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| author | CoprDistGit <infra@openeuler.org> | 2024-04-16 03:34:25 +0000 |
|---|---|---|
| committer | CoprDistGit <infra@openeuler.org> | 2024-04-16 03:34:25 +0000 |
| commit | 95ad6c38a6e3c03c1fac8d153ebd7306b67595b6 (patch) | |
| tree | 9b8b011ced005efa18597f042aa88ace25f80c03 | |
| parent | 1e4b44a75de868fb66d5f5afdf46b14767d98a04 (diff) | |
automatic import of torchrl
| -rw-r--r-- | .gitignore | 1 | ||||
| -rw-r--r-- | sources | 1 | ||||
| -rw-r--r-- | torchrl.spec | 59 |
3 files changed, 61 insertions, 0 deletions
@@ -0,0 +1 @@ +/rl-0.3.1.tar.gz @@ -0,0 +1 @@ +a4e642b5994701b4e00e628ad3efd6dd rl-0.3.1.tar.gz diff --git a/torchrl.spec b/torchrl.spec new file mode 100644 index 0000000..3d95e7b --- /dev/null +++ b/torchrl.spec @@ -0,0 +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 %{name}-%{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 |