#!/usr/bin/env python

density = []
distance = []
import copy

def full_map(density):
	# append columns
	for row in density:
		o = copy.copy(row)
		for count in range(4):
			for x in o:
				t = (x+count+1)
				if t > 9:
					t += 1
				row.append(t%10)

	# append rows
	rows = len(density)
	for count in range(4):
		for r in range(rows):
			t = []
			for v in density[r]:
				v = v+count+1
				if v > 9:
					v += 1
				t.append(v%10)			
			density.append(t)

def shortes_path(density, distance):
	queue = []
	queue.append((0,0))

	#import pdb; pdb.set_trace()
	while(len(queue)):
		pos = queue.pop(0)
		v = distance[pos[1]][pos[0]]

		for move in ((0,1), (0,-1), (1,0), (-1,0)):
			move_x = move[0] + pos[0]
			move_y = move[1] + pos[1]

			if (move_x) < 0:
				continue
			if (move_y) < 0:
				continue
			if (move_y) >= len(density):
				continue
			if (move_x) >= len(density[move_y]):
				continue

			if distance[move_y][move_x] is None:
				distance[move_y][move_x] = v + density[move_y][move_x]
				queue.append((move_x, move_y))
				continue

			if density[move_y][move_x] + v <  distance[move_y][move_x]:
				distance[move_y][move_x] = v + density[move_y][move_x]
				queue.append((move_x, move_y))
				continue			

with open("input01.txt","r") as f:
	for line in f:
		density.append([int(i) for i in line.strip()])
		#distance.append([None]*len(line.strip()))

full_map(density)
for r in density:
	distance.append([None]*len(r))
distance[0][0] = density[0][0]

shortes_path(density,distance)
print(distance[-1][-1]-distance[0][0])