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leela_lite.py
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leela_lite.py
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#!/usr/bin/python3
from lcztools import load_network, LeelaBoard
import search
import chess
import chess.pgn
import sys
import time
if len(sys.argv) != 3:
print("Usage: python3 leela_lite.py <weights file or network server ID> <nodes>")
print(len(sys.argv))
exit(1)
else:
weights = sys.argv[1]
nodes = int(sys.argv[2])
network_id = None
try:
# If the parameter is an integer, assume it's a network server ID
network_id = int(weights)
weights = None
except:
pass
def load_leela_network():
global net, nn
if network_id is not None:
net = load_network(backend='net_client', network_id=network_id, policy_softmax_temp=2.2)
else:
net = load_network(backend='pytorch_cuda', filename=weights, policy_softmax_temp=2.2)
nn = search.NeuralNet(net=net, lru_size=min(5000, nodes))
load_leela_network()
SELFPLAY = True
board = LeelaBoard()
while True:
if not SELFPLAY:
print(board.unicode())
print("Enter move: ", end='')
sys.stdout.flush()
line = sys.stdin.readline()
line = line.rstrip()
board.push_uci(line)
print(board.unicode())
print("thinking...")
start = time.time()
best, node = search.UCT_search(board, nodes, net=nn, C=3.4)
elapsed = time.time() - start
print("best: ", best)
print("Time: {:.3f} nps".format(nodes/elapsed))
print(nn.evaluate.cache_info())
board.push_uci(best)
if board.pc_board.is_game_over() or board.is_draw():
result = board.pc_board.result(claim_draw=True)
print("Game over... result is {}".format(result))
print(board.unicode())
print()
pgn_game = chess.pgn.Game.from_board(board.pc_board)
pgn_game.headers['Result'] = result
print(pgn_game)
break
for i in range(13):
print('\033[F', end = '\r')