Warn if a global function has no previous declaration

[stockfish] / src / nnue / evaluate_nnue.cpp

diff --git a/src/nnue/evaluate_nnue.cpp b/src/nnue/evaluate_nnue.cpp
index 0fd58462b78b9dc2bafe273e9bb5ac2498626511..a06c1978517b34bede52f8fd873ee85913505b43 100644 (file)
--- a/src/nnue/evaluate_nnue.cpp
+++ b/src/nnue/evaluate_nnue.cpp
@@ -1,6 +1,6 @@
 /*
   Stockfish, a UCI chess playing engine derived from Glaurung 2.1
-  Copyright (C) 2004-2022 The Stockfish developers (see AUTHORS file)
+  Copyright (C) 2004-2023 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
@@ -83,7 +83,7 @@ namespace Stockfish::Eval::NNUE {
   }  // namespace Detail
 
   // Initialize the evaluation function parameters
-  void initialize() {
+  static void initialize() {
 
     Detail::initialize(featureTransformer);
     for (std::size_t i = 0; i < LayerStacks; ++i)
@@ -91,7 +91,7 @@ namespace Stockfish::Eval::NNUE {
   }
 
   // Read network header
-  bool read_header(std::istream& stream, std::uint32_t* hashValue, std::string* desc)
+  static bool read_header(std::istream& stream, std::uint32_t* hashValue, std::string* desc)
   {
     std::uint32_t version, size;
 
@@ -105,17 +105,17 @@ namespace Stockfish::Eval::NNUE {
   }
 
   // Write network header
-  bool write_header(std::ostream& stream, std::uint32_t hashValue, const std::string& desc)
+  static bool write_header(std::ostream& stream, std::uint32_t hashValue, const std::string& desc)
   {
     write_little_endian<std::uint32_t>(stream, Version);
     write_little_endian<std::uint32_t>(stream, hashValue);
-    write_little_endian<std::uint32_t>(stream, desc.size());
+    write_little_endian<std::uint32_t>(stream, (std::uint32_t)desc.size());
     stream.write(&desc[0], desc.size());
     return !stream.fail();
   }
 
   // Read network parameters
-  bool read_parameters(std::istream& stream) {
+  static bool read_parameters(std::istream& stream) {
 
     std::uint32_t hashValue;
     if (!read_header(stream, &hashValue, &netDescription)) return false;
@@ -127,7 +127,7 @@ namespace Stockfish::Eval::NNUE {
   }
 
   // Write network parameters
-  bool write_parameters(std::ostream& stream) {
+  static bool write_parameters(std::ostream& stream) {
 
     if (!write_header(stream, HashValue, netDescription)) return false;
     if (!Detail::write_parameters(stream, *featureTransformer)) return false;
@@ -137,13 +137,13 @@ namespace Stockfish::Eval::NNUE {
   }
 
   // Evaluation function. Perform differential calculation.
-  Value evaluate(const Position& pos, bool adjusted) {
+  Value evaluate(const Position& pos, bool adjusted, int* complexity) {
 
     // We manually align the arrays on the stack because with gcc < 9.3
     // overaligning stack variables with alignas() doesn't work correctly.
 
     constexpr uint64_t alignment = CacheLineSize;
-    int delta = 7;
+    int delta = 24 - pos.non_pawn_material() / 9560;
 
 #if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN)
     TransformedFeatureType transformedFeaturesUnaligned[
@@ -157,13 +157,16 @@ namespace Stockfish::Eval::NNUE {
 
     ASSERT_ALIGNED(transformedFeatures, alignment);
 
-    const std::size_t bucket = (pos.count<ALL_PIECES>() - 1) / 4;
+    const int bucket = (pos.count<ALL_PIECES>() - 1) / 4;
     const auto psqt = featureTransformer->transform(pos, transformedFeatures, bucket);
     const auto positional = network[bucket]->propagate(transformedFeatures);
 
+    if (complexity)
+        *complexity = abs(psqt - positional) / OutputScale;
+
     // Give more value to positional evaluation when adjusted flag is set
     if (adjusted)
-        return static_cast<Value>(((128 - delta) * psqt + (128 + delta) * positional) / 128 / OutputScale);
+        return static_cast<Value>(((1024 - delta) * psqt + (1024 + delta) * positional) / (1024 * OutputScale));
     else
         return static_cast<Value>((psqt + positional) / OutputScale);
   }
@@ -197,7 +200,7 @@ namespace Stockfish::Eval::NNUE {
 
     NnueEvalTrace t{};
     t.correctBucket = (pos.count<ALL_PIECES>() - 1) / 4;
-    for (std::size_t bucket = 0; bucket < LayerStacks; ++bucket) {
+    for (IndexType bucket = 0; bucket < LayerStacks; ++bucket) {
       const auto materialist = featureTransformer->transform(pos, transformedFeatures, bucket);
       const auto positional = network[bucket]->propagate(transformedFeatures);
 
@@ -217,7 +220,7 @@ namespace Stockfish::Eval::NNUE {
 
     buffer[0] = (v < 0 ? '-' : v > 0 ? '+' : ' ');
 
-    int cp = std::abs(100 * v / PawnValueEg);
+    int cp = std::abs(100 * v / UCI::NormalizeToPawnValue);
     if (cp >= 10000)
     {
         buffer[1] = '0' + cp / 10000; cp %= 10000;
@@ -248,7 +251,7 @@ namespace Stockfish::Eval::NNUE {
 
     buffer[0] = (v < 0 ? '-' : v > 0 ? '+' : ' ');
 
-    double cp = 1.0 * std::abs(int(v)) / PawnValueEg;
+    double cp = 1.0 * std::abs(int(v)) / UCI::NormalizeToPawnValue;
     sprintf(&buffer[1], "%6.2f", cp);
   }