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# Maintainer: Chih-Hsuan Yen <yan12125@gmail.com>
pkgbase=python-onnxruntime
# Not split DNNL EP to another package as it's needed unconditionally at runtime if built at compile time
# https://github.com/microsoft/onnxruntime/blob/v1.9.1/onnxruntime/python/onnxruntime_pybind_state.cc#L533
pkgname=(python-onnxruntime python-onnxruntime-cuda)
pkgver=1.11.0
pkgdesc='Cross-platform, high performance scoring engine for ML models'
pkgrel=1
arch=(x86_64)
url='https://github.com/microsoft/onnxruntime'
license=(MIT)
depends=(nsync re2 python-flatbuffers python-numpy python-protobuf openmpi onednn)
makedepends=(git cmake pybind11 python-setuptools nlohmann-json chrono-date boost eigen flatbuffers cuda cudnn nccl)
optdepends=(
# https://github.com/microsoft/onnxruntime/pull/9969
'python-onnx: for the backend API, quantization, orttraining, transformers and various tools'
'python-coloredlogs: for transformers' # also used by TensorRT tools, but we don't build for it, anyway
'python-psutil: for transformers'
'python-py-cpuinfo: for transformers'
'python-py3nvml: for transformers'
'python-packaging: for transformers and various tools'
'python-transformers: for transformers'
'python-scipy: for transformers and various tools'
'python-pytorch: for transformers, orttraining and various tools'
'python-cerberus: for orttraining'
'python-h5py: for orttraining'
'python-sympy: for transformers and various tools'
)
# not de-vendored libraries
# onnx: needs shared libonnx (https://github.com/onnx/onnx/issues/3030)
source=("git+https://github.com/microsoft/onnxruntime#tag=v$pkgver"
"git+https://github.com/onnx/onnx.git"
"git+https://github.com/dcleblanc/SafeInt.git"
"git+https://github.com/tensorflow/tensorboard.git"
"git+https://github.com/dmlc/dlpack.git"
"git+https://github.com/jarro2783/cxxopts.git"
"pytorch_cpuinfo::git+https://github.com/pytorch/cpuinfo.git"
build-fixes.patch
install-orttraining-files.diff
system-dnnl.diff)
sha512sums=('SKIP'
'SKIP'
'SKIP'
'SKIP'
'SKIP'
'SKIP'
'SKIP'
'80ea85ea20bbbdec7991f965a66b627a5f42828bc0c72be0913078d927833a82402fb1af6c5c9f6ecae861b45582fa42c98ce83b02768e4bf875ab89dd1c607c'
'06a002361cc324184d0bfcb520b472f57749c0537329f0e0dee833cc7fce2f08b14590b77bc0211422dfb933dbef6f249f19939f9e0df465c48ee8fc7827e31c'
'6735c7aca2ba2f1f2a5286eb064125bf7f2c68a575d572dd157769d15778ff3e717b3a53d696c767748229f23ee6c3a7c82679df1d86283d7c4dd0ec9103ae08')
# CUDA seems not working with LTO
options+=('!lto')
# Check PKGBUILDs of python-pytorch and tensorflow for CUDA architectures built by official packages
_CUDA_ARCHITECTURES="52-real;53-real;60-real;61-real;62-real;70-real;72-real;75-real;80-real;86-real;86-virtual"
prepare() {
cd onnxruntime
patch -Np1 -i ../build-fixes.patch
patch -Np1 -i ../install-orttraining-files.diff
patch -Np1 -i ../system-dnnl.diff
git submodule init
for mod in onnx SafeInt tensorboard dlpack cxxopts pytorch_cpuinfo; do
git config submodule.cmake/external/$mod.url "$srcdir"/$mod
git submodule update cmake/external/$mod
done
cd onnxruntime/core/flatbuffers/schema
python compile_schema.py --flatc /usr/bin/flatc
}
build() {
cd "$srcdir"/onnxruntime
local cmake_args=(
-DCMAKE_INSTALL_PREFIX=/usr
-Donnxruntime_ENABLE_PYTHON=ON
-Donnxruntime_PREFER_SYSTEM_LIB=ON
-Donnxruntime_BUILD_SHARED_LIB=ON
-Donnxruntime_BUILD_UNIT_TESTS=OFF
-Donnxruntime_ENABLE_TRAINING=ON
-Donnxruntime_USE_MPI=ON
-Donnxruntime_USE_PREINSTALLED_EIGEN=ON
-Donnxruntime_USE_DNNL=ON
-Deigen_SOURCE_PATH=/usr/include/eigen3
)
# Use protobuf-lite instead of full protobuf to workaround symbol conflicts
# with onnx; see https://github.com/onnx/onnx/issues/1277 for details.
cmake_args+=(
-DONNX_CUSTOM_PROTOC_EXECUTABLE=/usr/bin/protoc
-Donnxruntime_USE_FULL_PROTOBUF=OFF
)
# 1. Enable parallel builds for NVCC via -t0, which spawns multiple
# cicc and ptxas processes for each nvcc invocation. The number of
# total processes may be much larger than the number of cores - let
# the scheduler handle it.
cmake_args+=(
-DCMAKE_CUDA_FLAGS="-t0"
-DCMAKE_CUDA_ARCHITECTURES="$_CUDA_ARCHITECTURES"
-DCMAKE_CUDA_STANDARD_REQUIRED=ON
-DCMAKE_CXX_STANDARD_REQUIRED=ON
-Donnxruntime_USE_CUDA=ON
-Donnxruntime_CUDA_HOME=/opt/cuda
-DCMAKE_CUDA_COMPILER:PATH=/opt/cuda/bin/nvcc
-Donnxruntime_CUDNN_HOME=/usr
-Donnxruntime_USE_NCCL=ON
)
cmake -B build -S cmake "${cmake_args[@]}" "$@"
cd build
cmake --build .
python ../setup.py build
}
package_python-onnxruntime() {
cd onnxruntime/build
DESTDIR="$pkgdir" cmake --install .
python ../setup.py install --root="$pkgdir" --skip-build --optimize=1
PY_ORT_DIR="$(python -c 'import site; print(site.getsitepackages()[0])')/onnxruntime"
install -Ddm755 "$pkgdir"/usr/share/licenses/$pkgname
for f in LICENSE ThirdPartyNotices.txt ; do
ln -s "$PY_ORT_DIR/$f" "$pkgdir"/usr/share/licenses/$pkgname/$f
done
# already installed by `cmake --install`, and not useful as this path is not looked up by the linker
rm -vf "$pkgdir/$PY_ORT_DIR"/capi/libonnxruntime_providers_*
# installed as split packages
rm -vf "$pkgdir"/usr/lib/libonnxruntime_providers_cuda.so
}
package_python-onnxruntime-cuda() {
depends+=(cuda cudnn nccl python-onnxruntime)
pkgdesc+=' (CUDA execution provider)'
cd onnxruntime/build
install -Dm755 libonnxruntime_providers_cuda.so -t "$pkgdir"/usr/lib
install -Ddm755 "$pkgdir"/usr/share/licenses
ln -s python-onnxruntime "$pkgdir"/usr/share/licenses/$pkgname
}
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