ubuntu16+tensorflow-gpu安装cuda

  1. 初始化环境
sudo apt-get update sudo apt-get upgrade sudo apt-get install -y build-essential git python-pip libfreetype6-dev libxft-dev libncurses-dev libopenblas-dev gfortran python-matplotlib libblas-dev liblapack-dev libatlas-base-dev python-dev python-pydot linux-headers-generic linux-image-extra-virtual unzip python-numpy swig python-pandas python-sklearn unzip wget pkg-config zip g++ zlib1g-dev

  1. 下载 cuda [注:tensorflow-gpu当前pip安装版本1.9,支持cuda9.0+cudnn7.1.4for cuda9.0
http://developer.download.nvidia.com/compute/cuda/repos/ 选择对应系统版本,本次使用cuda9sudo dpkg -icuda-repo-ubuntu1410_XXXX_amd64.deb rm cuda-repo-ubuntu1410_XXXX_amd64.deb sudo apt-get update sudo apt-get install -y cuda安装错误卸载 sudo dpkg -P packagename, sudo apt-get autoremove cuda

  1. 下载cudnn
https://developer.nvidia.com/rdp/cudnn-archive 选择 cuDNN vXXX Library for Linux,目前下载cudnn7.1.4 for cuda9.0cp cudnn-XXX.solitairetheme8 cudnn-linux-x64.tgz tar -xvf cudnn-linux-x64.tgzsudo cp cuda/include/cudnn.h /usr/local/cuda/includesudo cp cuda/lib64/libcudnn*/usr/local/cuda/lib64sudo chmod a+r/usr/local/cuda/include/cudnn.h/usr/local/cuda/lib64/libcudnn*

  1. 配置环境变量
sudo vi ~/.bashrc export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64" export CUDA_HOME=/usr/local/cuda export PATH="$CUDA_HOME/bin:$PATH" source ~/.bashrc

  1. 安装tensorflow-gpu == 1.9
pip install keras pip install tensorflow-gpu==1.9

  1. 安装运行
import tensorflow as tf

提示
【ubuntu16+tensorflow-gpu安装cuda】h5py numpy警告
pip install h5py==2.8.0rc1

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