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%global _empty_manifest_terminate_build 0
Name: python-Dandelion
Version: 0.17.26
Release: 1
Summary: A light weight deep learning framework
License: Mozilla Public License v2.0
URL: https://github.com/david-leon/Dandelion
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/c5/95/ffc8f66952f46c0d05228ccd233f6c319d596382879cd8ccfe33ec67bc6e/Dandelion-0.17.26.tar.gz
BuildArch: noarch
%description
module | all neual network module definitions
functional | operations on tensor with no parameter to be learned
initialization | initialization methods for neural network modules
activation | definition of all activation functions
objective | definition of all loss objectives
update | definition of all optimizers
util | utility functions
model | model implementations out-of-the-box
ext | extensions
## Credits
The design of Dandelion heavily draws on [Lasagne](https://github.com/Lasagne/Lasagne) and [Pytorch](http://pytorch.org/), both my favorate DL libraries.
Special thanks to **Radomir Dopieralski**, who transferred the `dandelion` project name on pypi to us. Now you can install the package by simply `pip install dandelion`.
%package -n python3-Dandelion
Summary: A light weight deep learning framework
Provides: python-Dandelion
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-Dandelion
module | all neual network module definitions
functional | operations on tensor with no parameter to be learned
initialization | initialization methods for neural network modules
activation | definition of all activation functions
objective | definition of all loss objectives
update | definition of all optimizers
util | utility functions
model | model implementations out-of-the-box
ext | extensions
## Credits
The design of Dandelion heavily draws on [Lasagne](https://github.com/Lasagne/Lasagne) and [Pytorch](http://pytorch.org/), both my favorate DL libraries.
Special thanks to **Radomir Dopieralski**, who transferred the `dandelion` project name on pypi to us. Now you can install the package by simply `pip install dandelion`.
%package help
Summary: Development documents and examples for Dandelion
Provides: python3-Dandelion-doc
%description help
module | all neual network module definitions
functional | operations on tensor with no parameter to be learned
initialization | initialization methods for neural network modules
activation | definition of all activation functions
objective | definition of all loss objectives
update | definition of all optimizers
util | utility functions
model | model implementations out-of-the-box
ext | extensions
## Credits
The design of Dandelion heavily draws on [Lasagne](https://github.com/Lasagne/Lasagne) and [Pytorch](http://pytorch.org/), both my favorate DL libraries.
Special thanks to **Radomir Dopieralski**, who transferred the `dandelion` project name on pypi to us. Now you can install the package by simply `pip install dandelion`.
%prep
%autosetup -n Dandelion-0.17.26
%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-Dandelion -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.17.26-1
- Package Spec generated
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