Ubuntu install TensorFlow 1.10 + CUDA 9.2 + cuDNN 7.2

 

为了装TensorFlow 1.10 下面升级一下系统的软件环境

NVIDIA DRIVER

去官网下载最新的linux驱动   http://www.nvidia.com/Download/index.aspx 

 

直接运行会报错

 

sudo bash NVIDIA-Linux-x86_64-390.87.run

 

ERROR: You appear to be running an X server; please exit X before
         installing. For further details, please see the section INSTALLING
         THE NVIDIA DRIVER in the README available on the Linux driver
         download page at www.nvidia.com.

需要先关闭图形界面，在另一台电脑上用ssh登录这台电脑然后运行

sudo init 3 
sudo killall Xorg

然后再运行 

sudo bash NVIDIA-Linux-x86_64-390.87.run

装好后运行 

nvidia-smi

出现下图结果说明成功安装

再运行下面命令恢复图形界面

sudo init 5

可以重启一下确认显卡驱动是否正常

 

如果需要改gcc 或g++版本 请参考上一篇博文 https://www.cnblogs.com/jins-note/p/9597210.html

 

 

CUDA 9.2

由于TensorFlow 1.10 支持cuda 9.2 

去官网下载最新版本 

https://developer.nvidia.com/cuda-downloads?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1710&target_type=runfilelocal

先安装一些推荐库

sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev libglfw3-dev libgles2-mesa-dev

 

这里注意：cuda里带的驱动比刚从官网下的新，那么用cuda里带的驱动（居然比官网下的显卡驱动新？？）

不然会报错 

cudaerrorinsufficientdriver

然后安装

sudo init 3
sudo killall Xorg
sudo bash cuda_9.2.148_396.37_linux.run

安装过程如下

 

Description

The NVIDIA CUDA Toolkit provides command-line and graphical
Do you accept the previously read EULA?
accept/decline/quit: accept

Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 396.37?
(y)es/(n)o/(q)uit: y

Install the CUDA 9.2 Toolkit?
(y)es/(n)o/(q)uit: y

Enter Toolkit Location
 [ default is /usr/local/cuda-9.2 ]:

Do you want to install a symbolic link at /usr/local/cuda?
(y)es/(n)o/(q)uit: y

Install the CUDA 9.2 Samples?
(y)es/(n)o/(q)uit: y

Enter CUDA Samples Location
 [ default is /home/whatever ]:

安装 补丁

sudo bash cuda_9.2.148.1_linux.run

装好后修改环境变量 ~/.bashrc 在末尾添加

export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64"
export CUDA_HOME=/usr/local/cuda
export PATH="$CUDA_HOME/bin:$PATH"

修改完毕之后执行一下使其生效：

source ~/.bashrc

恢复显示

sudo init 5

 装好后去 CUDA Samples  目录编译一些例子看看能不能运行，能运行就ok  

cd ~/NVIDIA_CUDA-9.2_Samples/
make -j8

编译好后去下面目录里运行

cd bin/x86_64/linux/release

 

cuDNN

去官网下载对应版本 https://developer.nvidia.com/rdp/cudnn-download 需要登录才能下载

 

下载后的文件后缀名应该是 *.tgz 如果 是 .solitairetheme8 那就改成 .tgz

安装很简单，解压复制到对应目录就好

tar -zxvf cudnn-9.2-linux-x64-v7.2.1.38.tgz
sudo cp cuda/include/cudnn.h /usr/local/cuda/include/
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/ -d
sudo chmod a+r /usr/local/cuda/include/cudnn.h
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*

 

TensorFlow 1.10

安装 Anaconda   从这里下载 https://www.anaconda.com/download/

更换为国内源 https://mirrors.ustc.edu.cn/help/anaconda.html

conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.ustc.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.ustc.edu.cn/anaconda/cloud/conda-forge/
conda config --set show_channel_urls yes

然后安装

conda install tensorflow-gpu==1.10

装好后测试

import tensorflow as tf
tf.__version__

 

 

 

 

 

 

 

参考： https://cuiqingcai.com/5822.html