blob: 2608227139654baaf5f736717964e2f1e191c1e8 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
|
%global _empty_manifest_terminate_build 0
Name: pytorch
Version: 2.1.2
Release: 2
Summary: Tensors and Dynamic neural networks in Python with strong GPU acceleration
License: BSD-3
URL: https://pytorch.org/
Source0: https://github.com/pytorch/pytorch/releases/download/v%{version}/pytorch-v%{version}.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-pytorch
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-pytorch
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-pytorch-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}-v%{version}
%build
export CFLAGS+=" -Wno-error=maybe-uninitialized -Wno-error=uninitialized -Wno-error=restrict -fPIC"
export CXXFLAGS+=" -Wno-error=maybe-uninitialized -Wno-error=uninitialized -Wno-error=restrict -fPIC"
%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
* Fri Mar 29 2024 youser
- Package init
|