def test_train_model_no_test(gm, ms, imp, config, caplog):
with caplog.at_level(logging.DEBUG):
_, metrics = ma.train_model(config, cache=False, test=False)
assert metrics == {}
assert "training".lower() in caplog.text.lower()
ms_instance = ms.return_value
ms_instance.dump_trained_model.assert_called_once()
def test_train_model_no_persist(gm, ms, imp, config):
model, _ = ma.train_model(config, cache=False, persist=False)
ms_instance = ms.return_value
ms_instance.dump_trained_model.assert_not_called()
def test_train_model(gm, ms, imp, config):
ma.train_model(config, cache=False)
ms_instance = ms.return_value
ms_instance.dump_trained_model.assert_called_once()
def test_train_model_renamed(gm, ms, imp, config, caplog):
with caplog.at_level(logging.DEBUG):
ma.train_model(config, cache=False)
assert "renamed".lower() in caplog.text.lower()
def test_train_model_not_found(gm, ms, imp, config, caplog):
with caplog.at_level(logging.DEBUG):
ma.train_model(config, cache=False)
assert "No old model".lower() in caplog.text.lower()
def test_train_model_own_model(gm, ms, imp, config):
model, _ = ma.train_model(config, cache=False, model=mock.Mock())
gm.assert_not_called()