Ubuntu 16.04编译安装TensorFlow 1.7.0 开发环境

1. Ref

2. Clone TensorFlow repository

• Clone TensorFlow repo with protobuf sub-modules

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

• checkout需要的tag

$ cd tensorflow
$ git tag             # 查看有哪些tag
$ git checkout Branch # where Branch is the desired branch
$ git checkout v1.7.0 # checkout v1.7.0
$ git status          # 查看当前代码的状态

3. 环境安装 (CPU)

3.1 安装 bazel

• 安装JDK8

$ sudo apt-get install openjdk-8-jdk

• 增加bazel安装包源

$ 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 -

• 安装并升级bazel

$ sudo apt-get update && sudo apt-get install bazel
$ sudo apt-get upgrade bazel

3.2 安装TensorFlow Python依赖包

• numpy, which is a numerical processing package that TensorFlow requires.
• dev, which enables adding extensions to Python.
• pip, which enables you to install and manage certain Python packages.

• wheel, which enables you to manage Python compressed packages in the wheel (.whl) format.

• 对于Python2.7，需要执行

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

• 对于Python3.n， 需要执行

sudo apt-get install python3-numpy python3-dev python3-pip python3-wheel

• 对于Pythoh2.7或Python3.n，在执行TensorFlow的configure时，需要输入对应的路径

4. 配置并编译TensorFlow

4.1 配置TensorFlow

$ ./configure

• 在重新执行configure之前，需要执行bazel clean
• gcc版本要求：gcc 5 or later

4.2 编译pip包

• 仅支持CPU

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

• 支持GPU

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

• The bazel build command builds a script named build_pip_package
• Running this script as follows will build a .whl file within the /tmp/tensorflow_pkg directory
• 创建.whl文件

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

安装pip包

• 包名依赖于平台和TensorFlow版本叼，对于TensorFlow 1.7.0 on Linux，安装命令如下

$ sudo pip3 install --upgrade pip  # 升级pip3
$ sudo pip3 install /tmp/tensorflow_pkg/tensorflow-1.7.0-py2-none-any.whl

5. 验证

ai@aivm:~/tools$ python3
Python 3.5.2 (default, Nov 23 2017, 16:37:01) 
[GCC 5.4.0 20160609] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> a = tf.constant(3)
>>> b = tf.constant(5)
>>> c = a + b
>>> sess = tf.Session()
>>> print(sess.run(c))
8
>>> 

6. 安装jupyter notebook

• IPython是一个 Python 的一个交互式 shell，它提供了很多内建的函数。Jupyter Notebook是IPython的一个Web接口，其实它也支持其它语言；允许您创建和共享包含实时代码，方程，可视化和说明文本的文档。 用途包括：数据清理和转换，数值模拟，统计建模，机器学习等等。

• 安装Jupyter Notebook

$ sudo pip3 install jupyter 

7. 安装Virtualenv

• 安装Virtualenv

$ sudo apt-get install python3-pip python3-dev python-virtualenv # for Python 3.n

• 创建Virtualenv环境

$ virtualenv --system-site-packages -p python3 targetDirectory # for Python 3.n
$ virtualenv --system-site-packages -p python3 ~/tensorflow # for Python 3.n例子

• 激活Virtualenv环境

$ source ~/tensorflow/bin/activate # bash, sh, ksh, or zsh

• 确认pip ≥8.1

(tensorflow)$ easy_install -U pip

• 在激活的Virtualenv环境中安装TensorFlow

(tensorflow)$ pip install --upgrade tensorflow      # for Python 2.7
(tensorflow)$ pip3 install --upgrade tensorflow     # for Python 3.n
(tensorflow)$ pip install --upgrade tensorflow-gpu  # for Python 2.7 and GPU
(tensorflow)$ pip3 install --upgrade tensorflow-gpu # for Python 3.n and GPU

• 退出Virtualenv

(tensorflow)$ deactivate 

• 卸载TensorFlow

$ rm -r targetDirectory
$ rm -r ~/tensorflow