154 lines
4.8 KiB
Nix
154 lines
4.8 KiB
Nix
{ stdenv, buildBazelPackage, lib, fetchFromGitHub, fetchpatch, symlinkJoin
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, buildPythonPackage, isPy3k, pythonOlder, pythonAtLeast
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, which, swig, binutils, glibcLocales
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, python, jemalloc, openmpi
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, numpy, six, protobuf, tensorflow-tensorboard, backports_weakref, mock, enum34, absl-py
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, xlaSupport ? true
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, cudaSupport ? false, nvidia_x11 ? null, cudatoolkit ? null, cudnn ? null
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# Default from ./configure script
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, cudaCapabilities ? [ "3.5" "5.2" ]
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, sse42Support ? false
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, avx2Support ? false
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, fmaSupport ? false
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}:
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assert cudaSupport -> nvidia_x11 != null
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&& cudatoolkit != null
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&& cudnn != null;
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# unsupported combination
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assert ! (stdenv.isDarwin && cudaSupport);
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let
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withTensorboard = pythonOlder "3.6";
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cudatoolkit_joined = symlinkJoin {
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name = "${cudatoolkit.name}-unsplit";
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paths = [ cudatoolkit.out cudatoolkit.lib ];
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};
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tfFeature = x: if x then "1" else "0";
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version = "1.5.0";
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pkg = buildBazelPackage rec {
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name = "tensorflow-build-${version}";
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src = fetchFromGitHub {
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owner = "tensorflow";
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repo = "tensorflow";
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rev = "v${version}";
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sha256 = "1c4djsaip901nasm7a6dsimr02bsv70a7b1g0kysb4n39qpdh22q";
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};
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patches = [
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# Fix build with Bazel >= 0.10
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(fetchpatch {
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url = "https://github.com/tensorflow/tensorflow/commit/6fcfab770c2672e2250e0f5686b9545d99eb7b2b.patch";
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sha256 = "0p61za1mx3a7gj1s5lsps16fcw18iwnvq2b46v1kyqfgq77a12vb";
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})
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(fetchpatch {
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url = "https://github.com/tensorflow/tensorflow/commit/3f57956725b553d196974c9ad31badeb3eabf8bb.patch";
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sha256 = "11dja5gqy0qw27sc9b6yw9r0lfk8dznb32vrqqfcnypk2qmv26va";
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})
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];
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nativeBuildInputs = [ swig which ];
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buildInputs = [ python jemalloc openmpi glibcLocales numpy ]
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++ lib.optionals cudaSupport [ cudatoolkit cudnn nvidia_x11 ];
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preConfigure = ''
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patchShebangs configure
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export PYTHON_BIN_PATH="${python.interpreter}"
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export PYTHON_LIB_PATH="$NIX_BUILD_TOP/site-packages"
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export TF_NEED_GCP=1
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export TF_NEED_HDFS=1
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export TF_ENABLE_XLA=${tfFeature xlaSupport}
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export CC_OPT_FLAGS=" "
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# https://github.com/tensorflow/tensorflow/issues/14454
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export TF_NEED_MPI=${tfFeature cudaSupport}
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export TF_NEED_CUDA=${tfFeature cudaSupport}
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${lib.optionalString cudaSupport ''
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export CUDA_TOOLKIT_PATH=${cudatoolkit_joined}
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export TF_CUDA_VERSION=${cudatoolkit.majorVersion}
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export CUDNN_INSTALL_PATH=${cudnn}
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export TF_CUDNN_VERSION=${cudnn.majorVersion}
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export GCC_HOST_COMPILER_PATH=${cudatoolkit.cc}/bin/gcc
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export TF_CUDA_COMPUTE_CAPABILITIES=${lib.concatStringsSep "," cudaCapabilities}
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''}
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mkdir -p "$PYTHON_LIB_PATH"
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'';
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NIX_LDFLAGS = lib.optionals cudaSupport [ "-lcublas" "-lcudnn" "-lcuda" "-lcudart" ];
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hardeningDisable = [ "all" ];
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bazelFlags = [ "--config=opt" ]
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++ lib.optional sse42Support "--copt=-msse4.2"
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++ lib.optional avx2Support "--copt=-mavx2"
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++ lib.optional fmaSupport "--copt=-mfma"
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++ lib.optional cudaSupport "--config=cuda";
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bazelTarget = "//tensorflow/tools/pip_package:build_pip_package";
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fetchAttrs = {
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preInstall = ''
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rm -rf $bazelOut/external/{bazel_tools,\@bazel_tools.marker,local_*,\@local_*}
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'';
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sha256 = "1nc98aqrp14q7llypcwaa0kdn9xi7r0p1mnd3vmmn1m299py33ca";
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};
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buildAttrs = {
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preBuild = ''
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patchShebangs .
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find -type f -name CROSSTOOL\* -exec sed -i \
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-e 's,/usr/bin/ar,${binutils.bintools}/bin/ar,g' \
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{} \;
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'';
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installPhase = ''
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sed -i 's,.*bdist_wheel.*,cp -rL . "$out"; exit 0,' bazel-bin/tensorflow/tools/pip_package/build_pip_package
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bazel-bin/tensorflow/tools/pip_package/build_pip_package $PWD/dist
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'';
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};
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dontFixup = true;
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};
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in buildPythonPackage rec {
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pname = "tensorflow";
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inherit version;
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name = "${pname}-${version}";
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src = pkg;
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installFlags = lib.optional (!withTensorboard) "--no-dependencies";
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postPatch = lib.optionalString (pythonAtLeast "3.4") ''
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sed -i '/enum34/d' setup.py
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'';
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propagatedBuildInputs = [ numpy six protobuf absl-py ]
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++ lib.optional (!isPy3k) mock
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++ lib.optionals (pythonOlder "3.4") [ backports_weakref enum34 ]
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++ lib.optional withTensorboard tensorflow-tensorboard;
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# Actual tests are slow and impure.
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checkPhase = ''
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${python.interpreter} -c "import tensorflow"
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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 = with platforms; if cudaSupport then linux else linux ++ darwin;
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};
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}
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