一. Pip安装：

$ sudo apt-get install python-pip python-dev   # for python  

$ sudo apt-get install python3-pip python3-dev # for python3

二.安装英伟达显卡驱动

1查看自身版本

lspci | grep -i vga
lspci | grep -i nvidia

或
去官网上查看适合你GPU的驱动
http://www.nvidia.com/Download/index.aspx?lang=en-us

2安装

对ubuntu16 可通过 系统设置-软件和更新-附加驱动 安装

3

执行完上述后，重启reboot

安装完后再运行

nvidia-smi 来看看 如果出现了你的GPU列表，则说明驱动安装成功了。 另外也可以通过，或者输入nvidia-settings 查看

三.安装cuda

https://developer.nvidia.com/cuda-downloads据其所说方式安装

ubuntu的gcc编译器是5.4.0，然而cuda8.0不支持5.0以上的编译器，因此需要降级，把编译器版本降到4.9：

在terminal中执行

sudo apt-get install gcc-4.9 gcc-5 g++-4.9 g++-5
 
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.9 20
 
sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-5 10
 
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.9 20
 
sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-5 10
 
sudo update-alternatives --install /usr/bin/cc cc /usr/bin/gcc 30
 
sudo update-alternatives --set cc /usr/bin/gcc
 
sudo update-alternatives --install /usr/bin/c++ c++ /usr/bin/g++ 30
 
sudo update-alternatives --set c++ /usr/bin/g++ 

配置cuda8.0之后主要加上的一个环境变量声明，

gedit ~/.bashrc 

在文件~/.bashrc末尾加上

export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}

export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}

通过命令查看CUDA安装是否成功

cd /usr/local/cuda-8.0/samples/1_Utilities/deviceQuery  
sudo make  
./deviceQuery 

四.cudnn

https://developer.nvidia.com/cudnn tensorflow1.1 支持cudnnv5.1

下载完cudnn后

cd ~/Downloads/
tar zxvf cudnn-8.0-linux-x64-v5.1.tgz #解压文件

# 复制头文件和lib文件  
sudo cp include/cudnn.h /usr/local/cuda/include/  
sudo cp lib64/lib* /usr/local/cuda/lib64/  

# 进入文件夹
cd /usr/local/cuda/lib64/ 
sudo rm -rf libcudnn.so libcudnn.so.5    #删除原有动态文件
# 然后修改文件权限，并创建新的软连接
sudo chmod u=rwx,g=rx,o=rx libcudnn.so.5.1.10  #若这里不修改权限会有如下错误
sudo ln -s libcudnn.so.5.1.5 libcudnn.so.5  #生成软衔接
sudo ln -s libcudnn.so.5 libcudnn.so      #生成软链接

# 错误
Traceback (most recent call last):
  File "<stdin>",line 1,in <module>
ImportError: No module named rensorflow
>>> import tensorflow
Traceback (most recent call last):
  File "<stdin>",in <module>
  File "/home/yojiu/.local/lib/python2.7/site-packages/tensorflow/__init__.py",line 24,in <module>
    from tensorflow.python import *
  File "/home/yojiu/.local/lib/python2.7/site-packages/tensorflow/python/__init__.py",line 51,in <module>
    from tensorflow.python import pywrap_tensorflow
  File "/home/yojiu/.local/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow.py",line 52,in <module>
    raise ImportError(msg)
ImportError: Traceback (most recent call last):
  File "/home/yojiu/.local/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow.py",line 41,in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "/home/yojiu/.local/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow_internal.py",line 28,in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "/home/yojiu/.local/lib/python2.7/site-packages/tensorflow/python/pywrap_tensorflow_internal.py",in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal',fp,pathname,description)
ImportError: libcudnn.so.5: cannot open shared object file: No such file or directory
Failed to load the native TensorFlow runtime.
See https://www.tensorflow.org/install/install_sources#common_installation_problems
for some common reasons and solutions.  Include the entire stack trace
above this error message when asking for help.

五.安装tensorflow

直接配置URL在线 whl 进行安装：

$ sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.1.0rc2-cp27-none-linux_x86_64.whl
                             #或其他网站镜像