Ubuntu18.04+VNC+Git+Nvidia Driver+Cuda+Cudnn+Vscode+Anaconda+PyTorch+Keras+Tensorflow+...

1. install ubuntu18.04
2. add mirrors
3. update

   sudo apt-get update
   sudo apt-get upgrade
   

4. install vncserver,ssh,gvim,git…

   sudo apt-get install vnc4server
   sudo apt-get install openssh-server
   sudo apt-get install openssh-client
   #check if the install successed by ps -e | grep sshd
   sudo systemctl start ssh # start server
   sudo apt remove vim-common # remove vim
   sudo apt-get install vim-gtk # install gvim
   sudo apt-get install git
   

5. #---5. install nvidia driver,cuda,cudnn
   
   # 1). disable nouveau
   sudo vim /etc/modprobe.d/blacklist.conf
   # add following 2 lines in the end of the /etc/modprobe.d/blacklist.conf
   blacklist nouveau
   options nouveau modeset=0
   # update
   sudo update-initramfs -u
   # reboot
   sudo reboot
   # after reboot,check
   lsmod | grep nouveau # nothing get here
   
   
   # 2). install nvidia driver
   a.
   ubuntu-drivers devices #other devices
   sudo apt-get remove --purge nvidia*
   sudo ubuntu-drivers autoinstall 
   or sudo apt install nvidia-410
   b.
   sudo add-apt-repository ppa:graphics-drivers/ppa
   sudo apt-get update
   sudo apt-get install nvidia-390
   sudo apt-get install mesa-common-dev
   sudo apt-get install freeglut3-dev
   
   #reboot
   sudo reboot
   #after reboot,check
   nvidia-smi
   
   # 3). install cuda
   a.
   sudo sh ~name/ubuntu_setup/cuda_9.0.176_384.81_linux.run
   # add cuda path to ~/.bashrc
   #run cuda tests in the NVIDIA_CUDA-9.0_Samples
   cd ~NVIDIA_CUDA-9.0_Samples/xx/xx
   make run
   
   b.
   sudo apt-key add /var/cuda-repo-10-0-local-10.0.130-410.48/7fa2af80.pub
   ok
   sudo dpkg -i cuda-repo-ubuntu1804-10-0-local-10.0.130-410.48_1.0-1_amd64.deb
   sudo apt-get update
   sudo apt-get install cuda
   
   path config:
   sudo ~/.bashrc
   export PATH=/usr/local/cuda-10.0/bin${PATH:+:$PATH}}			   
   export LD_LIBRARY_PATH=/usr/local/cuda-10.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
   source ~/.bashrc
   
   # 4). install cudnn
   a.
   sudo dpkg -i ~name/ubuntu_setup/libcudnn7_7.1.4.18-1+cuda9.0_amd64.deb
   sudo dpkg -i ~name/ubuntu_setup/libcudnn7-dev_7.1.4.18-1+cuda9.0_amd64.deb
   sudo dpkg -i ~name/ubuntu_setup/libcudnn7-doc_7.1.4.18-1+cuda9.0_amd64.deb
   
   b.
   $ tar -xzvf cudnn-10.0-linux-x64-v7.4.1.5.tgz
   $ 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 /usr/local/cuda/lib64/libcudnn*
   
   #then run cudnn tests
   cp /usr/src/cudnn_samples_v7 . -rf
   cd cudnn_samples_v7/mnistCUDNN
   make run
   
   #look version
   cat  /usr/local/cuda/version.txt
   cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2
   nvcc -V
   
   #---6. install vscode
   #1). install code
   # download from https://code.visualstudio.com/docs/?dv=linux64 gzip linux 64
   tar -xzvf code-stable-1534444642.tar.gz
   sudo mv VSCode-linux-x64/ /tool/
   # add /tool/VSCode-linux-x64/code to your PATH in .bashrc
   #2). fix the code error in vnc
   cd /usr/lib/x86_64-linux-gnu
   sudo cp libxcb.so.1.1.0 libxcb.so.1.1.0.bkp
   sudo sed -i 's/BIG-REQUESTS/_IG-REQUESTS/' /usr/lib/x86_64-linux-gnu/libxcb.so.1
   # libxcb.so.1 is a soft link to libxcb.so.1.1.0
   
   #---7 install anaconda, pytorch,tensorflow...
   #1) install anaconda
   sudo sh ~name/ubuntu_setup/Anaconda3-5.2.0-Linux-x86_64.sh
   
   #2) create env for pytorch
   sudo /tool/anaconda3/bin/conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
   sudo /tool/anaconda3/bin/conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
   sudo /tool/anaconda3/bin/conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
   sudo /tool/anaconda3/bin/conda config --set show_channel_urls yes
   
   sudo /tool/anaconda3/bin/conda create --name torch python=3.7
   source activate torch
   sudo /tool/anaconda3/bin/conda install jupyter --name torch
   sudo /tool/anaconda3/bin/conda install spyder --name torch
   sudo /tool/anaconda3/bin/conda install pytorch torchvision cuda90 -c pytorch --name torch
   sudo /tool/anaconda3/bin/conda install pandas --name torch
   sudo /tool/anaconda3/bin/conda install matplotlib --name torch
   sudo /tool/anaconda3/bin/conda install scipy --name torch
   sudo /tool/anaconda3/envs/torch/bin/pip install opencv-python
   conda deactivate
   
   #3) create env for keras + tensorflow
   sudo /tool/anaconda3/bin/conda create --name keras python=3.7
   source activate keras
   sudo /tool/anaconda3/envs/keras/bin/pip install tensorflow-gpu==1.10 keras
   sudo /tool/anaconda3/bin/conda install jupyter --name keras
   sudo /tool/anaconda3/bin/conda install spyder --name keras
   sudo /tool/anaconda3/bin/conda install pandas --name keras
   sudo /tool/anaconda3/bin/conda install matplotlib --name keras
   sudo /tool/anaconda3/bin/conda install scipy --name keras
   sudo /tool/anaconda3/envs/keras/bin/pip install opencv-python
   conda deactivate
   
   #---8 install opencv
   #1) install cmake
   sudo apt-get install cmake
   sudo apt-get install build-essential libgtk2.0-dev libavcodec-dev libavformat-dev libjpeg.dev libtiff4.dev libswscale-dev libjasper-dev
   
   #2) install opencv
   # download from https://opencv.org/releases.html
   sudo apt-get install build-essential
   sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
   #python3
   sudo apt-get install python3-dev python3-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff5-dev  libtiff-dev libdc1394-22-dev       
   sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev liblapacke-dev  
   sudo apt-get install libxvidcore-dev libx264-dev  
   sudo apt-get install libatlas-base-dev gfortran      
   sudo apt-get install ffmpeg
   
   unzip opencv-3.4.2.zip
   cd opencv-3.4.2
   mkdir build
   cd build
   cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local ..
   sudo make -j8
   sudo make install
   sudo vi /etc/ld.so.conf.d/opencv.conf
   # add /usr/local/lib in the end of /etc/ld.so.conf.d/opencv.conf
   sudo ldconfig
   # add env in .bashrc
   PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
   export PKG_CONFIG_PATH
   #then run test
   cd opencv-3.4.2/samples/cpp/example_cmake
   cmake .
   make
   ./opencv_example
   

AI Server installation Ubuntu 18.04
#–1 首先按照 AI Server installation Ubuntu16.04 的推荐，严格分区，＂/＂为主分区，其余为逻辑分区
#–2 安装完上述第4步的vnc4server后，在命令行输入vnc4server，生成隐藏文件.vnc，进入，备份并参照其他服务器配置xstartup，安装所需组件
#–3 安装驱动: 410.104, cuda: 10.0, cudnn: , 7.6.3, 并测试
#–4 在安装anaconda过程中记得自己设置安装路径: /tool/anaconda3  
       创建虚拟环境: conda create -n name pytohn=3.7
       查看虚拟环境: conda-env list
       删除虚拟环境: conda remove -n name -all
#–5 安装pytorch: sudo /tool/anaconda3/bin/conda install pytorch torchvision cudatoolkit=10.0 --name torch, 去掉了-c pytorch
#–6 安装tensorflow: sudo /tool/anaconda3/envs/keras/bin/pip install tensorflow-gpu keras
#–7 框架中设计的其余组件按照 AI Server installation Ubuntu16.04
#–8 设置静态IP
         sudo gvim /etc/netplan/01...
         IPv4 默认网关 192.168.13.1
         IPv4 DHCP服务器 192.168.13.1
         IPv4 DNS服务器 192.168.11.13
                       192.168.11.33
         sudo netplan apply #立即生效
#–9 vnc 配置
       运行vnc4server, 生成 .vnc 
       cd .vnc
       cp xstartup xstartup.bak
       gvim xstartup
       ... or cp others xstartup
       sudo apt-get install ...
       sudo chmod +x .vnc/xstartup
#–10 git管理
     sudo apt-get install git openssh-server openssh-client
     sudo adduser git
     sudo mkdir /home/git/code
     cd /home/git/code
     sudo git init --bare sample.git
     ssh-keygen -t rsa 
     cp /home/name/.ssh/id_rsa.pub /home/git/
     touch authorized_keys  #git log in
     mv authorized_keys .ssh
     cat id_rsa.pub >> .ssh/authorized_keys
     git clone [email protected].**.**:/home/git/code/sample.git

xstartup

#!/bin/sh
xrdb $HOME/.Xresources
xsetroot -solid grey
vncconfig -nowin &
eval `dbus-launch | grep ADDRES | sed -e 's/^/export /'`
export DESKTOP_SESSION=ubuntu
export GDMSESSION=ubuntu
export STARTUP="/usr/bin/gnome-session --session=gnome-flashback-metacity"
export XDG_CURRENT_DESKTOP="GNOME-Flashback:GNOME"
export XDG_MENU_PREFIX="gnome-flashback-"

gnome-session &
nautilus --force-desktop &
metacity &
gnome-panel &
gnome-settings-daemon &
gnome-terminal &

Partition: