# cython: infer_types=True # cython: profile=True from libcpp.vector cimport vector from libc.stdint cimport int32_t, uint64_t, uint16_t from preshed.maps cimport PreshMap from cymem.cymem cimport Pool from murmurhash.mrmr cimport hash64 from .typedefs cimport attr_t, hash_t from .structs cimport TokenC from .lexeme cimport attr_id_t from .vocab cimport Vocab from .tokens.doc cimport Doc from .tokens.doc cimport get_token_attr from .attrs cimport ID, attr_id_t, NULL_ATTR from .attrs import IDS 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 cdef enum action_t: REJECT = 0000 MATCH = 1000 ADVANCE = 0100 RETRY = 0010 RETRY_EXTEND = 0011 MATCH_EXTEND = 1001 MATCH_REJECT = 2000 cdef enum quantifier_t: ZERO ZERO_ONE ZERO_PLUS ONE ONE_PLUS cdef struct AttrValueC: attr_id_t attr attr_t value cdef struct TokenPatternC: AttrValueC* attrs int32_t nr_attr quantifier_t quantifier hash_t key cdef struct ActionC: char emit_match char next_state_next_token char next_state_same_token char same_state_next_token cdef struct PatternStateC: TokenPatternC* pattern int32_t start int32_t length cdef struct MatchC: attr_t pattern_id int32_t start int32_t length cdef find_matches(TokenPatternC** patterns, int n, Doc doc): cdef vector[PatternStateC] states cdef vector[MatchC] matches cdef PatternStateC state cdef Pool mem = Pool() # TODO: Prefill this with the extra attribute values. extra_attrs = mem.alloc(len(doc), sizeof(attr_t*)) # Main loop cdef int i, j for i in range(doc.length): for j in range(n): states.push_back(PatternStateC(patterns[j], i, 0)) transition_states(states, matches, &doc.c[i], extra_attrs[i]) # Handle matches that end in 0-width patterns finish_states(matches, states) return [(matches[i].pattern_id, matches[i].start, matches[i].start+matches[i].length) for i in range(matches.size())] cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& matches, const TokenC* token, const attr_t* extra_attrs) except *: cdef int q = 0 cdef vector[PatternStateC] new_states for i in range(states.size()): action = get_action(states[i], token, extra_attrs) if action == REJECT: continue state = states[i] states[q] = state while action in (RETRY, RETRY_EXTEND): if action == RETRY_EXTEND: new_states.push_back( PatternStateC(pattern=state.pattern, start=state.start, length=state.length+1)) states[q].pattern += 1 action = get_action(states[q], token, extra_attrs) if action == REJECT: pass elif action == ADVANCE: states[q].pattern += 1 states[q].length += 1 q += 1 else: ent_id = state.pattern[1].attrs.value if action == MATCH: matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length+1)) elif action == MATCH_REJECT: matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length)) elif action == MATCH_EXTEND: matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length)) states[q].length += 1 q += 1 states.resize(q) for i in range(new_states.size()): states.push_back(new_states[i]) cdef void finish_states(vector[MatchC]& matches, vector[PatternStateC]& states) except *: '''Handle states that end in zero-width patterns.''' cdef PatternStateC state for i in range(states.size()): state = states[i] while get_quantifier(state) in (ZERO_PLUS, ZERO_ONE): is_final = get_is_final(state) if is_final: ent_id = state.pattern[1].attrs.value matches.push_back( MatchC(pattern_id=ent_id, start=state.start, length=state.length)) break else: state.pattern += 1 cdef action_t get_action(PatternStateC state, const TokenC* token, const attr_t* extra_attrs) nogil: '''We need to consider: a) Does the token match the specification? [Yes, No] b) What's the quantifier? [1, 0+, ?] c) Is this the last specification? [final, non-final] We can transition in the following ways: a) Do we emit a match? b) Do we add a state with (next state, next token)? c) Do we add a state with (next state, same token)? d) Do we add a state with (same state, next token)? We'll code the actions as boolean strings, so 0000 means no to all 4, 1000 means match but no states added, etc. 1: Yes, final: 1000 Yes, non-final: 0100 No, final: 0000 No, non-final 0000 0+: Yes, final: 1001 Yes, non-final: 0011 No, final: 1000 (note: Don't include last token!) No, non-final: 0010 ?: Yes, final: 1000 Yes, non-final: 0100 No, final: 1000 (note: Don't include last token!) No, non-final: 0010 Possible combinations: 1000, 0100, 0000, 1001, 0011, 0010, We'll name the bits "match", "advance", "retry", "extend" REJECT = 0000 MATCH = 1000 ADVANCE = 0100 RETRY = 0010 MATCH_EXTEND = 1001 RETRY_EXTEND = 0011 MATCH_REJECT = 2000 # Match, but don't include last token Problem: If a quantifier is matching, we're adding a lot of open partials ''' cdef char is_match is_match = get_is_match(state, token, extra_attrs) quantifier = get_quantifier(state) is_final = get_is_final(state) if quantifier == ZERO: is_match = not is_match quantifier = ONE if quantifier == ONE: if is_match and is_final: # Yes, final: 1000 return MATCH elif is_match and not is_final: # Yes, non-final: 0100 return ADVANCE elif not is_match and is_final: # No, final: 0000 return REJECT else: return REJECT elif quantifier == ZERO_PLUS: if is_match and is_final: # Yes, final: 1001 return MATCH_EXTEND elif is_match and not is_final: # Yes, non-final: 0011 return RETRY_EXTEND elif not is_match and is_final: # No, final 2000 (note: Don't include last token!) return MATCH_REJECT else: # No, non-final 0010 return RETRY elif quantifier == ZERO_ONE: if is_match and is_final: # Yes, final: 1000 return MATCH elif is_match and not is_final: # Yes, non-final: 0100 return ADVANCE elif not is_match and is_final: # No, final 2000 (note: Don't include last token!) return MATCH_REJECT else: # No, non-final 0010 return RETRY cdef char get_is_match(PatternStateC state, const TokenC* token, const attr_t* extra_attrs) nogil: spec = state.pattern for attr in spec.attrs[:spec.nr_attr]: if get_token_attr(token, attr.attr) != attr.value: return 0 else: return 1 cdef char get_is_final(PatternStateC state) nogil: if state.pattern[1].attrs[0].attr == ID and state.pattern[1].nr_attr == 0: return 1 else: return 0 cdef char get_quantifier(PatternStateC state) nogil: return state.pattern.quantifier cdef TokenPatternC* init_pattern(Pool mem, attr_t entity_id, object token_specs) except NULL: pattern = 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 = 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 pattern[i].key = hash64(pattern[i].attrs, pattern[i].nr_attr * sizeof(AttrValueC), 0) i = len(token_specs) pattern[i].attrs = mem.alloc(2, sizeof(AttrValueC)) pattern[i].attrs[0].attr = ID pattern[i].attrs[0].value = entity_id pattern[i].nr_attr = 0 return pattern cdef attr_t get_pattern_key(const TokenPatternC* pattern) nogil: while pattern.nr_attr != 0: pattern += 1 id_attr = pattern[0].attrs[0] return id_attr.value def _convert_strings(token_specs, string_store): # Support 'syntactic sugar' operator '+', as combination of ONE, ZERO_PLUS operators = {'*': (ZERO_PLUS,), '+': (ONE, ZERO_PLUS), '?': (ZERO_ONE,), '1': (ONE,), '!': (ZERO,)} tokens = [] op = ONE for spec in token_specs: if not spec: # Signifier for 'any token' tokens.append((ONE, [(NULL_ATTR, 0)])) continue 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: msg = "Unknown operator '%s'. Options: %s" raise KeyError(msg % (value, ', '.join(operators.keys()))) if isinstance(attr, basestring): attr = IDS.get(attr.upper()) if isinstance(value, basestring): value = string_store.add(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 cdef class Matcher: """Match sequences of tokens, based on pattern rules.""" cdef Pool mem cdef vector[TokenPatternC*] patterns cdef readonly Vocab vocab cdef public object _patterns cdef public object _entities cdef public object _callbacks def __init__(self, vocab): """Create the Matcher. vocab (Vocab): The vocabulary object, which must be shared with the documents the matcher will operate on. RETURNS (Matcher): The newly constructed object. """ self._patterns = {} self._entities = {} self._callbacks = {} self.vocab = vocab self.mem = Pool() def __reduce__(self): data = (self.vocab, self._patterns, self._callbacks) return (unpickle_matcher, data, None, None) def __len__(self): """Get the number of rules added to the matcher. Note that this only returns the number of rules (identical with the number of IDs), not the number of individual patterns. RETURNS (int): The number of rules. """ return len(self._patterns) def __contains__(self, key): """Check whether the matcher contains rules for a match ID. key (unicode): The match ID. RETURNS (bool): Whether the matcher contains rules for this match ID. """ return self._normalize_key(key) in self._patterns def add(self, key, on_match, *patterns): """Add a match-rule to the matcher. A match-rule consists of: an ID key, an on_match callback, and one or more patterns. If the key exists, the patterns are appended to the previous ones, and the previous on_match callback is replaced. The `on_match` callback will receive the arguments `(matcher, doc, i, matches)`. You can also set `on_match` to `None` to not perform any actions. A pattern consists of one or more `token_specs`, where a `token_spec` is a dictionary mapping attribute IDs to values, and optionally a quantifier operator under the key "op". The available quantifiers are: '!': Negate the pattern, by requiring it to match exactly 0 times. '?': Make the pattern optional, by allowing it to match 0 or 1 times. '+': Require the pattern to match 1 or more times. '*': Allow the pattern to zero or more times. The + and * operators are usually interpretted "greedily", i.e. longer matches are returned where possible. However, if you specify two '+' and '*' patterns in a row and their matches overlap, the first operator will behave non-greedily. This quirk in the semantics makes the matcher more efficient, by avoiding the need for back-tracking. key (unicode): The match ID. on_match (callable): Callback executed on match. *patterns (list): List of token descritions. """ for pattern in patterns: if len(pattern) == 0: msg = ("Cannot add pattern for zero tokens to matcher.\n" "key: {key}\n") raise ValueError(msg.format(key=key)) key = self._normalize_key(key) for pattern in patterns: specs = _convert_strings(pattern, self.vocab.strings) self.patterns.push_back(init_pattern(self.mem, key, specs)) self._patterns.setdefault(key, []) self._callbacks[key] = on_match self._patterns[key].extend(patterns) def remove(self, key): """Remove a rule from the matcher. A KeyError is raised if the key does not exist. key (unicode): The ID of the match rule. """ key = self._normalize_key(key) self._patterns.pop(key) self._callbacks.pop(key) cdef int i = 0 while i < self.patterns.size(): pattern_key = get_pattern_key(self.patterns.at(i)) if pattern_key == key: self.patterns.erase(self.patterns.begin()+i) else: i += 1 def has_key(self, key): """Check whether the matcher has a rule with a given key. key (string or int): The key to check. RETURNS (bool): Whether the matcher has the rule. """ key = self._normalize_key(key) return key in self._patterns def get(self, key, default=None): """Retrieve the pattern stored for a key. key (unicode or int): The key to retrieve. RETURNS (tuple): The rule, as an (on_match, patterns) tuple. """ key = self._normalize_key(key) if key not in self._patterns: return default return (self._callbacks[key], self._patterns[key]) def pipe(self, docs, batch_size=1000, n_threads=2): """Match a stream of documents, yielding them in turn. docs (iterable): A stream of documents. batch_size (int): Number of documents to accumulate into a working set. n_threads (int): The number of threads with which to work on the buffer in parallel, if the implementation supports multi-threading. YIELDS (Doc): Documents, in order. """ for doc in docs: self(doc) yield doc def __call__(self, Doc doc): """Find all token sequences matching the supplied pattern. doc (Doc): The document to match over. RETURNS (list): A list of `(key, start, end)` tuples, describing the matches. A match tuple describes a span `doc[start:end]`. The `label_id` and `key` are both integers. """ matches = find_matches(&self.patterns[0], self.patterns.size(), doc) for i, (key, start, end) in enumerate(matches): on_match = self._callbacks.get(key, None) if on_match is not None: on_match(self, doc, i, matches) return matches def _normalize_key(self, key): if isinstance(key, basestring): return self.vocab.strings.add(key) else: return key def unpickle_matcher(vocab, patterns, callbacks): matcher = Matcher(vocab) for key, specs in patterns.items(): callback = callbacks.get(key, None) matcher.add(key, callback, *specs) return matcher def _get_longest_matches(matches): '''Filter out matches that have a longer equivalent.''' longest_matches = {} for pattern_id, start, end in matches: key = (pattern_id, start) length = end-start if key not in longest_matches or length > longest_matches[key]: longest_matches[key] = length return [(pattern_id, start, start+length) for (pattern_id, start), length in longest_matches.items()] def get_bilou(length): if length == 0: raise ValueError("Length must be >= 1") elif length == 1: return [U_ENT] elif length == 2: return [B2_ENT, L2_ENT] elif length == 3: return [B3_ENT, I3_ENT, L3_ENT] else: return [B4_ENT, I4_ENT] + [I4_ENT] * (length-3) + [L4_ENT] cdef class PhraseMatcher: cdef Pool mem cdef Vocab vocab cdef Matcher matcher cdef PreshMap phrase_ids cdef int max_length cdef public object _callbacks cdef public object _patterns def __init__(self, Vocab vocab, max_length=10): self.mem = Pool() self.max_length = max_length self.vocab = vocab self.matcher = Matcher(self.vocab) self.phrase_ids = PreshMap() abstract_patterns = [ [{U_ENT: True}], [{B2_ENT: True}, {L2_ENT: True}], [{B3_ENT: True}, {I3_ENT: True}, {L3_ENT: True}], [{B4_ENT: True}, {I4_ENT: True}, {I4_ENT: True, "OP": "+"}, {L4_ENT: True}], ] self.matcher.add('Candidate', None, *abstract_patterns) self._callbacks = {} def __len__(self): """Get the number of rules added to the matcher. Note that this only returns the number of rules (identical with the number of IDs), not the number of individual patterns. RETURNS (int): The number of rules. """ return len(self.phrase_ids) def __contains__(self, key): """Check whether the matcher contains rules for a match ID. key (unicode): The match ID. RETURNS (bool): Whether the matcher contains rules for this match ID. """ cdef hash_t ent_id = self.matcher._normalize_key(key) return ent_id in self._callbacks def __reduce__(self): return (self.__class__, (self.vocab,), None, None) def add(self, key, on_match, *docs): """Add a match-rule to the matcher. A match-rule consists of: an ID key, an on_match callback, and one or more patterns. key (unicode): The match ID. on_match (callable): Callback executed on match. *docs (Doc): `Doc` objects representing match patterns. """ cdef Doc doc cdef hash_t ent_id = self.matcher._normalize_key(key) self._callbacks[ent_id] = on_match cdef int length cdef int i cdef hash_t phrase_hash cdef Pool mem = Pool() for doc in docs: length = doc.length if length == 0: continue tags = get_bilou(length) phrase_key = mem.alloc(length, sizeof(attr_t)) for i, tag in enumerate(tags): lexeme = self.vocab[doc.c[i].lex.orth] lexeme.set_flag(tag, True) phrase_key[i] = lexeme.orth phrase_hash = hash64(phrase_key, length * sizeof(attr_t), 0) self.phrase_ids.set(phrase_hash, ent_id) def __call__(self, Doc doc): """Find all sequences matching the supplied patterns on the `Doc`. doc (Doc): The document to match over. RETURNS (list): A list of `(key, start, end)` tuples, describing the matches. A match tuple describes a span `doc[start:end]`. The `label_id` and `key` are both integers. """ matches = [] for _, start, end in self.matcher(doc): ent_id = self.accept_match(doc, start, end) if ent_id is not None: matches.append((ent_id, start, end)) for i, (ent_id, start, end) in enumerate(matches): on_match = self._callbacks.get(ent_id) if on_match is not None: on_match(self, doc, i, matches) return matches def pipe(self, stream, batch_size=1000, n_threads=2, return_matches=False, as_tuples=False): """Match a stream of documents, yielding them in turn. docs (iterable): A stream of documents. batch_size (int): Number of documents to accumulate into a working set. n_threads (int): The number of threads with which to work on the buffer in parallel, if the implementation supports multi-threading. return_matches (bool): Yield the match lists along with the docs, making results (doc, matches) tuples. as_tuples (bool): Interpret the input stream as (doc, context) tuples, and yield (result, context) tuples out. If both return_matches and as_tuples are True, the output will be a sequence of ((doc, matches), context) tuples. YIELDS (Doc): Documents, in order. """ if as_tuples: for doc, context in stream: matches = self(doc) if return_matches: yield ((doc, matches), context) else: yield (doc, context) else: for doc in stream: matches = self(doc) if return_matches: yield (doc, matches) else: yield doc def accept_match(self, Doc doc, int start, int end): cdef int i, j cdef Pool mem = Pool() phrase_key = mem.alloc(end-start, sizeof(attr_t)) for i, j in enumerate(range(start, end)): phrase_key[i] = doc.c[j].lex.orth cdef hash_t key = hash64(phrase_key, (end-start) * sizeof(attr_t), 0) ent_id = self.phrase_ids.get(key) if ent_id == 0: return None else: return ent_id