参考资料
Windows 下安装 CUDA 和 Pytorch 跑深度学习 - 动手学深度学习v2
CUDA环境安装
- 下载CUDA
电脑需配置NVIDIA显卡
CUDA Toolkit 12.4 Update 1 Downloads
- 测试
Microsoft Windows [版本 10.0.19045.4170]
(c) Microsoft Corporation。保留所有权利。
C:\Users\JIA>nvidia-smi
Sat Apr 6 10:26:55 2024
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 552.12 Driver Version: 552.12 CUDA Version: 12.4 |
|-----------------------------------------+------------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA GeForce RTX 3070 Ti WDDM | 00000000:01:00.0 On | N/A |
| 0% 43C P8 21W / 290W | 1121MiB / 8192MiB | 8% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
C:\Users\JIA>
python环境安装
- miniconda
不要安装最新版本，安装历史版本python3.8版本
https://docs.anaconda.com/free/miniconda/miniconda-other-installer-links/
Miniconda3-py38_23.10.0-1-Windows-x86_64.exe 71.6M 2023-11-16 13:51:53 126cda8fd680553cf13b79b0fc4f23f089f11ba03d3fc9c1927ae8af0c5bed3a
Miniconda3-py38_23.10.0-1-MacOSX-x86_64.sh 82.3M 2023-11-16 13:51:53 0e6921f44b4278aa178969f59da57ca4ced2a55ef7730c774296f1de1801c561
Miniconda3-py38_23.10.0-1-MacOSX-x86_64.pkg 81.9M 2023-11-16 13:51:53 d76c4f3347906d5d7027bb82d4bfd7e3996dbfdca87ea3f7493dc183cc6fa458
Miniconda3-py38_23.10.0-1-MacOSX-arm64.sh 80.1M 2023-11-16 13:51:53 c5ece9fce0a2f3c68600476e4256146f03511f82f76d05324eedbdc9eb06bed7
Miniconda3-py38_23.10.0-1-MacOSX-arm64.pkg 79.7M 2023-11-16 13:51:53 20d8610d667088fe0692de2341ce04159b327579a799bcbf9789d0f3824b3309
Miniconda3-py38_23.10.0-1-Linux-x86_64.sh 106.1M 2023-11-16 13:51:53 6842afb93a64fd4f04daa0f49f4618857d2327ead1366851eb0e49f1ae460f00
Miniconda3-py38_23.10.0-1-Linux-s390x.sh 101.9M 2023-11-16 13:51:53 095bfb828b3155e6a345b7e821010451dfd291e8373b618a3b72a050a1c7a909
Miniconda3-py38_23.10.0-1-Linux-ppc64le.sh 91.7M 2023-11-16 13:51:53 1d7ccb2fa31042116b38ec518a63428d9cf87adba8771ffa9f0e3241f6b5a72a
Miniconda3-py38_23.10.0-1-Linux-aarch64.sh 89.8M 2023-11-16 13:51:53 aee297bdefb15cfee9e2cb4c0881f811ce18c1a066ac75b811b21967ccd41acd
- 测试
运行 Anaconda Powershell Prompt (miniconda3)
(base) PS C:\Users\JIA> python --version
Python 3.8.18
pytorch安装
- pytorch
https://pytorch.org/get-started/locally/
- 验证
(base) PS C:\Users\JIA> python
Python 3.8.18 (default, Sep 11 2023, 13:39:12) [MSC v.1916 64 bit (AMD64)] :: Anaconda, Inc. on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> a=torch.ones((3,1))
>>> a=a.cuda(0)
>>> b=torch.ones((3,1)).cuda(0)
>>> a+b
tensor([[2.],
[2.],
[2.]], device='cuda:0')
>>>
深度案例测试
- 安装jupyter d2l
pip install jupyter d2l
- 下载案例
http://localhost:8888/notebooks/pytorch/chapter_convolutional-modern/resnet.ipynb
- 启动安装jupyter
jupyter notebook
