TensorLayer: A Versatile Library for Efficient Deep Learning Development
Abstract
Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others. Developing a deep learning system is arduous and complex, as it involves constructing neural network architectures, managing training/trained models, tuning optimization process, preprocessing and organizing data, etc. TensorLayer is a versatile Python library that aims at helping researchers and engineers efficiently develop deep learning systems. It offers rich abstractions for neural networks, model and data management, and parallel workflow mechanism. While boosting efficiency, TensorLayer maintains both performance and scalability. TensorLayer was released in September 2016 on GitHub, and has helped people from academia and industry develop real-world applications of deep learning.
Cite
@article{arxiv.1707.08551,
title = {TensorLayer: A Versatile Library for Efficient Deep Learning Development},
author = {Hao Dong and Akara Supratak and Luo Mai and Fangde Liu and Axel Oehmichen and Simiao Yu and Yike Guo},
journal= {arXiv preprint arXiv:1707.08551},
year = {2017}
}
Comments
ACM Multimedia 2017