Ubuntu：从源码安装tensorflow r1.0

官方链接：install tensorflow from sources

本文记录如何从源码安装tensorflow1.0，CPU版本，Python 2.7：

1. 安装依赖：bazel，Tensorflow Python dependencies

1）Bazel：

官方链接：install bazel on Ubuntu
1.install JDK 8 ：

$ sudo add-apt-repository ppa:webupd8team/java$ sudo apt-get update$ sudo apt-get install oracle-java8-installer

我电脑已经有了jdk，所以跳过这一步，验证：

2.install bazel：

$ echo "deb [arch=amd64] http://storage.googleapis.com/bazel-apt stable jdk1.8" | sudo tee /etc/apt/sources.list.d/bazel.list$ curl https://bazel.build/bazel-release.pub.gpg | sudo apt-key add -$ sudo apt-get update && sudo apt-get install bazel$ sudo apt-get upgrade bazel

2）Tensorflow Python dependencies：

包括：numpy，dev，pip，wheel

$ sudo apt-get install python-numpy python-dev python-pip python-wheel

2. 安装tensorflow：

1）Clone the TensorFlow repository：

这里用到git，如需安装，参见install git

$ git clone https://github.com/tensorflow/tensorflow$ cd tensorflow$ git checkout r1.0

2.Configure the installation

还是在刚刚的文件夹目录下，命令行输入：

$ cd tensorflow  # cd to the top-level directory created$ ./configure

然后会是一连串选择，官方示例如下：

Please specify the location of python. [Default is /usr/bin/python]: /usr/bin/python2.7Please 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 enabledDo you wish to build TensorFlow with Google Cloud Platform support? [y/N]No Google Cloud Platform support will be enabled for TensorFlowDo you wish to build TensorFlow with Hadoop File System support? [y/N]No Hadoop File System support will be enabled for TensorFlowDo you wish to build TensorFlow with the XLA just-in-time compiler (experimental)? [y/N]No XLA JIT support will be enabled for TensorFlowFound possible Python library paths:  /usr/local/lib/python2.7/dist-packages  /usr/lib/python2.7/dist-packagesPlease 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-packagesDo you wish to build TensorFlow with OpenCL support? [y/N] NNo OpenCL support will be enabled for TensorFlowDo you wish to build TensorFlow with CUDA support? [y/N] YCUDA support will be enabled for TensorFlowPlease specify which gcc should be used by nvcc as the host compiler. [Default is /usr/bin/gcc]:Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave empty to use system default]: 8.0Please specify the location where CUDA 8.0 toolkit is installed. Refer to README.md for more details. [Default is /usr/local/cuda]:Please specify the cuDNN version you want to use. [Leave empty to use system default]: 5Please specify the location where cuDNN 5 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"]: 3.0Setting up Cuda includeSetting up Cuda libSetting up Cuda binSetting up Cuda nvvmSetting up CUPTI includeSetting up CUPTI lib64Configuration finished

根据自己需要选择就好了。

3）Build the pip package

命令号运行：

$ bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package

这一步会比较耗内存，如果对电脑没信心的话，可以加上“–local_resources 2048,.5,1.0 while invoking bazel”：

$ bazel build --config=opt //tensorflow/tools/pip_package:build_pip_package --local_resources 2048,.5,1.0 while invoking bazel

之后会是漫长的等待，我的电脑足足跑了1个小时，不过我们离成功已经很近了，加油！再输入：

$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg

这一步会生成 .whl文件，聪明的你肯定知道这就是黎明前的曙光了，没错，接下来，我们：

4）Install the pip package

你的 .whi 文件会在“/tmp/tensorflow_pkg”目录下，没错，找到它，然后输入：

$ sudo pip install /tmp/tensorflow_pkg/name-of-you-whl.whl

比如我的文件名是-“tensorflow-1.0.1-cp27-cp27mu-linux_x86_64.whl”，所以就输入：

$ sudo pip install /tmp/tensorflow_pkg/ tensorflow-1.0.1-cp27-cp27mu-linux_x86_64.whl

OK，now check it out.

3.Validate your installation

以上，幸会。
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