Repeat boundaries for every registered SLO

runs/frontier-multicase-sufficiency-v0/best_effort/fixed_cohort_rank.py

@@ -52,7 +52,7 @@ PROTOCOL_SCHEMA = "qwen235b-prefill-fixed-cohort-protocol-v1"
 FRONTIER_SCHEMA = "frontier-qwen235b-prefill-fixed-cohort-v1"
 COMMUNITY_SCHEMA = "community-qwen235b-prefill-fixed-cohort-v1"
 COMPARISON_SCHEMA = "frontier-community-qwen235b-rank-comparison-v1"
-REPEAT_SELECTION_SCHEMA = "community-qwen235b-boundary-repeat-selection-v2"
+REPEAT_SELECTION_SCHEMA = "community-qwen235b-boundary-repeat-selection-v3"
 COHORT_SIZE = 64
 COHORT_SEED = 2026071501
 CONFIG_ORDER_SEED = 2026071502
@@ -879,8 +879,10 @@ def prepare_community(args: argparse.Namespace) -> Path:
     return path
 
 
-def _boundary_repeat_rates(config_result: dict[str, Any]) -> list[float]:
-    """Select every adjacent load pair whose primary feasibility label changes."""
+def _boundary_repeat_rates(
+    config_result: dict[str, Any], *, slo_name: str = PRIMARY_SLO
+) -> list[float]:
+    """Select every adjacent load pair whose SLO feasibility label changes."""
     loads = sorted(
         config_result["loads"], key=lambda item: float(item["offered_request_rate"])
     )
@@ -889,7 +891,7 @@ def _boundary_repeat_rates(config_result: dict[str, Any]) -> list[float]:
         raise ValueError(f"duplicate offered rate in {config_result['config']['name']}")
     if not rates:
         raise ValueError(f"no loads in {config_result['config']['name']}")
-    feasibility = [bool(item["scores"][PRIMARY_SLO]["feasible"]) for item in loads]
+    feasibility = [bool(item["scores"][slo_name]["feasible"]) for item in loads]
     selected: set[float] = set()
     for index in range(len(loads) - 1):
         if feasibility[index] != feasibility[index + 1]:
@@ -956,11 +958,27 @@ def prepare_community_repeat(args: argparse.Namespace) -> Path:
         reversed(first_execution_order), start=1
     ):
         name = source_record["config"]["name"]
-        boundary_rates = _boundary_repeat_rates(first_results[name])
-        refinement_rates = sorted(
+        boundary_rates_by_slo = {
+            slo_name: _boundary_repeat_rates(
+                first_results[name], slo_name=slo_name
+            )
+            for slo_name in SLO_VARIANTS
+        }
+        boundary_rates = sorted(
+            {
                 rate
+                for rates in boundary_rates_by_slo.values()
+                for rate in rates
+            }
+        )
+        refinement_rates = sorted(
+            {
+                rate
+                for rates in boundary_rates_by_slo.values()
+                for low, high in zip(rates, rates[1:])
                 for rate in duration_by_rate
-            if min(boundary_rates) < rate < max(boundary_rates)
+                if low < rate < high and rate not in boundary_rates
+            }
         )
         selected_rates = sorted(set(boundary_rates) | set(refinement_rates))
         source_relative_order = [
@@ -971,17 +989,6 @@ def prepare_community_repeat(args: argparse.Namespace) -> Path:
         if set(source_relative_order) != set(boundary_rates):
             raise ValueError(f"repeat rate is absent from source order: {name}")
         reversed_boundaries = list(reversed(source_relative_order))
-        if len(reversed_boundaries) == 2:
-            refinement_order = sorted(
-                refinement_rates,
-                reverse=reversed_boundaries[0] > reversed_boundaries[1],
-            )
-            repeat_order = [
-                reversed_boundaries[0],
-                *refinement_order,
-                reversed_boundaries[1],
-            ]
-        else:
         repeat_order = [*reversed_boundaries, *reversed(refinement_rates)]
         records.append(
             {
@@ -996,6 +1003,7 @@ def prepare_community_repeat(args: argparse.Namespace) -> Path:
         selections.append(
             {
                 "config": name,
+                "boundary_rates_by_slo": boundary_rates_by_slo,
                 "boundary_rates": boundary_rates,
                 "added_refinement_rates": refinement_rates,
                 "selected_rates": selected_rates,
@@ -1035,10 +1043,10 @@ def prepare_community_repeat(args: argparse.Namespace) -> Path:
         },
         "execution_contract": {
             "schema": REPEAT_SELECTION_SCHEMA,
-            "selection": "all_adjacent_primary_slo_feasibility_transitions_plus_between_rate_refinement",
+            "selection": "all_adjacent_pre_registered_slo_feasibility_transitions_plus_between_rate_refinement",
             "fallback_when_no_transition": "top_two_if_all_feasible_else_bottom_two",
             "config_order": "reverse_of_first_pass",
-            "rate_order": "reverse_first_pass_boundary_order_with_between_rate_refinement",
+            "rate_order": "reverse_first_pass_boundary_order_then_descending_refinement_rates",
             "one_fresh_server_launch_per_config": True,
             "warmup": source_manifest["execution_contract"]["warmup"],
             "estimated_replay_wall_seconds_excluding_model_loads": total_replay_seconds,

runs/frontier-multicase-sufficiency-v0/best_effort/test_fixed_cohort_rank.py

@@ -259,6 +259,13 @@ def test_boundary_repeat_rates_keep_every_transition_and_censored_fallback() ->
         0.2,
     ]
 
+    sensitivity = result([True, True, False, False])
+    for load, feasible in zip(sensitivity["loads"], [True, True, True, False]):
+        load["scores"]["linear_6k"] = {"feasible": feasible}
+    assert MODULE._boundary_repeat_rates(
+        sensitivity, slo_name="linear_6k"
+    ) == [0.3, 0.4]
+
 
 def test_request_slo_classification_exposes_aggregate_error_cancellation() -> None:
     def results(ttfts: list[float]) -> list[dict[str, object]]: