%global _empty_manifest_terminate_build 0
Name:		python-dm-control
Version:	1.0.12
Release:	1
Summary:	Continuous control environments and MuJoCo Python bindings.
License:	Apache License 2.0
URL:		https://github.com/deepmind/dm_control
Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/6b/dd/851022971997f7d064cbd4daa8f834ec48cb5e7728021a128821321934c6/dm_control-1.0.12.tar.gz
BuildArch:	noarch

Requires:	python3-absl-py
Requires:	python3-dm-env
Requires:	python3-dm-tree
Requires:	python3-glfw
Requires:	python3-labmaze
Requires:	python3-lxml
Requires:	python3-mujoco
Requires:	python3-numpy
Requires:	python3-protobuf
Requires:	python3-pyopengl
Requires:	python3-pyparsing
Requires:	python3-requests
Requires:	python3-setuptools
Requires:	python3-scipy
Requires:	python3-tqdm
Requires:	python3-h5py

%description

# `dm_control`: DeepMind Infrastructure for Physics-Based Simulation.

DeepMind's software stack for physics-based simulation and Reinforcement
Learning environments, using MuJoCo physics.

An **introductory tutorial** for this package is available as a Colaboratory
notebook: [Open In Google Colab](https://colab.research.google.com/github/deepmind/dm_control/blob/main/tutorial.ipynb).


%package -n python3-dm-control
Summary:	Continuous control environments and MuJoCo Python bindings.
Provides:	python-dm-control
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-dm-control

# `dm_control`: DeepMind Infrastructure for Physics-Based Simulation.

DeepMind's software stack for physics-based simulation and Reinforcement
Learning environments, using MuJoCo physics.

An **introductory tutorial** for this package is available as a Colaboratory
notebook: [Open In Google Colab](https://colab.research.google.com/github/deepmind/dm_control/blob/main/tutorial.ipynb).


%package help
Summary:	Development documents and examples for dm-control
Provides:	python3-dm-control-doc
%description help

# `dm_control`: DeepMind Infrastructure for Physics-Based Simulation.

DeepMind's software stack for physics-based simulation and Reinforcement
Learning environments, using MuJoCo physics.

An **introductory tutorial** for this package is available as a Colaboratory
notebook: [Open In Google Colab](https://colab.research.google.com/github/deepmind/dm_control/blob/main/tutorial.ipynb).


%prep
%autosetup -n dm-control-1.0.12

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

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

%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.12-1
- Package Spec generated