62 lines
3.0 KiB
RPMSpec
62 lines
3.0 KiB
RPMSpec
%global _empty_manifest_terminate_build 0
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Name: tensorflow
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Version: 2.3.1
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Release: 1
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Summary: An Open Source Machine Learning Framework for Everyone
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License: Apache License 2.0
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URL: https://www.tensorflow.org/
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Source0: https://github.com/tensorflow/tensorflow/archive/v%{version}.tar.gz#/tensorflow-%{version}.tar.gz
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#sh -x updateSource1.sh
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Source1: external-%{_arch}.tar.bz2
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Patch0001: 0001-Add-arm-source-file-into-aws-checksums.patch
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Requires: python3-future
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Requires: python3-numpy
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%description
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TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
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TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well.
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TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages.
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%package -n python3-tensorflow
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Summary: An Open Source Machine Learning Framework for Everyone
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Provides: python-tensorflow
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#It is because external-$(arch).tar.bz2 is built on bazel 3.5.0
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BuildRequires: bazel == 3.5.0
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BuildRequires: python3-numpy python3-devel python3-Keras-Preprocessing
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BuildRequires: python3-pip python3-wheel
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%description -n python3-tensorflow
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TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.
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TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well.
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TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages.
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%prep
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%autosetup -p1
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extdir=$(bazel --output_user_root=`pwd`/../output_user_root info output_base)
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mkdir -p ${extdir}
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tar xf %{SOURCE1} -C ${extdir}
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ln -sfn $(find ${extdir}/../install -name embedded_tools) ${extdir}/external/bazel_tools
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ln -sfn $(find ${extdir}/../install -maxdepth 2 -name platforms) ${extdir}/external/platforms
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rm -rf ${extdir}/external/local_config*
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%build
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bazel --output_user_root=`pwd`/../output_user_root build //tensorflow/tools/pip_package:build_pip_package
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./bazel-bin/tensorflow/tools/pip_package/build_pip_package dist
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%install
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%py3_install_wheel *
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%files -n python3-tensorflow
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%{python3_sitearch}/*
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%{_bindir}/*
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%changelog
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* Wed Sep 30 2020 Zhipeng Xie<xiezhipeng1@huawei.com> - 2.3.1-1
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- Package init
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