Document type
Journal articles
Document subtype
Full paper
Title
TensorX: Extensible API for Neural Network Model Design and Deployment
Participants in the publication
Davide Nunes (Author)
Dep. Informática
Dep. Informática
LabMAg
BioISI
Luis Antunes (Author)
Dep. Informática
LabMAg
BioISI
LASIGE
Summary
TensorX is a Python library for prototyping, design, and deployment of complex neural network models in TensorFlow. A special emphasis is put on ease of use, performance, and API consistency. It aims to make available high-level components like neural network layers that are, in effect, stateful functions, easy to compose and reuse. Its architecture allows for the expression of patterns commonly found when building neural network models either on research or industrial settings. Incorporating ideas from several other deep learning libraries, it makes it easy to use components commonly found in state-of-the-art models. The library design mixes functional dataflow computation graphs with object-oriented neural network building blocks. TensorX combines the dynamic nature of Python with the high-performance GPU-enabled operations of TensorFlow.\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\nThis library has minimal core dependencies (TensorFlow and NumPy) and is distributed under Apache License 2.0 licence, encouraging its use in both an academic and commercial settings. Full documentation, source code, and binaries can be found in https://tensorx.org/.
Date of Submisson/Request
2020-12-29
Date of Acceptance
2021-01-02
Date of Publication
2021-01-02
Institution
FACULDADE DE CIÊNCIAS DA UNIVERSIDADE DE LISBOA
Where published
CoRR, December 2020
Publication Identifiers
Document Identifiers
URL -
https://arxiv.org/abs/2012.14539
DOI -
https://doi.org/10.48550/arXiv.2012.14539