def load_default_model():
engine.model.Network.FILTERS = 128
engine.model.Network.BLOCK_COUNT = 12
engine.setup_evaluator(use_rpc=False)
engine.initialize_model("/tmp/model-156.npy")
if args.visits == None:
move = eng.genmove(ms * 1e-3, use_weighted_exponent=5.0)
else:
# This is safe, because of the visit limit we set above.
move = eng.genmove(1000000.0, use_weighted_exponent=5.0)
print "bestmove %s" % (uai_encode_move(move), )
elif line == "showboard":
print board
print "boardok"
sys.stdout.flush()
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--network-path",
metavar="NETWORK",
type=str,
help="Name of the model to load.")
parser.add_argument("--visits",
metavar="VISITS",
default=None,
type=int,
help="Number of visits during MCTS.")
args = parser.parse_args()
print >> sys.stderr, args
engine.setup_evaluator(use_rpc=False)
engine.initialize_model(args.network_path)
main(args)
def generate_game(args):
config = chomp_rules.ChompGameConfig(16, 16)
board = chomp_rules.ChompState.empty_board(config)
e = engine.MCTSEngine()
while True:
print board
selected_move = e.genmove(1.0,
early_out=False,
use_weighted_exponent=5.0)
board.apply_move(selected_move)
e.set_state(board.copy())
if board.winner != None:
break
raw_input(">")
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--network",
metavar="PATH",
required=True,
help="Path of the model to load.")
args = parser.parse_args()
engine.setup_evaluator(use_rpc=False)
engine.initialize_model(args.network)
generate_game(args)
self.accumulated_features.append(array)
self.accumulated_slots.append(result_slot)
except gevent.queue.Empty:
self.process()
if len(self.accumulated_features) >= self.MARSHALL_COUNT:
# print "Processing due to full batch."
self.process()
class NetworkServer(RPCServer):
def network(self, feature_string):
result_slot = gevent.event.AsyncResult()
submit_queue.put((feature_string, result_slot))
return result_slot.get()
if len(sys.argv) != 3:
print("Usage: %s model_path port-to-host-on" % (sys.argv[0], ))
exit(1)
#model_path = train.model_path(sys.argv[1])
engine.initialize_model(sys.argv[1])
port = int(sys.argv[2])
print()
print("Launching on port:", port)
gevent.spawn(Processor)
server = gevent.server.StreamServer(("127.0.0.1", port), NetworkServer)
server.serve_forever()
metavar="N",
default=100,
type=int,
help="Number of milliseconds per move for supervised generation.")
args = parser.parse_args()
network_path = args.network
network_name = os.path.splitext(os.path.basename(args.network))
if args.random_play:
print("Doing random play! Loading no model, and not using RPC.")
elif args.use_rpc:
engine.setup_evaluator(use_rpc=True, temperature=LOGIT_TEMPERATURE)
else:
engine.setup_evaluator(use_rpc=False, temperature=LOGIT_TEMPERATURE)
engine.initialize_model(network_path)
if args.supervised != None:
args.uai_player = uai_ringmaster.UAIPlayer(args.supervised)
if args.output_games == None:
output_directory = os.path.join("games", network_name)
if not os.path.exists(output_directory):
os.mkdir(output_directory)
output_path = os.path.join(output_directory,
os.urandom(8).encode("hex") + ".json")
else:
output_path = args.output_games
if args.no_write:
output_path = "/dev/null"
print("[%3i] Writing to: %s" % (args.group_index, output_path))
