%global _empty_manifest_terminate_build 0
Name:		python-bert-for-tf2
Version:	0.14.9
Release:	1
Summary:	A TensorFlow 2.0 Keras implementation of BERT.
License:	MIT
URL:		https://github.com/kpe/bert-for-tf2/
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/a5/a1/acb891630749c56901e770a34d6bac8a509a367dd74a05daf7306952e910/bert-for-tf2-0.14.9.tar.gz
BuildArch:	noarch


%description
|Build Status| |Coverage Status| |Version Status| |Python Versions| |Downloads|
This repo contains a `TensorFlow 2.0`_ `Keras`_ implementation of `google-research/bert`_
with support for loading of the original `pre-trained weights`_,
and producing activations **numerically identical** to the one calculated by the original model.
`ALBERT`_ and `adapter-BERT`_ are also supported by setting the corresponding
configuration parameters (``shared_layer=True``, ``embedding_size`` for `ALBERT`_
and ``adapter_size`` for `adapter-BERT`_). Setting both will result in an adapter-ALBERT
by sharing the BERT parameters across all layers while adapting every layer with layer specific adapter.
The implementation is build from scratch using only basic tensorflow operations,
following the code in `google-research/bert/modeling.py`_
(but skipping dead code and applying some simplifications). It also utilizes `kpe/params-flow`_ to reduce
common Keras boilerplate code (related to passing model and layer configuration arguments).
`bert-for-tf2`_ should work with both `TensorFlow 2.0`_ and `TensorFlow 1.14`_ or newer.

%package -n python3-bert-for-tf2
Summary:	A TensorFlow 2.0 Keras implementation of BERT.
Provides:	python-bert-for-tf2
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-bert-for-tf2
|Build Status| |Coverage Status| |Version Status| |Python Versions| |Downloads|
This repo contains a `TensorFlow 2.0`_ `Keras`_ implementation of `google-research/bert`_
with support for loading of the original `pre-trained weights`_,
and producing activations **numerically identical** to the one calculated by the original model.
`ALBERT`_ and `adapter-BERT`_ are also supported by setting the corresponding
configuration parameters (``shared_layer=True``, ``embedding_size`` for `ALBERT`_
and ``adapter_size`` for `adapter-BERT`_). Setting both will result in an adapter-ALBERT
by sharing the BERT parameters across all layers while adapting every layer with layer specific adapter.
The implementation is build from scratch using only basic tensorflow operations,
following the code in `google-research/bert/modeling.py`_
(but skipping dead code and applying some simplifications). It also utilizes `kpe/params-flow`_ to reduce
common Keras boilerplate code (related to passing model and layer configuration arguments).
`bert-for-tf2`_ should work with both `TensorFlow 2.0`_ and `TensorFlow 1.14`_ or newer.

%package help
Summary:	Development documents and examples for bert-for-tf2
Provides:	python3-bert-for-tf2-doc
%description help
|Build Status| |Coverage Status| |Version Status| |Python Versions| |Downloads|
This repo contains a `TensorFlow 2.0`_ `Keras`_ implementation of `google-research/bert`_
with support for loading of the original `pre-trained weights`_,
and producing activations **numerically identical** to the one calculated by the original model.
`ALBERT`_ and `adapter-BERT`_ are also supported by setting the corresponding
configuration parameters (``shared_layer=True``, ``embedding_size`` for `ALBERT`_
and ``adapter_size`` for `adapter-BERT`_). Setting both will result in an adapter-ALBERT
by sharing the BERT parameters across all layers while adapting every layer with layer specific adapter.
The implementation is build from scratch using only basic tensorflow operations,
following the code in `google-research/bert/modeling.py`_
(but skipping dead code and applying some simplifications). It also utilizes `kpe/params-flow`_ to reduce
common Keras boilerplate code (related to passing model and layer configuration arguments).
`bert-for-tf2`_ should work with both `TensorFlow 2.0`_ and `TensorFlow 1.14`_ or newer.

%prep
%autosetup -n bert-for-tf2-0.14.9

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-bert-for-tf2 -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Sun Apr 23 2023 Python_Bot <Python_Bot@openeuler.org> - 0.14.9-1
- Package Spec generated