2 Stockfish, a UCI chess playing engine derived from Glaurung 2.1
3 Copyright (C) 2004-2023 The Stockfish developers (see AUTHORS file)
5 Stockfish is free software: you can redistribute it and/or modify
6 it under the terms of the GNU General Public License as published by
7 the Free Software Foundation, either version 3 of the License, or
8 (at your option) any later version.
10 Stockfish is distributed in the hope that it will be useful,
11 but WITHOUT ANY WARRANTY; without even the implied warranty of
12 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 GNU General Public License for more details.
15 You should have received a copy of the GNU General Public License
16 along with this program. If not, see <http://www.gnu.org/licenses/>.
30 #include "incbin/incbin.h"
32 #include "nnue/evaluate_nnue.h"
38 // Macro to embed the default efficiently updatable neural network (NNUE) file
39 // data in the engine binary (using incbin.h, by Dale Weiler).
40 // This macro invocation will declare the following three variables
41 // const unsigned char gEmbeddedNNUEData[]; // a pointer to the embedded data
42 // const unsigned char *const gEmbeddedNNUEEnd; // a marker to the end
43 // const unsigned int gEmbeddedNNUESize; // the size of the embedded file
44 // Note that this does not work in Microsoft Visual Studio.
45 #if !defined(_MSC_VER) && !defined(NNUE_EMBEDDING_OFF)
46 INCBIN(EmbeddedNNUE, EvalFileDefaultName);
48 const unsigned char gEmbeddedNNUEData[1] = {0x0};
49 const unsigned char* const gEmbeddedNNUEEnd = &gEmbeddedNNUEData[1];
50 const unsigned int gEmbeddedNNUESize = 1;
58 std::string currentEvalFileName = "None";
60 // NNUE::init() tries to load a NNUE network at startup time, or when the engine
61 // receives a UCI command "setoption name EvalFile value nn-[a-z0-9]{12}.nnue"
62 // The name of the NNUE network is always retrieved from the EvalFile option.
63 // We search the given network in three locations: internally (the default
64 // network may be embedded in the binary), in the active working directory and
65 // in the engine directory. Distro packagers may define the DEFAULT_NNUE_DIRECTORY
66 // variable to have the engine search in a special directory in their distro.
70 std::string eval_file = std::string(Options["EvalFile"]);
71 if (eval_file.empty())
72 eval_file = EvalFileDefaultName;
74 #if defined(DEFAULT_NNUE_DIRECTORY)
75 std::vector<std::string> dirs = {"<internal>", "", CommandLine::binaryDirectory,
76 stringify(DEFAULT_NNUE_DIRECTORY)};
78 std::vector<std::string> dirs = {"<internal>", "", CommandLine::binaryDirectory};
81 for (const std::string& directory : dirs)
82 if (currentEvalFileName != eval_file)
84 if (directory != "<internal>")
86 std::ifstream stream(directory + eval_file, std::ios::binary);
87 if (NNUE::load_eval(eval_file, stream))
88 currentEvalFileName = eval_file;
91 if (directory == "<internal>" && eval_file == EvalFileDefaultName)
93 // C++ way to prepare a buffer for a memory stream
94 class MemoryBuffer: public std::basic_streambuf<char> {
96 MemoryBuffer(char* p, size_t n) {
103 const_cast<char*>(reinterpret_cast<const char*>(gEmbeddedNNUEData)),
104 size_t(gEmbeddedNNUESize));
105 (void) gEmbeddedNNUEEnd; // Silence warning on unused variable
107 std::istream stream(&buffer);
108 if (NNUE::load_eval(eval_file, stream))
109 currentEvalFileName = eval_file;
114 // NNUE::verify() verifies that the last net used was loaded successfully
115 void NNUE::verify() {
117 std::string eval_file = std::string(Options["EvalFile"]);
118 if (eval_file.empty())
119 eval_file = EvalFileDefaultName;
121 if (currentEvalFileName != eval_file)
125 "Network evaluation parameters compatible with the engine must be available.";
126 std::string msg2 = "The network file " + eval_file + " was not loaded successfully.";
128 "The UCI option EvalFile might need to specify the full path, including the directory name, to the network file.";
130 "The default net can be downloaded from: https://tests.stockfishchess.org/api/nn/"
131 + std::string(EvalFileDefaultName);
132 std::string msg5 = "The engine will be terminated now.";
134 sync_cout << "info string ERROR: " << msg1 << sync_endl;
135 sync_cout << "info string ERROR: " << msg2 << sync_endl;
136 sync_cout << "info string ERROR: " << msg3 << sync_endl;
137 sync_cout << "info string ERROR: " << msg4 << sync_endl;
138 sync_cout << "info string ERROR: " << msg5 << sync_endl;
143 sync_cout << "info string NNUE evaluation using " << eval_file << sync_endl;
148 // simple_eval() returns a static, purely materialistic evaluation of the position
149 // from the point of view of the given color. It can be divided by PawnValue to get
150 // an approximation of the material advantage on the board in terms of pawns.
152 Value Eval::simple_eval(const Position& pos, Color c) {
153 return PawnValue * (pos.count<PAWN>(c) - pos.count<PAWN>(~c))
154 + (pos.non_pawn_material(c) - pos.non_pawn_material(~c));
158 // evaluate() is the evaluator for the outer world. It returns a static evaluation
159 // of the position from the point of view of the side to move.
161 Value Eval::evaluate(const Position& pos) {
163 assert(!pos.checkers());
166 Color stm = pos.side_to_move();
167 int shuffling = pos.rule50_count();
168 int simpleEval = simple_eval(pos, stm) + (int(pos.key() & 7) - 3);
170 bool lazy = abs(simpleEval) >= RookValue + KnightValue + 16 * shuffling * shuffling
171 + abs(pos.this_thread()->bestValue)
172 + abs(pos.this_thread()->rootSimpleEval);
175 v = Value(simpleEval);
179 Value nnue = NNUE::evaluate(pos, true, &nnueComplexity);
181 Value optimism = pos.this_thread()->optimism[stm];
183 // Blend optimism and eval with nnue complexity and material imbalance
184 optimism += optimism * (nnueComplexity + abs(simpleEval - nnue)) / 512;
185 nnue -= nnue * (nnueComplexity + abs(simpleEval - nnue)) / 32768;
187 int npm = pos.non_pawn_material() / 64;
188 v = (nnue * (915 + npm + 9 * pos.count<PAWN>()) + optimism * (154 + npm)) / 1024;
191 // Damp down the evaluation linearly when shuffling
192 v = v * (200 - shuffling) / 214;
194 // Guarantee evaluation does not hit the tablebase range
195 v = std::clamp(v, VALUE_TB_LOSS_IN_MAX_PLY + 1, VALUE_TB_WIN_IN_MAX_PLY - 1);
200 // trace() is like evaluate(), but instead of returning a value, it returns
201 // a string (suitable for outputting to stdout) that contains the detailed
202 // descriptions and values of each evaluation term. Useful for debugging.
203 // Trace scores are from white's point of view
205 std::string Eval::trace(Position& pos) {
208 return "Final evaluation: none (in check)";
210 // Reset any global variable used in eval
211 pos.this_thread()->bestValue = VALUE_ZERO;
212 pos.this_thread()->rootSimpleEval = VALUE_ZERO;
213 pos.this_thread()->optimism[WHITE] = VALUE_ZERO;
214 pos.this_thread()->optimism[BLACK] = VALUE_ZERO;
216 std::stringstream ss;
217 ss << std::showpoint << std::noshowpos << std::fixed << std::setprecision(2);
218 ss << '\n' << NNUE::trace(pos) << '\n';
220 ss << std::showpoint << std::showpos << std::fixed << std::setprecision(2) << std::setw(15);
223 v = NNUE::evaluate(pos, false);
224 v = pos.side_to_move() == WHITE ? v : -v;
225 ss << "NNUE evaluation " << 0.01 * UCI::to_cp(v) << " (white side)\n";
228 v = pos.side_to_move() == WHITE ? v : -v;
229 ss << "Final evaluation " << 0.01 * UCI::to_cp(v) << " (white side)";
230 ss << " [with scaled NNUE, ...]";
236 } // namespace Stockfish