TensorFlow implementation of a library for working with Tensor Train (TT) decomposition which is also known as Matrix Product State (MPS).
The documentation is available via readthedocs.
There are about a dozen other libraries implementing Tensor Train decomposition.
The main difference between t3f
and other libraries is that t3f
has extensive support for Riemannian optimization and that it uses TensorFlow as backend and thus supports GPUs, automatic differentiation, and batch processing. For a more detailed comparison with other libraries, see the corresponding page in the docs.
nosetests --logging-level=WARNING
The documentation is build by sphinx and hosted on readthedocs.org. To locally rebuild the documentation, install sphinx and compile the docs by
cd docs
make html
If you use T3F in your research work, we kindly ask you to cite the paper describing this library
@article{JMLR:v21:18-008,
author = {Alexander Novikov and Pavel Izmailov and Valentin Khrulkov and Michael Figurnov and Ivan Oseledets},
title = {Tensor Train Decomposition on TensorFlow (T3F)},
journal = {Journal of Machine Learning Research},
year = {2020},
volume = {21},
number = {30},
pages = {1-7},
url = {http://jmlr.org/papers/v21/18-008.html}
}