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This is another refactor which aims to decouple uci from stockfish. A new engine class manages all engine related logic and uci is a "small" wrapper around it. In the future we should also try to remove the need for the Position object in the uci and replace the options with an actual options struct instead of using a map. Also convert the std::string's in the Info structs a string_view. closes #5147 No functional change
204 lines
6.5 KiB
C++
204 lines
6.5 KiB
C++
/*
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Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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Copyright (C) 2004-2024 The Stockfish developers (see AUTHORS file)
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Stockfish is free software: you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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Stockfish is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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// Code for calculating NNUE evaluation function
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#include "nnue_misc.h"
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#include <cmath>
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#include <cstdlib>
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#include <cstring>
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#include <iomanip>
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#include <iosfwd>
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#include <iostream>
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#include <sstream>
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#include <string_view>
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#include "../evaluate.h"
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#include "../position.h"
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#include "../types.h"
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#include "../uci.h"
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#include "network.h"
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#include "nnue_accumulator.h"
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namespace Stockfish::Eval::NNUE {
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constexpr std::string_view PieceToChar(" PNBRQK pnbrqk");
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void hint_common_parent_position(const Position& pos, const Networks& networks) {
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int simpleEvalAbs = std::abs(simple_eval(pos, pos.side_to_move()));
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if (simpleEvalAbs > Eval::SmallNetThreshold)
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networks.small.hint_common_access(pos, simpleEvalAbs > Eval::PsqtOnlyThreshold);
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else
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networks.big.hint_common_access(pos, false);
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}
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namespace {
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// Converts a Value into (centi)pawns and writes it in a buffer.
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// The buffer must have capacity for at least 5 chars.
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void format_cp_compact(Value v, char* buffer, const Position& pos) {
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buffer[0] = (v < 0 ? '-' : v > 0 ? '+' : ' ');
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int cp = std::abs(UCIEngine::to_cp(v, pos));
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if (cp >= 10000)
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{
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buffer[1] = '0' + cp / 10000;
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cp %= 10000;
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buffer[2] = '0' + cp / 1000;
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cp %= 1000;
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buffer[3] = '0' + cp / 100;
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buffer[4] = ' ';
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}
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else if (cp >= 1000)
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{
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buffer[1] = '0' + cp / 1000;
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cp %= 1000;
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buffer[2] = '0' + cp / 100;
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cp %= 100;
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buffer[3] = '.';
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buffer[4] = '0' + cp / 10;
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}
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else
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{
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buffer[1] = '0' + cp / 100;
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cp %= 100;
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buffer[2] = '.';
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buffer[3] = '0' + cp / 10;
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cp %= 10;
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buffer[4] = '0' + cp / 1;
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}
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}
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// Converts a Value into pawns, always keeping two decimals
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void format_cp_aligned_dot(Value v, std::stringstream& stream, const Position& pos) {
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const double pawns = std::abs(0.01 * UCIEngine::to_cp(v, pos));
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stream << (v < 0 ? '-'
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: v > 0 ? '+'
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: ' ')
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<< std::setiosflags(std::ios::fixed) << std::setw(6) << std::setprecision(2) << pawns;
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}
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}
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// Returns a string with the value of each piece on a board,
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// and a table for (PSQT, Layers) values bucket by bucket.
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std::string trace(Position& pos, const Eval::NNUE::Networks& networks) {
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std::stringstream ss;
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char board[3 * 8 + 1][8 * 8 + 2];
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std::memset(board, ' ', sizeof(board));
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for (int row = 0; row < 3 * 8 + 1; ++row)
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board[row][8 * 8 + 1] = '\0';
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// A lambda to output one box of the board
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auto writeSquare = [&board, &pos](File file, Rank rank, Piece pc, Value value) {
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const int x = int(file) * 8;
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const int y = (7 - int(rank)) * 3;
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for (int i = 1; i < 8; ++i)
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board[y][x + i] = board[y + 3][x + i] = '-';
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for (int i = 1; i < 3; ++i)
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board[y + i][x] = board[y + i][x + 8] = '|';
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board[y][x] = board[y][x + 8] = board[y + 3][x + 8] = board[y + 3][x] = '+';
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if (pc != NO_PIECE)
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board[y + 1][x + 4] = PieceToChar[pc];
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if (value != VALUE_NONE)
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format_cp_compact(value, &board[y + 2][x + 2], pos);
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};
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// We estimate the value of each piece by doing a differential evaluation from
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// the current base eval, simulating the removal of the piece from its square.
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Value base = networks.big.evaluate(pos);
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base = pos.side_to_move() == WHITE ? base : -base;
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for (File f = FILE_A; f <= FILE_H; ++f)
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for (Rank r = RANK_1; r <= RANK_8; ++r)
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{
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Square sq = make_square(f, r);
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Piece pc = pos.piece_on(sq);
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Value v = VALUE_NONE;
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if (pc != NO_PIECE && type_of(pc) != KING)
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{
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auto st = pos.state();
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pos.remove_piece(sq);
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st->accumulatorBig.computed[WHITE] = st->accumulatorBig.computed[BLACK] =
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st->accumulatorBig.computedPSQT[WHITE] = st->accumulatorBig.computedPSQT[BLACK] =
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false;
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Value eval = networks.big.evaluate(pos);
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eval = pos.side_to_move() == WHITE ? eval : -eval;
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v = base - eval;
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pos.put_piece(pc, sq);
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st->accumulatorBig.computed[WHITE] = st->accumulatorBig.computed[BLACK] =
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st->accumulatorBig.computedPSQT[WHITE] = st->accumulatorBig.computedPSQT[BLACK] =
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false;
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}
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writeSquare(f, r, pc, v);
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}
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ss << " NNUE derived piece values:\n";
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for (int row = 0; row < 3 * 8 + 1; ++row)
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ss << board[row] << '\n';
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ss << '\n';
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auto t = networks.big.trace_evaluate(pos);
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ss << " NNUE network contributions "
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<< (pos.side_to_move() == WHITE ? "(White to move)" : "(Black to move)") << std::endl
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<< "+------------+------------+------------+------------+\n"
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<< "| Bucket | Material | Positional | Total |\n"
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<< "| | (PSQT) | (Layers) | |\n"
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<< "+------------+------------+------------+------------+\n";
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for (std::size_t bucket = 0; bucket < LayerStacks; ++bucket)
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{
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ss << "| " << bucket << " ";
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ss << " | ";
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format_cp_aligned_dot(t.psqt[bucket], ss, pos);
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ss << " "
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<< " | ";
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format_cp_aligned_dot(t.positional[bucket], ss, pos);
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ss << " "
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<< " | ";
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format_cp_aligned_dot(t.psqt[bucket] + t.positional[bucket], ss, pos);
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ss << " "
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<< " |";
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if (bucket == t.correctBucket)
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ss << " <-- this bucket is used";
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ss << '\n';
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}
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ss << "+------------+------------+------------+------------+\n";
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return ss.str();
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}
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} // namespace Stockfish::Eval::NNUE
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