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spaCy/spacy/matcher.pyx

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Cython
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# cython: profile=True
from __future__ import unicode_literals
from os import path
from .typedefs cimport attr_t
from .typedefs cimport hash_t
from .attrs cimport attr_id_t
from .structs cimport TokenC, LexemeC
from .lexeme cimport Lexeme
from cymem.cymem cimport Pool
from preshed.maps cimport PreshMap
from libcpp.vector cimport vector
from libcpp.pair cimport pair
from murmurhash.mrmr cimport hash64
from libc.stdint cimport int32_t
from .attrs cimport ID, LENGTH, ENT_TYPE, ORTH, NORM, LEMMA, LOWER, SHAPE
from . import attrs
from .tokens.doc cimport get_token_attr
from .tokens.doc cimport Doc
from .vocab cimport Vocab
from .attrs import FLAG61 as U_ENT
from .attrs import FLAG60 as B2_ENT
from .attrs import FLAG59 as B3_ENT
from .attrs import FLAG58 as B4_ENT
from .attrs import FLAG57 as B5_ENT
from .attrs import FLAG56 as B6_ENT
from .attrs import FLAG55 as B7_ENT
from .attrs import FLAG54 as B8_ENT
from .attrs import FLAG53 as B9_ENT
from .attrs import FLAG52 as B10_ENT
from .attrs import FLAG51 as I3_ENT
from .attrs import FLAG50 as I4_ENT
from .attrs import FLAG49 as I5_ENT
from .attrs import FLAG48 as I6_ENT
from .attrs import FLAG47 as I7_ENT
from .attrs import FLAG46 as I8_ENT
from .attrs import FLAG45 as I9_ENT
from .attrs import FLAG44 as I10_ENT
from .attrs import FLAG43 as L2_ENT
from .attrs import FLAG42 as L3_ENT
from .attrs import FLAG41 as L4_ENT
from .attrs import FLAG40 as L5_ENT
from .attrs import FLAG39 as L6_ENT
from .attrs import FLAG38 as L7_ENT
from .attrs import FLAG37 as L8_ENT
from .attrs import FLAG36 as L9_ENT
from .attrs import FLAG35 as L10_ENT
try:
import ujson as json
except ImportError:
import json
cpdef enum quantifier_t:
_META
ONE
ZERO
ZERO_ONE
ZERO_PLUS
cdef enum action_t:
REJECT
ADVANCE
REPEAT
ACCEPT
ADVANCE_ZERO
PANIC
cdef struct AttrValueC:
attr_id_t attr
attr_t value
cdef struct TokenPatternC:
AttrValueC* attrs
int32_t nr_attr
quantifier_t quantifier
ctypedef TokenPatternC* TokenPatternC_ptr
ctypedef pair[int, TokenPatternC_ptr] StateC
cdef TokenPatternC* init_pattern(Pool mem, object token_specs, attr_t entity_id,
attr_t entity_type) except NULL:
pattern = <TokenPatternC*>mem.alloc(len(token_specs) + 1, sizeof(TokenPatternC))
cdef int i
for i, (quantifier, spec) in enumerate(token_specs):
pattern[i].quantifier = quantifier
pattern[i].attrs = <AttrValueC*>mem.alloc(len(spec), sizeof(AttrValueC))
pattern[i].nr_attr = len(spec)
for j, (attr, value) in enumerate(spec):
pattern[i].attrs[j].attr = attr
pattern[i].attrs[j].value = value
i = len(token_specs)
pattern[i].attrs = <AttrValueC*>mem.alloc(3, sizeof(AttrValueC))
pattern[i].attrs[0].attr = ID
pattern[i].attrs[0].value = entity_id
pattern[i].attrs[1].attr = ENT_TYPE
pattern[i].attrs[1].value = entity_type
pattern[i].nr_attr = 0
return pattern
cdef int get_action(const TokenPatternC* pattern, const TokenC* token) nogil:
for attr in pattern.attrs[:pattern.nr_attr]:
if get_token_attr(token, attr.attr) != attr.value:
if pattern.quantifier == ONE:
return REJECT
elif pattern.quantifier == ZERO:
return ACCEPT if (pattern+1).nr_attr == 0 else ADVANCE
elif pattern.quantifier in (ZERO_ONE, ZERO_PLUS):
return ACCEPT if (pattern+1).nr_attr == 0 else ADVANCE_ZERO
else:
return PANIC
if pattern.quantifier == ZERO:
return REJECT
elif pattern.quantifier in (ONE, ZERO_ONE):
return ACCEPT if (pattern+1).nr_attr == 0 else ADVANCE
elif pattern.quantifier == ZERO_PLUS:
return REPEAT
else:
return PANIC
def _convert_strings(token_specs, string_store):
# Support 'syntactic sugar' operator '+', as combination of ONE, ZERO_PLUS
operators = {'!': (ZERO,), '*': (ZERO_PLUS,), '+': (ONE, ZERO_PLUS),
'?': (ZERO_ONE,)}
tokens = []
op = ONE
for spec in token_specs:
token = []
ops = (ONE,)
for attr, value in spec.items():
if isinstance(attr, basestring) and attr.upper() == 'OP':
if value in operators:
ops = operators[value]
else:
raise KeyError(
"Unknown operator. Options: %s" % ', '.join(operators.keys()))
if isinstance(attr, basestring):
attr = attrs.IDS.get(attr.upper())
if isinstance(value, basestring):
value = string_store[value]
if isinstance(value, bool):
value = int(value)
if attr is not None:
token.append((attr, value))
for op in ops:
tokens.append((op, token))
return tokens
def get_bilou(length):
if length == 1:
return [U_ENT]
elif length == 2:
return [B2_ENT, L2_ENT]
elif length == 3:
return [B3_ENT, I3_ENT, L3_ENT]
elif length == 4:
return [B4_ENT, I4_ENT, I4_ENT, L4_ENT]
elif length == 5:
return [B5_ENT, I5_ENT, I5_ENT, I5_ENT, L5_ENT]
elif length == 6:
return [B6_ENT, I6_ENT, I6_ENT, I6_ENT, I6_ENT, L6_ENT]
elif length == 7:
return [B7_ENT, I7_ENT, I7_ENT, I7_ENT, I7_ENT, I7_ENT, L7_ENT]
elif length == 8:
return [B8_ENT, I8_ENT, I8_ENT, I8_ENT, I8_ENT, I8_ENT, I8_ENT, L8_ENT]
elif length == 9:
return [B9_ENT, I9_ENT, I9_ENT, I9_ENT, I9_ENT, I9_ENT, I9_ENT, I9_ENT, L9_ENT]
elif length == 10:
return [B10_ENT, I10_ENT, I10_ENT, I10_ENT, I10_ENT, I10_ENT, I10_ENT,
I10_ENT, I10_ENT, L10_ENT]
else:
raise ValueError("Max length currently 10 for phrase matching")
cdef class Matcher:
cdef Pool mem
cdef vector[TokenPatternC*] patterns
cdef readonly Vocab vocab
cdef public object _patterns
@classmethod
def load(cls, path, vocab):
if (path / 'patterns.json').exists():
with (path / 'patterns.json').open() as file_:
patterns = json.load(file_)
return cls(vocab, patterns)
def __init__(self, vocab, patterns={}):
self._patterns = dict(patterns) # Make sure we own the object
self.vocab = vocab
self.mem = Pool()
self.vocab = vocab
for entity_key, (etype, attrs, specs) in sorted(self._patterns.items()):
self.add(entity_key, etype, attrs, specs)
def __reduce__(self):
return (self.__class__, (self.vocab, self._patterns), None, None)
property n_patterns:
def __get__(self): return self.patterns.size()
def add(self, entity_key, etype, attrs, specs):
self._patterns[entity_key] = (etype, dict(attrs), list(specs))
if isinstance(entity_key, basestring):
entity_key = self.vocab.strings[entity_key]
if isinstance(etype, basestring):
etype = self.vocab.strings[etype]
elif etype is None:
etype = -1
# TODO: Do something more clever about multiple patterns for single
# entity
for spec in specs:
spec = _convert_strings(spec, self.vocab.strings)
self.patterns.push_back(init_pattern(self.mem, spec, entity_key, etype))
def __call__(self, Doc doc, acceptor=None):
cdef vector[StateC] partials
cdef int n_partials = 0
cdef int q = 0
cdef int i, token_i
cdef const TokenC* token
cdef StateC state
matches = []
for token_i in range(doc.length):
token = &doc.c[token_i]
q = 0
# Go over the open matches, extending or finalizing if able. Otherwise,
# we over-write them (q doesn't advance)
for state in partials:
action = get_action(state.second, token)
while action == ADVANCE_ZERO:
state.second += 1
action = get_action(state.second, token)
if action == REPEAT:
# Leave the state in the queue, and advance to next slot
# (i.e. we don't overwrite -- we want to greedily match more
# pattern.
q += 1
elif action == REJECT:
pass
elif action == ADVANCE:
partials[q].second += 1
q += 1
elif action == ACCEPT:
# TODO: What to do about patterns starting with ZERO? Need to
# adjust the start position.
start = state.first
end = token_i+1
ent_id = state.second[1].attrs[0].value
label = state.second[1].attrs[1].value
if acceptor is None or acceptor(doc, ent_id, label, start, end):
matches.append((ent_id, label, start, end))
partials.resize(q)
# Check whether we open any new patterns on this token
for pattern in self.patterns:
action = get_action(pattern, token)
while action == ADVANCE_ZERO:
pattern += 1
action = get_action(pattern, token)
if action == REPEAT:
state.first = token_i
state.second = pattern
partials.push_back(state)
elif action == ADVANCE:
# TODO: What to do about patterns starting with ZERO? Need to
# adjust the start position.
state.first = token_i
state.second = pattern + 1
partials.push_back(state)
elif action == ACCEPT:
start = token_i
end = token_i+1
ent_id = pattern[1].attrs[0].value
label = pattern[1].attrs[1].value
if acceptor is None or acceptor(doc, ent_id, label, start, end):
matches.append((ent_id, label, start, end))
return matches
def pipe(self, docs, batch_size=1000, n_threads=2):
for doc in docs:
self(doc)
yield doc
cdef class PhraseMatcher:
cdef Pool mem
cdef Vocab vocab
cdef Matcher matcher
cdef PreshMap phrase_ids
cdef int max_length
cdef attr_t* _phrase_key
def __init__(self, Vocab vocab, phrases, max_length=10):
self.mem = Pool()
self._phrase_key = <attr_t*>self.mem.alloc(max_length, sizeof(attr_t))
self.max_length = max_length
self.vocab = vocab
self.matcher = Matcher(self.vocab, {})
self.phrase_ids = PreshMap()
for phrase in phrases:
if len(phrase) < max_length:
self.add(phrase)
abstract_patterns = []
for length in range(1, max_length):
abstract_patterns.append([{tag: True} for tag in get_bilou(length)])
self.matcher.add('Candidate', 'MWE', {}, abstract_patterns)
def add(self, Doc tokens):
cdef int length = tokens.length
assert length < self.max_length
tags = get_bilou(length)
assert len(tags) == length, length
cdef int i
for i in range(self.max_length):
self._phrase_key[i] = 0
for i, tag in enumerate(tags):
lexeme = self.vocab[tokens.c[i].lex.orth]
lexeme.set_flag(tag, True)
self._phrase_key[i] = lexeme.orth
cdef hash_t key = hash64(self._phrase_key, self.max_length * sizeof(attr_t), 0)
self.phrase_ids[key] = True
def __call__(self, Doc doc):
matches = []
for label, start, end in self.matcher(doc, acceptor=self.accept_match):
cand = doc[start : end]
start = cand[0].idx
end = cand[-1].idx + len(cand[-1])
matches.append((start, end, cand.root.tag_, cand.text, 'MWE'))
for match in matches:
doc.merge(*match)
return matches
def pipe(self, stream, batch_size=1000, n_threads=2):
for doc in stream:
self(doc)
yield doc
def accept_match(self, Doc doc, int label, int start, int end):
assert (end - start) < self.max_length
cdef int i, j
for i in range(self.max_length):
self._phrase_key[i] = 0
for i, j in enumerate(range(start, end)):
self._phrase_key[i] = doc.c[j].lex.orth
cdef hash_t key = hash64(self._phrase_key, self.max_length * sizeof(attr_t), 0)
if self.phrase_ids.get(key):
return True
else:
return False
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