Jetson4.6 安装pytorch1.8.0 cuda10.2

在Jetson 4.6上安装PyTorch 1.8.0和CUDA 10.2可以按照以下步骤进行：

1. 安装依赖项：在终端中运行以下命令来安装必要的依赖项：

   sudo apt-get update
   sudo apt-get install -y build-essential python3-pip python3-dev python3-setuptools libavcodec-dev libavformat-dev libswscale-dev libv4l-dev libxvidcore-dev libx264-dev libjpeg-dev libpng-dev libtiff-dev libgtk-3-dev libcanberra-gtk* libatlas-base-dev gfortran libhdf5-serial-dev protobuf-compiler libprotobuf-dev openssl libssl-dev libffi-dev libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libdc1394-22-dev libopenexr-dev libeigen3-dev libtbb-dev libvtk6-dev zlib1g-dev liblapack-dev liblapacke-dev libopenblas-dev libopenblas-base libatlas-base-dev liblapack3 liblapack-dev liblapacke liblapacke-dev liblapack-pic python3-numpy python3-scipy python3-matplotlib python3-sklearn python3-skimage python3-h5py python3-yaml python3-pyqt5 libgstreamer1.0-0 libgstreamer-plugins-base1.0-0

2. 下载JetPack 4.6的CUDA工具包：从NVIDIA Jetson下载页面下载适合你的Jetson版本的CUDA工具包。

3. 安装CUDA工具包：在终端中进入下载目录，运行以下命令来安装CUDA：

   sudo dpkg -i cuda-repo-l4t-10-2-local-10.2.89_1.0-1_arm64.deb
   sudo apt-key add /var/cuda-repo-10-2-local-10.2.89/7fa2af80.pub
   sudo apt-get update
   sudo apt-get install cuda-toolkit-10-2

4. 安装PyTorch：在终端中运行以下命令来安装PyTorch：

   sudo apt-get install python3-pip libopenblas-base libopenmpi-dev
   sudo pip3 install Cython
   sudo pip3 install numpy torch-1.8.0+cu102 torchvision-0.9.0+cu102 -f https://download.pytorch.org/whl/cu102/torch_stable.html

5. 验证安装：在终端中运行以下命令来验证PyTorch和CUDA是否成功安装：

   python3
   import torch
   print(torch.__version__)
   print(torch.cuda.is_available())

如果你看到了PyTorch的版本信息以及True（即CUDA可用），说明安装成功。

注意：以上步骤仅适用于Jetson 4.6和PyTorch 1.8.0和CUDA 10.2，如果你的系统或版本不同，请查看相应的安装方法。