1 files changed, 0 insertions, 78 deletions
diff --git a/infra/libkookie/nixpkgs/pkgs/development/libraries/onnxruntime/default.nix b/infra/libkookie/nixpkgs/pkgs/development/libraries/onnxruntime/default.nix
deleted file mode 100644
index 06d0d194cd59..000000000000
--- a/infra/libkookie/nixpkgs/pkgs/development/libraries/onnxruntime/default.nix
+++ /dev/null
@@ -1,78 +0,0 @@
-{ stdenv, fetchFromGitHub, glibcLocales
-, cmake, python3, libpng, zlib
-}:
-
-stdenv.mkDerivation rec {
-  pname = "onnxruntime";
-  version = "1.3.1";
-
-  src = fetchFromGitHub {
-    owner = "microsoft";
-    repo = "onnxruntime";
-    rev = "v${version}";
-    sha256 = "0rbk1jbfc447x2wybz2hsba6w1ij0fq21996l52cqv39898lvy9d";
-    # TODO: use nix-versions of grpc, onnx, eigen, googletest, etc.
-    # submodules increase src size and compile times significantly
-    # not currently feasible due to how integrated cmake build is with git
-    fetchSubmodules = true;
-    # Remove unicode file names which leads to different checksums on HFS+
-    # vs. other filesystems because of unicode normalisation.
-    postFetch = ''
-      rm -rf $out/winml/test/collateral/models/UnicodePath/
-    '';
-  };
-
-  # TODO: build server, and move .so's to lib output
-  outputs = [ "out" "dev" ];
-
-  nativeBuildInputs = [
-    cmake
-    python3 # for shared-lib or server
-  ];
-
-  buildInputs = [
-    # technically optional, but highly recommended
-    libpng
-    zlib
-  ];
-
-  cmakeDir = "../cmake";
-
-  cmakeFlags = [
-    "-Donnxruntime_USE_OPENMP=ON"
-    "-Donnxruntime_BUILD_SHARED_LIB=ON"
-    "-Donnxruntime_ENABLE_LTO=ON"
-  ];
-
-  # ContribOpTest.StringNormalizerTest sets locale to en_US.UTF-8"
-  preCheck = stdenv.lib.optionalString stdenv.isLinux ''
-    export LOCALE_ARCHIVE="${glibcLocales}/lib/locale/locale-archive"
-  '';
-  doCheck = true;
-
-  postInstall = ''
-    rm -r $out/bin   # ctest runner
-  '';
-
-  enableParallelBuilding = true;
-
-  meta = with stdenv.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";
-    # https://github.com/microsoft/onnxruntime/blob/master/BUILD.md#architectures
-    platforms = platforms.unix;
-    license = licenses.mit;
-    maintainers = with maintainers; [ jonringer ];
-  };
-
-}