Use NNUE complexity in search, retune related parameters

[stockfish] / src / nnue / evaluate_nnue.cpp

diff --git a/src/nnue/evaluate_nnue.cpp b/src/nnue/evaluate_nnue.cpp
index a534753add5380a8e2aeb2fc01a706e495b243ee..ba2ed36746c00cb2bf4da9c1fd2457c4309350cd 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) 2004-2021 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
@@ -109,7 +109,7 @@ namespace Stockfish::Eval::NNUE {
   {
     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();
   }
@@ -137,37 +137,36 @@ 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[
       FeatureTransformer::BufferSize + alignment / sizeof(TransformedFeatureType)];
-    char bufferUnaligned[Network::BufferSize + alignment];
 
     auto* transformedFeatures = align_ptr_up<alignment>(&transformedFeaturesUnaligned[0]);
-    auto* buffer = align_ptr_up<alignment>(&bufferUnaligned[0]);
 #else
     alignas(alignment)
       TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize];
-    alignas(alignment) char buffer[Network::BufferSize];
 #endif
 
     ASSERT_ALIGNED(transformedFeatures, alignment);
-    ASSERT_ALIGNED(buffer, 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, buffer)[0];
+    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);
   }
@@ -190,27 +189,20 @@ namespace Stockfish::Eval::NNUE {
 #if defined(ALIGNAS_ON_STACK_VARIABLES_BROKEN)
     TransformedFeatureType transformedFeaturesUnaligned[
       FeatureTransformer::BufferSize + alignment / sizeof(TransformedFeatureType)];
-    char bufferUnaligned[Network::BufferSize + alignment];
 
     auto* transformedFeatures = align_ptr_up<alignment>(&transformedFeaturesUnaligned[0]);
-    auto* buffer = align_ptr_up<alignment>(&bufferUnaligned[0]);
 #else
     alignas(alignment)
       TransformedFeatureType transformedFeatures[FeatureTransformer::BufferSize];
-    alignas(alignment) char buffer[Network::BufferSize];
 #endif
 
     ASSERT_ALIGNED(transformedFeatures, alignment);
-    ASSERT_ALIGNED(buffer, alignment);
 
     NnueEvalTrace t{};
     t.correctBucket = (pos.count<ALL_PIECES>() - 1) / 4;
-    for (std::size_t bucket = 0; bucket < LayerStacks; ++bucket) {
-      const auto psqt = featureTransformer->transform(pos, transformedFeatures, bucket);
-      const auto output = network[bucket]->propagate(transformedFeatures, buffer);
-
-      int materialist = psqt;
-      int positional  = output[0];
+    for (IndexType bucket = 0; bucket < LayerStacks; ++bucket) {
+      const auto materialist = featureTransformer->transform(pos, transformedFeatures, bucket);
+      const auto positional = network[bucket]->propagate(transformedFeatures);
 
       t.psqt[bucket] = static_cast<Value>( materialist / OutputScale );
       t.positional[bucket] = static_cast<Value>( positional / OutputScale );