# cython: profile=True # cython: embedsignature=True """Common classes and utilities across languages. Provides the main implementation for the spacy tokenizer. Specific languages subclass the Language class, over-writing the tokenization rules as necessary. Special-case tokenization rules are read from data//tokenization . """ from __future__ import unicode_literals from libc.stdlib cimport calloc, free import json import random from os import path from .util import read_lang_data from spacy.tokens import Tokens from spacy.lexeme cimport LexemeC, lexeme_init from murmurhash.mrmr cimport hash64 from spacy._hashing cimport PointerHash from spacy import orth from spacy import util cdef enum Flags: Flag_IsAlpha Flag_IsAscii Flag_IsDigit Flag_IsLower Flag_IsPunct Flag_IsSpace Flag_IsTitle Flag_IsUpper Flag_CanAdj Flag_CanAdp Flag_CanAdv Flag_CanConj Flag_CanDet Flag_CanNoun Flag_CanNum Flag_CanPdt Flag_CanPos Flag_CanPron Flag_CanPrt Flag_CanPunct Flag_CanVerb Flag_OftLower Flag_OftTitle Flag_OftUpper Flag_N cdef enum Views: View_CanonForm View_WordShape View_NonSparse View_Asciied View_N # Assign the flag and view functions by enum value. # This is verbose, but it ensures we don't get nasty order sensitivities. STRING_VIEW_FUNCS = [None] * View_N STRING_VIEW_FUNCS[View_CanonForm] = orth.canon_case STRING_VIEW_FUNCS[View_WordShape] = orth.word_shape STRING_VIEW_FUNCS[View_NonSparse] = orth.non_sparse STRING_VIEW_FUNCS[View_Asciied] = orth.asciied FLAG_FUNCS = [None] * Flag_N FLAG_FUNCS[Flag_IsAlpha] = orth.is_alpha FLAG_FUNCS[Flag_IsAscii] = orth.is_ascii FLAG_FUNCS[Flag_IsDigit] = orth.is_digit FLAG_FUNCS[Flag_IsLower] = orth.is_lower FLAG_FUNCS[Flag_IsPunct] = orth.is_punct FLAG_FUNCS[Flag_IsSpace] = orth.is_space FLAG_FUNCS[Flag_IsTitle] = orth.is_title FLAG_FUNCS[Flag_IsUpper] = orth.is_upper FLAG_FUNCS[Flag_CanAdj] = orth.can_tag('ADJ') FLAG_FUNCS[Flag_CanAdp] = orth.can_tag('ADP') FLAG_FUNCS[Flag_CanAdv] = orth.can_tag('ADV') FLAG_FUNCS[Flag_CanConj] = orth.can_tag('CONJ') FLAG_FUNCS[Flag_CanDet] = orth.can_tag('DET') FLAG_FUNCS[Flag_CanNoun] = orth.can_tag('NOUN') FLAG_FUNCS[Flag_CanNum] = orth.can_tag('NUM') FLAG_FUNCS[Flag_CanPdt] = orth.can_tag('PDT') FLAG_FUNCS[Flag_CanPos] = orth.can_tag('POS') FLAG_FUNCS[Flag_CanPron] = orth.can_tag('PRON') FLAG_FUNCS[Flag_CanPrt] = orth.can_tag('PRT') FLAG_FUNCS[Flag_CanPunct] = orth.can_tag('PUNCT') FLAG_FUNCS[Flag_CanVerb] = orth.can_tag('VERB') FLAG_FUNCS[Flag_OftLower] = orth.oft_case('lower', 0.7) FLAG_FUNCS[Flag_OftTitle] = orth.oft_case('title', 0.7) FLAG_FUNCS[Flag_OftUpper] = orth.oft_case('upper', 0.7) cdef class Language: """Base class for language-specific tokenizers. Most subclasses will override the _split or _split_one methods, which take a string of non-whitespace characters and output a list of strings. This function is called by _tokenize, which sits behind a cache and turns the list of strings into Lexeme objects via the Lexicon. Most languages will not need to override _tokenize or tokenize. The language is supplied a list of boolean functions, used to compute flag features. These are passed to the language's Lexicon object. The language's name is used to look up default data-files, found in data//tokenization table, which handles special cases like contractions; * The appropriate :py:meth:`find_split` function, which is used to split off punctuation etc. Args: string (unicode): The string to be tokenized. Returns: tokens (Tokens): A Tokens object, giving access to a sequence of LexIDs. """ cdef size_t length = len(string) cdef Tokens tokens = Tokens(length) if length == 0: return tokens cdef size_t start = 0 cdef size_t i = 0 cdef Py_UNICODE* chars = string cdef Py_UNICODE c cdef String span for i in range(length): c = chars[i] if Py_UNICODE_ISSPACE(c) == 1: if start < i: string_from_slice(&span, chars, start, i) self._tokenize(tokens, &span) start = i + 1 i += 1 if start < i: string_from_slice(&span, chars, start, i) self._tokenize(tokens, &span) return tokens cdef int _tokenize(self, Tokens tokens, String* string): cdef LexemeC** lexemes = self.cache.get(string.key) cdef size_t i if lexemes != NULL: i = 0 while lexemes[i] != NULL: tokens.push_back(lexemes[i]) i += 1 return 0 cdef uint64_t key = string.key cdef size_t first_token = tokens.length cdef int split cdef int remaining = string.n cdef String prefix while remaining >= 1: split = self._split_one(string.chars, string.n) remaining -= split string_slice_prefix(string, &prefix, split) lexemes = self.specials.get(prefix.key) if lexemes != NULL: i = 0 while lexemes[i] != NULL: tokens.push_back(lexemes[i]) i += 1 else: tokens.push_back(self.lexicon.get(&prefix)) lexemes = calloc(tokens.length - first_token, sizeof(LexemeC*)) cdef size_t j for i, j in enumerate(range(first_token, tokens.length)): lexemes[i] = tokens.lexemes[j] self.cache.set(key, lexemes) cdef int _split_one(self, Py_UNICODE* characters, size_t length): return length def _load_special_tokenization(self, token_rules): '''Load special-case tokenization rules. Loads special-case tokenization rules into the Language.cache cache, read from data//tokenization . The special cases are loaded before any language data is tokenized, giving these priority. For instance, the English tokenization rules map "ain't" to ["are", "not"]. Args: token_rules (list): A list of (chunk, tokens) pairs, where chunk is a string and tokens is a list of strings. ''' cdef LexemeC** lexemes cdef uint64_t hashed cdef String string for uni_string, substrings in token_rules: lexemes = calloc(len(substrings) + 1, sizeof(LexemeC*)) for i, substring in enumerate(substrings): string_from_unicode(&string, substring) lexemes[i] = self.lexicon.get(&string) lexemes[i + 1] = NULL string_from_unicode(&string, uni_string) self.specials.set(string.key, lexemes) self.cache.set(string.key, lexemes) cdef class Lexicon: def __cinit__(self, words, probs, clusters, case_stats, tag_stats, string_features, flag_features): self._flag_features = flag_features self._string_features = string_features self._dict = PointerHash(2 ** 20) self.size = 0 cdef String string for uni_string in words: prob = probs.get(uni_string, 0.0) cluster = clusters.get(uni_string, 0.0) cases = case_stats.get(uni_string, {}) tags = tag_stats.get(uni_string, {}) views = [string_view(uni_string, prob, cluster, cases, tags) for string_view in self._string_features] flags = set() for i, flag_feature in enumerate(self._flag_features): if flag_feature(uni_string, prob, cluster, cases, tags): flags.add(i) lexeme = lexeme_init(uni_string, prob, cluster, views, flags) string_from_unicode(&string, uni_string) self._dict.set(string.key, lexeme) self.size += 1 cdef LexemeC* get(self, String* string): cdef LexemeC* lexeme lexeme = self._dict.get(string.key) if lexeme != NULL: return lexeme cdef unicode uni_string = string.chars[:string.n] views = [string_view(uni_string, 0.0, 0, {}, {}) for string_view in self._string_features] flags = set() for i, flag_feature in enumerate(self._flag_features): if flag_feature(uni_string, 0.0, {}, {}): flags.add(i) lexeme = lexeme_init(uni_string, 0, 0, views, flags) self._dict.set(string.key, lexeme) self.size += 1 return lexeme cpdef Lexeme lookup(self, unicode uni_string): """Retrieve (or create, if not found) a Lexeme for a string, and return it. Args string (unicode): The string to be looked up. Must be unicode, not bytes. Returns: lexeme (Lexeme): A reference to a lexical type. """ cdef String string string_from_unicode(&string, uni_string) cdef LexemeC* lexeme = self.get(&string) return Lexeme(lexeme) _unicodes = set() cdef void string_from_unicode(String* s, unicode uni): global _unicodes _unicodes.add(uni) cdef Py_UNICODE* c_uni = uni string_from_slice(s, c_uni, 0, len(uni)) cdef inline void string_from_slice(String* s, Py_UNICODE* chars, size_t start, size_t end) nogil: s.chars = &chars[start] s.n = end - start s.key = hash64(s.chars, s.n * sizeof(Py_UNICODE), 0) cdef inline void string_slice_prefix(String* s, String* prefix, size_t n) nogil: string_from_slice(prefix, s.chars, 0, n) s.chars += n s.n -= n s.key = hash64(s.chars, s.n * sizeof(Py_UNICODE), 0)