Ubuntu 22.04LTS + 深度学习环境安装全流程

一、 CUDA Toolkit 安装

1. 选择需要安装的版本(下载地址)

2. 选择自己的系统版本获取下载地址和安装指令

3. 运行安装指令进行安装

wget https://developer.download.nvidia.com/compute/cuda/12.2.2/local_installers/cuda_12.2.2_535.104.05_linux.run
sudo sh cuda_12.2.2_535.104.05_linux.run
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选择安装选项:

这里安装显卡驱动比较麻烦，所以这一步按空格或者Enter键去掉安装显卡驱动的选项，然后选择install

安装正常:

配置环境变量:

vim ~/.bashrc

# 添加一行
export PATH=/usr/local/cuda-12.2/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-12.2/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

# 保存并加载环境变量
source ~/.bashrc
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验证安装是否成功:

root@service2:~# nvcc -V
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2023 NVIDIA Corporation
Built on Tue_Aug_15_22:02:13_PDT_2023
Cuda compilation tools, release 12.2, V12.2.140
Build cuda_12.2.r12.2/compiler.33191640_0

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4. 可能出现测错误

gcc未安装或版本不对:

报错 :

	cat /var/log/cuda-installer.log
	
	[INFO]: Driver not installed.
	[INFO]: Checking compiler version...
	[INFO]: gcc location: G 
	[ERROR]: Missing gcc. gcc is required to continue.
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解决方法 :

	# 确保 GCC 已经安装：
	gcc --version
	
	# 如果输出显示 GCC 版本信息，则说明已经安装。
	
	# 如果没有安装，请执行以下命令安装 GCC：
	sudo apt update
	sudo apt install gcc
	
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驱动不兼容

报错:

cat /var/log/nvidia-installer.log
ERROR: The Nouveau kernel driver is currently in use by your system.  This driver is incompatible with the NVIDIA driver, and must be disabled before proceeding.  Please consult the NVIDIA driver README and your Linux distribution's documentation for details on how to correctly disable the Nouveau kernel driver.
-> For some distributions, Nouveau can be disabled by adding a file in the modprobe configuration directory.  Would you like nvidia-installer to attempt to create this modprobe file for you? (Answer: Yes)
-> One or more modprobe configuration files to disable Nouveau have been written.  For some distributions, this may be sufficient to disable Nouveau; other distributions may require modification of the initial ramdisk.  Please reboot your system and attempt NVIDIA driver installation again.  Note if you later wish to re-enable Nouveau, you will need to delete these files: /usr/lib/modprobe.d/nvidia-installer-disable-nouveau.conf, /etc/modprobe.d/nvidia-installer-disable-nouveau.conf
ERROR: Installation has failed.  Please see the file '/var/log/nvidia-installer.log' for details.  You may find suggestions on fixing installation problems in the README available on the Linux driver download page at www.nvidia.com.
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解决方式

echo "blacklist nouveau" >> /lib/modprobe.d/dist-blacklist.conf
echo "options nouveau modeset=0" >> /lib/modprobe.d/dist-blacklist.conf
 
mv /boot/initramfs-$(uname -r).img /boot/initramfs-$(uname -r).img.bak
dracut /boot/initramfs-$(uname -r).img $(uname -r) 
systemctl set-default multi-user.target 
reboot

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1.2 显卡驱动安装(需要重启)

自动安装显卡驱动:

sudo ubuntu-drivers autoinstall

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检验驱动是否安装成功: nvidia-smi

如果有下面报错:

root@service5:/home/voke# sudo ubuntu-drivers autoinstall
Traceback (most recent call last):
  File "/usr/bin/ubuntu-drivers", line 513, in <module>
    greet()
  File "/usr/lib/python3/dist-packages/click/core.py", line 1128, in __call__
    return self.main(*args, **kwargs)
  File "/usr/lib/python3/dist-packages/click/core.py", line 1053, in main
    rv = self.invoke(ctx)
  File "/usr/lib/python3/dist-packages/click/core.py", line 1659, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/usr/lib/python3/dist-packages/click/core.py", line 1395, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/usr/lib/python3/dist-packages/click/core.py", line 754, in invoke
    return __callback(*args, **kwargs)
  File "/usr/lib/python3/dist-packages/click/decorators.py", line 84, in new_func
    return ctx.invoke(f, obj, *args, **kwargs)
  File "/usr/lib/python3/dist-packages/click/core.py", line 754, in invoke
    return __callback(*args, **kwargs)
  File "/usr/bin/ubuntu-drivers", line 432, in autoinstall
    command_install(config)
  File "/usr/bin/ubuntu-drivers", line 187, in command_install
    UbuntuDrivers.detect.nvidia_desktop_pre_installation_hook(to_install)
  File "/usr/lib/python3/dist-packages/UbuntuDrivers/detect.py", line 839, in nvidia_desktop_pre_installation_hook
    with_nvidia_kms = version >= 470
UnboundLocalError: local variable 'version' referenced before assignment
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查询可安装的驱动:

# 更新包管理
sudo apt update
sudo apt upgrade

# 更新 ubuntu-drivers 工具
sudo apt install --reinstall ubuntu-drivers-common

# 手动安装 NVIDIA 驱动
ubuntu-drivers list
sudo apt install 上面显示的驱动程序名称

# ***-server 服务器版本
# ****-open 开源版本

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二、安装 cuDNN

访问官网,获取下载地址(需要开发者账号)

下载并安装

# 登录并下载文件后,上传到服务器, 再进行安装
apt install ./cudnn-local-repo-ubuntu2204-8.9.3.28_1.0-1_amd64.deb
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三、安装Mincanda

mkdir -p ~/miniconda3
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3
rm -rf ~/miniconda3/miniconda.sh
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运行系统环境变量初始化命令:

~/miniconda3/bin/conda init bash
~/miniconda3/bin/conda init zsh
source ~/.bashrc
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3.1 更换清华源镜像

各系统都可以通过修改用户目录下的 .condarc 文件来使用 TUNA 镜像源

conda config --set show_channel_urls yes
vim ~/.condarc
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编辑入如下内容:

channels:
  - defaults
show_channel_urls: true
default_channels:
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r
  - https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2
custom_channels:
  conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  pytorch-lts: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud
  deepmodeling: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/
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运行 conda clean -i 清除索引缓存，保证用的是镜像站提供的索引。

3.2pip设置清华源

创建或编辑pip配置文件：

如果没有~/.pip目录，首先创建它：

mkdir -p ~/.pip
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接下来，创建或编辑~/.pip/pip.conf文件。您可以使用任何文本编辑器，比如nano或vim。

vim ~/.pip/pip.conf
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在编辑器中，将以下内容添加到pip.conf文件中，以将pip源设置为清华大学镜像：

[global]
index-url = https://pypi.tuna.tsinghua.edu.cn/simple
trusted-host = pypi.tuna.tsinghua.edu.cn
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验证更改：

pip config get global.index-url
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这将显示全局pip源的URL，应该显示清华源的URL。

四、安装PyTorch

选择系统版本获取下载命令

直接安装最新版即可

conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia

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出现如下内容表示成功

Preparing transaction: done                                              
Verifying transaction: done                                              
Executing transaction: done   
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验证安装是否成功:

执行 python

# 验证torch安装
import torch
print(torch.__version__)

#验证cuda安装
print(torch.cuda.is_available())
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