452 lines
14 KiB
Nix
452 lines
14 KiB
Nix
{ stdenv, pkgs, bazel_0_26, buildBazelPackage, lib, fetchFromGitHub, fetchpatch, symlinkJoin
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, addOpenGLRunpath
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# Python deps
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, buildPythonPackage, isPy3k, isPy27, pythonOlder, pythonAtLeast, python
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# Python libraries
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, numpy, tensorflow-tensorboard_1, backports_weakref, mock, enum34, absl-py
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, future, setuptools, wheel, keras-preprocessing, keras-applications, google-pasta
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, functools32
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, opt-einsum
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, termcolor, grpcio, six, wrapt, protobuf, tensorflow-estimator_1
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# Common deps
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, git, swig, which, binutils, glibcLocales, cython
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# Common libraries
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, jemalloc, openmpi, astor, gast, grpc, sqlite, openssl, jsoncpp, re2
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, curl, snappy, flatbuffers, icu, double-conversion, libpng, libjpeg, 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, nvidia_x11 ? null, cudatoolkit ? null, cudnn ? null, nccl ? null
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, mklSupport ? false, mkl ? null
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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 ? [ "3.5" "5.2" ]
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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 -> nvidia_x11 != null
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&& 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";
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cudatoolkit_joined = symlinkJoin {
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name = "${cudatoolkit.name}-merged";
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paths = [
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cudatoolkit.lib
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cudatoolkit.out
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# for some reason some of the required libs are in the targets/x86_64-linux
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# directory; not sure why but this works around it
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"${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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pkgs.protobuf
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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 = "1.15.4";
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variant = if cudaSupport then "-gpu" else "";
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pname = "tensorflow${variant}";
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pythonEnv = python.withPackages (_:
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[ # python deps needed during wheel build time (not runtime, see the buildPythonPackage part for that)
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numpy
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keras-preprocessing
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protobuf
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wrapt
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gast
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astor
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absl-py
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termcolor
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keras-applications
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setuptools
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wheel
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] ++ lib.optionals (!isPy3k)
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[ future
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functools32
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mock
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]);
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bazel-build = buildBazelPackage {
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name = "${pname}-${version}";
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bazel = bazel_0_26;
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src = fetchFromGitHub {
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owner = "tensorflow";
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repo = "tensorflow";
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rev = "v${version}";
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sha256 = "0lg8ahyr2k7dmp0yfypk8ivl9a0xcg3j0f0dakmn5ljk8nsji0bj";
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};
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patches = [
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# Work around https://github.com/tensorflow/tensorflow/issues/24752
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../no-saved-proto.patch
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# Fixes for NixOS jsoncpp
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../system-jsoncpp.patch
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# https://github.com/tensorflow/tensorflow/pull/29673
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(fetchpatch {
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name = "fix-compile-with-cuda-and-mpi.patch";
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url = "https://github.com/tensorflow/tensorflow/pull/29673/commits/498e35a3bfe38dd75cf1416a1a23c07c3b59e6af.patch";
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sha256 = "1m2qmwv1ysqa61z6255xggwbq6mnxbig749bdvrhnch4zydxb4di";
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})
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(fetchpatch {
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name = "backport-pr-18950.patch";
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url = "https://github.com/tensorflow/tensorflow/commit/73640aaec2ab0234d9fff138e3c9833695570c0a.patch";
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sha256 = "1n9ypbrx36fc1kc9cz5b3p9qhg15xxhq4nz6ap3hwqba535nakfz";
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})
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(fetchpatch {
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# be compatible with gast >0.2 instead of only gast 0.2.2
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name = "gast-update.patch";
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url = "https://github.com/tensorflow/tensorflow/commit/85751ad6c7f5fd12c6c79545d96896cba92fa8b4.patch";
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sha256 = "077cpj0kzyqxzdya1dwh8df17zfzhqn7c685hx6iskvw2979zg2n";
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})
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./lift-gast-restriction.patch
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(fetchpatch {
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# fix compilation with numpy >= 1.19
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name = "add-const-overload.patch";
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url = "https://github.com/tensorflow/tensorflow/commit/75ea0b31477d6ba9e990e296bbbd8ca4e7eebadf.patch";
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sha256 = "1xp1icacig0xm0nmb05sbrf4nw4xbln9fhc308birrv8286zx7wv";
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})
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# cuda 10.2 does not have "-bin2c-path" option anymore
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# https://github.com/tensorflow/tensorflow/issues/34429
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../cuda-10.2-no-bin2c-path.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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swig which pythonEnv
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] ++ lib.optional cudaSupport addOpenGLRunpath;
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buildInputs = [
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jemalloc
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openmpi
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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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openssl
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jsoncpp
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pkgs.protobuf
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curl
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snappy
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flatbuffers
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icu
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double-conversion
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libpng
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libjpeg
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giflib
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re2
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pkgs.lmdb
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] ++ lib.optionals cudaSupport [
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cudatoolkit
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cudnn
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nvidia_x11
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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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"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_google_protobuf"
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"com_googlesource_code_re2"
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"curl"
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"cython"
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"double_conversion"
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"flatbuffers"
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"gast_archive"
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"gif_archive"
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# Lots of errors, requires an older version
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# "grpc"
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"hwloc"
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"icu"
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"jpeg"
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"jsoncpp_git"
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"keras_applications_archive"
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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_archive"
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"six_archive"
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"snappy"
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"swig"
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"termcolor_archive"
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"wrapt"
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"zlib_archive"
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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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# https://github.com/tensorflow/tensorflow/issues/20919
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sed -i '/androidndk/d' tensorflow/lite/kernels/internal/BUILD
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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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substituteInPlace tensorflow/tools/pip_package/setup.py \
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--replace "numpy >= 1.16.0, < 1.19.0" "numpy >= 1.16.0"
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'';
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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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# FIXME: Tensorflow uses dlopen() for CUDA libraries.
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NIX_LDFLAGS = lib.optionalString cudaSupport "-lcudart -lcublas -lcufft -lcurand -lcusolver -lcusparse -lcudnn";
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hardeningDisable = [ "format" ];
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bazelFlags = [
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# temporary fixes to make the build work with bazel 0.27
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"--incompatible_no_support_tools_in_action_inputs=false"
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];
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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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fetchAttrs = {
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# So that checksums don't depend on these.
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TF_SYSTEM_LIBS = null;
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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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"1bi6aydidgi943hiqj0d279jbz2g173hvafdqla1ifw2qdsm73pb"
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else
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"0l5510fr8n22c4hx9llr0vqqhx9wlgkyxl55fxbixhssd0ai05r4";
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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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};
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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; linux ++ darwin;
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# The py2 build fails due to some issue importing protobuf. Possibly related to the fix in
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# https://github.com/akesandgren/easybuild-easyblocks/commit/1f2e517ddfd1b00a342c6abb55aef3fd93671a2b
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broken = !(xlaSupport -> cudaSupport) || !isPy3k;
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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 = isPy27 || (pythonAtLeast "3.8");
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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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astor
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gast
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google-pasta
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keras-applications
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keras-preprocessing
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numpy
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six
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protobuf
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tensorflow-estimator_1
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termcolor
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wrapt
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grpcio
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opt-einsum
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] ++ lib.optionals (!isPy3k) [
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mock
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future
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functools32
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] ++ lib.optionals (pythonOlder "3.4") [
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backports_weakref enum34
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] ++ lib.optionals withTensorboard [
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tensorflow-tensorboard_1
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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 "$lib"
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done
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'';
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# Actual tests are slow and impure.
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# TODO try to run them anyway
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# TODO better test (files in tensorflow/tools/ci_build/builds/*test)
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checkPhase = ''
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${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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sess = tf.Session()
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sess.run(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_random_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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# regression test for #77626
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from tensorflow.contrib import tensor_forest
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EOF
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'';
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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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meta = bazel-build.meta // {
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broken = gast.version != "0.3.2";
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};
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}
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