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|
%global _empty_manifest_terminate_build 0
Name: python-larq-zoo
Version: 2.3.1
Release: 1
Summary: Reference implementations of popular Binarized Neural Networks
License: Apache 2.0
URL: https://github.com/plumerai/larq-zoo
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/22/6f/be82c107662a9855a3cad052c31a5108929f4b6f466ff3df4b6821d0d671/larq-zoo-2.3.1.tar.gz
BuildArch: noarch
Requires: python3-numpy
Requires: python3-packaging
Requires: python3-larq
Requires: python3-zookeeper
Requires: python3-importlib-metadata
Requires: python3-tensorflow
Requires: python3-tensorflow-gpu
Requires: python3-black
Requires: python3-flake8
Requires: python3-isort
Requires: python3-pytype
Requires: python3-pytest
Requires: python3-pytest-cov
Requires: python3-pytest-mock
Requires: python3-pytest-xdist
Requires: python3-Pillow
Requires: python3-tensorflow-datasets
%description
# Larq Zoo
[](https://github.com/larq/zoo/actions?workflow=Unittest) [](https://codecov.io/github/larq/zoo?branch=main) [](https://pypi.org/project/larq-zoo/) [](https://pypi.org/project/larq-zoo/) [](https://github.com/plumerai/larq-zoo/blob/main/LICENSE) [](https://github.com/ambv/black)
For more information, see [larq.dev/zoo](https://docs.larq.dev/zoo/).
*Larq Zoo is part of a family of libraries for BNN development; you can also check out [Larq](https://github.com/larq/larq) for building and training BNNs and [Larq Compute Engine](https://github.com/larq/compute-engine) for deployment on mobile and edge devices.*
## Requirements
Before installing Larq Zoo, please install:
- [Python](https://python.org) version `3.6`, `3.7`, `3.8`, or `3.9`
- [Tensorflow](https://www.tensorflow.org/install) version `1.15`, `2.0`, `2.1`, `2.2`, `2.3`, `2.4`, `2.5`, `2.6`, 2.7`, or `2.8`
## Installation
You can install Larq Zoo with Python's [pip](https://pip.pypa.io/en/stable/) package manager:
```shell
pip install larq-zoo
```
## About
Larq Zoo is being developed by a team of deep learning researchers and engineers at Plumerai to help accelerate both our own research and the general adoption of Binarized Neural Networks.
%package -n python3-larq-zoo
Summary: Reference implementations of popular Binarized Neural Networks
Provides: python-larq-zoo
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-larq-zoo
# Larq Zoo
[](https://github.com/larq/zoo/actions?workflow=Unittest) [](https://codecov.io/github/larq/zoo?branch=main) [](https://pypi.org/project/larq-zoo/) [](https://pypi.org/project/larq-zoo/) [](https://github.com/plumerai/larq-zoo/blob/main/LICENSE) [](https://github.com/ambv/black)
For more information, see [larq.dev/zoo](https://docs.larq.dev/zoo/).
*Larq Zoo is part of a family of libraries for BNN development; you can also check out [Larq](https://github.com/larq/larq) for building and training BNNs and [Larq Compute Engine](https://github.com/larq/compute-engine) for deployment on mobile and edge devices.*
## Requirements
Before installing Larq Zoo, please install:
- [Python](https://python.org) version `3.6`, `3.7`, `3.8`, or `3.9`
- [Tensorflow](https://www.tensorflow.org/install) version `1.15`, `2.0`, `2.1`, `2.2`, `2.3`, `2.4`, `2.5`, `2.6`, 2.7`, or `2.8`
## Installation
You can install Larq Zoo with Python's [pip](https://pip.pypa.io/en/stable/) package manager:
```shell
pip install larq-zoo
```
## About
Larq Zoo is being developed by a team of deep learning researchers and engineers at Plumerai to help accelerate both our own research and the general adoption of Binarized Neural Networks.
%package help
Summary: Development documents and examples for larq-zoo
Provides: python3-larq-zoo-doc
%description help
# Larq Zoo
[](https://github.com/larq/zoo/actions?workflow=Unittest) [](https://codecov.io/github/larq/zoo?branch=main) [](https://pypi.org/project/larq-zoo/) [](https://pypi.org/project/larq-zoo/) [](https://github.com/plumerai/larq-zoo/blob/main/LICENSE) [](https://github.com/ambv/black)
For more information, see [larq.dev/zoo](https://docs.larq.dev/zoo/).
*Larq Zoo is part of a family of libraries for BNN development; you can also check out [Larq](https://github.com/larq/larq) for building and training BNNs and [Larq Compute Engine](https://github.com/larq/compute-engine) for deployment on mobile and edge devices.*
## Requirements
Before installing Larq Zoo, please install:
- [Python](https://python.org) version `3.6`, `3.7`, `3.8`, or `3.9`
- [Tensorflow](https://www.tensorflow.org/install) version `1.15`, `2.0`, `2.1`, `2.2`, `2.3`, `2.4`, `2.5`, `2.6`, 2.7`, or `2.8`
## Installation
You can install Larq Zoo with Python's [pip](https://pip.pypa.io/en/stable/) package manager:
```shell
pip install larq-zoo
```
## About
Larq Zoo is being developed by a team of deep learning researchers and engineers at Plumerai to help accelerate both our own research and the general adoption of Binarized Neural Networks.
%prep
%autosetup -n larq-zoo-2.3.1
%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-larq-zoo -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 2.3.1-1
- Package Spec generated
|
