Problem: For a given weighted graph G(V, E) and a source r, find the source shortest path to each vertex from the source (SSSP: Single Source Shortest Path).

Constraints

* 1 ≤ |V| ≤ 100000
* 0 ≤ di ≤ 10000
* 0 ≤ |E| ≤ 500000
* There are no parallel edges
* There are no self-loops

Input

An edge-weighted graph G (V, E) and the source r.


|V| |E| r
s0 t0 d0
s1 t1 d1
:
s|E|-1 t|E|-1 d|E|-1


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

si and ti represent source and target vertices of i-th edge (directed) and di represents the cost of the i-th edge.

Output

Print the costs of SSSP in the following format.


c0
c1
:
c|V|-1


The output consists of |V| lines. Print the cost of the shortest path from the source r to each vertex 0, 1, ... |V|-1 in order. If there is no path from the source to a vertex, print INF.

Examples

Input

4 5 0
0 1 1
0 2 4
1 2 2
2 3 1
1 3 5


Output

0
1
3
4


Input

4 6 1
0 1 1
0 2 4
2 0 1
1 2 2
3 1 1
3 2 5


Output

3
0
2
INF

Solution (in PYTHON3):

Solution:
#!/usr/bin/env python
from collections import defaultdict
from heapq import heappop, heappush
from math import isinf

V, E, r = map(int, input().split())

e = defaultdict(list)
for i in range(E):
    s, t, length = map(int, input().split())
    e[s].append((length, t))

distance = [float('inf')] * V          # 各頂点への距離の初期値
distance[r] = 0                        # 始点への距離は 0

# ダイクストラ
heap = [(distance[r], r)]
while heap:
    du, u = heappop(heap)
    for length, v in e[u]:
        if distance[v] > distance[u] + length:
            distance[v] = distance[u] + length
            heappush(heap, (distance[v], v))

for d in distance:
    print('INF' if isinf(d) else d)