tensorflow: 1.3.0 ->1.3.1
Build from source. It's implemented as a two-staged Bazel build (see also 546b4aec776b3ea676bb4d58d89751919ce4f1ef).
This commit is contained in:
Nikolay Amiantov
parent
e3afbd6d26
commit
fe153d73ce
@ -1,156 +1,179 @@
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{ stdenv
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, symlinkJoin
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, lib
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, fetchurl
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, buildPythonPackage
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, isPy3k, isPy35, isPy36, isPy27
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, cudaSupport ? false
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, cudatoolkit ? null
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, cudnn ? null
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, linuxPackages ? null
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, numpy
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, six
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, protobuf
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, mock
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, backports_weakref
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, zlib
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, tensorflow-tensorboard
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{ stdenv, lib, fetchFromGitHub, fetchpatch, symlinkJoin, buildPythonPackage, isPy3k, pythonOlder
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, bazel, which, swig, binutils, glibcLocales
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, python, jemalloc, openmpi
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, numpy, six, protobuf, tensorflow-tensorboard, backports_weakref
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, wheel, mock, scipy
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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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}:
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assert cudaSupport -> cudatoolkit != null
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&& cudnn != null
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&& linuxPackages != 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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# tensorflow is built from a downloaded wheel, because the upstream
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# project's build system is an arcane beast based on
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# bazel. Untangling it and building the wheel from source is an open
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# problem.
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let
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buildPythonPackage rec {
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pname = "tensorflow";
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version = "1.3.0";
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name = "${pname}-${version}";
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format = "wheel";
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disabled = ! (isPy35 || isPy36 || isPy27);
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withTensorboard = pythonOlder "3.6";
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# cudatoolkit is split (see https://github.com/NixOS/nixpkgs/commit/bb1c9b027d343f2ce263496582d6b56af8af92e6)
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# However this means that libcusolver is not loadable by tensor flow. So we undo the split here.
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cudatoolkit_joined = symlinkJoin {
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name = "unsplit_cudatoolkit";
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paths = [ cudatoolkit.out
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cudatoolkit.lib ];};
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name = "${cudatoolkit.name}-unsplit";
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paths = [ cudatoolkit.out cudatoolkit.lib ];
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};
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src = let
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tfurl = sys: proc: pykind:
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let
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tfpref = if proc == "gpu"
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then "gpu/tensorflow_gpu"
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else "cpu/tensorflow";
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in
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"https://storage.googleapis.com/tensorflow/${sys}/${tfpref}-${version}-${pykind}.whl";
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dls =
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{
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darwin.cpu = {
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py2 = {
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url = tfurl "mac" "cpu" "py2-none-any" ;
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sha256 = "0nkymqbqjx8rsmc8vkc26cfsg4hpr6lj9zrwhjnfizvkzbbsh5z4";
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};
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py3 = {
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url = tfurl "mac" "cpu" "py3-none-any" ;
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sha256 = "1rj4m817w3lajnb1lgn3bwfwwk3qwvypyx11dim1ybakbmsc1j20";
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};
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};
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linux-x86_64.cpu = {
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py2 = {
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url = tfurl "linux" "cpu" "cp27-none-linux_x86_64";
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sha256 = "09pcyx0yfil4dm6cij8n3907pfgva07a38avrbai4qk5h6hxm8w9";
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};
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py35 = {
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url = tfurl "linux" "cpu" "cp35-cp35m-linux_x86_64";
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sha256 = "0p10zcf41pi33bi025fibqkq9rpd3v0rrbdmc9i9yd7igy076a07";
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};
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py36 = {
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url = tfurl "linux" "cpu" "cp36-cp36m-linux_x86_64";
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sha256 = "1qm8lm2f6bf9d462ybgwrz0dn9i6cnisgwdvyq9ssmy2f1gp8hxk";
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};
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};
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linux-x86_64.cuda = {
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py2 = {
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url = tfurl "linux" "gpu" "cp27-none-linux_x86_64";
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sha256 = "10yyyn4g2fsv1xgmw99bbr0fg7jvykay4gb5pxrrylh7h38h6wah";
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};
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py35 = {
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url = tfurl "linux" "gpu" "cp35-cp35m-linux_x86_64";
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sha256 = "0icwnhkcf3fxr6bmbihqzipnn4pxybd06qv7l3k0p4xdgycwzmzk";
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};
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py36 = {
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url = tfurl "linux" "gpu" "cp36-cp36m-linux_x86_64";
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sha256 = "12g3akkr083gs3sisjbmm0lpsk8phn3dvy7jjfadfxshqc7za14i";
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};
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};
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};
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in
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fetchurl (
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if stdenv.isDarwin then
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if isPy3k then
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dls.darwin.cpu.py3
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else
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dls.darwin.cpu.py2
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else
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if isPy35 then
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if cudaSupport then
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dls.linux-x86_64.cuda.py35
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else
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dls.linux-x86_64.cpu.py35
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else if isPy36 then
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if cudaSupport then
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dls.linux-x86_64.cuda.py36
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else
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dls.linux-x86_64.cpu.py36
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else
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if cudaSupport then
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dls.linux-x86_64.cuda.py2
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else
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dls.linux-x86_64.cpu.py2
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);
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cudaLibPath = lib.makeLibraryPath [ cudatoolkit.out cudatoolkit.lib nvidia_x11 cudnn ];
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propagatedBuildInputs =
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[ numpy six protobuf mock backports_weakref ]
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++ lib.optional (!isPy36) tensorflow-tensorboard
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++ lib.optionals cudaSupport [ cudatoolkit_joined cudnn stdenv.cc ];
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tfFeature = x: if x then "1" else "0";
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# tensorflow-gpu depends on tensorflow_tensorboard, which cannot be
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common = rec {
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version = "1.3.1";
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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 = "0gvi32dvv4ynr05p0gg5i0a6c55pig48k5qm7zslcqnp4sifwx0i";
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};
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nativeBuildInputs = [ swig which wheel scipy ];
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buildInputs = [ python jemalloc openmpi glibcLocales ]
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++ lib.optionals cudaSupport [ cudatoolkit cudnn ];
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propagatedBuildInputs = [ numpy six protobuf ]
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++ lib.optional (!isPy3k) mock
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++ lib.optional (pythonOlder "3.4") backports_weakref
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++ lib.optional withTensorboard tensorflow-tensorboard;
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preConfigure = ''
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patchShebangs configure
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export HOME="$NIX_BUILD_TOP"
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export PYTHON_BIN_PATH="${python.interpreter}"
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export TF_NEED_GCP=1
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export TF_NEED_HDFS=1
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export TF_NEED_CUDA=${tfFeature cudaSupport}
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export TF_NEED_MPI=1
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export TF_ENABLE_XLA=${tfFeature xlaSupport}
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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=${lib.concatStringsSep "," cudaCapabilities}
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''}
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# There is _no_ non-interactive mode of configure.
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sed -i \
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-e 's,read -p,echo,g' \
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-e 's,lib64,lib,g' \
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configure
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'';
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hardeningDisable = [ "all" ];
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bazelFlags = [ "--config=opt" ]
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++ lib.optional cudaSupport "--config=cuda";
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bazelTarget = "//tensorflow/tools/pip_package:build_pip_package";
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meta = with stdenv.lib; {
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description = "Computation using data flow graphs for scalable machine learning";
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homepage = "http://tensorflow.org";
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license = licenses.asl20;
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maintainers = with maintainers; [ jyp abbradar ];
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platforms = with platforms; if cudaSupport then linux else linux ++ darwin;
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};
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};
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in buildPythonPackage (common // {
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name = "tensorflow-${common.version}";
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deps = stdenv.mkDerivation (common // {
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name = "tensorflow-external-${common.version}";
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nativeBuildInputs = common.nativeBuildInputs ++ [ bazel ];
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preConfigure = common.preConfigure + ''
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export PYTHON_LIB_PATH="$(pwd)/site-packages"
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'';
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buildPhase = ''
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mkdir site-packages
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bazel --output_base="$(pwd)/output" fetch $bazelFlags $bazelTarget
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'';
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installPhase = ''
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rm -rf output/external/{bazel_tools,\@bazel_tools.marker,local_*,\@local_*}
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# Patching markers to make them deterministic
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for i in output/external/\@*.marker; do
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sed -i 's, -\?[0-9][0-9]*$, 1,' "$i"
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done
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# Patching symlinks to remove build directory reference
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find output/external -type l | while read symlink; do
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ln -sf $(readlink "$symlink" | sed "s,$NIX_BUILD_TOP,NIX_BUILD_TOP,") "$symlink"
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done
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cp -r output/external $out
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'';
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dontFixup = true;
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outputHashMode = "recursive";
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outputHashAlgo = "sha256";
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outputHash = "0xs2n061gnpizfcnhs5jjpfk2av634j1l2l17zhy10bbmrwn3vrp";
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});
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nativeBuildInputs = common.nativeBuildInputs ++ [ (bazel.override { enableNixHacks = true; }) ];
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configurePhase = ''
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runHook preConfigure
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export PYTHON_LIB_PATH="$out/${python.sitePackages}"
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./configure
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runHook postConfigure
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'';
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buildPhase = ''
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mkdir -p output/external
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cp -r $deps/* output/external
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chmod -R +w output
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find output -type l | while read symlink; do
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ln -sf $(readlink "$symlink" | sed "s,NIX_BUILD_TOP,$NIX_BUILD_TOP,") "$symlink"
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done
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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}/bin/ar,g' \
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{} \;
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mkdir -p $out/${python.sitePackages}
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bazel --output_base="$(pwd)/output" build $bazelFlags $bazelTarget
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bazel-bin/tensorflow/tools/pip_package/build_pip_package $PWD/dist
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'';
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# tensorflow depends on tensorflow_tensorboard, which cannot be
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# built at the moment (some of its dependencies do not build
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# [htlm5lib9999999 (seven nines) -> tensorboard], and it depends on an old version of
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# bleach) Hence we disable dependency checking for now.
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installFlags = lib.optional isPy36 "--no-dependencies";
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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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(if cudaSupport then
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[ stdenv.cc.cc.lib zlib cudatoolkit_joined cudnn
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linuxPackages.nvidia_x11 ]
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else
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[ stdenv.cc.cc.lib zlib ]
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);
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in
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''
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find $out -name '*.so' -exec patchelf --set-rpath "${rpath}" {} \;
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'';
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installFlags = lib.optional (!withTensorboard) "--no-dependencies";
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# Tests are slow and impure.
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doCheck = false;
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meta = with stdenv.lib; {
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description = "TensorFlow helps the tensors flow";
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homepage = http://tensorflow.org;
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license = licenses.asl20;
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maintainers = with maintainers; [ jyp ];
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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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# For some reason, CUDA is not retained in RPATH.
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postFixup = lib.optionalString cudaSupport ''
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libPath="$out/${python.sitePackages}/tensorflow/python/_pywrap_tensorflow_internal.so"
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patchelf --set-rpath "$(patchelf --print-rpath "$libPath"):${cudaLibPath}" "$libPath"
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'';
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doInstallCheck = true;
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installCheckPhase = ''
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cd $NIX_BUILD_TOP
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${python.interpreter} -c "import tensorflow"
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'';
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})
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@ -25974,8 +25974,12 @@ EOF
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tensorflow-tensorboard = callPackage ../development/python-modules/tensorflow-tensorboard { };
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tensorflow = callPackage ../development/python-modules/tensorflow {
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tensorflow = callPackage ../development/python-modules/tensorflow rec {
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bazel = pkgs.bazel_0_4;
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cudaSupport = pkgs.config.cudaSupport or false;
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inherit (pkgs.linuxPackages) nvidia_x11;
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cudatoolkit = pkgs.cudatoolkit8;
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cudnn = pkgs.cudnn6_cudatoolkit8;
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};
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tensorflowWithoutCuda = self.tensorflow.override {
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