mirror of
https://github.com/NixOS/nixpkgs.git
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34d1d336ad
The Python bindings to onnxruntime were added by me in #193188. Adding Python support this way is not a good way. Here a wheel was created (which is fine) and installed in a python output. The propagated-build-inputs file is put in the dev output. That's fine, except that stdenv.mkDerivation does not automatically add dev when python is included, because other outputs are only added when no output is explicitly selected. This means that when you want to use these bindings in another Python package, pip will complain it cannot find the dependencies of the bindings. In this PR, the onnxruntime derivation outputs a wheel in the dist output. Then, in python-packages.nix we have a separate onnxruntime package which installs the bindings. The Python bindings have quite some dependencies which, depending on your use case, are not required. Thus the dependency relax hook is used to remove some of these dependencies. Note there is also an issue with protobuf versions. The onnxruntime bindings require an older protobuf and Python protobuf which we cannot offer. Thus protobuf is also removed as Python dependency.
154 lines
4.1 KiB
Nix
154 lines
4.1 KiB
Nix
{ stdenv
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, lib
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, fetchFromGitHub
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, fetchpatch
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, fetchurl
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, pkg-config
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, cmake
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, python3Packages
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, libpng
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, zlib
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, eigen
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, protobuf
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, howard-hinnant-date
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, nlohmann_json
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, boost
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, oneDNN
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, gtest
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, pythonSupport ? false
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, nsync
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, flatbuffers
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}:
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# Python Support
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#
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# When enabling Python support a wheel is made and stored in a `dist` output.
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# This wheel is then installed in a separate derivation.
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assert pythonSupport -> lib.versionOlder protobuf.version "3.20";
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let
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# prefetch abseil
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# Note: keep URL in sync with `cmake/external/abseil-cpp.cmake`
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abseil = fetchurl {
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url = "https://github.com/abseil/abseil-cpp/archive/refs/tags/20211102.0.zip";
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sha256 = "sha256-pFZ/8C+spnG5XjHTFbqxi0K2xvGmDpHG6oTlohQhEsI=";
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};
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in
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stdenv.mkDerivation rec {
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pname = "onnxruntime";
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version = "1.12.1";
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src = fetchFromGitHub {
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owner = "microsoft";
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repo = "onnxruntime";
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rev = "v${version}";
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sha256 = "sha256-wwllEemiHTp9aJcCd1gsTS4WUVMp5wW+4i/+6DzmAeM=";
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fetchSubmodules = true;
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};
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patches = [
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# Use dnnl from nixpkgs instead of submodules
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(fetchpatch {
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name = "system-dnnl.patch";
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url = "https://aur.archlinux.org/cgit/aur.git/plain/system-dnnl.diff?h=python-onnxruntime&id=0185531906bda3a9aba93bbb0f3dcfeb0ae671ad";
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sha256 = "sha256-58RBrQnAWNtc/1pmFs+PkZ6qCsL1LfMY3P0exMKzotA=";
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})
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];
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nativeBuildInputs = [
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cmake
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pkg-config
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python3Packages.python
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gtest
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] ++ lib.optionals pythonSupport (with python3Packages; [
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setuptools
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wheel
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pip
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pythonOutputDistHook
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]);
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buildInputs = [
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libpng
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zlib
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howard-hinnant-date
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nlohmann_json
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boost
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oneDNN
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protobuf
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] ++ lib.optionals pythonSupport [
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nsync
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python3Packages.numpy
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python3Packages.pybind11
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];
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# TODO: build server, and move .so's to lib output
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# Python's wheel is stored in a separate dist output
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outputs = [ "out" "dev" ] ++ lib.optionals pythonSupport [ "dist" ];
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enableParallelBuilding = true;
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cmakeDir = "../cmake";
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cmakeFlags = [
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"-Donnxruntime_PREFER_SYSTEM_LIB=ON"
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"-Donnxruntime_BUILD_SHARED_LIB=ON"
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"-Donnxruntime_ENABLE_LTO=ON"
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"-Donnxruntime_BUILD_UNIT_TESTS=ON"
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"-Donnxruntime_USE_PREINSTALLED_EIGEN=ON"
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"-Donnxruntime_USE_MPI=ON"
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"-Deigen_SOURCE_PATH=${eigen.src}"
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"-Donnxruntime_USE_DNNL=YES"
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] ++ lib.optionals pythonSupport [
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"-Donnxruntime_ENABLE_PYTHON=ON"
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];
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doCheck = true;
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postPatch = ''
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substituteInPlace cmake/external/abseil-cpp.cmake \
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--replace "${abseil.url}" "${abseil}"
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substituteInPlace cmake/libonnxruntime.pc.cmake.in \
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--replace '$'{prefix}/@CMAKE_INSTALL_ @CMAKE_INSTALL_
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'';
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postBuild = lib.optionalString pythonSupport ''
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${python3Packages.python.interpreter} ../setup.py bdist_wheel
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'';
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postInstall = ''
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# perform parts of `tools/ci_build/github/linux/copy_strip_binary.sh`
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install -m644 -Dt $out/include \
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../include/onnxruntime/core/framework/provider_options.h \
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../include/onnxruntime/core/providers/cpu/cpu_provider_factory.h \
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../include/onnxruntime/core/session/onnxruntime_*.h
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'';
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passthru = {
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inherit protobuf;
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tests = lib.optionalAttrs pythonSupport {
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python = python3Packages.onnxruntime;
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};
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};
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meta = with lib; {
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description = "Cross-platform, high performance scoring engine for ML models";
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longDescription = ''
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ONNX Runtime is a performance-focused complete scoring engine
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for Open Neural Network Exchange (ONNX) models, with an open
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extensible architecture to continually address the latest developments
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in AI and Deep Learning. ONNX Runtime stays up to date with the ONNX
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standard with complete implementation of all ONNX operators, and
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supports all ONNX releases (1.2+) with both future and backwards
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compatibility.
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'';
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homepage = "https://github.com/microsoft/onnxruntime";
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changelog = "https://github.com/microsoft/onnxruntime/releases/tag/v${version}";
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# https://github.com/microsoft/onnxruntime/blob/master/BUILD.md#architectures
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platforms = platforms.unix;
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license = licenses.mit;
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maintainers = with maintainers; [ jonringer puffnfresh ck3d ];
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};
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}
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