// Initialize score by reading the incrementally updated scores included in
// the position object (material + piece square tables) and the material
// imbalance. Score is computed internally from the white point of view.
- Score score = pos.psq_score() + me->imbalance() + pos.this_thread()->trend;
+ Score score = pos.psq_score() + me->imbalance();
// Probe the pawn hash table
pe = Pawns::probe(pos);
Value Eval::evaluate(const Position& pos, int* complexity) {
Value v;
- Color stm = pos.side_to_move();
Value psq = pos.psq_eg_stm();
- // We use the much less accurate but faster Classical eval when the NNUE
+ // We use the much less accurate but faster Classical eval when the NNUE
// option is set to false. Otherwise we use the NNUE eval unless the
- // PSQ advantage is decisive and several pieces remain (~3 Elo)
+ // PSQ advantage is decisive and several pieces remain. (~3 Elo)
bool useClassical = !useNNUE || (pos.count<ALL_PIECES>() > 7 && abs(psq) > 1760);
+
if (useClassical)
v = Evaluation<NO_TRACE>(pos).value();
else
{
int nnueComplexity;
int scale = 1064 + 106 * pos.non_pawn_material() / 5120;
+
+ Color stm = pos.side_to_move();
Value optimism = pos.this_thread()->optimism[stm];
Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
+
// Blend nnue complexity with (semi)classical complexity
- nnueComplexity = (104 * nnueComplexity + 131 * abs(nnue - psq)) / 256;
- if (complexity) // Return hybrid NNUE complexity to caller
+ nnueComplexity = ( 416 * nnueComplexity
+ + 424 * abs(psq - nnue)
+ + (optimism > 0 ? int(optimism) * int(psq - nnue) : 0)
+ ) / 1024;
+
+ // Return hybrid NNUE complexity to caller
+ if (complexity)
*complexity = nnueComplexity;
optimism = optimism * (269 + nnueComplexity) / 256;
std::memset(scores, 0, sizeof(scores));
// 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;