if __name__ == "__main__":
parser=argparse.ArgumentParser(description="tournament between agents")
#parser.add_argument("num_games", type=int, help="num of paired games playing")
parser.add_argument("model_path", help="where the model locates", type=str)
parser.add_argument("--wolve_path",default="/home/cgao3/benzene/src/wolve/wolve", help="where is the wolve", type=str)
parser.add_argument("--value_net", help="whether it is valuenet model", action="store_true", default=False)
parser.add_argument("--verbose", help="verbose?", action="store_true", default=False)
args=parser.parse_args()
num_games=1000
think_time=1
net_exe=EXE_NN_AGENT_NAME + args.model_path +" 2>/dev/null"
EXE_HEX_PATH=args.wolve_path
wolve_exe=EXE_HEX_PATH+" 2>/dev/null"
wolve=WrapperAgent(wolve_exe, True)
net=WrapperAgent(net_exe, True)
wolve.sendCommand("param_wolve max_time "+repr(think_time))
white_win_count=0
black_win_count=0
for i in range(num_games):
wolve.reconnect()
wolve.sendCommand("param_wolve max_time "+ repr(think_time))
wolve.sendCommand("boardsize "+ repr(BOARD_SIZE))
win=run_single_match(net, wolve, False)
if win==0: black_win_count += 1
if win==1: white_win_count +=1
print(i+1, "black: ", black_win_count, "white: ", white_win_count)
net.sendCommand("close")
print("black win ", black_win_count, "white win count ", white_win_count)