Restore the default NNUE setting (enabled) after a bench command.
This also makes the resulting program settings independent of the
number of FENs that are being benched.
Fixes issue #3112.
closes https://github.com/official-stockfish/Stockfish/pull/3113
No functional change.
This fixes#3108 and removes some NNUE code that is currently not used.
At the moment, do_null_move() copies the accumulator from the previous
state into the new state, which is correct. It then clears the "computed_score"
flag because the side to move has changed, and with the other side to move
NNUE will return a completely different evaluation (normally with changed
sign but also with different NNUE-internal tempo bonus).
The problem is that do_null_move() clears the wrong flag. It clears the
computed_score flag of the old state, not of the new state. It turns out
that this almost never affects the search. For example, fixing it does not
change the current bench (but it does change the previous bench). This is
because the search code usually avoids calling evaluate() after a null move.
This PR corrects do_null_move() by removing the computed_score flag altogether.
The flag is not needed because nnue_evaluate() is never called twice on a position.
This PR also removes some unnecessary {}s and inserts a few blank lines
in the modified NNUE files in line with SF coding style.
Resulf ot STC non-regression test:
LLR: 2.95 (-2.94,2.94) {-1.25,0.25}
Total: 26328 W: 3118 L: 3012 D: 20198
Ptnml(0-2): 126, 2208, 8397, 2300, 133
https://tests.stockfishchess.org/tests/view/5f553ccc2d02727c56b36db1
closes https://github.com/official-stockfish/Stockfish/pull/3109
bench: 4109324
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] 84f3e86790
[3] https://stockfishchess.org/get-involved/
std::sort() is not stable so different implementations can produce different results:
use the stable version instead.
Observed for '8/6k1/5r2/8/8/8/1K6/Q7 w - - 0 1' yielding different bench results for gcc and MSVC
and 3-4-5 syzygy TB prior to this patch.
closes https://github.com/official-stockfish/Stockfish/pull/3083
No functional change.
