v0.32.0

In this release, the code has been reorganized and undergone major changes. Therefore this changelog will be less detailed and describe the changes in major groups.

• We have a new search API that allows search algorithms to co-exist. Currently available are classic (the default), dag-preview (more later), valuehead and policyhead. The default algorithm can be changed either at build time by the default_search option or by renaming the executable to include the algorithm name (e.g. lc0-valuehead).
• We also have a new backend interface that is chess oriented and not tied to the network architecture. The existing backends still use the old interface through a wrapper.
• The source code is reorganized, with a more logical directory structure.
• The original search was ported to the new search and backend interfaces and is renamed to classic. This has allowed some streamlining and simplifications.
• The dag-preview search is the DAG algorithm that lived in a separate branch up to now. It hasn't been so well tested, that's why it has "preview" in its name for now, but lives in the src/search/dag-classic directory.
• The valuehead search replaces ValueOnly mode and selects the move with the best value head evaluation.
• The policyhead search is equivalent to a single node search, selecting the best move using just the policy head.
• The new default_backend build option allows to override the fixed priority for the backend used by default.
• The new native_arch build option to override the -march=native compiler default for linux release builds, to help with distribution package creation.
• We have a new sycl backend that will work with amd, intel and nvidia gpus.
• There is also a new onnx-trt backend, using tensorrt on nvidia gpus.
• The metal backend received several improvements.
• Support simple/normal/pro mode in options was cleaned up, using a common mechanism.
• Added the wait uci extension command to allow running simple tests from the command line.
• Removed the fen uci extension command as it was unnecessarily complicating things.
• Some preliminary fp8 support was added for onnx and xla. This is not functional, just there to make experimentation easier.
• Several build system changes and improvements.
• We now generate binaries for cuda 12, onnx-trt and macos.
• The onnx-trt package has a readme with instructions and an install script.
• Support for using lc0 with openbench.
• New bench mode for a quicker benchmark.
• RPE nets are now detected and give an error instead of bad results.
• The rescorer code and training data header were refactored to make them usable by external tools.
• Assorted small fixes and improvements.

v0.32.0-rc2

In this version:

• Fix for onnx-trt bug, where the wrong network could be used from the cache.
• Added code to detect RPE nets and give an error instead of bad results.
• Better instructions in the readme and install script for onnx-trt.
• Made UCI_ShowWDL again off by default again as some GUIs have issues.
• Fixed a long standing issue when compiled with -ffast-math (or icx -O3).
• Several improvements to the sycl backend.
• Several improvements to the metal backend.
• Refactored the rescorer code and training data header to make them usable by external tools.
• Relaxed cuda/cudnn version checks so that no warnings are shown for mismatched versions that are supported.
• Several build system updates.
• Assorted small fixes and improvements.

v0.32.0-rc1

In this release, the code has been reorganized and undergone major changes. Therefore this changelog will be less detailed and describe the changes in major groups.

• We have a new search API that allows search algorithms to co-exist. Currently available are classic (the default), dag-preview (more later), valuehead and policyhead. The default algorithm can be changed either at build time by the default_search option or by renaming the executable to include the algorithm name (e.g. lc0-valuehead).
• We also have a new backend interface that is chess oriented and not tied to the network architecture. The existing backends still use the old interface through a wrapper.
• The source code is reorganized, with a more logical directory structure.
• The original search was ported to the new search and backend interfaces and is renamed to classic. This has allowed some streamlining and simplifications.
• The dag-preview search is the DAG algorithm that lived in a separate branch up to now. It hasn't been so well tested, that's why it has "preview" in its name for now, but lives in the src/search/dag-classic directory.
• The valuehead search replaces ValueOnly mode and selects the move with the best value head evaluation.
• The policyhead search is equivalent to a single node search, selecting the best move using just the policy head.
• The new default_backend build option allows to override the fixed priority for the backend used by default.
• The new native_arch build option to override the -march=native compiler default for linux release builds, to help with distribution package creation.
• We have a new sycl backend that will work with amd, intel and nvidia gpus.
• There is also a new onnx-trt backend, using tensorrt on nvidia gpus.
• Support simple/normal/pro mode in options was cleaned up, using a common mechanism.
• Added the wait uci extension command to allow running simple tests from the command line.
• Removed the fen uci extension command as it was unnecessarily complicating things.
• Some preliminary fp8 support was added for onnx and xla. This is not functional, just there to make experimentation easier.
• Several build system changes and improvements.
• We now generate binaries for cuda 12, onnx-trt and macos.
• Support for using lc0 with openbench.
• New bench mode for a quicker benchmark.
• Assorted small fixes and improvements.

v0.31.2

In this version:

• Updated the WDL_mu centipawn fallback.
• Fix for build issues with newer Linux c++ libraries.
• Fix for an XLA Mish bug.
• Minor README.md update.

v0.31.1

In this version:

• Make WDL_mu score type work as intended.
• Fix macos CI builds.

v0.31.0

In this version:

• 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.
• The search task workers can be set automatically, to either 0 for cpu backends or up to 4 depending on the number of cpu cores. This is enabled by --task-workers=-1 (the new default).
• Changed cuda compilation options to use -arch=native or -arch=all-major if no specific version is requested, with fallback for older cuda that don't support those options.
• Updated android builds to use openblas 0.3.27.
• The WDLDrawRateTarget option now accepts the value 0 (new default) to retain raw WDL values if WDLCalibrationElo is set to 0 (default).
• Improvements to the verbose move stats if `WDLEvalObjectivity is used.
• The centipawn score is displayed by default for old nets without WDL output.
• Several assorted fixes and code cleanups.

v0.31.0-rc3

In this version:

• The WDLDrawRateTarget option now accepts the value 0 (new default) to retain raw WDL values if WDLCalibrationElo is set to 0 (default).
• Improvements to the verbose move stats if `WDLEvalObjectivity is used.
• The centipawn score is displayed by default for old nets without WDL output.
• Some build system improvements.

v0.31.0-rc2

In this version:

• Changed cuda compilation options to use -arch=native or -arch=all-major if no specific version is requested, with fallback for older cuda that don't support those options.
• Updated android builds to use openblas 0.3.27.
• A few small fixes.

v0.31.0-rc1

In this version:

• 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 evaluation, 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.
• The search task workers can be set automatically, to either 0 for cpu backends or up to 4 depending on the number of cpu cores. This is enabled by --task-workers=-1 (the new default).
• Several assorted fixes and code cleanups.

v0.30.0

In this version:

• Support for networks with attention body and smolgen added to blas, cuda, metal and onnx backends.
• 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. For details on how it works see https://lczero.org/blog/2023/07/the-lc0-v0.30.0-wdl-rescale/contempt-implementation/.
• A new score type WDL_mu which follows the new eval convention, where +1.00 means 50% white win chance.
• Changed mlh threshold effect to create a smooth transition.
• WDL_mu score type is now the default and the --moves-left-threshold default was changed from 0 to 0.8.
• 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.
• 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.
• 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.
• Fixes for contempt with infinite search/pondering and for the wdl display when pondering.
• Some assorted fixes and code cleanups.