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arXiv · 2104.05018

TedNet: A Pytorch Toolkit for Tensor Decomposition Networks

Yu Pan·Maolin Wang·Zenglin Xu
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Abstract

Tensor Decomposition Networks (TDNs) prevail for their inherent compact architectures. To give more researchers a flexible way to exploit TDNs, we present a Pytorch toolkit named TedNet. TedNet implements 5 kinds of tensor decomposition(i.e., CANDECOMP/PARAFAC (CP), Block-Term Tucker (BTT), Tucker-2, Tensor Train (TT) and Tensor Ring (TR) on traditional deep neural layers, the convolutional layer and the fully-connected layer. By utilizing the basic layers, it is simple to construct a variety of TDNs. TedNet is available at https://github.com/tnbar/tednet.

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Yu Pan, Maolin Wang, Zenglin Xu. 2021-04-11. TedNet: A Pytorch Toolkit for Tensor Decomposition Networks. https://doi.org/10.1016/j.neucom.2021.10.064

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