along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
+#include "evaluate.h"
+
#include <algorithm>
#include <cassert>
+#include <cstdlib>
#include <fstream>
#include <iomanip>
-#include <sstream>
#include <iostream>
-#include <streambuf>
+#include <sstream>
#include <vector>
-#include "bitboard.h"
-#include "evaluate.h"
+#include "incbin/incbin.h"
#include "misc.h"
+#include "nnue/evaluate_nnue.h"
+#include "position.h"
#include "thread.h"
-#include "timeman.h"
+#include "types.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).
#endif
-using namespace std;
-
namespace Stockfish {
namespace Eval {
- string currentEvalFileName = "None";
-
- static double to_cp(Value v) { return double(v) / UCI::NormalizeToPawnValue; }
+ std::string currentEvalFileName = "None";
/// NNUE::init() tries to load a NNUE network at startup time, or when the engine
/// receives a UCI command "setoption name EvalFile value nn-[a-z0-9]{12}.nnue"
void NNUE::init() {
- string eval_file = string(Options["EvalFile"]);
+ std::string eval_file = std::string(Options["EvalFile"]);
if (eval_file.empty())
eval_file = EvalFileDefaultName;
#if defined(DEFAULT_NNUE_DIRECTORY)
- vector<string> dirs = { "<internal>" , "" , CommandLine::binaryDirectory , stringify(DEFAULT_NNUE_DIRECTORY) };
+ std::vector<std::string> dirs = { "<internal>" , "" , CommandLine::binaryDirectory , stringify(DEFAULT_NNUE_DIRECTORY) };
#else
- vector<string> dirs = { "<internal>" , "" , CommandLine::binaryDirectory };
+ std::vector<std::string> dirs = { "<internal>" , "" , CommandLine::binaryDirectory };
#endif
- for (const string& directory : dirs)
+ for (const std::string& directory : dirs)
if (currentEvalFileName != eval_file)
{
if (directory != "<internal>")
{
- ifstream stream(directory + eval_file, ios::binary);
+ std::ifstream stream(directory + eval_file, std::ios::binary);
if (NNUE::load_eval(eval_file, stream))
currentEvalFileName = eval_file;
}
if (directory == "<internal>" && eval_file == EvalFileDefaultName)
{
// C++ way to prepare a buffer for a memory stream
- class MemoryBuffer : public basic_streambuf<char> {
+ class MemoryBuffer : public std::basic_streambuf<char> {
public: MemoryBuffer(char* p, size_t n) { setg(p, p, p + n); setp(p, p + n); }
};
size_t(gEmbeddedNNUESize));
(void) gEmbeddedNNUEEnd; // Silence warning on unused variable
- istream stream(&buffer);
+ std::istream stream(&buffer);
if (NNUE::load_eval(eval_file, stream))
currentEvalFileName = eval_file;
}
/// NNUE::verify() verifies that the last net used was loaded successfully
void NNUE::verify() {
- string eval_file = string(Options["EvalFile"]);
+ std::string eval_file = std::string(Options["EvalFile"]);
if (eval_file.empty())
eval_file = EvalFileDefaultName;
if (currentEvalFileName != eval_file)
{
- string msg1 = "Network evaluation parameters compatible with the engine must be available.";
- string msg2 = "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/" + std::string(EvalFileDefaultName);
- string msg5 = "The engine will be terminated now.";
+ std::string msg1 = "Network evaluation parameters compatible with the engine must be available.";
+ std::string msg2 = "The network file " + eval_file + " was not loaded successfully.";
+ std::string msg3 = "The UCI option EvalFile might need to specify the full path, including the directory name, to the network file.";
+ std::string msg4 = "The default net can be downloaded from: https://tests.stockfishchess.org/api/nn/" + std::string(EvalFileDefaultName);
+ std::string msg5 = "The engine will be terminated now.";
sync_cout << "info string ERROR: " << msg1 << sync_endl;
sync_cout << "info string ERROR: " << msg2 << sync_endl;
}
}
-/// evaluate() is the evaluator for the outer world. It returns a static
-/// evaluation of the position from the point of view of the side to move.
-Value Eval::evaluate(const Position& pos) {
+/// simple_eval() returns a static, purely materialistic evaluation of the position
+/// from the point of view of the given color. It can be divided by PawnValue to get
+/// an approximation of the material advantage on the board in terms of pawns.
- assert(!pos.checkers());
-
- Value v;
- Value psq = pos.psq_eg_stm();
+Value Eval::simple_eval(const Position& pos, Color c) {
+ return PawnValue * (pos.count<PAWN>(c) - pos.count<PAWN>(~c))
+ + (pos.non_pawn_material(c) - pos.non_pawn_material(~c));
+}
- int nnueComplexity;
- int npm = pos.non_pawn_material() / 64;
- Color stm = pos.side_to_move();
- Value optimism = pos.this_thread()->optimism[stm];
+/// evaluate() is the evaluator for the outer world. It returns a static evaluation
+/// of the position from the point of view of the side to move.
- Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
+Value Eval::evaluate(const Position& pos) {
- // Blend optimism with nnue complexity and (semi)classical complexity
- optimism += optimism * (nnueComplexity + abs(psq - nnue)) / 512;
+ assert(!pos.checkers());
- v = ( nnue * (915 + npm + 9 * pos.count<PAWN>())
- + optimism * (154 + npm + pos.count<PAWN>())) / 1024;
+ Value v;
+ Color stm = pos.side_to_move();
+ int shuffling = pos.rule50_count();
+ int simpleEval = simple_eval(pos, stm) + (int(pos.key() & 7) - 3);
+
+ bool lazy = abs(simpleEval) >= RookValue + KnightValue
+ + 16 * shuffling * shuffling
+ + abs(pos.this_thread()->bestValue)
+ + abs(pos.this_thread()->rootSimpleEval);
+
+ if (lazy)
+ v = Value(simpleEval);
+ else
+ {
+ int nnueComplexity;
+ Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
+
+ Value optimism = pos.this_thread()->optimism[stm];
+
+ // Blend optimism and eval with nnue complexity and material imbalance
+ optimism += optimism * (nnueComplexity + abs(simpleEval - nnue)) / 512;
+ nnue -= nnue * (nnueComplexity + abs(simpleEval - nnue)) / 32768;
+
+ int npm = pos.non_pawn_material() / 64;
+ v = ( nnue * (915 + npm + 9 * pos.count<PAWN>())
+ + optimism * (154 + npm )) / 1024;
+ }
// Damp down the evaluation linearly when shuffling
- v = v * (200 - pos.rule50_count()) / 214;
+ v = v * (200 - shuffling) / 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);
// Reset any global variable used in eval
pos.this_thread()->bestValue = VALUE_ZERO;
+ pos.this_thread()->rootSimpleEval = VALUE_ZERO;
pos.this_thread()->optimism[WHITE] = VALUE_ZERO;
pos.this_thread()->optimism[BLACK] = VALUE_ZERO;
Value v;
v = NNUE::evaluate(pos, false);
v = pos.side_to_move() == WHITE ? v : -v;
- ss << "NNUE evaluation " << to_cp(v) << " (white side)\n";
+ ss << "NNUE evaluation " << 0.01 * UCI::to_cp(v) << " (white side)\n";
v = evaluate(pos);
v = pos.side_to_move() == WHITE ? v : -v;
- ss << "Final evaluation " << to_cp(v) << " (white side)";
+ ss << "Final evaluation " << 0.01 * UCI::to_cp(v) << " (white side)";
ss << " [with scaled NNUE, ...]";
ss << "\n";
projects / stockfish / blobdiff