%global _empty_manifest_terminate_build 0
Name:		python-skl2onnx
Version:	1.14.0
Release:	1
Summary:	Convert scikit-learn models to ONNX
License:	Apache License v2.0
URL:		https://github.com/onnx/sklearn-onnx
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/e4/3b/5ef1025362a0408916e5a625a3d876f1b9004318c8cc4d6b9963f65e4822/skl2onnx-1.14.0.tar.gz
BuildArch:	noarch

Requires:	python3-onnx
Requires:	python3-scikit-learn
Requires:	python3-onnxconverter-common

%description
## Introduction
*sklearn-onnx* converts [scikit-learn](https://scikit-learn.org/stable/) models to [ONNX](https://github.com/onnx/onnx).
Once in the ONNX format, you can use tools like [ONNX Runtime](https://github.com/Microsoft/onnxruntime) for high performance scoring.
All converters are tested with [onnxruntime](https://onnxruntime.ai/).

## Documentation
Full documentation including tutorials is available at [https://onnx.ai/sklearn-onnx/](https://onnx.ai/sklearn-onnx/).
[Supported scikit-learn Models](https://onnx.ai/sklearn-onnx/supported.html)
Last supported opset is 15.

You may also find answers in [existing issues](https://github.com/onnx/sklearn-onnx/issues?utf8=%E2%9C%93&q=is%3Aissue)
or submit a new one.

## Installation
You can install from [PyPi](https://pypi.org/project/skl2onnx/):
```
pip install skl2onnx
```
Or you can install from the source with the latest changes.
```
pip install git+https://github.com/onnx/sklearn-onnx.git
```

## Contribute
We welcome contributions in the form of feedback, ideas, or code.

## License
[Apache License v2.0](LICENSE)


%package -n python3-skl2onnx
Summary:	Convert scikit-learn models to ONNX
Provides:	python-skl2onnx
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-skl2onnx
## Introduction
*sklearn-onnx* converts [scikit-learn](https://scikit-learn.org/stable/) models to [ONNX](https://github.com/onnx/onnx).
Once in the ONNX format, you can use tools like [ONNX Runtime](https://github.com/Microsoft/onnxruntime) for high performance scoring.
All converters are tested with [onnxruntime](https://onnxruntime.ai/).

## Documentation
Full documentation including tutorials is available at [https://onnx.ai/sklearn-onnx/](https://onnx.ai/sklearn-onnx/).
[Supported scikit-learn Models](https://onnx.ai/sklearn-onnx/supported.html)
Last supported opset is 15.

You may also find answers in [existing issues](https://github.com/onnx/sklearn-onnx/issues?utf8=%E2%9C%93&q=is%3Aissue)
or submit a new one.

## Installation
You can install from [PyPi](https://pypi.org/project/skl2onnx/):
```
pip install skl2onnx
```
Or you can install from the source with the latest changes.
```
pip install git+https://github.com/onnx/sklearn-onnx.git
```

## Contribute
We welcome contributions in the form of feedback, ideas, or code.

## License
[Apache License v2.0](LICENSE)


%package help
Summary:	Development documents and examples for skl2onnx
Provides:	python3-skl2onnx-doc
%description help
## Introduction
*sklearn-onnx* converts [scikit-learn](https://scikit-learn.org/stable/) models to [ONNX](https://github.com/onnx/onnx).
Once in the ONNX format, you can use tools like [ONNX Runtime](https://github.com/Microsoft/onnxruntime) for high performance scoring.
All converters are tested with [onnxruntime](https://onnxruntime.ai/).

## Documentation
Full documentation including tutorials is available at [https://onnx.ai/sklearn-onnx/](https://onnx.ai/sklearn-onnx/).
[Supported scikit-learn Models](https://onnx.ai/sklearn-onnx/supported.html)
Last supported opset is 15.

You may also find answers in [existing issues](https://github.com/onnx/sklearn-onnx/issues?utf8=%E2%9C%93&q=is%3Aissue)
or submit a new one.

## Installation
You can install from [PyPi](https://pypi.org/project/skl2onnx/):
```
pip install skl2onnx
```
Or you can install from the source with the latest changes.
```
pip install git+https://github.com/onnx/sklearn-onnx.git
```

## Contribute
We welcome contributions in the form of feedback, ideas, or code.

## License
[Apache License v2.0](LICENSE)


%prep
%autosetup -n skl2onnx-1.14.0

%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-skl2onnx -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Mon Apr 10 2023 Python_Bot <Python_Bot@openeuler.org> - 1.14.0-1
- Package Spec generated