硬件一览

深度学习环境

安装miniconda

https://docs.conda.io/en/latest/miniconda.html

bash Miniconda3-latest-Linux-x86_64.sh
#配置清华源
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --set show_channel_urls yes
conda create -n jupyter-tf2 python=3.8
conda activate jupyter-tf2

安装nvidia显卡驱动（可省略，cuda toolkit包含了驱动）

apt-get install build-essential

下载适合自己的驱动https://www.nvidia.com/Download/index.aspx?lang=en-us#

bash NVIDIA-Linux-x86_64-515.48.07.run

安装cuda toolkit

https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html

wget https://developer.download.nvidia.com/compute/cuda/11.7.0/local_installers/cuda-repo-debian11-11-7-local_11.7.0-515.43.04-1_amd64.deb
dpkg -i cuda-repo-debian11-11-7-local_11.7.0-515.43.04-1_amd64.deb
cp /var/cuda-repo-debian11-11-7-local/cuda-*-keyring.gpg /usr/share/keyrings/
add-apt-repository contrib
apt-get update
apt-get -y install cuda

安装cudnn

https://docs.nvidia.com/deeplearning/cudnn/install-guide/index.html

apt install zlib1g
dpkg -i cudnn-local-repo-ubuntu2004-8.4.1.50_1.0-1_amd64.deb
cp /var/cudnn-local-repo-*/cudnn-local-*-keyring.gpg /usr/share/keyrings/
apt-get install libcudnn8=8.4.1.50_1.0-1+cuda11.7
apt-get install libcudnn8-dev=8.4.1.50_1.0-1+cuda11.7
apt-get install libcudnn8-samples=8.4.1_1.0-1+cuda11.7

安装TensorRT

https://docs.nvidia.com/deeplearning/tensorrt/archives/index.html#trt_6

安装tensorflow2

https://www.tensorflow.org/install?hl=zh-cn

conda install tensorflow

安装jupyter notebook

conda install jupyter notebook