blob: 105f6a71c91534a7461339de41e52efe1dca2da4 (
plain) (
blame)
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
|
{ lib
, buildPythonPackage
, fetchFromGitHub
, numba
, numpy
, pytestCheckHook
, pythonOlder
, torchvision
, scikit-learn
, scipy
, setuptools
, tqdm
}:
buildPythonPackage rec {
pname = "apricot-select";
version = "0.6.1";
pyproject = true;
disabled = pythonOlder "3.7";
src = fetchFromGitHub {
owner = "jmschrei";
repo = "apricot";
rev = "refs/tags/${version}";
hash = "sha256-v9BHFxmlbwXVipPze/nV35YijdFBuka3gAl85AlsffQ=";
};
nativeBuildInputs = [
setuptools
];
propagatedBuildInputs = [
numba
numpy
scipy
tqdm
];
nativeCheckInputs = [
pytestCheckHook
torchvision
scikit-learn
];
pythonImportsCheck = [
"apricot"
];
disabledTestPaths = [
# Tests require nose
"tests/test_optimizers/test_knapsack_facility_location.py"
"tests/test_optimizers/test_knapsack_feature_based.py"
];
meta = with lib; {
description = "Module for submodular optimization for the purpose of selecting subsets of massive data sets";
homepage = "https://github.com/jmschrei/apricot";
changelog = "https://github.com/jmschrei/apricot/releases/tag/${version}";
license = licenses.mit;
maintainers = with maintainers; [ fab ];
};
}
|