X-Git-Url: https://git.sesse.net/?a=blobdiff_plain;f=src%2Fevaluate.cpp;h=ab71fa67df0cc40161ad0fca2259eb3e82b76058;hb=ad926d34c0105d523bfa5cb92cbcf9f337d54c08;hp=2f1d5067d013ce2d0ffee3785aefe78910d689c1;hpb=f7494961de13c3341a1ca2d05ea5f3d28fa35d31;p=stockfish

diff --git a/src/evaluate.cpp b/src/evaluate.cpp
index 2f1d5067..ab71fa67 100644
--- a/src/evaluate.cpp
+++ b/src/evaluate.cpp
@@ -1,6 +1,6 @@
 /*
   Stockfish, a UCI chess playing engine derived from Glaurung 2.1
-  Copyright (C) 2004-2021 The Stockfish developers (see AUTHORS file)
+  Copyright (C) 2004-2022 The Stockfish developers (see AUTHORS file)
 
   Stockfish is free software: you can redistribute it and/or modify
   it under the terms of the GNU General Public License as published by
@@ -988,7 +988,9 @@ namespace {
 
     // 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))
@@ -1080,27 +1082,36 @@ make_v:
 Value Eval::evaluate(const Position& pos) {
 
   Value v;
+  bool useClassical = false;
 
-  // Deciding between classical and NNUE eval: for high PSQ imbalance we use classical,
+  // Deciding between classical and NNUE eval (~10 Elo): 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
+      useClassical = abs(v) >= 300;
+  }
+
+  // If result of a classical evaluation is much lower than threshold fall back to NNUE
+  if (useNNUE && !useClassical)
   {
-      int scale =   883
-                  + 32 * pos.count<PAWN>()
-                  + 32 * pos.non_pawn_material() / 1024;
+       Value nnue     = NNUE::evaluate(pos, true);     // NNUE
+       int scale      = 1136 + 20 * pos.non_pawn_material() / 1024;
+       Color stm      = pos.side_to_move();
+       Value optimism = pos.this_thread()->optimism[stm];
+       Value psq      = (stm == WHITE ? 1 : -1) * eg_value(pos.psq_score());
+       int complexity = abs(nnue - psq) / 256;
 
-       v = NNUE::evaluate(pos, true) * scale / 1024;  // NNUE
+       optimism *= (1 + complexity);
+       v = (nnue + optimism) * scale / 1024 - optimism;
 
        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);
@@ -1125,7 +1136,11 @@ std::string Eval::trace(Position& pos) {
 
   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();