summaryrefslogtreecommitdiff
diff options
context:
space:
mode:
authorCoprDistGit <infra@openeuler.org>2024-04-15 17:46:43 +0000
committerCoprDistGit <infra@openeuler.org>2024-04-15 17:46:43 +0000
commitb54103aede782dcbf2bf74b19bf0c53eab835a2d (patch)
treec4edb99ad77f063522f564b9c75ec9bea431247b
parent0f35927c38cefce5719925073935f98a06866800 (diff)
automatic import of pytorch3dopeneuler23.09
-rw-r--r--torch3d.spec120
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