"""Deterministic mapping from raw diagnosis_hypothesis / workload_type strings (as actually observed in the frozen Phase 4.4/4.5 evidence) to the canonical FailureClass enum defined in PHASE5_1_SCHEMA.json. This mapping is itself a DERIVED_LABEL transformation (leakage policy rule 6): it is computed once, deterministically, from the raw diagnosis_hypothesis/workload_type strings already present at generation time -- never back-filled from a later diagnosis or memory record. """ from __future__ import annotations # diagnosis_hypothesis (as emitted by src/phase4/diagnosis.py) -> FailureClass DIAGNOSIS_TO_FAILURE_CLASS = { "NETWORK_CONNECTIVITY_FAILURE": "NETWORK_FAILURE", "PROCESS_EXIT_FAILURE": "GENERIC_FAIL", "RUNTIME_TIMEOUT": "PROCESS_TIMEOUT_CPU", "OUT_OF_MEMORY": "PROCESS_OOM", "RESOURCE_CONTENTION": "RESOURCE_UNAVAILABLE", "GPU_UNAVAILABLE": "GPU_DEVICE_UNAVAILABLE", "DATA_CORRUPTION": "DATA_INTEGRITY_FAILURE", "INTERMITTENT_FAILURE": "INTERMITTENT_TRANSIENT_FAILURE", None: "NONE", } # workload_type / workload_id-derived scenario mode -> FailureClass, used # only as a fallback when diagnosis_hypothesis is None but the workload was # not a pure success workload (i.e. the episode's own scenario intent is # still the best available evidence of the intended failure family). WORKLOAD_TYPE_TO_FAILURE_CLASS = { "success": "NONE", "network": "NETWORK_FAILURE", "fail": "GENERIC_FAIL", "oom": "PROCESS_OOM", "timeout": "PROCESS_TIMEOUT_CPU", "resource_unavailable": "RESOURCE_UNAVAILABLE", "gpu": "GPU_DEVICE_UNAVAILABLE", "corruption": "DATA_INTEGRITY_FAILURE", "flaky": "INTERMITTENT_TRANSIENT_FAILURE", } def infer_failure_class(diagnosis_hypothesis, workload_type_or_id: str) -> tuple[str, bool]: """Returns (failure_class, was_unmapped_fallback_to_generic). Tries diagnosis_hypothesis first (it is the more specific, real-time signal); falls back to a substring match against workload_type/ workload_id; falls back to GENERIC_FAIL (flagged) if genuinely unknown. """ if diagnosis_hypothesis in DIAGNOSIS_TO_FAILURE_CLASS: return DIAGNOSIS_TO_FAILURE_CLASS[diagnosis_hypothesis], False wl = (workload_type_or_id or "").lower() for key, fc in WORKLOAD_TYPE_TO_FAILURE_CLASS.items(): if key in wl: return fc, False return "GENERIC_FAIL", True