2015-01-14 16:33:16 +03:00
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# cython: embedsignature=True
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2014-09-15 05:22:40 +04:00
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from cpython.ref cimport Py_INCREF
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2014-09-18 01:09:24 +04:00
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from cymem.cymem cimport Pool
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2014-10-29 15:19:38 +03:00
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from murmurhash.mrmr cimport hash64
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2014-09-15 05:22:40 +04:00
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2014-10-22 18:57:59 +04:00
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from libc.string cimport memset
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2015-01-05 10:49:19 +03:00
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from .orth cimport word_shape
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2015-07-01 19:50:37 +03:00
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from .typedefs cimport attr_t, flags_t
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2015-01-17 08:21:17 +03:00
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import numpy
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2014-09-10 22:41:37 +04:00
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2015-07-26 17:37:16 +03:00
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from .attrs cimport IS_ALPHA, IS_ASCII, IS_DIGIT, IS_LOWER, IS_PUNCT, IS_SPACE
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from .attrs cimport IS_TITLE, IS_UPPER, LIKE_URL, LIKE_NUM, LIKE_EMAIL, IS_STOP
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2015-07-27 02:50:06 +03:00
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from .attrs cimport IS_OOV
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2015-07-26 17:37:16 +03:00
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2014-10-09 12:53:30 +04:00
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2015-01-12 02:26:22 +03:00
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memset(&EMPTY_LEXEME, 0, sizeof(LexemeC))
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2014-10-09 12:53:30 +04:00
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2015-01-17 08:21:17 +03:00
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cdef int set_lex_struct_props(LexemeC* lex, dict props, StringStore string_store,
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const float* empty_vec) except -1:
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2015-01-13 16:03:48 +03:00
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lex.length = props['length']
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2015-01-22 18:08:25 +03:00
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lex.orth = string_store[props['orth']]
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2015-04-19 11:31:31 +03:00
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lex.lower = string_store[props['lower']]
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lex.norm = string_store[props['norm']]
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lex.shape = string_store[props['shape']]
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2015-01-13 16:03:48 +03:00
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lex.prefix = string_store[props['prefix']]
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lex.suffix = string_store[props['suffix']]
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2015-04-19 11:31:31 +03:00
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2015-01-13 16:03:48 +03:00
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lex.cluster = props['cluster']
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lex.prob = props['prob']
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lex.sentiment = props['sentiment']
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lex.flags = props['flags']
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2015-01-21 18:03:54 +03:00
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lex.repvec = empty_vec
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2015-01-12 02:26:22 +03:00
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2015-01-12 03:23:44 +03:00
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cdef class Lexeme:
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2015-01-24 12:48:34 +03:00
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"""An entry in the vocabulary. A Lexeme has no string context --- it's a
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word-type, as opposed to a word token. It therefore has no part-of-speech
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tag, dependency parse, or lemma (lemmatization depends on the part-of-speech
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tag).
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"""
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2015-01-17 08:21:17 +03:00
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def __cinit__(self, int vec_size):
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2015-01-22 18:08:25 +03:00
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self.repvec = numpy.ndarray(shape=(vec_size,), dtype=numpy.float32)
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2015-02-07 16:42:44 +03:00
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@property
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def has_repvec(self):
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return self.l2_norm != 0
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2015-07-26 17:37:16 +03:00
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cpdef bint check_flag(self, attr_id_t flag_id) except -1:
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cdef flags_t one = 1
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return self.flags & (one << flag_id)
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2015-07-27 02:50:06 +03:00
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property is_oov:
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def __get__(self): return self.check_flag(IS_OOV)
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2015-07-26 17:37:16 +03:00
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property is_alpha:
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def __get__(self): return self.check_flag(IS_ALPHA)
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property is_ascii:
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def __get__(self): return self.check_flag(IS_ASCII)
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property is_digit:
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def __get__(self): return self.check_flag(IS_DIGIT)
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property is_lower:
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def __get__(self): return self.check_flag(IS_LOWER)
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property is_title:
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def __get__(self): return self.check_flag(IS_TITLE)
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property is_punct:
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def __get__(self): return self.check_flag(IS_PUNCT)
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property is_space:
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def __get__(self): return self.check_flag(IS_SPACE)
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property like_url:
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def __get__(self): return self.check_flag(LIKE_URL)
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property like_num:
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def __get__(self): return self.check_flag(LIKE_NUM)
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property like_email:
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def __get__(self): return self.check_flag(LIKE_EMAIL)
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