mirror of
https://github.com/opelly27/Stockfish.git
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Linmiao Xu
8e75548f2a
Created by retraining the previous main net `nn-baff1edbea57.nnue` with: - some of the same options as before: ranger21, more WDL skipping - the addition of T80 nov+dec 2023 data - increasing loss by 15% when prediction is too high, up from 10% - use of torch.compile to speed up training by over 25% ```yaml experiment-name: 2560--S9-514G-T80-augtodec2023-more-wdl-skip-15p-more-loss-high-q-sk28 training-dataset: # https://github.com/official-stockfish/Stockfish/pull/4782 - /data/S6-514G-1ee1aba5ed.binpack - /data/test80-aug2023-2tb7p.v6.min.binpack - /data/test80-sep2023-2tb7p.binpack - /data/test80-oct2023-2tb7p.binpack - /data/test80-nov2023-2tb7p.binpack - /data/test80-dec2023-2tb7p.binpack early-fen-skipping: 28 start-from-engine-test-net: True nnue-pytorch-branch: linrock/nnue-pytorch/r21-more-wdl-skip-15p-more-loss-high-q-torch-compile num-epochs: 1000 lr: 4.375e-4 gamma: 0.995 start-lambda: 1.0 end-lambda: 0.7 ``` Epoch 819 trained with the above config led to this PR. Use of torch.compile decorators in nnue-pytorch model.py was found to speed up training by at least 25% on Ampere gpus when using recent pytorch compiled with cuda 12: https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch See recent main net PRs for more info on - ranger21 and more WDL skipping: https://github.com/official-stockfish/Stockfish/pull/4942 - increasing loss when Q is too high: https://github.com/official-stockfish/Stockfish/pull/4972 Training data can be found at: https://robotmoon.com/nnue-training-data/ Passed STC: https://tests.stockfishchess.org/tests/view/65cd76151d8e83c78bfd2f52 LLR: 2.98 (-2.94,2.94) <0.00,2.00> Total: 78336 W: 20504 L: 20115 D: 37717 Ptnml(0-2): 317, 9225, 19721, 9562, 343 Passed LTC: https://tests.stockfishchess.org/tests/view/65ce5be61d8e83c78bfd43e9 LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 41016 W: 10492 L: 10159 D: 20365 Ptnml(0-2): 22, 4533, 11071, 4854, 28 closes https://github.com/official-stockfish/Stockfish/pull/5056 Bench: 1351997
72 lines
2.1 KiB
C++
72 lines
2.1 KiB
C++
/*
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Stockfish, a UCI chess playing engine derived from Glaurung 2.1
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Copyright (C) 2004-2024 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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the Free Software Foundation, either version 3 of the License, or
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(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
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program. If not, see <http://www.gnu.org/licenses/>.
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*/
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#ifndef EVALUATE_H_INCLUDED
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#define EVALUATE_H_INCLUDED
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#include <string>
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#include <unordered_map>
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#include "types.h"
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namespace Stockfish {
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class Position;
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class OptionsMap;
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namespace Eval {
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std::string trace(Position& pos);
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int simple_eval(const Position& pos, Color c);
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Value evaluate(const Position& pos, int optimism);
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// The default net name MUST follow the format nn-[SHA256 first 12 digits].nnue
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// for the build process (profile-build and fishtest) to work. Do not change the
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// name of the macro, as it is used in the Makefile.
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#define EvalFileDefaultNameBig "nn-b1a57edbea57.nnue"
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#define EvalFileDefaultNameSmall "nn-baff1ede1f90.nnue"
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struct EvalFile {
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// UCI option name
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std::string optionName;
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// Default net name, will use one of the macros above
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std::string defaultName;
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// Selected net name, either via uci option or default
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std::string current;
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// Net description extracted from the net file
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std::string netDescription;
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};
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namespace NNUE {
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enum NetSize : int;
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using EvalFiles = std::unordered_map<Eval::NNUE::NetSize, EvalFile>;
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EvalFiles load_networks(const std::string&, const OptionsMap&, EvalFiles);
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void verify(const OptionsMap&, const EvalFiles&);
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} // namespace NNUE
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} // namespace Eval
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} // namespace Stockfish
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#endif // #ifndef EVALUATE_H_INCLUDED
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