From 61c0d3660d7b19d56130ae43771b7c0a75760f32 Mon Sep 17 00:00:00 2001 From: CoprDistGit Date: Tue, 16 Apr 2024 04:50:57 +0000 Subject: automatic import of torchrl --- torchrl.spec | 116 +++++++++++++++++++++++++++++------------------------------ 1 file changed, 58 insertions(+), 58 deletions(-) diff --git a/torchrl.spec b/torchrl.spec index db67173..cdcc713 100644 --- a/torchrl.spec +++ b/torchrl.spec @@ -1,59 +1,59 @@ -%global _empty_manifest_terminate_build 0 -Name: torchrl -Version: 0.3.1 -Release: 1 -Summary: TorchRL is a library of reusable components for deep learning with reinforcement learning -License: MIT -URL: https://torchrl.org/ -Source0: https://github.com/pytorch/rl/archive/refs/tags/v%{version}.tar.gz/rl-%{version}.tar.gz - -BuildRequires: g++ -Requires: python3-torch -Requires: python3-gym - -%description -TorchRL provides efficient, reusable components for Reinforcement Learning research with PyTorch. -Key features include: -- Data structures for storing and manipulating reinforcement learning environments -- Efficient operations on these structures (sampling, loss functions) -- A framework for policy gradient methods -- A framework for Q-learning methods. - -%package -n python3-torchrl -Summary: TorchRL is a library of reusable components for deep learning with reinforcement learning -Provides: python-torchrl - -BuildRequires: python3-devel -BuildRequires: python3-setuptools -BuildRequires: python3-setuptools_scm -BuildRequires: python3-pbr -BuildRequires: python3-pip -BuildRequires: python3-wheel - -%description -n python3-torchrl -TorchRL provides efficient, reusable components for Reinforcement Learning research with PyTorch. -Key features include: -- Data structures for storing and manipulating reinforcement learning environments -- Efficient operations on these structures (sampling, loss functions) -- A framework for policy gradient methods -- A framework for Q-learning methods. - -%prep -%autosetup -p1 -n rl-%{version} - -%build -%py3_build - -%install -%py3_install - -%files -n python3-torchrl -%doc *.md -%license LICENSE -%{_bindir}/torchrl_runner -%{_bindir}/torchrl_visualizer -%{python3_sitearch}/* - -%changelog -* Mon Apr 15 2024 weilaijishu +%global _empty_manifest_terminate_build 0 +Name: torchrl +Version: 0.3.1 +Release: 1 +Summary: TorchRL is a library of reusable components for deep learning with reinforcement learning +License: MIT +URL: https://torchrl.org/ +Source0: https://github.com/pytorch/rl/archive/refs/tags/v%{version}.tar.gz/rl-%{version}.tar.gz + +BuildRequires: g++ +Requires: python3-torch +Requires: python3-gym + +%description +TorchRL provides efficient, reusable components for Reinforcement Learning research with PyTorch. +Key features include: +- Data structures for storing and manipulating reinforcement learning environments +- Efficient operations on these structures (sampling, loss functions) +- A framework for policy gradient methods +- A framework for Q-learning methods. + +%package -n python3-torchrl +Summary: TorchRL is a library of reusable components for deep learning with reinforcement learning +Provides: python-torchrl + +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-setuptools_scm +BuildRequires: python3-pbr +BuildRequires: python3-pip +BuildRequires: python3-wheel + +%description -n python3-torchrl +TorchRL provides efficient, reusable components for Reinforcement Learning research with PyTorch. +Key features include: +- Data structures for storing and manipulating reinforcement learning environments +- Efficient operations on these structures (sampling, loss functions) +- A framework for policy gradient methods +- A framework for Q-learning methods. + +%prep +%autosetup -p1 -n rl-%{version} + +%build +%py3_build + +%install +%py3_install + +%files -n python3-torchrl +%doc *.md +%license LICENSE +%{_bindir}/torchrl_runner +%{_bindir}/torchrl_visualizer +%{python3_sitearch}/* + +%changelog +* Mon Apr 15 2024 weilaijishu - Initial package -- cgit v1.2.3