A bipartite graph G = (V, E) is a graph in which the vertex set V can be divided into two disjoint subsets X and Y such that every edge e ∈ E has one end point in X and the other end point in Y.

A matching M is a subset of edges such that each node in V appears in at most one edge in M.

Given a bipartite graph, find the size of the matching which has the largest size.

Constraints

* 1 ≤ |X|, |Y| ≤ 100
* 0 ≤ |E| ≤ 10,000

Input


|X| |Y| |E|
x0 y0
x1 y1
:
x|E|-1 y|E|-1


|X| and |Y| are the number of vertices in X and Y respectively, and |E| is the number of edges in the graph G. The vertices in X are named with the numbers 0, 1,..., |X|-1, and vertices in Y are named with the numbers 0, 1,..., |Y|-1, respectively.

xi and yi are the node numbers from X and Y respectevely which represent the end-points of the i-th edge.

Output

Print the largest size of the matching.

Example

Input

3 4 6
0 0
0 2
0 3
1 1
2 1
2 3


Output

3
import sys, re
from collections import deque, defaultdict, Counter
from math import ceil, sqrt, hypot, factorial, pi, sin, cos, radians
from itertools import accumulate, permutations, combinations, product, groupby, combinations_with_replacement
from operator import itemgetter, mul
from copy import deepcopy
from string import ascii_lowercase, ascii_uppercase, digits
from bisect import bisect, bisect_left
from fractions import gcd
from heapq import heappush, heappop
from functools import reduce
def input(): return sys.stdin.readline().strip()
def INT(): return int(input())
def MAP(): return map(int, input().split())
def LIST(): return list(map(int, input().split()))
def ZIP(n): return zip(*(MAP() for _ in range(n)))
sys.setrecursionlimit(10 ** 9)
INF = float('inf')
mod = 10 ** 9 + 7

class Dinic:
    def __init__(self, v, inf=10**10):
        self.v = v
        self.inf = inf
        self.G = [[] for _ in range(v)]
        self.level = [-1]*v  # 深さ
        self.ite = [0]*v  # DFSでの探索が済んでいるか
    def add_edge(self, fr, to, cap):
        self.G[fr].append([to, cap, len(self.G[to])])
        self.G[to].append([fr, 0, len(self.G[fr])-1])
    def bfs(self, s):  # BFSで深さ決定,sがstart
        self.level = [-1]*self.v  # 必要
        self.level[s] = 0
        Q = deque()
        Q.append(s)
        while Q:
            v = Q.popleft()
            for i in range(len(self.G[v])):
                e = self.G[v][i]
                if e[1]>0 and self.level[e[0]]<0: ###capacity>0かつtoの深さ未定
                    self.level[e[0]] = self.level[v]+1
                    Q.append(e[0])
    def dfs(self, v, t, f):  # DFSで増加パス探索,v開始、t終点、総フローf
        if v==t:
            return f
        for i in range(self.ite[v],len(self.G[v])):
            self.ite[v] = i
            e = self.G[v][i]
            if e[1]>0 and self.level[v]<self.level[e[0]]:
                d = self.dfs(e[0], t, min(f, e[1]))
                if d>0:
                    e[1] -= d  # cap減少
                    self.G[e[0]][e[2]][1] += d  # 逆辺のcap増加
                    return d
        return 0
    def max_flow(self, s, t):
        flow = 0
        while True:
            self.bfs(s)
            if self.level[t]<0:
                return flow
            self.ite = [0]*self.v  # DFSでの探索が済んでいるか否か
            f = self.dfs(s,t,self.inf)
            while f>0:
                flow += f
                f = self.dfs(s,t,self.inf)

X, Y, E = MAP()
D = Dinic(X+Y+2)
s = X+Y
t = X+Y+1

for i in range(X):
	D.add_edge(s, i, 1)

for i in range(Y):
	D.add_edge(X+i, t, 1)

for _ in range(E):
	x, y = MAP()
	D.add_edge(x, X+y, 1)

print(D.max_flow(s, t))

