tensorlayer · luomai · Jun 4, 2018 · Jun 4, 2018 · Jun 4, 2018 · Jun 4, 2018
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -87,6 +87,7 @@ To release a new version, please update the changelog as followed:
     - py3 + cpu
     - py3 + gpu
 - Documentation:
+  - Clean README (by @luomai in #677)
   - Release semantic version added on index page (by @DEKHTIARJonathan in #633)
   - Optimizers page added (by @DEKHTIARJonathan in #636)
   - `AMSGrad` added on Optimizers page added (by @DEKHTIARJonathan in #636)

diff --git a/README.md b/README.md
@@ -4,18 +4,23 @@
     </div>
 </a>
 
-[![Build Status](https://img.shields.io/travis/tensorlayer/tensorlayer.svg?label=Travis&branch=master)](https://travis-ci.org/tensorlayer/tensorlayer)
+[![Codacy Badge](https://api.codacy.com/project/badge/Grade/ca2a29ddcf7445588beff50bee5406d9)](https://app.codacy.com/app/tensorlayer/tensorlayer)
+[![Mentioned in Awesome TensorLayer](https://awesome.re/mentioned-badge.svg)](https://github.com/tensorlayer/awesome-tensorlayer)
+[![English Documentation](https://img.shields.io/badge/documentation-english-blue.svg)](https://tensorlayer.readthedocs.io/)
+[![Chinese Documentation](https://img.shields.io/badge/documentation-中文-blue.svg)](https://tensorlayercn.readthedocs.io/)
+[![Chinese Book](https://img.shields.io/badge/book-中文-blue.svg)](http://www.broadview.com.cn/book/5059/)
+
 [![PyPI version](https://badge.fury.io/py/tensorlayer.svg)](https://pypi.org/project/tensorlayer/)
 [![Github commits (since latest release)](https://img.shields.io/github/commits-since/tensorlayer/tensorlayer/latest.svg)](https://github.com/tensorlayer/tensorlayer/compare/1.8.6rc1...master)
 [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/tensorlayer.svg)](https://pypi.org/project/tensorlayer/)
 [![Supported TF Version](https://img.shields.io/badge/tensorflow-1.6.0+-blue.svg)](https://github.com/tensorflow/tensorflow/releases)
-[![Codacy Badge](https://api.codacy.com/project/badge/Grade/ca2a29ddcf7445588beff50bee5406d9)](https://app.codacy.com/app/tensorlayer/tensorlayer)
 
+[![Build Status](https://img.shields.io/travis/tensorlayer/tensorlayer.svg?label=Travis&branch=master)](https://travis-ci.org/tensorlayer/tensorlayer)
 [![CircleCI](https://img.shields.io/circleci/project/github/tensorlayer/tensorlayer.svg?label=Docker%20Build&branch=master)](https://circleci.com/gh/tensorlayer/tensorlayer/tree/master)
-[![Docker Pulls](https://img.shields.io/docker/pulls/tensorlayer/tensorlayer.svg?maxAge=604800)](https://hub.docker.com/r/tensorlayer/tensorlayer/)
 [![Documentation Status](https://img.shields.io/readthedocs/tensorlayer/latest.svg?label=ReadTheDocs-EN)](https://tensorlayer.readthedocs.io/)
 [![Documentation Status](https://img.shields.io/readthedocs/tensorlayercn/latest.svg?label=ReadTheDocs-CN)](https://tensorlayercn.readthedocs.io/)
 [![PyUP Updates](https://pyup.io/repos/github/tensorlayer/tensorlayer/shield.svg)](https://pyup.io/repos/github/tensorlayer/tensorlayer/)
+[![Docker Pulls](https://img.shields.io/docker/pulls/tensorlayer/tensorlayer.svg?maxAge=604800)](https://hub.docker.com/r/tensorlayer/tensorlayer/)
 
 <br/>
 
@@ -27,62 +32,37 @@
 
 <br/>
 
-[![Mentioned in Awesome TensorLayer](https://awesome.re/mentioned-badge.svg)](https://github.com/tensorlayer/awesome-tensorlayer)
-[![English Documentation](https://img.shields.io/badge/documentation-english-blue.svg)](https://tensorlayer.readthedocs.io/)
-[![Chinese Documentation](https://img.shields.io/badge/documentation-中文-blue.svg)](https://tensorlayercn.readthedocs.io/)
-[![Chinese Book](https://img.shields.io/badge/book-中文-blue.svg)](http://www.broadview.com.cn/book/5059/)
-
-TensorLayer is a deep learning and reinforcement learning library on top of [TensorFlow](https://www.tensorflow.org). It provides rich neural layers and utility functions to help researchers and engineers build real-world AI applications. TensorLayer is awarded the 2017 Best Open Source Software by the prestigious [ACM Multimedia Society](http://www.acmmm.org/2017/mm-2017-awardees/).
+TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides a large collection of customizable neural layers / functions that are key to build real-world AI applications. TensorLayer is awarded the 2017 Best Open Source Software by the [ACM Multimedia Society](http://www.acmmm.org/2017/mm-2017-awardees/).
 
 # Why another deep learning library: TensorLayer
 
-## Features
-
-As TensorFlow users, we have been looking for a library that can serve for various development
- phases. This library is easy for beginners by providing rich neural network implementations,
-examples and tutorials. Later, its APIs shall naturally allow users to leverage the powerful
-features of TensorFlow, exhibiting best performance in addressing real-world problems. In the
-end, the extra abstraction shall not compromise TensorFlow performance, and thus suit for
-production deployment. TensorLayer is a novel library that aims to satisfy these requirements.
-
-It has three key features:
-
-- ***Simplicity*** : TensorLayer lifts the low-level dataflow abstraction of TensorFlow to *high-level* layers. It also provides users with [rich examples](https://github.com/tensorlayer/awesome-tensorlayer) to minimize learning barrier.
-- ***Flexibility*** : TensorLayer APIs are transparent: it does not mask TensorFlow from users; but leaving massive hooks that support diverse *low-level tuning*.
-- ***Zero-cost Abstraction*** : TensorLayer has negligible overheads and can thus achieve the *full performance* of TensorFlow.
-
-## Negligible overhead
-
-To show the overhead, we train classic deep learning models using TensorLayer and native TensorFlow
-on a Titan X Pascal GPU.
-
-|             	| CIFAR-10      	| PTB LSTM      	| Word2Vec      	|
-|-------------	|---------------	|---------------	|---------------	|
-| TensorLayer 	| 2528 images/s 	| 18063 words/s 	| 58167 words/s 	|
-| TensorFlow  	| 2530 images/s 	| 18075 words/s 	| 58181 words/s 	|
-
+As deep learning practitioners, we have been looking for a library that can address various development
+ purposes. This library is easy to adopt by providing diverse examples, tutorials and pre-trained models. 
+Also, it allow users to easily fine-tune TensorFlow; while being suitable for production deployment. TensorLayer aims to satisfy all these purposes. It has three key features:
 
-## Why using TensorLayer instead of Keras or TFLearn
+- ***Simplicity*** : TensorLayer lifts the low-level dataflow interface of TensorFlow to *high-level* layers / models. It is very easy to learn through the rich [example codes](https://github.com/tensorlayer/awesome-tensorlayer) contributed by a wide community.
+- ***Flexibility*** : TensorLayer APIs are transparent: it does not mask TensorFlow from users; but leaving massive hooks that help *low-level tuning* and *deep customization*.
+- ***Zero-cost Abstraction*** : TensorLayer can achieve the *full power* of TensorFlow. The following table shows the training speeds of classic models using TensorLayer and native TensorFlow on a Titan X Pascal GPU.
 
-Similar to TensorLayer, Keras and TFLearn are also popular TensorFlow wrapper libraries.
-These libraries are comfortable to start with. They provide high-level abstractions;
-but mask the underlying engine from users. It is thus hard to customize model behaviors
-and touch the essential features of TensorFlow.
+	|             	| CIFAR-10      | PTB LSTM      | Word2Vec      |
+	|-------------	|---------------|---------------|---------------|
+	| TensorLayer 	| 2528 images/s | 18063 words/s | 58167 words/s |
+	| TensorFlow  	| 2530 images/s | 18075 words/s | 58181 words/s |
 
-Without compromise in simplicity, TensorLayer APIs are generally more flexible and transparent.
-Users often find it easy to start with the examples and tutorials of TensorLayer, and then dive
-into the TensorFlow low-level APIs only if need. TensorLayer does not create library lock-in. Users can easily import models from Keras, TFSlim and TFLearn into a TensorLayer environment.
 
-TensorLayer has a fast growing usage in academic and industry organizations. It is used by researchers from
-Imperial College London, Carnegie Mellon University, Stanford University,
-University of Technology of Compiegne (UTC), Tsinghua University, UCLA,
-and etc., as well as engineers from Google, Microsoft, Alibaba, Tencent, Xiaomi, Penguins Innovate, Bloomberg and many others.
+TensorLayer stands at a unique spot in the library landscape. Other wrapper libraries like Keras and TFLearn also provide high-level abstractions. They, however, often
+hide the underlying engine from users, which make them hard to customize 
+and fine-tune. On the contrary, TensorLayer APIs are generally flexible and transparent. 
+Users often find it easy to start with the examples and tutorials, and then dive
+into TensorFlow seamlessly. In addition, TensorLayer does not create library lock-in through native supports for importing components from Keras, TFSlim and TFLearn.
 
-# Installation
+TensorLayer has a fast growing usage among top researchers and engineers, from universities like
+Imperial College London, UC Berkeley, Carnegie Mellon University, Stanford University, and
+University of Technology of Compiegne (UTC), and companies like Google, Microsoft, Alibaba, Tencent, Xiaomi, and Bloomberg.
 
-TensorLayer has pre-requisites including TensorFlow, numpy, matplotlib and nltk (optional). For GPU support, CUDA and cuDNN are required.
+# Install
 
-The simplest way to install TensorLayer is to use the Python Package Index (PyPI):
+TensorLayer has pre-requisites including TensorFlow, numpy, matplotlib and nltk (optional). For GPU support, CUDA and cuDNN are required. The simplest way to install TensorLayer is to use the Python Package Index (PyPI):
 
 ```bash
 # for last stable version
@@ -129,11 +109,11 @@ docker pull tensorlayer/tensorlayer:latest-gpu-py3
 nvidia-docker run -it --rm -p 8888:8888 -p 6006:6006 -e PASSWORD=JUPYTER_NB_PASSWORD tensorlayer/tensorlayer:latest-gpu-py3
 ```
 
-# Contribute to TensorLayer
+# Contribute
 
 Please read the [Contributor Guideline](https://github.com/tensorlayer/tensorlayer/blob/rearrange-readme/CONTRIBUTING.md) before submitting your PRs.
 
-# Citation
+# Cite
 If you find this project useful, we would be grateful if you cite the TensorLayer paper：
 
 ```