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added engine factory and adapted command line parsing, added lc0_strategy.py, added stockfish and lc0 standalone engines

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This commit is contained in:
Lukas Kuess
2024-01-30 19:44:09 +01:00
parent 50cd4cde9b
commit b2ce73f06b
9 changed files with 214 additions and 56 deletions
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37
chesspp/engine.py
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@@ -1,5 +1,6 @@
import random
import time
import os
from abc import ABC, abstractmethod
from torch import distributions as dist
@@ -15,13 +16,13 @@ from typing import Dict
class Limit:
""" Class to determine when to stop searching for moves """
time: float|None
time: float | None
""" Search for `time` seconds """
nodes: int|None
nodes: int | None
""" Search for a limited number of `nodes`"""
def __init__(self, time: float|None = None, nodes: int|None = None):
def __init__(self, time: float | None = None, nodes: int | None = None):
self.time = time
self.nodes = nodes
@@ -44,7 +45,7 @@ class Limit:
def _run_time(self, func, *args, **kwargs):
start = time.perf_counter_ns()
while (time.perf_counter_ns()-start)/1e9 < self.time:
while (time.perf_counter_ns() - start) / 1e9 < self.time:
func(*args, **kwargs)
@@ -56,7 +57,7 @@ class Engine(ABC):
strategy: IStrategy
"""The strategy used to pick moves when simulating games."""
def __init__(self, board: chess.Board, color: chess.Color, strategy: IStrategy):
def __init__(self, board: chess.Board, color: chess.Color, strategy: IStrategy | None):
self.board = board
self.color = color
self.strategy = strategy
@@ -138,3 +139,29 @@ class RandomEngine(Engine):
def play(self, board: chess.Board, limit: Limit) -> chess.engine.PlayResult:
move = random.choice(list(board.legal_moves))
return chess.engine.PlayResult(move=move, ponder=None)
class StockFishEngine(Engine):
def __init__(self, board: chess.Board, color: chess, path="../stockfish/stockfish-ubuntu-x86-64-avx2"):
super().__init__(board, color, None)
self.stockfish = chess.engine.SimpleEngine.popen_uci(path)
def play(self, board: chess.Board, limit: Limit) -> chess.engine.PlayResult:
return self.stockfish.play(board, limit)
@staticmethod
def get_name() -> str:
return "Stockfish"
class Lc0Engine(Engine):
def __init__(self, board: chess.Board, color: chess, path="../lc0/lc0"):
super().__init__(board, color, None)
self.lc0 = chess.engine.SimpleEngine.popen_uci(path)
def play(self, board: chess.Board, limit: Limit) -> chess.engine.PlayResult:
return self.lc0.play(board, limit)
@staticmethod
def get_name() -> str:
return "Lc0"

76
chesspp/engine_factory.py Normal file
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@@ -0,0 +1,76 @@
from enum import Enum
from chesspp.engine import *
from chesspp.lc0_strategy import Lc0Strategy
from chesspp.random_strategy import RandomStrategy
from chesspp.stockfish_strategy import StockFishStrategy
from chesspp.i_strategy import IStrategy
import chess
class EngineEnum(Enum):
ClassicMcts = 0
BayesianMcts = 1
Stockfish = 2
Lc0 = 3
Random = 4
class StrategyEnum(Enum):
Stockfish = 0
Lc0 = 1
Random = 2
class EngineFactory:
@staticmethod
def create_engine(engine_name: EngineEnum, strategy_name: StrategyEnum, color: chess.Color, stockfish_path: str, lc0_path: str, rollout_depth: int = 4) -> Engine:
match strategy_name:
case StrategyEnum.Stockfish:
strategy = EngineFactory._get_stockfish_strategy(stockfish_path, rollout_depth)
case StrategyEnum.Lc0:
strategy = EngineFactory._get_lc0_strategy(lc0_path, rollout_depth)
case StrategyEnum.Random:
strategy = EngineFactory._get_random_strategy(rollout_depth)
match engine_name:
case EngineEnum.ClassicMcts:
return EngineFactory.classic_mcts(color, strategy)
case EngineEnum.BayesianMcts:
return EngineFactory.bayesian_mcts(color, strategy)
case EngineEnum.Stockfish:
return EngineFactory.stockfish_engine(color, stockfish_path)
case EngineEnum.Lc0:
return EngineFactory.lc0_engine(color, lc0_path)
@staticmethod
def stockfish_engine(color: chess.Color, engine_path: str, board: chess.Board | None = chess.Board()) -> Engine:
return StockFishEngine(board, color, engine_path)
@staticmethod
def lc0_engine(color: chess.Color, engine_path: str, board: chess.Board | None = chess.Board()) -> Engine:
return Lc0Engine(board, color, engine_path)
@staticmethod
def bayesian_mcts(color: chess.Color, strategy: IStrategy, board: chess.Board | None = chess.Board()) -> Engine:
return BayesMctsEngine(board, color, strategy)
@staticmethod
def classic_mcts(color: chess.Color, strategy: IStrategy, board: chess.Board | None = chess.Board()) -> Engine:
return ClassicMctsEngine(board, color, strategy)
@staticmethod
def _get_random_strategy(rollout_depth: int) -> IStrategy:
return RandomStrategy(random.Random(), rollout_depth)
@staticmethod
def _get_stockfish_strategy(engine_path: str, rollout_depth: int) -> IStrategy:
return StockFishStrategy(engine_path, rollout_depth)
@staticmethod
def _get_lc0_strategy(engine_path: str, rollout_depth: int) -> IStrategy:
return Lc0Strategy(engine_path, rollout_depth)

34
chesspp/eval.py
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@@ -76,12 +76,12 @@ king_eval = [
]
king_endgame_eval = [
50, -30, -30, -30, -30, -30, -30, -50,
-30, -30, 0, 0, 0, 0, -30, -30,
-30, -30, 0, 0, 0, 0, -30, -30,
-30, -10, 20, 30, 30, 20, -10, -30,
-30, -10, 30, 40, 40, 30, -10, -30,
-30, -10, 30, 40, 40, 30, -10, -30,
-30, -10, 20, 30, 30, 20, -10, -30,
-30, -20, -10, 0, 0, -10, -20, -30,
-30, -20, -10, 0, 0, -10, -20, -30,
-50, -40, -30, -20, -20, -30, -40, -50
]
@@ -124,18 +124,18 @@ def check_endgame(board: chess.Board) -> bool:
if piece.piece_type == chess.QUEEN:
if piece.color == chess.WHITE:
queens_white += 1
queens_white += 1
else:
queens_black += 1
if piece.piece_type == chess.BISHOP or piece.piece_type == chess.KNIGHT:
if piece.color == chess.WHITE:
minors_white += 1
minors_white += 1
else:
minors_black += 1
return (queens_black == 0 and queens_white == 0) or ((queens_black >= 1 >= minors_black) or (
queens_white >= 1 >= minors_white))
queens_white >= 1 >= minors_white))
def score_manual(board: chess.Board) -> int:
@@ -173,30 +173,38 @@ def score_manual(board: chess.Board) -> int:
return score
def score_stockfish(board: chess.Board, stockfish: chess.engine.SimpleEngine | None = None) -> int:
def score_stockfish(board: chess.Board, stockfish: chess.engine.SimpleEngine | None = None,
limit: chess.engine.Limit = chess.engine.Limit(depth=0)) -> int:
"""
Calculate the score of the given board using stockfish
:param board:
:param stockfish:
:param limit:
:return:
"""
if stockfish is None:
engine = chess.engine.SimpleEngine.popen_uci(
"/home/luke/projects/pp-project/chess-engine-pp/stockfish/stockfish-ubuntu-x86-64-avx2")
info = engine.analyse(board, chess.engine.Limit(depth=0))
info = engine.analyse(board, limit)
engine.quit()
return info['score'].white().score(mate_score=100_000)
else:
info = stockfish.analyse(board, chess.engine.Limit(depth=0))
info = stockfish.analyse(board, limit)
return info['score'].white().score(mate_score=100_000)
def score_lc0(board: chess.Board) -> chess.engine.PovScore:
def score_lc0(board: chess.Board, lc0: chess.engine.SimpleEngine | None = None,
limit: chess.engine.Limit= chess.engine.Limit(depth=0)) -> int:
"""
Calculate the score of the given board using lc0
:param board:
:return:
"""
engine = chess.engine.SimpleEngine.popen_uci("/home/luke/projects/pp-project/chess-engine-pp/lc0/lc0")
info = engine.analyse(board, chess.engine.Limit(depth=4))
engine.quit()
return info["score"]
if lc0 is None:
engine = chess.engine.SimpleEngine.popen_uci("/home/luke/projects/pp-project/chess-engine-pp/lc0/lc0")
info = engine.analyse(board, limit)
engine.quit()
return info["score"]
else:
info = lc0.analyse(board, limit)
return info['score'].white().score(mate_score=100_000)

5
chesspp/i_strategy.py
View File

@@ -3,8 +3,11 @@ from abc import ABC, abstractmethod
import chess
# TODO extend class
class IStrategy(ABC):
rollout_depth: int
def __init__(self, rollout_depth: int = 4):
self.rollout_depth = rollout_depth
@abstractmethod
def pick_next_move(self, board: chess.Board) -> chess.Move:

39
chesspp/lc0_strategy.py Normal file
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@@ -0,0 +1,39 @@
import chess
import chess.engine
import os
from chesspp.i_strategy import IStrategy
from chesspp.eval import score_lc0
_DIR = os.path.abspath(os.path.dirname(__file__))
class Lc0Strategy(IStrategy):
def __init__(self, path="../lc0/lc0", rollout_depth: int = 4,
limit: chess.engine.Limit = chess.engine.Limit(depth=4)):
super().__init__(rollout_depth)
self._lc0 = None
self.path = path
self.limit = limit
def __del__(self):
if self._lc0 is not None:
self._lc0.quit()
@property
def lc0(self) -> chess.engine.SimpleEngine:
if self._lc0 is None:
self._lc0 = self.lc0 = chess.engine.SimpleEngine.popen_uci(self.path)
return self._lc0
@lc0.setter
def lc0(self, value):
self._lc0 = value
def pick_next_move(self, board: chess.Board) -> chess.Move | None:
return self.lc0.play(board, self.limit).move
def analyze_board(self, board: chess.Board) -> int:
score = score_lc0(board, self.lc0)
print("lc0 score", score)
return score

3
chesspp/random_strategy.py
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@@ -5,7 +5,8 @@ from chesspp.eval import score_manual
class RandomStrategy(IStrategy):
def __init__(self, random_state: random.Random):
def __init__(self, random_state: random.Random, rollout_depth: int = 4):
super().__init__(rollout_depth)
self.random_state = random_state
def pick_next_move(self, board: chess.Board) -> chess.Move | None:

27
chesspp/simulation.py
View File

@@ -5,8 +5,8 @@ import chess.pgn
from typing import Tuple, List
from enum import Enum
from dataclasses import dataclass
from chesspp.i_strategy import IStrategy
from chesspp.engine_factory import StrategyEnum, EngineFactory, EngineEnum
from chesspp.engine import Engine, Limit
@@ -36,32 +36,39 @@ def simulate_game(white: Engine, black: Engine, limit: Limit, board: chess.Board
class Evaluation:
def __init__(self, engine_a: Engine.__class__, strategy_a, engine_b: Engine.__class__, strategy_b, limit: Limit):
def __init__(self, engine_a: EngineEnum, strategy_a, engine_b: EngineEnum, strategy_b, limit: Limit,
stockfish_path: str, lc0_path: str):
self.engine_a = engine_a
self.strategy_a = strategy_a
self.engine_b = engine_b
self.strategy_b = strategy_b
self.stockfish_path = stockfish_path
self.lc0_path = lc0_path
self.limit = limit
def run(self, n_games=100, proc=mp.cpu_count()) -> List[EvaluationResult]:
proc = min(proc, mp.cpu_count())
with mp.Pool(proc) as pool:
args = [(self.engine_a, self.strategy_a, self.engine_b, self.strategy_b, self.limit) for i in range(n_games)]
args = [(self.engine_a, self.strategy_a, self.engine_b, self.strategy_b, self.limit, self.stockfish_path, self.lc0_path) for i
in
range(n_games)]
return pool.map(Evaluation._test_simulate, args)
@staticmethod
def _test_simulate(arg: Tuple[Engine.__class__, IStrategy, Engine.__class__, IStrategy, Limit]) -> EvaluationResult:
engine_a, strategy_a, engine_b, strategy_b, limit = arg
def _test_simulate(arg: Tuple[EngineEnum, StrategyEnum, EngineEnum, StrategyEnum, Limit, str, str]) -> EvaluationResult:
engine_a, strategy_a, engine_b, strategy_b, limit, stockfish_path, lc0_path = arg
flip_engines = bool(random.getrandbits(1))
board = chess.Board()
if flip_engines:
black, white = engine_a(board.copy(), chess.BLACK, strategy_a), engine_b(board.copy(), chess.WHITE, strategy_b)
black, white = EngineFactory.create_engine(engine_a, strategy_a, chess.BLACK,
stockfish_path, lc0_path), EngineFactory.create_engine(
engine_b, strategy_b, chess.WHITE, stockfish_path, lc0_path)
else:
white, black = engine_a(board.copy(), chess.WHITE, strategy_a), engine_b(board.copy(), chess.BLACK, strategy_b)
white, black = EngineFactory.create_engine(engine_a, strategy_a, chess.WHITE,
stockfish_path, lc0_path), EngineFactory.create_engine(
engine_b, strategy_b, chess.BLACK, stockfish_path, lc0_path)
game = simulate_game(white, black, limit, board)
game = simulate_game(white, black, limit, chess.Board())
winner = game.end().board().outcome().winner
result = Winner.Draw

12
chesspp/stockfish_strategy.py
View File

@@ -4,14 +4,15 @@ from chesspp.i_strategy import IStrategy
from chesspp.eval import score_stockfish
import chess.engine
_DIR = os.path.abspath(os.path.dirname(__file__))
class StockFishStrategy(IStrategy):
def __init__(self, path="../stockfish/stockfish-windows-x86-64-avx2"):
def __init__(self, path="../stockfish/stockfish-windows-x86-64-avx2", rollout_depth: int = 4,
limit: chess.engine.Limit = chess.engine.Limit(depth=4)):
super().__init__(rollout_depth)
self._stockfish = None
self.path = path
self.limit = limit
def __del__(self):
if self._stockfish is not None:
@@ -20,8 +21,7 @@ class StockFishStrategy(IStrategy):
@property
def stockfish(self) -> chess.engine.SimpleEngine:
if self._stockfish is None:
self._stockfish = self.stockfish = chess.engine.SimpleEngine.popen_uci(
os.path.join(_DIR, self.path))
self._stockfish = self.stockfish = chess.engine.SimpleEngine.popen_uci(self.path)
return self._stockfish
@stockfish.setter
@@ -29,7 +29,7 @@ class StockFishStrategy(IStrategy):
self._stockfish = stockfish
def pick_next_move(self, board: chess.Board) -> chess.Move | None:
return self.stockfish.play(board, chess.engine.Limit(depth=4)).move
return self.stockfish.play(board, self.limit).move
def analyze_board(self, board: chess.Board) -> int:
return score_stockfish(board, self.stockfish)

37
main.py
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@@ -1,11 +1,11 @@
import random
import time
import chess
import chess.engine
import chess.pgn
from chesspp.classic_mcts import ClassicMcts
from chesspp.baysian_mcts import BayesianMcts
from chesspp.engine_factory import EngineEnum, StrategyEnum
from chesspp.random_strategy import RandomStrategy
from chesspp.stockfish_strategy import StockFishStrategy
from chesspp import engine
@@ -87,26 +87,17 @@ def analyze_results(moves: dict):
def test_evaluation():
a, b, s1, s2, n, limit, stockfish_path, proc = read_arguments()
a, b, s1, s2, n, limit, stockfish_path, lc0_path, proc = read_arguments()
limit = engine.Limit(time=limit)
if s1 == StockFishStrategy:
strat1 = StockFishStrategy(stockfish_path)
else:
strat1 = s1()
if s2 == StockFishStrategy:
strat2 = StockFishStrategy(stockfish_path)
else:
strat2 = s1()
evaluator = simulation.Evaluation(a, strat1, b, strat2, limit)
evaluator = simulation.Evaluation(a, s1, b, s2, limit, stockfish_path, lc0_path)
results = evaluator.run(n, proc)
a_results = len(list(filter(lambda x: x.winner == simulation.Winner.Engine_A, results))) / len(results) * 100
b_results = len(list(filter(lambda x: x.winner == simulation.Winner.Engine_B, results))) / len(results) * 100
draws = len(list(filter(lambda x: x.winner == simulation.Winner.Draw, results))) / len(results) * 100
print(f"Engine {a.get_name()} won {a_results}% of games")
print(f"Engine {b.get_name()} won {b_results}% of games")
print(f"Engine {a} won {a_results}% of games")
print(f"Engine {b} won {b_results}% of games")
print(f"{draws}% of games resulted in a draw")
@@ -116,19 +107,24 @@ def read_arguments():
description='Compare two engines by playing multiple games against each other'
)
engines = {"ClassicMCTS": engine.ClassicMctsEngine, "BayesianMCTS": engine.BayesMctsEngine, "Random": engine.RandomEngine}
strategies = {"Random": RandomStrategy, "Stockfish": StockFishStrategy}
engines = {"ClassicMCTS": EngineEnum.ClassicMcts, "BayesianMCTS": EngineEnum.BayesianMcts,
"Random": EngineEnum.Random, "Stockfish": EngineEnum.Stockfish, "Lc0": EngineEnum.Lc0}
strategies = {"Random": StrategyEnum.Random, "Stockfish": StrategyEnum.Stockfish, "Lc0": StrategyEnum.Lc0}
if os.name == 'nt':
stockfish_default = "../stockfish/stockfish-windows-x86-64-avx2"
lc0_default = "../lc0/lc0.exe"
else:
stockfish_default = "../stockfish/stockfish-ubuntu-x86-64-avx2"
lc0_default = "../lc0/lc0"
parser.add_argument("--proc", default=2, help="Number of processors to use for simulation, default=1")
parser.add_argument("--time", default=0.5, help="Time limit for each simulation step, default=0.5")
parser.add_argument("-n", default=100, help="Number of games to simulate, default=100")
parser.add_argument("--stockfish", default=stockfish_default,
help=f"Path for stockfish executable, default='{stockfish_default}'")
parser.add_argument("--stockfish_path", default=stockfish_default,
help=f"Path for engine executable, default='{stockfish_default}'")
parser.add_argument("--lc0_path", default=lc0_default,
help=f"Path for engine executable, default='{stockfish_default}'")
parser.add_argument("--engine1", "--e1", help="Engine A for the simulation", choices=engines.keys(), required=True)
parser.add_argument("--engine2", "--e2", help="Engine B for the simulation", choices=engines.keys(), required=True)
parser.add_argument("--strategy1", "--s1", default=list(strategies.keys())[0],
@@ -136,7 +132,7 @@ def read_arguments():
choices=strategies.keys())
parser.add_argument("--strategy2", "--s2", default=list(strategies.keys())[0],
help="Strategy for engine B for the rollout",
choices=strategies)
choices=strategies.keys())
args = parser.parse_args()
engine1 = engines[args.engine1]
@@ -144,7 +140,8 @@ def read_arguments():
strategy1 = strategies[args.strategy1]
strategy2 = strategies[args.strategy2]
return engine1, engine2, strategy1, strategy2, int(args.n), float(args.time), args.stockfish, int(args.proc)
print(engine1, engine2, strategy1, strategy2, int(args.n), float(args.time), args.stockfish_path, args.lc0_path, int(args.proc))
return engine1, engine2, strategy1, strategy2, int(args.n), float(args.time), args.stockfish_path, args.lc0_path, int(args.proc)
def main():