%global _empty_manifest_terminate_build 0
Name:		python-mice
Version:	0.1.30
Release:	1
Summary:	Multi-iteration Stochastic Estimator
License:	GPLv3
URL:		https://bitbucket.org/agcarlon/mice
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/77/c9/8f0135b0a9d099b0c6073243274e5867b6dfa72548b871d265f987890afd/mice-0.1.30.tar.gz
BuildArch:	noarch

Requires:	python3-numpy
Requires:	python3-scipy
Requires:	python3-pandas
Requires:	python3-matplotlib

%description
The `Multi-Iteration stochastiC Estimator`_ (MICE) is an estimator of gradients to be used in stochastic optimization. It uses control variates to build a hierarchy of iterations, adaptively sampling to keep the statistical variance below tolerance in an optimal fashion, cost-wise. The tolerance on the statistical error decreases proportionally to the square of the gradient norm, thus, SGD-MICE converges linearly in strongly convex L-smooth functions.
This python implementation of MICE is able to
* estimate expectations or finite sums of gradients of functions;
* choose the optimal sample sizes in order to minimize the sampling cost;
* build a hierarchy of iterations that minimizes the total work;
* use a resampling technique to compute the gradient norm, thus enforcing stability;
* define a tolerance on the norm of the gradient estimate or a maximum number of evaluations as a stopping criterion.

%package -n python3-mice
Summary:	Multi-iteration Stochastic Estimator
Provides:	python-mice
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-mice
The `Multi-Iteration stochastiC Estimator`_ (MICE) is an estimator of gradients to be used in stochastic optimization. It uses control variates to build a hierarchy of iterations, adaptively sampling to keep the statistical variance below tolerance in an optimal fashion, cost-wise. The tolerance on the statistical error decreases proportionally to the square of the gradient norm, thus, SGD-MICE converges linearly in strongly convex L-smooth functions.
This python implementation of MICE is able to
* estimate expectations or finite sums of gradients of functions;
* choose the optimal sample sizes in order to minimize the sampling cost;
* build a hierarchy of iterations that minimizes the total work;
* use a resampling technique to compute the gradient norm, thus enforcing stability;
* define a tolerance on the norm of the gradient estimate or a maximum number of evaluations as a stopping criterion.

%package help
Summary:	Development documents and examples for mice
Provides:	python3-mice-doc
%description help
The `Multi-Iteration stochastiC Estimator`_ (MICE) is an estimator of gradients to be used in stochastic optimization. It uses control variates to build a hierarchy of iterations, adaptively sampling to keep the statistical variance below tolerance in an optimal fashion, cost-wise. The tolerance on the statistical error decreases proportionally to the square of the gradient norm, thus, SGD-MICE converges linearly in strongly convex L-smooth functions.
This python implementation of MICE is able to
* estimate expectations or finite sums of gradients of functions;
* choose the optimal sample sizes in order to minimize the sampling cost;
* build a hierarchy of iterations that minimizes the total work;
* use a resampling technique to compute the gradient norm, thus enforcing stability;
* define a tolerance on the norm of the gradient estimate or a maximum number of evaluations as a stopping criterion.

%prep
%autosetup -n mice-0.1.30

%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-mice -f filelist.lst
%dir %{python3_sitelib}/*

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

%changelog
* Mon May 15 2023 Python_Bot <Python_Bot@openeuler.org> - 0.1.30-1
- Package Spec generated