Wire NNUE eval into search, build the training pipeline, and add a fast

2026-10-20T16:26:44Z

move/eval-agreement benchmark against Stockfish (tests/lop) Implements the architecture decisions in src/docs/NNUE.md: HalfKAv2_hm feature set, int16/int8 quantization, per-ply accumulator backup for king moves, and a lazy-eval-ready integration into search.c/eval.c. Adds the full annotate_pgns/ training pipeline (extraction, K-fit/ labeling, quiet filtering, tensor building, training, export) plus an end-to-end orchestrator (run_nnue_pipeline.py) and validation tooling (sanity_check_net.py, compare_vs_stockfish_net.py). Adds tests/lop: a 10k-position list-of-positions benchmark comparing engine eval rank and move choice against pre-computed Stockfish/lc0 references, much cheaper than a full self-play match for day-to-day progress checks. First sd10-matched self-play result against classic HCE: LLR +2.28 (H1=+2.94), -72=119+169 over 360 games, confirming the net is "smarter per node" at matched depth. A real-time (--st 4) match is currently weaker (candidate loses ~3 plies of depth to a ~3.3-3.7x nps gap against an unrecalibrated search), consistent with NNUE.md's adoption-criterion section -- pruning/reduction constants still need retuning for the new eval's score scale before a fair real-time comparison is possible. Co-Authored-By: Claude Sonnet 5

Redesign lazy/super-lazy eval margins with position-specific percentile

2026-09-18T16:43:17Z

tables, and fix four real search/recognizer bugs found while validating it Main theme: replace the flat, heavily-padded LAZY_EVAL_BASE_MARGIN / SUPER_LAZY_MARGIN_BY_ARMY constants with per-material-bucket percentile tables (king safety by attacker army, residual by own army, separate tables for the lazy vs super-lazy baselines) derived from a 30k-position calibration pool, targeting a measured ~1-1.5% exceeded-margin rate instead of an unmeasured "add lots of headroom" floor. QSearch's FUTILITY_BASE_MARGIN_LAZY/SUPERLAZY were re-derived to match the new, now-meaningful (p50-based) iPositional this produces. Self-play confirms the working tree beats both HEAD, a more liberal (~5% miss target) variant, and a more conservative (near-zero miss) variant of the same margin mechanism. Along the way, an initial self-play regression (this margin work bundled with several changes in one pass, one of which broke things) led to a day of ZFS-snapshot bisection and then targeted DEBUG-build fuzzing against a stratified 200k-position corpus (tests/cross_sectional_200k.ep_, new), which is what actually found and fixed four distinct, real, pre-existing engine bugs -- none of them related to the margin redesign itself: - searchsup.c (CommonSearchInit): three early-return paths (timer abort, draw, too-deep bailout) left a node's own PV[] row stale instead of clearing it, letting an ancestor's UpdatePV splice a leftover move from a completely unrelated node into the displayed PV -- root cause of a WalkPV/MakeMove assert ("moving a piece to capture, but nothing was on the target square"). - dynamic.c (RecordEnprisePieceAtPly): the two-slot en-prise dedup compared (square, piece) instead of square alone, so a same-square re-record with a different piece (legitimate -- a fail-high capture's victim is restored by UnmakeMove and can differ across calls at the same ply) shifted a duplicate square into both slots, tripping ValueOfMaterialInTroubleDespiteMove's two-distinct-squares assert. - recogn.c (_RecognizeKBKP): the wrong-colored-bishop corner-fortress draw shortcut fired even when the weak side has its own pawn(s), which can hand the strong side real zugzwang resources the fortress logic doesn't account for -- produced a false hard draw bound where EGTB shows a near-forced loss. - eval.c (_EvalPasserRacesAgainstLoneKings): a rook pawn's race was credited as winning even when the strong side's own king sits exactly on its own pawn's queening square (distance 0 specifically -- adjacent is fine, the square is empty) -- a classic stalemate resource the race heuristic can't see. Only reachable through _RecognizeKPK's pawn-hash-cache-hit path, which is why testrecogn.c's TestRecognExhaustiveKPK reported "0 wrong" the whole time; extended it to cover both color assignments and the full board (no mirror-shortcut) and documented the remaining cache-hit coverage gap for a future session to close. Also: match_play.py gains a local_ebf metric (geometric-mean of depth-normalized node-growth ratios between consecutive completed iterations) alongside the existing cumulative nodes**(1/depth) ebf, which turned out to be misleading when comparing engines with different lazy-exit aggressiveness -- and probe.c/hash.c pick up two small, independently-found correctness fixes (TB root-probe promotion piece missing its color bit; ASSERT(g_pHashTable) crashing on the legitimate "--hash none" config) noticed along the way. Co-Authored-By: Claude Sonnet 5

typhoon.git/tests/walkpv_bug_repro.txt, branch master

Wire NNUE eval into search, build the training pipeline, and add a fast

Redesign lazy/super-lazy eval margins with position-specific percentile