Accept force_candidate_generation in axolotl main

Reviewed By: Cesar-Cardoso

Differential Revision: D65066157

ax/service/tests/scheduler_test_utils.py

@@ -321,7 +321,7 @@ class AxSchedulerTestCase(TestCase):
         "retries=False, wait_for_running_trials=True, fetch_kwargs={}, "
         "validate_metrics=True, status_quo_weight=0.0, "
         "enforce_immutable_search_space_and_opt_config=True, "
-        "mt_experiment_trial_type=None))"
+        "mt_experiment_trial_type=None, force_candidate_generation=False))"
     )
 
     def setUp(self) -> None:

ax/service/tests/test_scheduler.py

@@ -57,7 +57,7 @@ class TestAxSchedulerMultiTypeExperiment(AxSchedulerTestCase):
         "retries=False, wait_for_running_trials=True, fetch_kwargs={}, "
         "validate_metrics=True, status_quo_weight=0.0, "
         "enforce_immutable_search_space_and_opt_config=True, "
-        "mt_experiment_trial_type='type1'))"
+        "mt_experiment_trial_type='type1', force_candidate_generation=False))"
     )
 
     def setUp(self) -> None:

ax/service/utils/scheduler_options.py

@@ -117,6 +117,10 @@ class SchedulerOptions:
             is currently required for MultiTypeExperiments. This is ignored for
             "regular" or single type experiments. If you don't know what a single type
             experiment is, you don't need this.
+        force_candidate_generation: Whether to force candidate generation even if the
+            generation strategy is not ready to generate candidates, meaning one of the
+            transition criteria with block_gen_if_met is met.
+            **This is not yet implemented.**
     """
 
     max_pending_trials: int = 10
@@ -143,3 +147,4 @@ class SchedulerOptions:
     status_quo_weight: float = 0.0
     enforce_immutable_search_space_and_opt_config: bool = True
     mt_experiment_trial_type: str | None = None
+    force_candidate_generation: bool = False