Use full search range for every trial

src/aituner/store.py

@@ -85,15 +85,11 @@ class StudyStore:
         trial_root = self.study_root(study.study_id) / "trials" / trial_id
         trial_root.mkdir(parents=True, exist_ok=True)
         parallel_size = _parallel_size_for_proposal(study=study, proposal=proposal)
-        search_low = _derive_search_floor(study=study, state=state, parallel_size=parallel_size)
         spec = TrialSpec(
             study_id=study.study_id,
             trial_id=trial_id,
             config_patch=proposal.config_patch,
-            search=replace(
-                study.search,
-                low=search_low,
-            ),
+            search=study.search,
             study_spec_path=str((self.study_root(study.study_id) / "study_spec.source").resolve()),
             artifact_dir=str(trial_root),
             probe_log_path=str(trial_root / "probe_history.json"),
@@ -305,15 +301,3 @@ def _request_rate_per_gpu(best_request_rate: Any, parallel_size: int | None) ->
         return None
     return float(best_request_rate) / float(parallel_size)
 
-
-def _derive_search_floor(*, study: StudySpec, state: StudyState, parallel_size: int) -> float:
-    low = study.search.low
-    high = study.search.high
-    group_incumbent = (state.best_by_parallel_size or {}).get(str(parallel_size))
-    if isinstance(group_incumbent, dict) and isinstance(
-        group_incumbent.get("best_sampling_u"), (int, float)
-    ):
-        candidate = float(group_incumbent["best_sampling_u"])
-    else:
-        candidate = low
-    return min(high, max(low, candidate))

tests/test_core_flow.py

@@ -2100,7 +2100,12 @@ class CoreFlowTests(unittest.TestCase):
                 }
             )
             trial, _ = store.materialize_trial(study=study, state=state, proposal=proposal)
-            self.assertEqual(trial.search.low, 0.5)
+            self.assertEqual(trial.search.low, 0.0)
+
+            trial_spec_path = Path(trial.artifact_dir) / "trial_spec.json"
+            trial_spec_payload = json.loads(trial_spec_path.read_text(encoding="utf-8"))
+            trial_spec_payload["search"]["low"] = 0.5
+            trial_spec_path.write_text(json.dumps(trial_spec_payload), encoding="utf-8")
 
             def fake_replay(requests, **kwargs):
                 passing = len(requests) <= 1
@@ -2126,7 +2131,7 @@ class CoreFlowTests(unittest.TestCase):
                 with mock.patch("aituner.worker._wait_for_server_or_exit", return_value=None):
                     with mock.patch("aituner.worker._terminate_process_tree", return_value=None):
                         with mock.patch("aituner.worker._replay_requests", side_effect=fake_replay):
-                            result = run_trial(Path(trial.artifact_dir) / "trial_spec.json")
+                            result = run_trial(trial_spec_path)
 
             self.assertEqual(result["status"], "completed")
             self.assertEqual(result["best_source"], "lower_range_fallback")
@@ -2168,7 +2173,7 @@ class CoreFlowTests(unittest.TestCase):
             self.assertEqual(state.trials, [])
             self.assertEqual(len(next_state.trials), 1)
 
-    def test_materialize_trial_uses_incumbent_sampling_u_as_search_floor(self) -> None:
+    def test_materialize_trial_uses_full_search_range_with_incumbent(self) -> None:
         with tempfile.TemporaryDirectory() as tmp:
             tmp_path = Path(tmp)
             study_path = _write_study_assets(tmp_path)
@@ -2203,10 +2208,10 @@ class CoreFlowTests(unittest.TestCase):
                 }
             )
             trial, _ = store.materialize_trial(study=study, state=state, proposal=proposal)
-            self.assertEqual(trial.search.low, 0.375)
+            self.assertEqual(trial.search.low, study.search.low)
             self.assertEqual(trial.search.high, 1.0)
 
-    def test_materialize_trial_uses_same_parallel_group_incumbent(self) -> None:
+    def test_materialize_trial_uses_full_search_range_for_same_parallel_group(self) -> None:
         with tempfile.TemporaryDirectory() as tmp:
             tmp_path = Path(tmp)
             study_path = _write_study_assets(tmp_path)
@@ -2241,7 +2246,7 @@ class CoreFlowTests(unittest.TestCase):
                 }
             )
             trial, _ = store.materialize_trial(study=study, state=state, proposal=proposal)
-            self.assertEqual(trial.search.low, 0.125)
+            self.assertEqual(trial.search.low, study.search.low)
 
     def test_materialize_trial_resets_search_floor_for_new_parallel_group(self) -> None:
         with tempfile.TemporaryDirectory() as tmp:
@@ -2359,7 +2364,7 @@ class CoreFlowTests(unittest.TestCase):
                     "max-num-seqs": 160,
                 },
             )
-            self.assertEqual(trial.search.low, 0.125)
+            self.assertEqual(trial.search.low, study.search.low)
             self.assertEqual(
                 next_state.trials[-1].config_patch["flag_patch"],
                 {