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changelog.txt
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v0.31.0-rc1 (2024-03-25)
~~~~~~~
* The blas, cuda, eigen, metal and onnx backends now have support for multihead
network architecture and can run BT3/BT4 nets.
* Updated the internal Elo model to better align with regular Elo for human
players.
* There is a new XLA backend that uses OpenXLA compiler to produce code to
execute the neural network. See
<https://github.com/LeelaChessZero/lc0/wiki/XLA-backend> for details. Related
are new leela2onnx options to output the HLO format that XLA understands.
* There is a vastly simplified lc0 interface available by renaming the
executable to `lc0simple`.
* The backends can now suggest a minibatch size to the search, this is enabled
by `--minibatch-size=0` (the new default).
* If the cudnn backend detected an unsupported network architecture it will
switch to the cuda backend.
* Two new selfplay options enable value and policy tournaments. A policy
tournament is using a single node policy to select the move to play, while a
value tournament searches all possible moves at depth 1 to select the one with
the best q.
* While it is easy to get a single node policy evaluation (`go nodes 1` using
uci), there was no simple way to get the effect of a value only evalaution, so
the `--value-only` option was added.
* Button uci options were implemented and a button to clear the tree was added
(as hidden option).
* Support for the uci `go mate` option was added.
* The rescorer can now be built from the lc0 code base instead of a separate
branch.
* A dicrete onnx layernorm implementation was added to get around a onnxruntime
bug with directml - this has some overhead so it is only enabled for onnx-dml
and can be switched off with the `alt_layernorm=false` backend option.
* The `--onnx2pytoch` option was added to leela2onnx to generate pytorch
compatible models.
* There is a cuda `min_batch` backend option to reduce non-determinism with
small batches.
* New options were added to onnx2leela to fix tf exported onnx models.
* The onnx backend can now be built for amd's rocm.
* Fixed a bug where the Contempt effect on eval was too low for nets with
natively higher draw rates.
* Made the WDL Rescale sharpness limit configurable via the `--wdl-max-s` hidden
option.
* Several assorted fixes and code cleanups.
v0.30.0 (2023-07-21)
~~~~~~~
* WDL_mu score type is now the default and the mlh-threshold default was
changed from 0 to 0.8.
* Fixes for contempt with infinite search and pondering and for the wdl display
when pondering.
v0.30.0-rc2 (2023-06-15)
~~~~~~~
* WDL conversion for more realistic WDL score and contempt. Adds an Elo based
WDL transformation of the NN value head output. Helps with more accurate play
at high level (WDL sharpening), more aggressive play against weaker opponents
and draw avoiding openings (contempt), piece odds play. There will be a blog
post soon explaining in detail how it works.
* A new score type `WDL_mu` which follows the new eval convention, where +1.00
means 50% white win chance.
* Simplified to a single `--draw-score` parameter, adjusting the draw score from
white's perspective: 0 gives standard scoring, -1 gives Armageddon scoring.
* Updated describenet for new net architectures.
* Added a `first-move-bonus` option to the legacy time manager, to accompany
`book-ply-bonus` for shallow openings.
* Changed mlh threshold effect to create a smooth transition.
* Revised 'simple' time manager.
* A new spinlock implementation (selected with `--search-spin-backoff`) to help
with many cpu threads (e.g. 128 threads), obviously for cpu backends only.
* Some assorted fixes and code cleanups.
v0.30.0-rc1 (2023-04-24)
~~~~~~~
* Support for networks with attention body and smolgen added to blas, cuda,
metal and onnx backends.
* Persistent L2 cache optimization for the cuda backend. Use the
`cache_opt=true` backend option to turn it on.
* Some performance improvements for the cuda, onnx and blas backends.
* Added the `threads` backend option to onnx, defaults to 0 (let the
onnxruntime decide) except for onnx-cpu that defaults to 1.
* The onnx-dml package now includes a `directml.dll` installation script.
* Some users experienced memory issues with onnx-dml, so the defaults were
changed. This may affect performance, in which case you can use the `steps=8`
backend option to get the old behavior.
* The Python bindings are available as a package, see the README for
instructions.
* Some assorted fixes and code cleanups.
v0.29.0 (2022-12-13)
~~~~~~~
* Updated onednn version to the latest one.
v0.29.0-rc1 (2022-12-09)
~~~~~~~
* New metal backend for apple systems. This is now the default backend for
macos builds.
* New onnx-dml backend to use DirectML under windows, has better net
compatibility than dx12 and is faster than opencl. See the README for use
instructions, a separate download of the DirectML dll is required.
* Full attention policy support in cuda, cudnn, metal, onnx, blas, dnnl, and
eigen backends.
* Partial attention policy support in onednn backend (good enough for T79).
* Now the onnx backends can use fp16 when running with a network file (not with
.onnx model files). This is the default for onnx-cuda and onnx-dml, can be
switched on or off with by setting the `fp16` backend option to `true` or
`false` respectively.
* The onednn package comes with a dnnl compiled to allow running on an intel gpu
by adding `gpu=0` to the backend options.
* The default net is now 791556 for most backends except opencl and dx12 that
get 753723 (as they lack attention policy support).
* Support for using pgn book with long lines in training: selfplay can start at
a random point in the book.
* New "simple" time manager.
* Support for double Fischer random chess (dfrc).
* Added TC-dependent output to the backendbench assistant.
* Starting with this version, the check backend compares policy for valid moves
after softmax.
* Some assorted fixes and code cleanups.
v0.29.0-rc0 (2022-04-03)
~~~~~~~
* Initial support for attention policy, only cuda backend and partially in
blas/dnnl/eigen (good enough for T79).
* Non multigather (legacy) search code and `--multigather` option are removed.
* 15b default net is now 753723.
* The onnx backend now allows selecting gpu to use.
* Improved error messages for unsupported network files.
* Some assorted fixes.
v0.28.2 (2021-12-13)
~~~~~~~
* No changes from v0.28.1-rc1 as the v0.28.1 release was botched.
v0.28.1 (2021-12-12)
~~~~~~~
* No changes from rc1.
v0.28.1-rc1 (2021-12-05)
~~~~~~~
* Improved cuda performance for 512 filter networks on Amprere GPUs.
* Several fixes for the onnx backend.
* Command line options for network file conversion to/from onnx.
* Documentation updates.
* Correctness fixes for rescorer support functions.
v0.28.0 (2021-08-25)
~~~~~~~
* Fixed an issue with small third-party nets on the cuda/cudnn backends.
* Minor tweak to the default task-workers for the cpu packages.
v0.28.0-rc2 (2021-08-20)
~~~~~~~
* The cuda backend option multi_stream is now off by default. You should
consider setting it to on if you have a recent gpu with a lot of vram.
* The default time manager is back to "legacy".
* Updated default parameters.
* Newer and stronger nets are included in the release packages.
* Added support for onnx network files and runtime with the "onnx" backend.
* Several bug and stability fixes.
v0.28.0-rc1 (2021-06-16)
~~~~~~~
* Multigather is now made the default (and also improved). Some search settings
have changed meaning, so if you have modified values please discard them.
Specifically, `max-collision-events`, `max-collision-visits` and
`max-out-of-order-evals-factor` have changed default values, but other options
also affect the search. Similarly, check that your gui is not caching the old
values.
* Performance improvements for the cuda/cudnn backends.
* Support for policy focus during training.
* Larger/stronger 15b default net for all packages except android, blas and dnnl
that get a new 10b network.
* The distributed binaries come with the mimalloc memory allocator for better
performance when a large tree has to be destroyed (e.g. after an unexpected
move).
* The `legacy` time manager will use more time for the first move after a long
book line.
* The `--preload` command line flag will initialize the backend and load the
network during startup.
* A 'fen' command was added as a UCI extension to print the current position.
* Experimental onednn backend for recent intel cpus and gpus.
v0.27.0 (2021-02-21)
~~~~~~~
* A better value for the backendbench Clippy threshold.
v0.27.0-rc2 (2021-02-18)
~~~~~~~
* Fix additional cases where 'invalid move' could be incorrectly reported.
* Replace WDL softmax in cudnn backend with same implementation as cuda
backend. This fixes some inaccuracy issues that were causing training
data to be rejected at a fairly low frequency.
* Ensure that training data Q/D pairs form valid WDL targets even if there
is accumulated drift in calculation.
* Fix for the calculation of the 'best q is proven' bit in training data.
* Multiple fixes for timelosses and infinite instamoving in smooth time
manager. Smooth time manager now made default after these fixes.
v0.27.0-rc1 (2021-02-06)
~~~~~~~
* Fix a bug which meant `position ... moves ...` didn't work if the moves
went off the end of the existing tree.
v0.27.0-rc0 (2021-02-06)
~~~~~~~
* Multigather search inspired by Ceres.
* V6 training format with additional info for training experiments.
* Updated default search parameters.
* A better algorithm for the backendbench assistant.
* Terminate search early if only 1 move isn't a proven loss.
* Various build system changes.
v0.26.3 (2020-10-10)
~~~~~~~
* Increased maximum value of TempDecayMoves.
v0.26.3-rc2 (2020-10-03)
~~~~~~~
* Fix for uninitialized variable that led to crashes with the cudnn backend.
* Correct windows support for systems with more than 64 threads.
* A new package is built for the `cuda` backend with cuda 11.1. The old cuda
package is renamed to `cudnn`.
v0.26.3-rc1 (2020-09-28)
~~~~~~~
* Residual block fusion optimization for cudnn backend, that depends on
`custom_winograd=true`. Enabled by default only for networks with up to 384
filters in fp16 mode and never in fp32 mode. Default can be overridden with
`--backend-opts=res_block_fusing=false` to disable (or `=true` to enable).
* New experimental cuda backend without cudnn dependency (`cuda-auto`, `cuda`
and `cuda-fp16` are available).
v0.26.2 (2020-08-31)
~~~~~~~
* No changes from rc1.
v0.26.2-rc1 (2020-08-28)
~~~~~~~~~~~
* Repetitions in the search tree are marked as draws, to explore more promising
lines. Enabled by default (except in selfplay mode) use
`--two-fold-draws=false` to disable.
* Syzygy tablebase files can now be used in selfplay. Still need to add
adjudication support before we can consider using this for training.
* Default net updated to 703810.
* Fix for book with CR/LF line endings.
* Updated Eigen wrap to use new download link.
v0.26.1 (2020-07-15)
~~~~~~~
* Fix a bug where invalid openings-pgn settings would result in the book
being ignored rather than used.
* Add support for compressed book files.
v0.26.0 (2020-07-03)
~~~~~~~
* No changes from rc1.
v0.26.0-rc1 (2020-06-29)
~~~~~~~~~~~
* Verbose move stats now includes a line for the root node itself.
* Added optional `alphazero` time manager type for fixed fraction of
remaining time per move.
* The WL score is now tracked with double pecision to improve accuracy
during very long search.
* Fix for a performance bug when playing from tablebase position with
tablebases enabled and the PV move was changing frequently.
* Illegal searchmove restrictions will now be ignored rather than crash.
* Policy is cleared for terminal losses to encourage better quality MLH
estimates by reducing how many visits a move that will not be selected
(unless all other options are equally bad) receives.
* Smart pruning will now cause leela to play immediately once mate score has
been declared.
* Fix an issue where sometimes the pv reported wouldn't match the move that
would be selected at that moment.
* Improvement for logic for when to disable custom_winograd optimization to
avoid running out of video ram.
* `--show-hidden` can now be specified after `--help` and still work.
* Performance tuning for populating the policy into nodes after nn eval
completes.
* Enable custom optimized SE paths for nets with 384 filters when using the
custom_winograd=false path.
* Updates to zlib/gtest/eigen when included via meson wrap.
* Added build option to build python bindings to the lc0 engine.
* Only show the git hash in uci name if not a release tag build.
* Add `--nps-limit` option to artificially reduce nps to make for easier
opponent or whatever other reason you want.
* Fixed a bug where search tree shape could be affected even when the
`--smart-pruning-factor` setting was 0.
* Changed the search logic to find the lc0.config file if left on the default
value.
* Changed the search logic to find network files in autodiscover mode.
* Changed the logic to determine the default location for training games
generated by selfplay in training mode.
* Changed the logic to decide where to look for the opencl backend tuning
settings file.
* Android binaries published by appveyor are now stripped.
* Build can now use system installed eigen if available.
* When nodes in the tree get proven terminal, parents are updated as if they
had always been terminal. This allows for faster convergence on more
accurate MLH estimates amongst other details.
* Removed shortsightedness and logit-q options that have not found a reliable
use case.
* Fixed a bug where m_effect calculated as part of S in verbose move stats was
not consistent with the value used in search itself.
* Added 'pro' mode as an alternative to `--show-hidden` for UCI hosts that do
not support command line arguments. Simply rename the lc0 binary to include
'pro' in order to enable.
* `backendbench` now has a `--clippy` option to try and auto suggest which
batch size is a good idea.
* The demux backend now splits the batch into equal sizes based on the number
of threads that demux is using rather than number of backends. By default
this is no change as usually there is 1 thread per backend. But it allows
to more easily use demux against a blas backend sending one chunk per core.
* Added support for new training input variants canonical_hectoplies and
canonical_hectoplies_armageddon.
* Fixed a bug where if the network search paths for autodiscover contain files
which lc0 cannot open it would error out rather than continuing on to other
files.
* Blas backends no longer have a `blas_cores` option, as it never seemed useful
compared to running more threads at a higher level.
* `--help-md` option removed as it was deemed not very useful.
* Updated to the latest version of dnnl for the dnnl build.
* Selfplay mode now supports per color settings in addition to per player
settings. Per player settings have higher priority if there is a conflict.
This will be used as part of armageddon training.
* Added a new experimental backend type: `recordreplay`. This allows to
record the output of a backend under a particular search and then replay it
back again later. Theoretically this lets you simulate a CPU bottlenecked
environment but still use a search tree that is a match for what might be a
GPU bottlenecked environment. In practice there are a lot of corner cases
where replay is not reliable yet. At a minimum you must disable prefetch.
* During search the node tree is occasionally compacted to reduce cache misses
during the search tree walk. New option `--solid-tree-threshold` can be used
to adjust how aggressive this optimization is. Note that very small values
can cause very large growth in ram usage and are not a good idea. The default
value is a little conservative, if you have plenty of spare ram it can be
good to decrease it a bit.
* Small performance optimization for windows build with MLH enabled.
* Meson configuration changed to build with LTO by default. Note that meson
does not always configure visual studio project files to apply this
correctly on windows.
* The included net in appveyor builds is now 703350. This network supports MLH
although the default MLH parameters are still threshold 1.0 which means it
will not trigger without parameter adjustment.
* New backend option to explicitly override the net details and force MLH
disabled. If you weren't going to use MLH anyway, this may give a tiny nps
increase.
* New flag `--show-movesleft` (or `UCI_ShowMovesLeft` for UCI hosts that
support it) will cause movesleft (in moves) to be reported in the uci info
messages. Only works with networks that have MLH enabled.
* More sensible default values for MLH are in. Note that threshold is still
1.0 by default, so that will still need to be configured to enable it.
* The `smooth-experimental` time manager has been renamed `smooth` and support
added to increase search time whenever the best N does not correspond with
the move with best utility estimate. `legacy` remains the default for now
as `smooth` has only been tuned for short time controls and evidence suggests
it doesn't scale with these defaults.
* Selfplay mode now supports a logfile parameter just like normal mode.
* Reinstated the 4 billion visit limit on search to avoid overflowing counters
and causing very strange behavior to occur.
* Performance optimization to make tree walk faster by ensuring that node
edges are always sorted by policy. This has some very small side effects to
do with tiebreaks in search no longer always being dominated by movegen
order.
* Appveyor built blas and Android binaries now default to minibatch size 1
and prefetch 0, which should be much better than the normal GPU optimized
defaults. Note this *only* affects Appveyor built binaries.
* The included client in Windows Appveyor releases is now v27 and is named
`lc0-training-client.exe` instead of `client.exe`.
v0.25.1 (2020-04-30)
~~~~~~~
* Fixed some issues with cudnn backend on the 16xx GTX models and also for
low memory devices with large network files where the new optimizations
could result in out of memory errors.
* Added a workaround for a cutechess issue where reporting depth 0 during
instamoves causes it to ignore our info message.
v0.25.0 (2020-04-28)
~~~~~~~
* Relax strictness for complete standard fens in uci and opening books. Fen
must still be standard, but default values will be substituted for sections
that are missing.
* Restore some backwards compatibility in cudnn backends that was lost with
the addition of the new convolution implementation. It is also on by default
for more scenarios, although still off for fp16 on RTX gpus.
* Small logic fix for nps smoothing in the new optional experimental time
manager.
v0.25.0-rc2 (2020-04-23)
~~~~~~~~~~~
* Increased upper limit for maximum collision events.
* Allow negative values for some of the extended moves left head parameters.
* Fix a critical bug in training data generation for input type 3.
* Fix for switching between positions in uci mode that only differ by 50 move
rule in initial fen.
* Some refinements of certainty propagation.
* Better support for c++17 implementations that are missing charconv.
* Option to more accurately apply time management for uci hosts using
cuteseal or similar timing techniques.
* Fix for selfplay mode to allow exactly book length total games.
* Fix for selfplay opening books with castling moves starting from chess960 fens.
* Add build option to override nvcc compiler.
* Improved validity checking for some uci input parameters.
* Updated the Q to CP conversion formula to better fit recent T60 net outputs to
expectations.
* Add a new experimental time manager.
* Bug fix for the Q+U in verbose move stats. It is now called S: and contains
the total score, including any moves left based effect if applicable.
* New temperature decay option to allow to delay the start of decay.
* All temperature options have been hidden by default.
* New optional cuda backend convolution implementation. Off by default for
cudnn-fp16 until an issue with cublas performance on some gpus is resolved.
v0.25.0-rc1 (2020-04-09)
~~~~~~~~~~~
* Now requires a c++17 supporting compilation environment to build.
* Support for Moves Left Head based networks. Includes options to adjust search
to favour shorter/longer wins/losses based on the moves left head output.
* Mate score reporting is now possible, and move selection will prefer shorter
mates over longer ones when they are proven.
* Training now outputs v5 format data. This passes the moves left information
back to training. This also includes support for multiple sub formats,
including the existing standard, a new variant which can encode FRC960
castling, and also a further extension of that which tries to make training
data cannonical, so there aren't multiple positions that are trivially
equivalent with different network inputs.
* Benchmark now includes a suite of 34 positions to test by default instead of
just start position.
* Tensorflow backend works once more, almost just as hard to compile as it used
to be though.
* `--noise` flag is gone, use `--noise-epsilon=0.25` to get the old behavior.
* Some bug fixes related to drawscore.
* Selfplay mode now defaults to the same value as match play for
`--root-has-own-cpuct-params` (true).
* Some advanced time management parameters are now accessed via the new
`--time-manager` parameter instead of individual parameters.
* Windows build script has been modernized.
* Separate Eigen backend option for CPU.
* Random backend no longer requires a network.
* Random backend supports producing training data of any input format sub type.
* Integer parameters now give better error messages when given invalid values.
v0.24.1 (2020-03-15)
~~~~~~~
* Fix issues where logitq was being passed as drawscore and logitq wasn't
passed to some GetQ calls. Causing major performance issues when either
setting was non-default.
v0.24.0 (2020-03-11)
~~~~~~~
* New parameter `--max-out-of-order-evals-factor` replaces
`--max-out-of-order-evals` that was introduced in v0.24.0-rc3 and provides
the factor to multiply the maximum batch size to set maximum number
out-of-order evals per batch. The default value of 1.0 keeps the behavior
of previous releases.
* Bug fix for hangs with very early stop command from non-conforming UCI hosts.
v0.24.0-rc3 (2020-03-08)
~~~~~~~~~~~
* New parameter `--max-out-of-order-evals` to set maximum number out-of-order
evals per batch (was equal to the batch size before).
* It's now possible to embed networks into the binary. It allows easier builds
of .apk for Android.
* New parameter `--smart-pruning-minimum-batches` to only allow smart pruning
to stop after at least k batches, preventing insta-moves on slow backends.
v0.24.0-rc2 (2020-03-01)
~~~~~~~~~~~
* All releases are now bundled with network id591226 (and the file date is old
enough so it has a lower priority than networks that you already may have
in your directory).
* Added a 'backendbench' mode to benchmark NN evaluation performance without
search.
* Android builds are added to the official releases.
v0.24.0-rc1 (2020-02-23)
~~~~~~~~~~~
* Introduced DirectX12 backend.
* Optimized Cpuct/FPU parameters are now default.
* There is now a separate set of CPuct parameters for the root node.
* Support of running selfplay games from an opening book.
* It's possible to adjust draw score from 0 to something else.
* There is a new --max-concurrent-seachers parameter (default is 1) which
helps with thread congestion at the beginning of the search.
* Cache fullness is not reported in UCI info line by default anymore.
* Removed libproto dependency.
v0.23.3 (2020-02-18)
~~~~~~~
* Fix a bug in time management which sometimes led to insta-moves in long time
control.
v0.23.2 (2019-12-31)
~~~~~~~
* Fixed a bug where odd length openings had reversed training data results in
selfplay.
* Fixed a bug where zero length training games could be generated due to
discard pile containing positions that were already considered end of game.
* Add cudnn-auto backend.
v0.23.1 (2019-12-03)
~~~~~~~
* Fixed a bug with Lc0 crashing sometimes during match phase of training game
generation.
* Release packages now include CUDNN version without DLLs bundled.
v0.23.0 (2019-12-01)
~~~~~~~
* Fixed the order of BLAS options so that Eigen is lower priority, to match
assumption in check_opencl patch introduced in v0.23.0-rc2.
v0.23.0-rc2 (2019-11-27)
~~~~~~~~~~~
* Fixes in nps and time reporting during search.
* Introduced DNNL BLAS build for modern CPUs in addition to OpenBLAS.
* Build fixes on MacOS without OpenCL.
* Fixed smart pruning and KLDGain trying to stop search in `go infinite` mode.
* OpenCL package now has check_opencl tool to find computation behaves sanely.
* Fixed a bug in interoperation of shortsighteness and certainty propagation.
v0.23.0-rc1 (2019-11-21)
~~~~~~~~~~~
* Support for Fischer Random Chess (`UCI_Chess960` option to enable FRC-style
castling). Also added support for FRC-compatible weight files, but no training
code yet.
* New option `--logit-q` (UCI: `LogitQ`). Changes subtree selection algorithm a
bit, possibly making it stronger (experimental, default off).
* Lc0 now reports WDL score. To enable it, use `--show-wdl` command-line
argument or `UCI_ShowWdl` UCI option.
* Added "Badgame split" mode during the training. After the engine makes
inferior move due to temperature, the game is branched and later the game is
replayed from the position of the branch.
* Added experimental `--short-sightedness` (UCI: `ShortSightedness`) parameter.
Treats longer variations as more "drawish".
* Lc0 can now open Fat Fritz weight files.
* Time management code refactoring. No functional changes, but will make time
management changes easier.
* Lc0 logo is now printed in red! \o/
* Command line argument `-v` is now short for `--verbose-move-stats`.
* Errors in `--backend-opts` parameter syntax are now reported.
* The most basic version of "certainty propagation" feature (actually without
"propagation"). If the engine sees checkmate, it plays it!
(before it could play other good move).
* Benchmark mode no longer supports smart pruning.
* Various small changes: hidden options to control Dirichlet noise, floating
point optimizations, Better error reporting if there is exception in worker
thread, better error messages in CUDA backend.
v0.22.0 (2019-08-05)
~~~~~~~
(no changes)
v0.22.0-rc1 (2019-08-03)
~~~~~~~~~~~
* Remove softmax calculation from backends and apply it after filtering for
illegal moves to ensure spurious outputs on illegal moves don't reduce (or
entirely remove) the quality of the policy values on the legal moves.
* Fix for blas backend allocation bug with small network sizes.
* The blas backend can be built with eigen - the result is reasonably optimized
for the build machine.
* Other small tweaks piled up in master branch.
v0.21.4 (2019-07-28)
~~~~~~~~~~~~~~~~~~~~
* A fix for crashes that can occur during use of sticky-endgames.
* Change the false positive value reported when in wdl style resign and display
average nodes per move as part of tournament stats in selfplay mode.
v0.21.3 (2019-07-21)
~~~~~~~
* Fix for potential memory corruption/crash in using small networks or using the
wdl head with cuda backends. (#892)
* Fix for building with newer versions of meson. (#904)
v0.21.2 (2019-06-09)
~~~~~~~
* Divide by a slightly smaller divisor to truncate to +/-12800. (#880)
v0.21.2-rc3 (2019-06-08)
~~~~~~~~~~~
* Centipawn conversion (#860)
v0.21.2-rc2 (2019-05-22)
~~~~~~~~~~~
* Add 320 and 352 channel support for fused SE layer (#855)
* SE layer fix when not using fused kernel (#852)
* Fp16 nchw for cudnn-fp16 backend (support GTX 16xx GPUs) (#849)
v0.21.2-rc1 (2019-05-05)
~~~~~~~~~~~
* Make --sticky-endgames on by default (still off in training) (#844)
* update download links in README (#842)
* Recalibrate centipawn formula (#841)
* Also make parents Terminal if any move is a win or all moves are loss or draw. (#822)
* Use parent Q as a default score instead of 0 for unvisited pv. (#828)
* Add stop command to selfplay interactive mode to allow for graceful exit. (#810)
* Increased hard limit on batch size in opencl backend to 32 (#807)
v0.21.0-rc2 (2019-03-06)
~~~~~~~~~~~
* Add support for cudnn7.0 (#717)
* Informative Tournament Stats (#698)
* Memory leak fix cuda backend (#747)
* cudnn-fp16 fallback path for unusual se-ratios. (#739)
* Cudnn 7.4.2 in packaged binary and warning for using old cudnn with new gpu (#741)
* Move mode specific options to end of help. (#745)
* LogLiveStats hidden option (#754)
* Optional markdown support for help output (#769)
* Improved folding of batch norm into weights and biases - fixes negative gamma bug. (#779)
v0.21.0-rc1 (2019-02-16)
~~~~~~~~~~~
* Check Syzygy tablebase file sizes for corruption (#690)
* search for nvcc on the path first (#709)
* AZ-style policy head support (#712)
* Implement V4TrainingData (#722)
* WDL value head support (#635)
* Add option for doing kldgain thresholding rather than absolute visit
limiting (#721)
* Easily run latest releases of lc0 and client using NVIDIA docker (#621)
* Add WDL style resign option. (#724)
* Add a uniform output option for random backend to support a0 seed data
style (#725)
* Fix c hw switching in cudnn-fp16 mode with convolution policy head.
(#729)
* misc (non-functional) changes to cudnn backend (#731)
* handle 64 filter SE networks (#624)
v0.20.2 (2019-02-01)
~~~~~~~~~~~
* Favor winning moves that minimize DTZ to reduce shuffling by assuming
repeated position by default (#708)
* Print cuda and gpu info, warn if mismatches are noticed (#711)
v0.20.2-rc1 (2019-01-27)
~~~~~~~~~~~
* no terminal multivisits (#683)
* better fix for issue 651 (#693)
* Changed output of --help flag to stdout rather than stderr (#687)
* Movegen speedup via magic bitboards (#640)
* modify default benchmark setting to run for 10 seconds (#681)
* Fix incorrect index in OpenCL Winograd output transform (#676)
* Update OpenCL (#655)
v0.20.1 (2019-01-07)
~~~~~~~~~~~
* Change to atomic for cache capacity. (#665)
v0.20.1-rc3 (2019-01-07)
~~~~~~~~~~~
* Remove ffast-math from the default flags (#661)
v0.20.1-rc2 (2019-01-05)
~~~~~~~~~~~
* Don't use Winograd for 1x1 conv. (#659)
* Fix issues with pondering and search limits. (#658)
* Check for zero capacity in cache (#648)
* fix undefined behavior in DiscoverWeightsFile() (#650)
* fix fastmath.h undefined behavior and clean it up (#643)
v0.20.1-rc1 (2019-01-01)
~~~~~~~~~~~
* Simplify movestogo approximator to use median residual time. (#634)
* Replace time curve logic with movestogo approximator. (#271)
* Cache best edge to improve PickNodeToExtend performance. (#619)
* fix building with tensorflow 1.12 (#626)
* Minor changes to `src/chess` (#606)
* make uci search parameters the defaults ones (#609)
* Preallocate nodes in advance of their need to avoid the allocation being
behind a mutex. (#613)
* imrpove meson error when no backends enabled (#614)
* allow building with the mklml library as an mkl alternative (#612)
* Only build the history up if we are actually going to extend the position.
(#607)
* fix warning (#604)
v0.20.0 (2019-01-01)
~~~~~~~~~~~
* no lto builds by default (#625)
v0.20.0-rc2 (2018-12-24)
~~~~~~~~~~~
* Fix for demux backend to match cuda expected threading model for
computations. (#605)
v0.20.0-rc1 (2018-12-22)
~~~~~~~~~~~
* Squeeze-and-Excitation Networks are now supported! (lc0.org/se)
* Older text network files are no longer supported.
* Various performance fixes (most major being having fast approximate math
functions).
* For systems with multiple GPUs, in addition to "multiplexing" backend
we now also have "demux" backend and "roundrobin" backend.
* Compiler settings tweaks (use VS2017 for windows builds, always have LTO
enabled, windows releases have PGO enabled).
* Benchmark mode has more options now (e.g. movetime) and saner defaults.
* Added an option to prevent engine to resign too early (used in training).
* Fixed a bug when number of visits could be too high in collision nodes.
The fix is pretty hacky, there will be better fix later.
* 32-bit version compiles again.
v0.19.1 (2018-12-10)
~~~~~~~
(no changes relative to v0.19.1-rc2)
v0.19.1-rc2 (2018-12-07)
~~~~~~~~~~~
* Temperature and FPU related params. (#568)
* Rework Cpuct related params. (#567)
v0.19.1-rc1 (2018-12-06)
~~~~~~~~~~~
* Updated cpuct formula from alphazero paper. (#563)
* remove UpdateFromUciOptions() from EnsureReady() (#558)
* revert IsSearchActive() and better fix for one of #500 crashes (#555)
v0.19.0 (2018-11-19)
~~~~~~~
* remove Wait() from EngineController::Stop() (#522)
v0.19.0-rc5 (2018-11-17)
~~~~~~~~~~~
* OpenCL: replace thread_local with a resource pool. (#516)
* optional wtime and btime (#515)
* Make convolve1 work with workgroup size of 128 (#514)
* adjust average depth calculation for multivisits (#510)
v0.19.0-rc4 (2018-11-12)
~~~~~~~~~~~
* Microseconds have 6 digits, not 3! (#505)
* use bestmove_is_sent_ for Search::IsSearchActive() (#502)
v0.19.0-rc3 (2018-11-07)
~~~~~~~~~~~
* Fix OpenCL tuner always loading the first saved tuning (#491)
* Do not show warning when ComputeBlocking() takes too much time. (#494)
* Output microseconds in log rather than milliseconds. (#495)
* Add benchmark features (#483)
* Fix EncodePositionForNN test failure (#490)
v0.19.0-rc2 (2018-11-03)
~~~~~~~~~~~
* Version v0.19.0-rc1 reported it's version as v0.19.0-dev
Therefore v0.19.0-rc2 is released with this issue fixed.
v0.19.0-rc1 (2018-11-03)
~~~~~~~~~~~
* Search algorithm changes
When visiting terminal nodes and collisions, instead of counting that as one
visit, estimate how many subsequent visits will also go to the same node, and
do a batch update.
That should slightly improve nps near terminal nodes and in multithread
configurations. Command line parameters that control that:
--max-collision-events – number of collision events allowed per batch.
Default is 32. This parameter is roughly equivalent to
--allowed-node-collisions in v0.18.
--max-collision-visits – total number of estimated collisions per NN batch.
Default is 9999.
* Time management
Multiple changes have been done to make Leela track used time more precisely
(particularly, the moment when to start timer is now much closer to the moment
GUIs start timer).
For smart pruning, Leela's timer only starts when the first batch comes from
NN eval. That should help against instamoves, especially on non-even GPUs.
Also Leela stops the search quicker now when it sees that time is up (it could
continue the search for hundreds of milliseconds after that, which caused time
trouble if opponent moves very fast).
Those changes should help a lot in ultra-bullet configurations.
* Better logging
Much more information is outputted now to the log file. That will allow us to
easier diagnose problems if they occur. To have debug file written, add a
command line option:
--logfile=/path/to/logfile
(or short option "-l /path/to/logfile", or corresponding UCI option "LogFile")
It's recommended to always have logging on, to make it easier to report bugs
when it happens.
* Configuration parameters change
Large part of parameter handling has been reworked. As the result:
All UCI parameters have been changed to have more "classical" look.
E.g. was "Network weights file path", became "WeightsFile".
Much more detailed help is shown than before when you run
./lc0 --help
Some flags have been renamed, e.g.
--futile-move-aversion
is renamed back to
--smart-pruning-factor.
After setting a parameter (using command line parameter or uci setoption
command), uci command "uci" shows updated result. That way you can check the
current option values.
Some command-line and UCI options are hidden now. Use --show-hidden command
line parameter to unhide them. E.g.
./lc0 --show-hidden --help
Also, in selfplay mode the per player configuration format has been changed
(although probably noone knew that anyway):
Was: ./lc0 selfplay player1: --movetime=14
Became: ./lc0 selfplay --player1.movetime=14
* Other
"go depth X" uci command now causes search to stop when depth information in
uci info line reaches X. Not that it makes much sense for it to work this way,
but at least it's better than noting.
Network file size can now be larger than 64MB.
There is now an experimental flag --ramlimit-mb. The engine tries to estimate
how much memory it uses and stops search when tree size (plus cache size)
reaches RAM limit. The estimation is very rough. We'll see how it performs and
improve estimation later.
In situations when search cannot be stopped (`go infinite` or ponder),
`bestmove` is not automatically outputted. Instead, search stops progress and
outputs warning.
Benchmark mode has been implemented. Run run, use the following command line:
./lc0 benchmark
This feature is pretty basic in the current version, but will be expanded later.
As Leela plays much weaker in positions without history, it now is able to
synthesize it and do not blunder in custom FEN positions. There is a
--history-fill flag for it. Setting it to "no" disables the feature, setting
to "fen_only" (default) enables it for all positions except chess start
position, and setting it to "always" enables it even for startpos.
Instead of output current win estimation as centipawn score approximation,
Leela can how show it's raw score. A flag that controls that is --score-type.
Possible values:
- centipawn (default) – approximate the win rate in centipawns, like Leela
always did.
- win_percentage – value from 0 to 100.0 which represents expected score in
percents.
- Q – the same, but scales from -100.0 to 100.0 rather than from 0 to 100.0
v0.18.1 (2018-10-02)
~~~~~~~
* Fix for falling into threefold repetition in a winning endgame tablebase position.
v0.18.0 (2018-09-30)
~~~~~~~
* No changes from rc2 except the version.
v0.18.0-rc2 (2018-09-26)
~~~~~~~~~~~
* Severe bug fixed: Race condition when out-of-order-eval was enabled (and it
was enabled by default)
* Windows 32-bit builds are now possible (CPU only for now)
v0.18.0-rc1 (2018-09-24)
~~~~~~~~~~~
KNOWN BUG!
* We have credible reports that in some rare cases Lc0 crashes!
However, we were not able to reproduce it reliably. If you see the crash,
please report to devs! What seems to increase crash probability:
- Very short move time (milliseconds)
- Proximity to a checkmate (happens 1-3 moves before the checkmate)
New features:
* Endgame tablebases support! Both WDL and DTZ now.
* Added MultiPv support.
Time management changes:
* Introduced --immediate-time-use flag. Yes, yet another time management
flag. Posible values are between 0.0 and 1.0. Setting it closer to
1.0 makes Leela use time saved from futile search aversion earlier.
* Some time management parameters were changed:
- Slowmover is 1.0 now (was 2.4)
- Immediate-time-use is 0.6 now (didn't exist before, so was 0.0)
* Fixed a bug, because of which futile search aversion tolerance was incorrectly
applied, which resulted in instamoves.
* Now search stops immediately when it runs out of budgeted time.
Should help against timeouts, especially on slow backends (e.g. BLAS).
* Move overhead now is a fixed time, doesn't depend on number of remaining
moves.
Other:
* Out of order eval is on by default. That brings slight nps improvement.
* Default FPU reduction is 1.2 now (was 0.9)
* Cudnn backend now has max_batch parameter.
(can be set for example like this --backend-opts=max_batch=100).
This is needed for lower end GPUs that didn't have enough VRAM for a buffer
of size 1024. Make sure that this setting is not lower than --minibatch-size.
* Small memory usage optimizations.
* Engine name in UCI response is shorter now. Fritz chess UI should be able
to work with Leela now
* Added flag --temp-visit-offset, will allow to offset temperature during
training.
* Command line and UCI parameter values are now checked for validity.
* You can now build for older processors that don't support the popcnt
instruction by passing -Dpopcnt=false to meson when building.
* 32-bit build is possible now. CPU only and we were only able to build it
in Linux for now, including Raspberry Pi.
* Threading issue which caused crash in heavily multithreaded environment
with slow backends was fixed.
v0.17.0 (2018-08-27)
~~~~~~~
No changes from rc2 except the version.
v0.17.0-rc2 (2018-08-21)
~~~~~~~~~~~
* Fixed a bug, that rule50 value was located in wrong place in a training data.