432 lines
13 KiB
Nix
432 lines
13 KiB
Nix
{ stdenv, bazel_3, buildBazelPackage, isPy3k, lib, fetchFromGitHub, symlinkJoin
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, addOpenGLRunpath, fetchpatch
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# Python deps
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, buildPythonPackage, pythonOlder, pythonAtLeast, python
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# Python libraries
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, numpy, tensorflow-tensorboard_2, absl-py
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, future, setuptools, wheel, keras-preprocessing, google-pasta
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, opt-einsum, astunparse, h5py
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, termcolor, grpcio, six, wrapt, protobuf, tensorflow-estimator_2
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, dill, flatbuffers-python, tblib, typing-extensions
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# Common deps
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, git, pybind11, which, binutils, glibcLocales, cython, perl
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# Common libraries
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, jemalloc, mpi, gast, grpc, sqlite, boringssl, jsoncpp
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, curl, snappy, flatbuffers-core, lmdb-core, icu, double-conversion, libpng, libjpeg_turbo, giflib
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# Upsteam by default includes cuda support since tensorflow 1.15. We could do
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# that in nix as well. It would make some things easier and less confusing, but
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# it would also make the default tensorflow package unfree. See
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# https://groups.google.com/a/tensorflow.org/forum/#!topic/developers/iRCt5m4qUz0
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, cudaSupport ? false, cudatoolkit ? null, cudnn ? null, nccl ? null
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, mklSupport ? false, mkl ? null
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, tensorboardSupport ? true
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# XLA without CUDA is broken
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, xlaSupport ? cudaSupport
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# Default from ./configure script
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, cudaCapabilities ? [ "sm_35" "sm_50" "sm_60" "sm_70" "sm_75" "compute_80" ]
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, sse42Support ? stdenv.hostPlatform.sse4_2Support
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, avx2Support ? stdenv.hostPlatform.avx2Support
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, fmaSupport ? stdenv.hostPlatform.fmaSupport
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# Darwin deps
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, Foundation, Security
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}:
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assert cudaSupport -> 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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assert mklSupport -> mkl != null;
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let
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withTensorboard = (pythonOlder "3.6") || tensorboardSupport;
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cudatoolkit_joined = symlinkJoin {
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name = "${cudatoolkit.name}-merged";
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paths = [
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cudatoolkit.lib
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cudatoolkit.out
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] ++ lib.optionals (lib.versionOlder cudatoolkit.version "11") [
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# for some reason some of the required libs are in the targets/x86_64-linux
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# directory; not sure why but this works around it
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"${cudatoolkit}/targets/${stdenv.system}"
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];
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};
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cudatoolkit_cc_joined = symlinkJoin {
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name = "${cudatoolkit.cc.name}-merged";
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paths = [
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cudatoolkit.cc
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binutils.bintools # for ar, dwp, nm, objcopy, objdump, strip
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];
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};
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# Needed for _some_ system libraries, grep INCLUDEDIR.
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includes_joined = symlinkJoin {
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name = "tensorflow-deps-merged";
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paths = [
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jsoncpp
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];
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};
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tfFeature = x: if x then "1" else "0";
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version = "2.4.2";
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variant = if cudaSupport then "-gpu" else "";
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pname = "tensorflow${variant}";
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pythonEnv = python.withPackages (_:
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[ # python deps needed during wheel build time (not runtime, see the buildPythonPackage part for that)
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# This list can likely be shortened, but each trial takes multiple hours so won't bother for now.
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absl-py
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astunparse
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dill
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flatbuffers-python
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gast
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google-pasta
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grpcio
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h5py
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keras-preprocessing
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numpy
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opt-einsum
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protobuf
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setuptools
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six
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tblib
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tensorflow-estimator_2
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tensorflow-tensorboard_2
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termcolor
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typing-extensions
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wheel
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wrapt
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]);
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bazel-build = buildBazelPackage {
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name = "${pname}-${version}";
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bazel = bazel_3;
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src = fetchFromGitHub {
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owner = "tensorflow";
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repo = "tensorflow";
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rev = "v${version}";
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sha256 = "07a2y05hixch1bjag5pzw3p1m7bdj3bq4gdvmsfk2xraz49b1pi8";
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};
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patches = [
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# included from 2.6.0 onwards
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(fetchpatch {
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name = "fix-numpy-1.20-notimplementederror.patch";
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url = "https://github.com/tensorflow/tensorflow/commit/b258941525f496763d4277045b6513c815720e3a.patch";
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sha256 = "19f9bzrcfsynk11s2hqvscin5c65zf7r6g3nb10jnimw79vafiry";
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})
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# Relax too strict Python packages versions dependencies.
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./relax-dependencies.patch
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# Add missing `io_bazel_rules_docker` dependency.
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./workspace.patch
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];
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# On update, it can be useful to steal the changes from gentoo
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# https://gitweb.gentoo.org/repo/gentoo.git/tree/sci-libs/tensorflow
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nativeBuildInputs = [
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which pythonEnv cython perl
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] ++ lib.optional cudaSupport addOpenGLRunpath;
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buildInputs = [
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jemalloc
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mpi
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glibcLocales
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git
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# libs taken from system through the TF_SYS_LIBS mechanism
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grpc
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sqlite
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boringssl
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jsoncpp
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curl
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pybind11
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snappy
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flatbuffers-core
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icu
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double-conversion
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libpng
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libjpeg_turbo
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giflib
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lmdb-core
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] ++ lib.optionals cudaSupport [
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cudatoolkit
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cudnn
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] ++ lib.optionals mklSupport [
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mkl
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] ++ lib.optionals stdenv.isDarwin [
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Foundation
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Security
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];
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# arbitrarily set to the current latest bazel version, overly careful
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TF_IGNORE_MAX_BAZEL_VERSION = true;
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# Take as many libraries from the system as possible. Keep in sync with
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# list of valid syslibs in
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# https://github.com/tensorflow/tensorflow/blob/master/third_party/systemlibs/syslibs_configure.bzl
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TF_SYSTEM_LIBS = lib.concatStringsSep "," [
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"absl_py"
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"astor_archive"
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"astunparse_archive"
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"boringssl"
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# Not packaged in nixpkgs
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# "com_github_googleapis_googleapis"
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# "com_github_googlecloudplatform_google_cloud_cpp"
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"com_github_grpc_grpc"
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# Multiple issues with custom protobuf.
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# First `com_github_googleapis` fails to configure. Can be worked around by disabling `com_github_googleapis`
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# and related functionality, but then the next error is about "dangling symbolic link", and in general
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# looks like that's only the beginning: see
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# https://stackoverflow.com/questions/55578884/how-to-build-tensorflow-1-13-1-with-custom-protobuf
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# "com_google_protobuf"
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# Fails with the error: external/org_tensorflow/tensorflow/core/profiler/utils/tf_op_utils.cc:46:49: error: no matching function for call to 're2::RE2::FullMatch(absl::lts_2020_02_25::string_view&, re2::RE2&)'
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# "com_googlesource_code_re2"
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"curl"
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"cython"
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"dill_archive"
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"double_conversion"
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"enum34_archive"
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"flatbuffers"
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"functools32_archive"
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"gast_archive"
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"gif"
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"hwloc"
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"icu"
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"jsoncpp_git"
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"libjpeg_turbo"
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"lmdb"
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"nasm"
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# "nsync" # not packaged in nixpkgs
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"opt_einsum_archive"
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"org_sqlite"
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"pasta"
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"pcre"
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"png"
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"pybind11"
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"six_archive"
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"snappy"
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"tblib_archive"
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"termcolor_archive"
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"typing_extensions_archive"
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"wrapt"
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"zlib"
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];
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INCLUDEDIR = "${includes_joined}/include";
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PYTHON_BIN_PATH = pythonEnv.interpreter;
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TF_NEED_GCP = true;
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TF_NEED_HDFS = true;
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TF_ENABLE_XLA = tfFeature xlaSupport;
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CC_OPT_FLAGS = " ";
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# https://github.com/tensorflow/tensorflow/issues/14454
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TF_NEED_MPI = tfFeature cudaSupport;
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TF_NEED_CUDA = tfFeature cudaSupport;
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TF_CUDA_PATHS = lib.optionalString cudaSupport "${cudatoolkit_joined},${cudnn},${nccl}";
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GCC_HOST_COMPILER_PREFIX = lib.optionalString cudaSupport "${cudatoolkit_cc_joined}/bin";
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GCC_HOST_COMPILER_PATH = lib.optionalString cudaSupport "${cudatoolkit_cc_joined}/bin/gcc";
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TF_CUDA_COMPUTE_CAPABILITIES = lib.concatStringsSep "," cudaCapabilities;
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postPatch = ''
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# bazel 3.3 should work just as well as bazel 3.1
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rm -f .bazelversion
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'' + lib.optionalString (!withTensorboard) ''
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# Tensorboard pulls in a bunch of dependencies, some of which may
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# include security vulnerabilities. So we make it optional.
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# https://github.com/tensorflow/tensorflow/issues/20280#issuecomment-400230560
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sed -i '/tensorboard ~=/d' tensorflow/tools/pip_package/setup.py
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'';
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# https://github.com/tensorflow/tensorflow/pull/39470
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NIX_CFLAGS_COMPILE = [ "-Wno-stringop-truncation" ];
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preConfigure = let
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opt_flags = []
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++ lib.optionals sse42Support ["-msse4.2"]
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++ lib.optionals avx2Support ["-mavx2"]
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++ lib.optionals fmaSupport ["-mfma"];
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in ''
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patchShebangs configure
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# dummy ldconfig
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mkdir dummy-ldconfig
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echo "#!${stdenv.shell}" > dummy-ldconfig/ldconfig
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chmod +x dummy-ldconfig/ldconfig
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export PATH="$PWD/dummy-ldconfig:$PATH"
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export PYTHON_LIB_PATH="$NIX_BUILD_TOP/site-packages"
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export CC_OPT_FLAGS="${lib.concatStringsSep " " opt_flags}"
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mkdir -p "$PYTHON_LIB_PATH"
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# To avoid mixing Python 2 and Python 3
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unset PYTHONPATH
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'';
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configurePhase = ''
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runHook preConfigure
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./configure
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runHook postConfigure
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'';
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hardeningDisable = [ "format" ];
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bazelBuildFlags = [
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"--config=opt" # optimize using the flags set in the configure phase
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]
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++ lib.optionals (mklSupport) [ "--config=mkl" ];
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bazelTarget = "//tensorflow/tools/pip_package:build_pip_package //tensorflow/tools/lib_package:libtensorflow";
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removeRulesCC = false;
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# Without this Bazel complaints about sandbox violations.
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dontAddBazelOpts = true;
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fetchAttrs = {
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# cudaSupport causes fetch of ncclArchive, resulting in different hashes
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sha256 = if cudaSupport then
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"10m6qj3kchgxfgb6qh59vc51knm9r9pkng8bf90h00dnggvv8234"
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else
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"04a98yrp09nd0p17k0jbzkgjppxs0yma7m5zkfrwgvr4g0w71v68";
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};
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buildAttrs = {
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outputs = [ "out" "python" ];
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preBuild = ''
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patchShebangs .
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'';
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installPhase = ''
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mkdir -p "$out"
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tar -xf bazel-bin/tensorflow/tools/lib_package/libtensorflow.tar.gz -C "$out"
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# Write pkgconfig file.
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mkdir "$out/lib/pkgconfig"
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cat > "$out/lib/pkgconfig/tensorflow.pc" << EOF
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Name: TensorFlow
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Version: ${version}
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Description: Library for computation using data flow graphs for scalable machine learning
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Requires:
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Libs: -L$out/lib -ltensorflow
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Cflags: -I$out/include/tensorflow
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EOF
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# build the source code, then copy it to $python (build_pip_package
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# actually builds a symlink farm so we must dereference them).
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bazel-bin/tensorflow/tools/pip_package/build_pip_package --src "$PWD/dist"
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cp -Lr "$PWD/dist" "$python"
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'';
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postFixup = lib.optionalString cudaSupport ''
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find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
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addOpenGLRunpath "$lib"
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done
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'';
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requiredSystemFeatures = [
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"big-parallel"
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];
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};
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meta = with 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; linux ++ darwin;
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broken = !(xlaSupport -> cudaSupport);
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};
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};
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in buildPythonPackage {
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inherit version pname;
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disabled = !isPy3k;
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src = bazel-build.python;
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# Upstream has a pip hack that results in bin/tensorboard being in both tensorflow
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# and the propagated input tensorflow-tensorboard, which causes environment collisions.
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# Another possibility would be to have tensorboard only in the buildInputs
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# https://github.com/tensorflow/tensorflow/blob/v1.7.1/tensorflow/tools/pip_package/setup.py#L79
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postInstall = ''
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rm $out/bin/tensorboard
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'';
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setupPyGlobalFlags = [ "--project_name ${pname}" ];
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# tensorflow/tools/pip_package/setup.py
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propagatedBuildInputs = [
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absl-py
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astunparse
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dill
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flatbuffers-python
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gast
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google-pasta
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grpcio
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h5py
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keras-preprocessing
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numpy
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opt-einsum
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protobuf
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six
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tblib
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tensorflow-estimator_2
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termcolor
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typing-extensions
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wrapt
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] ++ lib.optionals withTensorboard [
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tensorflow-tensorboard_2
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];
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nativeBuildInputs = lib.optional cudaSupport addOpenGLRunpath;
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postFixup = lib.optionalString cudaSupport ''
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find $out -type f \( -name '*.so' -or -name '*.so.*' \) | while read lib; do
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addOpenGLRunpath "$lib"
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patchelf --set-rpath "${cudatoolkit}/lib:${cudatoolkit.lib}/lib:${cudnn}/lib:${nccl}/lib:$(patchelf --print-rpath "$lib")" "$lib"
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done
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'';
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# Actual tests are slow and impure.
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# TODO try to run them anyway
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# TODO better test (files in tensorflow/tools/ci_build/builds/*test)
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checkPhase = ''
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${python.interpreter} <<EOF
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# A simple "Hello world"
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import tensorflow as tf
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hello = tf.constant("Hello, world!")
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tf.print(hello)
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# Fit a simple model to random data
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import numpy as np
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np.random.seed(0)
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tf.random.set_seed(0)
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model = tf.keras.models.Sequential([
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tf.keras.layers.Dense(1, activation="linear")
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])
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model.compile(optimizer="sgd", loss="mse")
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x = np.random.uniform(size=(1,1))
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y = np.random.uniform(size=(1,))
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model.fit(x, y, epochs=1)
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EOF
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'';
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# Regression test for #77626 removed because not more `tensorflow.contrib`.
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passthru = {
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deps = bazel-build.deps;
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libtensorflow = bazel-build.out;
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};
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inherit (bazel-build) meta;
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}
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