diff options
author | CoprDistGit <infra@openeuler.org> | 2024-04-15 17:46:43 +0000 |
---|---|---|
committer | CoprDistGit <infra@openeuler.org> | 2024-04-15 17:46:43 +0000 |
commit | b54103aede782dcbf2bf74b19bf0c53eab835a2d (patch) | |
tree | c4edb99ad77f063522f564b9c75ec9bea431247b | |
parent | 0f35927c38cefce5719925073935f98a06866800 (diff) |
automatic import of pytorch3dopeneuler23.09
-rw-r--r-- | torch3d.spec | 120 |
1 files changed, 60 insertions, 60 deletions
diff --git a/torch3d.spec b/torch3d.spec index e73bbc3..44d439c 100644 --- a/torch3d.spec +++ b/torch3d.spec @@ -1,61 +1,61 @@ -%global _empty_manifest_terminate_build 0
-Name: pytorch3d
-Version: 0.7.5
-Release: 1
-Summary: PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
-License: BSD
-URL: https://pytorch3d.org/
-Source0: https://github.com/facebookresearch/pytorch3d/archive/refs/tags/v%{version}.zip#/%{name}-%{version}.zip
-
-BuildRequires: g++
-Requires: python3-fvcore
-Requires: python3-iopath
-
-%description
-PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch.
-Key features include:
-- Data structure for storing and manipulating triangle meshes
-- Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions)
-- A differentiable mesh renderer
-- Implicitron, see its README, a framework for new-view synthesis via implicit representations.
-
-%package -n python3-pytorch3d
-Summary: PyTorch3D is FAIR's library of reusable components for deep learning with 3D data
-Provides: python-pytorch3d
-
-BuildRequires: python3-devel
-BuildRequires: python3-setuptools
-BuildRequires: python3-setuptools_scm
-BuildRequires: python3-pbr
-BuildRequires: python3-pip
-BuildRequires: python3-wheel
-BuildRequires: python3-hatchling
-BuildRequires: python3-pytorch
-
-%description -n python3-pytorch3d
-PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch.
-Key features include:
-- Data structure for storing and manipulating triangle meshes
-- Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions)
-- A differentiable mesh renderer
-- Implicitron, see its README, a framework for new-view synthesis via implicit representations.
-
-%prep
-%autosetup -p1 -n %{name}-%{version}
-
-%build
-%py3_build
-
-%install
-%py3_install
-
-%files -n python3-pytorch3d
-%doc *.md
-%license LICENSE
-%{_bindir}/pytorch3d_implicitron_runner
-%{_bindir}/pytorch3d_implicitron_visualizer
-%{python3_sitearch}/*
-
-%changelog
-* Mon Apr 15 2024 weilaijishu
+%global _empty_manifest_terminate_build 0 +Name: pytorch3d +Version: 0.7.5 +Release: 1 +Summary: PyTorch3D is FAIR's library of reusable components for deep learning with 3D data +License: BSD +URL: https://pytorch3d.org/ +Source0: https://github.com/facebookresearch/pytorch3d/archive/refs/tags/v%{version}.zip#/%{name}-%{version}.zip + +BuildRequires: g++ +Requires: python3-fvcore +Requires: python3-iopath + +%description +PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. +Key features include: +- Data structure for storing and manipulating triangle meshes +- Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions) +- A differentiable mesh renderer +- Implicitron, see its README, a framework for new-view synthesis via implicit representations. + +%package -n python3-pytorch3d +Summary: PyTorch3D is FAIR's library of reusable components for deep learning with 3D data +Provides: python-pytorch3d + +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-setuptools_scm +BuildRequires: python3-pbr +BuildRequires: python3-pip +BuildRequires: python3-wheel +BuildRequires: python3-hatchling +BuildRequires: python3-pytorch + +%description -n python3-pytorch3d +PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. +Key features include: +- Data structure for storing and manipulating triangle meshes +- Efficient operations on triangle meshes (projective transformations, graph convolution, sampling, loss functions) +- A differentiable mesh renderer +- Implicitron, see its README, a framework for new-view synthesis via implicit representations. + +%prep +%autosetup -p1 -n %{name}-%{version} + +%build +%py3_build + +%install +%py3_install + +%files -n python3-pytorch3d +%doc *.md +%license LICENSE +%{_bindir}/pytorch3d_implicitron_runner +%{_bindir}/pytorch3d_implicitron_visualizer +%{python3_sitearch}/* + +%changelog +* Mon Apr 15 2024 weilaijishu - Initial package |