diff --git a/test/test_api/test_api.py b/test/test_api/test_api.py index 1ef1611f1..d3bb71119 100644 --- a/test/test_api/test_api.py +++ b/test/test_api/test_api.py @@ -609,7 +609,6 @@ def test_tabular_input_support(openml_id, backend): estimator = TabularClassificationTask( backend=backend, resampling_strategy=HoldoutValTypes.holdout_validation, - ensemble_size=0, ) estimator._do_dummy_prediction = unittest.mock.MagicMock() @@ -624,6 +623,7 @@ def test_tabular_input_support(openml_id, backend): func_eval_time_limit_secs=50, enable_traditional_pipeline=False, load_models=False, + ensemble_size=0, ) @@ -633,7 +633,6 @@ def test_do_dummy_prediction(dask_client, fit_dictionary_tabular): estimator = TabularClassificationTask( backend=backend, resampling_strategy=HoldoutValTypes.holdout_validation, - ensemble_size=0, ) # Setup pre-requisites normally set by search() diff --git a/test/test_api/test_base_api.py b/test/test_api/test_base_api.py index afaff86c9..edc9499d7 100644 --- a/test/test_api/test_base_api.py +++ b/test/test_api/test_base_api.py @@ -118,7 +118,7 @@ def test_set_pipeline_config(): ]) def test_pipeline_get_budget(fit_dictionary_tabular, min_budget, max_budget, budget_type, expected): BaseTask.__abstractmethods__ = set() - estimator = BaseTask(task_type='tabular_classification', ensemble_size=0) + estimator = BaseTask(task_type='tabular_classification') # Fixture pipeline config default_pipeline_config = { @@ -141,7 +141,7 @@ def test_pipeline_get_budget(fit_dictionary_tabular, min_budget, max_budget, bud smac_mock.return_value = smac estimator._search(optimize_metric='accuracy', dataset=dataset, tae_func=pipeline_fit, min_budget=min_budget, max_budget=max_budget, budget_type=budget_type, - enable_traditional_pipeline=False, + ensemble_size=0, enable_traditional_pipeline=False, total_walltime_limit=20, func_eval_time_limit_secs=10, load_models=False) assert list(smac_mock.call_args)[1]['ta_kwargs']['pipeline_config'] == default_pipeline_config @@ -210,7 +210,6 @@ def test_init_ensemble_builder(backend): BaseTask.__abstractmethods__ = set() estimator = BaseTask( backend=backend, - ensemble_size=0, ) # Setup pre-requisites normally set by search()