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dataset.py
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from collections import defaultdict
import numpy as np
class KBDataset(object):
def __init__(self, name):
self.name = name.lower()
self.ent_id = {}
self.rel_id = {}
self.nent = 0
self.nrel = 0
self.train = self.load_file("train")
self.valid = self.load_file("valid")
self.test = self.load_file("test")
self.triples_t = defaultdict(set)
self.triples_h = defaultdict(set)
for triple in np.concatenate([self.train, self.valid, self.test]):
self.triples_t[(triple[0], triple[1])].add(triple[2])
self.triples_h[(triple[1], triple[2])].add(triple[0])
self.rel_h = defaultdict(set)
self.rel_t = defaultdict(set)
self.train_triples = defaultdict(set)
for triple in self.train:
self.rel_h[triple[1]].add(triple[0])
self.rel_t[triple[1]].add(triple[2])
self.train_triples[(triple[0], triple[1])].add(triple[2])
def __repr__(self):
return ("%s | ent:%d | rel:%d | train:%d | valid:%d | test:%d" %
(self.name, self.nent, self.nrel,
len(self.train), len(self.valid), len(self.test)))
def load_file(self, filename):
with open("./data/%s/%s" % (self.name, filename)) as file:
temp = np.array(file.read().split())
triples_ = np.zeros(temp.size, dtype=np.int32)
for i in range(0, temp.size // 3):
if temp[3 * i] not in self.ent_id:
self.ent_id[temp[3 * i]] = self.nent
self.nent += 1
triples_[3 * i] = self.ent_id[temp[3 * i]]
if temp[3 * i + 2] not in self.ent_id:
self.ent_id[temp[3 * i + 2]] = self.nent
self.nent += 1
triples_[3 * i + 2] = self.ent_id[temp[3 * i + 2]]
if temp[3 * i + 1] not in self.rel_id:
self.rel_id[temp[3 * i + 1]] = self.nrel
self.nrel += 1
triples_[3 * i + 1] = self.rel_id[temp[3 * i + 1]]
return triples_.reshape((-1, 3))