mirror of
https://github.com/sockspls/badfish
synced 2025-04-30 00:33:09 +00:00
5d81071953
Created from 2 distinct spsa tunes of the latest main net (nn-31337bea577c.nnue) and applying the params to the prior main net (nn-e8bac1c07a5a.nnue). This effectively reverts the modifications to output weights and biases in https://github.com/official-stockfish/Stockfish/pull/5509 SPSA: A: 6000, alpha: 0.602, gamma: 0.101 1st - 437 feature transformer biases where values are < 25 54k / 120k games at 180+1.8 https://tests.stockfishchess.org/tests/view/66af98ac4ff211be9d4edad0 nn-808259761cca.nnue 2nd - 208 L2 weights where values are zero 112k / 120k games at 180+1.8 https://tests.stockfishchess.org/tests/view/66b0c3074ff211be9d4edbe5 nn-a56cb8c3d477.nnue When creating the above 2 nets (nn-808259761cca.nnue, nn-a56cb8c3d477.nnue), spsa params were unintentionally applied to nn-e8bac1c07a5a.nnue rather than nn-31337bea577c.nnue due to an issue in a script that creates nets by applying spsa results to base nets. Since they both passed STC and were neutral or slightly positive at LTC, they were combined to see if the elo from each set of params was additive. The 2 nets can be merged on top of nn-e8bac1c07a5a.nnue with: https://github.com/linrock/nnue-tools/blob/90942d3/spsa/combine_nnue.py ``` python3 combine_nnue.py \ nn-e8bac1c07a5a.nnue \ nn-808259761cca.nnue \ nn-a56cb8c3d477.nnue ``` Merging yields nn-87caa003fc6a.nnue which was renamed to nn-1111cefa1111.nnue with an updated nnue-namer around 10x faster than before by: - using a prefix trie for efficient prefix matches - modifying 4 non-functional bytes near the end of the file instead of 2 https://github.com/linrock/nnue-namer Thanks to @MinetaS for pointing out in #nnue-dev what the non-functional bytes are: L3 is 32, 4 bytes for biases, 32 bytes for weights. (fc_2) So -38 and -37 are technically -2 and -1 of fc_1 (type AffineTransform<30, 32>) And since InputDimension is padded to 32 there are total 32 of 2 adjacent bytes padding. So yes, it's non-functional whatever values are there. It's possible to tweak bytes at -38 - 32 * N and -37 - 32 * N given N = 0 ... 31 The net renamed with the new method passed non-regression STC vs. the original net: https://tests.stockfishchess.org/tests/view/66c0f0a821503a509c13b332 To print the spsa params with nnue-pytorch: ``` import features from serialize import NNUEReader feature_set = features.get_feature_set_from_name("HalfKAv2_hm") with open("nn-31337bea577c.nnue", "rb") as f: model = NNUEReader(f, feature_set).model c_end = 16 for i,ft_bias in enumerate(model.input.bias.data[:3072]): value = int(ft_bias * 254) if abs(value) < 25: print(f"ftB[{i}],{value},-1024,1024,{c_end},0.0020") c_end = 6 for i in range(8): for j in range(32): for k in range(30): value = int(model.layer_stacks.l2.weight.data[32 * i + j, k] * 64) if value == 0: print(f"twoW[{i}][{j}][{k}],{value},-127,127,{c_end},0.0020") ``` New params found with the same method as: https://github.com/official-stockfish/Stockfish/pull/5459 Passed STC: https://tests.stockfishchess.org/tests/view/66b4d4464ff211be9d4edf6e LLR: 2.94 (-2.94,2.94) <0.00,2.00> Total: 136416 W: 35753 L: 35283 D: 65380 Ptnml(0-2): 510, 16159, 34416, 16597, 526 Passed LTC: https://tests.stockfishchess.org/tests/view/66b76e814ff211be9d4ee1cc LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 159336 W: 40753 L: 40178 D: 78405 Ptnml(0-2): 126, 17497, 43864, 18038, 143 closes https://github.com/official-stockfish/Stockfish/pull/5534 bench 1613043
56 lines
1.8 KiB
C++
56 lines
1.8 KiB
C++
/*
|
|
Stockfish, a UCI chess playing engine derived from Glaurung 2.1
|
|
Copyright (C) 2004-2024 The Stockfish developers (see AUTHORS file)
|
|
|
|
Stockfish is free software: you can redistribute it and/or modify
|
|
it under the terms of the GNU General Public License as published by
|
|
the Free Software Foundation, either version 3 of the License, or
|
|
(at your option) any later version.
|
|
|
|
Stockfish is distributed in the hope that it will be useful,
|
|
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
GNU General Public License for more details.
|
|
|
|
You should have received a copy of the GNU General Public License
|
|
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
|
*/
|
|
|
|
#ifndef EVALUATE_H_INCLUDED
|
|
#define EVALUATE_H_INCLUDED
|
|
|
|
#include <string>
|
|
|
|
#include "types.h"
|
|
|
|
namespace Stockfish {
|
|
|
|
class Position;
|
|
|
|
namespace Eval {
|
|
|
|
// The default net name MUST follow the format nn-[SHA256 first 12 digits].nnue
|
|
// for the build process (profile-build and fishtest) to work. Do not change the
|
|
// name of the macro or the location where this macro is defined, as it is used
|
|
// in the Makefile/Fishtest.
|
|
#define EvalFileDefaultNameBig "nn-1111cefa1111.nnue"
|
|
#define EvalFileDefaultNameSmall "nn-37f18f62d772.nnue"
|
|
|
|
namespace NNUE {
|
|
struct Networks;
|
|
struct AccumulatorCaches;
|
|
}
|
|
|
|
std::string trace(Position& pos, const Eval::NNUE::Networks& networks);
|
|
|
|
int simple_eval(const Position& pos, Color c);
|
|
bool use_smallnet(const Position& pos);
|
|
Value evaluate(const NNUE::Networks& networks,
|
|
const Position& pos,
|
|
Eval::NNUE::AccumulatorCaches& caches,
|
|
int optimism);
|
|
} // namespace Eval
|
|
|
|
} // namespace Stockfish
|
|
|
|
#endif // #ifndef EVALUATE_H_INCLUDED
|