[Rebase]

Author: franchuterivera

test/test_api/test_api.py

@@ -72,7 +72,7 @@ def test_tabular_classification(openml_id, resampling_strategy, backend):
 
     # Internal dataset has expected settings
     assert estimator.dataset.task_type == 'tabular_classification'
-    expected_num_splits = 1 if resampling_strategy == HoldoutValTypes.holdout_validation else 3
+    expected_num_splits = 1 if resampling_strategy == HoldoutValTypes.holdout_validation else 5
     assert estimator.resampling_strategy == resampling_strategy
     assert estimator.dataset.resampling_strategy == resampling_strategy
     assert len(estimator.dataset.splits) == expected_num_splits
@@ -140,7 +140,7 @@ def test_tabular_classification(openml_id, resampling_strategy, backend):
         model = estimator._backend.load_cv_model_by_seed_and_id_and_budget(
             estimator.seed, successful_num_run, run_key.budget)
         assert isinstance(model, VotingClassifier)
-        assert len(model.estimators_) == 3
+        assert len(model.estimators_) == 5
         assert isinstance(model.estimators_[0].named_steps['network'].get_network(),
                           torch.nn.Module)
     else:
@@ -243,7 +243,7 @@ def test_tabular_regression(openml_name, resampling_strategy, backend):
 
     # Internal dataset has expected settings
     assert estimator.dataset.task_type == 'tabular_regression'
-    expected_num_splits = 1 if resampling_strategy == HoldoutValTypes.holdout_validation else 3
+    expected_num_splits = 1 if resampling_strategy == HoldoutValTypes.holdout_validation else 5
     assert estimator.resampling_strategy == resampling_strategy
     assert estimator.dataset.resampling_strategy == resampling_strategy
     assert len(estimator.dataset.splits) == expected_num_splits
@@ -310,7 +310,7 @@ def test_tabular_regression(openml_name, resampling_strategy, backend):
         model = estimator._backend.load_cv_model_by_seed_and_id_and_budget(
             estimator.seed, successful_num_run, run_key.budget)
         assert isinstance(model, VotingRegressor)
-        assert len(model.estimators_) == 3
+        assert len(model.estimators_) == 5
         assert isinstance(model.estimators_[0].named_steps['network'].get_network(),
                           torch.nn.Module)
     else: