标签：xor ror bash 下载 驱动 sys ORC ref end
1 安装nvidia驱动
1.1 设置root
sudo passwd 123
1.2 检测nvidia显卡
ubuntu-drivers devices
(base) dxs@dxs-ubuntu:~$ ubuntu-drivers devices == /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 == modalias : pci:v000010DEd00002184sv00001458sd00003FC7bc03sc00i00 vendor : NVIDIA Corporation driver : nvidia-driver-430 - distro non-free recommended driver : xserver-xorg-video-nouveau - distro free builtin (base) dxs@dxs-ubuntu:~$
1.3 安装nvidia驱动
sudo apt install nvidia-driver-430
1.4 安装完成后 reboot
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2 安装anaconda3
2.1 下载Anaconda3-5.2.0-Linux-x86_64.sh
2.2 安装：sudo sh Anaconda3-5.2.0-Linux-x86_64.sh
2.3 设置conda镜像
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 --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/ conda config --set show_channel_urls yes
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3 安装cuda cudnn
conda install cudatoolkit=10.0 conda install cudnn=7.6.0
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4 安装tensorflow-gpu
conda install tensorflow-gpu=1.13.1
5 安装pytorch
在线安装： conda install pytorch torchvision cudatoolkit=10.0 -c pytorch
离线安装： 先去 https://download.pytorch.org/whl/cu100/torch_stable.html 下载 torch-1.2.0-cp36-cp36m-manylinux1_x86_64.whl 和 torchvision-0.4.0-cp36-cp36m-manylinux1_x86_64.whl ， 然后安装
6 安装caffe
conda install -c defaults caffe-gpu
标签：xor ror bash 下载 驱动 sys ORC ref end
原文地址：https://www.cnblogs.com/dxscode/p/11633657.html
