allow more candidate trials than max_trials in Scheduler

ax/service/scheduler.py

@@ -920,13 +920,6 @@ def run_trials_and_yield_results(
         n_initial_candidate_trials = len(self.candidate_trials)
         if n_initial_candidate_trials == 0 and max_trials < 0:
             raise UserInputError(f"Expected `max_trials` >= 0, got {max_trials}.")
-        elif max_trials < n_initial_candidate_trials:
-            raise UserInputError(
-                "The number of pre-attached candidate trials "
-                f"({n_initial_candidate_trials}) is greater than `max_trials = "
-                f"{max_trials}`. Increase `max_trials` or reduce the number of "
-                "pre-attached candidate trials."
-            )
 
         # trials are pre-existing only if they do not still require running
         n_existing = len(self.experiment.trials) - n_initial_candidate_trials
@@ -1570,6 +1563,7 @@ def _complete_optimization(
             num_preexisting_trials=num_preexisting_trials,
             status=RunTrialsStatus.SUCCESS,
         )
+        self.warn_if_non_terminal_trials()
         return res
 
     def _validate_options(self, options: SchedulerOptions) -> None:
@@ -2151,6 +2145,17 @@ def _get_failure_rate_exceeded_error(
             )
         )
 
+    def warn_if_non_terminal_trials(self) -> None:
+        """Warns if there are any non-terminal trials on the experiment."""
+        non_terminal_trials = [
+            t.index for t in self.experiment.trials.values() if not t.status.is_terminal
+        ]
+        if len(non_terminal_trials) > 0:
+            self.logger.warning(
+                f"Found {len(non_terminal_trials)} non-terminal trials on "
+                f"{self.experiment.name}: {non_terminal_trials}."
+            )
+
 
 def get_fitted_model_bridge(
     scheduler: Scheduler, force_refit: bool = False

ax/service/tests/scheduler_test_utils.py

@@ -798,10 +798,11 @@ def test_run_preattached_trials_only(self) -> None:
         # pyre-fixme[6]: For 1st param expected `Dict[str, Union[None, bool, float,
         #  int, str]]` but got `Dict[str, int]`.
         trial.add_arm(Arm(parameters=parameter_dict))
-        with self.assertRaisesRegex(
-            UserInputError, "number of pre-attached candidate trials .* is greater than"
-        ):
-            scheduler.run_n_trials(max_trials=0)
+
+        # check no new trials are run, when max_trials = 0
+        scheduler.run_n_trials(max_trials=0)
+        self.assertEqual(trial.status, TrialStatus.CANDIDATE)
+        # check that candidate trial is run, when max_trials = 1
         scheduler.run_n_trials(max_trials=1)
         self.assertEqual(len(scheduler.experiment.trials), 1)
         self.assertDictEqual(
@@ -813,6 +814,43 @@ def test_run_preattached_trials_only(self) -> None:
             all(t.completed_successfully for t in scheduler.experiment.trials.values())
         )
 
+    def test_run_multiple_preattached_trials_only(self) -> None:
+        gs = self._get_generation_strategy_strategy_for_test(
+            experiment=self.branin_experiment,
+            generation_strategy=self.two_sobol_steps_GS,
+        )
+        # assert that pre-attached trials run when max_trials = number of
+        # pre-attached trials
+        scheduler = Scheduler(
+            experiment=self.branin_experiment,  # Has runner and metrics.
+            generation_strategy=gs,
+            options=SchedulerOptions(
+                init_seconds_between_polls=0,  # Short between polls so test is fast.
+                trial_type=TrialType.BATCH_TRIAL,
+            ),
+            db_settings=self.db_settings_if_always_needed,
+        )
+        trial1 = scheduler.experiment.new_trial()
+        trial1.add_arm(Arm(parameters={"x1": 5, "x2": 5}))
+        trial2 = scheduler.experiment.new_trial()
+        trial2.add_arm(Arm(parameters={"x1": 6, "x2": 3}))
+
+        # check that first candidate trial is run when called with max_trials = 1
+        with self.assertLogs(logger="ax.service.scheduler") as lg:
+            scheduler.run_n_trials(max_trials=1)
+            self.assertIn(
+                "Found 1 non-terminal trials on branin_test_experiment: [1]",
+                lg.output[-1],
+            )
+        self.assertIn(trial1.status, [TrialStatus.RUNNING, TrialStatus.COMPLETED])
+        self.assertEqual(trial2.status, TrialStatus.CANDIDATE)
+        # check that next candidate trial is run, when max_trials = 1
+        scheduler.run_n_trials(max_trials=1)
+        self.assertEqual(len(scheduler.experiment.trials), 2)
+        self.assertTrue(  # Make sure all trials got to complete.
+            all(t.completed_successfully for t in scheduler.experiment.trials.values())
+        )
+
     def test_global_stopping(self) -> None:
         gs = self._get_generation_strategy_strategy_for_test(
             experiment=self.branin_experiment,