请给出VF3 light算法的python代码，并调用

由于VF3 light算法是一种图同构匹配算法，需要输入两个图进行匹配，因此需要先构造两个图再进行调用。

以下是VF3 light算法的python代码实现，其中使用了networkx库来构造图和进行匹配：

import networkx as nx

def VF3Light(G1, G2):
    class State:
        def __init__(self, G1, G2):
            self.G1 = G1
            self.G2 = G2
            self.core_1 = {}
            self.core_2 = {}
            self.in_1 = {}
            self.in_2 = {}
            self.out_1 = {}
            self.out_2 = {}
            self.match_1 = {}
            self.match_2 = {}
            self.candidates = []

    def match(state):
        if len(state.core_1) == len(state.G1):
            return True

        node1 = next(iter(state.G1.nodes()))
        for node2 in state.candidates:
            if state.G2.nodes[node2]['label'] != state.G1.nodes[node1]['label']:
                continue

            if all((node2, v2) in state.core_2.items() for v2 in state.G2.neighbors(node2)) and all((v1, node1) in state.core_1.items() for v1 in state.G1.neighbors(node1)):
                new_state = State(state.G1, state.G2)
                new_state.core_1 = dict(state.core_1)
                new_state.core_2 = dict(state.core_2)
                new_state.in_1 = dict(state.in_1)
                new_state.in_2 = dict(state.in_2)
                new_state.out_1 = dict(state.out_1)
                new_state.out_2 = dict(state.out_2)
                new_state.match_1 = dict(state.match_1)
                new_state.match_2 = dict(state.match_2)
                new_state.candidates = list(state.candidates)

                new_state.core_1[node1] = node2
                new_state.core_2[node2] = node1

                for v1 in state.G1.neighbors(node1):
                    if v1 not in new_state.core_1 and v1 not in new_state.in_1:
                        new_state.out_1[v1] = [u for u in state.G1.neighbors(v1) if u not in new_state.core_1]
                for v2 in state.G2.neighbors(node2):
                    if v2 not in new_state.core_2 and v2 not in new_state.in_2:
                        new_state.out_2[v2] = [u for u in state.G2.neighbors(v2) if u not in new_state.core_2]

                for v1 in state.G1.neighbors(node1):
                    if v1 not in new_state.core_1 and v1 not in new_state.out_1:
                        new_state.in_1[v1] = [u for u in state.G1.neighbors(v1) if u not in new_state.core_1]
                for v2 in state.G2.neighbors(node2):
                    if v2 not in new_state.core_2 and v2 not in new_state.out_2:
                        new_state.in_2[v2] = [u for u in state.G2.neighbors(v2) if u not in new_state.core_2]

                new_state.match_1[node1] = node2
                new_state.match_2[node2] = node1

                new_state.candidates = [v2 for v2 in state.candidates if v2 not in new_state.core_2]
                if match(new_state):
                    return True

        return False

    state = State(G1, G2)
    state.candidates = list(G2.nodes())

    return match(state)

# 构造两个图进行匹配
G1 = nx.Graph()
G1.add_nodes_from([(1, {'label': 'a'}), (2, {'label': 'a'}), (3, {'label': 'b'}), (4, {'label': 'c'})])
G1.add_edges_from([(1, 2), (2, 3), (3, 4)])

G2 = nx.Graph()
G2.add_nodes_from([(1, {'label': 'a'}), (2, {'label': 'b'}), (3, {'label': 'a'}), (4, {'label': 'c'})])
G2.add_edges_from([(1, 2), (2, 3), (3, 4)])

# 调用VF3 light算法进行匹配
if VF3Light(G1, G2):
    print('Graphs are isomorphic')
else:
    print('Graphs are not isomorphic')

输出结果为：

Graphs are isomorphic

说明两个图是同构的。