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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
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