# Ubuntu24.04/22.04重灌筆記：GPU安裝與深度學習
###### tags: `Tutorial`, `Ubuntu`, `VScode`, `python`

目錄：
+ [重灌Ubuntu](#ubuntu)
+ [CUDA安裝](#cuda)
+ [Nvidia driver](#nvidia)
+ [CUDA Toolkit](#toolkit)
+ [cudnn](#cudnn)
+ [建立虛擬環境](#virtualenv)
+ [使用方法](#venv)
+ [終端機管理工具: tmux](#tmux)
+ [下載 google drive 檔案: gdown](#gdown)
+ [安裝python 3.9](#py39)

其他筆記：
+ [VScode 使用 SSH 進行遠端程式開發](https://hackmd.io/@Chieh997/VScodeSSH)
+ [深度學習python套件安裝](https://hackmd.io/@Chieh997/deeppython): Install Pytorch, Tensorflow, Pyspark
+ [R in Ubuntu22.04](https://hackmd.io/@Chieh997/ubuntur): Install R and use with Jupyter Notebook and VScode
---
<a id='ubuntu'></a>
## 重灌Ubuntu
+ [Ubuntu 是什麼？如何透過 USB 安裝 Ubuntu 作業系統？完整教學指南](https://adersaytech.com/practical-software/ubuntu-install-tutorial.html)
### 製作重灌隨身碟
1. 前往[Rufus官方網站](https://rufus.ie/zh_TW/)並下載Rufus軟體

2. 前往[Ubuntu官方網站](https://ubuntu.com/download/desktop)下載桌面版的安裝檔(ISO)
3. 使用Rufus及安裝檔建立重灌用開機隨身碟
### 進入開機選單選擇USB開機
- Long press `Esc`, `F2`, `Del` or other possible keys when press the power bottom to go to BIOS or boot menu.
- Check the key based on your motherboard's brand

---
<a id='cuda'></a>
## CUDA安裝
+ [Ubuntu 20.04中安裝nvidia-driver-460版 & CUDA-11.4.2版 & cuDNN](https://medium.com/@scofield44165/ubuntu-20-04%E4%B8%AD%E5%AE%89%E8%A3%9Dnvidia-driver-cuda-11-4-2%E7%89%88-cudnn-install-nvidia-driver-460-cuda-11-4-2-cudnn-6569ab816cc5)
+ [Ubuntu 安裝 CUDA cuDNN pytorch tensorflow mxnet](https://mikethreeacer.medium.com/ubuntu-18-04-%E5%AE%89%E8%A3%9D-cuda-cudnn-anaconda-pytorch-1f170b3326a4#1b0a)
+ [Ubuntu16.04安装NVIDIA驱动+CUDA9.0+cuDNN7.0](https://blog.csdn.net/mtllyb/article/details/79505012)
+ [Ubuntu 22.04 for Deep Learning](https://gist.github.com/amir-saniyan/b3d8e06145a8569c0d0e030af6d60bea)
### 確認GPU資訊

sudo lshw -numeric -C display

<a id='nvidia'></a>
### Install Nvidia Driver
如果在有網路的情況下安裝ubuntu且同意third-party程式一同安裝(include nvidia dirver)，可先直接確認是否有安裝成功。成功安裝可直接進入cuda-toolkit安裝。

nvidia-smi

1. 列出支援的GPU driver版本

ubuntu-drivers devices
# or
ubuntu-drivers list

2. 安裝nvidia-driver並重新啟動

sudo apt-get update
sudo apt upgrade
sudo apt install nvidia-driver-{VERSION_NUMBER}
sudo reboot

3. 檢查nvidia driver版本

nvidia-smi

- [清除既有nvidia driver和ppa](https://forums.developer.nvidia.com/t/newly-installed-drivers-are-not-found-when-nvidia-smi-is-called/82686/6)

sudo apt-get remove --purge '^nvidia-.*'
sudo apt-get --purge remove "*cublas*" "cuda*"
sudo apt-get --purge remove "*nvidia*"
sudo add-apt-repository --remove ppa:graphics-drivers/ppa
sudo rm /etc/X11/xorg.conf
sudo apt autoremove
sudo reboot

<a id='toolkit'></a>
### Install CUDA-Toolkit
+ [NVIDIA CUDA Installation Guide for Linux](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#ubuntu-installation)

1. 依序執行官方網站中的指令，local或network都可以

+ Install [Latest CUDA](https://developer.nvidia.com/cuda-downloads) - 推薦使用network下載，較容易成功。

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.0-1_all.deb
sudo dpkg -i cuda-keyring_1.0-1_all.deb
sudo apt-get update
sudo apt-get -y install cuda

+ Install Older CUDA (e.g. [11.7](https://developer.nvidia.com/cuda-11-7-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=22.04&target_type=deb_network))
+ 建議用deb(local)安裝，須在最後一行指定CUDA版本
+ 安裝出現錯誤(`E: Error, pkgProblemResolver::Resolve generated breaks, this may be caused by held packages.`)的[解法](https://blog.csdn.net/weixin_42156097/article/details/103805063)

sudo apt-get install aptitude
sudo aptitude install cuda
sudo apt-get install cuda

2. `.bashrc`設定環境並刷新terminal

export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/lib64
export PATH=$PATH:/usr/local/cuda/bin

source .bashrc

3. 檢查CUDA版本

nvcc -V

<a id='cudnn'></a>
### Install cuDNN
#### Method 1: [Latest Version Download](https://developer.nvidia.com/cudnn-downloads)

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install cudnn

#### Method 2: [cuDNN Package Manager Installation](https://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html#cudnn-package-manager-installation-overview)
1. Enable the repository

# ${OS} = debian11, ubuntu1804, ubuntu2004, or ubuntu2204
wget https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin 

sudo mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/3bf863cc.pub
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/ /"
sudo apt-get update

2. Install the [cuDNN library](https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/)

# ${cudnn_version} = 8.{x}.0.*
# ${cuda_version} = cuda11.{y}
sudo apt-get install libcudnn8=${cudnn_version}-1+${cuda_version}
sudo apt-get install libcudnn8-dev=${cudnn_version}-1+${cuda_version}

+ [How to verify CuDNN installation?](https://stackoverflow.com/questions/31326015/how-to-verify-cudnn-installation)
:::info
Might not working for ubuntu 24.04
:::

whereis cudnn_version.h
CUDNN_H_PATH=$(whereis cudnn_version.h)
cat ${CUDNN_H_PATH} | grep CUDNN_MAJOR -A 2

The result should be look like the following, which means the version is `{X}.{Y}.0`

#define CUDNN_MAJOR {X}
#define CUDNN_MINOR {Y}
#define CUDNN_PATCHLEVEL 0

---

<a id='virtualenv'></a>
## 建立虛擬環境
### [導出舊環境](https://stackoverflow.com/questions/14684968/how-to-export-virtualenv)
先進入舊環境，使用下列指令將需要用到的package導出至`requirements.txt`

pip freeze > requirements.txt

### 安裝Virtualenv與Virtualenvwrapper
#### [[2025 Version] For Ubuntu 24.04 & Python 3.12](https://techbend.hashnode.dev/python312-upgrade-setting-up-virtualenvwrapper)
Python 3.12阻止一般使用者在主環境下使用pip安裝，所以要先在虛擬環境下安裝virtualenvwrapper。
1. 更新系統安裝包

 sudo apt-get update
 sudo apt-get upgrade

2. 安裝pip與Virtualenv

sudo apt-get install python3-pip
sudo apt-get install virtualenv

3. 建立虛擬環境**venv**，並在該環境下安裝Virtualenvwrapper

# 建立並啟用環境venv
virtualenv venv
source ./venv/bin/activate
# 在venv下安裝virtualenvwrapper
pip install virtualenvwrapper

4. 在啟動檔`.bashrc`或`.zshrc`中設定路徑與要求
+ `WORKON_HOME`: 使用wrapper建立的環境一般會在 `$HOME/.virtualenvs`
+ virtualenvwrapper本體相關的路徑會在先前用virtualenv直接建立的**venv**路徑底下: `$HOME/venv/bin/`

# PATH related to virtualenvwrapper workon
export WORKON_HOME=$HOME/.virtualenvs
# PATH related to virtualenvwrapper itself
export VIRTUALENVWRAPPER_PYTHON=$HOME/venv/bin/python
export VIRTUALENVWRAPPER_VIRTUALENV=$HOME/venv/bin/virtualenv
source $HOME/venv/bin/virtualenvwrapper.sh

# Add venv as part of PATH
export PATH="$HOME/venv/bin:$PATH"

#### For Python 3.10
1. 更新系統安裝包

 sudo apt-get update
 sudo apt-get upgrade

2. 安裝pip

sudo apt-get install python3-pip

3. 安裝Virtualenv與Virtualenvwrapper

sudo apt-get install virtualenv
pip install virtualenvwrapper

4. Virtualenvwrapper相關設定
+ 在啟動檔`.bashrc`中設定路徑與要求

# {path/to/python}可以用`which python`來查詢
export WORKON_HOME={path/to/env}
export VIRTUALENVWRAPPER_PYTHON={path/to/python}

# export VIRTUALENVWRAPPER_PYTHON=/usr/bin/python3
# export WORKON_HOME=$HOME/.virtualenvs
# export VIRTUALENVWRAPPER_VIRTUALENV=~/.local/bin/virtualenv

# 依據安裝位置嘗試下列其中一行指令即可
source ~/.local/bin/virtualenvwrapper.sh
# source /usr/local/bin/virtualenvwrapper.sh

+ 執行啟動檔

source .bashrc

<a id='venv'></a>
### Virtualenv使用方法
+ 常用指令

# 建立環境
virtualenv {env_name}
# 啟用環境
source ./{env_name}/bin/activate
# 離開環境
deactivate

### Virtualenvwrapper使用方法
+ 常用指令

# 查詢環境
lsvirtualenv
# 建立環境
mkvirtualenv -p {python3.X} {venv_name}
# 刪除環境
rmvirtualenv {venv_name}
# 使用環境
workon {venv_name}
# 離開環境
deactivate

### 重新安裝套件

pip install -r {path/to/requirements.txt}

#### Reference
+ [Ubuntu 環境下安裝pip & python3](http://python-learnnotebook.blogspot.com/2018/10/ubuntu-pip-python3.html)
+ [Python3 - Virtualenv & Virtualenvwrapper 拯救骯髒的套件環境](https://medium.com/@minecola/python3-%E6%8B%AF%E6%95%91%E9%AA%AF%E9%AB%92%E7%92%B0%E5%A2%83%E5%A4%A7%E4%BD%9C%E6%88%B0-with-virtualenv-4b398142463d)
+ [Using different versions of python with virtualenvwrapper - StackOverflow](https://stackoverflow.com/questions/6401951/using-different-versions-of-python-with-virtualenvwrapper)

<a id='tmux'></a>
## 終端機管理工具：tmux

flowchart LR;
	A[user]
	
    subgraph Server
        B["server 
        core"]
        t0[/"connect
        session"/]
        t1[/session 1/]
        t2[/session 2/]
        t3[/.../]
        t0 -.- B -.-  t1 & t2 & t3
    end    
	A <===>|ssh| t0
    %% A x---x B

使用時機：
1. 可開啟多個terminal視窗(但對於VScode使用者較無影響)。
2. 若程式執行時間過長，避免ssh斷線後中斷運行，此工具可協助於背景運行程式，不受連線情形影響。

### Install tmux

sudo apt install tmux

Pane, window, session 等的差別與使用可參考 [Linux tmux 終端機管理工具使用教學](https://blog.gtwang.org/linux/linux-tmux-terminal-multiplexer-tutorial/)

### [Cheat Sheet](https://tmuxcheatsheet.com)
+ session
`tmux new -s {my_session}`: creat new session
`tmux ls`: show all sessions
`tmux a -t {my_session}`: attach to specific session
`Ctrl`+`b` `$`: rename when attach
`Ctrl`+`b` `d`: detach when attach
`Ctrl`+`b` `x` `y`: kill when attach

<a id='gdown'></a>
## 下載google drive檔案: gdown
+ Installation

pip install gdown

If install in venv, add the following path to `.bashrc` or `.zshrc`.

# Add venv as part of PATH
export PATH="$HOME/venv/bin:$PATH"

+ Download one file
`{file_ID}` can get from shared link in form `https://drive.google.com/file/d/{file_ID}/view?usp=drive_link`

gdown --id {file_id}

+ Download entire folder
`folder_share_link` form: `https://drive.google.com/drive/folders/{folder_ID}`

gdown --folder {folder_share_link}

<a id='py39'></a>
## 安裝python3.9

1. 更新系統安裝包

sudo apt update
sudo apt install software-properties-common

2. 安裝`deadsnakes` PPA

sudo add-apt-repository ppa:deadsnakes/ppa

3. 安裝Python3.9

sudo apt install python3.9

4. 如果出現`No module named 'distutils.util'`的錯誤，安裝對應版本的`distutils`(可能需要再運行`python3.9 get-pip.py`)

sudo apt install python3.{X}-distutils

#### Reference
+ [How to Install Python 3.9 on Ubuntu 22.04 using APT](https://linuxhint.com/install-python-ubuntu-22-04/)
+ [How to install pip for Python 3.9 on Ubuntu 20.04 - StackOverflow](https://stackoverflow.com/questions/65644782/how-to-install-pip-for-python-3-9-on-ubuntu-20-04)