cuda12.1+torch2.1.0安装_安装torch 2.1.0

nvidia-smi
sudo apt update
sudo apt install gcc g++ make
sudo apt install libglu1-mesa libxi-dev libxmu-dev libglu1-mesa-dev freeglut3-dev
wget https://developer.download.nvidia.com/compute/cuda/12.1.0/local_installers/cuda_12.1.0_530.30.02_linux.run
sudo sh cuda_12.1.0_530.30.02_linux.run
ls -l /usr/local | grep cuda
nvcc -V

export PATH=$PATH:/usr/local/cuda-12.1/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda-12.1/lib64

source ~/.bashrc

#上一步把cuda目录要加进去再刷新

cudnn是计算库，加上运行速度更快

tar -xvf cudnn-linux-x86_64-8.9.6.50_cuda12-archive.tar.xz
sudo cp cudnn-linux-x86_64-8.9.6.50_cuda12-archive/include/cudnn.h    /usr/local/cuda-12.1/include
sudo cp cudnn-linux-x86_64-8.9.6.50_cuda12-archive/lib/libcudnn*    /usr/local/cuda-12.1/lib64
sudo chmod a+r /usr/local/cuda-12.1/include/cudnn.h

#自动指令不行的情况下自己下载包安装，安装包下载地址如下：
https://download.pytorch.org/whl/torch_stable.html
 

conda install pytorch torchvision torchaudio pytorch-cuda=12.1 -c pytorch
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
pip list
pip uninstall torch
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
ls
#上述自动安装失败后手动下载后安装
pip install torch-2.1.0+cu121-cp38-cp38-linux_x86_64.whl
pip uninstall torchvision
pip install torchvision-0.16.0+cu121-cp38-cp38-linux_x86_64.whl

python3
import torch
torch.cuda.is_available()

TRUE就大功告成