#!/usr/bin/env python3
# Based on https://en.wikipedia.org/wiki/Ford???Fulkerson_algorithm

import collections
import sys
import uuid


REC_LIMIT = 10000


class Edge(object):

    def __init__(self, source, sink, capacity):
        self.source = source
        self.sink = sink
        self.capacity = capacity
        self.rev_edge = None
        self.edge_id = uuid.uuid4()

    def __str__(self):
        return "Edge {} -> {} : {}".format(self.source,
                                           self.sink, self.capacity)


class Network(object):

    def __init__(self):
        self.adj_edges = collections.defaultdict(list)
        self.flow = dict()
        self.used_edge = None

    def get_edges_from(self, vertex):
        return self.adj_edges[vertex]

    def add_edge(self, source, sink, capacity):
        assert source != sink
        f_edge = Edge(source, sink, capacity)
        b_edge = Edge(sink, source, 0)
        f_edge.rev_edge = b_edge
        b_edge.rev_edge = f_edge
        self.adj_edges[source].append(f_edge)
        self.adj_edges[sink].append(b_edge)
        self.flow[f_edge] = 0
        self.flow[b_edge] = 0

    def find_path_rec(self, source, sink, path):
        if source == sink:
            return path
        for edge in self.get_edges_from(source):
            residual = edge.capacity - self.flow[edge]
            if residual > 0 and not self.used_edge[edge.edge_id]:
                self.used_edge[edge.edge_id] = True
                result = self.find_path_rec(edge.sink, sink, path + [edge])
                if result is not None:
                    return result

    def find_path(self, *args):
        self.used_edge = collections.defaultdict(bool)
        return self.find_path_rec(*args)

    def max_flow(self, source, sink):
        while True:
            path = self.find_path(source, sink, [])
            if path is None:
                break
            flow = min(edge.capacity - self.flow[edge] for edge in path)
            for edge in path:
                self.flow[edge] += flow
                self.flow[edge.rev_edge] -= flow
        return sum(self.flow[edge] for edge in self.get_edges_from(source))


def main():
    v, e = map(int, input().split())
    network = Network()
    for _ in range(e):
        network.add_edge(*map(int, input().split()))
    mf = network.max_flow(0, v - 1)
    print(mf)


if __name__ == '__main__':
    main()

### FIXED CODE ###

#!/usr/bin/env python3
# Based on
# https://en.wikipedia.org/wiki/Ford???Fulkerson_algorithm
# http://algoogle.hadrori.jp/algorithm/ford-fulkerson.html

import array
import collections
import sys


REC_LIMIT = 10000
INF = 10 ** 8


Edge = collections.namedtuple("Edge", "source sink capacity")


class FlowNetwork(object):

    def __init__(self, num_vertices):
        self.adj_edges = [set() for _ in range(num_vertices)]
        self.flow = None
        self.rev_edge = dict()
        self.used = None

    def get_edges_from(self, vertex):
        return self.adj_edges[vertex]

    def add_edge(self, source, sink, capacity):
        assert source != sink
        forward_edge = Edge(source, sink, capacity)
        backward_edge = Edge(sink, source, 0)
        self.rev_edge[forward_edge] = backward_edge
        self.rev_edge[backward_edge] = forward_edge
        self.adj_edges[source].add(forward_edge)
        self.adj_edges[sink].add(backward_edge)

    def dfs(self, source, sink, flow):
        if source == sink:
            return flow
        self.used[source] = True
        for edge in self.get_edges_from(source):
            rest = edge.capacity - self.flow[edge]
            if self.used[edge.sink] or rest <= 0:
                continue
            d = self.dfs(edge.sink, sink, min(flow, rest))
            if d > 0:
                self.flow[edge] += d
                self.flow[self.rev_edge[edge]] -= d
                return d
        return 0

    def ford_fulkerson(self, source, sink):
        self.flow = collections.defaultdict(int)
        max_flow = 0
        while True:
            self.used = collections.defaultdict(bool)
            df = self.dfs(source, sink, INF)
            if df == 0:
                return max_flow
            else:
                max_flow += df


def main():
    sys.setrecursionlimit(REC_LIMIT)
    v, e = map(int, input().split())
    network = FlowNetwork(v)
    for _ in range(e):
        network.add_edge(*map(int, input().split()))
    mf = network.ford_fulkerson(0, v - 1)
    print(mf)


if __name__ == '__main__':
    main()