nixpkgs/pkgs/development/python-modules/tensorflow/bin.nix
Colin f634a929d4 pythonPackages.tensorflow: Hardcode a second search class. (#65584)
It appears without this, libcuda.so.1 is not picked up and nvidia
graphics are broken
2019-07-31 13:00:12 +03:00

109 lines
3.2 KiB
Nix

{ stdenv
, lib
, fetchurl
, buildPythonPackage
, isPy3k, pythonOlder
, astor
, gast
, google-pasta
, wrapt
, numpy
, six
, termcolor
, protobuf
, absl-py
, grpcio
, mock
, backports_weakref
, tensorflow-estimator
, tensorflow-tensorboard
, cudaSupport ? false
, cudatoolkit ? null
, cudnn ? null
, nvidia_x11 ? null
, zlib
, python
, symlinkJoin
, keras-applications
, keras-preprocessing
}:
# We keep this binary build for two reasons:
# - the source build doesn't work on Darwin.
# - the source build is currently brittle and not easy to maintain
assert cudaSupport -> cudatoolkit != null
&& cudnn != null
&& nvidia_x11 != null;
let
cudatoolkit_joined = symlinkJoin {
name = "unsplit_cudatoolkit";
paths = [ cudatoolkit.out
cudatoolkit.lib ];};
in buildPythonPackage rec {
pname = "tensorflow";
version = "1.14.0";
format = "wheel";
src = let
pyVerNoDot = lib.strings.stringAsChars (x: if x == "." then "" else x) "${python.pythonVersion}";
pyver = if stdenv.isDarwin then builtins.substring 0 1 pyVerNoDot else pyVerNoDot;
platform = if stdenv.isDarwin then "mac" else "linux";
unit = if cudaSupport then "gpu" else "cpu";
key = "${platform}_py_${pyver}_${unit}";
dls = import (./. + "/tf${version}-hashes.nix");
in fetchurl dls.${key};
propagatedBuildInputs = [
protobuf
numpy
termcolor
grpcio
six
astor
absl-py
gast
google-pasta
wrapt
tensorflow-estimator
tensorflow-tensorboard
keras-applications
keras-preprocessing
] ++ lib.optional (!isPy3k) mock
++ lib.optionals (pythonOlder "3.4") [ backports_weakref ];
# Upstream has a pip hack that results in bin/tensorboard being in both tensorflow
# and the propageted input tensorflow-tensorboard which causes environment collisions.
# another possibility would be to have tensorboard only in the buildInputs
# https://github.com/tensorflow/tensorflow/blob/v1.7.1/tensorflow/tools/pip_package/setup.py#L79
postInstall = ''
rm $out/bin/tensorboard
'';
# Note that we need to run *after* the fixup phase because the
# libraries are loaded at runtime. If we run in preFixup then
# patchelf --shrink-rpath will remove the cuda libraries.
postFixup = let
rpath = stdenv.lib.makeLibraryPath
([ stdenv.cc.cc.lib zlib ] ++ lib.optionals cudaSupport [ cudatoolkit_joined cudnn nvidia_x11 ]);
in
lib.optionalString (stdenv.isLinux) ''
rrPath="$out/${python.sitePackages}/tensorflow/:$out/${python.sitePackages}/tensorflow/contrib/tensor_forest/:${rpath}"
internalLibPath="$out/${python.sitePackages}/tensorflow/python/_pywrap_tensorflow_internal.so"
find $out \( -name '*.so' -or -name '*.so.*' \) -exec patchelf --set-rpath "$rrPath" {} \;
'';
meta = with stdenv.lib; {
description = "Computation using data flow graphs for scalable machine learning";
homepage = http://tensorflow.org;
license = licenses.asl20;
maintainers = with maintainers; [ jyp abbradar ];
platforms = with platforms; linux ++ lib.optionals (!cudaSupport) darwin;
# Python 2.7 build uses different string encoding.
# See https://github.com/NixOS/nixpkgs/pull/37044#issuecomment-373452253
broken = stdenv.isDarwin && !isPy3k;
};
}