A set of matrix and tensor decomposition models implemented as PyTorch classes
Project description
PyTorchDecomp
A set of matrix and tensor decomposition models implemented as PyTorch classes
Installation
Because PyTorchDecomp is a PyPI package, please install it by pip
command as follows:
python -m venv env
pip install torchdecomp
For the other OS-specific or package-manager-specific installation, please check the README.md of PyTorch.
Usage
import torchdecomp as td
import torch
References
- Non-negative Matrix Factorization (NMF)
- Kimura, K. A Study on Efficient Algorithms for Nonnegative Matrix/Tensor Factorization, Ph.D. Thesis, 2017
- Exponent term depending on Beta parameter
- Nakano, M. et al., Convergence-guaranteed multiplicative algorithms for nonnegative matrix factorization with Beta-divergence. IEEE MLSP, 283-288, 2010
- Beta-divergence NMF and Backpropagation
Contributing
If you have suggestions for how PyTorchDecomp
could be improved, or want to report a bug, open an issue! We'd love all and any contributions.
For more, check out the Contributing Guide.
License
PyTorchDecomp has a MIT license, as found in the LICENSE file.
Authors
- Koki Tsuyuzaki
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