch.org/get-started/locally/

maskrcnn-benchmark

python3 tools/train_net.py --config-file ~/github/maskrcnn-benchmark-master/configs/e2e_mask_rcnn_R_101_FPN_1x.yaml

https://github.com/facebookresearch/maskrcnn-benchmark
https://blog.csdn.net/ChuiGeDaQiQiu/article/details/83868512
https://blog.csdn.net/yang332233/article/details/97205123
https://yq.aliyun.com/articles/701361