Per fox's 2026-05-08 review of fbd99a8: implement adaptation_efficiency
and feedback_efficiency in run_finetuning + run_feedback_loop with
explicit sentinels — not Python floating-point accidents.
_efficiency(gain, cost) helper:
- cost > 0: standard ratio
- cost == 0, gain > 0: EFFICIENCY_INFINITE (free improvement)
- cost == 0, gain == 0: EFFICIENCY_UNDEFINED (= 0.0; no signal)
- cost == 0, gain < 0: -EFFICIENCY_INFINITE (free regression)
Battery-level metrics report mean_finite (computed over finite
values only) + infinite_count + neg_infinite_count so the mean
stays dimensionally truthful and consumers can pivot on the special
buckets separately.
Phase 1a cost proxies:
- run_finetuning: _capital_cost_delta sums resource_budget
(max_compute_ms_delta * 1e-3 + max_storage_delta_bytes / 1e6).
Phase 1b.2 will replace with real capital_ledger reads.
- run_feedback_loop: chain length = cost. Phase 1b.2 capital_ledger
integration replaces it.
Tests added (7):
- _efficiency over four boundary cases
- 5F finetuning + feedback_loop emit the new metrics keys
- Synthetic zero-cost finetuning fixture verifies +inf path
Full suite: 1110 passed, 36 skipped.
Closes the one actionable from the fbd99a8 review.
russell@unturf.com
3bff55234f