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@@ -0,0 +1 @@ +/dirichletcal-0.3.dev4.tar.gz diff --git a/python-dirichletcal.spec b/python-dirichletcal.spec new file mode 100644 index 0000000..8913e01 --- /dev/null +++ b/python-dirichletcal.spec @@ -0,0 +1,336 @@ +%global _empty_manifest_terminate_build 0 +Name: python-dirichletcal +Version: 0.3.dev4 +Release: 1 +Summary: Python code for Dirichlet calibration +License: MIT License +URL: https://github.com/dirichletcal/dirichlet_python +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/fe/11/8d51ecdb233cbdfbe2d66454fa35da8b66f83ba2b5ef928e40c6893b0625/dirichletcal-0.3.dev4.tar.gz +BuildArch: noarch + + +%description +[![CI][ci:b]][ci] +[![License BSD3][license:b]][license] +![Python3.8][python:b] +[![pypi][pypi:b]][pypi] +[![codecov][codecov:b]][codecov] + +[ci]: https://github.com/dirichletcal/dirichlet_python/actions/workflows/ci.yml +[ci:b]: https://github.com/dirichletcal/dirichlet_python/workflows/CI/badge.svg +[license]: https://github.com/dirichletcal/dirichlet_python/blob/master/LICENSE.txt +[license:b]: https://img.shields.io/github/license/dirichletcal/dirichlet_python.svg +[python:b]: https://img.shields.io/badge/python-3.8-blue +[pypi]: https://badge.fury.io/py/dirichletcal +[pypi:b]: https://badge.fury.io/py/dirichletcal.svg +[codecov]: https://codecov.io/gh/dirichletcal/dirichlet_python +[codecov:b]: https://codecov.io/gh/dirichletcal/dirichlet_python/branch/master/graph/badge.svg + +# Dirichlet Calibration Python implementation + +This is a Python implementation of the Dirichlet Calibration presented in +__Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities +with Dirichlet calibration__ at NeurIPS 2019. + +# Installation + +``` +# Clone the repository +git clone git@github.com:dirichletcal/dirichlet_python.git +# Go into the folder +cd dirichlet_python +# Create a new virtual environment with Python3 +python3.8 -m venv venv +# Load the generated virtual environment +source venv/bin/activate +# Upgrade pip +pip install --upgrade pip +# Install all the dependencies +pip install -r requirements.txt +pip install --upgrade jaxlib +``` + +# Unittest + +``` +python -m unittest discover dirichletcal +``` + + +# Cite + +If you use this code in a publication please cite the following paper + + +``` +@inproceedings{kull2019dircal, + title={Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration}, + author={Kull, Meelis and Nieto, Miquel Perello and K{\"a}ngsepp, Markus and Silva Filho, Telmo and Song, Hao and Flach, Peter}, + booktitle={Advances in Neural Information Processing Systems}, + pages={12295--12305}, + year={2019} +} +``` + +# Examples + +You can find some examples on how to use this package in the folder +[examples](examples) + +# Pypi + +To push a new version to Pypi first build the package + +``` +python3.8 setup.py sdist +``` + +And then upload to Pypi with twine + +``` +twine upload dist/* +``` + +It may require user and password if these are not set in your home directory a +file __.pypirc__ + +``` +[pypi] +username = __token__ +password = pypi-yourtoken +``` + +%package -n python3-dirichletcal +Summary: Python code for Dirichlet calibration +Provides: python-dirichletcal +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-dirichletcal +[![CI][ci:b]][ci] +[![License BSD3][license:b]][license] +![Python3.8][python:b] +[![pypi][pypi:b]][pypi] +[![codecov][codecov:b]][codecov] + +[ci]: https://github.com/dirichletcal/dirichlet_python/actions/workflows/ci.yml +[ci:b]: https://github.com/dirichletcal/dirichlet_python/workflows/CI/badge.svg +[license]: https://github.com/dirichletcal/dirichlet_python/blob/master/LICENSE.txt +[license:b]: https://img.shields.io/github/license/dirichletcal/dirichlet_python.svg +[python:b]: https://img.shields.io/badge/python-3.8-blue +[pypi]: https://badge.fury.io/py/dirichletcal +[pypi:b]: https://badge.fury.io/py/dirichletcal.svg +[codecov]: https://codecov.io/gh/dirichletcal/dirichlet_python +[codecov:b]: https://codecov.io/gh/dirichletcal/dirichlet_python/branch/master/graph/badge.svg + +# Dirichlet Calibration Python implementation + +This is a Python implementation of the Dirichlet Calibration presented in +__Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities +with Dirichlet calibration__ at NeurIPS 2019. + +# Installation + +``` +# Clone the repository +git clone git@github.com:dirichletcal/dirichlet_python.git +# Go into the folder +cd dirichlet_python +# Create a new virtual environment with Python3 +python3.8 -m venv venv +# Load the generated virtual environment +source venv/bin/activate +# Upgrade pip +pip install --upgrade pip +# Install all the dependencies +pip install -r requirements.txt +pip install --upgrade jaxlib +``` + +# Unittest + +``` +python -m unittest discover dirichletcal +``` + + +# Cite + +If you use this code in a publication please cite the following paper + + +``` +@inproceedings{kull2019dircal, + title={Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration}, + author={Kull, Meelis and Nieto, Miquel Perello and K{\"a}ngsepp, Markus and Silva Filho, Telmo and Song, Hao and Flach, Peter}, + booktitle={Advances in Neural Information Processing Systems}, + pages={12295--12305}, + year={2019} +} +``` + +# Examples + +You can find some examples on how to use this package in the folder +[examples](examples) + +# Pypi + +To push a new version to Pypi first build the package + +``` +python3.8 setup.py sdist +``` + +And then upload to Pypi with twine + +``` +twine upload dist/* +``` + +It may require user and password if these are not set in your home directory a +file __.pypirc__ + +``` +[pypi] +username = __token__ +password = pypi-yourtoken +``` + +%package help +Summary: Development documents and examples for dirichletcal +Provides: python3-dirichletcal-doc +%description help +[![CI][ci:b]][ci] +[![License BSD3][license:b]][license] +![Python3.8][python:b] +[![pypi][pypi:b]][pypi] +[![codecov][codecov:b]][codecov] + +[ci]: https://github.com/dirichletcal/dirichlet_python/actions/workflows/ci.yml +[ci:b]: https://github.com/dirichletcal/dirichlet_python/workflows/CI/badge.svg +[license]: https://github.com/dirichletcal/dirichlet_python/blob/master/LICENSE.txt +[license:b]: https://img.shields.io/github/license/dirichletcal/dirichlet_python.svg +[python:b]: https://img.shields.io/badge/python-3.8-blue +[pypi]: https://badge.fury.io/py/dirichletcal +[pypi:b]: https://badge.fury.io/py/dirichletcal.svg +[codecov]: https://codecov.io/gh/dirichletcal/dirichlet_python +[codecov:b]: https://codecov.io/gh/dirichletcal/dirichlet_python/branch/master/graph/badge.svg + +# Dirichlet Calibration Python implementation + +This is a Python implementation of the Dirichlet Calibration presented in +__Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities +with Dirichlet calibration__ at NeurIPS 2019. + +# Installation + +``` +# Clone the repository +git clone git@github.com:dirichletcal/dirichlet_python.git +# Go into the folder +cd dirichlet_python +# Create a new virtual environment with Python3 +python3.8 -m venv venv +# Load the generated virtual environment +source venv/bin/activate +# Upgrade pip +pip install --upgrade pip +# Install all the dependencies +pip install -r requirements.txt +pip install --upgrade jaxlib +``` + +# Unittest + +``` +python -m unittest discover dirichletcal +``` + + +# Cite + +If you use this code in a publication please cite the following paper + + +``` +@inproceedings{kull2019dircal, + title={Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with Dirichlet calibration}, + author={Kull, Meelis and Nieto, Miquel Perello and K{\"a}ngsepp, Markus and Silva Filho, Telmo and Song, Hao and Flach, Peter}, + booktitle={Advances in Neural Information Processing Systems}, + pages={12295--12305}, + year={2019} +} +``` + +# Examples + +You can find some examples on how to use this package in the folder +[examples](examples) + +# Pypi + +To push a new version to Pypi first build the package + +``` +python3.8 setup.py sdist +``` + +And then upload to Pypi with twine + +``` +twine upload dist/* +``` + +It may require user and password if these are not set in your home directory a +file __.pypirc__ + +``` +[pypi] +username = __token__ +password = pypi-yourtoken +``` + +%prep +%autosetup -n dirichletcal-0.3.dev4 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-dirichletcal -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.3.dev4-1 +- Package Spec generated @@ -0,0 +1 @@ +977d36bf52f90520b9415c6ef1057cea dirichletcal-0.3.dev4.tar.gz |