def main():
global start_time, time_limit
start_time = datetime.now()
time_limit = 11.6
raw = Utils.json_input()
request = raw['requests']
model = load_best_model()
board, player = game_init()
if not (request['x'] == -2 and request['y'] == -2):
board, player = make_play(request['x'] - 1, request['y'] - 1, board)
if player == 1:
color = 'B'
else:
color = 'W'
engine = ModelEngine(model, conf['MCTS_SIMULATIONS'], board)
x, y, _, _, _, _, _ = engine.genmove(color)
response = {}
response['x'], response['y'] = x + 1, y + 1
if y == conf['SIZE']:
response['x'], response['y'] = -1, -1
Utils.json_output({'response': response})
print(">>>BOTZONE_REQUEST_KEEP_RUNNING<<<")
time_limit = 3.6
while True:
try:
start_time = datetime.now()
raw = Utils.json_input()
request = raw['requests']
if not (request['x'] == -1 and request['y'] == -1):
engine.play('B',
request['x'] - 1,
request['y'] - 1,
update_tree=True)
x, y, _, _, _, _, _ = engine.genmove(color)
response = {}
response['x'], response['y'] = x + 1, y + 1
if y == conf['SIZE']:
response['x'], response['y'] = -1, -1
Utils.json_output({'response': response})
print(">>>BOTZONE_REQUEST_KEEP_RUNNING<<<")
except json.JSONDecodeError:
break
class Engine(object):
def __init__(self, model, logfile):
self.board, self.player = game_init()
self.start_engine(model)
self.logfile = logfile
def start_engine(self, model):
self.engine = ModelEngine(model, conf['MCTS_SIMULATIONS'], self.board)
def name(self):
return "AlphaGoZero Python - {} - {} simulations".format(self.engine.model.name, conf['MCTS_SIMULATIONS'])
def version(self):
return __version__
def protocol_version(self):
return "2"
def list_commands(self):
return ""
def boardsize(self, size):
size = int(size)
if size != SIZE:
raise Exception("The board size in configuration is {0}x{0} but GTP asked to play {1}x{1}".format(SIZE, size))
return ""
def komi(self, komi):
# Don't check komi in GTP engine. The algorithm has learned with a specific
# komi that we don't have any way to influence after learning.
return ""
def parse_move(self, move):
if move.lower() == 'pass':
x, y = 0, SIZE
return x, y
else:
letter = move[0]
number = move[1:]
x = string.ascii_uppercase.index(letter)
if x >= 9:
x -= 1 # I is a skipped letter
y = int(number) - 1
x, y = x, SIZE - y - 1
return x, y
def print_move(self, x, y):
x, y = x, SIZE - y - 1
if x >= 8:
x += 1 # I is a skipped letter
move = string.ascii_uppercase[x] + str(y + 1)
return move
def play(self, color, move):
announced_player = COLOR_TO_PLAYER[color]
assert announced_player == self.player
x, y = self.parse_move(move)
self.board, self.player = self.engine.play(color, x, y)
return ""
def genmove(self, color):
announced_player = COLOR_TO_PLAYER[color]
assert announced_player == self.player
x, y, policy_target, value, self.board, self.player, policy = self.engine.genmove(color)
self.player = self.board[0, 0, 0, -1] # engine updates self.board already
with open(self.logfile, 'a') as f:
f.write("PLAYER" + str(self.player) + '\n')
move_string = self.print_move(x, y)
result = move_string
return result
def clear_board(self):
self.board, self.player = game_init()
return ""
def parse_command(self, line):
tokens = line.strip().split(" ")
command = tokens[0]
args = tokens[1:]
method = getattr(self, command)
result = method(*args)
if not result.strip():
return "=\n\n"
return "= " + result + "\n\n"
def play_game(model1, model2, mcts_simulations, stop_exploration, self_play=False, num_moves=None, resign_model1=None, resign_model2=None):
board, player = game_init()
moves = []
engine1 = ModelEngine(model1, mcts_simulations, resign=resign_model1, temperature=1, board=np.copy(board), add_noise=self_play)
engine2 = ModelEngine(model2, mcts_simulations, resign=resign_model2, temperature=1, board=np.copy(board), add_noise=self_play)
if self_play:
engine2.tree = engine1.tree
last_value = None
value = None
skipped_last = False
start = datetime.datetime.now()
end_reason = "PLAYED ALL MOVES"
if num_moves is None:
num_moves = SIZE * SIZE * 2
for move_n in range(num_moves):
last_value = value
if move_n == stop_exploration:
engine1.set_temperature(0)
engine2.set_temperature(0)
if move_n % 2 == 0:
x, y, policy_target, value, _, _, policy = engine1.genmove("B")
if y == SIZE + 1:
end_reason = 'RESIGN'
break
engine2.play("B", x, y, update_tree=not self_play)
else:
x, y, policy_target, value, _, _, policy = engine2.genmove("W")
if y == SIZE + 1:
end_reason = 'RESIGN'
break
engine1.play("B", x, y, update_tree=not self_play)
move_data = {
'board': np.copy(board),
'policy': policy_target,
'policy_variation': np.linalg.norm(policy_target - policy),
'value': value,
'move': (x, y),
'move_n': move_n,
'player': player ,
}
moves.append(move_data)
if skipped_last and y == SIZE:
end_reason = "BOTH_PASSED"
break
skipped_last = y == SIZE
if y == SIZE + 1:
end_reason = 'RESIGN'
break
# Swap players
board, player = make_play(x, y, board)
if conf['SHOW_EACH_MOVE']:
# Inverted here because we already swapped players
color = "W" if player == 1 else "B"
print("%s(%s,%s)" % (color, x, y))
print("")
print(show_board(board))
print("")
winner, black_points, white_points = get_winner(board)
player_string = {1: "B", 0: "D", -1: "W"}
if end_reason == "resign":
winner_string = "%s+R" % (player_string[player])
else:
winner_string = "%s+%s" % (player_string[winner], abs(black_points - white_points))
winner_engine = engine1 if (winner == 1) else engine2
modelB, modelW = model1, model2
if conf['SHOW_END_GAME']:
if player == -1:
# black played last
bvalue, wvalue = value, last_value
else:
bvalue, wvalue = last_value, value
print("")
print("B:%s, W:%s" %(modelB.name, modelW.name))
print("Bvalue:%s, Wvalue:%s" %(bvalue, wvalue))
print(show_board(board))
print("Game played (%s: %s) : %s" % (winner_string, end_reason, datetime.datetime.now() - start))
game_data = {
'moves': moves,
'modelB_name': modelB.name,
'modelW_name': modelW.name,
'winner': winner,
'winner_model': winner_engine.model.name,
'result': winner_string,
'resign_model1': resign_model1,
'resign_model2': resign_model2,
}
return game_data