Stockfish Development Versions are build automatically if there are changes on the master branch in the git repository (https://github.com/official-stockfish/Stockfish). Use it at your own risk.
They are compiled with gcc 11.2/mingw 10 on Ubuntu 22.04.

Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Vizvezdenec
Date: Fri Jul 23 18:47:30 2021 +0200
Timestamp: 1627058850

Prune illegal moves in qsearch earlier

The main idea is that illegal moves influencing search or
qsearch obviously can't be any sort of good. The only reason
why initially legality checks for search and qsearch were done
after they actually can influence some heuristics is because
legality check is expensive computationally. Eventually in
search it was moved to the place where it makes sure that
illegal moves can't influence search.

This patch shows that the same can be done for qsearch + it
passed STC with elo-gaining bounds + it removes 3 lines of code
because one no longer needs to increment/decrement movecount
on illegal moves.

passed STC with elo-gaining bounds
https://tests.stockfishchess.org/tests/view/60f20aefd1189bed71812da0
LLR: 2.94 (-2.94,2.94) <-0.50,2.50>
Total: 61512 W: 4688 L: 4492 D: 52332 Elo +1.11
Ptnml(0-2): 139, 3730, 22848, 3874, 165

The same version functionally but with moving condition ever earlier
passed LTC with simplification bounds.
https://tests.stockfishchess.org/tests/view/60f292cad1189bed71812de9
LLR: 2.98 (-2.94,2.94) <-2.50,0.50>
Total: 60944 W: 1724 L: 1685 D: 57535 Elo +0.22
Ptnml(0-2): 11, 1556, 27298, 1597, 10

closes https://github.com/official-stockfish/Stockfish/pull/3618

bench 4709569
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Liam Keegan
Date: Fri Jul 23 18:16:05 2021 +0200
Timestamp: 1627056965

Add macOS and windows to CI

- macOS
- system clang
- gcc
- windows / msys2
- mingw 64-bit gcc
- mingw 32-bit gcc
- minor code fixes to get new CI jobs to pass
- code: suppress unused-parameter warning on 32-bit windows
- Makefile: if arch=any on macos, don't specify arch at all

fixes https://github.com/official-stockfish/Stockfish/issues/2958

closes https://github.com/official-stockfish/Stockfish/pull/3623

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: VoyagerOne
Date: Tue Jul 13 17:35:20 2021 +0200
Timestamp: 1626190520

Don't save excluded move eval in TT

STC:
LLR: 2.93 (-2.94,2.94) <-0.50,2.50>
Total: 17544 W: 1384 L: 1236 D: 14924 Elo +2.93
Ptnml(0-2): 37, 1031, 6499, 1157, 48
https://tests.stockfishchess.org/tests/view/60ec8d9bd1189bed71812999

LTC:
LLR: 2.95 (-2.94,2.94) <0.50,3.50>
Total: 26136 W: 823 L: 707 D: 24606 Elo +1.54
Ptnml(0-2): 6, 643, 11656, 755, 8
https://tests.stockfishchess.org/tests/view/60ecb11ed1189bed718129ba

closes https://github.com/official-stockfish/Stockfish/pull/3614

Bench: 5505251
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Vizvezdenec
Date: Tue Jul 13 17:33:20 2021 +0200
Timestamp: 1626190400

Remove second futility pruning depth limit

This patch removes futility pruning lmrDepth limit for futility pruning at parent nodes.
Since it's already capped by margin that is a function of lmrDepth there is no need to extra cap it with lmrDepth.

passed STC
https://tests.stockfishchess.org/tests/view/60e9b5dfd1189bed71812777
LLR: 2.97 (-2.94,2.94) <-2.50,0.50>
Total: 14872 W: 1264 L: 1145 D: 12463 Elo +2.78
Ptnml(0-2): 37, 942, 5369, 1041, 47

passed LTC
https://tests.stockfishchess.org/tests/view/60e9c635d1189bed71812790
LLR: 2.96 (-2.94,2.94) <-2.50,0.50>
Total: 40336 W: 1280 L: 1225 D: 37831 Elo +0.47
Ptnml(0-2): 24, 1057, 17960, 1094, 33

closes https://github.com/official-stockfish/Stockfish/pull/3612

bench: 5064969
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: pb00067
Date: Tue Jul 13 17:31:15 2021 +0200
Timestamp: 1626190275

SEE: simplify stm variable initialization

Pull #3458 removed the only usage of pos.see_ge() moving pieces that
don't belong to the side to move, so we can simplify this, adding an assert.

closes https://github.com/official-stockfish/Stockfish/pull/3607

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Vizvezdenec
Date: Tue Jul 13 17:23:30 2021 +0200
Timestamp: 1626189810

Remove futility pruning depth limit

This patch removes futility pruning depth limit for child node futility pruning.
In current master it was double capped by depth and by futility margin, which is also a function of depth, which didn't make much sense.

passed STC
https://tests.stockfishchess.org/tests/view/60e2418f9ea99d7c2d693e64
LLR: 2.95 (-2.94,2.94) <-2.50,0.50>
Total: 116168 W: 9100 L: 9097 D: 97971 Elo +0.01
Ptnml(0-2): 319, 7496, 42476, 7449, 344

passed LTC
https://tests.stockfishchess.org/tests/view/60e3374f9ea99d7c2d693f20
LLR: 2.96 (-2.94,2.94) <-2.50,0.50>
Total: 43304 W: 1282 L: 1231 D: 40791 Elo +0.41
Ptnml(0-2): 8, 1126, 19335, 1173, 10

closes https://github.com/official-stockfish/Stockfish/pull/3606

bench 4965493
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: SFisGOD
Date: Sat Jul 3 10:03:32 2021 +0200
Timestamp: 1625299412

Update default net to nn-9e3c6298299a.nnue

Optimization of nn-956480d8378f.nnue using SPSA
https://tests.stockfishchess.org/tests/view/60da2bf63beab81350ac9fe7

Same method as described in PR #3593

STC:
LLR: 2.93 (-2.94,2.94) <-0.50,2.50>
Total: 17792 W: 1525 L: 1372 D: 14895 Elo +2.99
Ptnml(0-2): 28, 1156, 6401, 1257, 54
https://tests.stockfishchess.org/tests/view/60deffc59ea99d7c2d693c19

LTC:
LLR: 2.96 (-2.94,2.94) <0.50,3.50>
Total: 36544 W: 1245 L: 1109 D: 34190 Elo +1.29
Ptnml(0-2): 12, 988, 16139, 1118, 15
https://tests.stockfishchess.org/tests/view/60df11339ea99d7c2d693c22

closes https://github.com/official-stockfish/Stockfish/pull/3601

Bench: 4687476
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Paul Mulders
Date: Sat Jul 3 09:51:03 2021 +0200
Timestamp: 1625298663

Allow passing RTLIB=compiler-rt to make

Not all linux users will have libatomic installed.
When using clang as the system compiler with compiler-rt as the default
runtime library instead of libgcc, atomic builtins may be provided by compiler-rt.
This change allows such users to pass RTLIB=compiler-rt to make sure
the build doesn't error out on the missing (unnecessary) libatomic.

closes https://github.com/official-stockfish/Stockfish/pull/3597

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: candirufish
Date: Sat Jul 3 09:44:05 2021 +0200
Timestamp: 1625298245

no cut node reduction for killer moves.

stc:
LLR: 2.95 (-2.94,2.94) <-0.50,2.50>
Total: 44344 W: 3474 L: 3294 D: 37576 Elo +1.41
Ptnml(0-2): 117, 2710, 16338, 2890, 117
https://tests.stockfishchess.org/tests/view/60d8ea673beab81350ac9eb8

ltc:
LLR: 2.93 (-2.94,2.94) <0.50,3.50>
Total: 82600 W: 2638 L: 2441 D: 77521 Elo +0.83
Ptnml(0-2): 38, 2147, 36749, 2312, 54
https://tests.stockfishchess.org/tests/view/60d9048f3beab81350ac9eed

closes https://github.com/official-stockfish/Stockfish/pull/3600

Bench: 5160239
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: xoto10
Date: Sat Jul 3 09:26:58 2021 +0200
Timestamp: 1625297218

Simplify lazy_skip.

Small speedup by removing operations in lazy_skip.

STC 10+0.1 :
LLR: 2.93 (-2.94,2.94) <-2.50,0.50>
Total: 55088 W: 4553 L: 4482 D: 46053 Elo +0.45
Ptnml(0-2): 163, 3546, 20045, 3637, 153
https://tests.stockfishchess.org/tests/view/60daa2cb3beab81350aca04d

LTC 60+0.6 :
LLR: 2.93 (-2.94,2.94) <-2.50,0.50>
Total: 46136 W: 1457 L: 1407 D: 43272 Elo +0.38
Ptnml(0-2): 10, 1282, 20442, 1316, 18
https://tests.stockfishchess.org/tests/view/60db0e753beab81350aca08e

closes https://github.com/official-stockfish/Stockfish/pull/3599

Bench 5122403
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Stéphane Nicolet
Date: Sat Jul 3 09:25:16 2021 +0200
Timestamp: 1625297116

Simplify format_cp_aligned_dot()

closes https://github.com/official-stockfish/Stockfish/pull/3583

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Joost VandeVondele
Date: Sat Jul 3 09:20:06 2021 +0200
Timestamp: 1625296806

Restore development version

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Joost VandeVondele
Date: Fri Jul 2 14:53:30 2021 +0200
Timestamp: 1625230410

Stockfish 14

Official release version of Stockfish 14

Bench: 4770936

---

Today, we have the pleasure to announce Stockfish 14.

As usual, downloads will be freely available at https://stockfishchess.org

The engine is now significantly stronger than just a few months ago,
and wins four times more game pairs than it loses against the previous
release version [0]. Stockfish 14 is now at least 400 Elo ahead of
Stockfish 7, a top engine in 2016 [1]. During the last five years,
Stockfish has thus gained about 80 Elo per year.

Stockfish 14 evaluates positions more accurately than Stockfish 13 as
a result of two major steps forward in defining and training the
efficiently updatable neural network (NNUE) that provides the evaluation
for positions.

First, the collaboration with the Leela Chess Zero team - announced
previously [2] - has come to fruition. The LCZero team has provided a
collection of billions of positions evaluated by Leela that we have
combined with billions of positions evaluated by Stockfish to train the
NNUE net that powers Stockfish 14. The fact that we could use and combine
these datasets freely was essential for the progress made and demonstrates
the power of open source and open data [3].

Second, the architecture of the NNUE network was significantly updated:
the new network is not only larger, but more importantly, it deals better
with large material imbalances and can specialize for multiple phases of
the game [4]. A new project, kick-started by Gary Linscott and
Tomasz Sobczyk, led to a GPU accelerated net trainer written in
pytorch.[5] This tool allows for training high-quality nets in a couple
of hours.

Finally, this release features some search refinements, minor bug
fixes and additional improvements. For example, Stockfish is now about
90 Elo stronger for chess960 (Fischer random chess) at short time control.

The Stockfish project builds on a thriving community of enthusiasts
(thanks everybody!) that contribute their expertise, time, and resources
to build a free and open-source chess engine that is robust, widely
available, and very strong. We invite our chess fans to join the fishtest
testing framework and programmers to contribute to the project on
github [6].

Stay safe and enjoy chess!

The Stockfish team

[0] https://tests.stockfishchess.org/tests/view/60dae5363beab81350aca077
[1] https://nextchessmove.com/dev-builds
[2] https://stockfishchess.org/blog/2021/stockfish-13/
[3] https://lczero.org/blog/2021/06/the-importance-of-open-data/
[4] https://github.com/official-stockfish/Stockfish/commit/e8d64af1
[5] https://github.com/glinscott/nnue-pytorch/
[6] https://stockfishchess.org/get-involved/
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Brad Knox
Date: Tue Jun 29 10:24:54 2021 +0200
Timestamp: 1624955094

Update Top CPU Contributors

closes https://github.com/official-stockfish/Stockfish/pull/3595

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: SFisGOD
Date: Mon Jun 28 21:31:58 2021 +0200
Timestamp: 1624908718

Update default net to nn-3475407dc199.nnue

Optimization of eight subnetwork output layers of Michael's nn-190f102a22c3.nnue using SPSA
https://tests.stockfishchess.org/tests/view/60d5510642a522cc50282ef3

Parameters: A total of 256 net weights and 8 net biases were tuned
New best values: The raw values at the end of the tuning run were used (800k games, 5 seconds TC)
Settings: default ck value and SPSA A is 30,000 (3.75% of the total number of games)

STC:
LLR: 2.94 (-2.94,2.94) <-0.50,2.50>
Total: 29064 W: 2435 L: 2269 D: 24360 Elo +1.98
Ptnml(0-2): 72, 1857, 10505, 2029, 69
https://tests.stockfishchess.org/tests/view/60d8ea123beab81350ac9eb6

LTC:
LLR: 2.93 (-2.94,2.94) <0.50,3.50>
Total: 61848 W: 2055 L: 1884 D: 57909 Elo +0.96
Ptnml(0-2): 18, 1708, 27310, 1861, 27
https://tests.stockfishchess.org/tests/view/60d8f0393beab81350ac9ec6

closes https://github.com/official-stockfish/Stockfish/pull/3593

Bench: 4770936
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: MichaelB7
Date: Mon Jun 28 21:20:05 2021 +0200
Timestamp: 1624908005

Make net nn-956480d8378f.nnue the default

Trained with the pytorch trainer: https://github.com/glinscott/nnue-pytorch

python train.py i:/bin/all.binpack i:/bin/all.binpack --gpus 1 --threads 4 --num-workers 30 --batch-size 16384 --progress_bar_refresh_rate 300 --smart-fen-skipping --random-fen-skipping 3 --features=HalfKAv2^ --lambda=1.0 --max_epochs=440 --seed %random%%random% --default_root_dir exp/run_18 --resume-from-model ./pt/nn-75980ca503c6.pt

This run is thus started from a previous master net.

all.binpack equaled 4 parts Wrong_NNUE_2.binpack https://drive.google.com/file/d/1seGNOqcVdvK_vPNq98j-zV3XPE5zWAeq/view?usp=sharing plus two parts of Training_Data.binpack https://drive.google.com/file/d/1RFkQES3DpsiJqsOtUshENtzPfFgUmEff/view?usp=sharing
Each set was concatenated together - making one large Wrong_NNUE 2 binpack and one large Training so the were approximately equal in size. They were then interleaved together. The idea was to give Wrong_NNUE.binpack closer to equal weighting with the Training_Data binpack

passed STC:
https://tests.stockfishchess.org/tests/view/60d0c0a7a8ec07dc34c072b2
LLR: 2.93 (-2.94,2.94) <-0.50,2.50>
Total: 18440 W: 1693 L: 1531 D: 15216 Elo +3.05
Ptnml(0-2): 67, 1225, 6464, 1407, 57

passed LTC:
https://tests.stockfishchess.org/tests/view/60d762793beab81350ac9d72
LLR: 2.98 (-2.94,2.94) <0.50,3.50>
Total: 93120 W: 3152 L: 2933 D: 87035 Elo +0.82
Ptnml(0-2): 48, 2581, 41076, 2814, 41

passed LTC (rebased branch to current master):
https://tests.stockfishchess.org/tests/view/60d85eeb3beab81350ac9e2b
LLR: 2.96 (-2.94,2.94) <0.50,3.50>
Total: 42688 W: 1347 L: 1206 D: 40135 Elo +1.15
Ptnml(0-2): 14, 1097, 18981, 1238, 14.

closes https://github.com/official-stockfish/Stockfish/pull/3592

Bench: 4906727
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Joost VandeVondele
Date: Mon Jun 28 21:13:30 2021 +0200
Timestamp: 1624907610

Update WDL model for NNUE

This updates the WDL model based on the LTC statistics in June this year (10M games),
so from pre-NNUE to NNUE based results.

(for old results see, https://github.com/official-stockfish/Stockfish/pull/2778)

As before the fit by the model to the data is quite good.

closes https://github.com/official-stockfish/Stockfish/pull/3582

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: bmc4
Date: Mon Jun 28 21:12:04 2021 +0200
Timestamp: 1624907524

Simplify Reductions Initialization

passed

STC:
LLR: 2.94 (-2.94,2.94) <-2.50,0.50>
Total: 45032 W: 3600 L: 3518 D: 37914 Elo +0.63
Ptnml(0-2): 111, 2893, 16435, 2957, 120
https://tests.stockfishchess.org/tests/view/60d2655d40925195e7a6c527

LTC:
LLR: 3.00 (-2.94,2.94) <-2.50,0.50>
Total: 25728 W: 786 L: 722 D: 24220 Elo +0.86
Ptnml(0-2): 5, 650, 11494, 706, 9
https://tests.stockfishchess.org/tests/view/60d2b14240925195e7a6c577

closes https://github.com/official-stockfish/Stockfish/pull/3584

bench: 4602977
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Stéphane Nicolet
Date: Tue Jun 22 11:51:03 2021 +0200
Timestamp: 1624355463

Detect fortresses a little bit quicker

In the so-called "hybrid" method of evaluation of current master, we use the
classical eval (because of its speed) instead of the NNUE eval when the classical
material balance approximation hints that the position is "winning enough" to
rely on the classical eval.

This trade-off idea between speed and accuracy works well in general, but in
some fortress positions the classical eval is just bad. So in shuffling branches
of the search tree, we (slowly) increase the thresehold so that eventually we
don't trust classical anymore and switch to NNUE evaluation.

This patch increases that threshold faster, so that we switch to NNUE quicker
in shuffling branches. Idea is to incite Stockfish to spend less time in fortresses
lines in the search tree, and spend more time searching the critical lines.

passed STC:
LLR: 2.96 (-2.94,2.94) <-0.50,2.50>
Total: 47872 W: 3908 L: 3720 D: 40244 Elo +1.36
Ptnml(0-2): 122, 3053, 17419, 3199, 143
https://tests.stockfishchess.org/tests/view/60cef34b457376eb8bcab79d

passed LTC:
LLR: 2.93 (-2.94,2.94) <0.50,3.50>
Total: 73616 W: 2326 L: 2143 D: 69147 Elo +0.86
Ptnml(0-2): 21, 1940, 32705, 2119, 23
https://tests.stockfishchess.org/tests/view/60cf6d842114332881e73528

Retested at LTC against lastest master:
LLR: 2.93 (-2.94,2.94) <0.50,3.50>
Total: 18264 W: 642 L: 532 D: 17090 Elo +2.09
Ptnml(0-2): 6, 479, 8055, 583, 9
https://tests.stockfishchess.org/tests/view/60d18cd540925195e7a6c351

closes https://github.com/official-stockfish/Stockfish/pull/3578

Bench: 5139233
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: MichaelB7
Date: Mon Jun 21 23:16:55 2021 +0200
Timestamp: 1624310215

Make net nn-190f102a22c3.nnue the default net.

Trained with the pytorch trainer: https://github.com/glinscott/nnue-pytorch

python train.py i:/bin/all.binpack i:/bin/all.binpack --gpus 1 --threads 4 --num-workers 30 --batch-size 16384 --progress_bar_refresh_rate 300 --smart-fen-skipping --random-fen-skipping 3 --features=HalfKAv2^ --lambda=1.0 --max_epochs=440 --seed %random%%random% --default_root_dir exp/run_17 --resume-from-model ./pt/nn-75980ca503c6.pt

This run is thus started from the previous master net.

all.binpack equaled 4 parts Wrong_NNUE_2.binpack https://drive.google.com/file/d/1seGNOqcVdvK_vPNq98j-zV3XPE5zWAeq/view?usp=sharing plus two parts of Training_Data.binpack https://drive.google.com/file/d/1RFkQES3DpsiJqsOtUshENtzPfFgUmEff/view?usp=sharing
Each set was concatenated together - making one large Wrong_NNUE 2 binpack and one large Training so the were approximately equal in size. They were then interleaved together. The idea was to give Wrong_NNUE.binpack closer to equal weighting with the Training_Data binpack

passed LTC
https://tests.stockfishchess.org/tests/view/60d09f52b4c17000d679517f
LLR: 2.93 (-2.94,2.94) <0.50,3.50>
Total: 32184 W: 1100 L: 970 D: 30114 Elo +1.40
Ptnml(0-2): 10, 878, 14193, 994, 17

passed STC
https://tests.stockfishchess.org/tests/view/60d086c02114332881e7368e
LLR: 2.93 (-2.94,2.94) <-0.50,2.50>
Total: 11360 W: 1056 L: 906 D: 9398 Elo +4.59
Ptnml(0-2): 25, 735, 4026, 853, 41

closes https://github.com/official-stockfish/Stockfish/pull/3576

Bench: 4631244
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Joost VandeVondele
Date: Mon Jun 21 23:14:58 2021 +0200
Timestamp: 1624310098

Fix build error on OSX

directly use integer version for cp calculation.

fixes https://github.com/official-stockfish/Stockfish/issues/3573

closes https://github.com/official-stockfish/Stockfish/pull/3574

No functional change
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Stéphane Nicolet
Date: Mon Jun 21 22:58:56 2021 +0200
Timestamp: 1624309136

Remove the Contempt UCI option

This patch removes the UCI option for setting Contempt in classical evaluation.

It is exactly equivalent to using Contempt=0 for the UCI contempt value and keeping
the dynamic part in the algo (renaming this dynamic part `trend` to better describe
what it does). We have tried quite hard to implement a working Contempt feature for
NNUE but nothing really worked, so it is probably time to give up.

Interested chess fans wishing to keep playing with the UCI option for Contempt and
use it with the classical eval are urged to download the version tagged "SF_Classical"
of Stockfish (dated 31 July 2020), as it was the last version where our search
algorithm was tuned for the classical eval and is probably our strongest classical
player ever: https://github.com/official-stockfish/Stockfish/tags

Passed STC:
LLR: 2.95 (-2.94,2.94) <-2.50,0.50>
Total: 72904 W: 6228 L: 6175 D: 60501 Elo +0.25
Ptnml(0-2): 221, 5006, 25971, 5007, 247
https://tests.stockfishchess.org/tests/view/60c98bf9457376eb8bcab18d

Passed LTC:
LLR: 2.93 (-2.94,2.94) <-2.50,0.50>
Total: 45168 W: 1601 L: 1547 D: 42020 Elo +0.42
Ptnml(0-2): 38, 1331, 19786, 1397, 32
https://tests.stockfishchess.org/tests/view/60c9c7fa457376eb8bcab1bb

closes https://github.com/official-stockfish/Stockfish/pull/3575

Bench: 4947716
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Stéphane Nicolet
Date: Sun Jun 20 23:17:07 2021 +0200
Timestamp: 1624223827

Keep more pawns and pieces when attacking

This patch increase the weight of pawns and pieces from 28 to 32
in the scaling formula we apply to the output of the NNUE pure eval.

Increasing this gradient for pawns and pieces means that Stockfish
will try a little harder to keep material when she has the advantage,
and try a little bit harder to escape into an endgame when she is
under pressure.

STC:
LLR: 2.93 (-2.94,2.94) <-0.50,2.50>
Total: 53168 W: 4371 L: 4177 D: 44620 Elo +1.27
Ptnml(0-2): 160, 3389, 19283, 3601, 151
https://tests.stockfishchess.org/tests/view/60cefd1d457376eb8bcab7ab

LTC:
LLR: 2.94 (-2.94,2.94) <0.50,3.50>
Total: 10888 W: 386 L: 288 D: 10214 Elo +3.13
Ptnml(0-2): 3, 260, 4821, 356, 4
https://tests.stockfishchess.org/tests/view/60cf709d2114332881e7352b

closes https://github.com/official-stockfish/Stockfish/pull/3571

Bench: 4965430
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: MichaelB7
Date: Sat Jun 19 23:24:35 2021 +0200
Timestamp: 1624137875

Make net nn-75980ca503c6.nnue the default.

trained with the Python command

c:\nnue>python train.py i:/bin/all.binpack i:/bin/all.binpack --gpus 1 --threads 4 --num-workers 30 --batch-size 16384 --progress_bar_refresh_rate 300 --smart-fen-skipping --random-fen-skipping 3 --features=HalfKAv2^ --lambda=1.0 --max_epochs=440 --seed %random%%random% --default_root_dir exp/run_10 --resume-from-model ./pt/nn-3b20abec10c1.pt
`
all.binpack equaled 4 parts Wrong_NNUE_2.binpack https://drive.google.com/file/d/1seGNOqcVdvK_vPNq98j-zV3XPE5zWAeq/view?usp=sharing plus two parts of Training_Data.binpack https://drive.google.com/file/d/1RFkQES3DpsiJqsOtUshENtzPfFgUmEff/view?usp=sharing
Each set was concatenated together - making one large Wrong_NNUE 2 binpack and one large Training so the were approximately equal in size. They were then interleaved together. The idea was to give Wrong_NNUE.binpack closer to equal weighting with the Training_Data binpack .

Net nn-3b20abec10c1.nnue was chosen as the --resume-from-model with the idea that through learning, the manually hex edited values will be learned and will not need to be manually adjusted going forward. They would also be fine tuned by the learning process.

passed STC:
https://tests.stockfishchess.org/tests/view/60cdf91e457376eb8bcab66f
LLR: 2.95 (-2.94,2.94) <-0.50,2.50>
Total: 18256 W: 1639 L: 1479 D: 15138 Elo +3.05
Ptnml(0-2): 59, 1179, 6505, 1313, 72

passed LTC:
https://tests.stockfishchess.org/tests/view/60ce2166457376eb8bcab6e1
LLR: 2.94 (-2.94,2.94) <0.50,3.50>
Total: 18792 W: 654 L: 542 D: 17596 Elo +2.07
Ptnml(0-2): 9, 490, 8291, 592, 14

closes https://github.com/official-stockfish/Stockfish/pull/3570

Bench: 5020972
see source
Windows x64 for Haswell CPUs
Windows x64 for modern computers + AVX2
Windows x64 for modern computers
Windows x64 + SSSE3
Windows x64
Windows 32
Linux x64 for Haswell CPUs
Linux x64 for modern computers + AVX2
Linux x64 for modern computers
Linux x64 + SSSE3
Linux x64
Author: Tomasz Sobczyk
Date: Sat Jun 19 11:57:01 2021 +0200
Timestamp: 1624096621

Change trace with NNUE eval support

This patch adds some more output to the `eval` command. It adds a board display
with estimated piece values (method is remove-piece, evaluate, put-piece), and
splits the NNUE evaluation with (psqt,layers) for each bucket for the NNUE net.

Example:

```

./stockfish
position fen 3Qb1k1/1r2ppb1/pN1n2q1/Pp1Pp1Pr/4P2p/4BP2/4B1R1/1R5K b - - 11 40
eval

Contributing terms for the classical eval:
+------------+-------------+-------------+-------------+
| Term | White | Black | Total |
| | MG EG | MG EG | MG EG |
+------------+-------------+-------------+-------------+
| Material | ---- ---- | ---- ---- | -0.73 -1.55 |
| Imbalance | ---- ---- | ---- ---- | -0.21 -0.17 |
| Pawns | 0.35 -0.00 | 0.19 -0.26 | 0.16 0.25 |
| Knights | 0.04 -0.08 | 0.12 -0.01 | -0.08 -0.07 |
| Bishops | -0.34 -0.87 | -0.17 -0.61 | -0.17 -0.26 |
| Rooks | 0.12 0.00 | 0.08 0.00 | 0.04 0.00 |
| Queens | 0.00 0.00 | -0.27 -0.07 | 0.27 0.07 |
| Mobility | 0.84 1.76 | 0.01 0.66 | 0.83 1.10 |
|King safety | -0.99 -0.17 | -0.72 -0.10 | -0.27 -0.07 |
| Threats | 0.27 0.27 | 0.73 0.86 | -0.46 -0.59 |
| Passed | 0.00 0.00 | 0.79 0.82 | -0.79 -0.82 |
| Space | 0.61 0.00 | 0.24 0.00 | 0.37 0.00 |
| Winnable | ---- ---- | ---- ---- | 0.00 -0.03 |
+------------+-------------+-------------+-------------+
| Total | ---- ---- | ---- ---- | -1.03 -2.14 |
+------------+-------------+-------------+-------------+

NNUE derived piece values:
+-------+-------+-------+-------+-------+-------+-------+-------+
| | | | Q | b | | k | |
| | | | +12.4 | -1.62 | | | |
+-------+-------+-------+-------+-------+-------+-------+-------+
| | r | | | p | p | b | |
| | -3.89 | | | -0.84 | -1.19 | -3.32 | |
+-------+-------+-------+-------+-------+-------+-------+-------+
| p | N | | n | | | q | |
| -1.81 | +3.71 | | -4.82 | | | -5.04 | |
+-------+-------+-------+-------+-------+-------+-------+-------+
| P | p | | P | p | | P | r |
| +1.16 | -0.91 | | +0.55 | +0.12 | | +0.50 | -4.02 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| | | | | P | | | p |
| | | | | +2.33 | | | +1.17 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| | | | | B | P | | |
| | | | | +4.79 | +1.54 | | |
+-------+-------+-------+-------+-------+-------+-------+-------+
| | | | | B | | R | |
| | | | | +4.54 | | +6.03 | |
+-------+-------+-------+-------+-------+-------+-------+-------+
| | R | | | | | | K |
| | +4.81 | | | | | | |
+-------+-------+-------+-------+-------+-------+-------+-------+

NNUE network contributions (Black to move)
+------------+------------+------------+------------+
| Bucket | Material | Positional | Total |
| | (PSQT) | (Layers) | |
+------------+------------+------------+------------+
| 0 | + 0.32 | - 1.46 | - 1.13 |
| 1 | + 0.25 | - 0.68 | - 0.43 |
| 2 | + 0.46 | - 1.72 | - 1.25 |
| 3 | + 0.55 | - 1.80 | - 1.25 |
| 4 | + 0.48 | - 1.77 | - 1.29 |
| 5 | + 0.40 | - 2.00 | - 1.60 |
| 6 | + 0.57 | - 2.12 | - 1.54 | <-- this bucket is used
| 7 | + 3.38 | - 2.00 | + 1.37 |
+------------+------------+------------+------------+

Classical evaluation -1.00 (white side)
NNUE evaluation +1.54 (white side)
Final evaluation +2.38 (white side) [with scaled NNUE, hybrid, ...]

```

Also renames the export_net() function to save_eval() while there.

closes https://github.com/official-stockfish/Stockfish/pull/3562

No functional change
see source

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