backgammon/restore_bot.py

from cup import Cup
import numpy as np
import tensorflow as tf
from network import Network
from board import Board
import random

class RestoreBot:

    def __init__(self, sym):
        self.cup = Cup()
        self.sym = sym

        self.graph = tf.Graph()
        with self.graph.as_default():
            self.session = tf.Session(graph = self.graph)
            self.network = Network(self.session)
            self.network.restore_model()

    def roll(self):
        print("{} rolled: ".format(self.sym))
        roll = self.cup.roll()
        print(roll)
        return roll
        

    def switch(self,cur):
        return -1 if cur == 1 else 1

    def get_sym(self):
        return self.sym

    def make_move(self, board, sym, roll):
        # print(Board.pretty(board))
        legal_moves = Board.calculate_legal_states(board, sym, roll)
        legal_list = list(legal_moves)
        move_scores = [ self.network.eval_state(np.array(move).reshape(1,26)) for move in legal_list ]
        print("Found the best state, being:", np.array(move_scores).argmax())
        return legal_list[np.array(move_scores).argmax()]
        
#        return random.choice(list(legal_moves))