适用于PyTorch 2.0.0的Ubuntu 22.04上CUDA v11.8和cuDNN 8.7安装指南
将下面内容保存为install.bash,直接用bash执行一把梭解决
(图片来源网络,侵删)
#!/bin/bash ### steps #### # verify the system has a cuda-capable gpu # download and install the nvidia cuda toolkit and cudnn # setup environmental variables # verify the installation ### ### to verify your gpu is cuda enable check lspci | grep -i nvidia ### If you have previous installation remove it first. sudo apt purge nvidia* -y sudo apt remove nvidia-* -y sudo rm /etc/apt/sources.list.d/cuda* sudo apt autoremove -y && sudo apt autoclean -y sudo rm -rf /usr/local/cuda* # system update sudo apt update && sudo apt upgrade -y # install other import packages sudo apt install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev # first get the PPA repository driver sudo add-apt-repository ppa:graphics-drivers/ppa sudo apt update # find recommended driver versions for you ubuntu-drivers devices # install nvidia driver with dependencies sudo apt install libnvidia-common-515 libnvidia-gl-515 nvidia-driver-515 -y # reboot sudo reboot now # verify that the following command works nvidia-smi sudo wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin sudo mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600 sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /" # Update and upgrade sudo apt update && sudo apt upgrade -y # installing CUDA-11.8 sudo apt install cuda-11-8 -y # setup your paths echo 'export PATH=/usr/local/cuda-11.8/bin:$PATH' >> ~/.bashrc echo 'export LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH' >> ~/.bashrc source ~/.bashrc sudo ldconfig # install cuDNN v11.8 # First register here: https://developer.nvidia.com/developer-program/signup CUDNN_TAR_FILE="cudnn-linux-x86_64-8.7.0.84_cuda11-archive.tar.xz" sudo wget https://developer.download.nvidia.com/compute/redist/cudnn/v8.7.0/local_installers/11.8/cudnn-linux-x86_64-8.7.0.84_cuda11-archive.tar.xz sudo tar -xvf ${CUDNN_TAR_FILE} sudo mv cudnn-linux-x86_64-8.7.0.84_cuda11-archive cuda # copy the following files into the cuda toolkit directory. sudo cp -P cuda/include/cudnn.h /usr/local/cuda-11.8/include sudo cp -P cuda/lib/libcudnn* /usr/local/cuda-11.8/lib64/ sudo chmod a+r /usr/local/cuda-11.8/lib64/libcudnn* # Finally, to verify the installation, check nvidia-smi nvcc -V # install Pytorch (an open source machine learning framework) pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
转载并汉化自Github
文章版权声明:除非注明,否则均为主机测评原创文章,转载或复制请以超链接形式并注明出处。