autoPyTorch/api/

Author: ravinkohli

test/test_api/test_api.py

@@ -429,7 +429,6 @@ 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()
@@ -444,6 +443,7 @@ def test_tabular_input_support(openml_id, backend):
             func_eval_time_limit_secs=50,
             enable_traditional_pipeline=False,
             load_models=False,
+            ensemble_size=0,
         )
 
 
@@ -453,7 +453,6 @@ 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()

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
@@ -167,7 +167,6 @@ def test_init_ensemble_builder(backend):
     BaseTask.__abstractmethods__ = set()
     estimator = BaseTask(
         backend=backend,
-        ensemble_size=0,
     )
 
     # Setup pre-requisites normally set by search()