This patch provides command line flags `--help` and `--license` as well as the corresponding `help` and `license` commands.
```
$ ./stockfish --help
Stockfish 200522 by the Stockfish developers (see AUTHORS file)
Stockfish is a powerful chess engine and free software licensed under the GNU GPLv3.
Stockfish is normally used with a separate graphical user interface (GUI).
Stockfish implements the universal chess interface (UCI) to exchange information.
For further information see https://github.com/official-stockfish/Stockfish#readme
or the corresponding README.md and Copying.txt files distributed with this program.
```
The idea is to provide a minimal help that links to the README.md file,
not replicating information that is already available elsewhere.
We use this opportunity to explicitly report the license as well.
closes https://github.com/official-stockfish/Stockfish/pull/4027
No functional change.
train a net using training data with a
heavier weight on positions having 16 pieces on the board. More specifically,
with a relative weight of `i * (32-i)/(16 * 16)+1` (where i is the number of pieces on the board).
This is done with the trainer branch https://github.com/glinscott/nnue-pytorch/pull/173
The command used is:
```
python train.py $datafile $datafile $restarttype $restartfile --gpus 1 --threads 4 --num-workers 12 --random-fen-skipping=3 --batch-size 16384 --progress_bar_refresh_rate 300 --smart-fen-skipping --features=HalfKAv2_hm^ --lambda=1.00 --max_epochs=$epochs --seed $RANDOM --default_root_dir exp/run_$i
```
The datafile is T60T70wIsRightFarseerT60T74T75T76.binpack, the restart is from the master net.
passed STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.50>
Total: 22728 W: 6197 L: 5945 D: 10586
Ptnml(0-2): 105, 2453, 6001, 2695, 110
https://tests.stockfishchess.org/tests/view/625cf944ff677a888877cd90
passed LTC:
LLR: 2.94 (-2.94,2.94) <0.50,3.00>
Total: 35664 W: 9535 L: 9264 D: 16865
Ptnml(0-2): 30, 3524, 10455, 3791, 32
https://tests.stockfishchess.org/tests/view/625d3c32ff677a888877d7ca
closes https://github.com/official-stockfish/Stockfish/pull/3989
Bench: 7269563
Official release version of Stockfish 15
Bench: 8129754
---
A new major release of Stockfish is now available at https://stockfishchess.org
Stockfish 15 continues to push the boundaries of chess, providing unrivalled
analysis and playing strength. In our testing, Stockfish 15 is ahead of
Stockfish 14 by 36 Elo points and wins nine times more game pairs than it
loses[1].
Improvements to the engine have made it possible for Stockfish to end up
victorious in tournaments at all sorts of time controls ranging from bullet to
classical and even at Fischer random chess[2]. At CCC, Stockfish won all of
the latest tournaments: CCC 16 Bullet, Blitz and Rapid, CCC 960 championship,
and the CCC 17 Rapid. At TCEC, Stockfish won the Season 21, Cup 9, FRC 4 and
in the current Season 22 superfinal, at the time of writing, has won 16 game
pairs and not yet lost a single one.
This progress is the result of a dedicated team of developers that comes up
with new ideas and improvements. For Stockfish 15, we tested nearly 13000
different changes and retained the best 200. These include the fourth
generation of our NNUE network architecture, as well as various search
improvements. To perform these tests, contributors provide CPU time for
testing, and in the last year, they have collectively played roughly a
billion chess games. In the last few years, our distributed testing
framework, Fishtest, has been operated superbly and has been developed and
improved extensively. This work by Pasquale Pigazzini, Tom Vijlbrief, Michel
Van den Bergh, and various other developers[3] is an essential part of the
success of the Stockfish project.
Indeed, the Stockfish project builds on a thriving community of enthusiasts
to offer 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[4].
The Stockfish team
[1] https://tests.stockfishchess.org/tests/view/625d156dff677a888877d1be
[2] https://en.wikipedia.org/wiki/Stockfish_(chess)#Competition_results
[3] https://github.com/glinscott/fishtest/blob/master/AUTHORS
[4] https://stockfishchess.org/get-involved/
retire msvc support and corresponding CI. No active development happens on msvc,
and build is much slower or wrong.
gcc (mingw) is our toolchain of choice also on windows, and the latter is tested.
No functional change
In case the evaluation at root is large, discourage the use of lazyEval.
This fixes https://github.com/official-stockfish/Stockfish/issues/3772
or at least improves it significantly. In this case, poor play with large
odds can be observed, in extreme cases leading to a loss despite large
advantage:
r1bq1b1r/ppp3p1/3p1nkp/n3p3/2B1P2N/2NPB3/PPP2PPP/R3K2R b KQ - 5 9
With this patch the poor move is only considered up to depth 13, in master
up to depth 28.
The patch did not pass at LTC with Elo gainer bounds, but with slightly
positive Elo nevertheless (95% LOS).
STC:
LLR: 2.94 (-2.94,2.94) <0.00,2.50>
Total: 40368 W: 10318 L: 10041 D: 20009
Ptnml(0-2): 103, 4493, 10725, 4750, 113
https://tests.stockfishchess.org/tests/view/61800ad259e71df00dcc420d
LTC:
LLR: -2.94 (-2.94,2.94) <0.50,3.00>
Total: 212288 W: 52997 L: 52692 D: 106599
Ptnml(0-2): 112, 22038, 61549, 22323, 122
https://tests.stockfishchess.org/tests/view/618050d959e71df00dcc426d
closes https://github.com/official-stockfish/Stockfish/pull/3780
Bench: 7127040
Official release version of Stockfish 14.1
Bench: 6334068
---
Today, we have the pleasure to announce Stockfish 14.1.
As usual, downloads will be freely available at stockfishchess.org/download [1].
With Stockfish 14.1 our users get access to the strongest chess engine
available today. In the period leading up to this release, Stockfish
convincingly won several chess engine tournaments, including the TCEC 21
superfinal, the TCEC Cup 9, and the Computer Chess Championship for
Fischer Random Chess (Chess960). In the latter tournament, Stockfish
was undefeated in 599 out of 600 games played.
Compared to Stockfish 14, this release introduces a more advanced NNUE
architecture and various search improvements. In self play testing, using
a book of balanced openings, Stockfish 14.1 wins three times more game
pairs than it loses [2]. At this high level, draws are very common, so the
Elo difference to Stockfish 14 is about 17 Elo. The NNUE evaluation method,
introduced to top level chess with Stockfish 12 about one year ago [3],
has now been adopted by several other strong CPU based chess engines.
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 [4].
Stay safe and enjoy chess!
The Stockfish team
[1] https://stockfishchess.org/download/
[2] https://tests.stockfishchess.org/tests/view/6175c320af70c2be1788fa2b
[3] https://github.com/official-stockfish/Stockfish/discussions/3628
[4] https://stockfishchess.org/get-involved/
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/
this tool with take N binpacks as input to produce 1 binpack as output.
The input binpacks are read in random order, with a probability related to their size,
but each input file is read sequentially. The output is thus an appropriately shuffled binpack.
The tool is much faster than cat'ing the files together followed by a shuffle.
It assumes that the input binpacks themselves have no particular internal ordering.
Official release version of Stockfish 13
Bench: 3766422
-----
It is our pleasure to release Stockfish 13 to chess fans worldwide.
As usual, downloads are freely available at
https://stockfishchess.org
The Stockfish project builds on a thriving community of enthusiasts
who contribute their expertise, time, and resources to build a free
and open-source chess engine that is robust, widely available, and
very strong. We would like to thank them all!
The good news first: from now on, our users can expect more frequent
high-quality releases of Stockfish! Sadly, this decision has been
triggered by the start of sales of the Fat Fritz 2 engine by ChessBase,
which is a copy of a very recent development version of Stockfish
with minor modifications. We refer to our statement on Fat Fritz 2[1]
and a community blog[2] for further information.
This version of Stockfish is significantly stronger than any of its
predecessors. Stockfish 13 outperforms Stockfish 12 by at least
35 Elo[3]. When playing against a one-year-old Stockfish, it wins 60
times more game pairs than it loses[4]. This release features an NNUE
network retrained on billions of positions, much faster network
evaluation code, and significantly improved search heuristics, as
well as additional evaluation tweaks. In the course of its development,
this version has won the superfinals of the TCEC Season 19 and
TCEC Season 20.
Going forward, the Leela Chess Zero and Stockfish teams will join
forces to demonstrate our commitment to open source chess engines and
training tools, and open data. We are convinced that our free and
open-source chess engines serve the chess community very well.
Stay safe and enjoy chess!
The Stockfish team
[1] https://blog.stockfishchess.org/post/643239805544792064/statement-on-fat-fritz-2
[2] https://lichess.org/blog/YCvy7xMAACIA8007/fat-fritz-2-is-a-rip-off
[3] https://tests.stockfishchess.org/tests/view/602bcccf7f517a561bc49b11
[4] https://tests.stockfishchess.org/tests/view/600fbb9c735dd7f0f0352d59
allows for repeating a depth N search K times.
Repeated searches improve the quality of eval, but don't bring in higher depth info.
Might allow for removing some of the noise in low depth scoring.
in case a score can be parsed from the comment field in the pgn, add it to the output.
This form works for the fishtest pgns, and is quite common (cutechess-cli among others).
older versions of gcc (<8.1) need this, even if they accept -std=c++17
with this patch, the code can be run on fishtest again,
at least by the majority of workers (fishtest doesn't require c++17 to be available)
See e.g.
https://tests.stockfishchess.org/tests/view/5fcfbf801ac1691201888235
Bench: 3820648
Using no searching time in case of a single legal move is not beneficial from
a strength point of view, and this special case can be easily removed:
STC:
LLR: 2.93 (-2.94,2.94) {-1.25,0.25}
Total: 22472 W: 2458 L: 2357 D: 17657
Ptnml(0-2): 106, 1733, 7453, 1842, 102
https://tests.stockfishchess.org/tests/view/5f926cbc81eda81bd78cb6df
LTC:
LLR: 2.94 (-2.94,2.94) {-0.75,0.25}
Total: 37880 W: 1736 L: 1682 D: 34462
Ptnml(0-2): 22, 1392, 16057, 1448, 21
https://tests.stockfishchess.org/tests/view/5f92a26081eda81bd78cb6fe
The advantage of using the normal time management for a single legal move is that scores
reported for that move are reasonable, not searching leads to artifacts during games
(see e.g. https://tcec-chess.com/#div=sf&game=96&season=19)
The disadvantage of using normal time management of a single legal move is that thinking
times can be unnaturally long, making it 'painful to watch' in online tournaments.
This patch uses normal time management, but caps the used time to 500ms.
This should lead to reasonable scores, and be hardly perceptible.
closes https://github.com/official-stockfish/Stockfish/pull/3195
closes https://github.com/official-stockfish/Stockfish/pull/3183
variant of a patch suggested by SFisGOD
No functional change.
RootInTB was an incorrectly shared global, probably leading to wrong scoreing
Minor:
setting TB global state from input by all threads (all threads write same values)
setting Limits global state by all threads (idem)
thread counting for finalization
CI can be enabled once races are fixed in the learner, manually goes like:
```
make clean && make -j2 ARCH=x86-64-modern sanitize=thread optimize=no debug=yes build
../tests/instrumented_learn.sh --sanitizer-thread
```
Needs some review.
additionally allow all options to be converted to string.
Without this, restoring of the options (multi_think.cpp:117) can't work.
fixes https://github.com/nodchip/Stockfish/issues/128
Now gensfen/learn pass with debug=yes in CI
1) Only access UCI option if defined
2) disable -Werror for now.
3) disable a few target that don't have _mm_malloc.
4) Add profile-learn target, with small speedup.
5) just test on Linux + gcc (skip macOS, unclear openblas, skip linux+clang, unclear omp/std::filesystem).
makes it a little easier to change the BLAS library used,
doesn't hardcode the mingw headers. Works on Linux with openblas installed.
Should be no change on Windows.
fixes valgrind errors as seen with:
```
setoption name Use NNUE value true
isready
gensfen depth 6 loop 10 use_draw_in_training_data_generation 1 eval_limit 32000 output_file_name training_data/training_data.bin use_raw_nnue_eval 0
quit
```
the latter script now runs without valgrind errors on linux
Official release version of Stockfish 12
Bench: 3624569
-----------------------
It is our pleasure to release Stockfish 12 to users world-wide
Downloads will be freely available at
https://stockfishchess.org/download/
This version 12 of Stockfish plays significantly stronger than
any of its predecessors. In a match against Stockfish 11,
Stockfish 12 will typically win at least ten times more game pairs
than it loses.
This jump in strength, visible in regular progression tests during
development[1], results from the introduction of an efficiently
updatable neural network (NNUE) for the evaluation in Stockfish[2],
and associated tuning of the engine as a whole. The concept of the
NNUE evaluation was first introduced in shogi, and ported to
Stockfish afterward. Stockfish remains a CPU-only engine, since the
NNUE networks can be very efficiently evaluated on CPUs. The
recommended parameters of the NNUE network are embedded in
distributed binaries, and Stockfish will use NNUE by default.
Both the NNUE and the classical evaluations are available, and
can be used to assign values to positions that are later used in
alpha-beta (PVS) search to find the best move. The classical
evaluation computes this value as a function of various chess
concepts, handcrafted by experts, tested and tuned using fishtest.
The NNUE evaluation computes this value with a neural network based
on basic inputs. The network is optimized and trained on the
evaluations of millions of positions.
The Stockfish project builds on a thriving community of enthusiasts
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 chess fans to join the fishtest testing
framework and programmers to contribute on github[3].
Stay safe and enjoy chess!
The Stockfish team
[1] https://github.com/glinscott/fishtest/wiki/Regression-Tests
[2] https://github.com/official-stockfish/Stockfish/commit/84f3e867903f62480c33243dd0ecbffd342796fc
[3] https://stockfishchess.org/get-involved/
