一、CUDA安装

1. 查询CUDA driver版本：

 

 2. 下载并安装：

CUDA Toolkit Archive | NVIDIA DeveloperPrevious releases of the CUDA Toolkit, GPU Computing SDK, documentation and developer drivers can be found using the links below. Please select the release you want from the list below, and be sure to check www.nvidia.com/drivers for more recent production drivers appropriate for your hardware configuration.https://developer.nvidia.com/cuda-toolkit-archive

3. 在环境中查看CUDA的版本

nvcc -V

二、Pytorch安装

1. pytorch官网：

 PyTorch An open source machine learning framework that accelerates the path from research prototyping to production deployment.https://pytorch.org/

2. 选择安装方式：

三、本地化安装方式：

1. 清华镜像源

Index of /anaconda/cloud/pytorch/win-64/ | 清华大学开源软件镜像站 | Tsinghua Open Source MirrorIndex of /anaconda/cloud/pytorch/win-64/ | 清华大学开源软件镜像站，致力于为国内和校内用户提供高质量的开源软件镜像、Linux 镜像源服务，帮助用户更方便地获取开源软件。本镜像站由清华大学 TUNA 协会负责运行维护。https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/win-64/

2. 本地安装

 

三、安装后测试

(pytorch-gpu) C:\Users\u_name>python
>>>import torch
>>>torch.__version__
'2.0.1'
>>>torch.cuda.is_available()
True