mirror of
https://github.com/opelly27/Stockfish.git
synced 2026-05-20 15:37:47 +00:00
Removed "#if 0" and "#if 1".
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+3
-21
@@ -166,7 +166,7 @@ namespace Learner
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output_file_stream.write(reinterpret_cast<const char*>(buf->data()), sizeof(PackedSfenValue) * buf->size());
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sfen_write_count += buf->size();
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#if 1
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// Add the processed number here, and if it exceeds save_every,
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// change the file name and reset this counter.
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sfen_write_count_current_file += buf->size();
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@@ -186,7 +186,7 @@ namespace Learner
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output_file_stream.open(new_filename, ios::out | ios::binary | ios::app);
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cout << endl << "output sfen file = " << new_filename << endl;
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}
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#endif
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// Output '.' every time when writing a game record.
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std::cout << ".";
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@@ -519,10 +519,6 @@ namespace Learner
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{
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// Write out one sfen.
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sfen_writer.write(thread_id, *it);
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#if 0
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pos.set_from_packed_sfen(it->sfen);
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cout << pos << "Win : " << it->is_win << " , " << it->score << endl;
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#endif
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}
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return quit;
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@@ -667,13 +663,12 @@ namespace Learner
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for (auto m : pv)
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{
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#if 1
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// There should be no illegal move. This is as a debugging precaution.
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if (!pos.pseudo_legal(m) || !pos.legal(m))
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{
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cout << "Error! : " << pos.fen() << m << endl;
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}
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#endif
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pos.do_move(m, states[ply++]);
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// Because the difference calculation of evaluate() cannot be
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@@ -803,19 +798,6 @@ namespace Learner
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// Save the move score for adjudication.
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move_hist_scores.push_back(search_value);
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#if 0
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dbg_hit_on(search_value == leaf_value);
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// gensfen depth 3 eval_limit 32000
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// Total 217749 Hits 203579 hit rate (%) 93.490
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// gensfen depth 6 eval_limit 32000
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// Total 78407 Hits 69190 hit rate (%) 88.245
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// gensfen depth 6 eval_limit 3000
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// Total 53879 Hits 43713 hit rate (%) 81.132
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// Problems such as pruning with moves in the substitution table.
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// This is a little uncomfortable as a teacher...
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#endif
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// If depth 0, pv is not obtained, so search again at depth 2.
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if (search_depth_min <= 0)
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{
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@@ -1163,11 +1163,6 @@ namespace Learner
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if (ps.gamePly < prng.rand(reduction_gameply))
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goto RETRY_READ;
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#if 0
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auto sfen = pos.sfen_unpack(ps.data);
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pos.set(sfen);
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#endif
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// ↑ Since it is slow when passing through sfen, I made a dedicated function.
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StateInfo si;
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const bool mirror = prng.rand(100) < mirror_percentage;
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if (pos.set_from_packed_sfen(ps.sfen, &si, th, mirror) != 0)
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@@ -1207,28 +1202,6 @@ namespace Learner
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// If it is the result of searching a completely different place, it may become noise.
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// It may be better not to study where the difference in evaluation values is too large.
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#if 0
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// If you do this, about 13% of the phases will be excluded
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// from the learning target. Good and bad are subtle.
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if (pv.size() >= 1 && (uint16_t)pv[0] != ps.move)
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{
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//dbg_hit_on(false);
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continue;
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}
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#endif
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#if 0
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// It may be better not to study where the difference in evaluation values is too large.
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// → It's okay because it passes the win rate function...
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// About 30% of the phases are out of the scope of learning...
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if (abs((int16_t)r.first - ps.score) >= Eval::PawnValue * 4)
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{
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//dbg_hit_on(false);
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continue;
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}
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//dbg_hit_on(true);
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#endif
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int ply = 0;
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// A helper function that adds the gradient to the current phase.
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@@ -1315,17 +1288,6 @@ namespace Learner
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// rewind the phase
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for (auto it = pv.rbegin(); it != pv.rend(); ++it)
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pos.undo_move(*it);
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#if 0
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// When adding the gradient to the root phase
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shallow_value =
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(rootColor == pos.side_to_move())
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? Eval::evaluate(pos)
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: -Eval::evaluate(pos);
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dj_dw = calc_grad(deep_value, shallow_value, ps);
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Eval::add_grad(pos, rootColor, dj_dw, without_kpp);
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#endif
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}
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}
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@@ -2058,18 +2020,6 @@ namespace Learner
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learn_think.best_nn_directory = std::string(Options["EvalDir"]);
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}
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#if 0
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// A test to give a gradient of 1.0 to the initial stage of Hirate.
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pos.set_hirate();
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cout << Eval::evaluate(pos) << endl;
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//Eval::print_eval_stat(pos);
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Eval::add_grad(pos, BLACK, 32.0, false);
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Eval::update_weights(1);
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pos.state()->sum.p[2][0] = VALUE_NOT_EVALUATED;
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cout << Eval::evaluate(pos) << endl;
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//Eval::print_eval_stat(pos);
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#endif
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cout << "init done." << endl;
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// Reflect other option settings.
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