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File tensorflow2.spec of Package tensorflow2
# # spec file for package tensorflow2 # # Copyright (c) 2020 SUSE LLC # # All modifications and additions to the file contributed by third parties # remain the property of their copyright owners, unless otherwise agreed # upon. The license for this file, and modifications and additions to the # file, is the same license as for the pristine package itself (unless the # license for the pristine package is not an Open Source License, in which # case the license is the MIT License). An "Open Source License" is a # license that conforms to the Open Source Definition (Version 1.9) # published by the Open Source Initiative. # Please submit bugfixes or comments via https://bugs.opensuse.org/ # # %define pname tensorflow2 %define vers 2.1.0 %define _vers 2_1_0 %define libmaj 2 %define libmin 1 %define libref 0 %define python_ver_hack python3.[0-9] %global flavor @BUILD_FLAVOR@%{nil} # Build tensorflow, not Tensorflow-lite %define is_lite 0 %if "%{flavor}" == "standard" %bcond_with cuda %bcond_with mpi %bcond_with opencl %endif %if "%{flavor}" == "lite" %define is_lite 1 %bcond_with cuda %bcond_with mpi %bcond_with opencl %define package_suffix -lite %endif %if "%{flavor}" == "hpc" %bcond_with cuda %bcond_with mpi %bcond_with opencl %bcond_without hpc %define compiler_family gnu %endif %if "%{flavor}" == "hpc-openmpi2" %define mpi_flavor openmpi %define mpi_vers 2 %bcond_with cuda %bcond_without mpi %bcond_with opencl %bcond_without hpc %define compiler_family gnu %endif %if "%{flavor}" == "hpc-mvapich2" %define mpi_flavor mvapich2 %bcond_with cuda %bcond_without mpi %bcond_with opencl %bcond_without hpc %define compiler_family gnu %endif %if "%{flavor}" == "cuda-10-1" %bcond_without cuda %bcond_with mpi %bcond_with opencl %endif %if "%{flavor}" == "opencl" %bcond_without opencl %bcond_with cuda %bcond_with mpi %endif %if %{with hpc} %{!?compiler_family:%global compiler_family gnu} %{hpc_init -c %compiler_family %{?with_mpi:-m %mpi_flavor} %{?c_f_ver:-v %{c_f_ver}} %{?mpi_ver:-V %{mpi_ver}} %{?ext:-e %{ext}}} %{?with_mpi:%global hpc_module_pname p%{pname}} %define python_flavor python3 %define package_name %{hpc_package_name %_vers} %define package_name_provide tensorflow2%{hpc_package_name_tail} %define package_name_conflict tensorflow%{hpc_package_name_tail} %define libname(l:s:) lib%{pname}%{-l*}%{hpc_package_name_tail %{?_vers}} %define package_python_sitearch %hpc_python_sitearch %define package_python_sitelib %{hpc_prefix}/lib64/%{python_ver_hack}/site-packages/ %define package_prefix %hpc_prefix %define package_bindir %hpc_bindir %define package_libdir %hpc_libdir %else %define package_name %pname%{?package_suffix} %define package_name_conflict tensorflow%{?package_suffix} %define package_python_sitearch %{python3_sitearch} %define package_python_sitelib %{python3_sitelib} %define package_prefix %_prefix %define package_bindir %_bindir %define package_libdir %_libdir %define libname(l:s:) lib%{pname}%{!-l:%{-s:-}}%{-l*}%{-s*}%{?package_suffix} %endif Name: %{package_name} Version: %vers Release: 0 Summary: A framework used for deep learning License: Apache-2.0 AND BSD-2-Clause AND BSD-3-Clause AND FSFUL AND MIT AND MPL-2.0 AND OpenSSL AND Python-2.0 Group: Development/Languages/Python URL: https://www.tensorflow.org/ Source0: https://github.com/tensorflow/tensorflow/archive/v%{version}.tar.gz#/tensorflow-v%{version}.tar.gz Source1: tensorflow2-rpmlintrc # IMPORTANT # although some of the following libraries are available in factory they could # not be used as # * explicit versions are needed which differ from the factory ones # * bazel and the obs version have different symbols due to hidden compiler flags # License10: Apache-2.0 Source10: https://github.com/bazelbuild/rules_closure/archive/308b05b2419edb5c8ee0471b67a40403df940149.tar.gz#/rules_closure.tar.gz # License15: MIT Source15: https://github.com/google/farmhash/archive/816a4ae622e964763ca0862d9dbd19324a1eaf45.tar.gz#/farmhash.tar.gz # License17: Apache-2.0 Source17: https://github.com/google/gemmlowp/archive/12fed0cd7cfcd9e169bf1925bc3a7a58725fdcc3.zip#/gemmlowp.zip # License18: BSD-3-Clause Source18: https://github.com/hfp/libxsmm/archive/1.9.tar.gz#/libxsmm_1.9.tar.gz # License19: Apache-2.0 Source19: https://github.com/abseil/abseil-cpp/archive/43ef2148c0936ebf7cb4be6b19927a9d9d145b8f.tar.gz#/abseil-cpp.tar.gz # License20: OpenSSL and ISC and Intel Source20: https://github.com/google/boringssl/archive/7f634429a04abc48e2eb041c81c5235816c96514.tar.gz#/boring_ssl.tar.gz # License21: Apache-2.0 Source21: https://github.com/googleapis/googleapis/archive/f81082ea1e2f85c43649bee26e0d9871d4b41cdb.zip#/googleapis.zip # License23: BSD-3-Clause Source23: https://github.com/NVlabs/cub/archive/1.8.0.zip#/cub_1.8.0.zip # License24: Apache-2.0 Source24: https://github.com/google/highwayhash/archive/fd3d9af80465e4383162e4a7c5e2f406e82dd968.tar.gz#/highwayhash.tar.gz # License26: MPL-2.0 # NOTE: tensorflow only uses MPL-2.0 part of eigen Source26: https://gitlab.com/libeigen/eigen/-/archive/4e696901f873a2347f76d931cf2f701e31e15d05/eigen-4e696901f873a2347f76d931cf2f701e31e15d05.tar.gz#/eigen.tar.gz # License27: BSD-2-Clause Source27: https://github.com/intel/ARM_NEON_2_x86_SSE/archive/1200fe90bb174a6224a525ee60148671a786a71f.tar.gz#/arm_neon_2_x86_sse.tar.gz Source28: https://docs.python.org/2.7/_sources/license.rst.txt#/license.rst.txt # License30: FSFUL Source30: http://www.kurims.kyoto-u.ac.jp/~ooura/fft.tgz#/fft.tar.gz # License34: BSD-3-Clause and Intel Source34: https://github.com/edenhill/librdkafka/archive/v0.11.5.tar.gz#/kafka-v0.11.5.tar.gz # License35: Apache-2.0 Source35: https://github.com/GoogleCloudPlatform/google-cloud-cpp/archive/v0.4.0.tar.gz#/google-cloud-cpp.tar.gz # License37: Apache-2.0 Source37: https://github.com/bazelbuild/rules_docker/archive/a9bb1dab84cdf46e34d1b34b53a17bda129b5eba.tar.gz#/rules_docker.tar.gz # License44: BSD like Source44: https://github.com/nanopb/nanopb/archive/f8ac463766281625ad710900479130c7fcb4d63b.tar.gz#/nanopb.tar.gz # License45: Python license itself, do need as sha256b have to match so could not use system one Source45: https://storage.googleapis.com/mirror.tensorflow.org/docs.python.org/2.7/_sources/license.rst.txt#/python-license.txt # License52: Source52: https://github.com/pybind/pybind11/archive/v2.3.0.tar.gz#/pybind11-v2.3.0.tar.gz # Deps sources for Tensorflow-Lite (use same eigen, gemmlowp and abseil_cpp packages as non lite version) # License53: Source53: https://storage.googleapis.com/mirror.tensorflow.org/www.kurims.kyoto-u.ac.jp/~ooura/fft2d.tgz # License54: Source54: https://github.com/llvm/llvm-project/archive/ecc999101aadc8dc7d4af9fd88be10fe42674aa0.tar.gz#/llvm.tar.gz # License56: Source56: https://github.com/mborgerding/kissfft/archive/36dbc057604f00aacfc0288ddad57e3b21cfc1b8.tar.gz#/kissfft.tar.gz # stable mkl version (bsc#1168839) # https://github.com/tensorflow/tensorflow/pull/36487 # https://github.com/tensorflow/tensorflow/pull/36488 Source57: https://storage.googleapis.com/mirror.tensorflow.org/github.com/intel/mkl-dnn/archive/v0.21.2.tar.gz#/mkl-v0.21.2.tar.gz Source100: https://github.com/google/googletest/archive/release-1.8.0.tar.gz Patch10: removed-docker-tools.patch # see https://github.com/tensorflow/tensorflow/pull/35943 Patch11: libjpeg_turbo-name.patch Patch12: right-json-location.patch Patch13: remove-weakref.patch Patch14: fix-lite.patch Patch17: json-feature-name.patch Patch18: fix-google-absl-memory.patch Requires: python3 Requires: python3-Keras-Applications Requires: python3-Keras-Preprocessing Requires: python3-abseil Requires: python3-astor Requires: python3-gast Requires: python3-opt-einsum Requires: python3-protobuf Requires: python3-termcolor Requires: python3-wrapt %if %{with hpc} Requires: python3-numpy-%{compiler_family}%{?c_f_ver}-hpc %else Requires: python3-numpy %endif Requires: python3-pip %if !%{is_lite} %if %{with hpc} Provides: python3-tensorflow-%{compiler_family}%{?c_f_ver}-hpc %else Provides: python3-tensorflow %endif Provides: tensorflow %endif BuildRequires: bazel = 0.29.1 BuildRequires: bazel-rules-cc-source BuildRequires: bazel-skylib-source BuildRequires: bazel-toolchains-source BuildRequires: curl %if %{with cuda} BuildRequires: cuda-compiler-10-1 BuildRequires: cuda-cufft-dev-10-1 BuildRequires: cuda-cupti-10-1 BuildRequires: cuda-curand-dev-10-1 BuildRequires: cuda-cusolver-dev-10-1 BuildRequires: cuda-cusparse-dev-10-1 BuildRequires: cuda-libraries-10-1 BuildRequires: libcublas-devel BuildRequires: libcudnn7-devel BuildRequires: libnccl2-devel %endif %if %{with opencl} Requires: Mesa-libOpenCL BuildRequires: opencl-cpp-headers BuildRequires: opencl-headers %endif BuildRequires: boringssl-devel BuildRequires: curl-devel BuildRequires: double-conversion-devel >= 3.1.5 BuildRequires: fdupes BuildRequires: fftw3-devel BuildRequires: flatbuffers-devel BuildRequires: giflib-devel BuildRequires: grpc-devel >= 1.25.0 %if 0%{?suse_version} > 1500 %if %{with cuda} # use gcc-7 for build with cuda, as nvcc can not handle # gcc9 BuildRequires: gcc7 BuildRequires: gcc7-c++ %endif %endif BuildRequires: jemalloc-devel BuildRequires: jsoncpp-devel BuildRequires: libicu-devel BuildRequires: libjpeg-turbo BuildRequires: libnsync-devel %if 0%{?suse_version} < 1550 BuildRequires: libjpeg62-turbo %endif BuildRequires: libjpeg-devel BuildRequires: libjpeg62-devel BuildRequires: libpng16-compat-devel BuildRequires: libpng16-devel BuildRequires: lmdb-devel BuildRequires: memory-constraints BuildRequires: nasm BuildRequires: pcre-devel # Requiring 3.9.1 which is the actual one in Leap 15.2 BuildRequires: protobuf-devel >= 3.9.1 BuildRequires: protobuf-java BuildRequires: python3 BuildRequires: python3-Cython BuildRequires: python3-Keras-Applications = 1.0.8 BuildRequires: python3-Keras-Preprocessing BuildRequires: python3-abseil BuildRequires: python3-astor BuildRequires: python3-base BuildRequires: python3-devel BuildRequires: python3-gast BuildRequires: python3-mock BuildRequires: python3-numpy-devel BuildRequires: python3-opt-einsum BuildRequires: python3-pip BuildRequires: python3-protobuf BuildRequires: python3-setuptools BuildRequires: python3-six BuildRequires: python3-termcolor BuildRequires: python3-wheel BuildRequires: python3-wrapt BuildRequires: re2-devel BuildRequires: snappy-devel BuildRequires: sqlite3-devel BuildRequires: swig BuildRequires: unzip BuildRequires: zlib-devel %if %{with hpc} %hpc_requires BuildRequires: %{compiler_family}%{?c_f_ver}-compilers-hpc-macros-devel BuildRequires: lua-lmod BuildRequires: suse-hpc %if %{with mpi} BuildRequires: %{mpi_flavor}%{?mpi_vers}-%{compiler_family}%{?c_f_ver}-hpc-macros-devel %endif %endif %if %{with hpc} Provides: %{package_name_provide} %endif Conflicts: %{package_name_conflict} # just use rpmlint # there are some serious compiler warnings, regarding no-return-in-nonvoid-function #!BuildRequires: -post-build-checks %if "%flavor" == "" ExclusiveArch: do_not_build %endif %if 0%{is_opensuse} %if "%{flavor}" == "cuda-10-1" # openSUSE has no CUDA package ExclusiveArch: do_not_build %endif %endif %if %{is_lite} ExcludeArch: %ix86 %else ExcludeArch: %ix86 %arm %endif %description This open source software library for numerical computation is used for data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs in a desktop, server, or mobile device without rewriting code. %{?with_hpc:%{hpc_master_package -a -L}} %package -n %{package_name}-devel Summary: Header files of tensorflow Group: Development/Languages/Python Requires: %{package_name} = %{version} %if %{with hpc} Provides: %{package_name_provide}-devel %endif Conflicts: %{package_name_conflict}-devel %if !%{is_lite} Requires: libtensorflow%{libmaj}%{?hpc_package_name_tail} = %{version} Requires: libtensorflow_cc%{libmaj}%{?hpc_package_name_tail} = %{version} Requires: libtensorflow_framework%{libmaj}%{?hpc_package_name_tail} = %{version} %endif %description -n %{package_name}-devel This open source software library for numerical computation is used for data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs in a desktop, server, or mobile device without rewriting code. This package provides necessary headers for the C/C++ Api %package -n %{package_name}-doc Summary: Examples from the tensorflow website Group: Documentation/Other Requires: %{package_name} = %{version} %description -n %{package_name}-doc This open source software library for numerical computation is used for data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs in a desktop, server, or mobile device without rewriting code. This package provides examples from the website. %package -n libtensorflow%{libmaj}%{?hpc_package_name_tail} Summary: Shared library for tensorflow Group: Libraries %description -n libtensorflow%{libmaj}%{?hpc_package_name_tail} This open source software library for numerical computation is used for data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs in a desktop, server, or mobile device without rewriting code. %package -n libtensorflow_cc%{libmaj}%{?hpc_package_name_tail} Summary: Shared library for tensorflow Group: Libraries %description -n libtensorflow_cc%{libmaj}%{?hpc_package_name_tail} This open source software library for numerical computation is used for data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs in a desktop, server, or mobile device without rewriting code. %package -n libtensorflow_framework%{libmaj}%{?hpc_package_name_tail} Summary: Shared library for tensorflow Group: Libraries %description -n libtensorflow_framework%{libmaj}%{?hpc_package_name_tail} This open source software library for numerical computation is used for data flow graphs. The graph nodes represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) that flow between them. This flexible architecture enables you to deploy computation to one or more CPUs in a desktop, server, or mobile device without rewriting code. %prep %{?!python_module:%define python_module() python-%{**} python3-%{**}} # fighting bazel %define bazeldir %{_sourcedir}/BAZEL %define bz_cachdir %{_sourcedir}/BAZEL_CACHE # macro for removing nested directories %define sanitize_dir() _uglydir=$(ls -d *); shopt -s dotglob;mv $_uglydir/* .; rmdir $_uglydir # macro for copying the files to the bazel cache dir %define makebazelcache() mkdir -p %{bz_cachdir}/content_addressable/sha256/%{?2:%2}%{?!2:$(sha256sum %1 | cut -f 1 -d ' ')}/; cp %1 %{bz_cachdir}/content_addressable/sha256/%{?2:%2}%{?!2:$(sha256sum %1 | cut -f 1 -d ' ')}/file ; # make clean for rebuild mkdir -p %{bazeldir} #create right direcory for bazel cache which depends on the actual source file %makebazelcache %{SOURCE10} %makebazelcache %{SOURCE15} %makebazelcache %{SOURCE17} %makebazelcache %{SOURCE18} %makebazelcache %{SOURCE19} %makebazelcache %{SOURCE20} %makebazelcache %{SOURCE21} %makebazelcache %{SOURCE23} %makebazelcache %{SOURCE24} %makebazelcache %{SOURCE26} %makebazelcache %{SOURCE27} %makebazelcache %{SOURCE28} %makebazelcache %{SOURCE30} %makebazelcache %{SOURCE34} %makebazelcache %{SOURCE35} %makebazelcache %{SOURCE37} %makebazelcache %{SOURCE44} %makebazelcache %{SOURCE45} %makebazelcache %{SOURCE52} %makebazelcache %{SOURCE53} %makebazelcache %{SOURCE54} %makebazelcache %{SOURCE56} %makebazelcache %{SOURCE57} # unpack tensorflow %setup -q -c -n %{pname}-%{version} %sanitize_dir %patch10 -p 1 %patch11 -p 1 %patch12 -p 1 %patch13 -p 1 %patch14 -p 1 %if 0%{?suse_version} > 1500 %patch17 -p 1 %endif %patch18 -p 1 %if %{is_lite} mkdir tensorflow/lite/tools/make/downloads/ pushd tensorflow/lite/tools/make/downloads/ # eigen, gemmlowp and abseil_cpp cp %{SOURCE26} %{SOURCE17} %{SOURCE19} . mkdir tmp tar xzf eigen.tar.gz -C tmp && mv tmp/* eigen unzip gemmlowp.zip -d tmp && mv tmp/* gemmlowp tar xzf %{SOURCE100} -C tmp && mv tmp/* fgoogletest tar xzf abseil-cpp.tar.gz -C tmp && mv tmp/* absl tar xzf %{SOURCE27} mv ARM_NEON_2_x86_SSE* neon_2_sse tar xzf %{SOURCE15} -C tmp && mv tmp/* farmhash # We use installed flatbuffers tar xzf %{SOURCE30} -C tmp && mv tmp/* fft2d # sed fixes from tensorflow/lite/tools/make/download_dependencies.sh sed -i -e 's#static uint32x4_t p4ui_CONJ_XOR = vld1q_u32( conj_XOR_DATA );#static uint32x4_t p4ui_CONJ_XOR; // = vld1q_u32( conj_XOR_DATA ); - Removed by script#' \ "./eigen/Eigen/src/Core/arch/NEON/Complex.h" sed -i -e 's#static uint32x2_t p2ui_CONJ_XOR = vld1_u32( conj_XOR_DATA );#static uint32x2_t p2ui_CONJ_XOR;// = vld1_u32( conj_XOR_DATA ); - Removed by scripts#' \ "./eigen/Eigen/src/Core/arch/NEON/Complex.h" sed -i -e 's#static uint64x2_t p2ul_CONJ_XOR = vld1q_u64( p2ul_conj_XOR_DATA );#static uint64x2_t p2ul_CONJ_XOR;// = vld1q_u64( p2ul_conj_XOR_DATA ); - Removed by script#' \ "./eigen/Eigen/src/Core/arch/NEON/Complex.h" find -name fixedpoint.h popd %endif %build %if !%{is_lite} %limit_build -m 6000 %endif %if %{is_lite} make %{?_smp_mflags} -f tensorflow/lite/tools/make/Makefile \ $(pwd)/tensorflow/lite/tools/make/gen/linux_$(uname -m)/lib/libtensorflow-lite.a \ $(pwd)/tensorflow/lite/tools/make/gen/linux_$(uname -m)/bin/minimal # Build of benchmark-lib.a is broken %else %if %{with hpc} %hpc_setup module load gnu %if %{with mpi} module load %mpi_flavor export MPI_HOME=${MPI_HOME:-$MPI_DIR} %endif %endif #rm /home/abuild/rpmbuild/SOURCES/BAZEL/_bazel_abuild/bffdb097c5cf04768665f957f68c33f9/external/bazel_toolchains/repositories/repositories.bzl export TEST_TMPDIR=%{bazeldir} export PYTHON_LIB_PATH=%{python3_sitearch} export PYTHON_BIN_PATH=/usr/bin/python3 export CC_OPT_FLAGS=-O2 export TF_NEED_JEMALLOC=0 export TF_NEED_GCP=0 export TF_NEED_HDFS=1 export TF_NEED_S3=1 export TF_ENABLE_XLA=0 export TF_NEED_VERBS=0 export TF_NEED_OPENCL=0 export TF_NEED_ROCM=0 export TF_SYSTEM_LIBS="\ absl_py,\ astor_archive,\ boringssl,\ com_github_googleapis_googleapis,\ com_github_googlecloudplatform_google_cloud_cpp,\ com_google_protobuf,\ com_googlesource_code_re2,\ curl,\ cython,\ double_conversion,\ enum34_archive,\ flatbuffers,\ functools32_archive,\ gast_archive,\ gif,\ grpc,\ hwloc,\ icu,\ libjpeg_turbo,\ jsoncpp_git,\ keras_applications_archive,\ lmdb,\ nasm,\ nsync,\ opt_einsum_archive,\ org_sqlite,\ pasta,\ pcre,\ png,\ six_archive,\ snappy,\ swig,\ termcolor_archive,\ wrapt,\ zlib_archive" %if %{with cuda} export PATH=PATH=/usr/lib/cuda-10.1/bin/:${PATH} export CUDA_HOME="/usr/lib/cuda-10.1,/usr" export CUDA_TOOLKIT_PATH=/"usr/lib/cuda-10.1,/usr" export TF_CUDA_PATHS="/usr/lib/cuda-10.1,/usr" export TF_NEED_CUDA=1 export TF_NCCL_VERSION=2.5.7 %else export TF_NEED_CUDA=0 %endif %if %{with mpi} export TF_NEED_MPI=1 %else export TF_NEED_MPI=0 %endif export TF_NEED_KAFKA=1 export TF_NEED_GDR=0 %if %{with opencl} export TF_NEED_OPENCL_SYCL=1 %else export TF_NEED_OPENCL_SYCL=0 %endif export TF_DOWNLOAD_CLANG=0 export ANDROID_NDK_HOME=0 # force the use python3 mkdir %{_topdir}/bin cd %{_topdir}/bin ln -s $(which python3) python %if 0%{?suse_version} < 1500 %if %{with cuda} ln -s $(which gcc-7) gcc ln -s $(which g++-7) g++ %endif %endif export PATH=%{_topdir}/bin/:${PATH} cd - ./configure %define bazelopts \\\ -c opt \\\ --repository_cache=%{bz_cachdir} \\\ --ignore_unsupported_sandboxing \\\ --verbose_failures \\\ --cxxopt="-D_GLIBCXX_USE_CXX11_ABI=1" \\\ --define=build_with_mkl_dnn_only=true \\\ --define=tensorflow_mkldnn_contraction_kernel=0 \\\ --config=v2 \\\ --config=noaws \\\ --incompatible_no_support_tools_in_action_inputs=false \\\ --override_repository="rules_cc=/usr/src/bazel-rules-cc" \\\ --override_repository="bazel_skylib=/usr/src/bazel-skylib"\\\ --override_repository="rules_toolchains=/usr/src/bazel-rules-toolchains" \\\ %{?copts} \\\ --jobs %{?jobs} \\\ %{nil} bazel build %{bazelopts} tensorflow/tools/pip_package:build_pip_package bazel-bin/tensorflow/tools/pip_package/build_pip_package %{_topdir}/%{name}-%{version} # Generate protobuf (for armNN) - https://github.com/ARM-software/armnn/blob/branches/armnn_19_08/scripts/generate_tensorflow_protobuf.sh export OUTPUT_DIR=./pb/ mkdir -p $OUTPUT_DIR for i in `find -name *.proto`; do protoc $i \ --proto_path=. \ --proto_path=%{_includedir} \ --cpp_out=$OUTPUT_DIR done bazel build \ %bazelopts \ //tensorflow:libtensorflow.so bazel build \ %bazelopts \ //tensorflow:libtensorflow_cc.so bazel build \ %bazelopts \ //tensorflow:libtensorflow_framework.so %endif # it_lite %install %if %{is_lite} pushd tensorflow/lite/tools/make/gen/linux_*/ install -D bin/minimal %{buildroot}%{_bindir}/tflite_minimal install -D lib/libtensorflow-lite.a %{buildroot}%{_libdir}/libtensorflow-lite.a popd install -D tensorflow/lite/schema/schema_generated.h %{buildroot}%{_includedir}/tensorflow/lite/schema/schema_generated.h install -D tensorflow/lite/schema/schema.fbs %{buildroot}%{_includedir}/tensorflow/lite/schema/schema.fbs %else pip install %{_topdir}/%{name}-%{version}/*whl --root=%{buildroot}%{?hpc_prefix} \ --no-warn-script-location --no-index --no-deps --no-compile # remove spurious executeable bits # for hpc build remove usr prefix dir %if %{with hpc} cd %{buildroot}%{?hpc_prefix} mv usr/* . rmdir usr mv lib/%{python_ver_hack}/site-packages/tensorflow_core/include/* lib64/%{python_ver_hack}/site-packages/tensorflow_core/include/ rm -r lib cd - %endif # install libtensorflow*.so #install -D bazel-bin/tensorflow/libtensorflow.so %{buildroot}%{package_libdir}/libtensorflow.so %fdupes -s %{buildroot}%{?hpc_prefix} # install after fdupes cp -vd \ bazel-bin/tensorflow/libtensorflow.so \ bazel-bin/tensorflow/libtensorflow.so.%{libmaj} \ bazel-bin/tensorflow/libtensorflow.so.%{libmaj}.%{libmin}.%{libref} \ bazel-bin/tensorflow/libtensorflow_cc.so \ bazel-bin/tensorflow/libtensorflow_cc.so.%{libmaj} \ bazel-bin/tensorflow/libtensorflow_cc.so.%{libmaj}.%{libmin}.%{libref} \ bazel-bin/tensorflow/libtensorflow_framework.so \ bazel-bin/tensorflow/libtensorflow_framework.so.%{libmaj} \ bazel-bin/tensorflow/libtensorflow_framework.so.%{libmaj}.%{libmin}.%{libref} \ %{buildroot}%{package_libdir}/ find %{buildroot} -name \*.h -type f -exec chmod 644 {} + find %{buildroot} -name LICENSE\* -type f -exec chmod 644 {} + %if %{with hpc} sitesearch_path=`python3 -c "import sysconfig as s; print(s.get_paths(vars={'platbase':'%{hpc_prefix}','base':'%{hpc_prefix}'}).get('platlib'))"` %hpc_write_modules_files #%%Module1.0##################################################################### proc ModulesHelp { } { puts stderr " " puts stderr "This module loads the %{pname} built with the %{compiler_family} toolchain." puts stderr "\nVersion %{version}\n" } module-whatis "Name: %{pname} built with %{compiler_family} toolchain" module-whatis "Version: %{version}" module-whatis "Category: runtime library" module-whatis "Description: %{SUMMARY:0}" module-whatis "URL: %{url}" set version %{version} prepend-path PATH %{hpc_prefix}/bin prepend-path LD_LIBRARY_PATH %{hpc_prefix}/%_lib prepend-path TENSORFLOWDIR %{hpc_prefix} prepend-path PYTHONPATH ${sitesearch_path} if [ expr [ module-info mode load ] || [module-info mode display ] ] { if { ![is-loaded python3-numpy] } { module load python3-numpy } } %if %{with mpi} if [ expr [ module-info mode load ] || [module-info mode display ] ] { if { ![is-loaded %mpi_flavor] } { module load %mpi_flavor } } %endif %{hpc_modulefile_add_pkgconfig_path} EOF %endif # Install generated protobuf export OUTPUT_DIR=./pb/ find -name *.pb.* cp -r $OUTPUT_DIR/tensorflow/* %{buildroot}/%{package_python_sitelib}/tensorflow_core/include/tensorflow/ # %%{is_lite} %endif %post -n libtensorflow%{libmaj}%{?hpc_package_name_tail} -p /sbin/ldconfig %postun -n libtensorflow%{libmaj}%{?hpc_package_name_tail} -p /sbin/ldconfig %post -n libtensorflow_cc%{libmaj}%{?hpc_package_name_tail} -p /sbin/ldconfig %postun -n libtensorflow_cc%{libmaj}%{?hpc_package_name_tail} -p /sbin/ldconfig %post -n libtensorflow_framework%{libmaj}%{?hpc_package_name_tail} -p /sbin/ldconfig %postun -n libtensorflow_framework%{libmaj}%{?hpc_package_name_tail} -p /sbin/ldconfig # Lite version is very different so package it separetly %if %{is_lite} %files %{package_bindir}/* %files -n %{package_name}-devel %{package_libdir}/libtensorflow-lite.a %dir %{_includedir}/tensorflow/lite/schema/ %{_includedir}/tensorflow/lite/schema/* %else # not lite build %files %defattr(-,root,root,-) %{package_bindir}/estimator_ckpt_converter %{package_bindir}/saved_model_cli %{package_bindir}/tensorboard %{package_bindir}/tf_upgrade_v2 %{package_bindir}/tflite_convert %{package_bindir}/toco* %{package_python_sitearch}/tensorflow_core/* %{package_python_sitearch}/tensorflow-%{version}* %{package_python_sitearch}/tensorflow #%%{package_python_sitelib}/tensorflow/ %exclude %{package_python_sitearch}/tensorflow_core/include %if %{with hpc} %hpc_modules_files %endif %files -n %{package_name}-devel %{package_python_sitelib}/tensorflow_core/include %{package_python_sitearch}/tensorflow_core/include %{package_libdir}/libtensorflow.so %{package_libdir}/libtensorflow_cc.so %{package_libdir}/libtensorflow_framework.so %files -n libtensorflow_framework%{libmaj}%{?hpc_package_name_tail} %{package_libdir}/libtensorflow_framework.so.%{libmaj}* %files -n libtensorflow_cc%{libmaj}%{?hpc_package_name_tail} %{package_libdir}/libtensorflow_cc.so.%{libmaj}* %files -n libtensorflow%{libmaj}%{?hpc_package_name_tail} %{package_libdir}/libtensorflow.so.%{libmaj}* %files -n %{package_name}-doc #%%{package_python_sitelib}/tensorflow/examples %endif %changelog
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