mirror of
https://github.com/opelly27/Stockfish.git
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Tools transform option for filtering data for training nn-335a9b2d8a80.nnue (#4324)
Append hash of first master net trained with filter method Hardcode depth 6 and remove option to set depth Underscores for consistency Filter out standard startpos positions too
This commit is contained in:
Linmiao Xu
+225
-1
@@ -63,6 +63,13 @@ namespace Stockfish::Tools
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}
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};
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struct FilterParams
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{
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std::string input_filename = "in.binpack";
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std::string output_filename = "out.binpack";
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bool debug_print = false;
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};
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[[nodiscard]] std::int16_t nudge(NudgedStaticParams& params, std::int16_t static_eval_i16, std::int16_t deep_eval_i16)
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{
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auto saturate_i32_to_i16 = [](int v) {
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@@ -502,11 +509,228 @@ namespace Stockfish::Tools
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do_rescore(params);
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}
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void do_filter_data_335a9b2d8a80(FilterParams& params)
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{
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// TODO: Use SfenReader once it works correctly in sequential mode. See issue #271
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auto in = Tools::open_sfen_input_file(params.input_filename);
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auto readsome = [&in, mutex = std::mutex{}](int n) mutable -> PSVector {
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PSVector psv;
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psv.reserve(n);
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std::unique_lock lock(mutex);
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for (int i = 0; i < n; ++i)
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{
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auto ps_opt = in->next();
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if (ps_opt.has_value())
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{
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psv.emplace_back(*ps_opt);
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}
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else
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{
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break;
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}
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}
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return psv;
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};
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auto sfen_format = SfenOutputType::Binpack;
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auto out = SfenWriter(
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params.output_filename,
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Threads.size(),
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std::numeric_limits<std::uint64_t>::max(),
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sfen_format);
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// About Search::Limits
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// Be careful because this member variable is global and affects other threads.
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auto& limits = Search::Limits;
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// Make the search equivalent to the "go infinite" command. (Because it is troublesome if time management is done)
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limits.infinite = true;
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// Since PV is an obstacle when displayed, erase it.
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limits.silent = true;
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// If you use this, it will be compared with the accumulated nodes of each thread. Therefore, do not use it.
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limits.nodes = 0;
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// depth is also processed by the one passed as an argument of Tools::search().
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limits.depth = 0;
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std::atomic<std::uint64_t> num_processed = 0;
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std::atomic<std::uint64_t> num_standard_startpos = 0;
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std::atomic<std::uint64_t> num_position_in_check = 0;
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std::atomic<std::uint64_t> num_move_already_is_capture = 0;
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std::atomic<std::uint64_t> num_capture_or_promo_skipped_multipv_cap0 = 0;
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std::atomic<std::uint64_t> num_capture_or_promo_skipped_multipv_cap1 = 0;
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Threads.execute_with_workers([&](auto& th){
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Position& pos = th.rootPos;
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StateInfo si;
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const bool frc = Options["UCI_Chess960"];
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const bool debug_print = params.debug_print;
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for (;;)
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{
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PSVector psv = readsome(5000);
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if (psv.empty())
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break;
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for(auto& ps : psv)
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{
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pos.set_from_packed_sfen(ps.sfen, &si, &th, frc);
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bool should_skip_position = false;
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if (pos.checkers()) {
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// Skip if in check
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if (debug_print) {
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sync_cout << "[debug] " << pos.fen() << sync_endl
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<< "[debug] Position is in check" << sync_endl
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<< "[debug]" << sync_endl;
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}
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num_position_in_check.fetch_add(1);
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should_skip_position = true;
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} else if (pos.capture_or_promotion((Stockfish::Move)ps.move)) {
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// Skip if the provided move is already a capture or promotion
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if (debug_print) {
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sync_cout << "[debug] " << pos.fen() << sync_endl
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<< "[debug] Provided move is capture or promo: "
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<< UCI::move((Stockfish::Move)ps.move, false)
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<< sync_endl
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<< "[debug]" << sync_endl;
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}
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num_move_already_is_capture.fetch_add(1);
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should_skip_position = true;
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} else if (pos.fen() == "rnbqkbnr/pppppppp/8/8/8/8/PPPPPPPP/RNBQKBNR w KQkq - 0 1") {
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num_standard_startpos.fetch_add(1);
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should_skip_position = true;
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} else {
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auto [search_val, pvs] = Search::search(pos, 6, 2);
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if (!pvs.empty() && th.rootMoves.size() > 0) {
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auto best_move = th.rootMoves[0].pv[0];
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bool more_than_one_valid_move = th.rootMoves.size() > 1;
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if (debug_print) {
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sync_cout << "[debug] " << pos.fen() << sync_endl;
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sync_cout << "[debug] Main PV move: "
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<< UCI::move(best_move, false) << " "
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<< th.rootMoves[0].score << " " << sync_endl;
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if (more_than_one_valid_move) {
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sync_cout << "[debug] 2nd PV move: "
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<< UCI::move(th.rootMoves[1].pv[0], false) << " "
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<< th.rootMoves[1].score << " " << sync_endl;
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} else {
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sync_cout << "[debug] The only valid move" << sync_endl;
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}
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}
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if (pos.capture_or_promotion(best_move)) {
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// skip if multipv 1st line bestmove is a capture or promo
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if (debug_print) {
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sync_cout << "[debug] Move is capture or promo: " << UCI::move(best_move, false)
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<< sync_endl
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<< "[debug] 1st best move at depth 6 multipv 2" << sync_endl
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<< "[debug]" << sync_endl;
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}
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num_capture_or_promo_skipped_multipv_cap0.fetch_add(1);
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should_skip_position = true;
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} else if (more_than_one_valid_move && pos.capture_or_promotion(th.rootMoves[1].pv[0])) {
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// skip if multipv 2nd line bestmove is a capture or promo
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if (debug_print) {
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sync_cout << "[debug] Move is capture or promo: " << UCI::move(best_move, false)
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<< sync_endl
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<< "[debug] 2nd best move at depth 6 multipv 2" << sync_endl
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<< "[debug]" << sync_endl;
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}
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num_capture_or_promo_skipped_multipv_cap1.fetch_add(1);
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should_skip_position = true;
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}
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}
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}
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pos.sfen_pack(ps.sfen, false);
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// nnue-pytorch training data loader skips positions with score VALUE_NONE
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if (should_skip_position)
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ps.score = 32002; // VALUE_NONE
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ps.padding = 0;
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out.write(th.id(), ps);
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auto p = num_processed.fetch_add(1) + 1;
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if (p % 10000 == 0) {
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auto c = num_position_in_check.load();
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auto a = num_move_already_is_capture.load();
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auto s = num_standard_startpos.load();
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auto multipv_cap0 = num_capture_or_promo_skipped_multipv_cap0.load();
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auto multipv_cap1 = num_capture_or_promo_skipped_multipv_cap1.load();
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sync_cout << "Processed " << p << " positions. Skipped " << (c + a + s + multipv_cap0 + multipv_cap1) << " positions."
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<< sync_endl
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<< " Static filter: " << (a + c + s)
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<< " (capture or promo: " << a << ", in check: " << c << ", startpos: " << s << ")"
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<< sync_endl
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<< " MultiPV filter: " << (multipv_cap0 + multipv_cap1)
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<< " (cap0: " << multipv_cap0 << ", cap1: " << multipv_cap1 << ")"
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<< " depth 6 multipv 2" << sync_endl;
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}
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}
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}
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});
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Threads.wait_for_workers_finished();
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std::cout << "Finished.\n";
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}
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void do_filter_335a9b2d8a80(FilterParams& params)
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{
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if (ends_with(params.input_filename, ".binpack"))
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{
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do_filter_data_335a9b2d8a80(params);
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}
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else
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{
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std::cerr << "Invalid input file type.\n";
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}
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}
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void filter_335a9b2d8a80(std::istringstream& is)
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{
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FilterParams params{};
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while(true)
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{
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std::string token;
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is >> token;
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if (token == "")
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break;
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else if (token == "input_file")
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is >> params.input_filename;
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else if (token == "output_file")
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is >> params.output_filename;
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else if (token == "debug_print")
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is >> params.debug_print;
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else
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{
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std::cout << "ERROR: Unknown option " << token << ". Exiting...\n";
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return;
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}
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}
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std::cout << "Performing transform filter_335a9b2d8a80 with parameters:\n";
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std::cout << "input_file : " << params.input_filename << '\n';
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std::cout << "output_file : " << params.output_filename << '\n';
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std::cout << "debug_print : " << params.debug_print << '\n';
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std::cout << '\n';
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do_filter_335a9b2d8a80(params);
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}
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void transform(std::istringstream& is)
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{
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const std::map<std::string, CommandFunc> subcommands = {
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{ "nudged_static", &nudged_static },
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{ "rescore", &rescore }
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{ "rescore", &rescore },
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{ "filter_335a9b2d8a80", &filter_335a9b2d8a80 }
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};
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Eval::NNUE::init();
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