TensorFlow Ubuntu 16.04配置

TensorFlow的配置方法主要分为两种：
一、通过Python的PIP来进行安装
这种方法相对比较简单，只需要一个命令就可以完成。主要针对不同的用户需求分为CPU安装和GPU安装，
CPU安装：
sudo pip install --upgrade tensorflow
GPU安装：

sudo pip install --upgrade tensorflow-gpu

二、通过源码编译

这种方法虽然比较繁琐，但是这种方法可以有个人的配置，同时还可以编译出适用于Android等平台的库。

首先去github上下载源码，记住一定要下tag版，不要直接git clone，这样获取的版本不一定会稳定。

然后装一下依赖：

sudo apt-get install pkg-config zip g++ zlib1g-dev unzip
sudo add-apt-repository ppa:openjdk-r/ppa
sudo apt-get update
sudo apt-get install openjdk-8-jdk bazel

之后，配置编译

[email protected]:~/TensorFlow/tensorflow-master/tensorflow $ sudo ./configure 
You have bazel 0.5.1- installed.
Please specify the location of python. [Default is /usr/bin/python]: 
Found possible Python library paths:
  /usr/local/lib/python2.7/dist-packages
  /usr/lib/python2.7/dist-packages
Please input the desired Python library path to use.  Default is [/usr/local/lib/python2.7/dist-packages]

Using python library path: /usr/local/lib/python2.7/dist-packages
Do you wish to build TensorFlow with MKL support? [y/N] y
MKL support will be enabled for TensorFlow
Do you wish to download MKL LIB from the web? [Y/n] n
Please specify the location where MKL is installed. [Default is /opt/intel/mklml]: /opt/intel/mkl
Please specify optimization flags to use during compilation when bazel option "--config=opt" is specified [Default is -march=native]: 
Do you wish to use jemalloc as the malloc implementation? [Y/n] 
jemalloc enabled
Do you wish to build TensorFlow with Google Cloud Platform support? [y/N] 
No Google Cloud Platform support will be enabled for TensorFlow
Do you wish to build TensorFlow with Hadoop File System support? [y/N] 
No Hadoop File System support will be enabled for TensorFlow
Do you wish to build TensorFlow with the XLA just-in-time compiler (experimental)? [y/N] 
No XLA support will be enabled for TensorFlow
Do you wish to build TensorFlow with VERBS support? [y/N] 
No VERBS support will be enabled for TensorFlow
Do you wish to build TensorFlow with OpenCL support? [y/N] 
No OpenCL support will be enabled for TensorFlow
Do you wish to build TensorFlow with CUDA support? [y/N] y
CUDA support will be enabled for TensorFlow
Do you want to use clang as CUDA compiler? [y/N] 
nvcc will be used as CUDA compiler
Please specify the CUDA SDK version you want to use, e.g. 7.0. [Leave empty to default to CUDA 8.0]: 
Please specify the location where CUDA  toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: 
Please specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]: 
Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 6.0]: 5.1
Please specify the location where cuDNN 5.1 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: 
Invalid path to cuDNN  toolkit. Neither of the following two files can be found:
/usr/local/cuda-8.0/lib64/libcudnn.so.5.1
/usr/local/cuda-8.0/libcudnn.so.5.1
.5.1
Please specify the cuDNN version you want to use. [Leave empty to default to cuDNN 6.0]: 5.1.10
Please specify the location where cuDNN 5.1.10 library is installed. Refer to README.md for more details. [Default is /usr/local/cuda]: 
Please specify a list of comma-separated Cuda compute capabilities you want to build with.
You can find the compute capability of your device at: https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your build time and binary size.
[Default is: "3.5,5.2"]: 6.1
Do you wish to build TensorFlow with MPI support? [y/N] 
MPI support will not be enabled for TensorFlow
Configuration finished

即可