return;
string eval_file = string(Options["EvalFile"]);
+ if (eval_file.empty())
+ eval_file = EvalFileDefaultName;
#if defined(DEFAULT_NNUE_DIRECTORY)
#define stringify2(x) #x
void NNUE::verify() {
string eval_file = string(Options["EvalFile"]);
+ if (eval_file.empty())
+ eval_file = EvalFileDefaultName;
if (useNNUE && eval_file_loaded != eval_file)
{
- UCI::OptionsMap defaults;
- UCI::init(defaults);
string msg1 = "If the UCI option \"Use NNUE\" is set to true, network evaluation parameters compatible with the engine must be available.";
string msg2 = "The option is set to true, but the network file " + eval_file + " was not loaded successfully.";
string msg3 = "The UCI option EvalFile might need to specify the full path, including the directory name, to the network file.";
- string msg4 = "The default net can be downloaded from: https://tests.stockfishchess.org/api/nn/" + string(defaults["EvalFile"]);
+ string msg4 = "The default net can be downloaded from: https://tests.stockfishchess.org/api/nn/" + std::string(EvalFileDefaultName);
string msg5 = "The engine will be terminated now.";
sync_cout << "info string ERROR: " << msg1 << sync_endl;
namespace {
// Threshold for lazy and space evaluation
- constexpr Value LazyThreshold1 = Value(1565);
- constexpr Value LazyThreshold2 = Value(1102);
- constexpr Value SpaceThreshold = Value(11551);
- constexpr Value NNUEThreshold1 = Value(800);
+ constexpr Value LazyThreshold1 = Value(3130);
+ constexpr Value LazyThreshold2 = Value(2204);
+ constexpr Value SpaceThreshold = Value(11551);
// KingAttackWeights[PieceType] contains king attack weights by piece type
constexpr int KingAttackWeights[PIECE_TYPE_NB] = { 0, 0, 81, 52, 44, 10 };
// Initialize score by reading the incrementally updated scores included in
// the position object (material + piece square tables) and the material
// imbalance. Score is computed internally from the white point of view.
- Score score = pos.psq_score() + me->imbalance() + pos.this_thread()->contempt;
+ Score score = pos.psq_score() + me->imbalance() + pos.this_thread()->trend;
// Probe the pawn hash table
pe = Pawns::probe(pos);
// Early exit if score is high
auto lazy_skip = [&](Value lazyThreshold) {
- return abs(mg_value(score) + eg_value(score)) / 2 > lazyThreshold + pos.non_pawn_material() / 64;
+ return abs(mg_value(score) + eg_value(score)) > lazyThreshold + pos.non_pawn_material() / 32;
};
if (lazy_skip(LazyThreshold1))
// Scale and shift NNUE for compatibility with search and classical evaluation
auto adjusted_NNUE = [&]()
{
- int scale = 903
+ int scale = 883
+ 32 * pos.count<PAWN>()
+ 32 * pos.non_pawn_material() / 1024;
return nnue;
};
- // If there is PSQ imbalance we use the classical eval.
+ // If there is PSQ imbalance we use the classical eval, but we switch to
+ // NNUE eval faster when shuffling or if the material on the board is high.
+ int r50 = pos.rule50_count();
Value psq = Value(abs(eg_value(pos.psq_score())));
- int r50 = 16 + pos.rule50_count();
- bool largePsq = psq * 16 > (NNUEThreshold1 + pos.non_pawn_material() / 64) * r50;
-
- v = largePsq ? Evaluation<NO_TRACE>(pos).value() // classical
- : adjusted_NNUE(); // NNUE
+ bool classical = psq * 5 > (850 + pos.non_pawn_material() / 64) * (5 + r50);
+ v = classical ? Evaluation<NO_TRACE>(pos).value() // classical
+ : adjusted_NNUE(); // NNUE
}
// Damp down the evaluation linearly when shuffling
std::memset(scores, 0, sizeof(scores));
- pos.this_thread()->contempt = SCORE_ZERO; // Reset any dynamic contempt
+ pos.this_thread()->trend = SCORE_ZERO; // Reset any dynamic contempt
v = Evaluation<TRACE>(pos).value();