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diff --git a/python-pyro-ppl.spec b/python-pyro-ppl.spec new file mode 100644 index 0000000..dfb33f7 --- /dev/null +++ b/python-pyro-ppl.spec @@ -0,0 +1,84 @@ +%global _empty_manifest_terminate_build 0 + +Name: python-pyro-ppl +Version: 1.8.6 +Release: 1 +Summary: Deep universal probabilistic programming with Python and PyTorch +License: Apache-2.0 +URL: https://github.com/pyro-ppl/pyro +Source0: https://github.com/pyro-ppl/pyro/archive/refs/tags/%{version}.tar.gz#/%{name}-%{version}.tar.gz + +Requires: python3-numpy +Requires: python3-opt-einsum +Requires: python3-pytorch +Requires: python3-tqdm + +%description +Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notably, it was designed with these principles in mind: +- Universal: Pyro is a universal PPL - it can represent any computable probability distribution. +- Scalable: Pyro scales to large data sets with little overhead compared to hand-written code. +- Minimal: Pyro is agile and maintainable. It is implemented with a small core of powerful, composable abstractions. +- Flexible: Pyro aims for automation when you want it, control when you need it. This is accomplished through high-level + abstractions to express generative and inference models, while allowing experts easy-access to customize inference. + +%package -n python3-pyro-ppl +Summary: Deep universal probabilistic programming with Python and PyTorch +Provides: python-pyro-ppl + +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-setuptools_scm +BuildRequires: python3-pbr +BuildRequires: python3-pip +BuildRequires: python3-wheel + +%description -n python3-pyro-ppl +Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notably, it was designed with these principles in mind: +- Universal: Pyro is a universal PPL - it can represent any computable probability distribution. +- Scalable: Pyro scales to large data sets with little overhead compared to hand-written code. +- Minimal: Pyro is agile and maintainable. It is implemented with a small core of powerful, composable abstractions. +- Flexible: Pyro aims for automation when you want it, control when you need it. This is accomplished through high-level + abstractions to express generative and inference models, while allowing experts easy-access to customize inference. + +%package help +Summary: Development documents and examples for python-pyro-ppl +Provides: python3-pyro-ppl-doc + +%description help +Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notably, it was designed with these principles in mind: +- Universal: Pyro is a universal PPL - it can represent any computable probability distribution. +- Scalable: Pyro scales to large data sets with little overhead compared to hand-written code. +- Minimal: Pyro is agile and maintainable. It is implemented with a small core of powerful, composable abstractions. +- Flexible: Pyro aims for automation when you want it, control when you need it. This is accomplished through high-level + abstractions to express generative and inference models, while allowing experts easy-access to customize inference. + +%prep +%autosetup -p1 -n pyro-%{version} + +%build +%pyproject_build + +%install +%pyproject_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +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}/doclist.lst . + +%files -n python3-pyro-ppl +%doc *.md +%license LICENSE.md +%{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Sun Jan 28 2024 Binshuo Zu <274620705z@gmail.com> - 1.8.6-1 +- Package init |