CUDA + CUDNN + Aanaconda + Tenso

1. Install CUDA

Install Nvidia-driver

sudo add-apt-repository ppa:graphics-drivers/ppa 
sudo apt update      

CUDA 9.0

https://developer.nvidia.com/cuda-90-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1704&target_type=runfilelocal

先安装一些依赖

sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libopenblas-dev liblapack-dev libatlas-base-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev
sudo apt-get install git cmake build-essential
sudo apt-get install freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libgl1-mesa-glx libglu1-mesa libglu1-mesa-dev 

sudo apt-get update

sudo chmod a+x cuda_9.0.176_384.81_linux.run
sudo sh ./cuda_9.0.176_384.81_linux.run

vim .bashrc

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

source ~/.bashrc

2. Install CUDNN

https://developer.nvidia.com/rdp/cudnn-archive

sudo mv cuda/include/cudnn.h /usr/local/cuda/include/
sudo mv cuda/lib64/libcudnn* /usr/local/cuda/lib64/
sudo chmod a+r /usr/local/cuda/include/cudnn.h
sudo chmod a+r /usr/local/cuda/lib64/libcudnn*

查看cudnn版本
cat /usr/local/cuda/include/cudnn.h | grep CUDNN_MAJOR -A 2

3. Install Anaconda

https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/?C=M&O=D
sudo chmod a+x Anaconda3-4.3.0-Linux-x86_64.sh
sudo ./Anaconda3-4.3.0-Linux-x86_64.sh

4. Install tensorflow-gpu

conda create -n cyr python=3.5
pip install tensorflow-gpu==1.10

import tensorflow as tf
print(tf.test.is_gpu_available())

5. Install pytorch-gpu

https://download.pytorch.org/whl/cu90/torch_stable.html
pip install torch-1.1.0-cp35-cp35m-linux_x86_64.whl
pip install torchvision-0.3.0-cp35-cp35m-manylinux1_x86_64.whl

import torch
torch.cuda.is_available()