You have just found TensorLayer! High performance DL and RL library for industry and academic.

1. Basics Examples

TensorLayer can define models in two ways. Static model allows you to build model in a fluent way while dynamic model allows you to fully control the forward process. Please read this DOCS before you start.

2. General Computer Vision

3. Quantization Networks

4. GAN

5. Natural Language Processing

6. Reinforcement Learning

7. (Variational) Autoencoders

8. Pretrained Models

9. Data and Model Managment Tools

If you find this project useful, we would be grateful if you cite the TensorLayer paper：

@article{tensorlayer2017,
    author  = {Dong, Hao and Supratak, Akara and Mai, Luo and Liu, Fangde and Oehmichen, Axel and Yu, Simiao and Guo, Yike},
    journal = {ACM Multimedia},
    title   = {{TensorLayer: A Versatile Library for Efficient Deep Learning Development}},
    url     = {http://tensorlayer.org},
    year    = {2017}
}