1.下载deepin镜像
2.制作U盘启动盘
3.进入bios界面，按F8/F2/F12，选择SECURE BOOT,选择USB启动，再按F8保存，最后重启电脑，选择deepin
系统。

鼠标放到上边 点右键 位置选择
模式 选择-高效

/dev/sda7       312G  266G   46G   86% /media/ym/000ECC01000EB07E
/dev/sda6       311G  273G   38G   88% /media/ym/000646FD00095115
/dev/sda5       311G   26G  285G    9% /media/ym/00084F160006811B

ip: 10.8.19.63
网关： 10.8.91.1
首选DNS：114.114.114.114
子网掩码：255.255.255.0

装NVIDIA显卡
2）添加源
sudo gedit /etc/apt/sources.list 
改为 
#deb http://packages.deepin.com/deepin/ stretch-backports main non-free contrib 
#deb-src http://packages.deepin.com/deepin panda main contrib non-free 
deb [by-hash=force] http://mirrors.tuna.tsinghua.edu.cn/deepin panda main contrib non-free 
deb https://mirrors.tuna.tsinghua.edu.cn/deepin/ stretch-backports main contrib non-free 
3）进行update 
sudo apt update -y 
4）通过命令行安装显卡驱动 
sudo apt-get install -t stretch-backports nvidia-driver nvidia-smi libcuda1 
安装完成后重启电脑 查看显卡信息 nvidia-smi

http://packages.deepin.com/deepin

安装cuda+cudnn
chmod +x cuda_10.0.130_410.48_linux.run
sh cuda_10.0.130_410.48_linux.run

解压cudnn压缩包
sudo cp cuda/include/cudnn.h /usr/local/cuda/include/
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/
sudo chmod a+r /usr/local/cuda/include/cudnn.h
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*j
添加
export PATH=/usr/local/cuda-10.0/bin:$PATH
export PATH=/usr/local/cuda-10.0/lib64:$LD_LIBRARY_PATH

安装conda后可用pip  conda
chmod +x Miniconda3-latest-Linux-x86_64.sh #给执行权限
bash Miniconda3-latest-Linux-x86_64.sh #运行
vi ~/.bashrc
export PATH=/home/ym/anaconda3/bin:$PATH
source ~/.bashrc

用pip安装：
https://pytorch.org/get-started/locally/#mac-anaconda
https://pytorch.org/get-started/previous-versions/

sudo apt update 

sudo apt-get upgrade
apt --fix-broken install