openvino 2023.0.0 -> 2023.3.0 https://repology.org/project/openvino/versions attrpath: openvino Checking auto update branch... No auto update branch exists Old version 2023.0.0" not present in master derivation file with contents: { lib , gcc12Stdenv , fetchFromGitHub , fetchpatch2 , fetchurl , cudaSupport ? opencv.cudaSupport or false # build , addOpenGLRunpath , autoPatchelfHook , cmake , git , libarchive , pkg-config , python , shellcheck , sphinx # runtime , flatbuffers , libusb1 , libxml2 , ocl-icd , opencv , protobuf , pugixml , snappy , tbb , cudaPackages }: let inherit (lib) cmakeBool ; stdenv = gcc12Stdenv; # See GNA_VERSION in cmake/dependencies.cmake gna_version = "03.05.00.2116"; gna = fetchurl { url = "https://storage.openvinotoolkit.org/dependencies/gna/gna_${gna_version}.zip"; hash = "sha256-lgNQVncCvaFydqxMBg11JPt8587XhQBL2GHIH/K/4sU="; }; tbbbind_version = "2_5"; tbbbind = fetchurl { url = "https://storage.openvinotoolkit.org/dependencies/thirdparty/linux/tbbbind_${tbbbind_version}_static_lin_v4.tgz"; hash = "sha256-Tr8wJGUweV8Gb7lhbmcHxrF756ZdKdNRi1eKdp3VTuo="; }; in stdenv.mkDerivation rec { pname = "openvino"; version = "2023.3.0"; src = fetchFromGitHub { owner = "openvinotoolkit"; repo = "openvino"; rev = "refs/tags/${version}"; fetchSubmodules = true; hash = "sha256-dXlQhar5gz+1iLmDYXUY0jZKh4rJ+khRpoZQphJXfcU="; }; patches = [ (fetchpatch2 { name = "enable-js-toggle.patch"; url = "https://github.com/openvinotoolkit/openvino/commit/0a8f1383826d949c497fe3d05fef9ad2b662fa7e.patch"; hash = "sha256-mQYunouPo3tRlD5Yp4EUth324ccNnVX8zmjPHvJBYKw="; }) ]; outputs = [ "out" "python" ]; nativeBuildInputs = [ addOpenGLRunpath autoPatchelfHook cmake git libarchive pkg-config (python.withPackages (ps: with ps; [ cython pybind11 setuptools ])) shellcheck sphinx ] ++ lib.optionals cudaSupport [ cudaPackages.cuda_nvcc ]; postPatch = '' mkdir -p temp/gna_${gna_version} pushd temp/ bsdtar -xf ${gna} autoPatchelf gna_${gna_version} echo "${gna.url}" > gna_${gna_version}/ie_dependency.info popd mkdir -p temp/tbbbind_${tbbbind_version} pushd temp/tbbbind_${tbbbind_version} bsdtar -xf ${tbbbind} echo "${tbbbind.url}" > ie_dependency.info popd ''; dontUseCmakeBuildDir = true; cmakeFlags = [ "-Wno-dev" "-DCMAKE_MODULE_PATH:PATH=${placeholder "out"}/lib/cmake" "-DCMAKE_PREFIX_PATH:PATH=${placeholder "out"}" "-DOpenCV_DIR=${opencv}/lib/cmake/opencv4/" "-DProtobuf_LIBRARIES=${protobuf}/lib/libprotobuf${stdenv.hostPlatform.extensions.sharedLibrary}" (cmakeBool "CMAKE_VERBOSE_MAKEFILE" true) (cmakeBool "NCC_SYLE" false) (cmakeBool "BUILD_TESTING" false) (cmakeBool "ENABLE_CPPLINT" false) (cmakeBool "ENABLE_TESTING" false) (cmakeBool "ENABLE_SAMPLES" false) # features (cmakeBool "ENABLE_INTEL_CPU" true) (cmakeBool "ENABLE_INTEL_GNA" true) (cmakeBool "ENABLE_JS" false) (cmakeBool "ENABLE_LTO" true) (cmakeBool "ENABLE_ONEDNN_FOR_GPU" false) (cmakeBool "ENABLE_OPENCV" true) (cmakeBool "ENABLE_PYTHON" true) # system libs (cmakeBool "ENABLE_SYSTEM_FLATBUFFERS" true) (cmakeBool "ENABLE_SYSTEM_OPENCL" true) (cmakeBool "ENABLE_SYSTEM_PROTOBUF" false) (cmakeBool "ENABLE_SYSTEM_PUGIXML" true) (cmakeBool "ENABLE_SYSTEM_SNAPPY" true) (cmakeBool "ENABLE_SYSTEM_TBB" true) ]; env.NIX_CFLAGS_COMPILE = lib.optionalString stdenv.isAarch64 "-Wno-narrowing"; autoPatchelfIgnoreMissingDeps = [ "libngraph_backend.so" ]; buildInputs = [ flatbuffers libusb1 libxml2 ocl-icd opencv.cxxdev pugixml snappy tbb ] ++ lib.optionals cudaSupport [ cudaPackages.cuda_cudart ]; enableParallelBuilding = true; postInstall = '' mkdir -p $python mv $out/python/* $python/ rmdir $out/python ''; postFixup = '' # Link to OpenCL find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do addOpenGLRunpath "$lib" done ''; meta = with lib; { description = "OpenVINO™ Toolkit repository"; longDescription = '' This toolkit allows developers to deploy pre-trained deep learning models through a high-level C++ Inference Engine API integrated with application logic. This open source version includes several components: namely Model Optimizer, nGraph and Inference Engine, as well as CPU, GPU, MYRIAD, multi device and heterogeneous plugins to accelerate deep learning inferencing on Intel® CPUs and Intel® Processor Graphics. It supports pre-trained models from the Open Model Zoo, along with 100+ open source and public models in popular formats such as Caffe*, TensorFlow*, MXNet* and ONNX*. ''; homepage = "https://docs.openvinotoolkit.org/"; license = with licenses; [ asl20 ]; platforms = platforms.all; broken = (stdenv.isLinux && stdenv.isAarch64) # requires scons, then fails with *** Source directory cannot be under variant directory. || stdenv.isDarwin; # Cannot find macos sdk maintainers = with maintainers; [ tfmoraes ]; }; }