ubuntu20.04安装anaconda3及虚拟环境创建、配置
ubuntu20.04安装anaconda3及虚拟环境创建、配置
- 1 anaconda3下载
- 2 安装anaconda3
- 2 指定虚拟环境安装路径
- 3 创建虚拟环境
- 3 在虚拟环境中安装pytorch
1 anaconda3下载
点击‘anaconda download’,关于anaconda版本,下载界面会根据访问网页所属的系统确定用户需要的Anaconda版本,如果你需要指定版本的anaconda, 请点击下载链接:
‘anaconda different version download’
2 安装anaconda3
进入anaconda下载路径,执行命令如下:
sudo bash Anaconda3-2024.06-1-Linux-x86_64.sh -p /opt/anaconda3
其中,参数-p后面是anaconda安装的地址,可自定义,以上仅为示例地址。
执行结果如下:
work@Legion:~/Downloads/soft$ sudo bash Anaconda3-2024.06-1-Linux-x86_64.sh -p /opt/anaconda3/
Welcome to Anaconda3 2024.06-1
In order to continue the installation process, please review the license
agreement.
Please, press ENTER to continue
>>>
根据提示按下ENTER键继续,并阅读协议、条款(按空格键翻页),阅读完后,如下输入**yes*:
...
10. Definitions.
1. "Anaconda Distribution", shortened form "Distribution", is an open-source distribution of Python and R programming languages for scientific computing and data science. It aims to simplify package management and deployment. An
aconda Distribution includes: (1) conda, a package and environment manager for your command line interface; (2) Anaconda Navigator; (3) 250 automatically installed packages; (3) access to the Anaconda Public Repository.
2. "Anaconda Navigator" means a graphical interface for launching common Python programs without having to use command lines, to install packages and manage environments. It also allows the user to launch applications and easily
manage conda packages, environments, and channels without using command-line commands.
3. "Anaconda Public Repository", means the Anaconda packages repository of 8000 open-source data science and machine learning packages at repo.anaconda.com.
Version 4.0 | Last Modified: March 31, 2024 | ANACONDA TOS
Do you accept the license terms? [yes|no]
>>> yes
根据提示按下ENTER确认安装位置,如下
Anaconda3 will now be installed into this location:
/opt/anaconda3/
- Press ENTER to confirm the location
- Press CTRL-C to abort the installation
- Or specify a different location below
[/opt/anaconda3/] >>>
确认路径后,anaconda开始安装。
安装完成后,会提示是否需要更新、安装初始化的anaconda,输入yes,完成安装及初始化,如下:
PREFIX=/opt/anaconda3
Unpacking payload ...
Installing base environment...
Downloading and Extracting Packages:
Downloading and Extracting Packages:
Preparing transaction: done
Executing transaction: done
installation finished.
Do you wish to update your shell profile to automatically initialize conda?
This will activate conda on startup and change the command prompt when activated.
If you'd prefer that conda's base environment not be activated on startup,
run the following command when conda is activated:
conda config --set auto_activate_base false
You can undo this by running `conda init --reverse $SHELL`? [yes|no]
[no] >>> yes
no change /opt/anaconda3/condabin/conda
no change /opt/anaconda3/bin/conda
no change /opt/anaconda3/bin/conda-env
no change /opt/anaconda3/bin/activate
no change /opt/anaconda3/bin/deactivate
no change /opt/anaconda3/etc/profile.d/conda.sh
no change /opt/anaconda3/etc/fish/conf.d/conda.fish
no change /opt/anaconda3/shell/condabin/Conda.psm1
no change /opt/anaconda3/shell/condabin/conda-hook.ps1
no change /opt/anaconda3/lib/python3.12/site-packages/xontrib/conda.xsh
no change /opt/anaconda3/etc/profile.d/conda.csh
modified /root/.bashrc
==> For changes to take effect, close and re-open your current shell. <==
Thank you for installing Anaconda3!
添加anaconda环境变量,执行命令:
echo 'export PATH="/opt/anaconda3/bin:$PATH"' >> ~/.bashrc
source ~/.bashrc
查看anaconda版本,执行‘conda -V’命令,会输出版本号,如下:
work@Legion:~/Downloads/soft$ echo 'export PATH="/opt/anaconda3/bin:$PATH"' >> ~/.bashrc
work@Legion:~/Downloads/soft$ source ~/.bashrc
work@Legion:~/Downloads/soft$ conda -V
conda 24.5.0
或者,执行conda init,将会在./bashrc中生成conda的环境变量,如下:
work@Legion:~/Downloads/soft$ conda init
然后执行:
work@Legion:~/Downloads/soft$ source ~/.bashrc
work@Legion:~/Downloads/soft$ conda -V
conda 24.5.0
然后设置不自动激活base虚拟环境,执行如下命令
work@Legion:~/Downloads/soft$ conda config --set auto_activate_base false
激活、关闭基础虚拟环境,如下:
work@Legion:~/Downloads/soft$ conda activate base
(base) work@Legion:~/Downloads/soft$
(base) work@Legion:~/Downloads/soft$ conda deactivate
work@Legion:~/Downloads/soft$
此时,anaconda安装完成。
2 指定虚拟环境安装路径
查看当前虚拟环境(envs_dirs)及包(pkgs_dirs)的路径设置,如下:
work@Legion:~/Downloads/soft$ conda config --show
... 此前省略
dry_run: False
enable_private_envs: False
env_prompt: ({default_env})
envs_dirs:
- /home/work/.conda/envs
- /opt/anaconda3/envs
error_upload_url: https://conda.io/conda-post/unexpected-error
execute_threads: 1
experimental: []
extra_safety_checks: False
fetch_threads: 5
force: False
force_32bit: False
force_reinstall: False
force_remove: False
ignore_pinned: False
json: False
local_repodata_ttl: 1
migrated_channel_aliases: []
migrated_custom_channels: {}
no_lock: False
no_plugins: False
non_admin_enabled: True
notify_outdated_conda: True
number_channel_notices: 5
offline: False
override_channels_enabled: True
path_conflict: clobber
pinned_packages: []
pip_interop_enabled: False
pkgs_dirs:
- /opt/anaconda3/pkgs
- /home/work/.conda/pkgs
proxy_servers: {}
quiet: False
register_envs: True
...此后省略
编辑用户路径下condarc文件(与bashrc同路径),然后设置虚拟环境(envs_dirs)和包(pkgs_dirs)的路径,如下:
work@Legion:~/Downloads/soft$ vim ~/.condarc
auto_activate_base: false
show_channel_urls: true
envs_dirs:
- /opt/anaconda3/envs
pkgs_dirs:
- /opt/anaconda3/pkgs
修改完成后,保存关闭,并再次查看当前虚拟环境及包的路径,执行:
conda config --show
3 创建虚拟环境
创建一个自定义的虚拟环境,如下:
work@Legion:~$ conda create -n test_env -y python=3.8
Channels:
- defaults
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: done
## Package Plan ##
environment location: /opt/anaconda3/envs/test_env
added / updated specs:
- python=3.8
The following packages will be downloaded:
...
输出如下命令时,说明自定义虚拟环境创建成功。
Downloading and Extracting Packages:
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
#
# To activate this environment, use
#
# $ conda activate test_env
#
# To deactivate an active environment, use
#
# $ conda deactivate
3 在虚拟环境中安装pytorch
示例为安装基于cuda的pytorch,示例系统中,安装的cuda版本为11.3,执行如下命令安装:
(test_env) work@Legion:~$ conda install pytorch==1.10.0 torchvision==0.11.0 cudatoolkit=11.3
若安装时,提示当前通道没有可用的包,则在test_env环境中添加通道链接后,执行上面的命令,如下:
(test_env) work@Legion:~$ conda install pytorch==1.10.0 torchvision==0.11.0 cudatoolkit=11.3
Channels:
- defaults
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: failed
PackagesNotFoundError: The following packages are not available from current channels:
- torchvision==0.11.0
- pytorch==1.10.0
Current channels:
- defaults
To search for alternate channels that may provide the conda package you're
looking for, navigate to
https://anaconda.org
and use the search bar at the top of the page.
(test_env) work@Legion:~$ conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/
(test_env) work@Legion:~$ conda install pytorch==1.10.0 torchvision==0.11.0 cudatoolkit=11.3
此时,将会顺利进入pytorch的安装流程,下载需要的库文件,下载完成后,提示是否继续执行安装操作,输入y,如下:
The following NEW packages will be INSTALLED:
cudatoolkit pkgs/main/linux-64::cudatoolkit-11.3.1-h2bc3f7f_2
ffmpeg anaconda/cloud/pytorch/linux-64::ffmpeg-4.3-hf484d3e_0
freetype pkgs/main/linux-64::freetype-2.12.1-h4a9f257_0
gmp pkgs/main/linux-64::gmp-6.2.1-h295c915_3
gnutls pkgs/main/linux-64::gnutls-3.6.15-he1e5248_0
jpeg pkgs/main/linux-64::jpeg-9e-h5eee18b_3
lame pkgs/main/linux-64::lame-3.100-h7b6447c_0
lcms2 pkgs/main/linux-64::lcms2-2.12-h3be6417_0
lerc pkgs/main/linux-64::lerc-3.0-h295c915_0
libdeflate pkgs/main/linux-64::libdeflate-1.17-h5eee18b_1
libiconv pkgs/main/linux-64::libiconv-1.16-h5eee18b_3
libidn2 pkgs/main/linux-64::libidn2-2.3.4-h5eee18b_0
libpng pkgs/main/linux-64::libpng-1.6.39-h5eee18b_0
libtasn1 pkgs/main/linux-64::libtasn1-4.19.0-h5eee18b_0
libtiff pkgs/main/linux-64::libtiff-4.5.1-h6a678d5_0
libunistring pkgs/main/linux-64::libunistring-0.9.10-h27cfd23_0
libuv pkgs/main/linux-64::libuv-1.48.0-h5eee18b_0
libwebp-base pkgs/main/linux-64::libwebp-base-1.3.2-h5eee18b_1
nettle pkgs/main/linux-64::nettle-3.7.3-hbbd107a_1
openh264 pkgs/main/linux-64::openh264-2.1.1-h4ff587b_0
openjpeg pkgs/main/linux-64::openjpeg-2.5.2-he7f1fd0_0
pillow pkgs/main/linux-64::pillow-10.4.0-py38h5eee18b_0
pytorch anaconda/cloud/pytorch/linux-64::pytorch-1.10.0-py3.8_cuda11.3_cudnn8.2.0_0
pytorch-mutex anaconda/cloud/pytorch/noarch::pytorch-mutex-1.0-cuda
torchvision anaconda/cloud/pytorch/linux-64::torchvision-0.11.0-py38_cu113
Proceed ([y]/n)? y
输入下面所示内容时,表示pytorch安装完成。
Downloading and Extracting Packages:
Preparing transaction: done
Verifying transaction: done
Executing transaction: | By downloading and using the CUDA Toolkit conda packages, you accept the terms and conditions of the CUDA End User License Agreement (EULA): https://docs.nvidia.com/cuda/eula/index.html
done