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在NSC+UPA的模型中,GetuEmbLayer.py里面有下面几行代码来区分是在句子层attention用user还是词汇层attention用user: if self.name == 'uemb_sentence': ualloc = T.alloc(u,maxsentencesum,T.shape(u)[0]) uflatten = ualloc.T.flatten() else: uflatten = u self.output = Uemb[uflatten] 我想知道为什么需要分开处理?谢谢!
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(⊙o⊙)…,突然想通了,已经懂了,谢谢!
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在NSC+UPA的模型中,GetuEmbLayer.py里面有下面几行代码来区分是在句子层attention用user还是词汇层attention用user:
if self.name == 'uemb_sentence':
ualloc = T.alloc(u,maxsentencesum,T.shape(u)[0])
uflatten = ualloc.T.flatten()
else:
uflatten = u
self.output = Uemb[uflatten]
我想知道为什么需要分开处理?谢谢!
The text was updated successfully, but these errors were encountered: