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dataset.py
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dataset.py
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from math import sqrt
from torch.utils.data import Dataset
from gensim import corpora
from gensim.models import TfidfModel
class corpus(Dataset):
def __init__(self,data,wv):
self.data=data
self.wv=wv #使用keyvector获取词向量
s=[''.join(line.split()[:-1]).split() for line in data]
self.dic = corpora.Dictionary(s)
self.new_corpus = [self.dic.doc2bow(text) for text in s]
self.tfidf=TfidfModel(self.new_corpus) #使用tfidf获取词向量
def __getitem__(self, index) :
line=self.data[index]
s=line.split()[:-1]
label=float(line.split('\t')[1][0])
c=0
vec=[0]*128
#使用tfidf进行的词向量获取
ind=self.tfidf[self.new_corpus[index]]
for i in s:
e=1
if i in self.dic:
id=self.dic[i]
for n in ind:
id1=[x for x in n][0]
v=[x for x in n][1]
if id==id1:
e=v
break
elif id<id1:
break
vec+=self.wv[i]*e
# for i in s:
# vec+=self.wv[i]
c+=1
return vec/c,label
def __len__(self):
return len(self.data)