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Papers

TensorLayer: A Versatile Library for Efficient Deep Learning Development

2017-07-26 · Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo

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.

📄 PDF Abstract BibTeX arXiv:1707.08551

Code (2)

akaraspt/tl_paper 공식 구현 tf
zsdonghao/tensorlayer 공식 구현 tf

Tasks

Deep LearningManagement

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