from collections import Counter

matrix = [[], [], []]

matrix[0] = list(map(int, input().strip().split(' ')))
matrix[1] = list(map(int, input().strip().split(' ')))
matrix[2] = list(map(int, input().strip().split(' ')))

num_cnt = dict(Counter([col for row in matrix for col in row]))
num_pos = {}
for row_ind in range(3):
    for col_ind in range(3):
        if matrix[row_ind][col_ind] not in num_pos:
            num_pos[matrix[row_ind][col_ind]] = []
        num_pos[matrix[row_ind][col_ind]].append((row_ind, col_ind)) 
        
missing = []
duplicated = []
for num in range(1, 9):
    if num not in num_cnt:
        missing.append(num)
    elif num_cnt[num] > 1:
        duplicated.append(num)
        
min_cost = None
for d in duplicated:
    for row_ind, col_ind in num_pos[d]:
        new_matrix = [[col for col in row] for row in matrix]
        for m in missing:
            new_matrix[row_ind][col_ind] = m
            
            row_0 = sum(new_matrix[0])
            row_1 = sum(new_matrix[1])
            row_2 = sum(new_matrix[2])

            col_0 = sum(list(zip(*new_matrix))[0])
            col_1 = sum(list(zip(*new_matrix))[1])
            col_2 = sum(list(zip(*new_matrix))[2])

            diag_0 = new_matrix[0][0] + new_matrix[1][1] + new_matrix[2][2]
            diag_1 = new_matrix[0][2] + new_matrix[1][1] + new_matrix[2][0]

            if row_0 == row_1 == row_2 == col_0 == col_1 == col_2 == diag_0 == diag_1:
                cost = abs(m - d)
                if min_cost is None or min_cost > cost:
                    min_cost = cost

print(min_cost)