Overview
综述
TensorFlow has APIs available in several languages both for constructing and executing a TensorFlow graph. The Python API is at present the most complete and the easiest to use, but the C++ API may offer some performance advantages in graph execution, and supports deployment to small devices such as Android.
TensorFlow 对构造和运行一个TensorFlow graph 提供多种语言的API。其中Python API 是最完整且最易用的，但是C++ PAI在执行时有更多的性能优势，而且支持部署在诸如Android的小型设备上。
Over time, we hope that the TensorFlow community will develop front ends for languages like Go, Java, Javascript, Lua R, and perhaps others. With SWIG, it's relatively easy to contribute a TensorFlow interface to your favorite language.
以后，我们希望TnesorFlow社区可以开发如Go,Java,Javascript,Lua R或者其他的语言版本。通过使用SWIG，你可以很容易使用自己喜欢的语言去调用TensorFlow接口。
Note: Many practical aspects of usage are covered in the Mechanics tab, and some additional documentation not specific to any particular language API is available in the Resources tab.
注意：许多使用的方法都包含在Mechanics tab中，一些额外不指定特定语言的API文档可以在Resources tab中找到。