+ vector<string> list = setup_bench(pos, args);
+ num = count_if(list.begin(), list.end(), [](const string& s) { return s.find("go ") == 0 || s.find("eval") == 0; });
+
+ TimePoint elapsed = now();
+
+ for (const auto& cmd : list)
+ {
+ istringstream is(cmd);
+ is >> skipws >> token;
+
+ if (token == "go" || token == "eval")
+ {
+ cerr << "\nPosition: " << cnt++ << '/' << num << " (" << pos.fen() << ")" << endl;
+ if (token == "go")
+ {
+ go(pos, is, states);
+ Threads.main()->wait_for_search_finished();
+ nodes += Threads.nodes_searched();
+ }
+ else
+ trace_eval(pos);
+ }
+ else if (token == "setoption") setoption(is);
+ else if (token == "position") position(pos, is, states);
+ else if (token == "ucinewgame") { Search::clear(); elapsed = now(); } // Search::clear() may take a while
+ }
+
+ elapsed = now() - elapsed + 1; // Ensure positivity to avoid a 'divide by zero'
+
+ dbg_print();
+
+ cerr << "\n==========================="
+ << "\nTotal time (ms) : " << elapsed
+ << "\nNodes searched : " << nodes
+ << "\nNodes/second : " << 1000 * nodes / elapsed << endl;
+ }
+
+ // The win rate model returns the probability of winning (in per mille units) given an
+ // eval and a game ply. It fits the LTC fishtest statistics rather accurately.
+ int win_rate_model(Value v, int ply) {
+
+ // The model only captures up to 240 plies, so limit the input and then rescale
+ double m = std::min(240, ply) / 64.0;
+
+ // The coefficients of a third-order polynomial fit is based on the fishtest data
+ // for two parameters that need to transform eval to the argument of a logistic
+ // function.
+ constexpr double as[] = { 0.38036525, -2.82015070, 23.17882135, 307.36768407};
+ constexpr double bs[] = { -2.29434733, 13.27689788, -14.26828904, 63.45318330 };
+
+ // Enforce that NormalizeToPawnValue corresponds to a 50% win rate at ply 64
+ static_assert(UCI::NormalizeToPawnValue == int(as[0] + as[1] + as[2] + as[3]));
+
+ double a = (((as[0] * m + as[1]) * m + as[2]) * m) + as[3];
+ double b = (((bs[0] * m + bs[1]) * m + bs[2]) * m) + bs[3];
+
+ // Transform the eval to centipawns with limited range
+ double x = std::clamp(double(v), -4000.0, 4000.0);
+
+ // Return the win rate in per mille units rounded to the nearest value
+ return int(0.5 + 1000 / (1 + std::exp((a - x) / b)));
+ }
+
+} // namespace
+
+
+/// UCI::loop() waits for a command from the stdin, parses it and then calls the appropriate
+/// function. It also intercepts an end-of-file (EOF) indication from the stdin to ensure a
+/// graceful exit if the GUI dies unexpectedly. When called with some command-line arguments,
+/// like running 'bench', the function returns immediately after the command is executed.
+/// In addition to the UCI ones, some additional debug commands are also supported.
+
+void UCI::loop(int argc, char* argv[]) {
+
+ Position pos;
+ string token, cmd;
+ StateListPtr states(new std::deque<StateInfo>(1));
+
+ pos.set(StartFEN, false, &states->back(), Threads.main());
+
+ for (int i = 1; i < argc; ++i)
+ cmd += std::string(argv[i]) + " ";
+
+ do {
+ if (argc == 1 && !getline(cin, cmd)) // Wait for an input or an end-of-file (EOF) indication
+ cmd = "quit";
+
+ istringstream is(cmd);
+
+ token.clear(); // Avoid a stale if getline() returns nothing or a blank line
+ is >> skipws >> token;
+
+ if ( token == "quit"
+ || token == "stop")
+ Threads.stop = true;
+
+ // The GUI sends 'ponderhit' to tell that the user has played the expected move.
+ // So, 'ponderhit' is sent if pondering was done on the same move that the user
+ // has played. The search should continue, but should also switch from pondering
+ // to the normal search.
+ else if (token == "ponderhit")
+ Threads.main()->ponder = false; // Switch to the normal search