Tensor Train decomposition on TensorFlow

matrix-product-states, tensor-train, tensorflow
pip install t3f==1.2.0


Build Status Coverage Status

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.

Comparison with other libraries

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

Building documentation

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

  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}