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https://github.com/opelly27/Stockfish.git
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Merge NNUE (master) in the cluster branch.
fixes minor merge conflicts, and a first quick testing looks OK: 4mpix4th vs 4th at 30+0.3s: Score of cluster vs master: 3 - 0 - 37 [0.537] 40 Elo difference: 26.1 +/- 28.5, LOS: 95.8 %, DrawRatio: 92.5 % No functional change.
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@@ -1,8 +1,6 @@
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/*
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Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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Copyright (C) 2004-2008 Tord Romstad (Glaurung author)
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Copyright (C) 2008-2015 Marco Costalba, Joona Kiiski, Tord Romstad
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Copyright (C) 2015-2020 Marco Costalba, Joona Kiiski, Gary Linscott, Tord Romstad
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Copyright (C) 2004-2020 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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@@ -19,6 +17,7 @@
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*/
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#include <cassert>
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#include <cmath>
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#include <iostream>
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#include <sstream>
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#include <string>
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@@ -78,6 +77,20 @@ namespace {
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}
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}
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// trace_eval() prints the evaluation for the current position, consistent with the UCI
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// options set so far.
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void trace_eval(Position& pos) {
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StateListPtr states(new std::deque<StateInfo>(1));
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Position p;
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p.set(pos.fen(), Options["UCI_Chess960"], &states->back(), Threads.main());
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Eval::verify_NNUE();
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sync_cout << "\n" << Eval::trace(p) << sync_endl;
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}
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// setoption() is called when engine receives the "setoption" UCI command. The
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// function updates the UCI option ("name") to the given value ("value").
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@@ -167,7 +180,7 @@ namespace {
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nodes += Threads.nodes_searched();
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}
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else if (Cluster::is_root())
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sync_cout << "\n" << Eval::trace(pos) << sync_endl;
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trace_eval(pos);
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}
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else if (token == "setoption") setoption(is);
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else if (token == "position") position(pos, is, states);
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@@ -185,6 +198,28 @@ namespace {
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<< "\nNodes/second : " << 1000 * nodes / elapsed << endl;
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}
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// The win rate model returns the probability (per mille) of winning given an eval
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// and a game-ply. The model fits rather accurately the LTC fishtest statistics.
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int win_rate_model(Value v, int ply) {
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// The model captures only up to 240 plies, so limit input (and rescale)
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double m = std::min(240, ply) / 64.0;
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// Coefficients of a 3rd order polynomial fit based on fishtest data
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// for two parameters needed to transform eval to the argument of a
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// logistic function.
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double as[] = {-8.24404295, 64.23892342, -95.73056462, 153.86478679};
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double bs[] = {-3.37154371, 28.44489198, -56.67657741, 72.05858751};
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double a = (((as[0] * m + as[1]) * m + as[2]) * m) + as[3];
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double b = (((bs[0] * m + bs[1]) * m + bs[2]) * m) + bs[3];
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// Transform eval to centipawns with limited range
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double x = Utility::clamp(double(100 * v) / PawnValueEg, -1000.0, 1000.0);
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// Return win rate in per mille (rounded to nearest)
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return int(0.5 + 1000 / (1 + std::exp((a - x) / b)));
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}
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} // namespace
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@@ -244,7 +279,7 @@ void UCI::loop(int argc, char* argv[]) {
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else if (token == "d" && Cluster::is_root())
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sync_cout << pos << sync_endl;
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else if (token == "eval" && Cluster::is_root())
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sync_cout << Eval::trace(pos) << sync_endl;
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trace_eval(pos);
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else if (token == "compiler" && Cluster::is_root())
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sync_cout << compiler_info() << sync_endl;
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else if (Cluster::is_root())
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@@ -276,6 +311,22 @@ string UCI::value(Value v) {
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}
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/// UCI::wdl() report WDL statistics given an evaluation and a game ply, based on
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/// data gathered for fishtest LTC games.
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string UCI::wdl(Value v, int ply) {
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stringstream ss;
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int wdl_w = win_rate_model( v, ply);
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int wdl_l = win_rate_model(-v, ply);
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int wdl_d = 1000 - wdl_w - wdl_l;
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ss << " wdl " << wdl_w << " " << wdl_d << " " << wdl_l;
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return ss.str();
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}
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/// UCI::square() converts a Square to a string in algebraic notation (g1, a7, etc.)
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std::string UCI::square(Square s) {
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