tensorflow源代码方式安装

　　本文介绍tensorflow源代码方式安装。安装的系统为 Ubuntu 15.04。

获取TensorFlow源代码

git clone --recurse-submodules https://github.com/tensorflow/tensorflow

使用 --recurse-submodules 选项来获取 TensorFlow 须要依赖的 protobuf 库文件。

安装 Bazel

　　听从如下 指令 来安装 bazel 依赖。bazel 安装文件：下载地址

　　bazel 缺省须要使用JDK1.8，如你使用JDK1.7，请下载相应的安装包。

　　安装 Bazel 其余所需依赖：

sudo apt-get install pkg-config zip g++ zlib1g-dev unzip

　　执行以下命令来安装Bazel：

chmod +x PATH_TO_INSTALL.SH
./PATH_TO_INSTALL.SH --user

 　　记住把 PATH_TO_INSTALL.SH 替换为你下载的Bazel安装文件名，如：

./bazel-0.1.4-installer-linux-x86_64.sh  --user

安装其余依赖

sudo apt-get install python-numpy swig python-dev

配置安装

　　运行 tensorflow 根目录下的 configure 脚本。这个脚本会要求你输入 python 解释器的安装路径，并容许你可选择安装CUDA库。

　　若是不安装CUDA，则这一步主要是定位python和numpy头文件所在位置：

./configure
Please specify the location of python. [Default is /usr/bin/python]:

 　　若是要安装CUDA，则除了指定 python 外，还需指定 CUDA 安装位置：

./configure
Please specify the location of python. [Default is /usr/bin/python]:
Do you wish to build TensorFlow with GPU support? [y/N] y
GPU support will be enabled for TensorFlow

Please specify the location where CUDA 7.0 toolkit is installed. Refer to
README.md for more details. [default is: /usr/local/cuda]: /usr/local/cuda

Please specify the location where the cuDNN v2 library is installed. Refer to
README.md for more details. [default is: /usr/local/cuda]: /usr/local/cuda

Setting up Cuda include
Setting up Cuda lib64
Setting up Cuda bin
Setting up Cuda nvvm
Configuration finished

 

构建支持GPU的Tensorflow 

　　在tensorflow 根目录下执行以下命令：

$ bazel build -c opt --config=cuda --spawn_strategy=standalone //tensorflow/cc:tutorials_example_trainer

$ bazel-bin/tensorflow/cc/tutorials_example_trainer --use_gpu
# Lots of output. This tutorial iteratively calculates the major eigenvalue of
# a 2x2 matrix, on GPU. The last few lines look like this. 000009/000005 lambda = 2.000000 x = [0.894427 -0.447214] y = [1.788854 -0.894427] 000006/000001 lambda = 2.000000 x = [0.894427 -0.447214] y = [1.788854 -0.894427] 000009/000009 lambda = 2.000000 x = [0.894427 -0.447214] y = [1.788854 -0.894427]

Note that "--config=cuda" is needed to enable the GPU support.