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## $PyTorch$ 安装
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### 1、查看本机的$CUDA$版本
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cmd命令行输入`nvidia-smi`，在第一行最右边可以看到CUDA的版本号，我的版本是12.4
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### 2、安装Pytroch
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(1)、官网：https://pytorch.org/
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然后选择Get Started，就是如下界面
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(2)、这里进行$Pytorch$版本的选择，首先我选择的是$Stable$稳定版，然后$OS$是$Windows$系统，$Package$包就使用$Conda$，$Language$肯定选$Python$，最后的$Compute$ $Platform$ 选择 $CUDA12.1$。
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> ```shell
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> conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
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> ```
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3、安装下$Anaconda$并创建一个$Python$环境,安装的是$python3.9$。
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```
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conda activate py39
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```
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4、关闭掉$VPN$，然后执行：
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```shell
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# 解决一些环境变量问题
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G:
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cd G:\anaconda3
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copy Library\bin\libcrypto-1_1-x64.dll DLLs\.
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copy Library\bin\libssl-1_1-x64.dll DLLs\.
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#开始安装
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conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch -c nvidia
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```
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> **注：如果环境变量不对了，需要重置一下环境：**
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```console
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conda config --remove-key channels
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```
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5、可以看到将要安装的包里面有$pytorch$和$cudatoolkit$，输入$y$确认，然后回车
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6、下面就等待这些$package$安装成功，可以看到$Pytorch$还是比较大的，所以耐心等待一下。如果下载过程中卡住的同学，直接到[torch镜像源](https://download.pytorch.org/whl/torch_stable.html)下载安装包进行安装，效果相同。
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7、安装完成后，会提示信息$done$。
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8、输入$pip$ $list$，查看我们的包是否被安装，这里可以看到$torch$相关的包都安装了。
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9、我们输入`python`进入下 $Python$ 环境，然后输入`
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```python
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import torch
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```
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如果没有报错说明可以导入成功。
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10、输入
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```py
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torch.cuda.is_available()
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```
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查看$torch$是否可以使用显卡，$True$就代表可以！
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