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Use same nnue divisor for both nets

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Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/6643ceeabc537f56194506f6
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 224800 W: 57910 L: 57896 D: 108994
Ptnml(0-2): 673, 26790, 57519, 26686, 732

Passed non-regression LTC:
https://tests.stockfishchess.org/tests/view/6643ff15bc537f5619451719
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 347658 W: 87574 L: 87688 D: 172396
Ptnml(0-2): 207, 39004, 95488, 38956, 174

closes https://github.com/official-stockfish/Stockfish/pull/5250

Bench: 1804704
This commit is contained in:
Linmiao Xu 2024-05-14 16:51:02 -04:00 • committed by Disservin
parent dcb0233784
commit 541406ab91
1 changed files with 4 additions and 4 deletions
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8
src/evaluate.cpp
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@ -68,10 +68,10 @@ Value Eval::evaluate(const Eval::NNUE::Networks& networks,
smallNet = false;
}
const auto adjustEval = [&](int nnueDiv, int pawnCountMul, int shufflingConstant) {
const auto adjustEval = [&](int pawnCountMul, int shufflingConstant) {
// Blend optimism and eval with nnue complexity and material imbalance
optimism += optimism * (nnueComplexity + std::abs(simpleEval - nnue)) / 584;
nnue -= nnue * (nnueComplexity * 5 / 3) / nnueDiv;
nnue -= nnue * (nnueComplexity * 5 / 3) / 32395;
int npm = pos.non_pawn_material() / 64;
v = (nnue * (npm + 943 + pawnCountMul * pos.count<PAWN>()) + optimism * (npm + 140)) / 1058;
@ -82,9 +82,9 @@ Value Eval::evaluate(const Eval::NNUE::Networks& networks,
};
if (!smallNet)
adjustEval(32395, 11, 178);
adjustEval(11, 178);
else
adjustEval(32793, 9, 206);
adjustEval(9, 206);
// Guarantee evaluation does not hit the tablebase range
v = std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);