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 get_sym(self):
        return self.sym

    def restore_model(self):
        with self.graph.as_default():
            self.network.restore_model()

    def make_move(self, board, sym, roll):
        # print(Board.pretty(board))
        legal_moves = Board.calculate_legal_states(board, sym, roll)
        moves_and_scores = [ (move, self.network.eval_state(np.array(move).reshape(1,26))) for move in legal_moves ]
        scores = [ x[1] for x in moves_and_scores ]
        best_move = moves_and_scores[np.array(scores).argmax()][0]
        #print("Found the best state, being:", np.array(move_scores).argmax())
        return best_move
        
#        return random.choice(list(legal_moves))