forked from mirrors_public/oddlama_nix-config
chore: update flake
This commit is contained in:
oddlama
parent
36c011b89b
commit
911f2954c6
5 changed files with 58 additions and 524 deletions
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@ -38,8 +38,7 @@ inputs: [
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#pythonPackagesExtensions =
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# prev.pythonPackagesExtensions
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# ++ [
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# (pythonFinal: _pythonPrev: {
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# jaxlib = pythonFinal.callPackage ./jaxlib.nix {};
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# (_pythonFinal: pythonPrev: {
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# })
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# ];
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451
pkgs/jaxlib.nix
451
pkgs/jaxlib.nix
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@ -1,451 +0,0 @@
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{
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lib,
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pkgs,
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# Build-time dependencies:
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autoAddDriverRunpath,
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bazel_6,
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binutils,
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buildBazelPackage,
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buildPythonPackage,
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curl,
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cython,
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fetchFromGitHub,
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git,
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jsoncpp,
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nsync,
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openssl,
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pybind11,
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setuptools,
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symlinkJoin,
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wheel,
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build,
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which,
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# Python dependencies:
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absl-py,
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flatbuffers,
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ml-dtypes,
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numpy,
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scipy,
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six,
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# Runtime dependencies:
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double-conversion,
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giflib,
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libjpeg_turbo,
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python,
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snappy,
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zlib,
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config,
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# CUDA flags:
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cudaSupport ? config.cudaSupport,
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cudaPackages,
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# MKL:
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mklSupport ? true,
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} @ inputs: let
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inherit
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(cudaPackages)
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cudaFlags
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cudaVersion
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cudnn
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nccl
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;
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pname = "jaxlib";
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version = "0.4.28";
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# It's necessary to consistently use backendStdenv when building with CUDA
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# support, otherwise we get libstdc++ errors downstream
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stdenv = throw "Use effectiveStdenv instead";
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effectiveStdenv =
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if cudaSupport
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then cudaPackages.backendStdenv
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else inputs.stdenv;
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meta = with lib; {
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description = "JAX is Autograd and XLA, brought together for high-performance machine learning research";
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homepage = "https://github.com/google/jax";
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license = licenses.asl20;
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maintainers = with maintainers; [ndl];
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platforms = platforms.unix;
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# aarch64-darwin is broken because of https://github.com/bazelbuild/rules_cc/pull/136
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# however even with that fix applied, it doesn't work for everyone:
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# https://github.com/NixOS/nixpkgs/pull/184395#issuecomment-1207287129
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# NOTE: We always build with NCCL; if it is unsupported, then our build is broken.
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broken = effectiveStdenv.isDarwin || nccl.meta.unsupported;
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};
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# These are necessary at build time and run time.
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cuda_libs_joined = symlinkJoin {
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name = "cuda-joined";
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paths = with cudaPackages; [
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cuda_cudart.lib # libcudart.so
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cuda_cudart.static # libcudart_static.a
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cuda_cupti.lib # libcupti.so
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libcublas.lib # libcublas.so
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libcufft.lib # libcufft.so
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libcurand.lib # libcurand.so
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libcusolver.lib # libcusolver.so
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libcusparse.lib # libcusparse.so
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];
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};
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# These are only necessary at build time.
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cuda_build_deps_joined = symlinkJoin {
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name = "cuda-build-deps-joined";
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paths = with cudaPackages; [
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cuda_libs_joined
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# Binaries
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cudaPackages.cuda_nvcc.bin # nvcc
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# Headers
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cuda_cccl.dev # block_load.cuh
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cuda_cudart.dev # cuda.h
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cuda_cupti.dev # cupti.h
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cuda_nvcc.dev # See https://github.com/google/jax/issues/19811
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cuda_nvml_dev # nvml.h
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cuda_nvtx.dev # nvToolsExt.h
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libcublas.dev # cublas_api.h
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libcufft.dev # cufft.h
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libcurand.dev # curand.h
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libcusolver.dev # cusolver_common.h
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libcusparse.dev # cusparse.h
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];
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};
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backend_cc_joined = symlinkJoin {
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name = "cuda-cc-joined";
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paths = [
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effectiveStdenv.cc
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binutils.bintools # for ar, dwp, nm, objcopy, objdump, strip
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];
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};
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# Copy-paste from TF derivation.
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# Most of these are not really used in jaxlib compilation but it's simpler to keep it
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# 'as is' so that it's more compatible with TF derivation.
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tf_system_libs = [
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"absl_py"
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"astor_archive"
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"astunparse_archive"
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# Not packaged in nixpkgs
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# "com_github_googleapis_googleapis"
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# "com_github_googlecloudplatform_google_cloud_cpp"
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# Issue with transitive dependencies after https://github.com/grpc/grpc/commit/f1d14f7f0b661bd200b7f269ef55dec870e7c108
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# "com_github_grpc_grpc"
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# ERROR: /build/output/external/bazel_tools/tools/proto/BUILD:25:6: no such target '@com_google_protobuf//:cc_toolchain':
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# target 'cc_toolchain' not declared in package '' defined by /build/output/external/com_google_protobuf/BUILD.bazel
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# "com_google_protobuf"
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# Fails with the error: external/org_tensorflow/tensorflow/core/profiler/utils/tf_op_utils.cc:46:49: error: no matching function for call to 're2::RE2::FullMatch(absl::lts_2020_02_25::string_view&, re2::RE2&)'
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# "com_googlesource_code_re2"
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"curl"
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"cython"
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"dill_archive"
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"double_conversion"
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"flatbuffers"
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"functools32_archive"
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"gast_archive"
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"gif"
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"hwloc"
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"icu"
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"jsoncpp_git"
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"libjpeg_turbo"
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"lmdb"
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"nasm"
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"opt_einsum_archive"
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"org_sqlite"
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"pasta"
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"png"
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# ERROR: /build/output/external/pybind11/BUILD.bazel: no such target '@pybind11//:osx':
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# target 'osx' not declared in package '' defined by /build/output/external/pybind11/BUILD.bazel
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# "pybind11"
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"six_archive"
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"snappy"
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"tblib_archive"
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"termcolor_archive"
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"typing_extensions_archive"
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"wrapt"
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"zlib"
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];
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arch =
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# KeyError: ('Linux', 'arm64')
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if effectiveStdenv.hostPlatform.isLinux && effectiveStdenv.hostPlatform.linuxArch == "arm64"
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then "aarch64"
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else effectiveStdenv.hostPlatform.linuxArch;
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xla = effectiveStdenv.mkDerivation {
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pname = "xla-src";
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version = "unstable";
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src = fetchFromGitHub {
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owner = "openxla";
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repo = "xla";
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# Update this according to https://github.com/google/jax/blob/jaxlib-v${version}/third_party/xla/workspace.bzl.
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rev = "e8247c3ea1d4d7f31cf27def4c7ac6f2ce64ecd4";
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hash = "sha256-ZhgMIVs3Z4dTrkRWDqaPC/i7yJz2dsYXrZbjzqvPX3E=";
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};
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dontBuild = true;
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# This is necessary for patchShebangs to know the right path to use.
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nativeBuildInputs = [python];
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# Main culprits we're targeting are third_party/tsl/third_party/gpus/crosstool/clang/bin/*.tpl
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postPatch = ''
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patchShebangs .
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'';
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installPhase = ''
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cp -r . $out
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'';
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};
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bazel-build = buildBazelPackage rec {
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name = "bazel-build-${pname}-${version}";
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# See https://github.com/google/jax/blob/main/.bazelversion for the latest.
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bazel = bazel_6;
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src = fetchFromGitHub {
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owner = "google";
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repo = "jax";
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# google/jax contains tags for jax and jaxlib. Only use jaxlib tags!
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rev = "refs/tags/${pname}-v${version}";
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hash = "sha256-qSHPwi3is6Ts7pz5s4KzQHBMbcjGp+vAOsejW3o36Ek=";
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};
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nativeBuildInputs = [
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cython
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pkgs.flatbuffers
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git
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setuptools
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wheel
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build
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which
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];
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buildInputs =
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[
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curl
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double-conversion
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giflib
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jsoncpp
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libjpeg_turbo
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numpy
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openssl
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pkgs.flatbuffers
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pkgs.protobuf
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pybind11
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scipy
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six
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snappy
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zlib
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]
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++ lib.optionals (!effectiveStdenv.isDarwin) [nsync];
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# We don't want to be quite so picky regarding bazel version
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postPatch = ''
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rm -f .bazelversion
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'';
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bazelRunTarget = "//jaxlib/tools:build_wheel";
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runTargetFlags = [
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"--output_path=$out"
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"--cpu=${arch}"
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# This has no impact whatsoever...
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"--jaxlib_git_hash='12345678'"
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];
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removeRulesCC = false;
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GCC_HOST_COMPILER_PREFIX = lib.optionalString cudaSupport "${backend_cc_joined}/bin";
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GCC_HOST_COMPILER_PATH = lib.optionalString cudaSupport "${backend_cc_joined}/bin/gcc";
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# The version is automatically set to ".dev" if this variable is not set.
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# https://github.com/google/jax/commit/e01f2617b85c5bdffc5ffb60b3d8d8ca9519a1f3
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JAXLIB_RELEASE = "1";
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preConfigure =
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# Dummy ldconfig to work around "Can't open cache file /nix/store/<hash>-glibc-2.38-44/etc/ld.so.cache" error
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''
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mkdir dummy-ldconfig
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echo "#!${effectiveStdenv.shell}" > dummy-ldconfig/ldconfig
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chmod +x dummy-ldconfig/ldconfig
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export PATH="$PWD/dummy-ldconfig:$PATH"
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''
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+
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# Construct .jax_configure.bazelrc. See https://github.com/google/jax/blob/b9824d7de3cb30f1df738cc42e486db3e9d915ff/build/build.py#L259-L345
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# for more info. We assume
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# * `cpu = None`
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# * `enable_nccl = True`
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# * `target_cpu_features = "release"`
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# * `rocm_amdgpu_targets = None`
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# * `enable_rocm = False`
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# * `build_gpu_plugin = False`
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# * `use_clang = False` (Should we use `effectiveStdenv.cc.isClang` instead?)
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#
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# Note: We should try just running https://github.com/google/jax/blob/ceb198582b62b9e6f6bdf20ab74839b0cf1db16e/build/build.py#L259-L266
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# instead of duplicating the logic here. Perhaps we can leverage the
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# `--configure_only` flag (https://github.com/google/jax/blob/ceb198582b62b9e6f6bdf20ab74839b0cf1db16e/build/build.py#L544-L548)?
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''
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cat <<CFG > ./.jax_configure.bazelrc
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build --strategy=Genrule=standalone
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build --repo_env PYTHON_BIN_PATH="${python}/bin/python"
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build --action_env=PYENV_ROOT
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build --python_path="${python}/bin/python"
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build --distinct_host_configuration=false
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build --define PROTOBUF_INCLUDE_PATH="${pkgs.protobuf}/include"
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''
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+ lib.optionalString cudaSupport ''
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build --config=cuda
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build --action_env CUDA_TOOLKIT_PATH="${cuda_build_deps_joined}"
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build --action_env CUDNN_INSTALL_PATH="${cudnn}"
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build --action_env TF_CUDA_PATHS="${cuda_build_deps_joined},${cudnn},${nccl}"
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build --action_env TF_CUDA_VERSION="${lib.versions.majorMinor cudaVersion}"
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build --action_env TF_CUDNN_VERSION="${lib.versions.major cudnn.version}"
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build:cuda --action_env TF_CUDA_COMPUTE_CAPABILITIES="${builtins.concatStringsSep "," cudaFlags.realArches}"
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''
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+
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# Note that upstream conditions this on `wheel_cpu == "x86_64"`. We just
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# rely on `effectiveStdenv.hostPlatform.avxSupport` instead. So far so
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# good. See https://github.com/google/jax/blob/b9824d7de3cb30f1df738cc42e486db3e9d915ff/build/build.py#L322
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# for upstream's version.
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lib.optionalString (effectiveStdenv.hostPlatform.avxSupport && effectiveStdenv.hostPlatform.isUnix)
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''
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build --config=avx_posix
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''
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+ lib.optionalString mklSupport ''
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build --config=mkl_open_source_only
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''
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+ ''
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CFG
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'';
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# Make sure Bazel knows about our configuration flags during fetching so that the
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# relevant dependencies can be downloaded.
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bazelFlags =
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[
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"-c opt"
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# See https://bazel.build/external/advanced#overriding-repositories for
|
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# information on --override_repository flag.
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"--override_repository=xla=${xla}"
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]
|
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++ lib.optionals effectiveStdenv.cc.isClang [
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# bazel depends on the compiler frontend automatically selecting these flags based on file
|
||||
# extension but our clang doesn't.
|
||||
# https://github.com/NixOS/nixpkgs/issues/150655
|
||||
"--cxxopt=-x"
|
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"--cxxopt=c++"
|
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"--host_cxxopt=-x"
|
||||
"--host_cxxopt=c++"
|
||||
];
|
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|
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# We intentionally overfetch so we can share the fetch derivation across all the different configurations
|
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fetchAttrs = {
|
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TF_SYSTEM_LIBS = lib.concatStringsSep "," tf_system_libs;
|
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# we have to force @mkl_dnn_v1 since it's not needed on darwin
|
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bazelTargets = [
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bazelRunTarget
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"@mkl_dnn_v1//:mkl_dnn"
|
||||
];
|
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bazelFlags =
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bazelFlags
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++ [
|
||||
"--config=avx_posix"
|
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"--config=mkl_open_source_only"
|
||||
]
|
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++ lib.optionals cudaSupport [
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# ideally we'd add this unconditionally too, but it doesn't work on darwin
|
||||
# we make this conditional on `cudaSupport` instead of the system, so that the hash for both
|
||||
# the cuda and the non-cuda deps can be computed on linux, since a lot of contributors don't
|
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# have access to darwin machines
|
||||
"--config=cuda"
|
||||
];
|
||||
|
||||
sha256 =
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(
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||||
if cudaSupport
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then {x86_64-linux = "sha256-vUoAPkYKEnHkV4fw6BI0mCeuP2e8BMCJnVuZMm9LwSA=";}
|
||||
else {
|
||||
x86_64-linux = "sha256-uOoAyMBLHPX6jzdN43b5wZV5eW0yI8sCDD7BSX2h4oQ=";
|
||||
aarch64-linux = "sha256-+SnGKY9LIT1Qhu/x6Uh7sHRaAEjlc//qyKj1m4t16PA=";
|
||||
}
|
||||
)
|
||||
.${effectiveStdenv.system}
|
||||
or (throw "jaxlib: unsupported system: ${effectiveStdenv.system}");
|
||||
};
|
||||
|
||||
buildAttrs = {
|
||||
outputs = ["out"];
|
||||
|
||||
TF_SYSTEM_LIBS = lib.concatStringsSep "," (
|
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tf_system_libs
|
||||
++ lib.optionals (!effectiveStdenv.isDarwin) [
|
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"nsync" # fails to build on darwin
|
||||
]
|
||||
);
|
||||
};
|
||||
|
||||
inherit meta;
|
||||
};
|
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platformTag =
|
||||
if effectiveStdenv.hostPlatform.isLinux
|
||||
then "manylinux2014_${arch}"
|
||||
else if effectiveStdenv.system == "x86_64-darwin"
|
||||
then "macosx_10_9_${arch}"
|
||||
else if effectiveStdenv.system == "aarch64-darwin"
|
||||
then "macosx_11_0_${arch}"
|
||||
else throw "Unsupported target platform: ${effectiveStdenv.hostPlatform}";
|
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in
|
||||
buildPythonPackage {
|
||||
inherit meta pname version;
|
||||
format = "wheel";
|
||||
|
||||
src = let
|
||||
cp = "cp${builtins.replaceStrings ["."] [""] python.pythonVersion}";
|
||||
in "${bazel-build}/jaxlib-${version}-${cp}-${cp}-${platformTag}.whl";
|
||||
|
||||
# Note that jaxlib looks for "ptxas" in $PATH. See https://github.com/NixOS/nixpkgs/pull/164176#discussion_r828801621
|
||||
# for more info.
|
||||
postInstall = lib.optionalString cudaSupport ''
|
||||
mkdir -p $out/bin
|
||||
ln -s ${cudaPackages.cuda_nvcc.bin}/bin/ptxas $out/bin/ptxas
|
||||
|
||||
find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
|
||||
patchelf --add-rpath "${
|
||||
lib.makeLibraryPath [
|
||||
cuda_libs_joined
|
||||
cudnn
|
||||
nccl
|
||||
]
|
||||
}" "$lib"
|
||||
done
|
||||
'';
|
||||
|
||||
nativeBuildInputs = lib.optionals cudaSupport [autoAddDriverRunpath];
|
||||
|
||||
dependencies = [
|
||||
absl-py
|
||||
curl
|
||||
double-conversion
|
||||
flatbuffers
|
||||
giflib
|
||||
jsoncpp
|
||||
libjpeg_turbo
|
||||
ml-dtypes
|
||||
numpy
|
||||
scipy
|
||||
six
|
||||
snappy
|
||||
];
|
||||
|
||||
pythonImportsCheck = [
|
||||
"jaxlib"
|
||||
# `import jaxlib` loads surprisingly little. These imports are actually bugs that appeared in the 0.4.11 upgrade.
|
||||
"jaxlib.cpu_feature_guard"
|
||||
"jaxlib.xla_client"
|
||||
];
|
||||
|
||||
# Without it there are complaints about libcudart.so.11.0 not being found
|
||||
# because RPATH path entries added above are stripped.
|
||||
dontPatchELF = cudaSupport;
|
||||
}
|
||||
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