一、conda安装
1.1 什么是conda？
试想要在一台机器上运行多个python程序，但是这些python程序对包的版本以来，A应用需要python2.7.0和numpy1.23.0，B应用需要python3.10.0和numpy2.2.6，如果应用越来越多，这些包的管理会越来越复杂。
为了解决python包管理问题，conda孕育而生，旨在解决安装多个版本的软件包及其依赖关系，并在它们之间轻松切换。conda是为python程序创建的，适用于Linux，Mac和Windows。
1.2 anaconda和miniconda
anaconda和miniconda中都包含conda，但是两者有如下区别：
anaconda：预装了超过1500个科学计算和数据分析相关的软件包，包括NumPy、SciPy、Pandas、Matplotlib、Seaborn、Scikit-learn、TensorFlow（CPU版）等。它还内置了 Jupyter Notebook 、 Spyder IDE 等工具，适合数据科学初学者和需要快速开始项目的用户。
miniconda：仅包含最基础的组件，如Python解释器、Conda包管理器、Pip工具和一些基础依赖。它不包含Anaconda的预装软件包，用户需要根据需要自行安装所需的包，适合高级Python开发者、需要严格控制环境依赖的用户以及磁盘空间有限的用户。
对一般人来说，安装miniconda即可。
1.3 下载conda
打开conda官网https://docs.conda.io/en/latest/找到Install：
可以选择对应的命令安装conda（例如Mac下执行brew install miniconda），也可以选择下载安装脚本的方式安装。我本地环境是如下的WSL+ubuntu22.04，选择了安装脚本的方式，因此下载Linux x86_64(amd64)这个包：
$ uname -a
Linux DESKTOP-72RD6OV 6.6.87.2-microsoft-standard-WSL2 #1 SMP PREEMPT_DYNAMIC Thu Jun 5 18:30:46 UTC 2025 x86_64 x86_64 x86_64 GNU/Linux
$ arch
x86_64
1.4 安装conda
把下载好的安装脚本（我这里是Miniconda3-latest-Linux-x86_64.sh）放到对应的目录下，执行./Miniconda3-latest-Linux-x86_64.sh命令进行安装（如果文件没有可执行权限，可能还需要chmod +x Miniconda3-latest-Linux-x86_64.sh命令配置可执行权限）。安装的时候会有一些确认步骤，还有一步让选择安装目录，安装目录可自由配置，其余选项默认即可。
$ ls -al
total 155752
drwxr-xr-x 2 nuczzz nuczzz 4096 Jun 29 09:51 .
drwxr-x--- 16 nuczzz nuczzz 4096 Jun 29 09:51 ..
-rwxrwxrwx 1 nuczzz nuczzz 159476510 Jun 28 21:49 Miniconda3-latest-Linux-x86_64.sh
$ ./Miniconda3-latest-Linux-x86_64.sh
Welcome to Miniconda3 py313_25.5.1-0
In order to continue the installation process, please review the license
agreement.
Please, press ENTER to continue
>>>
MINICONDA END USER LICENSE AGREEMENT
Copyright Notice: Miniconda(R) (C) 2015, Anaconda, Inc.
All rights reserved. Miniconda(R) is licensed, not sold.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer;
2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution;
3. The name Anaconda, Inc. or Miniconda(R) may not be used to endorse or promote products derived from this software without specific prior written permission from Anaconda, Inc.; and
4. Miniconda(R) may not be used to access or allow third parties to access Anaconda package repositories if such use would circumvent paid licensing requirements or is otherwise restricted by the Anaconda Terms of Service.
DISCLAIMER: THIS SOFTWARE IS PROVIDED BY ANACONDA "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE , AND NON-INFRINGEMENT ARE DISCLAIMED. IN NO EVENT SHALL ANACONDA BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTR
ACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF MINICONDA(R), EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Do you accept the license terms? [yes|no]
>>> yes
Miniconda3 will now be installed into this location:
/home/nuczzz/miniconda3
- Press ENTER to confirm the location
- Press CTRL-C to abort the installation
- Or specify a different location below
[/home/nuczzz/miniconda3] >>>
PREFIX=/home/nuczzz/miniconda3
Unpacking payload ...
...
...
...
You can undo this by running `conda init --reverse $SHELL`? [yes|no]
[no] >>> yes
no change /home/nuczzz/miniconda3/condabin/conda
no change /home/nuczzz/miniconda3/bin/conda
no change /home/nuczzz/miniconda3/bin/conda-env
no change /home/nuczzz/miniconda3/bin/activate
no change /home/nuczzz/miniconda3/bin/deactivate
no change /home/nuczzz/miniconda3/etc/profile.d/conda.sh
no change /home/nuczzz/miniconda3/etc/fish/conf.d/conda.fish
no change /home/nuczzz/miniconda3/shell/condabin/Conda.psm1
no change /home/nuczzz/miniconda3/shell/condabin/conda-hook.ps1
no change /home/nuczzz/miniconda3/lib/python3.13/site-packages/xontrib/conda.xsh
no change /home/nuczzz/miniconda3/etc/profile.d/conda.csh
modified /home/nuczzz/.bashrc
==> For changes to take effect, close and re-open your current shell. <==
Thank you for installing Miniconda3!
这个时候如果执行conda命令还会报如下错误，因为conda可执行文件不在系统默认目录下：
$ conda --version
conda: command not found
1.5 配置conda bin目录到PATH环境变量
我上述步骤安装目录是默认的/home/$user/miniconda3，也就是/home/nuczzz/miniconda3，对应的可执行文件在/home/nuczzz/miniconda3/bin目录下。为了方便后续执行conda命令，需要把该目录配置到PATH环境变量中，这里选择在/etc/profile中配置。/etc/profile文件末尾增加一行：
export PATH=$PATH:/home/nuczzz/miniconda3/bin
再source以下让配置立即生效，并验证conda命令是否能执行：
$ source /etc/profile
$ conda --version
conda 25.5.1
$ conda env list
# conda environments:
#
base * /home/nuczzz/miniconda3
二、创建pytorch环境
安装好conda后，用conda创建一个独立的环境来安装pytorch。当前pytorch对python版本建议是3.19~3.12:
Python 3.9-3.12 is generally installed by default on any of our supported Linux distributions, which meets our recommendation
我们基于python 3.12并执行conda create -n pytorch python=3.12命令来创建一个环境：
$ conda create -n pytorch python=3.12
Channels:
- defaults
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: done
## Package Plan ##
environment location: /home/nuczzz/miniconda3/envs/pytorch
added / updated specs:
- python=3.12
...
...
...
查看创建的环境：
$ conda env list
# conda environments:
#
base * /home/nuczzz/miniconda3
pytorch /home/nuczzz/miniconda3/envs/pytorch
$ conda activate pytorch
(pytorch)$ python --version
Python 3.12.11
三、pytorch安装
打开pytorch官网https://pytorch.org/get-started/locally/，根据自己得到环境选择对应的选项。由于我本地有一张nvidia RTX4060Ti的GPU卡，且之前安装好了cuda，并且有如下版本：
(pytorch) nuczzz@DESKTOP-72RD6OV:~$ nvidia-smi --version
NVIDIA-SMI version : 560.35.02
NVML version : 560.35
DRIVER version : 560.94
CUDA Version : 12.6
因此我的选择如下：
得到安装命令pip3 install torch torchvision torchaudio，执行该命令安装pytorch。安装可能需要下载几个G的内容，需要等待一段时间：
(pytorch) nuczzz@DESKTOP-72RD6OV:~$ pip3 install torch torchvision torchaudio
Collecting torch
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Collecting torchvision
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Collecting torchaudio
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Collecting typing-extensions>=4.10.0 (from torch)
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Requirement already satisfied: setuptools in ./miniconda3/envs/pytorch/lib/python3.12/site-packages (from torch) (78.1.1)
Collecting sympy>=1.13.3 (from torch)
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Collecting nvidia-nvjitlink-cu12==12.6.85 (from torch)
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Collecting triton==3.3.1 (from torch)
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Collecting numpy (from torchvision)
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Installing collected packages: nvidia-cusparselt-cu12, mpmath, typing-extensions, triton, sympy, pillow, nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufile-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, numpy, networkx, MarkupSafe, fsspec, filelock, nvidia-cusparse-cu12, nvidia-cufft-cu12, nvidia-cudnn-cu12, jinja2, nvidia-cusolver-cu12, torch, torchvision, torchaudio
Successfully installed MarkupSafe-3.0.2 filelock-3.18.0 fsspec-2025.5.1 jinja2-3.1.6 mpmath-1.3.0 networkx-3.5 numpy-2.3.1 nvidia-cublas-cu12-12.6.4.1 nvidia-cuda-cupti-cu12-12.6.80 nvidia-cuda-nvrtc-cu12-12.6.77 nvidia-cuda-runtime-cu12-12.6.77 nvidia-cudnn-cu12-9.5.1.17 nvidia-cufft-cu12-11.3.0.4 nvidia-cufile-cu12-1.11.1.6 nvidia-curand-cu12-10.3.7.77 nvidia-cusolver-cu12-11.7.1.2 nvidia-cusparse-cu12-12.5.4.2 nvidia-cusparselt-cu12-0.6.3 nvidia-nccl-cu12-2.26.2 nvidia-nvjitlink-cu12-12.6.85 nvidia-nvtx-cu12-12.6.77 pillow-11.2.1 sympy-1.14.0 torch-2.7.1 torchaudio-2.7.1 torchvision-0.22.1 triton-3.3.1 typing-extensions-4.14.0
验证pytorch是否安装成功：
(pytorch) nuczzz@DESKTOP-72RD6OV:~$ python
Python 3.12.11 | packaged by Anaconda, Inc. | (main, Jun 5 2025, 13:09:17) [GCC 11.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>>
验证pytorch是否可以调用GPU（基于pytorch的计算并非一定要有GPU才能运行，只是GPU在某些场景可以加速计算过程）：
(pytorch) nuczzz@DESKTOP-72RD6OV:~$ python
Python 3.12.11 | packaged by Anaconda, Inc. | (main, Jun 5 2025, 13:09:17) [GCC 11.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
True
>>>