Metadata-Version: 2.4
Name: qchaitea
Version: 0.0.15
Summary: Quantum TEA's python library for tensor network machine learning
Author: Marco Ballarin, Massimo Colombo, Alberto Coppi, Timo Felser, Guillermo Muñoz Menés, Daniel Jaschke, Marco Trenti
Project-URL: Homepage, https://www.quantumtea.it/
Project-URL: Repository, https://baltig.infn.it/quantum_tea/py_api_quantum_chai_tea.git
Project-URL: Documentation, https://quantum_tea.baltig-pages.infn.it/py_api_quantum_chai_tea/
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: Apache Software License
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: scikit-learn<1.6.0,>=1.5.0
Requires-Dist: hilbertcurve==2.0.5
Requires-Dist: qtealeaves<1.13,>=1.7.30
Requires-Dist: qredtea<0.5,>=0.3.14
Requires-Dist: torch<3.0,>2.0
Requires-Dist: autograd<2.0,>=1.8.0
Provides-Extra: cqa
Requires-Dist: pre-commit; extra == "cqa"
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Requires-Dist: black==24.4.2; extra == "cqa"
Requires-Dist: pylint==3.2.4; extra == "cqa"
Provides-Extra: tests
Requires-Dist: pytest; extra == "tests"
Requires-Dist: pytest-cov; extra == "tests"
Requires-Dist: pytest-subtests; extra == "tests"
Provides-Extra: docs
Requires-Dist: sphinx; extra == "docs"
Requires-Dist: sphinx-gallery; extra == "docs"
Requires-Dist: sphinx_rtd_theme; extra == "docs"
Provides-Extra: dev
Requires-Dist: qchaitea[cqa]; extra == "dev"
Requires-Dist: qchaitea[tests]; extra == "dev"
Dynamic: license-file

[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

qchaitea
========

The quantum chai tea library of Quantum TEA provides methods to handle machine learning
datasets and use tensor network machine learning

Documentation
=============

[Here](https://quantum_tea_internal.baltig-pages.infn.it/py_api_quantum_chai_tea/)
is the documentation. The documentation can also be built locally via sphinx.


License
=======

The project ``qchaitea`` is hosted at the repository
``https://baltig.infn.it/quantum_tea_internal/py_api_quantum_chai_tea.git``,
and is licensed under the following license:

[Apache License 2.0](LICENSE)

The license applies to the files of this project as indicated
in the header of each file, but not its dependencies.

Installation
============

The qchaitea library is never used as stand-alone package; it replaces
the tensor backend for one of the quantum TEA applications in agreement
with a qtealeaves version. Therefore, the minimal use-case to explore
the library is together with qtealeaves. Moreover, it can be used as
well with qmatchatea.

Local installation via pip
--------------------------

The package is available via a local pip installation as `pip install .`,
i.e., after cloning the repository.

Dependencies
------------

The python dependencies can be found in the [``pyproject.toml``](pyproject.toml) file
and are required independently of the following use-cases. Optional dependencies are 
required for specific use-cases, as indicated in the file.


Project history
===============

The project merges the effort of the Leto project with the aim to access the
tensor network machine learning algorithms of qtealeaves in a workflow adapted
to machine learning problems.

The Leto project originates in the master thesis of Massimo Colombo at the
tensor ai solutions GmbH under the supervision of Marco Trenti and Timo Felser.
Leto is a figure in Greek mythology, known as the Titaness and mother of the twin
deities Apollo and Artemis. She is often associated with motherhood, protectiveness,
and modesty. Leto faced challenges, including persecution by the jealous goddess
Hera during her pregnancy. She found refuge on the island of Delos, where she gave
birth to Apollo and Artemis. Leto is venerated as a protective and nurturing deity,
symbolizing the strength of motherhood in Greek mythology.
This thesis contained the implementation of 'convolutional' Tensor Networks layers.
 
