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{ stdenv
, lib
, fetchurl
, buildPythonPackage
, isPy3k, pythonOlder, pythonAtLeast, astor
, gast
, google-pasta
, wrapt
, numpy
, six
, termcolor
, packaging
, protobuf
, absl-py
, grpcio
, mock
, scipy
, wheel
, jax
, opt-einsum
, tensorflow-estimator-bin
, tensorboard
, config
, cudaSupport ? config.cudaSupport
, cudaPackages ? {}
, zlib
, python
, keras-applications
, keras-preprocessing
, addOpenGLRunpath
, astunparse
, flatbuffers
, h5py
, typing-extensions
}:
# 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
# unsupported combination
assert ! (stdenv.isDarwin && cudaSupport);
let
packages = import ./binary-hashes.nix;
inherit (cudaPackages) cudatoolkit cudnn;
in buildPythonPackage {
pname = "tensorflow" + lib.optionalString cudaSupport "-gpu";
inherit (packages) version;
format = "wheel";
src = let
pyVerNoDot = lib.strings.stringAsChars (x: lib.optionalString (x != ".") x) python.pythonVersion;
platform = if stdenv.isDarwin then "mac" else "linux";
unit = if cudaSupport then "gpu" else "cpu";
key = "${platform}_py_${pyVerNoDot}_${unit}";
in fetchurl (packages.${key} or {});
propagatedBuildInputs = [
astunparse
flatbuffers
typing-extensions
packaging
protobuf
numpy
scipy
jax
termcolor
grpcio
six
astor
absl-py
gast
opt-einsum
google-pasta
wrapt
tensorflow-estimator-bin
tensorboard
keras-applications
keras-preprocessing
h5py
] ++ lib.optional (!isPy3k) mock;
nativeBuildInputs = [ wheel ] ++ lib.optionals cudaSupport [ addOpenGLRunpath ];
preConfigure = ''
unset SOURCE_DATE_EPOCH
# Make sure that dist and the wheel file are writable.
chmod u+rwx -R ./dist
pushd dist
orig_name="$(echo ./*.whl)"
wheel unpack --dest unpacked ./*.whl
rm ./*.whl
(
cd unpacked/tensorflow*
# Adjust dependency requirements:
# - Relax flatbuffers, gast, protobuf, tensorboard, and tensorflow-estimator version requirements that don't match what we have packaged
# - The purpose of python3Packages.libclang is not clear at the moment and we don't have it packaged yet
# - keras and tensorlow-io-gcs-filesystem will be considered as optional for now.
# - numpy was pinned to fix some internal tests: https://github.com/tensorflow/tensorflow/issues/60216
sed -i *.dist-info/METADATA \
-e "/Requires-Dist: flatbuffers/d" \
-e "/Requires-Dist: gast/d" \
-e "/Requires-Dist: keras/d" \
-e "/Requires-Dist: libclang/d" \
-e "/Requires-Dist: protobuf/d" \
-e "/Requires-Dist: tensorboard/d" \
-e "/Requires-Dist: tensorflow-estimator/d" \
-e "/Requires-Dist: tensorflow-io-gcs-filesystem/d" \
-e "s/Requires-Dist: numpy (.*)/Requires-Dist: numpy/"
)
wheel pack ./unpacked/tensorflow*
mv *.whl $orig_name # avoid changes to the _os_arch.whl suffix
popd
'';
# Note that we need to run *after* the fixup phase because the
# libraries are loaded at runtime. If we run in preFixup then
# patchelf --shrink-rpath will remove the cuda libraries.
postFixup =
let
# rpaths we only need to add if CUDA is enabled.
cudapaths = lib.optionals cudaSupport [
cudatoolkit.out
cudatoolkit.lib
cudnn
];
libpaths = [
stdenv.cc.cc.lib
zlib
];
rpath = lib.makeLibraryPath (libpaths ++ cudapaths);
in
lib.optionalString stdenv.isLinux ''
# This is an array containing all the directories in the tensorflow2
# package that contain .so files.
#
# TODO: Create this list programmatically, and remove paths that aren't
# actually needed.
rrPathArr=(
"$out/${python.sitePackages}/tensorflow/"
"$out/${python.sitePackages}/tensorflow/core/kernels"
"$out/${python.sitePackages}/tensorflow/compiler/tf2tensorrt/"
"$out/${python.sitePackages}/tensorflow/compiler/tf2xla/ops/"
"$out/${python.sitePackages}/tensorflow/lite/experimental/microfrontend/python/ops/"
"$out/${python.sitePackages}/tensorflow/lite/python/analyzer_wrapper/"
"$out/${python.sitePackages}/tensorflow/lite/python/interpreter_wrapper/"
"$out/${python.sitePackages}/tensorflow/lite/python/metrics/"
"$out/${python.sitePackages}/tensorflow/lite/python/optimize/"
"$out/${python.sitePackages}/tensorflow/python/"
"$out/${python.sitePackages}/tensorflow/python/autograph/impl/testing"
"$out/${python.sitePackages}/tensorflow/python/client"
"$out/${python.sitePackages}/tensorflow/python/data/experimental/service"
"$out/${python.sitePackages}/tensorflow/python/framework"
"$out/${python.sitePackages}/tensorflow/python/grappler"
"$out/${python.sitePackages}/tensorflow/python/lib/core"
"$out/${python.sitePackages}/tensorflow/python/lib/io"
"$out/${python.sitePackages}/tensorflow/python/platform"
"$out/${python.sitePackages}/tensorflow/python/profiler/internal"
"$out/${python.sitePackages}/tensorflow/python/saved_model"
"$out/${python.sitePackages}/tensorflow/python/util"
"$out/${python.sitePackages}/tensorflow/tsl/python/lib/core"
"${rpath}"
)
# The the bash array into a colon-separated list of RPATHs.
rrPath=$(IFS=$':'; echo "''${rrPathArr[*]}")
echo "about to run patchelf with the following rpath: $rrPath"
find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
echo "about to patchelf $lib..."
chmod a+rx "$lib"
patchelf --set-rpath "$rrPath" "$lib"
${lib.optionalString cudaSupport ''
addOpenGLRunpath "$lib"
''}
done
'';
# Upstream has a pip hack that results in bin/tensorboard being in both tensorflow
# and the propagated input tensorboard, which causes environment collisions.
# Another possibility would be to have tensorboard only in the buildInputs
# See https://github.com/NixOS/nixpkgs/pull/44381 for more information.
postInstall = ''
rm $out/bin/tensorboard
'';
pythonImportsCheck = [
"tensorflow"
"tensorflow.python"
"tensorflow.python.framework"
];
passthru = {
inherit cudaPackages;
};
meta = with lib; {
description = "Computation using data flow graphs for scalable machine learning";
homepage = "http://tensorflow.org";
sourceProvenance = with sourceTypes; [ binaryNativeCode ];
license = licenses.asl20;
maintainers = with maintainers; [ jyp abbradar ];
platforms = [ "x86_64-linux" "x86_64-darwin" ];
};
}
|