601abf3649
Module for submodular optimization for the purpose of selecting subsets of massive data sets https://github.com/jmschrei/apricot
63 lines
1.2 KiB
Nix
63 lines
1.2 KiB
Nix
{ lib
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, buildPythonPackage
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, fetchFromGitHub
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, numba
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, numpy
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, pytestCheckHook
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, pythonOlder
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, torchvision
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, scikit-learn
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, scipy
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, setuptools
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, tqdm
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}:
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buildPythonPackage rec {
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pname = "apricot-select";
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version = "0.6.1";
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pyproject = true;
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disabled = pythonOlder "3.7";
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src = fetchFromGitHub {
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owner = "jmschrei";
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repo = "apricot";
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rev = "refs/tags/${version}";
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hash = "sha256-v9BHFxmlbwXVipPze/nV35YijdFBuka3gAl85AlsffQ=";
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};
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nativeBuildInputs = [
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setuptools
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];
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propagatedBuildInputs = [
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numba
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numpy
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scipy
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tqdm
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];
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nativeCheckInputs = [
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pytestCheckHook
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torchvision
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scikit-learn
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];
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pythonImportsCheck = [
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"apricot"
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];
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disabledTestPaths = [
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# Tests require nose
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"tests/test_optimizers/test_knapsack_facility_location.py"
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"tests/test_optimizers/test_knapsack_feature_based.py"
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];
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meta = with lib; {
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description = "Module for submodular optimization for the purpose of selecting subsets of massive data sets";
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homepage = "https://github.com/jmschrei/apricot";
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changelog = "https://github.com/jmschrei/apricot/releases/tag/${version}";
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license = licenses.mit;
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maintainers = with maintainers; [ fab ];
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};
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}
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