X-Git-Url: https://git.sesse.net/?p=stockfish;a=blobdiff_plain;f=src%2Fevaluate.cpp;h=a5c049a88adb8446cb14720a51b3ab109effa45d;hp=54216b97206b24cab5b90ba18601a3e9d5801df9;hb=HEAD;hpb=4c4cb185aaaa0b3175ca35ab6473f17e9ec64055
diff --git a/src/evaluate.cpp b/src/evaluate.cpp
index 54216b97..586cadc0 100644
--- a/src/evaluate.cpp
+++ b/src/evaluate.cpp
@@ -16,23 +16,25 @@
along with this program. If not, see .
*/
+#include "evaluate.h"
+
#include
#include
+#include
+#include
#include
#include
-#include
#include
-#include
+#include
#include
-#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).
@@ -42,48 +44,46 @@
// const unsigned int gEmbeddedNNUESize; // the size of the embedded file
// Note that this does not work in Microsoft Visual Studio.
#if !defined(_MSC_VER) && !defined(NNUE_EMBEDDING_OFF)
- INCBIN(EmbeddedNNUE, EvalFileDefaultName);
+INCBIN(EmbeddedNNUE, EvalFileDefaultName);
#else
- const unsigned char gEmbeddedNNUEData[1] = {0x0};
- const unsigned char *const gEmbeddedNNUEEnd = &gEmbeddedNNUEData[1];
- const unsigned int gEmbeddedNNUESize = 1;
+const unsigned char gEmbeddedNNUEData[1] = {0x0};
+const unsigned char* const gEmbeddedNNUEEnd = &gEmbeddedNNUEData[1];
+const unsigned int gEmbeddedNNUESize = 1;
#endif
-using namespace std;
-
namespace Stockfish {
namespace Eval {
- 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"
- /// The name of the NNUE network is always retrieved from the EvalFile option.
- /// We search the given network in three locations: internally (the default
- /// network may be embedded in the binary), in the active working directory and
- /// in the engine directory. Distro packagers may define the DEFAULT_NNUE_DIRECTORY
- /// variable to have the engine search in a special directory in their distro.
+std::string currentEvalFileName = "None";
- void 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"
+// The name of the NNUE network is always retrieved from the EvalFile option.
+// We search the given network in three locations: internally (the default
+// network may be embedded in the binary), in the active working directory and
+// in the engine directory. Distro packagers may define the DEFAULT_NNUE_DIRECTORY
+// variable to have the engine search in a special directory in their distro.
+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 dirs = { "" , "" , CommandLine::binaryDirectory , stringify(DEFAULT_NNUE_DIRECTORY) };
- #else
- vector dirs = { "" , "" , CommandLine::binaryDirectory };
- #endif
+#if defined(DEFAULT_NNUE_DIRECTORY)
+ std::vector dirs = {"", "", CommandLine::binaryDirectory,
+ stringify(DEFAULT_NNUE_DIRECTORY)};
+#else
+ std::vector dirs = {"", "", CommandLine::binaryDirectory};
+#endif
- for (const string& directory : dirs)
+ for (const std::string& directory : dirs)
if (currentEvalFileName != eval_file)
{
if (directory != "")
{
- 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;
}
@@ -91,36 +91,45 @@ namespace Eval {
if (directory == "" && eval_file == EvalFileDefaultName)
{
// C++ way to prepare a buffer for a memory stream
- class MemoryBuffer : public basic_streambuf {
- public: MemoryBuffer(char* p, size_t n) { setg(p, p, p + n); setp(p, p + n); }
+ class MemoryBuffer: public std::basic_streambuf {
+ public:
+ MemoryBuffer(char* p, size_t n) {
+ setg(p, p, p + n);
+ setp(p, p + n);
+ }
};
- MemoryBuffer buffer(const_cast(reinterpret_cast(gEmbeddedNNUEData)),
- size_t(gEmbeddedNNUESize));
- (void) gEmbeddedNNUEEnd; // Silence warning on unused variable
+ MemoryBuffer buffer(
+ const_cast(reinterpret_cast(gEmbeddedNNUEData)),
+ 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() {
+// 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;
@@ -132,78 +141,93 @@ namespace Eval {
}
sync_cout << "info string NNUE evaluation using " << eval_file << 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) {
+// 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.
+Value Eval::simple_eval(const Position& pos, Color c) {
+ return PawnValue * (pos.count(c) - pos.count(~c))
+ + (pos.non_pawn_material(c) - pos.non_pawn_material(~c));
+}
- assert(!pos.checkers());
- Value v;
+// 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) {
- int nnueComplexity;
- int npm = pos.non_pawn_material() / 64;
+ assert(!pos.checkers());
- Color stm = pos.side_to_move();
- Value optimism = pos.this_thread()->optimism[stm];
+ Value v;
+ Color stm = pos.side_to_move();
+ int shuffling = pos.rule50_count();
+ int simpleEval = simple_eval(pos, stm) + (int(pos.key() & 7) - 3);
- Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
+ bool lazy = std::abs(simpleEval) >= RookValue + KnightValue + 16 * shuffling * shuffling
+ + std::abs(pos.this_thread()->bestValue)
+ + std::abs(pos.this_thread()->rootSimpleEval);
- int material = pos.non_pawn_material(stm) - pos.non_pawn_material(~stm)
- + 126 * (pos.count(stm) - pos.count(~stm));
+ if (lazy)
+ v = Value(simpleEval);
+ else
+ {
+ int nnueComplexity;
+ Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
- // Blend optimism and eval with nnue complexity and material imbalance
- optimism += optimism * (nnueComplexity + abs(material - nnue)) / 512;
- nnue -= nnue * (nnueComplexity + abs(material - nnue)) / 32768;
+ Value optimism = pos.this_thread()->optimism[stm];
- v = ( nnue * (915 + npm + 9 * pos.count())
- + optimism * (154 + npm + pos.count())) / 1024;
+ // Blend optimism and eval with nnue complexity and material imbalance
+ optimism += optimism * (nnueComplexity + std::abs(simpleEval - nnue)) / 512;
+ nnue -= nnue * (nnueComplexity + std::abs(simpleEval - nnue)) / 32768;
- // Damp down the evaluation linearly when shuffling
- v = v * (200 - pos.rule50_count()) / 214;
+ int npm = pos.non_pawn_material() / 64;
+ v = (nnue * (915 + npm + 9 * pos.count()) + optimism * (154 + npm)) / 1024;
+ }
- // 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);
+ // Damp down the evaluation linearly when shuffling
+ v = v * (200 - shuffling) / 214;
- return v;
-}
+ // 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);
-/// trace() is like evaluate(), but instead of returning a value, it returns
-/// a string (suitable for outputting to stdout) that contains the detailed
-/// descriptions and values of each evaluation term. Useful for debugging.
-/// Trace scores are from white's point of view
+ return v;
+}
+// Like evaluate(), but instead of returning a value, it returns
+// a string (suitable for outputting to stdout) that contains the detailed
+// descriptions and values of each evaluation term. Useful for debugging.
+// Trace scores are from white's point of view
std::string Eval::trace(Position& pos) {
- if (pos.checkers())
- return "Final evaluation: none (in check)";
+ if (pos.checkers())
+ return "Final evaluation: none (in check)";
- // Reset any global variable used in eval
- pos.this_thread()->bestValue = VALUE_ZERO;
- pos.this_thread()->optimism[WHITE] = VALUE_ZERO;
- pos.this_thread()->optimism[BLACK] = VALUE_ZERO;
+ // 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;
- std::stringstream ss;
- ss << std::showpoint << std::noshowpos << std::fixed << std::setprecision(2);
- ss << '\n' << NNUE::trace(pos) << '\n';
+ std::stringstream ss;
+ ss << std::showpoint << std::noshowpos << std::fixed << std::setprecision(2);
+ ss << '\n' << NNUE::trace(pos) << '\n';
- ss << std::showpoint << std::showpos << std::fixed << std::setprecision(2) << std::setw(15);
+ ss << std::showpoint << std::showpos << std::fixed << std::setprecision(2) << std::setw(15);
- Value v;
- v = NNUE::evaluate(pos, false);
- v = pos.side_to_move() == WHITE ? v : -v;
- ss << "NNUE evaluation " << 0.01 * UCI::to_cp(v) << " (white side)\n";
+ Value v;
+ v = NNUE::evaluate(pos, false);
+ v = pos.side_to_move() == WHITE ? v : -v;
+ 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 " << 0.01 * UCI::to_cp(v) << " (white side)";
- ss << " [with scaled NNUE, ...]";
- ss << "\n";
+ v = evaluate(pos);
+ v = pos.side_to_move() == WHITE ? v : -v;
+ ss << "Final evaluation " << 0.01 * UCI::to_cp(v) << " (white side)";
+ ss << " [with scaled NNUE, ...]";
+ ss << "\n";
- return ss.str();
+ return ss.str();
}
-} // namespace Stockfish
+} // namespace Stockfish