spaCy/spacy/tokenizer.pyx

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# cython: embedsignature=True
from __future__ import unicode_literals
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from os import path
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import re
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from cython.operator cimport dereference as deref
from cython.operator cimport preincrement as preinc
from cpython cimport Py_UNICODE_ISSPACE
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from cymem.cymem cimport Pool
from preshed.maps cimport PreshMap
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from murmurhash.mrmr cimport hash64
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from .morphology cimport set_morph_from_dict
from .strings cimport hash_string
cimport cython
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from . import util
from .util import read_lang_data
from .tokens.doc cimport Doc
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cdef class Tokenizer:
def __init__(self, Vocab vocab, rules, prefix_re, suffix_re, infix_re):
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self.mem = Pool()
self._cache = PreshMap()
self._specials = PreshMap()
self._prefix_re = prefix_re
self._suffix_re = suffix_re
self._infix_re = infix_re
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self.vocab = vocab
self._load_special_tokenization(rules, self.vocab.pos_tags)
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@classmethod
def from_dir(cls, Vocab vocab, data_dir):
rules, prefix_re, suffix_re, infix_re = read_lang_data(data_dir)
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prefix_re = re.compile(prefix_re)
suffix_re = re.compile(suffix_re)
infix_re = re.compile(infix_re)
return cls(vocab, rules, prefix_re, suffix_re, infix_re)
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cpdef Doc tokens_from_list(self, list strings):
cdef Doc tokens = Doc(self.vocab)
if sum([len(s) for s in strings]) == 0:
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return tokens
cdef unicode py_string
cdef int idx = 0
for i, py_string in enumerate(strings):
# Note that we pass tokens.mem here --- the Doc object has ownership
tokens.push_back(
<const LexemeC*>self.vocab.get(tokens.mem, py_string), True)
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idx += len(py_string) + 1
return tokens
@cython.boundscheck(False)
def __call__(self, unicode string):
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"""Tokenize a string.
The tokenization rules are defined in three places:
* The data/<lang>/tokenization table, which handles special cases like contractions;
* The data/<lang>/prefix file, used to build a regex to split off prefixes;
* The data/<lang>/suffix file, used to build a regex to split off suffixes.
The string is first split on whitespace. To tokenize a whitespace-delimited
chunk, we first try to look it up in the special-cases. If it's not found,
we split off a prefix, and then try again. If it's still not found, we
split off a suffix, and repeat.
Args:
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string (unicode): The string to be tokenized.
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Returns:
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tokens (Doc): A Doc object, giving access to a sequence of LexemeCs.
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"""
cdef int length = len(string)
cdef Doc tokens = Doc(self.vocab)
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if length == 0:
return tokens
cdef int i = 0
cdef int start = 0
cdef bint cache_hit
cdef bint in_ws = Py_UNICODE_ISSPACE(string[0])
cdef unicode span
# Use of Py_UNICODE is deprecated, and I should be using Py_UCS4.
# But this is hard --- I need to acquire a pointer, but there's no
# Py_UCS4 API in Python 2.
cdef Py_UNICODE uc
cdef Py_UNICODE* chars_ptr = <Py_UNICODE*>string
# The task here is much like string.split, but not quite
# We find spans of whitespace and non-space characters, and ignore
# spans that are exactly ' '. So, our sequences will all be separated
# by either ' ' or nothing.
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for i in range(1, length):
uc = chars_ptr[i]
if Py_UNICODE_ISSPACE(uc) != in_ws:
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if start < i:
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key = hash64(&chars_ptr[start], (i - start) * sizeof(Py_UNICODE), 0)
cache_hit = self._try_cache(key, tokens)
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if not cache_hit:
self._tokenize(tokens, string[start:i], key)
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in_ws = not in_ws
if uc == ' ':
tokens.data[tokens.length - 1].spacy = True
start = i + 1
else:
start = i
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i += 1
if start < i:
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key = hash64(&chars_ptr[start], (i - start) * sizeof(Py_UNICODE), 0)
cache_hit = self._try_cache(key, tokens)
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if not cache_hit:
self._tokenize(tokens, string[start:], key)
tokens.data[tokens.length - 1].spacy = string[-1] == ' '
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return tokens
cdef int _try_cache(self, hash_t key, Doc tokens) except -1:
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cached = <_Cached*>self._cache.get(key)
if cached == NULL:
return False
cdef int i
if cached.is_lex:
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for i in range(cached.length):
tokens.push_back(cached.data.lexemes[i], False)
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else:
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for i in range(cached.length):
tokens.push_back(&cached.data.tokens[i], False)
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return True
cdef int _tokenize(self, Doc tokens, unicode span, hash_t orig_key) except -1:
cdef vector[LexemeC*] prefixes
cdef vector[LexemeC*] suffixes
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cdef int orig_size
orig_size = tokens.length
span = self._split_affixes(span, &prefixes, &suffixes)
self._attach_tokens(tokens, span, &prefixes, &suffixes)
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self._save_cached(&tokens.data[orig_size], orig_key, tokens.length - orig_size)
cdef unicode _split_affixes(self, unicode string, vector[const LexemeC*] *prefixes,
vector[const LexemeC*] *suffixes):
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cdef size_t i
cdef unicode prefix
cdef unicode suffix
cdef unicode minus_pre
cdef unicode minus_suf
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cdef size_t last_size = 0
while string and len(string) != last_size:
last_size = len(string)
pre_len = self.find_prefix(string)
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if pre_len != 0:
prefix = string[:pre_len]
minus_pre = string[pre_len:]
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# Check whether we've hit a special-case
if minus_pre and self._specials.get(hash_string(minus_pre)) != NULL:
string = minus_pre
prefixes.push_back(self.vocab.get(self.vocab.mem, prefix))
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break
suf_len = self.find_suffix(string)
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if suf_len != 0:
suffix = string[-suf_len:]
minus_suf = string[:-suf_len]
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# Check whether we've hit a special-case
if minus_suf and (self._specials.get(hash_string(minus_suf)) != NULL):
string = minus_suf
suffixes.push_back(self.vocab.get(self.vocab.mem, suffix))
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break
if pre_len and suf_len and (pre_len + suf_len) <= len(string):
string = string[pre_len:-suf_len]
prefixes.push_back(self.vocab.get(self.vocab.mem, prefix))
suffixes.push_back(self.vocab.get(self.vocab.mem, suffix))
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elif pre_len:
string = minus_pre
prefixes.push_back(self.vocab.get(self.vocab.mem, prefix))
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elif suf_len:
string = minus_suf
suffixes.push_back(self.vocab.get(self.vocab.mem, suffix))
if string and (self._specials.get(hash_string(string)) != NULL):
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break
return string
cdef int _attach_tokens(self, Doc tokens, unicode string,
vector[const LexemeC*] *prefixes,
vector[const LexemeC*] *suffixes) except -1:
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cdef bint cache_hit
cdef int split, end
cdef const LexemeC* const* lexemes
cdef const LexemeC* lexeme
cdef unicode span
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cdef int i
if prefixes.size():
for i in range(prefixes.size()):
tokens.push_back(prefixes[0][i], False)
if string:
cache_hit = self._try_cache(hash_string(string), tokens)
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if cache_hit:
pass
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else:
match = self.find_infix(string)
if match is None:
tokens.push_back(self.vocab.get(tokens.mem, string), False)
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else:
split = match.start()
end = match.end()
# Append the beginning, affix, end of the infix span
span = string[:split]
tokens.push_back(self.vocab.get(tokens.mem, span), False)
span = string[split:end]
tokens.push_back(self.vocab.get(tokens.mem, span), False)
span = string[end:]
tokens.push_back(self.vocab.get(tokens.mem, span), False)
cdef vector[const LexemeC*].reverse_iterator it = suffixes.rbegin()
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while it != suffixes.rend():
lexeme = deref(it)
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preinc(it)
tokens.push_back(lexeme, False)
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cdef int _save_cached(self, const TokenC* tokens, hash_t key, int n) except -1:
cdef int i
for i in range(n):
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if tokens[i].lex.id == 0:
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return 0
cached = <_Cached*>self.mem.alloc(1, sizeof(_Cached))
cached.length = n
cached.is_lex = True
lexemes = <const LexemeC**>self.mem.alloc(n, sizeof(LexemeC**))
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for i in range(n):
lexemes[i] = tokens[i].lex
cached.data.lexemes = <const LexemeC* const*>lexemes
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self._cache.set(key, cached)
def find_infix(self, unicode string):
return self._infix_re.search(string)
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def find_prefix(self, unicode string):
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match = self._prefix_re.search(string)
return (match.end() - match.start()) if match is not None else 0
def find_suffix(self, unicode string):
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match = self._suffix_re.search(string)
return (match.end() - match.start()) if match is not None else 0
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def _load_special_tokenization(self, object rules, object tag_map):
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'''Add a special-case tokenization rule.
'''
cdef int i
cdef list substrings
cdef unicode chunk
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cdef unicode form
cdef unicode lemma
cdef dict props
cdef LexemeC** lexemes
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cdef hash_t hashed
for chunk, substrings in sorted(rules.items()):
tokens = <TokenC*>self.mem.alloc(len(substrings) + 1, sizeof(TokenC))
for i, props in enumerate(substrings):
form = props['F']
lemma = props.get("L", None)
tokens[i].lex = <LexemeC*>self.vocab.get(self.vocab.mem, form)
if lemma is not None:
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tokens[i].lemma = self.vocab.strings[lemma]
else:
tokens[i].lemma = 0
if 'pos' in props:
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tokens[i].tag = self.vocab.strings[props['pos']]
tokens[i].pos = tag_map[props['pos']][0]
# These are defaults, which can be over-ridden by the
# token-specific props.
set_morph_from_dict(&tokens[i].morph, tag_map[props['pos']][1])
if tokens[i].lemma == 0:
tokens[i].lemma = tokens[i].lex.orth
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set_morph_from_dict(&tokens[i].morph, props)
cached = <_Cached*>self.mem.alloc(1, sizeof(_Cached))
cached.length = len(substrings)
cached.is_lex = False
cached.data.tokens = tokens
hashed = hash_string(chunk)
self._specials.set(hashed, cached)
self._cache.set(hashed, cached)