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|_ |_ |_| v0.20.2 built Feb 1 2019
Usage: lc0 [<mode>] [flags...]
Available modes. A help for a mode: lc0 <mode> --help
uci (default) Act as UCI engine
selfplay Play games with itself
benchmark Quick benchmark
Allowed command line flags for current mode:
-h, --help Show help and exit.
Number of (CPU) worker threads to use.
[UCI: Threads DEFAULT: 2 MIN: 1 MAX: 128]
Number of positions to store in a memory cache. A large cache can speed up
searching, but takes memory.
[UCI: NNCacheSize DEFAULT: 200000 MIN: 0 MAX: 999999999]
Budgeted time for a move is multiplied by this value, causing the engine to
spend more time (if value is greater than 1) or less time (if the value is less
[UCI: Slowmover DEFAULT: 1.00 MIN: 0.00 MAX: 100.00]
Amount of time, in milliseconds, that the engine subtracts from it's total
available time (to compensate for slow connection, interprocess communication,
[UCI: MoveOverheadMs DEFAULT: 200 MIN: 0 MAX: 100000000]
List of Syzygy tablebase directories, list entries separated by system separator
(";" for Windows, ":" for Linux).
This option is ignored. Here to please chess GUIs.
[UCI: Ponder DEFAULT: true]
Fraction of time saved by smart pruning, which is added to the budget to the
next move rather than to the entire game. When 1, all saved timeis added to the
next move's budget; when 0, saved time is distributed among all future moves.
[UCI: ImmediateTimeUse DEFAULT: 1.00 MIN: 0.00 MAX: 1.00]
Maximum memory usage for the engine, in megabytes. The estimation is very rough,
and can be off by a lot. For example, multiple visits to a terminal node counted
several times, and the estimation assumes that all positions have 30 possible
moves. When set to 0, no RAM limit is enforced.
[UCI: RamLimitMb DEFAULT: 0 MIN: 0 MAX: 100000000]
Path from which to load network weights.
Setting it to <autodiscover> makes it search in ./ and ./weights/ subdirectories
for the latest (by file date) file which looks like weights.
[UCI: WeightsFile DEFAULT: <autodiscover>]
Neural network computational backend to use.
[UCI: Backend DEFAULT: cudnn VALUES: cudnn,cudnn-fp16,check,random,roundrobin,multiplexing,demux]
Parameters of neural network backend. Exact parameters differ per backend.
How many positions the engine tries to batch together for parallel NN
computation. Larger batches may reduce strength a bit, especially with a small
number of playouts.
[UCI: MinibatchSize DEFAULT: 256 MIN: 1 MAX: 1024]
When the engine cannot gather a large enough batch for immediateuse, try to
prefetch up to X positions which are likely to be useful soon, and put them into
[UCI: MaxPrefetch DEFAULT: 32 MIN: 0 MAX: 1024]
cpuct_init constant from "UCT search" algorithm. Higher values promote more
exploration/wider search, lower values promote more confidence/deeper search.
[UCI: CPuct DEFAULT: 3.00 MIN: 0.00 MAX: 100.00]
cpuct_base constant from "UCT search" algorithm. Lower value means higher growth
of Cpuct as number of node visits grows.
[UCI: CPuctBase DEFAULT: 19652.00 MIN: 1.00 MAX: 1000000000.00]
Multiplier for the cpuct growth formula.
[UCI: CPuctFactor DEFAULT: 2.00 MIN: 0.00 MAX: 1000.00]
Tau value from softmax formula for the first move. If equal to 0, the engine
picks the best move to make. Larger values increase randomness while making the
[UCI: Temperature DEFAULT: 0.00 MIN: 0.00 MAX: 100.00]
Reduce temperature for every move from the game start to this number of moves,
decreasing linearly from initial temperature to 0. A value of 0 disables
[UCI: TempDecayMoves DEFAULT: 0 MIN: 0 MAX: 100]
Move number, starting from which endgame temperature is used rather than initial
temperature. Setting it to 0 disables cutoff.
[UCI: TempCutoffMove DEFAULT: 0 MIN: 0 MAX: 1000]
Temperature used during endgame (starting from cutoff move). Endgame temperature
[UCI: TempEndgame DEFAULT: 0.00 MIN: 0.00 MAX: 100.00]
When move is selected using temperature, bad moves (with win probability less
than X than the best move) are not considered at all.
[UCI: TempValueCutoff DEFAULT: 100.00 MIN: 0.00 MAX: 100.00]
Reduces visits by this value when picking a move with a temperature. When the
offset is less than number of visits for a particular move, thatmove is not
picked at all.
[UCI: TempVisitOffset DEFAULT: 0.00 MIN: -1.00 MAX: 1000.00]
Add Dirichlet noise to root node prior probabilities. This allows the engine to
discover new ideas during training by exploring moves which are known to be bad.
Not normally used during play.
[UCI: DirichletNoise DEFAULT: false]
Display Q, V, N, U and P values of every move candidate after each move.
[UCI: VerboseMoveStats DEFAULT: false]
Do not spend time on the moves which cannot become bestmove given the remaining
time to search. When no other move can overtake the current best, the search
stops, saving the time. Values greater than 1 stop less promising moves from
being considered even earlier. Values less than 1 causes hopeless moves to still
have some attention. When set to 0, smart pruning is deactivated.
[UCI: SmartPruningFactor DEFAULT: 1.33 MIN: 0.00 MAX: 10.00]
How is an eval of unvisited node determined. "reduction" subtracts
--fpu-reduction value from the parent eval. "absolute" sets evalof unvisited
nodes to the value specified in --fpu-value.
[UCI: FpuStrategy DEFAULT: reduction VALUES: reduction,absolute]
"First Play Urgency" reduction (used when FPU strategy is "reduction"). Normally
when a move has no visits, it's eval is assumed to be equal to parent's eval.
With non-zero FPU reduction, eval of unvisited move is decreasedby that value,
discouraging visits of unvisited moves, and saving those visits for (hopefully)
more promising moves.
[UCI: FpuReduction DEFAULT: 1.20 MIN: -100.00 MAX: 100.00]
"First Play Urgency" value. When FPU strategy is "absolute", value of unvisited
node is assumed to be equal to this value, and does not depend on parent eval.
[UCI: FpuValue DEFAULT: -1.00 MIN: -1.00 MAX: 1.00]
Length of history, in half-moves, to include into the cache key. When this value
is less than history that NN uses to eval a position, it's possble that the
search will use eval of the same position with different history taken from
[UCI: CacheHistoryLength DEFAULT: 0 MIN: 0 MAX: 7]
Policy softmax temperature. Higher values make priors of move candidates closer
to each other, widening the search.
[UCI: PolicyTemperature DEFAULT: 2.20 MIN: 0.10 MAX: 10.00]
Allowed node collision events, per batch.
[UCI: MaxCollisionEvents DEFAULT: 32 MIN: 1 MAX: 1024]
Total allowed node collision visits, per batch.
[UCI: MaxCollisionVisits DEFAULT: 9999 MIN: 1 MAX: 1000000]
During the gathering of a batch for NN to eval, if position happens to be in the
cache or is terminal, evaluate it right away without sending the batch to the
NN. When off, this may only happen with the very first node of abatch; when on,
this can happen with any node.
[UCI: OutOfOrderEval DEFAULT: true]
With DTZ tablebase files, only allow the network pick from winning moves that
have shortest DTZ to play faster (but not necessarily optimally).
[UCI: SyzygyFastPlay DEFAULT: true]
Number of game play lines (principal variations) to show in UCI info output.
[UCI: MultiPV DEFAULT: 1 MIN: 1 MAX: 500]
What to display as score. Either centipawns (the UCI default), win percentage or
Q (the actual internal score) multiplied by 100.
[UCI: ScoreType DEFAULT: centipawn VALUES: centipawn,win_percentage,Q]
Neural network uses 7 previous board positions in addition to the current one.
During the first moves of the game such historical positions don't exist, but
they can be synthesized. This parameter defines when to synthesize them (always,
never, or only at non-standard fen position).
[UCI: HistoryFill DEFAULT: fen_only VALUES: no,fen_only,always]
Path to a configuration file. The format of the file is one command line
parameter per line, e.g.:
[UCI: ConfigFile DEFAULT: lc0.config]
Write log to that file. Special value <stderr> to output the logto the console.