%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 - 0.17.26-1 - Package Spec generated