def __getitem__(self, item)->datasets.PredictionItem:
X=data0[item]
y1=np.zeros(168)
y1[gr[item]]=1
y2=np.zeros(11)
y2[vd[item]]=1
y3=np.zeros(7)
y3[cd[item]]=1
return datasets.PredictionItem(item,np.stack([X],axis=-1),[y1,y2,y3])
def __getitem__(self, item) -> datasets.PredictionItem:
tokenText = []
tokenClazz = []
if self.byDoc:
d = self.docs[item]
for sent in d.sentences:
tokenText = tokenText + [x.text for x in sent.tokens]
tokenClazz = tokenClazz + [
self.num2Class[self.clazzColumn][0][x.fields[
self.clazzColumn]] for x in sent.tokens
]
else:
sent = self.sentences[item]
tokenText = tokenText + [x.text for x in sent.tokens]
tokenClazz = tokenClazz + [
self.num2Class[self.clazzColumn][0][x.fields[self.clazzColumn]]
for x in sent.tokens
]
return datasets.PredictionItem(item, np.array(tokenText),
np.array(tokenClazz))
def __getitem__(self, item) -> datasets.PredictionItem:
return datasets.PredictionItem(
self.sorted[item][0], self.sorted[item][0],
(self.sorted[item][1], "count:" + str(self.sorted[item][2])))
def __getitem__(self, item) -> datasets.PredictionItem:
return datasets.PredictionItem(self.sorted[item][0],
self.sorted[item][0],
self.sorted[item][1])
def __getitem__(self, item):
return datasets.PredictionItem(
item, "H", (np.array([item % 2, item % 3])))
def __getitem__(self, item):
return datasets.PredictionItem(item, "H",
([item % 2], [item % 3]))
def __getitem__(self, item):
if item == 2:
raise ValueError()
return datasets.PredictionItem(item, "H", 0)
def __getitem__(self, item):
return datasets.PredictionItem(item, "H", (np.array(
[float(item % 2), float(item % 3)])))
def __getitem__(self, item):
return datasets.PredictionItem(item, self.get_questions(item),
np.array([self.target[item]]))
def __getitem__(self, item):
return datasets.PredictionItem(item, self.src[item], self.dest[item])
