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|
{ stdenv
, lib
, fetchFromGitHub
, fetchpatch
, fetchurl
, pkg-config
, cmake
, python3
, libpng
, zlib
, eigen
, protobuf
, howard-hinnant-date
, nlohmann_json
, boost
, oneDNN
, gtest
}:
let
# prefetch abseil
# Note: keep URL in sync with `cmake/external/abseil-cpp.cmake`
abseil = fetchurl {
url = "https://github.com/abseil/abseil-cpp/archive/refs/tags/20211102.0.zip";
sha256 = "sha256-pFZ/8C+spnG5XjHTFbqxi0K2xvGmDpHG6oTlohQhEsI=";
};
in
stdenv.mkDerivation rec {
pname = "onnxruntime";
version = "1.12.1";
src = fetchFromGitHub {
owner = "microsoft";
repo = "onnxruntime";
rev = "v${version}";
sha256 = "sha256-wwllEemiHTp9aJcCd1gsTS4WUVMp5wW+4i/+6DzmAeM=";
fetchSubmodules = true;
};
patches = [
# Use dnnl from nixpkgs instead of submodules
(fetchpatch {
name = "system-dnnl.patch";
url = "https://aur.archlinux.org/cgit/aur.git/plain/system-dnnl.diff?h=python-onnxruntime&id=0185531906bda3a9aba93bbb0f3dcfeb0ae671ad";
sha256 = "sha256-58RBrQnAWNtc/1pmFs+PkZ6qCsL1LfMY3P0exMKzotA=";
})
];
nativeBuildInputs = [
cmake
pkg-config
python3
gtest
];
buildInputs = [
libpng
zlib
protobuf
howard-hinnant-date
nlohmann_json
boost
oneDNN
];
# TODO: build server, and move .so's to lib output
outputs = [ "out" "dev" ];
enableParallelBuilding = true;
cmakeDir = "../cmake";
cmakeFlags = [
"-Donnxruntime_PREFER_SYSTEM_LIB=ON"
"-Donnxruntime_BUILD_SHARED_LIB=ON"
"-Donnxruntime_ENABLE_LTO=ON"
"-Donnxruntime_BUILD_UNIT_TESTS=ON"
"-Donnxruntime_USE_PREINSTALLED_EIGEN=ON"
"-Donnxruntime_USE_MPI=ON"
"-Deigen_SOURCE_PATH=${eigen.src}"
"-Donnxruntime_USE_DNNL=YES"
];
doCheck = true;
postPatch = ''
substituteInPlace cmake/external/abseil-cpp.cmake \
--replace "${abseil.url}" "${abseil}"
substituteInPlace cmake/libonnxruntime.pc.cmake.in \
--replace '$'{prefix}/@CMAKE_INSTALL_ @CMAKE_INSTALL_
'';
postInstall = ''
# perform parts of `tools/ci_build/github/linux/copy_strip_binary.sh`
install -m644 -Dt $out/include \
../include/onnxruntime/core/framework/provider_options.h \
../include/onnxruntime/core/providers/cpu/cpu_provider_factory.h \
../include/onnxruntime/core/session/onnxruntime_*.h
'';
meta = with lib; {
description = "Cross-platform, high performance scoring engine for ML models";
longDescription = ''
ONNX Runtime is a performance-focused complete scoring engine
for Open Neural Network Exchange (ONNX) models, with an open
extensible architecture to continually address the latest developments
in AI and Deep Learning. ONNX Runtime stays up to date with the ONNX
standard with complete implementation of all ONNX operators, and
supports all ONNX releases (1.2+) with both future and backwards
compatibility.
'';
homepage = "https://github.com/microsoft/onnxruntime";
changelog = "https://github.com/microsoft/onnxruntime/releases/tag/v${version}";
# https://github.com/microsoft/onnxruntime/blob/master/BUILD.md#architectures
platforms = platforms.unix;
license = licenses.mit;
maintainers = with maintainers; [ jonringer puffnfresh ck3d ];
};
}
|