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
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
|
%global _empty_manifest_terminate_build 0
Name: python-mlserver-mlflow
Version: 1.3.1
Release: 1
Summary: MLflow runtime for MLServer
License: Apache 2.0
URL: https://github.com/SeldonIO/MLServer.git
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a1/11/33e5697087b561feb025b10cdd895ee8e2185b35b08f1b0538c9f5c7af65/mlserver-mlflow-1.3.1.tar.gz
BuildArch: noarch
Requires: python3-mlserver
Requires: python3-mlflow
%description
# MLflow runtime for MLServer
This package provides a MLServer runtime compatible with [MLflow
models](https://www.mlflow.org/docs/latest/models.html).
## Usage
You can install the runtime, alongside `mlserver`, as:
```bash
pip install mlserver mlserver-mlflow
```
## Content Types
The MLflow inference runtime introduces a new `dict` content type, which
decodes an incoming V2 request as a [dictionary of
tensors](https://www.mlflow.org/docs/latest/models.html#deploy-mlflow-models).
This is useful for certain MLflow-serialised models, which will expect that the
model inputs are serialised in this format.
```{note}
The `dict` content type can be _stacked_ with other content types, like
[`np`](../../docs/user-guide/content-type).
This allows the user to use a different set of content types to decode each of
the dict entries.
```
%package -n python3-mlserver-mlflow
Summary: MLflow runtime for MLServer
Provides: python-mlserver-mlflow
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-mlserver-mlflow
# MLflow runtime for MLServer
This package provides a MLServer runtime compatible with [MLflow
models](https://www.mlflow.org/docs/latest/models.html).
## Usage
You can install the runtime, alongside `mlserver`, as:
```bash
pip install mlserver mlserver-mlflow
```
## Content Types
The MLflow inference runtime introduces a new `dict` content type, which
decodes an incoming V2 request as a [dictionary of
tensors](https://www.mlflow.org/docs/latest/models.html#deploy-mlflow-models).
This is useful for certain MLflow-serialised models, which will expect that the
model inputs are serialised in this format.
```{note}
The `dict` content type can be _stacked_ with other content types, like
[`np`](../../docs/user-guide/content-type).
This allows the user to use a different set of content types to decode each of
the dict entries.
```
%package help
Summary: Development documents and examples for mlserver-mlflow
Provides: python3-mlserver-mlflow-doc
%description help
# MLflow runtime for MLServer
This package provides a MLServer runtime compatible with [MLflow
models](https://www.mlflow.org/docs/latest/models.html).
## Usage
You can install the runtime, alongside `mlserver`, as:
```bash
pip install mlserver mlserver-mlflow
```
## Content Types
The MLflow inference runtime introduces a new `dict` content type, which
decodes an incoming V2 request as a [dictionary of
tensors](https://www.mlflow.org/docs/latest/models.html#deploy-mlflow-models).
This is useful for certain MLflow-serialised models, which will expect that the
model inputs are serialised in this format.
```{note}
The `dict` content type can be _stacked_ with other content types, like
[`np`](../../docs/user-guide/content-type).
This allows the user to use a different set of content types to decode each of
the dict entries.
```
%prep
%autosetup -n mlserver-mlflow-1.3.1
%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-mlserver-mlflow -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 1.3.1-1
- Package Spec generated
|