mirror of
https://github.com/NixOS/nixpkgs.git
synced 2024-12-04 19:45:54 +00:00
63 lines
1.8 KiB
Nix
63 lines
1.8 KiB
Nix
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{ stdenv, fetchFromGitHub, glibcLocales
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, cmake, python3
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}:
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stdenv.mkDerivation rec {
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pname = "onnxruntime";
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version = "0.5.0";
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src = fetchFromGitHub {
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owner = "microsoft";
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repo = "onnxruntime";
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rev = "v${version}";
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sha256 = "0s8ylc5xr55490hbz7zn3hnp9dnyp92d320ln8xw5hqkw3mgyr3p";
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# TODO: use nix-versions of grpc, onnx, eigen, googletest, etc.
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# submodules increase src size and compile times significantly
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# not currently feasible due to how integrated cmake build is with git
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fetchSubmodules = true;
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};
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# TODO: build server, and move .so's to lib output
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outputs = [ "out" "dev" ];
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nativeBuildInputs = [
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cmake
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python3 # for shared-lib or server
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];
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cmakeDir = "../cmake";
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cmakeFlags = [
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"-Donnxruntime_USE_OPENMP=ON"
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"-Donnxruntime_BUILD_SHARED_LIB=ON"
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"-Donnxruntime_ENABLE_LTO=ON"
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];
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# ContribOpTest.StringNormalizerTest sets locale to en_US.UTF-8"
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preCheck = stdenv.lib.optionalString stdenv.isLinux ''
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export LOCALE_ARCHIVE="${glibcLocales}/lib/locale/locale-archive"
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'';
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doCheck = true;
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postInstall = ''
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rm -r $out/bin # ctest runner
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'';
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meta = with stdenv.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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license = licenses.mit;
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maintainers = with maintainers; [ jonringer ];
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};
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}
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