nixpkgs/pkgs/development/python-modules/tensorflow/bin.nix

262 lines
8.3 KiB
Nix

{
stdenv,
lib,
fetchurl,
buildPythonPackage,
isPy3k,
astor,
gast,
google-pasta,
wrapt,
numpy,
six,
termcolor,
packaging,
protobuf,
absl-py,
grpcio,
mock,
scipy,
distutils,
wheel,
jax,
ml-dtypes,
opt-einsum,
tensorflow-estimator-bin,
tensorboard,
config,
cudaSupport ? config.cudaSupport,
cudaPackages,
zlib,
python,
keras-applications,
keras-preprocessing,
addDriverRunpath,
astunparse,
flatbuffers,
h5py,
llvmPackages,
typing-extensions,
}:
# We keep this binary build for three reasons:
# - the source build doesn't work on Darwin.
# - the source build is currently brittle and not easy to maintain
# - the source build doesn't work on NVIDIA Jetson platforms
# unsupported combination
assert !(stdenv.hostPlatform.isDarwin && cudaSupport);
let
packages = import ./binary-hashes.nix;
inherit (cudaPackages) cudatoolkit cudnn;
isCudaJetson = cudaSupport && cudaPackages.cudaFlags.isJetsonBuild;
isCudaX64 = cudaSupport && stdenv.hostPlatform.isx86_64;
in
buildPythonPackage rec {
pname = "tensorflow" + lib.optionalString cudaSupport "-gpu";
version = packages."${"version" + lib.optionalString isCudaJetson "_jetson"}";
format = "wheel";
src =
let
pyVerNoDot = lib.strings.stringAsChars (x: lib.optionalString (x != ".") x) python.pythonVersion;
platform = stdenv.system;
cuda = lib.optionalString cudaSupport (if isCudaJetson then "_jetson" else "_gpu");
key = "${platform}_${pyVerNoDot}${cuda}";
in
fetchurl (packages.${key} or (throw "tensoflow-bin: unsupported configuration: ${key}"));
buildInputs = [ llvmPackages.openmp ];
dependencies = [
astunparse
flatbuffers
typing-extensions
packaging
protobuf
numpy
scipy
(if isCudaX64 then jax else ml-dtypes)
termcolor
grpcio
six
astor
absl-py
gast
opt-einsum
google-pasta
wrapt
tensorflow-estimator-bin
tensorboard
keras-applications
keras-preprocessing
h5py
] ++ lib.optional (!isPy3k) mock;
build-system =
[
distutils
wheel
]
++ lib.optionals cudaSupport [ addDriverRunpath ]
++ lib.optionals isCudaJetson [ cudaPackages.autoAddCudaCompatRunpath ];
preConfigure = ''
unset SOURCE_DATE_EPOCH
# Make sure that dist and the wheel file are writable.
chmod u+rwx -R ./dist
pushd dist
for f in tensorflow-*+nv*.whl; do
# e.g. *nv24.07* -> *nv24.7*
mv "$f" "$(sed -E 's/(nv[0-9]+)\.0*([0-9]+)/\1.\2/' <<< "$f")"
done
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*
popd
'';
postFixup =
# When using the cpu-only wheel, the final package will be named `tensorflow_cpu`.
# Then, in each package requiring `tensorflow`, our pythonRuntimeDepsCheck will fail with:
# importlib.metadata.PackageNotFoundError: No package metadata was found for tensorflow
# Hence, we manually rename the package to `tensorflow`.
lib.optionalString ((builtins.match ".*tensorflow_cpu.*" src.url) != null) ''
(
cd $out/${python.sitePackages}
dest="tensorflow-${version}.dist-info"
mv tensorflow_cpu-${version}.dist-info "$dest"
(
cd "$dest"
substituteInPlace METADATA \
--replace-fail "tensorflow_cpu" "tensorflow"
substituteInPlace RECORD \
--replace-fail "tensorflow_cpu" "tensorflow"
)
)
''
# 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.
+ (
let
# rpaths we only need to add if CUDA is enabled.
cudapaths = lib.optionals cudaSupport [
cudatoolkit.out
cudatoolkit.lib
cudnn
];
libpaths = [
(lib.getLib stdenv.cc.cc)
zlib
];
rpath = lib.makeLibraryPath (libpaths ++ cudapaths);
in
lib.optionalString stdenv.hostPlatform.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/mlir/stablehlo/"
"$out/${python.sitePackages}/tensorflow/compiler/tf2tensorrt/"
"$out/${python.sitePackages}/tensorflow/compiler/tf2xla/ops/"
"$out/${python.sitePackages}/tensorflow/include/external/ml_dtypes/"
"$out/${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"
"$out/${python.sitePackages}/tensorflow.libs/"
"${rpath}"
)
# The the bash array into a colon-separated list of RPATHs.
rrPath=$(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"
${lib.optionalString cudaSupport ''
addDriverRunpath "$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"
];
meta = {
description = "Computation using data flow graphs for scalable machine learning";
homepage = "http://tensorflow.org";
sourceProvenance = with lib.sourceTypes; [ binaryNativeCode ];
license = lib.licenses.asl20;
maintainers = with lib.maintainers; [
jyp
abbradar
];
badPlatforms = [ "x86_64-darwin" ];
};
}