// Early exit if score is high
auto lazy_skip = [&](Value lazyThreshold) {
- return abs(mg_value(score) + eg_value(score)) > lazyThreshold + pos.non_pawn_material() / 32;
+ return abs(mg_value(score) + eg_value(score)) > lazyThreshold
+ + std::abs(pos.this_thread()->bestValue) * 5 / 4
+ + pos.non_pawn_material() / 32;
};
if (lazy_skip(LazyThreshold1))
Value v;
- if (!useNNUE)
- v = Evaluation<NO_TRACE>(pos).value();
+ // Deciding between classical and NNUE eval: for high PSQ imbalance we use classical,
+ // but we switch to NNUE during long shuffling or with high material on the board.
+
+ if ( !useNNUE
+ || abs(eg_value(pos.psq_score())) * 5 > (850 + pos.non_pawn_material() / 64) * (5 + pos.rule50_count()))
+ v = Evaluation<NO_TRACE>(pos).value(); // classical
else
{
- // Scale and shift NNUE for compatibility with search and classical evaluation
- auto adjusted_NNUE = [&]()
- {
- int scale = 883
- + 32 * pos.count<PAWN>()
- + 32 * pos.non_pawn_material() / 1024;
-
- Value nnue = NNUE::evaluate(pos, true) * scale / 1024;
-
- if (pos.is_chess960())
- nnue += fix_FRC(pos);
+ int scale = 1049
+ + 8 * pos.count<PAWN>()
+ + 20 * pos.non_pawn_material() / 1024;
- return nnue;
- };
+ Value nnue = NNUE::evaluate(pos, true); // NNUE
+ Color stm = pos.side_to_move();
+ Value optimism = pos.this_thread()->optimism[stm];
- // If there is PSQ imbalance we use the classical eval, but we switch to
- // NNUE eval faster when shuffling or if the material on the board is high.
- int r50 = pos.rule50_count();
- Value psq = Value(abs(eg_value(pos.psq_score())));
- bool classical = psq * 5 > (850 + pos.non_pawn_material() / 64) * (5 + r50);
+ v = (nnue + optimism) * scale / 1024 - optimism;
- v = classical ? Evaluation<NO_TRACE>(pos).value() // classical
- : adjusted_NNUE(); // NNUE
+ if (pos.is_chess960())
+ v += fix_FRC(pos);
}
// Damp down the evaluation linearly when shuffling
- v = v * (100 - pos.rule50_count()) / 100;
+ v = v * (207 - pos.rule50_count()) / 207;
// 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);
std::memset(scores, 0, sizeof(scores));
- pos.this_thread()->trend = SCORE_ZERO; // Reset any dynamic contempt
+ // Reset any global variable used in eval
+ pos.this_thread()->trend = SCORE_ZERO;
+ pos.this_thread()->bestValue = VALUE_ZERO;
+ pos.this_thread()->optimism[WHITE] = VALUE_ZERO;
+ pos.this_thread()->optimism[BLACK] = VALUE_ZERO;
v = Evaluation<TRACE>(pos).value();