Latest abrok Development Version September 11th Update default net to nn-1ee1aba5ed4c.nnue (SF The gift that keeps on giving

Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64

Author: Linmiao Xu
Date: Mon Sep 11 22:37:39 2023 +0200
Timestamp: 1694464659

Update default net to nn-1ee1aba5ed4c.nnue

Created by retraining the master net on a dataset composed by:
- adding Leela data from T60 jul-dec 2020, T77 nov 2021, T80 jun-jul 2023
- deduplicating and unminimizing parts of the dataset before interleaving

Trained initially with max epoch 800, then increased near the end of training
twice. First to 960, then 1200. After training, post-processing involved:
- greedy permuting L1 weights with https://github.com/official-stockfish/Stockfish/pull/4620
- greedy 2- and 3- cycle permuting with https://github.com/official-stockfish/Stockfish/pull/4640

python3 easy_train.py \
--experiment-name 2048-retrain-S6-sk28 \
--training-dataset /data/S6.binpack \
--early-fen-skipping 28 \
--start-from-engine-test-net True \
--max_epoch 1200 \
--lr 4.375e-4 \
--gamma 0.995 \
--start-lambda 1.0 \
--end-lambda 0.7 \
--tui False \
--seed $RANDOM \
--gpus 0

In the list of datasets below, periods in the filename represent the sequence of
steps applied to arrive at the particular binpack. For example:

test77-dec2021-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
1. test77 dec2021 data rescored with 16 TB of syzygy tablebases during data conversion
2. filtered with csv_filter_v6_dd.py - v6 filtering and deduplication in one step
3. minimized with the original mar2023 implementation of `minimize_binpack` in
the tools branch
4. unminimized by removing all positions with score == 32002 (`VALUE_NONE`)

Binpacks were:
- filtered with: https://github.com/linrock/nnue-data
- unminimized with: https://github.com/linrock/Stockfish/tree/tools-unminify
- deduplicated with: https://github.com/linrock/Stockfish/tree/tools-dd

DATASETS=(
leela96-filt-v2.min.unminimized.binpack
dfrc99-16tb7p-eval-filt-v2.min.unminimized.binpack

# most of the 0dd1cebea57 v6-dd dataset (without test80-jul2022)
# https://github.com/official-stockfish/Stockfish/pull/4606
test60-novdec2021-12tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test77-dec2021-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test78-jantomay2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test78-juntosep2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test79-apr2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test79-may2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test80-jun2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test80-aug2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test80-sep2022-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test80-oct2022-16tb7p.filter-v6-dd.min.binpack
test80-nov2022-16tb7p.filter-v6-dd.min.binpack
test80-jan2023-3of3-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack
test80-feb2023-16tb7p.filter-v6-dd.min-mar2023.unminimized.binpack

# older Leela data, recently converted
test60-octnovdec2020-2tb7p.min.unminimized.binpack
test60-julaugsep2020-2tb7p.min.binpack
test77-nov2021-2tb7p.min.dd.binpack

# newer Leela data
test80-mar2023-2tb7p.min.unminimized.binpack
test80-apr2023-2tb7p.filter-v6-sk16.min.unminimized.binpack
test80-may2023-2tb7p.min.dd.binpack
test80-jun2023-2tb7p.min.binpack
test80-jul2023-2tb7p.binpack
)
python3 interleave_binpacks.py ${DATASETS[@]} /data/S6.binpack

Training data can be found at:
https://robotmoon.com/nnue-training-data/

Local elo at 25k nodes per move:
nn-epoch1059 : 2.7 +/- 1.6

Passed STC:
https://tests.stockfishchess.org/tests/view/64fc8d705dab775b5359db42
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 168352 W: 43216 L: 42704 D: 82432 Elo +1.06
Ptnml(0-2): 599, 19672, 43134, 20160, 611

Passed LTC:
https://tests.stockfishchess.org/tests/view/64fd44a75dab775b5359f065
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 154194 W: 39436 L: 38881 D: 75877 Elo +1.25
Ptnml(0-2): 78, 16577, 43238, 17120, 84

closes https://github.com/official-stockfish/Stockfish/pull/4782

Bench: 1603079
see source

Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64

Author: Michael Chaly
Date: Mon Sep 11 22:36:26 2023 +0200
Timestamp: 1694464586

Do more futility pruning in qsearch

This patch introduces a third futility pruning heuristic in qsearch. The idea is
that the static exchange evaluation is much worse than the difference between
futility base and alpha. Thus we can assume that the probability of the move
being good enough to beat alpha is low so it can be pruned.

Passed STC:
https://tests.stockfishchess.org/tests/view/64fc982a5dab775b5359dc83
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 36576 W: 9484 L: 9170 D: 17922 Elo +2.98
Ptnml(0-2): 121, 4119, 9495, 4431, 122

Passed LTC:
https://tests.stockfishchess.org/tests/view/64fcc7935dab775b5359e1a9
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 135408 W: 34556 L: 34041 D: 66811 Elo +1.32
Ptnml(0-2): 56, 14462, 38165, 14953, 68

closes https://github.com/official-stockfish/Stockfish/pull/4781

Bench: 1330793
see source

_________________
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Victor Hugo

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