feat(perception): prewarm RF-DETR before source admission

experiments/perception/run_m48s_reference_graph_shadow_worker.py

@@ -24,6 +24,7 @@ from k1link.perception.contracts import MotionState, ObjectProposal2D
 from k1link.perception.detector import (
     DetectorFrameTiming,
     DetectorProviderSnapshot,
+    DetectorWarmupSnapshot,
     RfDetrShadowDetectorProvider,
 )
 from k1link.perception.geometry import Ravnoves00GeometryAssociationProvider
@@ -51,7 +52,7 @@ from k1link.perception.reference_graph_runtime import ReferenceGraphRuntimePaths
 from k1link.perception.rolling_map import RollingLocalObstacleMapProvider
 from k1link.perception.temporal import BoundedSpatialTemporalProvider
 
-SCHEMA_VERSION: Final = "missioncore.m48s-reference-graph-shadow-load/v2"
+SCHEMA_VERSION: Final = "missioncore.m48s-reference-graph-shadow-load/v3"
 FRAME_EVIDENCE_SCHEMA: Final = "missioncore.m48s-reference-graph-frame-evidence/v1"
 PIPELINE_TIMING_SCHEMA: Final = "missioncore.m48s-frame-pipeline-timing/v0"
 GC_POLICY_SCHEMA: Final = "missioncore.cyclic-gc-hot-loop-policy/v0"
@@ -443,6 +444,7 @@ def main() -> int:
                             gc_telemetry,
                         ),
                     )
+                detector_warmup = runtime.warm_up_detector()
                 gc_policy = CyclicGcHotLoopPolicy()
                 with gc_policy:
                     loop_started_ns = time.monotonic_ns()
@@ -496,6 +498,7 @@ def main() -> int:
                 wall_seconds=loop_wall_seconds,
                 setup_seconds=setup_seconds,
                 gc_policy=gc_policy.to_dict(),
+                detector_warmup=detector_warmup,
             )
             loop_documents.append(loop_document)
             completion_ages_ms.extend(value / 1_000_000.0 for value in loop_completion_ages_ns)
@@ -578,6 +581,11 @@ def main() -> int:
             is cast(dict[str, object], loop["cyclic_gc_hot_loop"])["enabled_after"]
             for loop in loop_documents
         ),
+        "detector_warmup_completed_before_source_admission": all(
+            cast(dict[str, object], loop["detector_warmup"])["completed"] is True
+            and cast(dict[str, object], loop["detector_warmup"])["inference_passes"] == 1
+            for loop in loop_documents
+        ),
         "authority_remains_false": all(value is False for value in AUTHORITY.values()),
     }
     integrated_runtime_gate_passed = all(checks.values())
@@ -604,6 +612,10 @@ def main() -> int:
             "terminal_outcomes": dict(sorted(accounting.items())),
             "queue_high_watermarks": queue_high_watermarks,
             "loops": loop_documents,
+            "startup_warmup_inference_passes": sum(
+                cast(int, cast(dict[str, object], loop["detector_warmup"])["inference_passes"])
+                for loop in loop_documents
+            ),
             "frame_evidence": {
                 "schema_version": FRAME_EVIDENCE_SCHEMA,
                 "path": frame_ledger.name,
@@ -690,6 +702,7 @@ def _loop_document(
     wall_seconds: float,
     setup_seconds: float,
     gc_policy: dict[str, object],
+    detector_warmup: DetectorWarmupSnapshot,
 ) -> dict[str, object]:
     outcomes = Counter(item.outcome.value for item in result.terminal_outcomes)
     outcome_stages = Counter(
@@ -701,6 +714,7 @@ def _loop_document(
         "wall_seconds": round(wall_seconds, 6),
         "setup_seconds": round(setup_seconds, 6),
         "cyclic_gc_hot_loop": gc_policy,
+        "detector_warmup": asdict(detector_warmup),
         "admitted_count": result.admitted_count,
         "delivered_count": len(result.deliveries),
         "effective_world_state_fps": round(len(result.deliveries) / wall_seconds, 6),