spaCy/spacy/syntax/stateclass.pyx

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# coding: utf-8
# cython: infer_types=True
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from __future__ import unicode_literals
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import numpy
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from ..tokens.doc cimport Doc
cdef class StateClass:
def __init__(self, Doc doc=None, int offset=0):
cdef Pool mem = Pool()
self.mem = mem
if doc is not None:
self.c = new StateC(doc.c, doc.length)
self.c.offset = offset
def __dealloc__(self):
del self.c
@property
def stack(self):
return {self.S(i) for i in range(self.c._s_i)}
@property
def queue(self):
return {self.B(i) for i in range(self.c.buffer_length())}
@property
def token_vector_lenth(self):
return self.doc.tensor.shape[1]
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@property
def history(self):
hist = numpy.ndarray((8,), dtype='i')
for i in range(8):
hist[i] = self.c.get_hist(i+1)
return hist
def is_final(self):
return self.c.is_final()
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def copy(self):
cdef StateClass new_state = StateClass.init(self.c._sent, self.c.length)
new_state.c.clone(self.c)
return new_state
def print_state(self, words):
words = list(words) + ['_']
top = words[self.S(0)] + '_%d' % self.S_(0).head
second = words[self.S(1)] + '_%d' % self.S_(1).head
third = words[self.S(2)] + '_%d' % self.S_(2).head
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n0 = words[self.B(0)]
n1 = words[self.B(1)]
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return ' '.join((third, second, top, '|', n0, n1))