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/*
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
Copyright (C) 2004-2021 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
the Free Software Foundation, either version 3 of the License, or
(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
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef POSITION_H_INCLUDED
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#define POSITION_H_INCLUDED
#include <cassert>
#include <deque>
#include <memory> // For std::unique_ptr
#include <string>
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#include "bitboard.h"
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
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#include "evaluate.h"
#include "psqt.h"
#include "types.h"
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Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
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#include "nnue/nnue_accumulator.h"
namespace Stockfish {
/// StateInfo struct stores information needed to restore a Position object to
/// its previous state when we retract a move. Whenever a move is made on the
/// board (by calling Position::do_move), a StateInfo object must be passed.
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struct StateInfo {
// Copied when making a move
Key pawnKey;
Key materialKey;
Value nonPawnMaterial[COLOR_NB];
int castlingRights;
int rule50;
int pliesFromNull;
Square epSquare;
// Not copied when making a move (will be recomputed anyhow)
Key key;
Bitboard checkersBB;
StateInfo* previous;
Bitboard blockersForKing[COLOR_NB];
Bitboard pinners[COLOR_NB];
Bitboard checkSquares[PIECE_TYPE_NB];
Piece capturedPiece;
int repetition;
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
// Used by NNUE
Eval::NNUE::Accumulator accumulator;
DirtyPiece dirtyPiece;
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};
/// A list to keep track of the position states along the setup moves (from the
/// start position to the position just before the search starts). Needed by
/// 'draw by repetition' detection. Use a std::deque because pointers to
/// elements are not invalidated upon list resizing.
typedef std::unique_ptr<std::deque<StateInfo>> StateListPtr;
/// Position class stores information regarding the board representation as
/// pieces, side to move, hash keys, castling info, etc. Important methods are
/// do_move() and undo_move(), used by the search to update node info when
/// traversing the search tree.
class Thread;
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class Position {
public:
static void init();
Position() = default;
Position(const Position&) = delete;
Position& operator=(const Position&) = delete;
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// FEN string input/output
Position& set(const std::string& fenStr, bool isChess960, StateInfo* si, Thread* th);
Position& set(const std::string& code, Color c, StateInfo* si);
std::string fen() const;
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// Position representation
Bitboard pieces(PieceType pt) const;
Bitboard pieces(PieceType pt1, PieceType pt2) const;
Bitboard pieces(Color c) const;
Bitboard pieces(Color c, PieceType pt) const;
Bitboard pieces(Color c, PieceType pt1, PieceType pt2) const;
Piece piece_on(Square s) const;
Square ep_square() const;
bool empty(Square s) const;
template<PieceType Pt> int count(Color c) const;
template<PieceType Pt> int count() const;
template<PieceType Pt> Square square(Color c) const;
bool is_on_semiopen_file(Color c, Square s) const;
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// Castling
CastlingRights castling_rights(Color c) const;
bool can_castle(CastlingRights cr) const;
bool castling_impeded(CastlingRights cr) const;
Square castling_rook_square(CastlingRights cr) const;
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// Checking
Bitboard checkers() const;
Bitboard blockers_for_king(Color c) const;
Bitboard check_squares(PieceType pt) const;
Bitboard pinners(Color c) const;
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// Attacks to/from a given square
Bitboard attackers_to(Square s) const;
Bitboard attackers_to(Square s, Bitboard occupied) const;
Bitboard slider_blockers(Bitboard sliders, Square s, Bitboard& pinners) const;
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// Properties of moves
bool legal(Move m) const;
bool pseudo_legal(const Move m) const;
bool capture(Move m) const;
bool capture_or_promotion(Move m) const;
bool gives_check(Move m) const;
Piece moved_piece(Move m) const;
Piece captured_piece() const;
// Piece specific
bool pawn_passed(Color c, Square s) const;
bool opposite_bishops() const;
int pawns_on_same_color_squares(Color c, Square s) const;
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// Doing and undoing moves
void do_move(Move m, StateInfo& newSt);
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void do_move(Move m, StateInfo& newSt, bool givesCheck);
void undo_move(Move m);
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void do_null_move(StateInfo& newSt);
void undo_null_move();
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// Static Exchange Evaluation
bool see_ge(Move m, Value threshold = VALUE_ZERO) const;
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// Accessing hash keys
Key key() const;
Key key_after(Move m) const;
Key material_key() const;
Key pawn_key() const;
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// Other properties of the position
Color side_to_move() const;
int game_ply() const;
bool is_chess960() const;
Thread* this_thread() const;
Threefold repetition detection Implement a threefold repetition detection. Below are the examples of problems fixed by this change. Loosing move in a drawn position. position fen 8/k7/3p4/p2P1p2/P2P1P2/8/8/K7 w - - 0 1 moves a1a2 a7a8 a2a1 The old code suggested a loosing move "bestmove a8a7", the new code suggests "bestmove a8b7" leading to a draw. Incorrect evaluation (happened in a real game in TCEC Season 9). position fen 4rbkr/1q3pp1/b3pn2/7p/1pN5/1P1BBP1P/P1R2QP1/3R2K1 w - - 5 31 moves e3d4 h8h6 d4e3 The old code evaluated it as "cp 0", the new code evaluation is around "cp -50" which is adequate. Brings 0.5-1 ELO gain. Passes [-3.00,1.00]. STC: http://tests.stockfishchess.org/tests/view/584ece040ebc5903140c5aea LLR: 2.96 (-2.94,2.94) [-3.00,1.00] Total: 47744 W: 8537 L: 8461 D: 30746 LTC: http://tests.stockfishchess.org/tests/view/584f134d0ebc5903140c5b37 LLR: 2.96 (-2.94,2.94) [-3.00,1.00] Total: 36775 W: 4739 L: 4639 D: 27397 Patch has been rewritten into current form for simplification and logic slightly changed so that return a draw score if the position repeats once earlier but after or at the root, or repeats twice strictly before the root. In its original form, repetition at root was not returned as an immediate draw. After retestimng testing both version with SPRT[-3, 1], both passed succesfully, but this version was chosen becuase more natural. There is an argument about MultiPV in which an extended draw at root may be sensible. See discussion here: https://github.com/official-stockfish/Stockfish/pull/925 For documentation, current version passed both at STC and LTC: STC LLR: 2.96 (-2.94,2.94) [-3.00,1.00] Total: 51562 W: 9314 L: 9245 D: 33003 LTC LLR: 2.96 (-2.94,2.94) [-3.00,1.00] Total: 115663 W: 14904 L: 14906 D: 85853 bench: 5468995
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bool is_draw(int ply) const;
Use cycle detection to bound search value A position which has a move which draws by repetition, or which could have been reached from an earlier position in the game tree, is considered to be at least a draw for the side to move. Cycle detection algorithm by Marcel van Kervink: https://marcelk.net/2013-04-06/paper/upcoming-rep-v2.pdf ---------------------------- How does the algorithm work in practice? The algorithm is an efficient method to detect if the side to move has a drawing move, without doing any move generation, thus possibly giving a cheap cutoffThe most interesting conditions are both on line 1195: ``` if ( originalKey == (progressKey ^ stp->key) || progressKey == Zobrist::side) ``` This uses the position keys as a sort-of Bloom filter, to avoid the expensive checks which follow. For "upcoming repetition" consider the opening Nf3 Nf6 Ng1. The XOR of this position's key with the starting position gives their difference, which can be used to look up black's repeating move (Ng8). But that look-up is expensive, so line 1195 checks that the white pieces are on their original squares. This is the subtlest part of the algorithm, but the basic idea in the above game is there are 4 positions (starting position and the one after each move). An XOR of the first pair (startpos and after Nf3) gives a key matching Nf3. An XOR of the second pair (after Nf6 and after Ng1) gives a key matching the move Ng1. But since the difference in each pair is the location of the white knight those keys are "identical" (not quite because while there are 4 keys the the side to move changed 3 times, so the keys differ by Zobrist::side). The loop containing line 1195 does this pair-wise XOR-ing. Continuing the example, after line 1195 determines that the white pieces are back where they started we still need to make sure the changes in the black pieces represents a legal move. This is done by looking up the "moveKey" to see if it corresponds to possible move, and that there are no pieces blocking its way. There is the additional complication that, to match the behavior of is_draw(), if the repetition is not inside the search tree then there must be an additional repetition in the game history. Since a position can have more than one upcoming repetition a simple count does not suffice. So there is a search loop ending on line 1215. On the other hand, the "no-progress' is the same thing but offset by 1 ply. I like the concept but think it currently has minimal or negative benefit, and I'd be happy to remove it if that would get the patch accepted. This will not, however, save many lines of code. ----------------------------- STC: LLR: 2.95 (-2.94,2.94) [0.00,5.00] Total: 36430 W: 7446 L: 7150 D: 21834 http://tests.stockfishchess.org/tests/view/5afc123f0ebc591fdf408dfc LTC: LLR: 2.96 (-2.94,2.94) [0.00,5.00] Total: 12998 W: 2045 L: 1876 D: 9077 http://tests.stockfishchess.org/tests/view/5afc2c630ebc591fdf408e0c How could we continue after the patch: • The code in search() that checks for cycles has numerous possible variants. Perhaps the check need could be done in qsearch() too. • The biggest improvement would be to get "no progress" to be of actual benefit, and it would be helpful understand why it (probably) isn't. Perhaps there is an interaction with the transposition table or the (fantastically complex) tree search. Perhaps this would be hard to fix, but there may be a simple oversight. Closes https://github.com/official-stockfish/Stockfish/pull/1575 Bench: 4550412
2018-05-16 14:47:41 -06:00
bool has_game_cycle(int ply) const;
Tablebases root ranking This patch corrects both MultiPV behaviour and "go searchmoves" behaviour for tablebases. We change the logic of table base probing at root positions from filtering to ranking. The ranking code is much more straightforward than the current filtering code (this is a simplification), and also more versatile. If the root is a TB position, each root move is probed and assigned a TB score and a TB rank. The TB score is the Value to be displayed to the user for that move (unless the search finds a mate score), while the TB rank determines which moves should appear higher in a multi-pv search. In game play, the engine will always pick a move with the highest rank. Ranks run from -1000 to +1000: 901 to 1000 : TB win 900 : normally a TB win, in rare cases this could be a draw 1 to 899 : cursed TB wins 0 : draw -1 to -899 : blessed TB losses -900 : normally a TB loss, in rare cases this could be a draw -901 to -1000 : TB loss Normally all winning moves get rank 1000 (to let the search pick the best among them). The exception is if there has been a first repetition. In that case, moves are ranked strictly by DTZ so that the engine will play a move that lowers DTZ (and therefore cannot repeat the position a second time). Losing moves get rank -1000 unless they have relatively high DTZ, meaning they have some drawing chances. Those get ranks towards -901 (when they cross -900 the draw is certain). Closes https://github.com/official-stockfish/Stockfish/pull/1467 No functional change (without tablebases).
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bool has_repeated() const;
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int rule50_count() const;
Score psq_score() const;
Value non_pawn_material(Color c) const;
Value non_pawn_material() const;
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// Position consistency check, for debugging
bool pos_is_ok() const;
void flip();
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Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
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// Used by NNUE
StateInfo* state() const;
Change trace with NNUE eval support This patch adds some more output to the `eval` command. It adds a board display with estimated piece values (method is remove-piece, evaluate, put-piece), and splits the NNUE evaluation with (psqt,layers) for each bucket for the NNUE net. Example: ``` ./stockfish position fen 3Qb1k1/1r2ppb1/pN1n2q1/Pp1Pp1Pr/4P2p/4BP2/4B1R1/1R5K b - - 11 40 eval Contributing terms for the classical eval: +------------+-------------+-------------+-------------+ | Term | White | Black | Total | | | MG EG | MG EG | MG EG | +------------+-------------+-------------+-------------+ | Material | ---- ---- | ---- ---- | -0.73 -1.55 | | Imbalance | ---- ---- | ---- ---- | -0.21 -0.17 | | Pawns | 0.35 -0.00 | 0.19 -0.26 | 0.16 0.25 | | Knights | 0.04 -0.08 | 0.12 -0.01 | -0.08 -0.07 | | Bishops | -0.34 -0.87 | -0.17 -0.61 | -0.17 -0.26 | | Rooks | 0.12 0.00 | 0.08 0.00 | 0.04 0.00 | | Queens | 0.00 0.00 | -0.27 -0.07 | 0.27 0.07 | | Mobility | 0.84 1.76 | 0.01 0.66 | 0.83 1.10 | |King safety | -0.99 -0.17 | -0.72 -0.10 | -0.27 -0.07 | | Threats | 0.27 0.27 | 0.73 0.86 | -0.46 -0.59 | | Passed | 0.00 0.00 | 0.79 0.82 | -0.79 -0.82 | | Space | 0.61 0.00 | 0.24 0.00 | 0.37 0.00 | | Winnable | ---- ---- | ---- ---- | 0.00 -0.03 | +------------+-------------+-------------+-------------+ | Total | ---- ---- | ---- ---- | -1.03 -2.14 | +------------+-------------+-------------+-------------+ NNUE derived piece values: +-------+-------+-------+-------+-------+-------+-------+-------+ | | | | Q | b | | k | | | | | | +12.4 | -1.62 | | | | +-------+-------+-------+-------+-------+-------+-------+-------+ | | r | | | p | p | b | | | | -3.89 | | | -0.84 | -1.19 | -3.32 | | +-------+-------+-------+-------+-------+-------+-------+-------+ | p | N | | n | | | q | | | -1.81 | +3.71 | | -4.82 | | | -5.04 | | +-------+-------+-------+-------+-------+-------+-------+-------+ | P | p | | P | p | | P | r | | +1.16 | -0.91 | | +0.55 | +0.12 | | +0.50 | -4.02 | +-------+-------+-------+-------+-------+-------+-------+-------+ | | | | | P | | | p | | | | | | +2.33 | | | +1.17 | +-------+-------+-------+-------+-------+-------+-------+-------+ | | | | | B | P | | | | | | | | +4.79 | +1.54 | | | +-------+-------+-------+-------+-------+-------+-------+-------+ | | | | | B | | R | | | | | | | +4.54 | | +6.03 | | +-------+-------+-------+-------+-------+-------+-------+-------+ | | R | | | | | | K | | | +4.81 | | | | | | | +-------+-------+-------+-------+-------+-------+-------+-------+ NNUE network contributions (Black to move) +------------+------------+------------+------------+ | Bucket | Material | Positional | Total | | | (PSQT) | (Layers) | | +------------+------------+------------+------------+ | 0 | + 0.32 | - 1.46 | - 1.13 | | 1 | + 0.25 | - 0.68 | - 0.43 | | 2 | + 0.46 | - 1.72 | - 1.25 | | 3 | + 0.55 | - 1.80 | - 1.25 | | 4 | + 0.48 | - 1.77 | - 1.29 | | 5 | + 0.40 | - 2.00 | - 1.60 | | 6 | + 0.57 | - 2.12 | - 1.54 | <-- this bucket is used | 7 | + 3.38 | - 2.00 | + 1.37 | +------------+------------+------------+------------+ Classical evaluation -1.00 (white side) NNUE evaluation +1.54 (white side) Final evaluation +2.38 (white side) [with scaled NNUE, hybrid, ...] ``` Also renames the export_net() function to save_eval() while there. closes https://github.com/official-stockfish/Stockfish/pull/3562 No functional change
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void put_piece(Piece pc, Square s);
void remove_piece(Square s);
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private:
// Initialization helpers (used while setting up a position)
void set_castling_right(Color c, Square rfrom);
void set_state(StateInfo* si) const;
void set_check_info(StateInfo* si) const;
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// Other helpers
void move_piece(Square from, Square to);
template<bool Do>
void do_castling(Color us, Square from, Square& to, Square& rfrom, Square& rto);
// Data members
Piece board[SQUARE_NB];
Bitboard byTypeBB[PIECE_TYPE_NB];
Bitboard byColorBB[COLOR_NB];
int pieceCount[PIECE_NB];
int castlingRightsMask[SQUARE_NB];
Square castlingRookSquare[CASTLING_RIGHT_NB];
Bitboard castlingPath[CASTLING_RIGHT_NB];
Thread* thisThread;
StateInfo* st;
int gamePly;
Color sideToMove;
Score psq;
bool chess960;
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};
extern std::ostream& operator<<(std::ostream& os, const Position& pos);
inline Color Position::side_to_move() const {
return sideToMove;
}
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inline Piece Position::piece_on(Square s) const {
assert(is_ok(s));
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return board[s];
}
inline bool Position::empty(Square s) const {
return piece_on(s) == NO_PIECE;
}
inline Piece Position::moved_piece(Move m) const {
return piece_on(from_sq(m));
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}
inline Bitboard Position::pieces(PieceType pt = ALL_PIECES) const {
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return byTypeBB[pt];
}
inline Bitboard Position::pieces(PieceType pt1, PieceType pt2) const {
return pieces(pt1) | pieces(pt2);
}
inline Bitboard Position::pieces(Color c) const {
return byColorBB[c];
}
inline Bitboard Position::pieces(Color c, PieceType pt) const {
return pieces(c) & pieces(pt);
}
inline Bitboard Position::pieces(Color c, PieceType pt1, PieceType pt2) const {
return pieces(c) & (pieces(pt1) | pieces(pt2));
}
template<PieceType Pt> inline int Position::count(Color c) const {
return pieceCount[make_piece(c, Pt)];
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}
template<PieceType Pt> inline int Position::count() const {
return count<Pt>(WHITE) + count<Pt>(BLACK);
}
template<PieceType Pt> inline Square Position::square(Color c) const {
assert(count<Pt>(c) == 1);
return lsb(pieces(c, Pt));
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}
inline Square Position::ep_square() const {
return st->epSquare;
}
inline bool Position::is_on_semiopen_file(Color c, Square s) const {
return !(pieces(c, PAWN) & file_bb(s));
}
inline bool Position::can_castle(CastlingRights cr) const {
return st->castlingRights & cr;
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}
inline CastlingRights Position::castling_rights(Color c) const {
return c & CastlingRights(st->castlingRights);
}
inline bool Position::castling_impeded(CastlingRights cr) const {
assert(cr == WHITE_OO || cr == WHITE_OOO || cr == BLACK_OO || cr == BLACK_OOO);
return pieces() & castlingPath[cr];
}
inline Square Position::castling_rook_square(CastlingRights cr) const {
assert(cr == WHITE_OO || cr == WHITE_OOO || cr == BLACK_OO || cr == BLACK_OOO);
return castlingRookSquare[cr];
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}
inline Bitboard Position::attackers_to(Square s) const {
return attackers_to(s, pieces());
}
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inline Bitboard Position::checkers() const {
return st->checkersBB;
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}
inline Bitboard Position::blockers_for_king(Color c) const {
return st->blockersForKing[c];
}
inline Bitboard Position::pinners(Color c) const {
return st->pinners[c];
}
inline Bitboard Position::check_squares(PieceType pt) const {
return st->checkSquares[pt];
}
inline bool Position::pawn_passed(Color c, Square s) const {
return !(pieces(~c, PAWN) & passed_pawn_span(c, s));
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}
inline int Position::pawns_on_same_color_squares(Color c, Square s) const {
return popcount(pieces(c, PAWN) & ((DarkSquares & s) ? DarkSquares : ~DarkSquares));
}
inline Key Position::key() const {
return st->rule50 < 14 ? st->key
: st->key ^ make_key((st->rule50 - 14) / 8);
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}
inline Key Position::pawn_key() const {
return st->pawnKey;
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}
inline Key Position::material_key() const {
return st->materialKey;
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}
inline Score Position::psq_score() const {
return psq;
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}
inline Value Position::non_pawn_material(Color c) const {
return st->nonPawnMaterial[c];
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}
inline Value Position::non_pawn_material() const {
return non_pawn_material(WHITE) + non_pawn_material(BLACK);
}
inline int Position::game_ply() const {
return gamePly;
}
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inline int Position::rule50_count() const {
return st->rule50;
}
inline bool Position::opposite_bishops() const {
return count<BISHOP>(WHITE) == 1
&& count<BISHOP>(BLACK) == 1
&& opposite_colors(square<BISHOP>(WHITE), square<BISHOP>(BLACK));
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}
inline bool Position::is_chess960() const {
return chess960;
}
inline bool Position::capture_or_promotion(Move m) const {
assert(is_ok(m));
return type_of(m) != NORMAL ? type_of(m) != CASTLING : !empty(to_sq(m));
}
inline bool Position::capture(Move m) const {
assert(is_ok(m));
// Castling is encoded as "king captures rook"
return (!empty(to_sq(m)) && type_of(m) != CASTLING) || type_of(m) == EN_PASSANT;
}
inline Piece Position::captured_piece() const {
return st->capturedPiece;
}
inline Thread* Position::this_thread() const {
return thisThread;
}
inline void Position::put_piece(Piece pc, Square s) {
board[s] = pc;
byTypeBB[ALL_PIECES] |= byTypeBB[type_of(pc)] |= s;
byColorBB[color_of(pc)] |= s;
pieceCount[pc]++;
pieceCount[make_piece(color_of(pc), ALL_PIECES)]++;
psq += PSQT::psq[pc][s];
}
inline void Position::remove_piece(Square s) {
Piece pc = board[s];
byTypeBB[ALL_PIECES] ^= s;
byTypeBB[type_of(pc)] ^= s;
byColorBB[color_of(pc)] ^= s;
Change trace with NNUE eval support This patch adds some more output to the `eval` command. It adds a board display with estimated piece values (method is remove-piece, evaluate, put-piece), and splits the NNUE evaluation with (psqt,layers) for each bucket for the NNUE net. Example: ``` ./stockfish position fen 3Qb1k1/1r2ppb1/pN1n2q1/Pp1Pp1Pr/4P2p/4BP2/4B1R1/1R5K b - - 11 40 eval Contributing terms for the classical eval: +------------+-------------+-------------+-------------+ | Term | White | Black | Total | | | MG EG | MG EG | MG EG | +------------+-------------+-------------+-------------+ | Material | ---- ---- | ---- ---- | -0.73 -1.55 | | Imbalance | ---- ---- | ---- ---- | -0.21 -0.17 | | Pawns | 0.35 -0.00 | 0.19 -0.26 | 0.16 0.25 | | Knights | 0.04 -0.08 | 0.12 -0.01 | -0.08 -0.07 | | Bishops | -0.34 -0.87 | -0.17 -0.61 | -0.17 -0.26 | | Rooks | 0.12 0.00 | 0.08 0.00 | 0.04 0.00 | | Queens | 0.00 0.00 | -0.27 -0.07 | 0.27 0.07 | | Mobility | 0.84 1.76 | 0.01 0.66 | 0.83 1.10 | |King safety | -0.99 -0.17 | -0.72 -0.10 | -0.27 -0.07 | | Threats | 0.27 0.27 | 0.73 0.86 | -0.46 -0.59 | | Passed | 0.00 0.00 | 0.79 0.82 | -0.79 -0.82 | | Space | 0.61 0.00 | 0.24 0.00 | 0.37 0.00 | | Winnable | ---- ---- | ---- ---- | 0.00 -0.03 | +------------+-------------+-------------+-------------+ | Total | ---- ---- | ---- ---- | -1.03 -2.14 | +------------+-------------+-------------+-------------+ NNUE derived piece values: +-------+-------+-------+-------+-------+-------+-------+-------+ | | | | Q | b | | k | | | | | | +12.4 | -1.62 | | | | +-------+-------+-------+-------+-------+-------+-------+-------+ | | r | | | p | p | b | | | | -3.89 | | | -0.84 | -1.19 | -3.32 | | +-------+-------+-------+-------+-------+-------+-------+-------+ | p | N | | n | | | q | | | -1.81 | +3.71 | | -4.82 | | | -5.04 | | +-------+-------+-------+-------+-------+-------+-------+-------+ | P | p | | P | p | | P | r | | +1.16 | -0.91 | | +0.55 | +0.12 | | +0.50 | -4.02 | +-------+-------+-------+-------+-------+-------+-------+-------+ | | | | | P | | | p | | | | | | +2.33 | | | +1.17 | +-------+-------+-------+-------+-------+-------+-------+-------+ | | | | | B | P | | | | | | | | +4.79 | +1.54 | | | +-------+-------+-------+-------+-------+-------+-------+-------+ | | | | | B | | R | | | | | | | +4.54 | | +6.03 | | +-------+-------+-------+-------+-------+-------+-------+-------+ | | R | | | | | | K | | | +4.81 | | | | | | | +-------+-------+-------+-------+-------+-------+-------+-------+ NNUE network contributions (Black to move) +------------+------------+------------+------------+ | Bucket | Material | Positional | Total | | | (PSQT) | (Layers) | | +------------+------------+------------+------------+ | 0 | + 0.32 | - 1.46 | - 1.13 | | 1 | + 0.25 | - 0.68 | - 0.43 | | 2 | + 0.46 | - 1.72 | - 1.25 | | 3 | + 0.55 | - 1.80 | - 1.25 | | 4 | + 0.48 | - 1.77 | - 1.29 | | 5 | + 0.40 | - 2.00 | - 1.60 | | 6 | + 0.57 | - 2.12 | - 1.54 | <-- this bucket is used | 7 | + 3.38 | - 2.00 | + 1.37 | +------------+------------+------------+------------+ Classical evaluation -1.00 (white side) NNUE evaluation +1.54 (white side) Final evaluation +2.38 (white side) [with scaled NNUE, hybrid, ...] ``` Also renames the export_net() function to save_eval() while there. closes https://github.com/official-stockfish/Stockfish/pull/3562 No functional change
2021-06-17 04:36:06 -06:00
board[s] = NO_PIECE;
pieceCount[pc]--;
pieceCount[make_piece(color_of(pc), ALL_PIECES)]--;
psq -= PSQT::psq[pc][s];
}
inline void Position::move_piece(Square from, Square to) {
Piece pc = board[from];
Make Square and Bitboard operators commutative As Stockfish developers, we aim to make our code as legible and as close to simple English as possible. However, one of the more notable exceptions to this rule concerns operations between Squares and Bitboards. Prior to this pull request, AND, OR, and XOR were only defined when the Bitboard was the first operand, and the Square the second. For example, for a Bitboard b and Square s, "b & s" would be valid but "s & b" would not. This conflicts with natural reasoning about logical operators, both mathematically and intuitively, which says that logical operators should commute. More dangerously, however, both Square and Bitboard are defined as integers "under the hood." As a result, code like "s & b" would still compile and give reasonable bench values. This trap occasionally ensnares even experienced Stockfish developers, but it is especially dangerous for new developers not aware of this peculiarity. Because there is no compilation or runtime error, and a reasonable bench, only a close review by approvers can spot this error when a test has been submitted--and many times, these bugs have slipped past review. This is by far the most common logical error on Fishtest, and has wasted uncountable STC games over the years. However, it can be fixed by adding three non-functional lines of code. In this patch, we define the operators when the operands are provided in the opposite order, i.e., we make AND, OR, and XOR commutative for Bitboards and Squares. Because these are inline methods and implemented identically, the executable does not change at all. This patch has the small side-effect of requiring Squares to be explicitly cast to integers before AND, OR, or XOR with integers. This is only performed twice in Stockfish's source code, and again does not change the executable at all (since Square is an enum defined as an integer anyway). For demonstration purposes, this pull request also inverts the order of one AND and one OR, to show that neither the bench nor the executable change. (This change can be removed before merging, if preferred.) I hope that this pull request significantly lowers the barrier-of-entry for new developer to join the Stockfish project. I also hope that this change will improve our efficiency in using our generous CPU donors' machines, since it will remove one of the most common causes of buggy tests. Following helpful review and comments by Michael Stembera (@mstembera), we add a further clean-up by implementing OR for two Squares, to anticipate additional traps developers may encounter and handle them cleanly. Closes https://github.com/official-stockfish/Stockfish/pull/2387 No functional change.
2019-10-31 22:27:19 -06:00
Bitboard fromTo = from | to;
byTypeBB[ALL_PIECES] ^= fromTo;
byTypeBB[type_of(pc)] ^= fromTo;
byColorBB[color_of(pc)] ^= fromTo;
board[from] = NO_PIECE;
board[to] = pc;
psq += PSQT::psq[pc][to] - PSQT::psq[pc][from];
}
inline void Position::do_move(Move m, StateInfo& newSt) {
do_move(m, newSt, gives_check(m));
}
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
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inline StateInfo* Position::state() const {
return st;
}
} // namespace Stockfish
#endif // #ifndef POSITION_H_INCLUDED