https://forums.developer.nvidia.com/t/pytorch-for-jetson/72048


一、先重新装 jetpack

【Jetson Agx Orin】执行sudo apt install nvidia-jetpack命令时报错：E: Unable to locate package nvidia-jetpack

二、查看是否有/usr/local/cuda-11.4

jetson nano 查看 CUDA 版本：nvcc -V 报错：bash: nvcc: 未找到命令

此时切换到 ~ 目录下： cd ~ ；
然后打开 .bashrc 文件：vim .bashrc ；
接着按 i 键，进入编辑状态；
再接着在文件的末尾添加下面三行代码：

export PATH=/usr/local/cuda-11.4/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-11.4/lib64:$LD_LIBRARY_PATH
export CUDA_ROOT=/usr/local/cuda-11.4

紧接着，按 Esc 键，然后输入冒号 ，再按下 wq! （表示强制写入并退出）！

最后一步，也是容易忘记的一步，一定要 source 一下这个文件：

source .bashrc

上面的一切都操作OK后，再次输入 nvcc ，就可以看到系统中 CUDA 的版本信息了：

三、安装torch 1.13.0 GPU版本和torchvision

安装pytorch
jetson orin上的pytorch版本下载地址
https://forums.developer.nvidia.com/t/pytorch-for-jetson/72048

orin上安装cuda pytorch gpu运行环境_v8

sudo apt-get install python3-pip libopenblas-base libopenmpi-dev libomp-dev
pip3 install Cython
pip3 install numpy torch-1.13.0-cp38-cp38-linux_aarch64.whl

b.安装torchvison

torchvision下载网址：
https://github.com/pytorch/vision

选择main–>Tags 1.14.0 下载并解压。

cd torchvision
export BUILD_VERSION=0.14.0  
python3 setup.py install --user
cd ../  
pip install 'pillow<7'

查看版本

python
import torch
import torchvision
torch.__version__
torchvision.__version__

orin上安装cuda pytorch gpu运行环境_pytorch_02

可能遇到的错误

RuntimeError: Couldn’t load custom C++ ops. This can happen if your PyTorch and torchvision versions are incompatible

报错具体信息如下

jk@jk-desktop:~/Desktop/work/python_project/yolov8_tracking$ python examples/track.py --source /home/jk/Desktop/work/python_project/yolov8_tracking/test_1.mp4 --tracking-method deepocsort --yolo-model /home/jk/Desktop/work/python_project/yolov8_tracking/yolov8/ultralytics/weights/yolov8s.pt
/home/jk/.local/lib/python3.8/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension:
  warn(f"Failed to load image Python extension: {e}")
track: yolo_model=/home/jk/Desktop/work/python_project/yolov8_tracking/yolov8/ultralytics/weights/yolov8s.pt, reid_model=/home/jk/Desktop/work/python_project/yolov8_tracking/examples/weights/lmbn_n_cuhk03_d.pt, tracking_method=deepocsort, source=/home/jk/Desktop/work/python_project/yolov8_tracking/test_1.mp4, imgsz=[640], conf=0.5, device=, show=False, save=False, classes=None, project=/home/jk/Desktop/work/python_project/yolov8_tracking/runs/track, name=exp, exist_ok=False, half=False, vid_stride=1, hide_label=False, hide_conf=False, save_txt=False
/home/jk/.local/lib/python3.8/site-packages/examples/weights
/home/jk/.local/lib/python3.8/site-packages/examples
add by xxx = osnet_x1_0_imagenet.pth
add by xxxx cached_file= /home/jk/.cache/torch/checkpoints/osnet_x1_0_imagenet.pth
Successfully loaded imagenet pretrained weights from "/home/jk/.cache/torch/checkpoints/osnet_x1_0_imagenet.pth"
Traceback (most recent call last):
  File "examples/track.py", line 246, in <module>
    main(opt)
  File "examples/track.py", line 241, in main
    run(vars(opt))
  File "/home/jk/.local/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "examples/track.py", line 114, in run
    predictor.results = predictor.postprocess(preds, im, im0s)
  File "/home/jk/.local/lib/python3.8/site-packages/ultralytics/yolo/v8/detect/predict.py", line 14, in postprocess
    preds = ops.non_max_suppression(preds,
  File "/home/jk/.local/lib/python3.8/site-packages/ultralytics/yolo/utils/ops.py", line 246, in non_max_suppression
    i = torchvision.ops.nms(boxes, scores, iou_thres)  # NMS
  File "/home/jk/.local/lib/python3.8/site-packages/torchvision/ops/boxes.py", line 40, in nms
    _assert_has_ops()
  File "/home/jk/.local/lib/python3.8/site-packages/torchvision/extension.py", line 48, in _assert_has_ops
    raise RuntimeError(
RuntimeError: Couldn't load custom C++ ops. This can happen if your PyTorch and torchvision versions are incompatible, or if you had errors while compiling torchvision from source. For further information on the compatible versions, check https://github.com/pytorch/vision#installation for the compatibility matrix. Please check your PyTorch version with torch.__version__ and your torchvision version with torchvision.__version__ and verify if they are compatible, and if not please reinstall torchvision so that it matches your PyTorch install.

PyTorch and torchvision 版本不匹配

orin上安装cuda pytorch gpu运行环境_python_03


但是我打印出来，版本没有问题

orin上安装cuda pytorch gpu运行环境_pytorch_02

最终卸载重装了一下，

pip uninstall torch 
pip uninstall torchvision
pip uninstall torchaudio

多卸载几次

pip uninstall torch 
pip uninstall torchvision
pip uninstall torchaudio

其实卸载的过程中，我发现torchvision有多个版本，很可能是这个原因造成的。

然后按照步骤3重新来一次（重新安装很快）

运行成功。


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