%global _empty_manifest_terminate_build 0
%define debug_package %{nil}
Name:           vision
Version:        0.16.0
Release:        2
Summary:        Tensors and Dynamic neural networks in Python with strong GPU acceleration
License:        BSD-3
URL:            https://github.com/pytorch/vision
Source0:        https://atomgit.com/havefun/vision/raw/master/torchvision-0.16.0.tar.gz

BuildRequires:  g++
Requires:       python3-future
Requires:       python3-numpy

%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-vision
Summary:        Tensors and Dynamic neural networks in Python with strong GPU acceleration
Provides:       python-vision
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
BuildRequires:  python3-pytorch

AutoReqProv: no

%description -n python3-vision
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-vision-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 %{name}-%{version}

%build
%py3_build
#python3 setup.py build

%install
%define _unpackaged_files_terminate_build 0
%py3_install
#python3 setup.py install

%files -n python3-vision
%doc *.md
%license LICENSE
%{python3_sitearch}/*


%changelog
* Wed Jan 31 2024 Hongyu Li<543306408@qq.com>
- Package init