fix bug in adversarial trainer (#207)

Author: ravinkohli

autoPyTorch/pipeline/components/training/trainer/AdversarialTrainer.py

@@ -196,22 +196,35 @@ def get_hyperparameter_search_space(
 
         add_hyperparameter(cs, epsilon, UniformFloatHyperparameter)
         add_hyperparameter(cs, use_stochastic_weight_averaging, CategoricalHyperparameter)
+        snapshot_ensemble_flag = False
+        if any(use_snapshot_ensemble.value_range):
+            snapshot_ensemble_flag = True
+
         use_snapshot_ensemble = get_hyperparameter(use_snapshot_ensemble, CategoricalHyperparameter)
-        se_lastk = get_hyperparameter(se_lastk, Constant)
-        cs.add_hyperparameters([use_snapshot_ensemble, se_lastk])
-        cond = EqualsCondition(se_lastk, use_snapshot_ensemble, True)
-        cs.add_condition(cond)
+        cs.add_hyperparameter(use_snapshot_ensemble)
+
+        if snapshot_ensemble_flag:
+            se_lastk = get_hyperparameter(se_lastk, Constant)
+            cs.add_hyperparameter(se_lastk)
+            cond = EqualsCondition(se_lastk, use_snapshot_ensemble, True)
+            cs.add_condition(cond)
+
+        lookahead_flag = False
+        if any(use_lookahead_optimizer.value_range):
+            lookahead_flag = True
 
         use_lookahead_optimizer = get_hyperparameter(use_lookahead_optimizer, CategoricalHyperparameter)
         cs.add_hyperparameter(use_lookahead_optimizer)
-        la_config_space = Lookahead.get_hyperparameter_search_space(la_steps=la_steps,
-                                                                    la_alpha=la_alpha)
-        parent_hyperparameter = {'parent': use_lookahead_optimizer, 'value': True}
-        cs.add_configuration_space(
-            Lookahead.__name__,
-            la_config_space,
-            parent_hyperparameter=parent_hyperparameter
-        )
+
+        if lookahead_flag:
+            la_config_space = Lookahead.get_hyperparameter_search_space(la_steps=la_steps,
+                                                                        la_alpha=la_alpha)
+            parent_hyperparameter = {'parent': use_lookahead_optimizer, 'value': True}
+            cs.add_configuration_space(
+                Lookahead.__name__,
+                la_config_space,
+                parent_hyperparameter=parent_hyperparameter
+            )
 
         """
         if dataset_properties is not None: