from network import Network
import tensorflow as tf
import random
import numpy as np


from board import Board

import main

config = main.config.copy()
config['model'] = "player_testings"
config['ply'] = "1"
config['board_representation'] = 'quack-fat'
network = Network(config, config['model'])

network.restore_model()
initial_state = Board.initial_state

initial_state_1 = ( 0,
                    0, 0, 0, 2, 0, -5,
                    0, -3, 0, 0, 0, 0,
                    -5, 0, 0, 0, 3, 5,
                    0, 0, 0, 0, 5, -2,
                    0 )

initial_state_2 = ( 0,
                    -5, -5, -3, -2, 0, 0,
                    0, 0, 0, 0, 0, 0,
                    0, 0, 0, 15, 0, 0,
                    0, 0, 0, 0, 0, 0,
                    0 )

boards = {initial_state,
          initial_state_1,
          initial_state_2 }






# board = network.board_trans_func(Board.initial_state, 1)


# pair = network.make_move(Board.initial_state, [3,2], 1)

# print(pair[1])

# network.do_backprop(board, 0.9)


# network.print_variables()


# network.save_model(2)

# print(network.calculate_1_ply(Board.initial_state, [3,2], 1))


diff = [0, 0]
val = network.eval_state(Board.board_features_quack_fat(initial_state, 1))
print(val)
diff[0] += abs(-1-val)
diff[1] += 1

print(diff[1])