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Re-delegate vectors to vocab

This commit is contained in:
Matthew Honnibal 2017-05-28 11:46:10 +02:00
parent 6863d01361
commit 2445707f3c
1 changed files with 4 additions and 17 deletions
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21
spacy/tokens/token.pyx
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@ -234,12 +234,7 @@ cdef class Token:
def __get__(self):
if 'has_vector' in self.doc.user_token_hooks:
return self.doc.user_token_hooks['has_vector'](self)
cdef int i
for i in range(self.vocab.vectors_length):
if self.c.lex.vector[i] != 0:
return True
else:
return False
return self.vocab.has_vector(self.lex.c.orth)
property vector:
"""A real-valued meaning representation.
@ -250,16 +245,7 @@ cdef class Token:
def __get__(self):
if 'vector' in self.doc.user_token_hooks:
return self.doc.user_token_hooks['vector'](self)
cdef int length = self.vocab.vectors_length
if length == 0:
raise ValueError(
"Word vectors set to length 0. This may be because you "
"don't have a model installed or loaded, or because your "
"model doesn't include word vectors. For more info, see "
"the documentation: \n%s\n" % about.__docs_models__
)
vector_view = <float[:length,]>self.c.lex.vector
return numpy.asarray(vector_view)
return self.vocab.get_vector(self.c.lex.orth)
property vector_norm:
"""The L2 norm of the token's vector representation.
@ -269,7 +255,8 @@ cdef class Token:
def __get__(self):
if 'vector_norm' in self.doc.user_token_hooks:
return self.doc.user_token_hooks['vector_norm'](self)
return self.c.lex.l2_norm
vector = self.vector
return numpy.sqrt((vector ** 2).sum())
property n_lefts:
def __get__(self):