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Stop harness when search high is saturated

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This commit is contained in:
Gahow Wang
2026-05-02 11:04:59 +08:00
parent ccbf24ac47
commit 4c066c4e4e
2 changed files with 157 additions and 1 deletions
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100
src/aituner/harness.py
View File

@@ -41,7 +41,7 @@ def build_harness_context(
"workload_lca_profile": _workload_lca_profile(window_summary),
"recent_trial_diagnostics": recent_diagnostics,
"convergence_guard": _convergence_guard(state, recent_diagnostics),
"harness_stop": _harness_stop_decision(state, recent_diagnostics),
"harness_stop": _harness_stop_decision(study, state, recent_diagnostics),
"knob_harnesses": _knob_harnesses(study, window_summary, recent_diagnostics),
"proposal_rules": _proposal_rules(),
}
@@ -471,9 +471,17 @@ def _convergence_guard(
def _harness_stop_decision(
study: StudySpec,
state: StudyState,
recent_diagnostics: list[dict[str, Any]],
) -> dict[str, Any]:
high_saturation = _search_high_saturation_guard(study, state, recent_diagnostics)
if high_saturation["saturated"]:
return {
"should_stop": True,
"reason": high_saturation["reason"],
"evidence": high_saturation,
}
guard = _convergence_guard(state, recent_diagnostics)
if guard["deterministic_stop"]:
return {
@@ -496,12 +504,102 @@ def _harness_stop_decision(
"reason": "continue_harness_guided_search",
"evidence": {
"summary": "No deterministic harness stop condition is satisfied.",
"search_high_saturation": high_saturation,
"convergence_guard": guard,
"validation_exhausted": validation,
},
}
def _search_high_saturation_guard(
study: StudySpec,
state: StudyState,
recent_diagnostics: list[dict[str, Any]],
) -> dict[str, Any]:
default = {
"saturated": False,
"reason": "search_high_not_saturated",
"summary": "The incumbent has not saturated the configured search high.",
"incumbent_trial_id": state.best_trial_id,
"search_high": study.search.high,
"last_threshold": None,
"threshold_gap_to_high": None,
}
if not state.best_trial_id:
return default
incumbent = next(
(
item
for item in recent_diagnostics
if item.get("trial_id") == state.best_trial_id
),
None,
)
if not incumbent:
return {
**default,
"reason": "incumbent_not_in_recent_harness_history",
}
probe_summary = incumbent.get("probe_summary")
if not isinstance(probe_summary, dict):
return {
**default,
"reason": "incumbent_probe_summary_missing",
}
last_probe = probe_summary.get("last_probe")
if not isinstance(last_probe, dict):
return {
**default,
"reason": "incumbent_last_probe_missing",
}
last_threshold = _as_float(last_probe.get("threshold"))
threshold_gap = float(study.search.high) - last_threshold
binary_probe_resolution = max(
float(study.search.tolerance),
(float(study.search.high) - float(study.search.low)) / float(2 ** max(study.search.max_probes, 1)),
)
latency_summary = last_probe.get("latency_summary")
failed = latency_summary.get("failed_reason_counts") if isinstance(latency_summary, dict) else {}
if not isinstance(failed, dict):
failed = {}
if not last_probe.get("feasible"):
return {
**default,
"reason": "incumbent_last_probe_not_feasible",
"last_threshold": last_threshold,
"threshold_gap_to_high": threshold_gap,
}
if threshold_gap > binary_probe_resolution + 1e-12:
return {
**default,
"reason": "incumbent_not_close_to_search_high",
"last_threshold": last_threshold,
"threshold_gap_to_high": threshold_gap,
"binary_probe_resolution": binary_probe_resolution,
}
if failed:
return {
**default,
"reason": "incumbent_high_probe_has_slo_failures",
"last_threshold": last_threshold,
"threshold_gap_to_high": threshold_gap,
"failed_reason_counts": failed,
}
return {
"saturated": True,
"reason": "search_high_saturated_by_incumbent",
"summary": (
"The incumbent's highest measured probe is feasible, has no SLO failures, "
"and is within the configured binary-search resolution of search.high."
),
"incumbent_trial_id": state.best_trial_id,
"search_high": study.search.high,
"last_threshold": last_threshold,
"threshold_gap_to_high": threshold_gap,
"binary_probe_resolution": binary_probe_resolution,
}
def _validation_exhausted_guard(
state: StudyState,
recent_diagnostics: list[dict[str, Any]],

58
tests/test_core_flow.py
View File

@@ -538,6 +538,64 @@ class CoreFlowTests(unittest.TestCase):
self.assertFalse(context["harness_stop"]["should_stop"])
self.assertIsNone(build_harness_stop_proposal(context))
def test_harness_stop_when_incumbent_saturates_search_high(self) -> None:
with tempfile.TemporaryDirectory() as tmp:
tmp_path = Path(tmp)
study_path = _write_study_assets(tmp_path)
study = load_study_spec(study_path)
result_path = tmp_path / "trial-0001.json"
result_path.write_text(
json.dumps(
{
"status": "completed",
"best_sampling_u": 0.99609375,
"best_request_rate": 9.0,
"best_pass_rate": 1.0,
"probes": [
{
"threshold": 0.99609375,
"feasible": True,
"payload": {
"request_count": 10,
"pass_rate": 1.0,
"request_rate": 9.0,
"early_stopped": False,
"early_stop_reason": "",
"latency_summary": {"failed_reason_counts": {}},
},
}
],
}
),
encoding="utf-8",
)
state = StudyState(
study_id=study.study_id,
best_trial_id="trial-0001",
best_request_rate=9.0,
best_request_rate_per_gpu=9.0,
trials=[
TrialSummary(
trial_id="trial-0001",
status="completed",
best_request_rate=9.0,
best_request_rate_per_gpu=9.0,
result_path=str(result_path),
config_patch={"env_patch": {}, "flag_patch": {}},
)
],
)
context = build_harness_context(
study=study,
window_summary={"prompt_tokens_p95": 2048},
state=state,
)
self.assertTrue(context["harness_stop"]["should_stop"])
self.assertEqual(context["harness_stop"]["reason"], "search_high_saturated_by_incumbent")
proposal = build_harness_stop_proposal(context)
self.assertIsNotNone(proposal)
self.assertTrue(proposal.should_stop)
def test_trace_input_length_filter_keeps_only_matching_rows(self) -> None:
with tempfile.TemporaryDirectory() as tmp:
tmp_path = Path(tmp)