sudo apt update && sudo apt upgradesudo apt autoremove nvidia* --purgeubuntu-drivers devicesYou will install the NVIDIA driver whose version is tagged with recommended
sudo ubuntu-drivers autoinstallMy recommended version is 525, adapt to yours
sudo apt install nvidia-driver-525rebootafter restart verify that the following command works
nvidia-smisudo apt update && sudo apt upgradesudo apt install nvidia-cuda-toolkitnvcc --versionYou can download cuDNN file here. You will need an Nvidia account. Select the cuDNN version for the appropriate CUDA version, which is the version that appears when you run:
nvcc --versionsudo apt install ./<filename.deb>
sudo cp /var/cudnn-<something>.gpg /usr/share/keyrings/My cuDNN version is 8, adapt the following to your version:
sudo apt update
sudo apt install libcudnn8
sudo apt install libcudnn8-dev
sudo apt install libcudnn8-samplessudo apt-get install python3-pip
sudo pip3 install virtualenv
virtualenv -p py3.10 venv
source venv/bin/activatepip3 install torch torchvision torchaudioimport torch
print(torch.cuda.is_available()) # should be True
t = torch.rand(10, 10).cuda()
print(t.device) # should be CUDA
Pip package for pytorch which works with Cuda
Pytorch 与 Cuda 的版本兼容列表：
https://pytorch.org/get-started/previous-versions/
Q1: cuda 11.4 的驱动（nvidia-smi看到的版本号）， 如何安装 torch ?
A: cuda 11.4/11.6 的驱动，可以使用 torch cu113, cu118 兼容的 pip 包, 详细讨论:
pytorch/pytorch#75992
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
可以从镜像站下载包安装, 搭配 Python 3.10 的版本包：
wget https://mirror.sjtu.edu.cn/pytorch-wheels/cu113/torch-1.12.0+cu113-cp310-cp310-linux_x86_64.whl
Q2: 只有 cuda 11.4 的系统驱动(nvidia-smi)， 要使用 torch 2.0.1 以上的版本，如何安装 torch?
A: 如果需要使用 torch 2.0.1 以上的版本，但 ubuntu 系统只有 cuda 11.4 的驱动，可以使用 torch 2.0.1 & cu11 的编译版本：
pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 --index-url https://download.pytorch.org/whl/cu118
参考：https://discuss.pytorch.org/t/which-pytorch-version-2-0-1-support-cuda-11-4/190446/3