X-Git-Url: https://git.sesse.net/?a=blobdiff_plain;f=src%2Fevaluate.cpp;h=12883fcc43e57a8a18f71e407f3604816a989321;hb=66bf45b99e2061c1ba74f9975bc5059ac0121dfd;hp=d5cda3d80e86ef9a9f779abc1aa6b39c2bb7108e;hpb=fc5b59b88bae00b7e74bbad0de7c3c33136937cf;p=stockfish diff --git a/src/evaluate.cpp b/src/evaluate.cpp index d5cda3d8..12883fcc 100644 --- a/src/evaluate.cpp +++ b/src/evaluate.cpp @@ -36,7 +36,7 @@ #include "timeman.h" #include "uci.h" #include "incbin/incbin.h" - +#include "nnue/evaluate_nnue.h" // Macro to embed the default efficiently updatable neural network (NNUE) file // data in the engine binary (using incbin.h, by Dale Weiler). @@ -82,20 +82,18 @@ namespace Eval { eval_file = EvalFileDefaultName; #if defined(DEFAULT_NNUE_DIRECTORY) - #define stringify2(x) #x - #define stringify(x) stringify2(x) vector dirs = { "" , "" , CommandLine::binaryDirectory , stringify(DEFAULT_NNUE_DIRECTORY) }; #else vector dirs = { "" , "" , CommandLine::binaryDirectory }; #endif - for (string directory : dirs) + for (const string& directory : dirs) if (currentEvalFileName != eval_file) { if (directory != "") { ifstream stream(directory + eval_file, ios::binary); - if (load_eval(eval_file, stream)) + if (NNUE::load_eval(eval_file, stream)) currentEvalFileName = eval_file; } @@ -111,7 +109,7 @@ namespace Eval { (void) gEmbeddedNNUEEnd; // Silence warning on unused variable istream stream(&buffer); - if (load_eval(eval_file, stream)) + if (NNUE::load_eval(eval_file, stream)) currentEvalFileName = eval_file; } } @@ -159,24 +157,24 @@ namespace Trace { Score scores[TERM_NB][COLOR_NB]; - double to_cp(Value v) { return double(v) / UCI::NormalizeToPawnValue; } + static double to_cp(Value v) { return double(v) / UCI::NormalizeToPawnValue; } - void add(int idx, Color c, Score s) { + static void add(int idx, Color c, Score s) { scores[idx][c] = s; } - void add(int idx, Score w, Score b = SCORE_ZERO) { + static void add(int idx, Score w, Score b = SCORE_ZERO) { scores[idx][WHITE] = w; scores[idx][BLACK] = b; } - std::ostream& operator<<(std::ostream& os, Score s) { + static std::ostream& operator<<(std::ostream& os, Score s) { os << std::setw(5) << to_cp(mg_value(s)) << " " << std::setw(5) << to_cp(eg_value(s)); return os; } - std::ostream& operator<<(std::ostream& os, Term t) { + static std::ostream& operator<<(std::ostream& os, Term t) { if (t == MATERIAL || t == IMBALANCE || t == WINNABLE || t == TOTAL) os << " ---- ----" << " | " << " ---- ----"; @@ -193,8 +191,8 @@ using namespace Trace; namespace { // Threshold for lazy and space evaluation - constexpr Value LazyThreshold1 = Value(3631); - constexpr Value LazyThreshold2 = Value(2084); + constexpr Value LazyThreshold1 = Value(3622); + constexpr Value LazyThreshold2 = Value(1962); constexpr Value SpaceThreshold = Value(11551); // KingAttackWeights[PieceType] contains king attack weights by piece type @@ -388,10 +386,10 @@ namespace { template template Score Evaluation::pieces() { - constexpr Color Them = ~Us; - constexpr Direction Down = -pawn_push(Us); - constexpr Bitboard OutpostRanks = (Us == WHITE ? Rank4BB | Rank5BB | Rank6BB - : Rank5BB | Rank4BB | Rank3BB); + constexpr Color Them = ~Us; + [[maybe_unused]] constexpr Direction Down = -pawn_push(Us); + [[maybe_unused]] constexpr Bitboard OutpostRanks = (Us == WHITE ? Rank4BB | Rank5BB | Rank6BB + : Rank5BB | Rank4BB | Rank3BB); Bitboard b1 = pos.pieces(Us, Pt); Bitboard b, bb; Score score = SCORE_ZERO; @@ -430,7 +428,7 @@ namespace { int mob = popcount(b & mobilityArea[Us]); mobility[Us] += MobilityBonus[Pt - 2][mob]; - if (Pt == BISHOP || Pt == KNIGHT) + if constexpr (Pt == BISHOP || Pt == KNIGHT) { // Bonus if the piece is on an outpost square or can reach one // Bonus for knights (UncontestedOutpost) if few relevant targets @@ -1063,7 +1061,7 @@ Value Eval::evaluate(const Position& pos, int* complexity) { else { int nnueComplexity; - int scale = 1076 + 96 * pos.non_pawn_material() / 5120; + int scale = 1001 + 5 * pos.count() + 61 * pos.non_pawn_material() / 4096; Color stm = pos.side_to_move(); Value optimism = pos.this_thread()->optimism[stm]; @@ -1072,8 +1070,7 @@ Value Eval::evaluate(const Position& pos, int* complexity) { // Blend nnue complexity with (semi)classical complexity nnueComplexity = ( 406 * nnueComplexity - + 424 * abs(psq - nnue) - + (optimism > 0 ? int(optimism) * int(psq - nnue) : 0) + + (424 + optimism) * abs(psq - nnue) ) / 1024; // Return hybrid NNUE complexity to caller