#
# spec file for package armnn
#
# Copyright (c) 2018 SUSE LINUX GmbH, Nuernberg, Germany.
#
# All modifications and additions to the file contributed by third parties
# remain the property of their copyright owners, unless otherwise agreed
# upon. The license for this file, and modifications and additions to the
# file, is the same license as for the pristine package itself (unless the
# license for the pristine package is not an Open Source License, in which
# case the license is the MIT License). An "Open Source License" is a
# license that conforms to the Open Source Definition (Version 1.9)
# published by the Open Source Initiative.

# Please submit bugfixes or comments via http://bugs.opensuse.org/
#

%define target @BUILD_FLAVOR@%{nil}

# Disable LTO until lto link is fixed - https://github.com/ARM-software/armnn/issues/251
%define _lto_cflags %{nil}

%if "%{target}" != ""
%define package_suffix -%{target}
%endif

# Compute library has neon enabled for aarch64 only
%ifarch aarch64
%bcond_without compute_neon
%else
%bcond_with compute_neon
%endif

%if "%{target}" == "opencl"
%bcond_without compute_cl
%else
%bcond_with compute_cl
%endif

# stb-devel is available on Leap 15.1+
%if 0%{?suse_version} > 1500 || ( 0%{?sle_version} > 150000 && 0%{?is_opensuse} )
%bcond_without armnn_tests
%else
%bcond_with armnn_tests
%endif

# Extra tests require opencv(3)-devel, but it is broken for Leap 15.x - boo#1154091
%if 0%{?suse_version} > 1500
%bcond_without armnn_extra_tests
%else
%bcond_with armnn_extra_tests
%endif

# flatbuffers-devel is available on Leap 15.2+
%if 0%{?suse_version} > 1500 || ( 0%{?sle_version} >= 150200 && 0%{?is_opensuse} )
%bcond_without armnn_flatbuffers
%else
%bcond_with armnn_flatbuffers
%endif

# Enable CAFFE
%bcond_without armnn_caffe

# Enable TensorFlow only on TW aarch64 and x86_64 (TF fails to build on Leap 15.x and on armv7 TW)
%if 0%{?suse_version} > 1500
%ifarch aarch64 x86_64
%bcond_without armnn_tf
%else
%bcond_with armnn_tf
%endif # ifarch
%else  # suse_version
%bcond_with armnn_tf
%endif # suse_version

# ONNX is available on Tumbleweed only
%if 0%{?suse_version} > 1500
%bcond_without armnn_onnx
%else
%bcond_with armnn_onnx
%endif

%define version_major 19
%define version_minor 08

Name:           armnn%{?package_suffix}
Version:        %{version_major}.%{version_minor}
Release:        0
Summary:        Arm NN SDK enables machine learning workloads on power-efficient devices
License:        MIT
Group:          Development/Libraries/Other
Url:            https://developer.arm.com/products/processors/machine-learning/arm-nn
Source0:        https://github.com/ARM-software/armnn/archive/v%{version}.tar.gz#/armnn-%{version}.tar.gz
Source1:        armnn-rpmlintrc
# PATCH-FIX-UPSTREAM - https://github.com/ARM-software/armnn/issues/275
Patch1:         armnn-generate-versioned-library.patch
# Patch: http://arago-project.org/git/?p=meta-arago.git;a=blob;f=meta-arago-extras/recipes-support/armnn/armnn/0007-enable-use-of-arm-compute-shared-library.patch;hb=master
Patch2:         0007-enable-use-of-arm-compute-shared-library.patch
# PATCH-FIX-UPSTREAM - https://github.com/ARM-software/armnn/issues/274
Patch3:         armnn-fix_boost.patch
# PATCH-FIX-UPSTREAM - https://github.com/ARM-software/armnn/issues/266
Patch4:         armnn-fix_arm32_dep.patch 
Patch5:         armnn-fix_arm32.patch 
# https://github.com/ARM-software/armnn/issues/207
# FIXME: remove this patch once *.pb.cc files are packaged properly in tensorflow-devel - https://github.com/ARM-software/armnn/issues/269
Patch100:       armnn-fix_tensorflow_link.patch
# PATCHES to add downstream ArmnnExamples binary - https://layers.openembedded.org/layerindex/recipe/87610/
Patch200:       0003-add-more-test-command-line-arguments.patch
Patch201:       0005-add-armnn-mobilenet-test-example.patch
Patch202:       0006-armnn-mobilenet-test-example.patch
Patch203:       0009-command-line-options-for-video-port-selection.patch
Patch204:       0010-armnnexamples-update-for-19.08-modifications.patch
Patch205:       armnn-fix_find_opencv.patch
%if 0%{?suse_version} < 1330
BuildRequires:  boost-devel >= 1.59
%else
BuildRequires:  libboost_filesystem-devel >= 1.59
BuildRequires:  libboost_log-devel >= 1.59
BuildRequires:  libboost_program_options-devel >= 1.59
BuildRequires:  libboost_system-devel >= 1.59
BuildRequires:  libboost_test-devel >= 1.59
BuildRequires:  libboost_thread-devel >= 1.59
%endif
%if %{with armnn_caffe}
BuildRequires:  caffe-devel
%endif
BuildRequires:  cmake >= 3.0.2
BuildRequires:  ComputeLibrary-devel >= 19.08
BuildRequires:  gcc-c++
%if %{with armnn_flatbuffers}
BuildRequires:  flatbuffers-devel
BuildRequires:  tensorflow-lite-devel
%endif
%if %{with compute_cl}
# Mesa-libOpenCl is required for tests
BuildRequires:  Mesa-libOpenCL
BuildRequires:  ocl-icd-devel
BuildRequires:  opencl-cpp-headers
%endif
%if %{with armnn_extra_tests}
%if 0%{?suse_version} > 1500
BuildRequires:  opencv3-devel
%else
BuildRequires:  opencv-devel
%endif
%endif
%if %{with armnn_onnx}
BuildRequires:  python3-onnx-devel
%endif
BuildRequires:  protobuf-devel
BuildRequires:  python-rpm-macros
%if %{with armnn_tests}
BuildRequires:  stb-devel
%endif
%if %{with armnn_tf}
BuildRequires:  tensorflow-devel
%endif
BuildRequires:  valgrind-devel
%if %{with compute_cl}
Recommends:     Mesa-libOpenCL
%endif
# Make armnn-opencl pulls lib*-opencl, and armnn pulls non opencl libs
Requires:       libarmnn%{version_major}%{?package_suffix} = %{version}
%if %{with armnn_flatbuffers}
Requires:       libarmnnSerializer%{version_major}%{?package_suffix} = %{version}
Requires:       libarmnnTfLiteParser%{version_major}%{?package_suffix} = %{version}
%endif
%if %{with armnn_caffe}
Requires:       libarmnnCaffeParser%{version_major}%{?package_suffix} = %{version}
%endif
%if %{with armnn_onnx}
Requires:       libarmnnOnnxParser%{version_major}%{?package_suffix} = %{version}
%endif
%if %{with armnn_tf}
Requires:       libarmnnTfParser%{version_major}%{?package_suffix} = %{version}
%endif
# Make sure we do not install both openCL and non-openCL (CPU only) versions.
%if "%{target}" == "opencl"
Conflicts:      armnn
%else
Conflicts:      armnn-opencl
%endif
BuildRoot:      %{_tmppath}/%{name}-%{version}-build

%description
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

%package devel
Summary:        Development headers and libraries for armnn
Group:          Development/Libraries/C and C++
# Make sure we do not install both openCL and non-openCL (CPU only) versions.
%if "%{target}" == "opencl"
Conflicts:      armnn-devel
%else
Conflicts:      armnn-opencl-devel
%endif
Requires:       %{name} = %{version}
Requires:       libarmnn%{version_major}%{?package_suffix} = %{version}
%if %{with armnn_flatbuffers}
Requires:       libarmnnSerializer%{version_major}%{?package_suffix} = %{version}
Requires:       libarmnnTfLiteParser%{version_major}%{?package_suffix} = %{version}
%endif
%if %{with armnn_caffe}
Requires:       libarmnnCaffeParser%{version_major}%{?package_suffix} = %{version}
%endif
%if %{with armnn_onnx}
Requires:       libarmnnOnnxParser%{version_major}%{?package_suffix} = %{version}
%endif
%if %{with armnn_tf}
Requires:       libarmnnTfParser%{version_major}%{?package_suffix} = %{version}
%endif

%description devel
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

This package contains the development libraries and headers for armnn.

%if %{with armnn_extra_tests}
%package -n %{name}-extratests
Summary:        Additionnal downstream tests for Arm NN
Group:          Development/Libraries/C and C++
# Make sure we do not install both openCL and non-openCL (CPU only) versions.
%if "%{target}" == "opencl"
Conflicts:      armnn-extratests
%else
Conflicts:      armnn-opencl-extratests
%endif
Requires:       %{name}

%description -n %{name}-extratests
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

This package contains additionnal downstream tests for armnn.
%endif

%package -n libarmnn%{version_major}%{?package_suffix}
%if "%{target}" == "opencl"
Conflicts:      libarmnn%{version_major}
%else
Conflicts:      libarmnn%{version_major}-opencl
%endif
Summary:        libarmnn from armnn
Group:          Development/Libraries/C and C++

%description -n libarmnn%{version_major}%{?package_suffix}
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

This package contains the libarmnn library from armnn.

%if %{with armnn_flatbuffers}
%package -n libarmnnSerializer%{version_major}%{?package_suffix}
%if "%{target}" == "opencl"
Conflicts:      libarmnnSerializer%{version_major}
%else
Conflicts:      libarmnnSerializer%{version_major}-opencl
%endif
Summary:        libarmnnSerializer from armnn
Group:          Development/Libraries/C and C++

%description -n libarmnnSerializer%{version_major}%{?package_suffix}
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

This package contains the libarmnnSerializer library from armnn.

%package -n libarmnnTfLiteParser%{version_major}%{?package_suffix}
%if "%{target}" == "opencl"
Conflicts:      libarmnnTfLiteParser%{version_major}
%else
Conflicts:      libarmnnTfLiteParser%{version_major}-opencl
%endif
Summary:        libarmnnTfLiteParser from armnn
Group:          Development/Libraries/C and C++

%description -n libarmnnTfLiteParser%{version_major}%{?package_suffix}
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

This package contains the libarmnnTfLiteParser library from armnn.
%endif

%if %{with armnn_tf}
%package -n libarmnnTfParser%{version_major}%{?package_suffix}
%if "%{target}" == "opencl"
Conflicts:      libarmnnTfParser%{version_major}
%else
Conflicts:      libarmnnTfParser%{version_major}-opencl
%endif
Summary:        libarmnnTfParser from armnn
Group:          Development/Libraries/C and C++

%description -n libarmnnTfParser%{version_major}%{?package_suffix}
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

This package contains the libarmnnTfParser library from armnn.
%endif

%if %{with armnn_caffe}
%package -n libarmnnCaffeParser%{version_major}%{?package_suffix}
%if "%{target}" == "opencl"
Conflicts:      libarmnnCaffeParser%{version_major}
%else
Conflicts:      libarmnnCaffeParser%{version_major}-opencl
%endif
Summary:        libarmnnCaffeParser from armnn
Group:          Development/Libraries/C and C++

%description -n libarmnnCaffeParser%{version_major}%{?package_suffix}
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

This package contains the libarmnnCaffeParser library from armnn.
%endif

%if %{with armnn_onnx}
%package -n libarmnnOnnxParser%{version_major}%{?package_suffix}
%if "%{target}" == "opencl"
Conflicts:      libarmnnOnnxParser%{version_major}
%else
Conflicts:      libarmnnOnnxParser%{version_major}-opencl
%endif
Summary:        libarmnnOnnxParser from armnn
Group:          Development/Libraries/C and C++

%description -n libarmnnOnnxParser%{version_major}%{?package_suffix}
Arm NN is an inference engine for CPUs, GPUs and NPUs. 
It bridges the gap between existing NN frameworks and the underlying IP. 
It enables efficient translation of existing neural network frameworks, 
such as TensorFlow and Caffe, allowing them to run efficiently – without 
modification – across Arm Cortex CPUs and Arm Mali GPUs.

This package contains the libarmnnOnnxParser library from armnn.
%endif

%prep
%setup -q -n armnn-%{version}
%patch1 -p1
%patch2 -p1
%patch3 -p1
%patch4 -p1
%patch5 -p1
%patch100 -p1
%patch200 -p1
%patch201 -p1
%patch202 -p1
%patch203 -p1
%patch204 -p1
%patch205 -p1
# Boost fixes for dynamic linking
sed -i 's/add_definitions("-DBOOST_ALL_NO_LIB")/add_definitions("-DBOOST_ALL_DYN_LINK")/'  ./cmake/GlobalConfig.cmake
sed -i 's/set(Boost_USE_STATIC_LIBS ON)/set(Boost_USE_STATIC_LIBS OFF)/' ./cmake/GlobalConfig.cmake
sed -i 's/find_package(Boost 1.59 REQUIRED COMPONENTS unit_test_framework system filesystem log program_options)/find_package(Boost 1.59 REQUIRED COMPONENTS unit_test_framework system filesystem log thread program_options)/' ./cmake/GlobalConfig.cmake
# Build fix
sed -i 's/-Wsign-conversion//' ./cmake/GlobalConfig.cmake

%build
%if %{with armnn_onnx}
mkdir onnx_deps
PROTO=$(find %{_libdir} -name onnx.proto)
protoc $PROTO --proto_path=. --proto_path=%{_includedir} --proto_path=$(dirname $(find %{_libdir} -name onnx)) --cpp_out=./onnx_deps
%endif
%cmake \
  -DCMAKE_CXX_FLAGS:STRING="%{optflags} -pthread" \
  -DBOOST_LIBRARYDIR=%{_libdir} \
%if %{with armnn_caffe}
  -DBUILD_CAFFE_PARSER=ON \
%else
  -DBUILD_CAFFE_PARSER=OFF \
%endif
  -DCAFFE_GENERATED_SOURCES=%{_includedir}/ \
%if %{with armnn_onnx}
  -DBUILD_ONNX_PARSER=ON \
  -DONNX_GENERATED_SOURCES=../onnx_deps/ \
%else
  -DBUILD_ONNX_PARSER=OFF \
%endif
%if %{with armnn_flatbuffers}
  -DBUILD_ARMNN_SERIALIZER=ON \
  -DFLATC_DIR=%{_bindir} \
  -DFLATBUFFERS_INCLUDE_PATH=%{_includedir} \
  -DBUILD_ARMNN_QUANTIZER=ON \
  -DBUILD_TF_LITE_PARSER=ON \
  -DTF_LITE_SCHEMA_INCLUDE_PATH=%{_includedir}/tensorflow/lite/schema/ \
%else
  -DBUILD_ARMNN_SERIALIZER=OFF \
  -DBUILD_ARMNN_QUANTIZER=OFF \
  -DBUILD_TF_LITE_PARSER=OFF \
%endif
%if %{with armnn_tf}
  -DBUILD_TF_PARSER=ON \
  -DTF_GENERATED_SOURCES=%{python3_sitelib}/tensorflow/include/ \
%else
  -DBUILD_TF_PARSER=OFF \
%endif
%if %{with compute_neon} || %{with compute_cl}
  -DARMCOMPUTE_INCLUDE=%{_includedir} \
  -DHALF_INCLUDE=%{_includedir}/half \
  -DARMCOMPUTE_BUILD_DIR=%{_libdir} \
  -DARMCOMPUTE_ROOT=/usr \
%endif
%if %{with compute_neon}
  -DARMCOMPUTENEON=ON \
%else
  -DARMCOMPUTENEON=OFF \
%endif
%if %{with compute_cl}
  -DARMCOMPUTECL=ON \
  -DOPENCL_INCLUDE=%{_includedir} \
%else
  -DARMCOMPUTECL=OFF \
%endif
  -DTHIRD_PARTY_INCLUDE_DIRS=%{_includedir} \
%if %{with armnn_flatbuffers}
  -DBUILD_SAMPLE_APP=ON \
%else
  -DBUILD_SAMPLE_APP=OFF \
%endif
%if %{with armnn_tests}
  -DBUILD_UNIT_TESTS=ON \
  -DBUILD_TESTS=ON \
%else
  -DBUILD_UNIT_TESTS=OFF \
  -DBUILD_TESTS=OFF \
%endif
%if %{with armnn_extra_tests}
  -DBUILD_ARMNN_EXAMPLES=ON
%else
  -DBUILD_ARMNN_EXAMPLES=OFF
%endif

%if %{suse_version} > 1500
%cmake_build
%else
%make_jobs
%endif
%if %{with armnn_tests}
pushd tests/
%if %{suse_version} > 1500
%cmake_build
%else
%make_jobs
%endif
popd
%endif

%install
%cmake_install
%if %{with armnn_tests}
# Install tests manually
install -d %{buildroot}%{_bindir}
CP_ARGS="-Prf --preserve=mode,timestamps --no-preserve=ownership" \
find ./build/tests -maxdepth 1 -type f -executable -exec cp $CP_ARGS {} %{buildroot}%{_bindir} \;
%endif
%if %{with armnn_flatbuffers}
# Install Sample app
cp $CP_ARGS ./build/samples/SimpleSample %{buildroot}%{_bindir}
%endif

# openCL UnitTests are failing in OBS due to the lack of openCL device
%if %{without compute_cl} && %{with armnn_tests}
%check
# Run tests
LD_LIBRARY_PATH="$(pwd)/build/" \
./build/UnitTests
%endif

%post -n libarmnn%{version_major}%{?package_suffix} -p /sbin/ldconfig
%postun -n libarmnn%{version_major}%{?package_suffix} -p /sbin/ldconfig

%if %{with armnn_flatbuffers}
%post -n libarmnnSerializer%{version_major}%{?package_suffix} -p /sbin/ldconfig
%postun -n libarmnnSerializer%{version_major}%{?package_suffix} -p /sbin/ldconfig

%post -n libarmnnTfLiteParser%{version_major}%{?package_suffix} -p /sbin/ldconfig
%postun -n libarmnnTfLiteParser%{version_major}%{?package_suffix} -p /sbin/ldconfig
%endif

%if %{with armnn_tf}
%post -n libarmnnTfParser%{version_major}%{?package_suffix} -p /sbin/ldconfig
%postun -n libarmnnTfParser%{version_major}%{?package_suffix} -p /sbin/ldconfig
%endif

%if %{with armnn_caffe}
%post -n libarmnnCaffeParser%{version_major}%{?package_suffix} -p /sbin/ldconfig
%postun -n libarmnnCaffeParser%{version_major}%{?package_suffix} -p /sbin/ldconfig
%endif

%if %{with armnn_onnx}
%post -n libarmnnOnnxParser%{version_major}%{?package_suffix} -p /sbin/ldconfig
%postun -n libarmnnOnnxParser%{version_major}%{?package_suffix} -p /sbin/ldconfig
%endif


%files
%defattr(-,root,root)
%doc README.md
%license LICENSE
%if %{with armnn_tests}
%{_bindir}/ExecuteNetwork
%if %{with armnn_caffe}
%{_bindir}/Caffe*-Armnn
%{_bindir}/MultipleNetworksCifar10
%endif
%if %{with armnn_flatbuffers}
%{_bindir}/TfLite*-Armnn
%{_bindir}/Image*Generator
%endif
%if %{with armnn_onnx}
%{_bindir}/Onnx*-Armnn
%endif
%if %{with armnn_tf}
%{_bindir}/Tf*-Armnn
%endif
%if %{with armnn_flatbuffers}
%{_bindir}/SimpleSample
%endif
%endif

%if %{with armnn_extra_tests}
%files -n %{name}-extratests
%{_bindir}/ArmnnExamples
%endif

%files -n libarmnn%{version_major}%{?package_suffix}
%{_libdir}/libarmnn.so.*

%if %{with armnn_flatbuffers}
%files -n libarmnnSerializer%{version_major}%{?package_suffix}
%{_libdir}/libarmnnSerializer.so.*

%files -n libarmnnTfLiteParser%{version_major}%{?package_suffix}
%{_libdir}/libarmnnTfLiteParser.so.*
%endif

%if %{with armnn_tf}
%files -n libarmnnTfParser%{version_major}%{?package_suffix}
%{_libdir}/libarmnnTfParser.so.*
%endif

%if %{with armnn_caffe}
%files -n libarmnnCaffeParser%{version_major}%{?package_suffix}
%{_libdir}/libarmnnCaffeParser.so.*
%endif

%if %{with armnn_onnx}
%files -n libarmnnOnnxParser%{version_major}%{?package_suffix}
%{_libdir}/libarmnnOnnxParser.so.*
%endif

%files devel
%defattr(-,root,root)
%dir %{_includedir}/armnn/
%{_includedir}/armnn/*.hpp
%dir %{_includedir}/armnnCaffeParser/
%{_includedir}/armnnCaffeParser/ICaffeParser.hpp
%dir %{_includedir}/armnnOnnxParser/
%{_includedir}/armnnOnnxParser/IOnnxParser.hpp
%dir %{_includedir}/armnnTfLiteParser/
%{_includedir}/armnnTfLiteParser/ITfLiteParser.hpp
%dir %{_includedir}/armnnTfParser/
%{_includedir}/armnnTfParser/ITfParser.hpp
%dir %{_includedir}/armnnDeserializer/
%{_includedir}/armnnDeserializer/IDeserializer.hpp
%dir %{_includedir}/armnnQuantizer
%{_includedir}/armnnQuantizer/INetworkQuantizer.hpp
%dir %{_includedir}/armnnSerializer/
%{_includedir}/armnnSerializer/ISerializer.hpp
%{_libdir}/libarmnn.so
%if %{with armnn_flatbuffers}
%{_libdir}/libarmnnSerializer.so
%{_libdir}/libarmnnTfLiteParser.so
%endif
%if %{with armnn_tf}
%{_libdir}/libarmnnTfParser.so
%endif
%if %{with armnn_caffe}
%{_libdir}/libarmnnCaffeParser.so
%endif
%if %{with armnn_onnx}
%{_libdir}/libarmnnOnnxParser.so
%endif


%changelog