Debian11.1.0安装人工智能深度学习环境（显卡驱动、cuda、cudnn、pytorch）-炼丹人士必看

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#给普通用户sudo权限
su
apt-get install -y vim
vim /etc/sudoers
quan    ALL=(ALL:ALL) ALL

#更改国内源
sudo vim /etc/apt/sources.list
deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bullseye main contrib non-free
# deb-src https://mirrors.tuna.tsinghua.edu.cn/debian/ bullseye main contrib non-free
deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bullseye-updates main contrib non-free
# deb-src https://mirrors.tuna.tsinghua.edu.cn/debian/ bullseye-updates main contrib non-free

deb https://mirrors.tuna.tsinghua.edu.cn/debian/ bullseye-backports main contrib non-free
# deb-src https://mirrors.tuna.tsinghua.edu.cn/debian/ bullseye-backports main contrib non-free

deb https://mirrors.tuna.tsinghua.edu.cn/debian-security bullseye-security main contrib non-free
# deb-src https://mirrors.tuna.tsinghua.edu.cn/debian-security bullseye-security main contrib non-free

#安装pip
sudo apt-get clean
sudo apt-get update
sudo apt-get upgrade -y
sudo apt-get install python3-pip

#安装中文输入法
sudo apt-get install -y fcitx fcitx5 fcitx-ui-classic fcitx-frontend-gtk* fcitx-frontend-qt* fcitx-table* fcitx-m17n fcitx5-chinese-addons fcitx5-rime fcitx5-frontend-gtk2 fcitx5-frontend-gtk3 fcitx5-config-qt fcitx5-module*

#换pip3源
sudo mkdir ~/.pip && sudo vim ~/.pip/pip.conf
[global]
timeout = 6000
index-url = https://pypi.tuna.tsinghua.edu.cn/simple
[install]
trusted-host = https://pypi.tuna.tsinghua.edu.cn

#卸载自带nVidia驱动（实际上并没有自带驱动）
sudo apt purge nvidia*

#禁用nouveau驱动
sudo vim /etc/modprobe.d/blacklist.conf
blacklist nouveau
options nouveau modeset=0
sudo update-initramfs -u

#重启并从ssh进去
sudo init 6
sudo /etc/init.d/lightdm stop
sudo apt-get install linux-headers-$(uname -r)

#查看nouveau驱动是否禁用
lsmod | grep nouveau

#安装cuda（含显卡驱动），我安装的最新版本，各位可访问官网来查找最新版本号
wget https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.19.01_linux.run
sudo sh cuda_11.3.1_465.19.01_linux.run
accept
选择Install

#配置环境变量
sudo vim ~/.bashrc
export PATH=/usr/local/cuda-11.3/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-11.3/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
source ~/.bashrc

#验证nVidia驱动
nvidia-smi

#验证cuda
nvcc -V

#安装cudnn,在官网下载
sudo tar zxvf cudnn-11.3-linux-x64-v8.2.1.32.tgz -C ./
sudo cp cuda/include/cudnn* /usr/local/cuda/include && sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/
sudo chmod a+r /usr/local/cuda/include/cudnn* /usr/local/cuda/lib64/libcudnn*
sudo dpkg -i libcudnn8_8.2.1.32-1+cuda11.3_amd64.deb
sudo dpkg -i libcudnn8-dev_8.2.1.32-1+cuda11.3_amd64.deb
sudo dpkg -i libcudnn8-samples_8.2.1.32-1+cuda11.3_amd64.deb
sudo init 6

#验证cudnn
cd /usr/local/cuda/samples/1_Utilities/deviceQuery
sudo make
./deviceQuery
出现Result = PASS成功

#安装pytorch
pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html


#验证pytorch
python3
import torch
import torchvision
print(torch.cuda.is_available())