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Reintroduce nnue eval pawn count multipliers again
With separate multipliers for nnue eval and optimism scaling. This patch used 4 out of 7 params tuned with spsa at 30+0.3 using this tuning config: Value LazyThreshold1 = Value(3622); Value LazyThreshold2 = Value(1962); int psqThresh = 2048; int nnueNpmBase = 945; int nnuePcMult = 0; int optNpmBase = 150; int optPcMult = 0; TUNE(SetRange(3322, 3922), LazyThreshold1); TUNE(SetRange(1662, 2262), LazyThreshold2); TUNE(SetRange(1748, 2348), psqThresh); TUNE(SetRange(745, 1145), nnueNpmBase); TUNE(SetRange(-16, 16), nnuePcMult); TUNE(SetRange(0, 300), optNpmBase); TUNE(SetRange(-16, 16), optPcMult); Passed STC: https://tests.stockfishchess.org/tests/view/64a5a9b402cd07745c60ed07 LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 173632 W: 44417 L: 43903 D: 85312 Ptnml(0-2): 547, 20025, 45068, 20719, 457 Passed LTC: https://tests.stockfishchess.org/tests/view/64a972a302cd07745c6136af LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 277644 W: 70955 L: 70147 D: 136542 Ptnml(0-2): 193, 29902, 77787, 30784, 156 closes https://github.com/official-stockfish/Stockfish/pull/4681 bench 1556301
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@ -157,7 +157,9 @@ Value Eval::evaluate(const Position& pos) {
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// Blend optimism with nnue complexity and (semi)classical complexity
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optimism += optimism * (nnueComplexity + abs(psq - nnue)) / 512;
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v = (nnue * (945 + npm) + optimism * (150 + npm)) / 1024;
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v = ( nnue * (915 + npm + 9 * pos.count<PAWN>())
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+ optimism * (154 + npm + pos.count<PAWN>())) / 1024;
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// Damp down the evaluation linearly when shuffling
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v = v * (200 - pos.rule50_count()) / 214;
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