Metadata-Version: 2.1
Name: torchkge
Version: 0.11.1
Summary: Knowledge Graph embedding in Python and Pytorch.
Home-page: https://github.com/torchkge-team/torchkge
Author: TorchKGE Developers
Author-email: aboschin@enst.fr
License: BSD license
Keywords: torchkge
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.7
Requires-Dist: torch (==1.3.0)
Requires-Dist: torchvision
Requires-Dist: tqdm (==4.36.1)
Requires-Dist: pandas

========
TorchKGE
========

.. image:: https://graphs.telecom-paristech.fr/images/logo_torchKGE_small.png
    :align: right
    :width: 100px
    :alt: logo torchkge

.. image:: https://img.shields.io/pypi/v/torchkge.svg
        :target: https://pypi.python.org/pypi/torchkge

.. image:: https://travis-ci.org/torchkge-team/torchkge.svg?branch=master
    :target: https://travis-ci.org/torchkge-team/torchkge

.. image:: https://readthedocs.org/projects/torchkge/badge/?version=latest
    :target: https://torchkge.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status

.. image:: https://pyup.io/repos/github/torchkge-team/torchkge/shield.svg
     :target: https://pyup.io/repos/github/torchkge-team/torchkge/
     :alt: Updates



TorchKGE: Knowledge Graph embedding in Python and Pytorch.


* Free software: BSD license
* Documentation: https://torchkge.readthedocs.io.


=======
History
=======

0.10.0 (2019-07-19)
-------------------

* Implemented Triplet Classification evaluation method
* Added Negative Sampler objects to standardize negative sampling methods.


0.9.0 (2019-07-17)
------------------

* Implemented HolE model (Nickel et al.)
* Implemented ComplEx model (Trouillon et al.)
* Implemented ANALOGY model (Liu et al.)
* Added knowledge graph splitting into train, validation and test instead of just train and test.

0.8.0 (2019-07-09)
------------------

* Implemented Bernoulli negative sampling as in Wang et al. paper on TransH (2014).

0.7.0 (2019-07-01)
------------------

* Implemented Mean Reciprocal Rank measure of performance.
* Implemented Logistic Loss.
* Changed implementation of margin loss to use torch methods.

0.6.0 (2019-06-25)
------------------

* Implemented DistMult

0.5.0 (2019-06-24)
------------------

* Changed implementation of LinkPrediction ranks by moving functions to model methods.
* Implemented RESCAL.


0.4.0 (2019-05-15)
------------------

* Fixed a major bug/problem in the Evaluation protocol of LinkPrediction.

0.3.1 (2019-05-10)
------------------

* Minor bug fixes in the various normalization functions.

0.3.0 (2019-05-09)
------------------

* Fixed CUDA support.

0.2.0 (2019-05-07)
------------------

* Added support for filtered performance measures.

0.1.7 (2019-04-03)
------------------

* First real release on PyPI.

0.1.0 (2019-04-01)
------------------

* First release on PyPI.


