continue
else:
move_num += 1
#current board is the integer representation of the game board based on given game move
fen_board = convert(board.fen())
#update game image with current board (users move)
game_image = update_image(game_image, fen_board, move_num)
#user move, board update
print("Your move:\n")
print(board)
'''Computer Move'''
#update game_image with trained model. play(args, new_gameboard, move_num) returns the game board
#the model wants to use in integer 2d representation.
#computer moved
predicted_board = dcgan.play(args,game_image,move_num + 1)
legal_moves, legal_boards = get_legals(board)
#list of all max differences for each cooresponding legal board and the predicted_board
max_differences = [max_diff(predicted_board,legal_board) for legal_board in legal_boards]
#get the index of the smallest value in max_differences
best_difference = min(max_differences)
best_index = max_differences.index(best_difference)
#best move and board based on the best index
best_move = legal_moves[best_index]
best_board = legal_boards[best_index]
board.push(best_move)
game_image = update_image(game_image,best_board,move_num)
print('\n',board)
print("Computer Move:",best_move,'\n')
