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Author SHA1 Message Date
Robert Nurnberg
9b92ada935 Base WDL model on material count and normalize evals dynamically
This PR proposes to change the parameter dependence of Stockfish's
internal WDL model from full move counter to material count. In addition
it ensures that an evaluation of 100 centipawns always corresponds to a
50% win probability at fishtest LTC, whereas for master this holds only
at move number 32. See also
https://github.com/official-stockfish/Stockfish/pull/4920 and the
discussion therein.

The new model was fitted based on about 340M positions extracted from
5.6M fishtest LTC games from the last three weeks, involving SF versions
from e67cc979fd (SF 16.1) to current
master.

The involved commands are for
[WDL_model](https://github.com/official-stockfish/WDL_model) are:
```
./updateWDL.sh --firstrev e67cc979fd
python scoreWDL.py updateWDL.json --plot save --pgnName update_material.png --momType "material" --momTarget 58 --materialMin 10 --modelFitting optimizeProbability
```

The anchor `58` for the material count value was chosen to be as close
as possible to the observed average material count of fishtest LTC games
at move 32 (`43`), while not changing the value of
`NormalizeToPawnValue` compared to the move-based WDL model by more than
1.

The patch only affects the displayed cp and wdl values.

closes https://github.com/official-stockfish/Stockfish/pull/5121

No functional change
2024-03-20 16:29:35 +01:00
Disservin
134e6d7bb4 Consistent use of anonymous namespace
Also change `bindThisThread` to match the current code style for function naming.

closes https://github.com/official-stockfish/Stockfish/pull/5118

No functional change
2024-03-20 16:15:37 +01:00
Disservin
55df0ee009 Fix Raspberry Pi Compilation
Reported by @Torom over discord.

> dev build fails on Raspberry Pi 5 with clang

```
clang++ -o stockfish benchmark.o bitboard.o evaluate.o main.o misc.o movegen.o movepick.o position.o search.o thread.o timeman.o tt.o uci.o ucioption.o tune.o tbprobe.o nnue_misc.o half_ka_v2_hm.o network.o  -fprofile-instr-generate -latomic -lpthread  -Wall -Wcast-qual -fno-exceptions -std=c++17 -fprofile-instr-generate  -pedantic -Wextra -Wshadow -Wmissing-prototypes -Wconditional-uninitialized -DUSE_PTHREADS -DNDEBUG -O3 -funroll-loops -DIS_64BIT -DUSE_POPCNT -DUSE_NEON=8 -march=armv8.2-a+dotprod -DUSE_NEON_DOTPROD -DGIT_SHA=627974c9 -DGIT_DATE=20240312 -DARCH=armv8-dotprod -flto=full
/tmp/lto-llvm-e9300e.o: in function `_GLOBAL__sub_I_network.cpp':
ld-temp.o:(.text.startup+0x704c): relocation truncated to fit: R_AARCH64_LDST64_ABS_LO12_NC against symbol `gEmbeddedNNUEBigEnd' defined in .rodata section in /tmp/lto-llvm-e9300e.o
/usr/bin/ld: ld-temp.o:(.text.startup+0x704c): warning: one possible cause of this error is that the symbol is being referenced in the indicated code as if it had a larger alignment than was declared where it was defined
ld-temp.o:(.text.startup+0x7068): relocation truncated to fit: R_AARCH64_LDST64_ABS_LO12_NC against symbol `gEmbeddedNNUESmallEnd' defined in .rodata section in /tmp/lto-llvm-e9300e.o
/usr/bin/ld: ld-temp.o:(.text.startup+0x7068): warning: one possible cause of this error is that the symbol is being referenced in the indicated code as if it had a larger alignment than was declared where it was defined
clang: error: linker command failed with exit code 1 (use -v to see invocation)
make[2]: *** [Makefile:1051: stockfish] Error 1
make[2]: Leaving directory '/home/torsten/chess/Stockfish_master/src'
make[1]: *** [Makefile:1058: clang-profile-make] Error 2
make[1]: Leaving directory '/home/torsten/chess/Stockfish_master/src'
make: *** [Makefile:886: profile-build] Error 2
```

closes https://github.com/official-stockfish/Stockfish/pull/5106

No functional change
2024-03-12 19:09:50 +01:00
Disservin
1a26d698de Refactor Network Usage
Continuing from PR #4968, this update improves how Stockfish handles network
usage, making it easier to manage and modify networks in the future.

With the introduction of a dedicated Network class, creating networks has become
straightforward. See uci.cpp:
```cpp
NN::NetworkBig({EvalFileDefaultNameBig, "None", ""}, NN::embeddedNNUEBig)
```

The new `Network` encapsulates all network-related logic, significantly reducing
the complexity previously required to support multiple network types, such as
the distinction between small and big networks #4915.

Non-Regression STC:
https://tests.stockfishchess.org/tests/view/65edd26c0ec64f0526c43584
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 33760 W: 8887 L: 8661 D: 16212
Ptnml(0-2): 143, 3795, 8808, 3961, 173

Non-Regression SMP STC:
https://tests.stockfishchess.org/tests/view/65ed71970ec64f0526c42fdd
LLR: 2.96 (-2.94,2.94) <-1.75,0.25>
Total: 59088 W: 15121 L: 14931 D: 29036
Ptnml(0-2): 110, 6640, 15829, 6880, 85

Compiled with `make -j profile-build`
```
bash ./bench_parallel.sh ./stockfish ./stockfish-nnue 13 50

sf_base =  1568540 +/-   7637 (95%)
sf_test =  1573129 +/-   7301 (95%)
diff    =     4589 +/-   8720 (95%)
speedup = 0.29260% +/- 0.556% (95%)
```

Compiled with `make -j build`
```
bash ./bench_parallel.sh ./stockfish ./stockfish-nnue 13 50

sf_base =  1472653 +/-   7293 (95%)
sf_test =  1491928 +/-   7661 (95%)
diff    =    19275 +/-   7154 (95%)
speedup = 1.30886% +/- 0.486% (95%)
```

closes https://github.com/official-stockfish/Stockfish/pull/5100

No functional change
2024-03-12 16:41:08 +01:00
Muzhen Gaming
10e2732978 VVLTC search tune
Result of 32k games of tuning at 60+0.6 8-thread. Link to the tuning
attempt:
https://tests.stockfishchess.org/tests/view/65def7b04b19edc854ebdec8

Passed VVLTC first SPRT:
https://tests.stockfishchess.org/tests/view/65e51b53416ecd92c162ab7f
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 37570 W: 9613 L: 9342 D: 18615
Ptnml(0-2): 2, 3454, 11601, 3727, 1

Passed VVLTC second SPRT:
https://tests.stockfishchess.org/tests/view/65e87d1c0ec64f0526c3eb39
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 123158 W: 31463 L: 31006 D: 60689
Ptnml(0-2): 5, 11589, 37935, 12044, 6

Note: The small net and psqt-only thresholds have been moved to
evaluate.h. The reasoning is that these values are used in both
`evaluate.cpp` and `evaluate_nnue.cpp`, and thus unifying their usage
avoids inconsistencies during testing, where one occurrence is changed
without the other (this happened during the search tune SPRT).

closes https://github.com/official-stockfish/Stockfish/pull/5101

Bench: 1741218
2024-03-11 10:04:37 +01:00
Disservin
b6dfd6bd54 Assorted cleanups
- fix naming convention for `workingDirectory`
- use type alias for `EvalFiles` everywhere
- move `ponderMode` into `LimitsType`
- move limits parsing into standalone static function

closes https://github.com/official-stockfish/Stockfish/pull/5098

No functional change
2024-03-11 09:02:13 +01:00
mstembera
7831131591 Only evaluate the PSQT part of the small net for large evals.
Thanks to Viren6 for suggesting to set complexity to 0.

STC https://tests.stockfishchess.org/tests/view/65d7d6709b2da0226a5a203f
LLR: 2.92 (-2.94,2.94) <0.00,2.00>
Total: 328384 W: 85316 L: 84554 D: 158514
Ptnml(0-2): 1414, 39076, 82486, 39766, 1450

LTC https://tests.stockfishchess.org/tests/view/65dce6d290f639b028a54d2e
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 165162 W: 41918 L: 41330 D: 81914
Ptnml(0-2): 102, 18332, 45124, 18922, 101

closes https://github.com/official-stockfish/Stockfish/pull/5083

bench: 1504003
2024-03-03 15:29:58 +01:00
mstembera
9699f4f79a Fix the alignment of the transformer buffer
Fixes the issue mentioned in
584d9efedc (r138417600).
Thanks to @cj5716 and @peregrineshahin for
spotting this!

closes https://github.com/official-stockfish/Stockfish/pull/5042

No functional change
2024-02-09 19:06:25 +01:00
FauziAkram
59691d46a1 Assorted trivial cleanups
Renaming doubleExtensions variable to multiExtensions, since now we have also triple extensions.

Some extra cleanups.

Recent tests used to measure the elo worth:
https://tests.stockfishchess.org/tests/view/659fd0c379aa8af82b96abc3
https://tests.stockfishchess.org/tests/view/65a8f3da79aa8af82b9751e3
https://tests.stockfishchess.org/tests/view/65b51824c865510db0272740
https://tests.stockfishchess.org/tests/view/65b58fbfc865510db0272f5b

closes https://github.com/official-stockfish/Stockfish/pull/5032

No functional change
2024-02-09 19:06:24 +01:00
mstembera
32e46fc47f Remove some outdated SIMD functions
Since https://github.com/official-stockfish/Stockfish/pull/4391 the x2
SIMD functions no longer serve any useful purpose.

Passed non-regression STC:
https://tests.stockfishchess.org/tests/view/659cf42579aa8af82b966d55
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 67392 W: 17222 L: 17037 D: 33133
Ptnml(0-2): 207, 7668, 17762, 7851, 208

closes https://github.com/official-stockfish/Stockfish/pull/4974

No functional change
2024-01-17 18:04:29 +01:00
Disservin
a107910951 Refactor global variables
This aims to remove some of the annoying global structure which Stockfish has.

Overall there is no major elo regression to be expected.

Non regression SMP STC (paused, early version):
https://tests.stockfishchess.org/tests/view/65983d7979aa8af82b9608f1
LLR: 0.23 (-2.94,2.94) <-1.75,0.25>
Total: 76232 W: 19035 L: 19096 D: 38101
Ptnml(0-2): 92, 8735, 20515, 8690, 84

Non regression STC (early version):
https://tests.stockfishchess.org/tests/view/6595b3a479aa8af82b95da7f
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 185344 W: 47027 L: 46972 D: 91345
Ptnml(0-2): 571, 21285, 48943, 21264, 609

Non regression SMP STC:
https://tests.stockfishchess.org/tests/view/65a0715c79aa8af82b96b7e4
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 142936 W: 35761 L: 35662 D: 71513
Ptnml(0-2): 209, 16400, 38135, 16531, 193

These global structures/variables add hidden dependencies and allow data
to be mutable from where it shouldn't it be (i.e. options). They also
prevent Stockfish from internal selfplay, which would be a nice thing to
be able to do, i.e. instantiate two Stockfish instances and let them
play against each other. It will also allow us to make Stockfish a
library, which can be easier used on other platforms.

For consistency with the old search code, `thisThread` has been kept,
even though it is not strictly necessary anymore. This the first major
refactor of this kind (in recent time), and future changes are required,
to achieve the previously described goals. This includes cleaning up the
dependencies, transforming the network to be self contained and coming
up with a plan to deal with proper tablebase memory management (see
comments for more information on this).

The removal of these global structures has been discussed in parts with
Vondele and Sopel.

closes https://github.com/official-stockfish/Stockfish/pull/4968

No functional change
2024-01-13 19:40:53 +01:00
Disservin
99cdb920fc Cleanup Evalfile handling
This cleans up the EvalFile handling after the merge of #4915,
which has become a bit confusing on what it is actually doing.

closes https://github.com/official-stockfish/Stockfish/pull/4971

No functional change
2024-01-08 18:33:38 +01:00
Disservin
7c5e3f2865 Prefix abs with std:: 2024-01-07 21:41:52 +01:00
Linmiao Xu
f09adaa4a4 Update smallnet to nn-baff1ede1f90.nnue with wider eval range
Created by training an L1-128 net from scratch with a wider range of
evals in the training data and wld-fen-skipping disabled during
training. The differences in this training data compared to the first
dual nnue PR are:

- removal of all positions with 3 pieces
- when piece count >= 16, keep positions with simple eval above 750
- when piece count < 16, remove positions with simple eval above 3000

The asymmetric data filtering was meant to flatten the training data
piece count distribution, which was previously heavily skewed towards
positions with low piece counts.

Additionally, the simple eval range where the smallnet is used was
widened to cover more positions previously evaluated by the big net and
simple eval.

```yaml
experiment-name: 128--S1-hse-S7-v4-S3-v1-no-wld-skip

training-dataset:
  - /data/hse/S3/leela96-filt-v2.min.high-simple-eval-1k.binpack
  - /data/hse/S3/dfrc99-16tb7p-eval-filt-v2.min.high-simple-eval-1k.binpack
  - /data/hse/S3/test80-apr2022-16tb7p.min.high-simple-eval-1k.binpack

  - /data/hse/S7/test60-2020-2tb7p.v6-3072.high-simple-eval-v4.binpack
  - /data/hse/S7/test60-novdec2021-12tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack

  - /data/hse/S7/test77-nov2021-2tb7p.v6-3072.min.high-simple-eval-v4.binpack
  - /data/hse/S7/test77-dec2021-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack
  - /data/hse/S7/test77-jan2022-2tb7p.high-simple-eval-v4.binpack

  - /data/hse/S7/test78-jantomay2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack
  - /data/hse/S7/test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack

  - /data/hse/S7/test79-apr2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack
  - /data/hse/S7/test79-may2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack

  - /data/hse/S7/test80-may2022-16tb7p.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-jun2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-jul2022-16tb7p.v6-dd.min.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-aug2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-sep2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-oct2022-16tb7p.v6-dd.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-nov2022-16tb7p-v6-dd.min.high-simple-eval-v4.binpack

  - /data/hse/S7/test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-feb2023-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-mar2023-2tb7p.v6-sk16.min.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-apr2023-2tb7p-filter-v6-sk16.min.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-may2023-2tb7p.v6.min.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-jun2023-2tb7p.v6-3072.min.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-jul2023-2tb7p.v6-3072.min.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-aug2023-2tb7p.v6.min.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-sep2023-2tb7p.high-simple-eval-v4.binpack
  - /data/hse/S7/test80-oct2023-2tb7p.high-simple-eval-v4.binpack

wld-fen-skipping: False
start-from-engine-test-net: False

nnue-pytorch-branch: linrock/nnue-pytorch/L1-128
engine-test-branch: linrock/Stockfish/L1-128-nolazy
engine-base-branch: linrock/Stockfish/L1-128

num-epochs: 500
start-lambda: 1.0
end-lambda: 1.0
```

Experiment yaml configs converted to easy_train.sh commands with:
https://github.com/linrock/nnue-tools/blob/4339954/yaml_easy_train.py

Binpacks interleaved at training time with:
https://github.com/official-stockfish/nnue-pytorch/pull/259

FT weights permuted with 10k positions from fishpack32.binpack with:
https://github.com/official-stockfish/nnue-pytorch/pull/254

Data filtered for high simple eval positions (v4) with:
https://github.com/linrock/Stockfish/blob/b9c8440/src/tools/transform.cpp#L640-L675

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

Local elo at 25k nodes per move of
L1-128 smallnet (nnue-only eval) vs. L1-128 trained on standard S1 data:
nn-epoch319.nnue : -241.7 +/- 3.2

Passed STC vs. 36db936:
https://tests.stockfishchess.org/tests/view/6576b3484d789acf40aabbfe
LLR: 2.94 (-2.94,2.94) <0.00,2.00>
Total: 21920 W: 5680 L: 5381 D: 10859
Ptnml(0-2): 82, 2488, 5520, 2789, 81

Passed LTC vs. DualNNUE #4915:
https://tests.stockfishchess.org/tests/view/65775c034d789acf40aac7e3
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 147606 W: 36619 L: 36063 D: 74924
Ptnml(0-2): 98, 16591, 39891, 17103, 120

closes https://github.com/official-stockfish/Stockfish/pull/4919

Bench: 1438336
2024-01-07 21:20:15 +01:00
Linmiao Xu
584d9efedc Dual NNUE with L1-128 smallnet
Credit goes to @mstembera for:
- writing the code enabling dual NNUE:
  https://github.com/official-stockfish/Stockfish/pull/4898
- the idea of trying L1-128 trained exclusively on high simple eval
  positions

The L1-128 smallnet is:
- epoch 399 of a single-stage training from scratch
- trained only on positions from filtered data with high material
  difference
  - defined by abs(simple_eval) > 1000

```yaml
experiment-name: 128--S1-only-hse-v2

training-dataset:
  - /data/hse/S3/dfrc99-16tb7p-eval-filt-v2.min.high-simple-eval-1k.binpack
  - /data/hse/S3/leela96-filt-v2.min.high-simple-eval-1k.binpack
  - /data/hse/S3/test80-apr2022-16tb7p.min.high-simple-eval-1k.binpack

  - /data/hse/S7/test60-2020-2tb7p.v6-3072.high-simple-eval-1k.binpack
  - /data/hse/S7/test60-novdec2021-12tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack

  - /data/hse/S7/test77-nov2021-2tb7p.v6-3072.min.high-simple-eval-1k.binpack
  - /data/hse/S7/test77-dec2021-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack
  - /data/hse/S7/test77-jan2022-2tb7p.high-simple-eval-1k.binpack

  - /data/hse/S7/test78-jantomay2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack
  - /data/hse/S7/test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack

  - /data/hse/S7/test79-apr2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack
  - /data/hse/S7/test79-may2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack

  # T80 2022
  - /data/hse/S7/test80-may2022-16tb7p.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-jun2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-jul2022-16tb7p.v6-dd.min.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-aug2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-sep2022-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-oct2022-16tb7p.v6-dd.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-nov2022-16tb7p-v6-dd.min.high-simple-eval-1k.binpack

  # T80 2023
  - /data/hse/S7/test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-feb2023-16tb7p-filter-v6-dd.min-mar2023.unmin.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-mar2023-2tb7p.v6-sk16.min.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-apr2023-2tb7p-filter-v6-sk16.min.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-may2023-2tb7p.v6.min.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-jun2023-2tb7p.v6-3072.min.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-jul2023-2tb7p.v6-3072.min.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-aug2023-2tb7p.v6.min.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-sep2023-2tb7p.high-simple-eval-1k.binpack
  - /data/hse/S7/test80-oct2023-2tb7p.high-simple-eval-1k.binpack

start-from-engine-test-net: False

nnue-pytorch-branch: linrock/nnue-pytorch/L1-128
engine-test-branch: linrock/Stockfish/L1-128-nolazy
engine-base-branch: linrock/Stockfish/L1-128

num-epochs: 500
lambda: 1.0
```

Experiment yaml configs converted to easy_train.sh commands with:
https://github.com/linrock/nnue-tools/blob/4339954/yaml_easy_train.py

Binpacks interleaved at training time with:
https://github.com/official-stockfish/nnue-pytorch/pull/259

Data filtered for high simple eval positions with:
https://github.com/linrock/nnue-data/blob/32d6a68/filter_high_simple_eval_plain.py
https://github.com/linrock/Stockfish/blob/61dbfe/src/tools/transform.cpp#L626-L655

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

Local elo at 25k nodes per move of
L1-128 smallnet (nnue-only eval) vs. L1-128 trained on standard S1 data:
nn-epoch399.nnue : -318.1 +/- 2.1

Passed STC:
https://tests.stockfishchess.org/tests/view/6574cb9d95ea6ba1fcd49e3b
LLR: 2.93 (-2.94,2.94) <0.00,2.00>
Total: 62432 W: 15875 L: 15521 D: 31036
Ptnml(0-2): 177, 7331, 15872, 7633, 203

Passed LTC:
https://tests.stockfishchess.org/tests/view/6575da2d4d789acf40aaac6e
LLR: 2.94 (-2.94,2.94) <0.50,2.50>
Total: 64830 W: 16118 L: 15738 D: 32974
Ptnml(0-2): 43, 7129, 17697, 7497, 49

closes https://github.com/official-stockfish/Stockfish/pulls

Bench: 1330050

Co-Authored-By: mstembera <5421953+mstembera@users.noreply.github.com>
2024-01-07 21:15:52 +01:00
FauziAkram
8b4583bce7 Remove redundant int cast
Remove a redundant int cast in the calculation of fwdOut. The variable
OutputType is already defined as std::int32_t, which is an integer type, making
the cast unnecessary.

closes https://github.com/official-stockfish/Stockfish/pull/4961

No functional change
2024-01-04 15:56:53 +01:00
Disservin
b987d4f033 Use type aliases instead of enums for Value types
The primary rationale behind this lies in the fact that enums were not
originally designed to be employed in the manner we currently utilize them.

The Value enum was used like a type alias throughout the code and was often
misused. Furthermore, changing the underlying size of the enum to int16_t broke
everything, mostly because of the operator overloads for the Value enum, were
causing data to be truncated. Since Value is now a type alias, the operator
overloads are no longer required.

Passed Non-Regression STC:
https://tests.stockfishchess.org/tests/view/6593b8bb79aa8af82b95b401
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 235296 W: 59919 L: 59917 D: 115460
Ptnml(0-2): 743, 27085, 62054, 26959, 807

closes https://github.com/official-stockfish/Stockfish/pull/4960

No functional change
2024-01-04 15:54:23 +01:00
Disservin
444f03ee95 Update copyright year
closes https://github.com/official-stockfish/Stockfish/pull/4954

No functional change
2024-01-04 15:47:10 +01:00
FauziAkram
833a2e2bc0 Cleanup comments
Tests used to derive some Elo worth comments:
https://tests.stockfishchess.org/tests/view/656a7f4e136acbc573555a31
https://tests.stockfishchess.org/tests/view/6585fb455457644dc984620f

closes https://github.com/official-stockfish/Stockfish/pull/4945

No functional change
2023-12-31 19:54:27 +01:00
FauziAkram
a069a1bbbf Use std::abs over abs
closes https://github.com/official-stockfish/Stockfish/pull/4926
closes https://github.com/official-stockfish/Stockfish/pull/4909

No functional change

Co-Authored-By: fffelix-huang <72808219+fffelix-huang@users.noreply.github.com>
2023-12-19 18:22:10 +01:00
Joost VandeVondele
ec02714b62 Cleanup comments and some code reorg.
passed STC:
https://tests.stockfishchess.org/tests/view/6536dc7dcc309ae83955b04d
LLR: 2.93 (-2.94,2.94) <-1.75,0.25>
Total: 58048 W: 14693 L: 14501 D: 28854
Ptnml(0-2): 200, 6399, 15595, 6669, 161

closes https://github.com/official-stockfish/Stockfish/pull/4846

No functional change
2023-10-24 17:43:05 +02:00
cj5716
d6a5c2b085 Small formatting improvements
Changes some C style casts to C++ style, and fixes some incorrect comments and variable names.

closes #4845

No functional change
2023-10-24 17:42:13 +02:00
Disservin
a105978bbd remove blank line between function and it's description
- remove the blank line between the declaration of the function and it's
  comment, leads to better IDE support when hovering over a function to see it's
  description
- remove the unnecessary duplication of the function name in the functions
  description
- slightly refactored code for lsb, msb in bitboard.h There are still a few
  things we can be improved later on, move the description of a function where
  it was declared (instead of implemented) and add descriptions to functions
  which are behind macros ifdefs

closes https://github.com/official-stockfish/Stockfish/pull/4840

No functional change
2023-10-23 20:39:48 +02:00
Disservin
2d0237db3f add clang-format
This introduces clang-format to enforce a consistent code style for Stockfish.

Having a documented and consistent style across the code will make contributing easier
for new developers, and will make larger changes to the codebase easier to make.

To facilitate formatting, this PR includes a Makefile target (`make format`) to format the code,
this requires clang-format (version 17 currently) to be installed locally.

Installing clang-format is straightforward on most OS and distros
(e.g. with https://apt.llvm.org/, brew install clang-format, etc), as this is part of quite commonly
used suite of tools and compilers (llvm / clang).

Additionally, a CI action is present that will verify if the code requires formatting,
and comment on the PR as needed. Initially, correct formatting is not required, it will be
done by maintainers as part of the merge or in later commits, but obviously this is encouraged.

fixes https://github.com/official-stockfish/Stockfish/issues/3608
closes https://github.com/official-stockfish/Stockfish/pull/4790

Co-Authored-By: Joost VandeVondele <Joost.VandeVondele@gmail.com>
2023-10-22 16:06:27 +02:00
mstembera
d3d0c69dc1 Remove outdated Tile naming.
cleanup variable naming after  #4816

closes #4833

No functional change
2023-10-21 10:28:55 +02:00
FauziAkram
edb4ab924f Standardize Comments
use double slashes (//) only for comments.

closes #4820

No functional change.
2023-10-21 10:25:03 +02:00
mstembera
c17a657b04 Optimize the most common update accumalator cases w/o tiling
In the most common case where we only update a single state
it's faster to not use temporary accumulation registers and tiling.
(Also includes a couple of small cleanups.)

passed STC
https://tests.stockfishchess.org/tests/view/651918e3cff46e538ee0023b
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 34944 W: 8989 L: 8687 D: 17268
Ptnml(0-2): 88, 3743, 9512, 4037, 92

A simpler version
https://tests.stockfishchess.org/tests/view/65190dfacff46e538ee00155
also passed but this version is stronger still
https://tests.stockfishchess.org/tests/view/6519b95fcff46e538ee00fa2

closes https://github.com/official-stockfish/Stockfish/pull/4816

No functional change
2023-10-08 07:42:39 +02:00
mstembera
8a912951de Remove handcrafted MMX code
too small a benefit to maintain this old target

closes https://github.com/official-stockfish/Stockfish/pull/4804

No functional change
2023-10-08 07:37:01 +02:00
Sebastian Buchwald
4f0fecad8a Use C++17 variable templates for type traits
The C++17 variable templates are slightly more readable and allow us to
remove the typename keyword in a few cases.

closes https://github.com/official-stockfish/Stockfish/pull/4806

No functional change
2023-09-29 22:22:40 +02:00
Linmiao Xu
70ba9de85c Update NNUE architecture to SFNNv8: L1-2560 nn-ac1dbea57aa3.nnue
Creating this net involved:
- a 6-stage training process from scratch. The datasets used in stages 1-5 were fully minimized.
- permuting L1 weights with https://github.com/official-stockfish/nnue-pytorch/pull/254

A strong epoch after each training stage was chosen for the next. The 6 stages were:

```
1. 400 epochs, lambda 1.0, default LR and gamma
   UHOx2-wIsRight-multinet-dfrc-n5000 (135G)
     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

2. 800 epochs, end-lambda 0.75, LR 4.375e-4, gamma 0.995, skip 12
   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

3. 800 epochs, end-lambda 0.725, LR 4.375e-4, gamma 0.995, skip 20
   leela93-v1-dfrc99-v2-T78juntosepT80jan-v6dd-T78janfebT79aprT80aprmay.min.binpack
     leela93-filt-v1.min.binpack
     dfrc99-16tb7p-filt-v2.min.binpack
     test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack
     test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack
     test78-janfeb2022-16tb7p.min.binpack
     test79-apr2022-16tb7p.min.binpack
     test80-apr2022-16tb7p.min.binpack
     test80-may2022-16tb7p.min.binpack

4. 800 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 24
   leela96-dfrc99-v2-T78juntosepT79mayT80junsepnovjan-v6dd-T80mar23-v6-T60novdecT77decT78aprmayT79aprT80may23.min.binpack
     leela96-filt-v2.min.binpack
     dfrc99-16tb7p-filt-v2.min.binpack
     test78-juntosep2022-16tb7p-filter-v6-dd.min-mar2023.binpack
     test79-may2022-16tb7p.filter-v6-dd.min.binpack
     test80-jun2022-16tb7p.filter-v6-dd.min.binpack
     test80-sep2022-16tb7p.filter-v6-dd.min.binpack
     test80-nov2022-16tb7p.filter-v6-dd.min.binpack
     test80-jan2023-3of3-16tb7p-filter-v6-dd.min-mar2023.binpack
     test80-mar2023-2tb7p.v6-sk16.min.binpack
     test60-novdec2021-16tb7p.min.binpack
     test77-dec2021-16tb7p.min.binpack
     test78-aprmay2022-16tb7p.min.binpack
     test79-apr2022-16tb7p.min.binpack
     test80-may2023-2tb7p.min.binpack

5. 960 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28
   Increased max-epoch to 960 near the end of the first 800 epochs
   5af11540bbfe dataset: https://github.com/official-stockfish/Stockfish/pull/4635

6. 1000 epochs, end-lambda 0.7, LR 4.375e-4, gamma 0.995, skip 28
   Increased max-epoch to 1000 near the end of the first 800 epochs
   1ee1aba5ed dataset: https://github.com/official-stockfish/Stockfish/pull/4782
```

L1 weights permuted with:
```bash
python3 serialize.py $nnue $nnue_permuted \
  --features=HalfKAv2_hm \
  --ft_optimize \
  --ft_optimize_data=/data/fishpack32.binpack \
  --ft_optimize_count=10000
```

Speed measurements from 100 bench runs at depth 13 with profile-build x86-64-avx2:
```
sf_base =  1329051 +/-   2224 (95%)
sf_test =  1163344 +/-   2992 (95%)
diff    =  -165706 +/-   4913 (95%)
speedup = -12.46807% +/- 0.370% (95%)
```

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

Local elo at 25k nodes per move (vs. L1-2048 nn-1ee1aba5ed4c.nnue)
ep959 : 16.2 +/- 2.3

Failed 10+0.1 STC:
https://tests.stockfishchess.org/tests/view/6501beee2cd016da89abab21
LLR: -2.92 (-2.94,2.94) <0.00,2.00>
Total: 13184 W: 3285 L: 3535 D: 6364
Ptnml(0-2): 85, 1662, 3334, 1440, 71

Failed 180+1.8 VLTC:
https://tests.stockfishchess.org/tests/view/6505cf9a72620bc881ea908e
LLR: -2.94 (-2.94,2.94) <0.00,2.00>
Total: 64248 W: 16224 L: 16374 D: 31650
Ptnml(0-2): 26, 6788, 18640, 6650, 20

Passed 60+0.6 th 8 VLTC SMP (STC bounds):
https://tests.stockfishchess.org/tests/view/65084a4618698b74c2e541dc
LLR: 2.95 (-2.94,2.94) <0.00,2.00>
Total: 90630 W: 23372 L: 23033 D: 44225
Ptnml(0-2): 13, 8490, 27968, 8833, 11

Passed 60+0.6 th 8 VLTC SMP:
https://tests.stockfishchess.org/tests/view/6501d45d2cd016da89abacdb
LLR: 2.95 (-2.94,2.94) <0.50,2.50>
Total: 137804 W: 35764 L: 35276 D: 66764
Ptnml(0-2): 31, 13006, 42326, 13522, 17

closes https://github.com/official-stockfish/Stockfish/pull/4795

bench 1246812
2023-09-22 19:26:16 +02:00
mstembera
95fe2b9a9d Reduce SIMD register count from 32 to 16
in the case of avx512 and vnni512 archs.

Up to 17% speedup, depending on the compiler, e.g.

```
AMD pro 7840u (zen4 phoenix apu 4nm)
bash bench_parallel.sh ./stockfish_avx512_gcc13 ./stockfish_avx512_pr_gcc13 20 10
sf_base =  1077737 +/-   8446 (95%)
sf_test =  1264268 +/-   8543 (95%)
diff    =   186531 +/-   4280 (95%)
speedup =  17.308% +/- 0.397% (95%)
```

Prior to this patch, it appears gcc spills registers.

closes https://github.com/official-stockfish/Stockfish/pull/4796

No functional change
2023-09-22 19:15:34 +02:00
cj5716
fce4cc1829 Make casting styles consistent
Make casting styles consistent with the rest of the code.

closes https://github.com/official-stockfish/Stockfish/pull/4793

No functional change
2023-09-22 19:14:29 +02:00
mstembera
97f706ecc1 Sparse impl of affine_transform_non_ssse3()
deal with the general case

About a 8.6% speedup (for general arch)

Results for 200 tests for each version:

            Base      Test      Diff
    Mean    141741    153998    -12257
    StDev   2990      3042      3742

p-value: 0.999
speedup: 0.086

closes https://github.com/official-stockfish/Stockfish/pull/4786

No functional change
2023-09-22 19:03:47 +02:00
Tomasz Sobczyk
1461d861c8 Prevent usage of AVX-512 for the last layer.
Add more static checks regarding the SIMD width match.

STC: https://tests.stockfishchess.org/tests/view/64f5c568a9bc5a78c669e70e
LLR: 2.95 (-2.94,2.94) <-1.75,0.25>
Total: 125216 W: 31756 L: 31636 D: 61824
Ptnml(0-2): 327, 13993, 33848, 14113, 327

Fixes a bug introduced in 2f2f45f, where with AVX-512 the weights and input to
the last layer were being read out of bounds. Now AVX-512 is only used for the
layers it can be used for. Additional static assertions have been added to
prevent more errors like this in the future.

closes https://github.com/official-stockfish/Stockfish/pull/4773

No functional change
2023-09-11 22:11:30 +02:00
Disservin
3c0e86a91e Cleanup includes
Reorder a few includes, include "position.h" where it was previously missing
and apply include-what-you-use suggestions. Also make the order of the includes
consistent, in the following way:

1. Related header (for .cpp files)
2. A blank line
3. C/C++ headers
4. A blank line
5. All other header files

closes https://github.com/official-stockfish/Stockfish/pull/4763
fixes https://github.com/official-stockfish/Stockfish/issues/4707

No functional change
2023-09-03 08:24:51 +02:00
Gian-Carlo Pascutto
c6f62363a6 Simplify Square Clipped ReLU code.
Squared numbers are never negative, so barring any wraparound there
is no need to clamp to 0. From reading the code, there's no obvious
way to get wraparound, so the entire operation can be simplified
away. Updated original truncated code comments to be sensible.

Verified by running ./stockfish bench 128 1 24 and by the following test:

STC: https://tests.stockfishchess.org/tests/view/64da4db95b17f7c21c0eabe7
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 60224 W: 15425 L: 15236 D: 29563
Ptnml(0-2): 195, 6576, 16382, 6763, 196

closes https://github.com/official-stockfish/Stockfish/pull/4751

No functional change
2023-08-22 11:14:19 +02:00
Matthies
9abef246a9 Allow compilation on Raspi (for ARMv8)
Current master fails to compile for ARMv8 on Raspi cause gcc (version 10.2.1)
does not like to cast between signed and unsigned vector types. This patch
fixes it by using unsigned vector pointer for ARM to avoid implicite cast.

closes https://github.com/official-stockfish/Stockfish/pull/4752

No functional change
2023-08-22 10:43:51 +02:00
Joost VandeVondele
8192945870 Improve testing coverage, remove unused code
a) Add further tests to CI to cover most features. This uncovered a potential race
in case setoption was sent between two searches. As the UCI protocol requires
this sent to be went the engine is not searching, setoption now ensures that
this is the case.

b) Remove some unused code

closes https://github.com/official-stockfish/Stockfish/pull/4730

No functional change
2023-08-11 19:27:46 +02:00
AndrovT
a6d9a302b8 Implement AffineTransformSparseInput for armv8
Implements AffineTransformSparseInput layer for the NNUE evaluation
for the armv8 and armv8-dotprod architectures. We measured some nice
speed improvements via 10 runs of our benchmark:

armv8, Cortex-X1                  :   18.5% speed-up
armv8, Cortex-A76                 :   13.2% speed-up
armv8-dotprod, Cortex-X1          :   27.1% speed-up
armv8-dotprod, Cortex-A76         :   12.1% speed-up
armv8, Cortex-A72, Raspberry Pi 4 :    8.2% speed-up (thanks Torom!)

closes https://github.com/official-stockfish/Stockfish/pull/4719

No functional change
2023-08-06 21:22:37 +02:00
Stéphane Nicolet
f84eb1f3ef Improve some comments
- clarify the examples for the bench command
- typo  in search.cpp

closes https://github.com/official-stockfish/Stockfish/pull/4710

No functional change
2023-07-28 23:38:49 +02:00
mstembera
cb22520a9c Remove unused return type from propagate()
Also make two get_weight_index() static methods constexpr, for
consistency with the other static get_hash_value() method right above.
Tested for speed by user Torom (thanks).

closes https://github.com/official-stockfish/Stockfish/pull/4708

No functional change
2023-07-28 23:24:42 +02:00
mstembera
1444837887 Remove inline assembly
closes https://github.com/official-stockfish/Stockfish/pull/4698

No functional change
2023-07-19 21:39:51 +02:00
Joost VandeVondele
e8a5c64988 Consolidate to centipawns conversion
avoid doing this calculations in multiple places.

closes https://github.com/official-stockfish/Stockfish/pull/4686

No functional change
2023-07-16 15:14:50 +02:00
AndrovT
a42ab95e1f remove large input specialization
Removes unused large input specialization for dense affine transform. It has been obsolete since #4612 was merged.

closes https://github.com/official-stockfish/Stockfish/pull/4684

No functional change
2023-07-16 15:12:21 +02:00
mstembera
529d3be8e2 More simplifications and cleanup in affine_transform_sparse_input.h
closes https://github.com/official-stockfish/Stockfish/pull/4677

No functional change
2023-07-13 08:20:33 +02:00
Joost VandeVondele
af110e02ec Remove classical evaluation
since the introduction of NNUE (first released with Stockfish 12), we
have maintained the classical evaluation as part of SF in frozen form.
The idea that this code could lead to further inputs to the NN or
search did not materialize. Now, after five releases, this PR removes
the classical evaluation from SF. Even though this evaluation is
probably the best of its class, it has become unimportant for the
engine's strength, and there is little need to maintain this
code (roughly 25% of SF) going forward, or to expend resources on
trying to improve its integration in the NNUE eval.

Indeed, it had still a very limited use in the current SF, namely
for the evaluation of positions that are nearly decided based on
material difference, where the speed of the classical evaluation
outweights its inaccuracies. This impact on strength is small,
roughly 2Elo, and probably decreasing in importance as the TC grows.

Potentially, removal of this code could lead to the development of
techniques to have faster, but less accurate NN evaluation,
for certain positions.

STC
https://tests.stockfishchess.org/tests/view/64a320173ee09aa549c52157
Elo: -2.35 ± 1.1 (95%) LOS: 0.0%
Total: 100000 W: 24916 L: 25592 D: 49492
Ptnml(0-2): 287, 12123, 25841, 11477, 272
nElo: -4.62 ± 2.2 (95%) PairsRatio: 0.95

LTC
https://tests.stockfishchess.org/tests/view/64a320293ee09aa549c5215b
 Elo: -1.74 ± 1.0 (95%) LOS: 0.0%
Total: 100000 W: 25010 L: 25512 D: 49478
Ptnml(0-2): 44, 11069, 28270, 10579, 38
nElo: -3.72 ± 2.2 (95%) PairsRatio: 0.96

VLTC SMP
https://tests.stockfishchess.org/tests/view/64a3207c3ee09aa549c52168
 Elo: -1.70 ± 0.9 (95%) LOS: 0.0%
Total: 100000 W: 25673 L: 26162 D: 48165
Ptnml(0-2): 8, 9455, 31569, 8954, 14
nElo: -3.95 ± 2.2 (95%) PairsRatio: 0.95

closes https://github.com/official-stockfish/Stockfish/pull/4674

Bench: 1444646
2023-07-11 22:56:49 +02:00
mstembera
f8e65d82eb Simplify away lookup_count.
https://tests.stockfishchess.org/tests/view/64a3c1a93ee09aa549c53167
LLR: 2.94 (-2.94,2.94) <-1.75,0.25>
Total: 32832 W: 8497 L: 8280 D: 16055
Ptnml(0-2): 80, 3544, 8967, 3729, 96

closes https://github.com/official-stockfish/Stockfish/pull/4662

No functional change
2023-07-06 23:02:11 +02:00
mstembera
80564bcfcd Simplify lookup_count and clean up pieces().
https://github.com/official-stockfish/Stockfish/pull/4656

No functional change
2023-07-03 18:20:10 +02:00
Linmiao Xu
915532181f Update NNUE architecture to SFNNv7 with larger L1 size of 2048
Creating this net involved:
- a 5-step training process from scratch
- greedy permuting L1 weights with https://github.com/official-stockfish/Stockfish/pull/4620
- leb128 compression with https://github.com/glinscott/nnue-pytorch/pull/251
- greedy 2- and 3- cycle permuting with https://github.com/official-stockfish/Stockfish/pull/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 https://github.com/official-stockfish/Stockfish/pull/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 https://github.com/official-stockfish/Stockfish/pull/4646

Bench: 2505168
2023-07-01 13:34:30 +02:00
Stéphane Nicolet
e355c70594 Document the LEB128 patch
Add some comments and harmonize style for the LEB128 patch.

closes https://github.com/official-stockfish/Stockfish/pull/4642

No functional change
2023-07-01 13:01:28 +02:00