2019-07-11 19:47:57 +01:00
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{ lib
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, buildPythonPackage
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, fetchPypi
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, pytest
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, mock
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, bokeh
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, plotly
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, chainer
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, xgboost
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, mpi4py
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, lightgbm
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, Keras
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, mxnet
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, scikit-optimize
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, tensorflow
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, sqlalchemy
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, numpy
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, scipy
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, six
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, cliff
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, colorlog
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, pandas
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, alembic
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, typing
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, pythonOlder
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, isPy27
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}:
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buildPythonPackage rec {
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pname = "optuna";
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2019-10-24 07:47:40 +01:00
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version = "0.17.1";
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2019-07-11 19:47:57 +01:00
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disabled = isPy27;
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src = fetchPypi {
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inherit pname version;
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2019-10-24 07:47:40 +01:00
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sha256 = "3d1d3547340c47f34f3a416a2e0761a0ff887ae8ce06474e84ebcc8600afd438";
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2019-07-11 19:47:57 +01:00
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};
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checkInputs = [
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pytest
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mock
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bokeh
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plotly
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chainer
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xgboost
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mpi4py
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lightgbm
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Keras
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mxnet
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scikit-optimize
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tensorflow
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];
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propagatedBuildInputs = [
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sqlalchemy
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numpy
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scipy
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six
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cliff
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colorlog
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pandas
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alembic
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] ++ lib.optionals (pythonOlder "3.5") [ typing ];
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configurePhase = if !(pythonOlder "3.5") then ''
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substituteInPlace setup.py \
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--replace "'typing'" ""
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'' else "";
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checkPhase = ''
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pytest --ignore tests/test_cli.py \
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--ignore tests/integration_tests/test_chainermn.py
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'';
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meta = with lib; {
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description = "A hyperparameter optimization framework";
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homepage = https://optuna.org/;
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license = licenses.mit;
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maintainers = [ maintainers.costrouc ];
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};
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}
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