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Split ONNXRuntime into ONNXRuntime, and ONNXRuntime_CUDA
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‎O/ONNXRuntime/ONNXRuntime/build_tarballs.jl‎

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# Note that this script can accept some limited command-line arguments, run
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# `julia build_tarballs.jl --help` to see a usage message.
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using BinaryBuilder, Pkg
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name = "ONNXRuntime"
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version = v"1.10.0"
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include(joinpath(@__DIR__, "..", "common.jl"))
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# Override the default sources
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append!(sources, [
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ArchiveSource("https://github.com/microsoft/onnxruntime/releases/download/v$version/onnxruntime-win-x64-$version.zip", "a0c6db3cff65bd282f6ba4a57789e619c27e55203321aa08c023019fe9da50d7"; unpack_target="onnxruntime-x86_64-w64-mingw32"),
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ArchiveSource("https://github.com/microsoft/onnxruntime/releases/download/v$version/onnxruntime-win-x86-$version.zip", "fd1680fa7248ec334efc2564086e9c5e0d6db78337b55ec32e7b666164bdb88c"; unpack_target="onnxruntime-i686-w64-mingw32"),
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])
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build_tarballs(ARGS, name, version, sources, script,
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platforms, products, dependencies;
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julia_compat = "1.6",
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preferred_gcc_version = v"8")

‎O/ONNXRuntime/ONNXRuntime_CUDA/build_tarballs.jl‎

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# Note that this script can accept some limited command-line arguments, run
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# `julia build_tarballs.jl --help` to see a usage message.
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using BinaryBuilder, Pkg
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const YGGDRASIL_DIR = "../../.."
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include(joinpath(YGGDRASIL_DIR, "fancy_toys.jl"))
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include(joinpath(YGGDRASIL_DIR, "platforms", "cuda.jl"))
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name = "ONNXRuntime_CUDA"
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version = v"1.10.0"
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# Cf. https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements
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# Cf. https://onnxruntime.ai/docs/execution-providers/TensorRT-ExecutionProvider.html#requirements
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cuda_versions = [
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v"10.2",
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v"11.3", # Using 11.3, and not 11.4, to be compatible with CUDNN v8.2.4, and with TensorRT (JLL) v8.0.1 (where the latter includes aarch64 support).
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]
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cudnn_version = v"8.2.4"
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tensorrt_version = v"8.0.1"
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cudnn_compat = string(cudnn_version.major)
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tensorrt_compat = string(tensorrt_version.major)
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include(joinpath(@__DIR__, "..", "common.jl"))
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# Override the default sources
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append!(sources, [
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ArchiveSource("https://github.com/microsoft/onnxruntime/releases/download/v$version/onnxruntime-win-x64-gpu-$version.zip", "0da11b8d953fad4ec75f87bb894f72dea511a3940cff2f4dad37451586d1ebbc"; unpack_target="onnxruntime-x86_64-w64-mingw32-cuda"),
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# aarch64-linux-gnu binaries for NVIDIA Jetson from NVIDIA-managed Jetson Zoo: https://elinux.org/Jetson_Zoo#ONNX_Runtime
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FileSource("https://nvidia.box.com/shared/static/jy7nqva7l88mq9i8bw3g3sklzf4kccn2.whl", "a608b7a4a4fc6ad5c90d6005edbfe0851847b991b08aafff4549bbbbdb938bf6"; filename = "onnxruntime-aarch64-linux-gnu-cuda.whl"),
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])
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# Override the default platforms
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platforms = CUDA.supported_platforms(min_version=v"10.2", max_version=v"11")
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filter!(p -> !(arch(p) == "x86_64" && Sys.islinux(p) && p["cuda"] == "10.2"), platforms) # Fails with: nvcc error : 'ptxas' died due to signal 11 (Invalid memory reference)
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push!(platforms, Platform("x86_64", "Linux"; cuda = "11.3"))
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push!(platforms, Platform("x86_64", "Windows"; cuda = "11.3"))
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platforms = expand_cxxstring_abis(platforms; skip=!Sys.islinux)
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# Override the default products
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append!(products, [
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LibraryProduct(["libonnxruntime_providers_cuda", "onnxruntime_providers_cuda"], :libonnxruntime_providers_cuda; dont_dlopen=true),
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LibraryProduct(["libonnxruntime_providers_shared", "onnxruntime_providers_shared"], :libonnxruntime_providers_shared),
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LibraryProduct(["libonnxruntime_providers_tensorrt", "onnxruntime_providers_tensorrt"], :libonnxruntime_providers_tensorrt; dont_dlopen=true),
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])
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append!(dependencies, [
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Dependency(get_addable_spec("CUDNN_jll", v"8.2.4+0"); compat = cudnn_compat), # Using v"8.2.4+0" to get support for cuda = "11.3"
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Dependency("TensorRT_jll", tensorrt_version; compat = tensorrt_compat),
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Dependency("Zlib_jll"),
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])
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builds = []
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for platform in platforms
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should_build_platform(platform) || continue
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additional_deps = BinaryBuilder.AbstractDependency[]
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if platform["cuda"] == "11.3"
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additional_deps = BinaryBuilder.AbstractDependency[
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BuildDependency(PackageSpec("CUDA_full_jll", v"11.3.1")),
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Dependency("CUDA_Runtime_jll", v"0.7.0"), # Using v"0.7.0" to get support for cuda = "11.3" - using Dependency rather than RuntimeDependency to be sure to pass audit
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]
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else
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additional_deps = CUDA.required_dependencies(platform, static_sdk = true)
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end
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push!(builds, (; platforms=[platform], dependencies=[dependencies; additional_deps]))
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end
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# don't allow `build_tarballs` to override platform selection based on ARGS.
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# we handle that ourselves by calling `should_build_platform`
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non_platform_ARGS = filter(arg -> startswith(arg, "--"), ARGS)
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# `--register` should only be passed to the latest `build_tarballs` invocation
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non_reg_ARGS = filter(arg -> arg != "--register", non_platform_ARGS)
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for (i, build) in enumerate(builds)
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build_tarballs(i == lastindex(builds) ? non_platform_ARGS : non_reg_ARGS,
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name, version, sources, script,
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build.platforms, products, build.dependencies;
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augment_platform_block = CUDA.augment,
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julia_compat = "1.6",
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lazy_artifacts = true,
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preferred_gcc_version = v"8")
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end

‎O/ONNXRuntime/build_tarballs.jl‎

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‎O/ONNXRuntime/common.jl‎

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using BinaryBuilder
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using BinaryBuilderBase
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using Pkg
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sources = AbstractSource[
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GitSource("https://github.com/microsoft/onnxruntime.git", "0d9030e79888d1d5828730b254fedc53c7b640c1"),
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]
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script = raw"""
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cd $WORKSPACE/srcdir
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cuda_version=${bb_full_target##*-cuda+}
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if [[ $target != *-w64-mingw32* ]]; then
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if [[ $bb_full_target == x86_64-linux-gnu-*-cuda* ]]; then
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export CUDA_PATH="$prefix/cuda"
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mkdir $WORKSPACE/tmpdir
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export TMPDIR=$WORKSPACE/tmpdir
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cmake_extra_args=(
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-DCUDAToolkit_ROOT=$CUDA_PATH
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-Donnxruntime_CUDA_HOME=$CUDA_PATH
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-Donnxruntime_CUDNN_HOME=$prefix
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-Donnxruntime_USE_CUDA=ON
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-Donnxruntime_USE_TENSORRT=ON
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)
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fi
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# Cross-compiling for aarch64-apple-darwin on x86_64 requires setting arch.: https://github.com/microsoft/onnxruntime/blob/v1.10.0/cmake/CMakeLists.txt#L186
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if [[ $target == aarch64-apple-darwin* ]]; then
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cmake_extra_args+=("-DCMAKE_OSX_ARCHITECTURES='arm64'")
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fi
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cd onnxruntime
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git submodule update --init --recursive --depth 1 --jobs $nproc
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mkdir build
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cd build
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cmake \
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-DCMAKE_INSTALL_PREFIX=$prefix \
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-DCMAKE_TOOLCHAIN_FILE=${CMAKE_TARGET_TOOLCHAIN} \
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-DCMAKE_BUILD_TYPE=Release \
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-DONNX_CUSTOM_PROTOC_EXECUTABLE=$host_bindir/protoc \
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-Donnxruntime_BUILD_SHARED_LIB=ON \
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-Donnxruntime_BUILD_UNIT_TESTS=OFF \
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-Donnxruntime_DISABLE_RTTI=OFF \
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"${cmake_extra_args[@]}" \
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$WORKSPACE/srcdir/onnxruntime/cmake
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make -j $nproc
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make install
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install_license $WORKSPACE/srcdir/onnxruntime/LICENSE
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else
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if [[ $bb_full_target == *-cuda* ]]; then
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srcdir=onnxruntime-$target-cuda
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else
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srcdir=onnxruntime-$target
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fi
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chmod 755 $srcdir/onnxruntime-*/lib/*
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mkdir -p $includedir $libdir
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cp -av $srcdir/onnxruntime-*/include/* $includedir
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find $srcdir/onnxruntime-*/lib -not -type d | xargs -Isrc cp -av src $libdir
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install_license $srcdir/onnxruntime-*/LICENSE
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fi
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if [[ $bb_full_target == aarch64-linux-gnu*-cuda* ]]; then
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cd $WORKSPACE/srcdir
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unzip -d onnxruntime-$target-cuda onnxruntime-$target-cuda.whl
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mkdir -p $libdir
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find onnxruntime-$target-cuda/onnxruntime_gpu*.data/purelib/onnxruntime/capi -name *.so* -not -name *py* | xargs -Isrc cp -av src $libdir
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fi
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"""
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function platform_exclude_filter(p::Platform)
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libc(p) == "musl" ||
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p == Platform("i686", "Linux") || # No binary - and source build fails linking CXX shared library libonnxruntime.so
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Sys.isfreebsd(p)
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end
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platforms = supported_platforms(; exclude=platform_exclude_filter)
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platforms = expand_cxxstring_abis(platforms; skip=!Sys.islinux)
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products = Product[
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LibraryProduct(["libonnxruntime", "onnxruntime"], :libonnxruntime)
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]
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dependencies = AbstractDependency[
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HostBuildDependency(PackageSpec("protoc_jll", v"3.16.1"))
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]
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