%global _empty_manifest_terminate_build 0
Name:       onnxruntime
Version:    1.17.1
Release:    1
Summary:    Open Source Neural Network Inference Engine
License:    MIT
URL:        https://github.com/microsoft/onnxruntime
Source0:    https://openi.pcl.ac.cn/JunJun-Liu/onnx-runtime/onnxruntime-1.17.1.tar.gz

BuildRequires:  gcc-c++
BuildRequires:  python3-devel
BuildRequires:  cmake
BuildRequires:  python3-pytorch >= 2.0.1
Requires:   python3-numpy
Requires:   python3-pytorch >= 2.0.1

%description
ONNX Runtime is a performance-focused inference engine for ONNX (Open Neural Network Exchange) models.
These models can come from a variety of frameworks, such as TensorFlow, PyTorch, or Keras.
ONNX Runtime provides an easy way to run models in a fast and efficient manner with minimal dependencies.

%prep
%setup -q -n onnxruntime-1.17.1

%build
export CFLAGS+=" -Wno-error=maybe-uninitialized -Wno-error=uninitialized -Wno-error=restrict -fPIC"
export CXXFLAGS+=" -Wno-error=maybe-uninitialized -Wno-error=uninitialized -Wno-error=restrict -fPIC"
mkdir -p build && cd build
cmake ../cmake -DCMAKE_BUILD_TYPE=Release \
         -DCMAKE_INSTALL_PREFIX=%{_prefix} \
         -DCMAKE_C_FLAGS_RELEASE="%{optflags}" \
         -DCMAKE_CXX_FLAGS_RELEASE="%{optflags}"
%make_build

%install
%make_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}
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
%doc *.md
%license LICENSE
%{_bindir}/*
%{python3_sitearch}/*

%changelog
* Wed Feb 28 2024 JunjunLiu <172074482@qq.com> - 1.17.1-1
- Initial package version for ONNX Runtime 1.17.1