# Example config for C++ (non-python) gtp bot

# SEE NOTES ABOUT PERFORMANCE AND MEMORY USAGE IN gtp_example.cfg

# Logs------------------------------------------------------------------------------------

# Where to output log?
logFile = gtp.log

# Controls the number of moves after the first move in a variation.
# analysisPVLen = 15

# Report winrates for analysis as (BLACK|WHITE|SIDETOMOVE).
reportAnalysisWinratesAs = BLACK

# Bot behavior---------------------------------------------------------------------------------------

# Handicap -------------

# Assume that if black makes many moves in a row right at the start of the game, then the game is a handicap game.
# This is necessary on some servers and for some GUIs and also when initializing from many SGF files, which may
# set up a handicap games using repeated GTP "play" commands for black rather than GTP "place_free_handicap" commands.
# However, it may also lead to incorrect undersanding of komi if whiteBonusPerHandicapStone = 1 and a server does NOT
# have such a practice.
# Defaults to true! Uncomment and set to false to disable this behavior.
# assumeMultipleStartingBlackMovesAreHandicap = true

# Passing and cleanup -------------

# Make the bot never assume that its pass will end the game, even if passing would end and "win" under Tromp-Taylor rules.
# Usually this is a good idea when using it for analysis or playing on servers where scoring may be implemented non-tromp-taylorly.
# Defaults to true! Uncomment and set to false to disable this.
conservativePass = true

# When using territory scoring, self-play games continue beyond two passes with special cleanup
# rules that may be confusing for human players. This option prevents the special cleanup phases from being
# reachable when using the bot for GTP play.
# Defaults to true! Uncomment and set to false if you want KataGo to be able to enter special cleanup.
# For example, if you are testing it against itself, or against another bot that has precisely implemented the rules
# documented at https://lightvector.github.io/KataGo/rules.html
# preventCleanupPhase = true

# Search limits-----------------------------------------------------------------------------------

# By default, if NOT specified in an individual request, limit maximum number of root visits per search to this much
maxVisits = 500
# If provided, cap search time at this many seconds
# maxTime = 60

# Number of threads to use in each search in parallel for any SINGLE position.
# NOTE: Analysis engine can specify number of POSITIONS to be able to search in parallel via command line argument
# so this number does not necessarily need to be larger than 1, although you can still set it larger if you prefer
# to analyze fewer positions in parallel but spend more threads on each position.
# Generally, having more threads on a single position will worsen the quality of search slightly, holding fixed the
# number of visits, and thread contention will reduce efficiency, so cross-position parallelization is preferable
# to numSearchThreads, but numSearchThreads is preferable if you want to reduce latency, and have individual
# searches complete faster by doing fewer of them at a time.
numSearchThreads = 6

# GPU Settings-------------------------------------------------------------------------------

# Maximum number of positions to send to GPU at once.
nnMaxBatchSize = 64
# Cache up to 2 ** this many neural net evaluations in case of transpositions in the tree.
nnCacheSizePowerOfTwo = 19
# Size of mutex pool for nnCache is 2 ** this
nnMutexPoolSizePowerOfTwo = 16
# Randomize board orientation when running neural net evals?
nnRandomize = true


# TO USE MULTIPLE GPUS:
# Set this to the number of GPUs you have and/or would like to use...
# AND if it is more than 1, uncomment the appropriate CUDA or OpenCL section below.
# numNNServerThreadsPerModel = 1


# CUDA GPU settings--------------------------------------
# These only apply when using the CUDA version of KataGo.

# IF USING ONE GPU: optionally uncomment and change this if the GPU you want to use turns out to be not device 0
# cudaDeviceToUse = 0

# IF USING TWO GPUS: Uncomment these two lines (AND set numNNServerThreadsPerModel above):
# cudaDeviceToUseThread0 = 0  # change this if the first GPU you want to use turns out to be not device 0
# cudaDeviceToUseThread1 = 1  # change this if the second GPU you want to use turns out to be not device 1

# IF USING THREE GPUS: Uncomment these three lines (AND set numNNServerThreadsPerModel above):
# cudaDeviceToUseThread0 = 0  # change this if the first GPU you want to use turns out to be not device 0
# cudaDeviceToUseThread1 = 1  # change this if the second GPU you want to use turns out to be not device 1
# cudaDeviceToUseThread2 = 2  # change this if the third GPU you want to use turns out to be not device 2

# You can probably guess the pattern if you have four, five, etc. GPUs.

# KataGo will automatically use FP16 or not based on the compute capability of your NVIDIA GPU. If you
# want to try to force a particular behavior though you can uncomment these lines and change them
# to "true" or "false". E.g. it's using FP16 but on your card that's giving an error, or it's not using
# FP16 but you think it should.
# cudaUseFP16 = auto
# cudaUseNHWC = auto


# OpenCL GPU settings--------------------------------------
# These only apply when using the OpenCL version of KataGo.

# Uncomment to tune OpenCL for every board size separately, rather than only the largest possible size
# openclReTunePerBoardSize = true

# IF USING ONE GPU: optionally uncomment and change this if the best device to use is guessed incorrectly.
# The default behavior tries to guess the 'best' GPU or device on your system to use, usually it will be a good guess.
# openclDeviceToUse = 0

# IF USING TWO GPUS: Uncomment these two lines and replace X and Y with the device ids of the devices you want to use.
# It might NOT be 0 and 1, some computers will have many OpenCL devices. You can see what the devices are when
# KataGo starts up - it should print or log all the devices it finds.
# (AND also set numNNServerThreadsPerModel above)
# openclDeviceToUseThread0 = X
# openclDeviceToUseThread1 = Y

# IF USING THREE GPUS: Uncomment these three lines and replace X and Y and Z with the device ids of the devices you want to use.
# It might NOT be 0 and 1 and 2, some computers will have many OpenCL devices. You can see what the devices are when
# KataGo starts up - it should print or log all the devices it finds.
# (AND also set numNNServerThreadsPerModel above)
# openclDeviceToUseThread0 = X
# openclDeviceToUseThread1 = Y
# openclDeviceToUseThread2 = Z

# You can probably guess the pattern if you have four, five, etc. GPUs.


# Root move selection and biases------------------------------------------------------------------------------
# Uncomment and edit any of the below values to change them from their default.
# Not all of these parameters are applicable to analysis, some are only used for actual play

# Temperature for the early game, randomize between chosen moves with this temperature
# chosenMoveTemperatureEarly = 0.5
# Decay temperature for the early game by 0.5 every this many moves, scaled with board size.
# chosenMoveTemperatureHalflife = 19
# At the end of search after the early game, randomize between chosen moves with this temperature
# chosenMoveTemperature = 0.10
# Subtract this many visits from each move prior to applying chosenMoveTemperature
# (unless all moves have too few visits) to downweight unlikely moves
# chosenMoveSubtract = 0
# The same as chosenMoveSubtract but only prunes moves that fall below the threshold, does not affect moves above
# chosenMovePrune = 1

# Number of symmetries to sample (WITH replacement) and average at the root
# rootNumSymmetriesToSample = 1

# Using LCB for move selection?
# useLcbForSelection = true
# How many stdevs a move needs to be better than another for LCB selection
# lcbStdevs = 5.0
# Only use LCB override when a move has this proportion of visits as the top move
# minVisitPropForLCB = 0.15

# Internal params------------------------------------------------------------------------------
# Uncomment and edit any of the below values to change them from their default.

# Scales the utility of winning/losing
# winLossUtilityFactor = 1.0
# Scales the utility for trying to maximize score
# staticScoreUtilityFactor = 0.10
# dynamicScoreUtilityFactor = 0.30
# Adjust dynamic score center this proportion of the way towards zero, capped at a reasonable amount.
# dynamicScoreCenterZeroWeight = 0.20
# dynamicScoreCenterScale = 0.75
# The utility of getting a "no result" due to triple ko or other long cycle in non-superko rulesets (-1 to 1)
# noResultUtilityForWhite = 0.0
# The number of wins that a draw counts as, for white. (0 to 1)
# drawEquivalentWinsForWhite = 0.5

# Exploration constant for mcts
# cpuctExploration = 0.9
# cpuctExplorationLog = 0.4
# FPU reduction constant for mcts
# fpuReductionMax = 0.2
# rootFpuReductionMax = 0.1
# Use parent average value for fpu base point instead of point value net estimate
# fpuUseParentAverage = true
# Amount to apply a downweighting of children with very bad values relative to good ones
# valueWeightExponent = 0.5
# Slight incentive for the bot to behave human-like with regard to passing at the end, filling the dame,
# not wasting time playing in its own territory, etc, and not play moves that are equivalent in terms of
# points but a bit more unfriendly to humans.
# rootEndingBonusPoints = 0.5
# Make the bot prune useless moves that are just prolonging the game to avoid losing yet
# rootPruneUselessMoves = true

# How big to make the mutex pool for search synchronization
# mutexPoolSize = 8192
# How many virtual losses to add when a thread descends through a node
# numVirtualLossesPerThread = 1