spaCy/spacy/pipeline/_parser_internals/stateclass.pyx
Sofie Van Landeghem ca491722ad
The Parser is now a Pipe (2) (#5844)
* moving syntax folder to _parser_internals

* moving nn_parser and transition_system

* move nn_parser and transition_system out of internals folder

* moving nn_parser code into transition_system file

* rename transition_system to transition_parser

* moving parser_model and _state to ml

* move _state back to internals

* The Parser now inherits from Pipe!

* small code fixes

* removing unnecessary imports

* remove link_vectors_to_models

* transition_system to internals folder

* little bit more cleanup

* newlines
2020-07-30 23:30:54 +02:00

55 lines
1.4 KiB
Cython

# cython: infer_types=True
import numpy
from ...tokens.doc cimport Doc
cdef class StateClass:
def __init__(self, Doc doc=None, int offset=0):
cdef Pool mem = Pool()
self.mem = mem
self._borrowed = 0
if doc is not None:
self.c = new StateC(doc.c, doc.length)
self.c.offset = offset
def __dealloc__(self):
if self._borrowed != 1:
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]
@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()
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 = f"{words[self.S(0)]}_{self.S_(0).head}"
second = f"{words[self.S(1)]}_{self.S_(1).head}"
third = f"{words[self.S(2)]}_{self.S_(2).head}"
n0 = words[self.B(0)]
n1 = words[self.B(1)]
return ' '.join((third, second, top, '|', n0, n1))