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+%global _empty_manifest_terminate_build 0
+%global pypi_name pytorch
+%global source_name pytorch
+
+Name: python-%{pypi_name}
+Version: 2.1.2
+Release: 1%{?dist}
+Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
+License: BSD-3-Clause
+URL: https://pytorch.org/
+Source0: https://github.com/pytorch/pytorch/archive/refs/tags/v%{version}.tar.gz#/%{name}-%{version}.tar.gz
+
+BuildRequires: g++
+Requires: python3-future
+Requires: python3-filelock
+Requires: python3-sympy
+Requires: python3-networkx
+Requires: python3-fsspec
+
+%description
+PyTorch is a Python package that provides two high-level features:
+- Tensor computation (like NumPy) with strong GPU acceleration
+- Deep neural networks built on a tape-based autograd system
+You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed.
+
+%package -n python3-%{pypi_name}
+Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
+Provides: python-torch
+BuildRequires: python3-devel
+BuildRequires: python3-setuptools
+BuildRequires: python3-setuptools_scm
+BuildRequires: python3-pbr
+BuildRequires: python3-pip
+BuildRequires: python3-wheel
+BuildRequires: python3-hatchling
+
+BuildRequires: python3-astunparse
+BuildRequires: python3-numpy
+BuildRequires: python3-pyyaml
+BuildRequires: cmake
+BuildRequires: python3-typing-extensions
+BuildRequires: python3-requests
+
+%description -n python3-%{pypi_name}
+PyTorch is a Python package that provides two high-level features:
+- Tensor computation (like NumPy) with strong GPU acceleration
+- Deep neural networks built on a tape-based autograd system
+You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed.
+
+%package help
+Summary: Development documents and examples for torch
+Provides: python3-%{pypi_name}-doc
+%description help
+PyTorch is a Python package that provides two high-level features:
+- Tensor computation (like NumPy) with strong GPU acceleration
+- Deep neural networks built on a tape-based autograd system
+You can reuse your favorite Python packages such as NumPy, SciPy and Cython to extend PyTorch when needed.
+
+%prep
+%autosetup -p1 -n %{pypi_name}-%{version}
+
+%build
+%pyproject_build
+
+%install
+%pyproject_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}
+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}/doclist.lst .
+
+%files -n python3-pytorch
+%doc *.md
+%license LICENSE
+%{_bindir}/convert-caffe2-to-onnx
+%{_bindir}/convert-onnx-to-caffe2
+%{_bindir}/torchrun
+%{python3_sitearch}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+
+%changelog
+* Mon Jan 22 2024 menma <1316818279@qq.com> - 0.9.5-1
+- Package init