【B站保姆级视频教程：Jetson配置YOLOv11环境（六）PyTorchTorchvision安装】
Jetson配置YOLOv11环境（6）PyTorch&Torchvision安装
文章目录
- 1. 安装PyTorch
- 1.1安装依赖项
- 1.2 下载torch wheel 安装包
- 1.3 安装
- 2. 安装torchvisiion
- 2.1 安装依赖
- 2.2 编译安装torchvision
- 2.2.1 Torchvisiion版本选择
- 2.2.2 下载torchvisiion到Downloads目录下
- 2.2.3 编译安装torchvision
- 2.3 安装过程可能出现的bug
- 3. 验证
1. 安装PyTorch
1.1安装依赖项
sudo apt install libopenblas-dev
libopenblas-dev作用：提供优化的BLAS（Basic Linear Algebra Subprograms）库，用于高效执行线性代数运算。
影响：PyTorch依赖于高效的线性代数运算来加速深度学习模型的训练和推理。libopenblas-dev提供了优化的BLAS实现，可以显著提升PyTorch的性能，尤其是在CPU上运行时。
1.2 下载torch wheel 安装包
前往PyTorch for Jetson，下载所安装的jetpack版本支持的最高版本的torch wheel 安装包到Downloads目录下。
cd /Downloads
wget https://developer.download.nvidia.cn/compute/redist/jp/v512/pytorch/torch-2.1.0a0+41361538.nv23.06-cp38-cp38-linux_aarch64.whl
例如：jetpack5.1.x对应下图中红框的torch安装包，需注意Python 版本为 3.8。
1.3 安装
pip install torch-2.1.0a0+41361538.nv23.06-cp38-cp38-linux_aarch64.whl
2. 安装torchvisiion
2.1 安装依赖
pip install numpy requests Pillow
sudo apt install libjpeg-dev libpng-dev zlib1g-dev libpython3-dev libavcodec-dev libavformat-dev libswscale-dev
2.2 编译安装torchvision
torchvision暂未发布直接能pip安装的whl版本，因此直接从源码编译。
2.2.1 Torchvisiion版本选择
以torch2.1.0为例，对应的torchvisiion版本为0.16.x。
torch与torchvision版本对应关系
torch | torchvision | Python |
|---|---|---|
main / nightly | main / nightly | >=3.9, <=3.12 |
2.5 | 0.20 | >=3.9, <=3.12 |
2.4 | 0.19 | >=3.8, <=3.12 |
2.3 | 0.18 | >=3.8, <=3.12 |
2.2 | 0.17 | >=3.8, <=3.11 |
2.1 | 0.16 | >=3.8, <=3.11 |
2.0 | 0.15 | >=3.8, <=3.11 |
2.2.2 下载torchvisiion到Downloads目录下
（1）网络ok的话，直接克隆到本地。
cd ./Downloads
git clone --branch v0.16.2 https://github.com/pytorch/vision
（2）网络不行clone慢的话，直接下载压缩包到PC
再上传jetson，解压即可
unzip vision-0.16.2.zip
2.2.3 编译安装torchvision
cd vision-0.16.2 # 进入torchvision目录
export BUILD_VERSION=0.16.2 # 将BUILD_VERSION环境变量设置为值 0.16.2
python3 setup.py install --user # 使用 Python 的 setuptools 工具将vision包安装到当前用户的本地目录中
需要等待30min左右，出现以下提示则安装成功
安装成功后退出torchvision的安装目录再import torchvision进行验证，否则会出现以下warning
(pytorch) nx@nx-desktop:~/Downloads/vision-0.15.2$ python
Python 3.8.18 (default, Sep 11 2023, 13:19:25)
[GCC 11.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torchvision
/home/nx/Downloads/vision-0.15.2/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: ''If you don't plan on using image functionality from `torchvision.io`, you can ignore this warning. Otherwise, there might be something wrong with your environment. Did you have `libjpeg` or `libpng` installed before building `torchvision` from source?
warn(
/home/nx/Downloads/vision-0.15.2/torchvision/__init__.py:25: UserWarning: You are importing torchvision within its own root folder (/home/nx/Downloads/vision-0.15.2). This is not expected to work and may give errors. Please exit the torchvision project source and relaunch your python interpreter.
warnings.warn(message.format(os.getcwd()))
2.3 安装过程可能出现的bug
若出现error: [Errno 2] No such file or directory: ':/usr/local/cuda/bin/nvcc'，请参照：
jetson编译torchvision出现 No such file or directory: ‘:/usr/local/cuda/bin/nvcc‘
3. 验证
查看pytorch运行时真正调用的cuda、cudnn版本：
python -c "import torch; import torchvision; print('PyTorch version:', torch.__version__); print('CUDA available:', torch.cuda.is_available()); print('CUDA version:', torch.version.cuda); print('cuDNN enabled:', torch.backends.cudnn.enabled); print('cuDNN version:', torch.backends.cudnn.version()); print('Torchvision version:', torchvision.__version__)"
