Problem: <image>


A directed acyclic graph (DAG) can be used to represent the ordering of tasks. Tasks are represented by vertices and constraints where one task can begin before another, are represented by edges. For example, in the above example, you can undertake task B after both task A and task B are finished. You can obtain the proper sequence of all the tasks by a topological sort.

Given a DAG $G$, print the order of vertices after the topological sort.

Constraints

* $1 \leq |V| \leq 10,000$
* $0 \leq |E| \leq 100,000$
* There are no parallel edges in $G$
* There are no self loops in $G$

Input

A directed graph $G$ is given in the following format:
$|V|\;|E|$
$s_0 \; t_0$
$s_1 \; t_1$
:
$s_{|E|-1} \; t_{|E|-1}$



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

$s_i$ and $t_i$ represent source and target nodes of $i$-th edge (directed).

Output

Print the vertices numbers in order. Print a number in a line.

If there are multiple possible solutions, print any one of them (the solution is judged by a special validator).

Example

Input

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


Output

0
3
1
4
5
2

Solution (in PYTHON3):

Solution:
#https://qiita.com/drken/items/996d80bcae64649a6580 3-3. 二部グラフ判定
from collections import deque

# 頂点数と辺数
N, M = map(int, input().split())

# グラフ入力受取
G = [[] for _ in range(N)]
deg = [0]*N # 各頂点の出次数
for i in range(M):
    a, b = map(int, input().split())
    G[b].append(a) # 逆向きに辺を張る
    deg[a]+=1 # 出次数

# シンクたちをキューに挿入する
que = deque()
for i in range(N):
    if deg[i] == 0:
        que.append(i)

# 探索開始
order = []
while len(que)!=0:
    # キューから頂点を取り出す
    v = que.popleft()
    order.append(v)

    # v へと伸びている頂点たちを探索する
    for nv in G[v]:
        # 辺 (nv, v) を削除する
        deg[nv]-=1

        # それによって nv が新たにシンクになったらキューに挿入
        if deg[nv] == 0:
            que.append(nv)

# 答えをひっくり返す
order.reverse()
for i in order:
    print(i)