Fix decode harness partial probe handling
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@@ -39,6 +39,7 @@ from aituner.spec import (
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from aituner.store import StudyStore
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from aituner.trace import load_trace_requests, summarize_window
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from aituner.worker import (
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_best_feasible_probe_record,
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_latency_summary,
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_run_one_request,
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_replay_requests,
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@@ -1518,6 +1519,103 @@ class CoreFlowTests(unittest.TestCase):
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"\n".join(context["proposal_rules"]),
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)
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def test_decode_topology_planner_prefers_dp_redistribution_and_preserves_ep(self) -> None:
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with tempfile.TemporaryDirectory() as tmp:
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tmp_path = Path(tmp)
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study_path = _write_study_assets(
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tmp_path,
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trace_overrides={"request_mode": "decode_only"},
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slo_overrides={
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"ttft_rule": None,
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"tpot_rule": {"kind": "fixed_ms", "threshold_ms": 40},
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},
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engine_overrides={
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"base_flags": {
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"host": "127.0.0.1",
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"port": 8000,
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"enable-expert-parallel": True,
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"tensor-parallel-size": 4,
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"data-parallel-size": 2,
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"expert-parallel-size": 8,
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"max-num-seqs": 192,
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},
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"tunable_flags": [
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"tensor-parallel-size",
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"data-parallel-size",
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"expert-parallel-size",
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"max-num-seqs",
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],
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"topology_constraints": {
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"allowed_tensor_parallel_sizes": [1, 2, 4, 8],
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"allowed_data_parallel_sizes": [1, 2, 4, 8],
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"allowed_expert_parallel_sizes": [1, 2, 4, 8],
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"require_tp_dp_product_equals_gpu_count": True,
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"require_ep_size_leq_tp_dp_product": True,
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"require_ep_size_divides_tp_dp_product": True,
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"require_enable_expert_parallel_when_ep_gt_one": True,
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},
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},
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)
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result_path = tmp_path / "trial-0001-result.json"
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result_path.write_text(
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json.dumps(
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{
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"status": "completed",
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"best_request_rate": 0.47,
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"best_pass_rate": 0.98,
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"probes": [
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{
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"threshold": 0.04,
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"feasible": False,
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"payload": {
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"request_rate": 0.72,
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"pass_rate": 0.3,
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"early_stop_reason": "slo_pass_rate_unrecoverable",
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"latency_summary": {
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"failed_reason_counts": {"tpot_ms>40.0": 80}
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},
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},
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}
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],
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}
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),
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encoding="utf-8",
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)
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study = load_study_spec(study_path)
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context = build_harness_context(
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study=study,
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window_summary={},
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state=StudyState(
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study_id=study.study_id,
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best_trial_id="trial-0001",
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best_request_rate=0.47,
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best_request_rate_per_gpu=0.05875,
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trials=[
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TrialSummary(
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trial_id="trial-0001",
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status="completed",
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best_request_rate=0.47,
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best_request_rate_per_gpu=0.05875,
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best_pass_rate=0.98,
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result_path=str(result_path),
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config_patch={"env_patch": {}, "flag_patch": {}},
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)
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],
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),
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)
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action = context["experiment_plan"]["next_action"]
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self.assertEqual(action["knob_family"], "topology")
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self.assertEqual(
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action["config_patch"]["flag_patch"],
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{"tensor-parallel-size": 2, "data-parallel-size": 4},
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)
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proposal = build_harness_guided_proposal(context)
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self.assertIsNotNone(proposal)
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self.assertEqual(
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proposal.config_patch.flag_patch,
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{"tensor-parallel-size": 2, "data-parallel-size": 4},
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)
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def test_prompt_can_disable_harness_for_ablation(self) -> None:
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with tempfile.TemporaryDirectory() as tmp:
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tmp_path = Path(tmp)
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@@ -1625,6 +1723,33 @@ class CoreFlowTests(unittest.TestCase):
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self.assertIn("data-parallel-size", active)
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self.assertIn("max-num-seqs", active)
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def test_best_feasible_probe_record_keeps_partial_probe_evidence(self) -> None:
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best = _best_feasible_probe_record(
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[
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{
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"threshold": 0.03125,
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"request_rate": 0.72,
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"pass_rate": 0.3,
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"feasible": False,
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},
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{
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"threshold": 0.015625,
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"request_rate": 0.3533,
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"pass_rate": 0.99,
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"feasible": True,
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},
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{
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"threshold": 0.017578125,
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"request_rate": 0.3833,
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"pass_rate": 0.995,
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"feasible": True,
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},
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]
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)
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self.assertIsNotNone(best)
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self.assertEqual(best["threshold"], 0.017578125)
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self.assertEqual(best["request_rate"], 0.3833)
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def test_load_study_spec_rejects_mismatched_served_model_name(self) -> None:
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with tempfile.TemporaryDirectory() as tmp:
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tmp_path = Path(tmp)
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