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
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
|
%global _empty_manifest_terminate_build 0
Name: python-textgenrnn
Version: 2.0.0
Release: 1
Summary: Easily train your own text-generating neural network of any size and complexity
License: MIT
URL: https://github.com/minimaxir/textgenrnn
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/27/60/419daf7e2d87bcafc6f0f65736ce76e5cc83cebbae758dd59b4c1fae99cd/textgenrnn-2.0.0.tar.gz
BuildArch: noarch
%description
Easily train your own text-generating neural network of
any size and complexity on any text dataset with a few lines
of code, or quickly train on a text using a pretrained model.
- A modern neural network architecture which utilizes new techniques as
attention-weighting and skip-embedding to accelerate training
and improve model quality.
- Able to train on and generate text at either the
character-level or word-level.
- Able to configure RNN size, the number of RNN layers,
and whether to use bidirectional RNNs.
- Able to train on any generic input text file, including large files.
- Able to train models on a GPU and then use them with a CPU.
- Able to utilize a powerful CuDNN implementation of RNNs
when trained on the GPU, which massively speeds up training time as
opposed to normal LSTM implementations.
- Able to train the model using contextual labels,
allowing it to learn faster and produce better results in some cases.
- Able to generate text interactively for customized stories.
%package -n python3-textgenrnn
Summary: Easily train your own text-generating neural network of any size and complexity
Provides: python-textgenrnn
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-textgenrnn
Easily train your own text-generating neural network of
any size and complexity on any text dataset with a few lines
of code, or quickly train on a text using a pretrained model.
- A modern neural network architecture which utilizes new techniques as
attention-weighting and skip-embedding to accelerate training
and improve model quality.
- Able to train on and generate text at either the
character-level or word-level.
- Able to configure RNN size, the number of RNN layers,
and whether to use bidirectional RNNs.
- Able to train on any generic input text file, including large files.
- Able to train models on a GPU and then use them with a CPU.
- Able to utilize a powerful CuDNN implementation of RNNs
when trained on the GPU, which massively speeds up training time as
opposed to normal LSTM implementations.
- Able to train the model using contextual labels,
allowing it to learn faster and produce better results in some cases.
- Able to generate text interactively for customized stories.
%package help
Summary: Development documents and examples for textgenrnn
Provides: python3-textgenrnn-doc
%description help
Easily train your own text-generating neural network of
any size and complexity on any text dataset with a few lines
of code, or quickly train on a text using a pretrained model.
- A modern neural network architecture which utilizes new techniques as
attention-weighting and skip-embedding to accelerate training
and improve model quality.
- Able to train on and generate text at either the
character-level or word-level.
- Able to configure RNN size, the number of RNN layers,
and whether to use bidirectional RNNs.
- Able to train on any generic input text file, including large files.
- Able to train models on a GPU and then use them with a CPU.
- Able to utilize a powerful CuDNN implementation of RNNs
when trained on the GPU, which massively speeds up training time as
opposed to normal LSTM implementations.
- Able to train the model using contextual labels,
allowing it to learn faster and produce better results in some cases.
- Able to generate text interactively for customized stories.
%prep
%autosetup -n textgenrnn-2.0.0
%build
%py3_build
%install
%py3_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}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
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}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-textgenrnn -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.0-1
- Package Spec generated
|
