SOTAVerified

TedNet: A Pytorch Toolkit for Tensor Decomposition Networks

2021-04-11Code Available1· sign in to hype

Yu Pan, Maolin Wang, Zenglin Xu

Code Available — Be the first to reproduce this paper.

Reproduce

Code

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.

Tasks

Reproductions