mirror of
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85 lines
2.5 KiB
Cython
85 lines
2.5 KiB
Cython
# coding: utf-8
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# cython: infer_types=True
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from __future__ import unicode_literals
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from libc.string cimport memcpy, memset
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from libc.stdint cimport uint32_t, uint64_t
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from ..vocab cimport EMPTY_LEXEME
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from ..structs cimport Entity
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from ..lexeme cimport Lexeme
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from ..symbols cimport punct
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from ..attrs cimport IS_SPACE
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from ..attrs cimport attr_id_t
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from ..tokens.token cimport Token
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cdef class StateClass:
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def __init__(self, int length):
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cdef Pool mem = Pool()
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self.mem = mem
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def __dealloc__(self):
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del self.c
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@property
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def stack(self):
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return {self.S(i) for i in range(self.c._s_i)}
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@property
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def queue(self):
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return {self.B(i) for i in range(self.c.buffer_length())}
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@property
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def token_vector_lenth(self):
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return self.doc.tensor.shape[1]
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def py_is_final(self):
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return self.c.is_final()
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def print_state(self, words):
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words = list(words) + ['_']
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top = words[self.S(0)] + '_%d' % self.S_(0).head
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second = words[self.S(1)] + '_%d' % self.S_(1).head
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third = words[self.S(2)] + '_%d' % self.S_(2).head
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n0 = words[self.B(0)]
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n1 = words[self.B(1)]
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return ' '.join((third, second, top, '|', n0, n1))
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def nr_context_tokens(self, int nF, int nB, int nS, int nL, int nR):
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return 8
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def set_context_tokens(self, int[:] output, nF=1, nB=0, nS=2,
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nL=2, nR=2):
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output[0] = self.B(0)
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output[1] = self.B(1)
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output[2] = self.S(0)
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output[3] = self.S(1)
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output[4] = self.L(self.S(0), 1)
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output[5] = self.L(self.S(0), 2)
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output[6] = self.R(self.S(0), 1)
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output[7] = self.R(self.S(0), 2)
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#output[7] = self.L(self.S(1), 1)
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#output[8] = self.L(self.S(1), 2)
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#output[9] = self.R(self.S(1), 1)
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#output[10] = self.R(self.S(1), 2)
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def set_attributes(self, uint64_t[:, :] vals, int[:] tokens, int[:] names):
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cdef int i, j, tok_i
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for i in range(tokens.shape[0]):
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tok_i = tokens[i]
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if tok_i >= 0:
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token = &self.c._sent[tok_i]
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for j in range(names.shape[0]):
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vals[i, j] = Token.get_struct_attr(token, <attr_id_t>names[j])
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else:
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vals[i] = 0
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def set_token_vectors(self, float[:, :] tokvecs,
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float[:, :] all_tokvecs, int[:] indices):
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for i in range(indices.shape[0]):
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if indices[i] >= 0:
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tokvecs[i] = all_tokvecs[indices[i]]
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else:
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tokvecs[i] = 0
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