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This net was arrived at from the previous net by greedily swapping neurons to build a permutation which maximizes the number of zero runs. The increase is roughly 1.5%.
Previous net used wrong encoding
Adds 0.2% sparsity
linrock
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Jun 29, 2023
Creating this net involved: - a 5-step training process from scratch - greedy permuting L1 weights with official-stockfish#4620 - leb128 compression with official-stockfish/nnue-pytorch#251 - greedy 2- and 3- cycle permuting with official-stockfish#4640 The 5 training steps were: 1. 400 epochs, lambda 1.0, lr 9.75e-4 UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9.binpack (178G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack large_gensfen_multipvdiff_100_d9.binpack ep399 chosen as start model for step2 2. 800 epochs, end-lambda 0.75, skip 16 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack ep559 chosen as start model for step3 3. 800 epochs, end-lambda 0.725, skip 20 leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr.binpack (223G) leela96-filt-v2.min.binpack dfrc99-16tb7p-eval-filt-v2.min.binpack test80-dec2022-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-jan2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-feb2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-mar2023-2tb7p-filter-v6.min.binpack test77-dec2021-16tb7p.no-db.min.binpack test78-janfeb2022-16tb7p.no-db.min.binpack test79-apr2022-16tb7p.no-db.min.binpack ep499 chosen as start model for step4 4. 800 epochs, end-lambda 0.7, skip 24 0dd1cebea57 dataset official-stockfish#4606 ep599 chosen as start model for step5 5. 800 epochs, end-lambda 0.7, skip 28 same dataset as step4 ep619 became nn-1b951f8b449d.nnue For the final step5 training: python3 easy_train.py \ --experiment-name L1-2048-S5-sameData-sk28-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9 \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack \ --early-fen-skipping 28 \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-2048 \ --engine-test-branch linrock/Stockfish/L1-2048 \ --start-from-engine-test-net False \ --start-from-model /data/experiments/experiment_L1-2048-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9/training/run_0/nn-epoch599.nnue --max_epoch 800 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 SF training data components for the step1 dataset: https://drive.google.com/drive/folders/1yLCEmioC3Xx9KQr4T7uB6GnLm5icAYGU Leela training data for steps 2-5 can be found at: https://robotmoon.com/nnue-training-data/ Due to larger L1 size and slower inference, the speed penalty loses elo at STC. Measurements from 100 bench runs at depth 13 with x86-64-modern on Intel Core i5-1038NG7 2.00GHz: sf_base = 1240730 +/- 3443 (95%) sf_test = 1153341 +/- 2832 (95%) diff = -87388 +/- 1616 (95%) speedup = -7.04330% +/- 0.130% (95%) Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch619.nnue : 21.1 +/- 3.2 Failed STC: https://tests.stockfishchess.org/tests/view/6498ee93dc7002ce609cf979 LLR: -2.95 (-2.94,2.94) <0.00,2.00> Total: 11680 W: 3058 L: 3299 D: 5323 Ptnml(0-2): 44, 1422, 3149, 1181, 44 LTC: https://tests.stockfishchess.org/tests/view/649b32f5dc7002ce609d20cf Elo: 0.68 ± 1.5 (95%) LOS: 80.5% Total: 40000 W: 10887 L: 10809 D: 18304 Ptnml(0-2): 36, 3938, 11958, 4048, 20 nElo: 1.50 ± 3.4 (95%) PairsRatio: 1.02 Passed VLTC 180+1.8: https://tests.stockfishchess.org/tests/view/64992b43dc7002ce609cfd20 LLR: 3.06 (-2.94,2.94) <0.00,2.00> Total: 38086 W: 10612 L: 10338 D: 17136 Ptnml(0-2): 9, 3316, 12115, 3598, 5 Passed VLTC SMP 60+0.6 th 8: https://tests.stockfishchess.org/tests/view/649a21fedc7002ce609d0c7d LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 38936 W: 11091 L: 10820 D: 17025 Ptnml(0-2): 1, 2948, 13305, 3207, 7 bench 2858591
linrock
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Jun 29, 2023
Creating this net involved: - a 5-step training process from scratch - greedy permuting L1 weights with official-stockfish#4620 - leb128 compression with official-stockfish/nnue-pytorch#251 - greedy 2- and 3- cycle permuting with official-stockfish#4640 The 5 training steps were: 1. 400 epochs, lambda 1.0, lr 9.75e-4 UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9.binpack (178G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack large_gensfen_multipvdiff_100_d9.binpack ep399 chosen as start model for step2 2. 800 epochs, end-lambda 0.75, skip 16 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack ep559 chosen as start model for step3 3. 800 epochs, end-lambda 0.725, skip 20 leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr.binpack (223G) leela96-filt-v2.min.binpack dfrc99-16tb7p-eval-filt-v2.min.binpack test80-dec2022-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-jan2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-feb2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-mar2023-2tb7p-filter-v6.min.binpack test77-dec2021-16tb7p.no-db.min.binpack test78-janfeb2022-16tb7p.no-db.min.binpack test79-apr2022-16tb7p.no-db.min.binpack ep499 chosen as start model for step4 4. 800 epochs, end-lambda 0.7, skip 24 0dd1cebea57 dataset official-stockfish#4606 ep599 chosen as start model for step5 5. 800 epochs, end-lambda 0.7, skip 28 same dataset as step4 ep619 became nn-1b951f8b449d.nnue For the final step5 training: python3 easy_train.py \ --experiment-name L1-2048-S5-sameData-sk28-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9 \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack \ --early-fen-skipping 28 \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-2048 \ --engine-test-branch linrock/Stockfish/L1-2048 \ --start-from-engine-test-net False \ --start-from-model /data/experiments/experiment_L1-2048-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9/training/run_0/nn-epoch599.nnue --max_epoch 800 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 SF training data components for the step1 dataset: https://drive.google.com/drive/folders/1yLCEmioC3Xx9KQr4T7uB6GnLm5icAYGU Leela training data for steps 2-5 can be found at: https://robotmoon.com/nnue-training-data/ Due to larger L1 size and slower inference, the speed penalty loses elo at STC. Measurements from 100 bench runs at depth 13 with x86-64-modern on Intel Core i5-1038NG7 2.00GHz: sf_base = 1240730 +/- 3443 (95%) sf_test = 1153341 +/- 2832 (95%) diff = -87388 +/- 1616 (95%) speedup = -7.04330% +/- 0.130% (95%) Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch619.nnue : 21.1 +/- 3.2 Failed STC: https://tests.stockfishchess.org/tests/view/6498ee93dc7002ce609cf979 LLR: -2.95 (-2.94,2.94) <0.00,2.00> Total: 11680 W: 3058 L: 3299 D: 5323 Ptnml(0-2): 44, 1422, 3149, 1181, 44 LTC: https://tests.stockfishchess.org/tests/view/649b32f5dc7002ce609d20cf Elo: 0.68 ± 1.5 (95%) LOS: 80.5% Total: 40000 W: 10887 L: 10809 D: 18304 Ptnml(0-2): 36, 3938, 11958, 4048, 20 nElo: 1.50 ± 3.4 (95%) PairsRatio: 1.02 Passed VLTC 180+1.8: https://tests.stockfishchess.org/tests/view/64992b43dc7002ce609cfd20 LLR: 3.06 (-2.94,2.94) <0.00,2.00> Total: 38086 W: 10612 L: 10338 D: 17136 Ptnml(0-2): 9, 3316, 12115, 3598, 5 Passed VLTC SMP 60+0.6 th 8: https://tests.stockfishchess.org/tests/view/649a21fedc7002ce609d0c7d LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 38936 W: 11091 L: 10820 D: 17025 Ptnml(0-2): 1, 2948, 13305, 3207, 7 bench 2858591
vondele
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Jul 1, 2023
Creating this net involved: - a 5-step training process from scratch - greedy permuting L1 weights with official-stockfish#4620 - leb128 compression with official-stockfish/nnue-pytorch#251 - greedy 2- and 3- cycle permuting with official-stockfish#4640 The 5 training steps were: 1. 400 epochs, lambda 1.0, lr 9.75e-4 UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9.binpack (178G) nodes5000pv2_UHO.binpack data_pv-2_diff-100_nodes-5000.binpack wrongIsRight_nodes5000pv2.binpack multinet_pv-2_diff-100_nodes-5000.binpack dfrc_n5000.binpack large_gensfen_multipvdiff_100_d9.binpack ep399 chosen as start model for step2 2. 800 epochs, end-lambda 0.75, skip 16 LeelaFarseer-T78juntoaugT79marT80dec.binpack (141G) T60T70wIsRightFarseerT60T74T75T76.binpack test78-junjulaug2022-16tb7p.no-db.min.binpack test79-mar2022-16tb7p.no-db.min.binpack test80-dec2022-16tb7p.no-db.min.binpack ep559 chosen as start model for step3 3. 800 epochs, end-lambda 0.725, skip 20 leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr.binpack (223G) leela96-filt-v2.min.binpack dfrc99-16tb7p-eval-filt-v2.min.binpack test80-dec2022-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-jan2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-feb2023-16tb7p-filter-v6-sk20.min-mar2023.binpack test80-mar2023-2tb7p-filter-v6.min.binpack test77-dec2021-16tb7p.no-db.min.binpack test78-janfeb2022-16tb7p.no-db.min.binpack test79-apr2022-16tb7p.no-db.min.binpack ep499 chosen as start model for step4 4. 800 epochs, end-lambda 0.7, skip 24 0dd1cebea57 dataset official-stockfish#4606 ep599 chosen as start model for step5 5. 800 epochs, end-lambda 0.7, skip 28 same dataset as step4 ep619 became nn-1b951f8b449d.nnue For the final step5 training: python3 easy_train.py \ --experiment-name L1-2048-S5-sameData-sk28-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9 \ --training-dataset /data/leela96-dfrc99-T60novdec-v2-T80juntonovjanfebT79aprmayT78jantosepT77dec-v6dd-T80apr.binpack \ --early-fen-skipping 28 \ --nnue-pytorch-branch linrock/nnue-pytorch/misc-fixes-L1-2048 \ --engine-test-branch linrock/Stockfish/L1-2048 \ --start-from-engine-test-net False \ --start-from-model /data/experiments/experiment_L1-2048-S4-0dd1cebea57-shuffled-S3-leela96-dfrc99-v2-T80dectofeb-sk20-mar-v6-T77decT78janfebT79apr-sk20-S2-LeelaFarseerT78T79T80-ep399-S1-UHOx2-wIsRight-multinet-dfrc-n5000-largeGensfen-d9/training/run_0/nn-epoch599.nnue --max_epoch 800 \ --lr 4.375e-4 \ --gamma 0.995 \ --start-lambda 1.0 \ --end-lambda 0.7 \ --tui False \ --seed $RANDOM \ --gpus 0 SF training data components for the step1 dataset: https://drive.google.com/drive/folders/1yLCEmioC3Xx9KQr4T7uB6GnLm5icAYGU Leela training data for steps 2-5 can be found at: https://robotmoon.com/nnue-training-data/ Due to larger L1 size and slower inference, the speed penalty loses elo at STC. Measurements from 100 bench runs at depth 13 with x86-64-modern on Intel Core i5-1038NG7 2.00GHz: sf_base = 1240730 +/- 3443 (95%) sf_test = 1153341 +/- 2832 (95%) diff = -87388 +/- 1616 (95%) speedup = -7.04330% +/- 0.130% (95%) Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch619.nnue : 21.1 +/- 3.2 Failed STC: https://tests.stockfishchess.org/tests/view/6498ee93dc7002ce609cf979 LLR: -2.95 (-2.94,2.94) <0.00,2.00> Total: 11680 W: 3058 L: 3299 D: 5323 Ptnml(0-2): 44, 1422, 3149, 1181, 44 LTC: https://tests.stockfishchess.org/tests/view/649b32f5dc7002ce609d20cf Elo: 0.68 ± 1.5 (95%) LOS: 80.5% Total: 40000 W: 10887 L: 10809 D: 18304 Ptnml(0-2): 36, 3938, 11958, 4048, 20 nElo: 1.50 ± 3.4 (95%) PairsRatio: 1.02 Passed VLTC 180+1.8: https://tests.stockfishchess.org/tests/view/64992b43dc7002ce609cfd20 LLR: 3.06 (-2.94,2.94) <0.00,2.00> Total: 38086 W: 10612 L: 10338 D: 17136 Ptnml(0-2): 9, 3316, 12115, 3598, 5 Passed VLTC SMP 60+0.6 th 8: https://tests.stockfishchess.org/tests/view/649a21fedc7002ce609d0c7d LLR: 2.95 (-2.94,2.94) <0.50,2.50> Total: 38936 W: 11091 L: 10820 D: 17025 Ptnml(0-2): 1, 2948, 13305, 3207, 7 closes official-stockfish#4646 Bench: 2505168
linrock
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Jul 6, 2023
This was a later epoch from the same experiment that led to the previous master net. After training, it was prepared the same way: 1. greedy permuting L1 weights with official-stockfish#4620 2. leb128 compression with official-stockfish/nnue-pytorch#251 3. greedy 2- and 3- cycle permuting with official-stockfish#4640 Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch739.nnue : 20.2 +/- 1.7 Passed STC: https://tests.stockfishchess.org/tests/view/64a050b33ee09aa549c4e4c8 LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 195552 W: 49977 L: 49430 D: 96145 Ptnml(0-2): 556, 22775, 50607, 23242, 596 Passed LTC: https://tests.stockfishchess.org/tests/view/64a127bd3ee09aa549c4f60c LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 235452 W: 60327 L: 59609 D: 115516 Ptnml(0-2): 119, 25173, 66426, 25887, 121 bench 2427629
vondele
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Jul 6, 2023
This was a later epoch from the same experiment that led to the previous master net. After training, it was prepared the same way: 1. greedy permuting L1 weights with official-stockfish#4620 2. leb128 compression with official-stockfish/nnue-pytorch#251 3. greedy 2- and 3- cycle permuting with official-stockfish#4640 Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch739.nnue : 20.2 +/- 1.7 Passed STC: https://tests.stockfishchess.org/tests/view/64a050b33ee09aa549c4e4c8 LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 195552 W: 49977 L: 49430 D: 96145 Ptnml(0-2): 556, 22775, 50607, 23242, 596 Passed LTC: https://tests.stockfishchess.org/tests/view/64a127bd3ee09aa549c4f60c LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 235452 W: 60327 L: 59609 D: 115516 Ptnml(0-2): 119, 25173, 66426, 25887, 121 bench 2427629
vondele
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Jul 6, 2023
This was a later epoch from the same experiment that led to the previous master net. After training, it was prepared the same way: 1. greedy permuting L1 weights with official-stockfish#4620 2. leb128 compression with official-stockfish/nnue-pytorch#251 3. greedy 2- and 3- cycle permuting with official-stockfish#4640 Local elo at 25k nodes per move (vs. L1-1536 nn-fdc1d0fe6455.nnue): nn-epoch739.nnue : 20.2 +/- 1.7 Passed STC: https://tests.stockfishchess.org/tests/view/64a050b33ee09aa549c4e4c8 LLR: 2.95 (-2.94,2.94) <0.00,2.00> Total: 195552 W: 49977 L: 49430 D: 96145 Ptnml(0-2): 556, 22775, 50607, 23242, 596 Passed LTC: https://tests.stockfishchess.org/tests/view/64a127bd3ee09aa549c4f60c LLR: 2.94 (-2.94,2.94) <0.50,2.50> Total: 235452 W: 60327 L: 59609 D: 115516 Ptnml(0-2): 119, 25173, 66426, 25887, 121 closes official-stockfish#4666 bench 2427629
linrock
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Sep 11, 2023
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 official-stockfish#4620 - greedy 2- and 3- cycle permuting with official-stockfish#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) 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[@]} 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 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 Ptnml(0-2): 78, 16577, 43238, 17120, 84 bench 1672490
linrock
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Sep 11, 2023
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 official-stockfish#4620 - greedy 2- and 3- cycle permuting with official-stockfish#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) # official-stockfish#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[@]} 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 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 Ptnml(0-2): 78, 16577, 43238, 17120, 84 bench 1672490
linrock
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Sep 11, 2023
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 official-stockfish#4620 - greedy 2- and 3- cycle permuting with official-stockfish#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) # official-stockfish#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 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 Ptnml(0-2): 78, 16577, 43238, 17120, 84 bench 1672490
Disservin
pushed a commit
that referenced
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Sep 11, 2023
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 #4620 - greedy 2- and 3- cycle permuting with #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) # #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 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 Ptnml(0-2): 78, 16577, 43238, 17120, 84 closes #4782 Bench: 1603079
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Activation data taken from https://drive.google.com/drive/folders/1Ec9YuuRx4N03GPnVPoQOW70eucOKngQe?usp=sharing
Permutation found using https://github.com/Ergodice/nnue-pytorch/blob/836387a0e5e690431d404158c46648710f13904d/ftperm.py
The algorithm greedily selects 2- and 3-cycles that can be permuted to increase the number of runs of zeroes. The percent of zero runs from the master net increased from 68.46 to 70.11 from 2-cycles and only increased to 70.32 when considering 3-cycles. Interestingly, allowing both halves of L1 to intermix when creating zero runs can give another 0.5% zero-run density increase with this method. Given how tiny the gain is when adding 3-cycles, I am led to believe that this is the limit for post-training permutation and that it may be beneficial to add sparsity awareness to nn training.
Speedup test courtesy of vondele
CPU: 16 x AMD Ryzen 9 3950X 16-Core Processor
Result of 50 runs
base (./stockfish.master ) = 1561556 +/- 5439
test (./stockfish.patch ) = 1575788 +/- 5427
diff = +14231 +/- 2636
speedup = +0.0091
P(speedup > 0) = 1.0000