{ config , stdenv , lib , fetchFromGitHub , Foundation , abseil-cpp , cmake , eigen , gtest , libpng , nlohmann_json , nsync , pkg-config , python3Packages , re2 , zlib , microsoft-gsl , libiconv , protobuf_21 , pythonSupport ? true , cudaSupport ? config.cudaSupport , cudaPackages ? {} }@inputs: let version = "1.16.3"; stdenv = throw "Use effectiveStdenv instead"; effectiveStdenv = if cudaSupport then cudaPackages.backendStdenv else inputs.stdenv; cudaArchitecturesString = cudaPackages.flags.cmakeCudaArchitecturesString; howard-hinnant-date = fetchFromGitHub { owner = "HowardHinnant"; repo = "date"; rev = "v2.4.1"; sha256 = "sha256-BYL7wxsYRI45l8C3VwxYIIocn5TzJnBtU0UZ9pHwwZw="; }; mp11 = fetchFromGitHub { owner = "boostorg"; repo = "mp11"; rev = "boost-1.79.0"; hash = "sha256-ZxgPDLvpISrjpEHKpLGBowRKGfSwTf6TBfJD18yw+LM="; }; safeint = fetchFromGitHub { owner = "dcleblanc"; repo = "safeint"; rev = "ff15c6ada150a5018c5ef2172401cb4529eac9c0"; hash = "sha256-PK1ce4C0uCR4TzLFg+elZdSk5DdPCRhhwT3LvEwWnPU="; }; pytorch_cpuinfo = fetchFromGitHub { owner = "pytorch"; repo = "cpuinfo"; # There are no tags in the repository rev = "5916273f79a21551890fd3d56fc5375a78d1598d"; hash = "sha256-nXBnloVTuB+AVX59VDU/Wc+Dsx94o92YQuHp3jowx2A="; }; flatbuffers = fetchFromGitHub { owner = "google"; repo = "flatbuffers"; rev = "v1.12.0"; hash = "sha256-L1B5Y/c897Jg9fGwT2J3+vaXsZ+lfXnskp8Gto1p/Tg="; }; onnx = fetchFromGitHub { owner = "onnx"; repo = "onnx"; rev = "refs/tags/v1.14.1"; hash = "sha256-ZVSdk6LeAiZpQrrzLxphMbc1b3rNUMpcxcXPP8s/5tE="; }; cutlass = fetchFromGitHub { owner = "NVIDIA"; repo = "cutlass"; rev = "v3.0.0"; sha256 = "sha256-YPD5Sy6SvByjIcGtgeGH80TEKg2BtqJWSg46RvnJChY="; }; in effectiveStdenv.mkDerivation rec { pname = "onnxruntime"; inherit version; src = fetchFromGitHub { owner = "microsoft"; repo = "onnxruntime"; rev = "refs/tags/v${version}"; hash = "sha256-bTW9Pc3rvH+c8VIlDDEtAXyA3sajVyY5Aqr6+SxaMF4="; fetchSubmodules = true; }; patches = [ # If you stumble on these patches trying to update onnxruntime, check # `git blame` and ping the introducers. # Context: we want the upstream to # - always try find_package first (FIND_PACKAGE_ARGS), # - use MakeAvailable instead of the low-level Populate, # - use Eigen3::Eigen as the target name (as declared by libeigen/eigen). ./0001-eigen-allow-dependency-injection.patch ] ++ lib.optionals cudaSupport [ # We apply the referenced 1064.patch ourselves to our nix dependency. # FIND_PACKAGE_ARGS for CUDA was added in https://github.com/microsoft/onnxruntime/commit/87744e5 so it might be possible to delete this patch after upgrading to 1.17.0 ./nvcc-gsl.patch ]; nativeBuildInputs = [ cmake pkg-config python3Packages.python protobuf_21 ] ++ lib.optionals pythonSupport (with python3Packages; [ pip python pythonOutputDistHook setuptools wheel ]) ++ lib.optionals cudaSupport [ cudaPackages.cuda_nvcc ]; buildInputs = [ eigen libpng zlib nlohmann_json microsoft-gsl ] ++ lib.optionals pythonSupport (with python3Packages; [ numpy pybind11 packaging ]) ++ lib.optionals effectiveStdenv.isDarwin [ Foundation libiconv ] ++ lib.optionals cudaSupport (with cudaPackages; [ cuda_cccl # cub/cub.cuh libcublas # cublas_v2.h libcurand # curand.h libcusparse # cusparse.h libcufft # cufft.h cudnn # cudnn.h cuda_cudart ]); nativeCheckInputs = [ gtest ] ++ lib.optionals pythonSupport (with python3Packages; [ pytest sympy onnx ]); # TODO: build server, and move .so's to lib output # Python's wheel is stored in a separate dist output outputs = [ "out" "dev" ] ++ lib.optionals pythonSupport [ "dist" ]; enableParallelBuilding = true; cmakeDir = "../cmake"; cmakeFlags = [ "-DABSL_ENABLE_INSTALL=ON" "-DFETCHCONTENT_FULLY_DISCONNECTED=ON" "-DFETCHCONTENT_QUIET=OFF" "-DFETCHCONTENT_SOURCE_DIR_ABSEIL_CPP=${abseil-cpp.src}" "-DFETCHCONTENT_SOURCE_DIR_DATE=${howard-hinnant-date}" "-DFETCHCONTENT_SOURCE_DIR_FLATBUFFERS=${flatbuffers}" "-DFETCHCONTENT_SOURCE_DIR_GOOGLE_NSYNC=${nsync.src}" "-DFETCHCONTENT_SOURCE_DIR_MP11=${mp11}" "-DFETCHCONTENT_SOURCE_DIR_ONNX=${onnx}" "-DFETCHCONTENT_SOURCE_DIR_PYTORCH_CPUINFO=${pytorch_cpuinfo}" "-DFETCHCONTENT_SOURCE_DIR_RE2=${re2.src}" "-DFETCHCONTENT_SOURCE_DIR_SAFEINT=${safeint}" "-DFETCHCONTENT_TRY_FIND_PACKAGE_MODE=ALWAYS" "-Donnxruntime_BUILD_SHARED_LIB=ON" (lib.cmakeBool "onnxruntime_BUILD_UNIT_TESTS" doCheck) "-Donnxruntime_ENABLE_LTO=ON" "-Donnxruntime_USE_FULL_PROTOBUF=OFF" (lib.cmakeBool "onnxruntime_USE_CUDA" cudaSupport) (lib.cmakeBool "onnxruntime_USE_NCCL" cudaSupport) ] ++ lib.optionals pythonSupport [ "-Donnxruntime_ENABLE_PYTHON=ON" ] ++ lib.optionals cudaSupport [ (lib.cmakeFeature "FETCHCONTENT_SOURCE_DIR_CUTLASS" "${cutlass}") (lib.cmakeFeature "onnxruntime_CUDNN_HOME" "${cudaPackages.cudnn}") (lib.cmakeFeature "CMAKE_CUDA_ARCHITECTURES" cudaArchitecturesString) (lib.cmakeFeature "onnxruntime_NVCC_THREADS" "1") ]; env = lib.optionalAttrs effectiveStdenv.cc.isClang { NIX_CFLAGS_COMPILE = toString [ "-Wno-error=deprecated-declarations" "-Wno-error=unused-but-set-variable" ]; }; doCheck = !cudaSupport; requiredSystemFeatures = lib.optionals cudaSupport [ "big-parallel" ]; postPatch = '' substituteInPlace cmake/libonnxruntime.pc.cmake.in \ --replace-fail '$'{prefix}/@CMAKE_INSTALL_ @CMAKE_INSTALL_ '' + lib.optionalString (effectiveStdenv.hostPlatform.system == "aarch64-linux") '' # https://github.com/NixOS/nixpkgs/pull/226734#issuecomment-1663028691 rm -v onnxruntime/test/optimizer/nhwc_transformer_test.cc ''; postBuild = lib.optionalString pythonSupport '' ${python3Packages.python.interpreter} ../setup.py bdist_wheel ''; postInstall = '' # perform parts of `tools/ci_build/github/linux/copy_strip_binary.sh` install -m644 -Dt $out/include \ ../include/onnxruntime/core/framework/provider_options.h \ ../include/onnxruntime/core/providers/cpu/cpu_provider_factory.h \ ../include/onnxruntime/core/session/onnxruntime_*.h ''; passthru = { inherit cudaSupport cudaPackages; # for the python module protobuf = protobuf_21; tests = lib.optionalAttrs pythonSupport { python = python3Packages.onnxruntime; }; }; meta = with lib; { description = "Cross-platform, high performance scoring engine for ML models"; longDescription = '' ONNX Runtime is a performance-focused complete scoring engine for Open Neural Network Exchange (ONNX) models, with an open extensible architecture to continually address the latest developments in AI and Deep Learning. ONNX Runtime stays up to date with the ONNX standard with complete implementation of all ONNX operators, and supports all ONNX releases (1.2+) with both future and backwards compatibility. ''; homepage = "https://github.com/microsoft/onnxruntime"; changelog = "https://github.com/microsoft/onnxruntime/releases/tag/v${version}"; # https://github.com/microsoft/onnxruntime/blob/master/BUILD.md#architectures platforms = platforms.unix; license = licenses.mit; maintainers = with maintainers; [ puffnfresh ck3d cbourjau ]; }; }