Ubuntu20.04 RTX3070 CUDA 11.0 深度学习环境配置

安装驱动

Software & Updates –> Additional Drivers

安装CUDA

下载安装

sudo sh cuda_11.0.2_450.51.05_linux.run

配置环境变量

vim ~/.bashrc
export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

source ~/.bashrc

验证是否安装成功

nvcc -V

安装CUDNN

下载安装

tar zxvf cudnn-11.0-linux-x64-v8.0.5.39.tgz

sudo cp cuda/include/cudnn.h    /usr/local/cuda/include/
sudo cp cuda/lib64/libcudnn*    /usr/local/cuda/lib64/
sudo chmod a+r /usr/local/cuda-11.0/include/cudnn.h
sudo chmod a+r /usr/local/cuda-11.0/lib64/libcudnn*

sudo dpkg -i libcudnn8_8.0.5.39-1+cuda11.0_amd64.deb
sudo dpkg -i libcudnn8-dev_8.0.5.39-1+cuda11.0_amd64.deb
sudo dpkg -i libcudnn8-samples_8.0.5.39-1+cuda11.0_amd64.deb

验证

cd /home/youda/NVIDIA_CUDA-11.0_Samples/1_Utilities/deviceQuery

make

./deviceQuery

sudo dpkg -i libcudnn8_8.0.5.39-1+cuda11.0_amd64.deb
sudo dpkg -i libcudnn8-dev_8.0.5.39-1+cuda11.0_amd64.deb
sudo dpkg -i libcudnn8-samples_8.0.5.39-1+cuda11.0_amd64.deb

安装pytorch

pip3 install torch==1.8.0+cu111 torchvision==0.9.0+cu111 torchaudio==0.8.0 -f https://download.pytorch.org/whl/torch_stable.html

(base)  youda@youda-ubuntu  ~  python
Python 3.8.5 (default, Sep  4 2020, 07:30:14)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.cuda.is_available()
True
>>> torch.Tensor(5,3).cuda()
tensor([[-1.6869e-04,  4.5850e-41, -1.6865e-04],
        [ 4.5850e-41, -1.6865e-04,  4.5850e-41],
        [-1.6865e-04,  4.5850e-41, -1.6865e-04],
        [ 4.5850e-41, -1.6865e-04,  4.5850e-41],
        [-1.6866e-04,  4.5850e-41, -1.6866e-04]], device='cuda:0')
>>>
>>>