(1)參考tensorflow官網給出的示例:https://www.tensorflow.org/install/gpu
# Add NVIDIA package repositories
# Add HTTPS support for apt-key
sudo apt-get install gnupg-curl
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/cuda-repo-ubuntu1604_10.1.243-1_amd64.deb
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/7fa2af80.pub
sudo dpkg -i cuda-repo-ubuntu1604_10.1.243-1_amd64.deb
sudo apt-get update
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1604/x86_64/nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb
sudo apt install ./nvidia-machine-learning-repo-ubuntu1604_1.0.0-1_amd64.deb
sudo apt-get update
# Install NVIDIA driver
# Issue with driver install requires creating /usr/lib/nvidia
sudo mkdir /usr/lib/nvidia
sudo apt-get install --no-install-recommends nvidia-418
# Reboot. Check that GPUs are visible using the command: nvidia-smi
# Install development and runtime libraries (~4GB)
sudo apt-get install --no-install-recommends \
cuda-10-1 \
libcudnn7=7.6.4.38-1+cuda10.1 \
libcudnn7-dev=7.6.4.38-1+cuda10.1
# Install TensorRT. Requires that libcudnn7 is installed above.
sudo apt-get install -y --no-install-recommends \
libnvinfer6=6.0.1-1+cuda10.1 \
libnvinfer-dev=6.0.1-1+cuda10.1 \
libnvinfer-plugin6=6.0.1-1+cuda10.1
(2)配置環境變量
# 打開配置文件
vi ~/.bashrc
# 也可以使用
gedit ~/.bashrc
#導入下面語句
export PATH=/usr/local/cuda/bin:${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/cuda/extras/CUPTI/lib64
(3)請注意這一句
sudo apt-get install --no-install-recommends nvidia-418
(4)安裝tensorflow2.2,集成了cpu和gpu版本,無需單獨安裝cpu或者gpu版本
pip install tensorflow
(5)運行python程序,測試tensorflow是否使用gpu,如果沒有使用gpu,那麼請注意我們之前安裝的語句
sudo apt-get install --no-install-recommends nvidia-418
(6)查看運行python程序時,會報錯 nvidia driver 418和450(我的是這個錯誤)不匹配
(7)這時我們只需要安裝對應的那個高的版本就可以了
sudo apt-get install --no-install-recommends nvidia-450
(8)錯誤不盡相同,這裏僅供參考