gahow/aituner
0
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Stop tuning when baseline is infeasible

Browse Source
This commit is contained in:
Gahow Wang
2026-05-08 01:07:36 +08:00
parent a7a5e9ad80
commit f212673f44
4 changed files with 170 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

75
src/aituner/cli.py
View File

@@ -19,6 +19,43 @@ from .trace import load_trace_requests, summarize_window
from .worker import run_trial
def _is_empty_config_patch(proposal: Proposal) -> bool:
return not proposal.config_patch.env_patch and not proposal.config_patch.flag_patch
def _baseline_all_infeasible_diagnosis(result: dict[str, object]) -> str | None:
if result.get("status") != "completed":
return None
if isinstance(result.get("best_request_rate"), (int, float)):
return None
probes = result.get("probes")
if not isinstance(probes, list) or not probes:
return None
if any(isinstance(probe, dict) and probe.get("feasible") for probe in probes):
return None
diagnostics = result.get("all_infeasible_diagnostics")
if not isinstance(diagnostics, dict):
diagnostics = {}
lowest_rate = diagnostics.get("request_rate")
lowest_threshold = diagnostics.get("threshold")
pass_rate = diagnostics.get("pass_rate")
early_stop_reason = str(diagnostics.get("early_stop_reason") or "").strip()
pieces = [
"Baseline configuration has no feasible probe under the current SLO.",
"Stopping tuning because even the lowest sampled request rate did not meet the target pass rate.",
]
if isinstance(lowest_rate, (int, float)):
pieces.append(f"lowest_sampled_request_rate={float(lowest_rate):.6g}")
if isinstance(lowest_threshold, (int, float)):
pieces.append(f"lowest_sampling_u={float(lowest_threshold):.6g}")
if isinstance(pass_rate, (int, float)):
pieces.append(f"lowest_probe_pass_rate={float(pass_rate):.6g}")
if early_stop_reason:
pieces.append(f"early_stop_reason={early_stop_reason}")
return " ".join(pieces)
def _study_source_path(study_root: Path) -> Path:
return Path((study_root / "study_spec.source").read_text(encoding="utf-8").strip())
@@ -126,6 +163,18 @@ def cmd_study_tune(args: argparse.Namespace) -> int:
executed: list[dict[str, object]] = []
for idx in range(max_trials):
state = store.load_state(study.study_id)
if state.tuning_stop_reason:
executed.append(
{
"trial_id": None,
"stopped": True,
"reason": state.tuning_stop_reason,
"diagnosis": state.tuning_stop_diagnosis,
"state_best_trial_id": state.best_trial_id,
"state_best_request_rate": state.best_request_rate,
}
)
break
if state.next_trial_index > max_trials:
break
window, requests = load_trace_requests(study, study_spec_path=spec_path)
@@ -228,6 +277,13 @@ def cmd_study_tune(args: argparse.Namespace) -> int:
}
)
break
is_auto_baseline = (
not proposal_files
and not args.skip_baseline
and state.next_trial_index == 1
and not state.trials
and _is_empty_config_patch(proposal)
)
trial, _ = store.materialize_trial(study=study, state=state, proposal=proposal)
trial_spec_path = Path(trial.artifact_dir) / "trial_spec.json"
result = run_trial(trial_spec_path)
@@ -248,6 +304,23 @@ def cmd_study_tune(args: argparse.Namespace) -> int:
"state_best_request_rate": state.best_request_rate,
}
)
if is_auto_baseline:
diagnosis = _baseline_all_infeasible_diagnosis(result)
if diagnosis is not None:
state.tuning_stop_reason = "baseline_all_infeasible"
state.tuning_stop_diagnosis = diagnosis
store.save_state(state)
executed.append(
{
"trial_id": None,
"stopped": True,
"reason": state.tuning_stop_reason,
"diagnosis": diagnosis,
"state_best_trial_id": state.best_trial_id,
"state_best_request_rate": state.best_request_rate,
}
)
break
final_state = store.load_state(study.study_id)
print(
@@ -257,6 +330,8 @@ def cmd_study_tune(args: argparse.Namespace) -> int:
"executed_trials": executed,
"best_trial_id": final_state.best_trial_id,
"best_request_rate": final_state.best_request_rate,
"tuning_stop_reason": final_state.tuning_stop_reason,
"tuning_stop_diagnosis": final_state.tuning_stop_diagnosis,
},
ensure_ascii=False,
)