forked from mirrors/nixpkgs
122 lines
3.4 KiB
Nix
122 lines
3.4 KiB
Nix
{ stdenv
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, lib
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, fetchurl
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, buildPythonPackage
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, isPy3k, pythonOlder, isPy38
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, astor
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, gast
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, google-pasta
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, wrapt
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, numpy
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, six
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, termcolor
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, protobuf
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, absl-py
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, grpcio
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, mock
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, backports_weakref
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, tensorflow-estimator
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, tensorflow-tensorboard
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, cudaSupport ? false
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, cudatoolkit ? null
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, cudnn ? null
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, nvidia_x11 ? null
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, zlib
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, python
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, symlinkJoin
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, keras-applications
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, keras-preprocessing
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, addOpenGLRunpath
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}:
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# We keep this binary build for two reasons:
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# - the source build doesn't work on Darwin.
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# - the source build is currently brittle and not easy to maintain
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assert cudaSupport -> cudatoolkit != null
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&& cudnn != null
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&& nvidia_x11 != null;
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# unsupported combination
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assert ! (stdenv.isDarwin && cudaSupport);
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let
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packages = import ./binary-hashes.nix;
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variant = if cudaSupport then "-gpu" else "";
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pname = "tensorflow${variant}";
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in buildPythonPackage {
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inherit pname;
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inherit (packages) version;
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format = "wheel";
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disabled = isPy38;
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src = let
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pyVerNoDot = lib.strings.stringAsChars (x: if x == "." then "" else x) python.pythonVersion;
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pyver = if stdenv.isDarwin then builtins.substring 0 1 pyVerNoDot else pyVerNoDot;
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platform = if stdenv.isDarwin then "mac" else "linux";
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unit = if cudaSupport then "gpu" else "cpu";
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key = "${platform}_py_${pyver}_${unit}";
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in fetchurl packages.${key};
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propagatedBuildInputs = [
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protobuf
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numpy
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termcolor
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grpcio
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six
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astor
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absl-py
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gast
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google-pasta
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wrapt
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tensorflow-estimator
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tensorflow-tensorboard
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keras-applications
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keras-preprocessing
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] ++ lib.optional (!isPy3k) mock
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++ lib.optionals (pythonOlder "3.4") [ backports_weakref ];
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nativeBuildInputs = lib.optional cudaSupport addOpenGLRunpath;
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# Upstream has a pip hack that results in bin/tensorboard being in both tensorflow
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# and the propageted input tensorflow-tensorboard which causes environment collisions.
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# another possibility would be to have tensorboard only in the buildInputs
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# https://github.com/tensorflow/tensorflow/blob/v1.7.1/tensorflow/tools/pip_package/setup.py#L79
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postInstall = ''
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rm $out/bin/tensorboard
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'';
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# Note that we need to run *after* the fixup phase because the
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# libraries are loaded at runtime. If we run in preFixup then
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# patchelf --shrink-rpath will remove the cuda libraries.
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postFixup = let
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rpath = stdenv.lib.makeLibraryPath
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([ stdenv.cc.cc.lib zlib ] ++ lib.optionals cudaSupport [ cudatoolkit.out cudatoolkit.lib cudnn nvidia_x11 ]);
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in
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lib.optionalString stdenv.isLinux ''
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rrPath="$out/${python.sitePackages}/tensorflow/:$out/${python.sitePackages}/tensorflow/contrib/tensor_forest/:${rpath}"
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internalLibPath="$out/${python.sitePackages}/tensorflow/python/_pywrap_tensorflow_internal.so"
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find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
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patchelf --set-rpath "$rrPath" "$lib"
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${lib.optionalString cudaSupport ''
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addOpenGLRunpath "$lib"
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''}
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done
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'';
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meta = with stdenv.lib; {
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description = "Computation using data flow graphs for scalable machine learning";
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homepage = http://tensorflow.org;
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license = licenses.asl20;
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maintainers = with maintainers; [ jyp abbradar ];
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platforms = [ "x86_64-linux" "x86_64-darwin" ];
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# Python 2.7 build uses different string encoding.
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# See https://github.com/NixOS/nixpkgs/pull/37044#issuecomment-373452253
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broken = stdenv.isDarwin && !isPy3k;
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};
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}
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