X-Git-Url: https://git.sesse.net/?a=blobdiff_plain;f=src%2Fevaluate.cpp;h=2d0df89c3e77f9d692e285cd5ec219b6619d6bf1;hb=b36d39de3d61b8f31c11d85233631aafaf760ee1;hp=3b6cbbcd8a644d47fb599107a44a565e7276533d;hpb=b60f9cc4515cdfb657a0166abb29a60257cc59e1;p=stockfish

diff --git a/src/evaluate.cpp b/src/evaluate.cpp
index 3b6cbbcd..2d0df89c 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<string> dirs = { "<internal>" , "" , CommandLine::binaryDirectory , stringify(DEFAULT_NNUE_DIRECTORY) };
     #else
     vector<string> dirs = { "<internal>" , "" , CommandLine::binaryDirectory };
     #endif
 
-    for (string directory : dirs)
+    for (const string& directory : dirs)
         if (currentEvalFileName != eval_file)
         {
             if (directory != "<internal>")
             {
                 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<Tracing T> template<Color Us, PieceType Pt>
   Score Evaluation<T>::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
@@ -1050,20 +1048,22 @@ make_v:
 
 Value Eval::evaluate(const Position& pos, int* complexity) {
 
+  assert(!pos.checkers());
+
   Value v;
   Value psq = pos.psq_eg_stm();
 
   // 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)
-  bool useClassical = !useNNUE || (pos.count<ALL_PIECES>() > 7 && abs(psq) > 1760);
+  // PSQ advantage is decisive. (~4 Elo at STC, 1 Elo at LTC)
+  bool useClassical = !useNNUE || abs(psq) > 2048;
 
   if (useClassical)
       v = Evaluation<NO_TRACE>(pos).value();
   else
   {
       int nnueComplexity;
-      int scale = 1076 + 96 * pos.non_pawn_material() / 5120;
+      int scale = 1001 + 5 * pos.count<PAWN>() + 61 * pos.non_pawn_material() / 4096;
 
       Color stm = pos.side_to_move();
       Value optimism = pos.this_thread()->optimism[stm];
@@ -1071,21 +1071,20 @@ Value Eval::evaluate(const Position& pos, int* complexity) {
       Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
 
       // Blend nnue complexity with (semi)classical complexity
-      nnueComplexity = (  412 * nnueComplexity
-                        + 428 * abs(psq - nnue)
-                        + (optimism  > 0 ? int(optimism) * int(psq - nnue) : 0)
+      nnueComplexity = (  406 * nnueComplexity
+                        + (424 + optimism) * abs(psq - nnue)
                         ) / 1024;
 
       // Return hybrid NNUE complexity to caller
       if (complexity)
           *complexity = nnueComplexity;
 
-      optimism = optimism * (278 + nnueComplexity) / 256;
-      v = (nnue * scale + optimism * (scale - 755)) / 1024;
+      optimism = optimism * (272 + nnueComplexity) / 256;
+      v = (nnue * scale + optimism * (scale - 748)) / 1024;
   }
 
   // Damp down the evaluation linearly when shuffling
-  v = v * (197 - pos.rule50_count()) / 214;
+  v = v * (200 - pos.rule50_count()) / 214;
 
   // 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);