Add TensorLayer and Selected Examples

Hi, thank you for this collection. 
I would like to add TensorLayer to the library list, and some selected examples.

README.md

@@ -43,6 +43,7 @@ More info [here](http://tensorflow.org).
 * [CS20 SI: TensorFlow for DeepLearning Research](http://web.stanford.edu/class/cs20si/syllabus.html) - Stanford Course about Tensorflow from 2017 - [Syllabus](http://web.stanford.edu/class/cs20si/syllabus.html) - [Unofficial Videos](https://youtu.be/g-EvyKpZjmQ?list=PLSPPwKHXGS2110rEaNH7amFGmaD5hsObs)
 * [TensorFlow World](https://github.com/astorfi/TensorFlow-World) - Concise and ready-to-use TensorFlow tutorials with detailed documentation are provided.
 * [Effective Tensorflow](https://github.com/vahidk/EffectiveTensorflow) - TensorFlow howtos and best practices. Covers the basics as well as advanced topics.
+* [TensorLayer](http://tensorlayer.readthedocs.io/en/latest/user/tutorial.html) - Modular implementation for TensorFlow's official tutorials. ([CN](https://tensorlayercn.readthedocs.io/zh/latest/user/tutorial.html)).
 
 <a name="github-projects" />
 
@@ -53,6 +54,7 @@ More info [here](http://tensorflow.org).
 * [Domain Transfer Network](https://github.com/yunjey/dtn-tensorflow) - Implementation of Unsupervised Cross-Domain Image Generation
 * [Show, Attend and Tell](https://github.com/yunjey/show_attend_and_tell) - Attention Based Image Caption Generator
 * [Neural Style](https://github.com/cysmith/neural-style-tf) Implementation of Neural Style
+* [SRGAN](https://github.com/tensorlayer/srgan) - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
 * [Pretty Tensor](https://github.com/google/prettytensor) - Pretty Tensor provides a high level builder API
 * [Neural Style](https://github.com/anishathalye/neural-style) - An implementation of neural style
 * [AlexNet3D](https://github.com/denti/AlexNet3D) - An implementations of AlexNet3D. Simple AlexNet model but with 3D convolutional layers (conv3d).
@@ -64,6 +66,12 @@ More info [here](http://tensorflow.org).
 * [GoogleNet Convolutional Neural Network Groups Movie Scenes By Setting](https://github.com/agermanidis/thingscoop) - Search, filter, and describe videos based on objects, places, and other things that appear in them
 * [Neural machine translation between the writings of Shakespeare and modern English using TensorFlow](https://github.com/tokestermw/tensorflow-shakespeare) - This performs a monolingual translation, going from modern English to Shakespeare and vice-versa.
 * [Chatbot](https://github.com/Conchylicultor/DeepQA) - Implementation of ["A neural conversational model"](http://arxiv.org/abs/1506.05869)
+* [Seq2seq-Chatbot](https://github.com/tensorlayer/seq2seq-chatbot) - Chatbot in 200 lines of code
+* [DCGAN](https://github.com/tensorlayer/dcgan) - Deep Convolutional Generative Adversarial Networks
+* [GAN-CLS](https://github.com/zsdonghao/text-to-image) -Generative Adversarial Text to Image Synthesis
+* [im2im](https://github.com/zsdonghao/Unsup-Im2Im) - Unsupervised Image to Image Translation with Generative Adversarial Networks
+* [Improved CycleGAN](https://github.com/luoxier/CycleGAN_Tensorlayer) - Unpaired Image to Image Translation
+* [DAGAN](https://github.com/nebulaV/DAGAN) - Fast Compressed Sensing MRI Reconstruction
 * [Colornet - Neural Network to colorize grayscale images](https://github.com/pavelgonchar/colornet) - Neural Network to colorize grayscale images
 * [Neural Caption Generator](https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow) - Implementation of ["Show and Tell"](http://arxiv.org/abs/1411.4555)
 * [Neural Caption Generator with Attention](https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow) - Implementation of ["Show, Attend and Tell"](http://arxiv.org/abs/1502.03044)
@@ -72,6 +80,12 @@ More info [here](http://tensorflow.org).
 * [HMM in TensorFlow](https://github.com/dwiel/tensorflow_hmm) - Implementation of viterbi and forward/backward algorithms for HMM
 * [DeepOSM](https://github.com/trailbehind/DeepOSM) - Train TensorFlow neural nets with OpenStreetMap features and satellite imagery.
 * [DQN-tensorflow](https://github.com/devsisters/DQN-tensorflow) - TensorFlow implementation of DeepMind's 'Human-Level Control through Deep Reinforcement Learning' with OpenAI Gym by Devsisters.com
+* [Policy Gradient](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_atari_pong.py) - For Playing Atari Ping Pong
+* [Deep Q-Network](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_frozenlake_dqn.py) - For Playing Frozen Lake Game
+* [AC](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_cartpole_ac.py) - Actor Critic for Playing Discrete Action space Game (Cartpole)
+* [A3C](https://github.com/zsdonghao/tensorlayer/blob/master/example/tutorial_bipedalwalker_a3c_continuous_action.py) - Asynchronous Advantage Actor Critic (A3C) for Continuous Action Space (Bipedal Walker)
+* [DAGGER](https://github.com/zsdonghao/Imitation-Learning-Dagger-Torcs) - For Playing [Gym Torcs](https://github.com/ugo-nama-kun/gym_torcs)
+* [TRPO](https://github.com/jjkke88/RL_toolbox) - For Continuous and Discrete Action Space by
 * [Highway Network](https://github.com/fomorians/highway-cnn) - TensorFlow implementation of ["Training Very Deep Networks"](http://arxiv.org/abs/1507.06228) with a [blog post](https://medium.com/jim-fleming/highway-networks-with-tensorflow-1e6dfa667daa#.ndicn1i27)
 * [Sentence Classification with CNN](https://github.com/dennybritz/cnn-text-classification-tf) - TensorFlow implementation of ["Convolutional Neural Networks for Sentence Classification"](http://arxiv.org/abs/1408.5882) with a [blog post](http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/)
 * [End-To-End Memory Networks](https://github.com/domluna/memn2n) - Implementation of [End-To-End Memory Networks](http://arxiv.org/abs/1503.08895)
@@ -81,10 +95,9 @@ More info [here](http://tensorflow.org).
 * [Mnemonic Descent Method](https://github.com/trigeorgis/mdm) - Tensorflow implementation of ["Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment"](http://ibug.doc.ic.ac.uk/media/uploads/documents/trigeorgis2016mnemonic.pdf)
 * [CNN visualization using Tensorflow](https://github.com/InFoCusp/tf_cnnvis) - Tensorflow implementation of ["Visualizing and Understanding Convolutional Networks"](https://www.cs.nyu.edu/~fergus/papers/zeilerECCV2014.pdf)
 * [VGAN Tensorflow](https://github.com/Singularity42/VGAN-Tensorflow) - Tensorflow implementation for MIT ["Generating Videos with Scene Dynamics"](http://carlvondrick.com/tinyvideo/) by Vondrick et al.
-
 * [3D Convolutional Neural Networks in TensorFlow](https://github.com/astorfi/3D-convolutional-speaker-recognition) - Implementation of ["3D Convolutional Neural Networks for Speaker Verification application"](https://arxiv.org/abs/1705.09422) in TensorFlow by Torfi et al.
-
-
+* [U-Net](https://github.com/zsdonghao/u-net-brain-tumor) - For Brain Tumor Segmentation
+* [Spatial Transformer Networks](https://github.com/zsdonghao/Spatial-Transformer-Nets) - Learn the Transformation Function 
 * [Lip Reading - Cross Audio-Visual Recognition using 3D Architectures in TensorFlow](https://github.com/astorfi/lip-reading-deeplearning) - TensorFlow Implementation of ["Cross Audio-Visual Recognition in the Wild Using Deep Learning"](https://arxiv.org/abs/1706.05739) by Torfi et al.
 * [Attentive Object Tracking](https://github.com/akosiorek/hart) - Implementation of ["Hierarchical Attentive Recurrent Tracking"](https://arxiv.org/abs/1706.09262)
 * [Holographic Embeddings for Graph Completion and Link Prediction](https://github.com/laxatives/TensorFlow-TransX) - Implementation of [Holographic Embeddings of Knowledge Graphs](http://arxiv.org/abs/1510.04935)
@@ -108,6 +121,7 @@ More info [here](http://tensorflow.org).
 * [tf.contrib.learn](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/learn/python/learn) - Simplified interface for Deep/Machine Learning (now part of TensorFlow)
 * [tensorflow.rb](https://github.com/somaticio/tensorflow.rb) - TensorFlow native interface for ruby using SWIG
 * [tflearn](https://github.com/tflearn/tflearn) - Deep learning library featuring a higher-level API
+* [TensorLayer](https://github.com/tensorlayer/tensorlayer) - Deep learning and reinforcement learning library for researchers and engineers
 * [TensorFlow-Slim](https://github.com/tensorflow/models/tree/master/inception/inception/slim) - High-level library for defining models
 * [TensorFrames](https://github.com/tjhunter/tensorframes) - TensorFlow binding for Apache Spark
 * [TensorForce](https://github.com/reinforceio/tensorforce) - TensorForce: A TensorFlow library for applied reinforcement learning
@@ -151,6 +165,7 @@ More info [here](http://tensorflow.org).
 * [Distributed TensorFlow with MPI](http://arxiv.org/abs/1603.02339) - In this paper, we extend recently proposed Google TensorFlow for execution on large scale clusters using Message Passing Interface (MPI)
 * [Globally Normalized Transition-Based Neural Networks](http://arxiv.org/abs/1603.06042) - This paper describes the models behind [SyntaxNet](https://github.com/tensorflow/models/tree/master/syntaxnet).
 * [TensorFlow: A system for large-scale machine learning](https://arxiv.org/abs/1605.08695) - This paper describes the TensorFlow dataflow model in contrast to existing systems and demonstrate the compelling performance
+* [TensorLayer: A Versatile Library for Efficient Deep Learning Development](https://arxiv.org/abs/1707.08551) - This paper describes a versatile Python library that aims at helping researchers and engineers efficiently develop deep learning systems. (Winner of The Best Open Source Software Award of ACM MM 2017)
 
 <a name="blogs" />
 
@@ -199,6 +214,7 @@ More info [here](http://tensorflow.org).
 * [Getting Started with TensorFlow](https://www.packtpub.com/big-data-and-business-intelligence/getting-started-tensorflow) - Get up and running with the latest numerical computing library by Google and dive deeper into your data, by Giancarlo Zaccone
 * [Hands-On Machine Learning with Scikit-Learn and TensorFlow](http://shop.oreilly.com/product/0636920052289.do) – by Aurélien Geron, former lead of the YouTube video classification team. Covers ML fundamentals, training and deploying deep nets across multiple servers and GPUs using TensorFlow, the latest CNN, RNN and Autoencoder architectures, and Reinforcement Learning (Deep Q).
 * [Building Machine Learning Projects with Tensorflow](https://www.packtpub.com/big-data-and-business-intelligence/building-machine-learning-projects-tensorflow) – by Rodolfo Bonnin. This book covers various projects in TensorFlow that expose what can be done with TensorFlow in different scenarios. The book provides projects on training models, machine learning, deep learning, and working with various neural networks. Each project is an engaging and insightful exercise that will teach you how to use TensorFlow and show you how layers of data can be explored by working with Tensors.
+* [Deep Learning using TensorLayer](http://www.broadview.com.cn/book/5059) - by Hao Dong et al. This book covers both deep learning and the implmentation by using TensorFlow and TensorLayer.
 
 
 
@@ -223,3 +239,4 @@ More info on the [guidelines](https://github.com/jtoy/awesome-tensorflow/blob/ma
 
 * Some of the python libraries were cut-and-pasted from [vinta](https://github.com/vinta/awesome-python)
 * The few go reference I found where pulled from [this page](https://code.google.com/p/go-wiki/wiki/Projects#Machine_Learning)
+