def sample(self):
if self.valid_set is None:
nodes = list(self.graph.nodes())
else:
assert len(self.valid_set) <= self.graph.number_of_nodes()
nodes = list(self.valid_set)
if len(nodes) > 0:
return nodes[np_random.randint(len(nodes))]
else:
return None
def sample(self):
return np_random.randint(self.n)
def sample(self, valid_list=None):
# TODO: need a better implementation for O(1) sampling
tmp_list = list(self.set)
idx = np_random.randint(len(tmp_list))
return tmp_list[idx]