mirror of
https://github.com/explosion/spaCy.git
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688 lines
23 KiB
Cython
688 lines
23 KiB
Cython
# cython: infer_types=True
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# cython: profile=True
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from __future__ import unicode_literals
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from libcpp.vector cimport vector
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from libc.stdint cimport int32_t, uint64_t, uint16_t
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from preshed.maps cimport PreshMap
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from cymem.cymem cimport Pool
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from murmurhash.mrmr cimport hash64
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from .typedefs cimport attr_t, hash_t
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from .structs cimport TokenC
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from .lexeme cimport attr_id_t
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from .vocab cimport Vocab
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from .tokens.doc cimport Doc
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from .tokens.doc cimport get_token_attr
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from .attrs cimport ID, attr_id_t, NULL_ATTR
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from .errors import Errors, TempErrors
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from .attrs import IDS
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from .attrs import FLAG61 as U_ENT
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from .attrs import FLAG60 as B2_ENT
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from .attrs import FLAG59 as B3_ENT
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from .attrs import FLAG58 as B4_ENT
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from .attrs import FLAG57 as B5_ENT
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from .attrs import FLAG56 as B6_ENT
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from .attrs import FLAG55 as B7_ENT
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from .attrs import FLAG54 as B8_ENT
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from .attrs import FLAG53 as B9_ENT
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from .attrs import FLAG52 as B10_ENT
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from .attrs import FLAG51 as I3_ENT
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from .attrs import FLAG50 as I4_ENT
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from .attrs import FLAG49 as I5_ENT
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from .attrs import FLAG48 as I6_ENT
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from .attrs import FLAG47 as I7_ENT
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from .attrs import FLAG46 as I8_ENT
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from .attrs import FLAG45 as I9_ENT
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from .attrs import FLAG44 as I10_ENT
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from .attrs import FLAG43 as L2_ENT
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from .attrs import FLAG42 as L3_ENT
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from .attrs import FLAG41 as L4_ENT
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from .attrs import FLAG40 as L5_ENT
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from .attrs import FLAG39 as L6_ENT
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from .attrs import FLAG38 as L7_ENT
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from .attrs import FLAG37 as L8_ENT
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from .attrs import FLAG36 as L9_ENT
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from .attrs import FLAG35 as L10_ENT
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cdef enum action_t:
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REJECT = 0000
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MATCH = 1000
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ADVANCE = 0100
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RETRY = 0010
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RETRY_EXTEND = 0011
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MATCH_EXTEND = 1001
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MATCH_REJECT = 2000
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cdef enum quantifier_t:
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ZERO
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ZERO_ONE
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ZERO_PLUS
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ONE
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ONE_PLUS
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cdef struct AttrValueC:
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attr_id_t attr
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attr_t value
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cdef struct TokenPatternC:
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AttrValueC* attrs
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int32_t nr_attr
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quantifier_t quantifier
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hash_t key
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cdef struct ActionC:
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char emit_match
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char next_state_next_token
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char next_state_same_token
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char same_state_next_token
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cdef struct PatternStateC:
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TokenPatternC* pattern
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int32_t start
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int32_t length
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cdef struct MatchC:
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attr_t pattern_id
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int32_t start
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int32_t length
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cdef find_matches(TokenPatternC** patterns, int n, Doc doc):
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cdef vector[PatternStateC] states
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cdef vector[MatchC] matches
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cdef PatternStateC state
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cdef Pool mem = Pool()
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# TODO: Prefill this with the extra attribute values.
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extra_attrs = <attr_t**>mem.alloc(len(doc), sizeof(attr_t*))
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# Main loop
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cdef int i, j
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for i in range(doc.length):
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for j in range(n):
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states.push_back(PatternStateC(patterns[j], i, 0))
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transition_states(states, matches, &doc.c[i], extra_attrs[i])
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# Handle matches that end in 0-width patterns
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finish_states(matches, states)
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return [(matches[i].pattern_id, matches[i].start, matches[i].start+matches[i].length)
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for i in range(matches.size())]
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cdef void transition_states(vector[PatternStateC]& states, vector[MatchC]& matches,
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const TokenC* token, const attr_t* extra_attrs) except *:
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cdef int q = 0
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cdef vector[PatternStateC] new_states
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for i in range(states.size()):
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action = get_action(states[i], token, extra_attrs)
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if action == REJECT:
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continue
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state = states[i]
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states[q] = state
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while action in (RETRY, RETRY_EXTEND):
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if action == RETRY_EXTEND:
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new_states.push_back(
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PatternStateC(pattern=state.pattern, start=state.start,
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length=state.length+1))
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states[q].pattern += 1
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action = get_action(states[q], token, extra_attrs)
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if action == REJECT:
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pass
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elif action == ADVANCE:
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states[q].pattern += 1
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states[q].length += 1
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q += 1
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else:
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ent_id = state.pattern[1].attrs.value
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if action == MATCH:
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matches.push_back(
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MatchC(pattern_id=ent_id, start=state.start,
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length=state.length+1))
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elif action == MATCH_REJECT:
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matches.push_back(
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MatchC(pattern_id=ent_id, start=state.start,
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length=state.length))
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elif action == MATCH_EXTEND:
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matches.push_back(
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MatchC(pattern_id=ent_id, start=state.start,
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length=state.length))
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states[q].length += 1
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q += 1
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states.resize(q)
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for i in range(new_states.size()):
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states.push_back(new_states[i])
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cdef void finish_states(vector[MatchC]& matches, vector[PatternStateC]& states) except *:
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'''Handle states that end in zero-width patterns.'''
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cdef PatternStateC state
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for i in range(states.size()):
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state = states[i]
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while get_quantifier(state) in (ZERO_PLUS, ZERO_ONE):
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is_final = get_is_final(state)
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if is_final:
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ent_id = state.pattern[1].attrs.value
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matches.push_back(
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MatchC(pattern_id=ent_id, start=state.start, length=state.length))
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break
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else:
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state.pattern += 1
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cdef action_t get_action(PatternStateC state, const TokenC* token, const attr_t* extra_attrs) nogil:
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'''We need to consider:
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a) Does the token match the specification? [Yes, No]
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b) What's the quantifier? [1, 0+, ?]
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c) Is this the last specification? [final, non-final]
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We can transition in the following ways:
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a) Do we emit a match?
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b) Do we add a state with (next state, next token)?
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c) Do we add a state with (next state, same token)?
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d) Do we add a state with (same state, next token)?
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We'll code the actions as boolean strings, so 0000 means no to all 4,
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1000 means match but no states added, etc.
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1:
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Yes, final:
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1000
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Yes, non-final:
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0100
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No, final:
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0000
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No, non-final
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0000
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0+:
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Yes, final:
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1001
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Yes, non-final:
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0011
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No, final:
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1000 (note: Don't include last token!)
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No, non-final:
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0010
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?:
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Yes, final:
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1000
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Yes, non-final:
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0100
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No, final:
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1000 (note: Don't include last token!)
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No, non-final:
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0010
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Possible combinations: 1000, 0100, 0000, 1001, 0011, 0010,
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We'll name the bits "match", "advance", "retry", "extend"
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REJECT = 0000
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MATCH = 1000
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ADVANCE = 0100
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RETRY = 0010
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MATCH_EXTEND = 1001
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RETRY_EXTEND = 0011
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MATCH_REJECT = 2000 # Match, but don't include last token
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Problem: If a quantifier is matching, we're adding a lot of open partials
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'''
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cdef char is_match
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is_match = get_is_match(state, token, extra_attrs)
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quantifier = get_quantifier(state)
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is_final = get_is_final(state)
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if quantifier == ZERO:
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is_match = not is_match
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quantifier = ONE
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if quantifier == ONE:
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if is_match and is_final:
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# Yes, final: 1000
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return MATCH
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elif is_match and not is_final:
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# Yes, non-final: 0100
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return ADVANCE
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elif not is_match and is_final:
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# No, final: 0000
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return REJECT
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else:
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return REJECT
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elif quantifier == ZERO_PLUS:
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if is_match and is_final:
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# Yes, final: 1001
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return MATCH_EXTEND
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elif is_match and not is_final:
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# Yes, non-final: 0011
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return RETRY_EXTEND
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elif not is_match and is_final:
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# No, final 2000 (note: Don't include last token!)
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return MATCH_REJECT
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else:
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# No, non-final 0010
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return RETRY
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elif quantifier == ZERO_ONE:
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if is_match and is_final:
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# Yes, final: 1000
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return MATCH
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elif is_match and not is_final:
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# Yes, non-final: 0100
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return ADVANCE
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elif not is_match and is_final:
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# No, final 2000 (note: Don't include last token!)
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return MATCH_REJECT
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else:
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# No, non-final 0010
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return RETRY
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cdef char get_is_match(PatternStateC state, const TokenC* token, const attr_t* extra_attrs) nogil:
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spec = state.pattern
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for attr in spec.attrs[:spec.nr_attr]:
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if get_token_attr(token, attr.attr) != attr.value:
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return 0
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else:
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return 1
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cdef char get_is_final(PatternStateC state) nogil:
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if state.pattern[1].attrs[0].attr == ID and state.pattern[1].nr_attr == 0:
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return 1
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else:
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return 0
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cdef char get_quantifier(PatternStateC state) nogil:
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return state.pattern.quantifier
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cdef TokenPatternC* init_pattern(Pool mem, attr_t entity_id,
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object token_specs) except NULL:
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pattern = <TokenPatternC*>mem.alloc(len(token_specs) + 1, sizeof(TokenPatternC))
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cdef int i
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for i, (quantifier, spec) in enumerate(token_specs):
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pattern[i].quantifier = quantifier
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pattern[i].attrs = <AttrValueC*>mem.alloc(len(spec), sizeof(AttrValueC))
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pattern[i].nr_attr = len(spec)
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for j, (attr, value) in enumerate(spec):
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pattern[i].attrs[j].attr = attr
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pattern[i].attrs[j].value = value
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pattern[i].key = hash64(pattern[i].attrs, pattern[i].nr_attr * sizeof(AttrValueC), 0)
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i = len(token_specs)
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pattern[i].attrs = <AttrValueC*>mem.alloc(2, sizeof(AttrValueC))
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pattern[i].attrs[0].attr = ID
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pattern[i].attrs[0].value = entity_id
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pattern[i].nr_attr = 0
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return pattern
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cdef attr_t get_pattern_key(const TokenPatternC* pattern) nogil:
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while pattern.nr_attr != 0:
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pattern += 1
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id_attr = pattern[0].attrs[0]
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if id_attr.attr != ID:
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with gil:
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raise ValueError(Errors.E074.format(attr=ID, bad_attr=id_attr.attr))
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return id_attr.value
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def _convert_strings(token_specs, string_store):
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# Support 'syntactic sugar' operator '+', as combination of ONE, ZERO_PLUS
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operators = {'*': (ZERO_PLUS,), '+': (ONE, ZERO_PLUS),
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'?': (ZERO_ONE,), '1': (ONE,), '!': (ZERO,)}
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tokens = []
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op = ONE
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for spec in token_specs:
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if not spec:
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# Signifier for 'any token'
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tokens.append((ONE, [(NULL_ATTR, 0)]))
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continue
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token = []
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ops = (ONE,)
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for attr, value in spec.items():
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if isinstance(attr, basestring) and attr.upper() == 'OP':
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if value in operators:
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ops = operators[value]
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else:
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keys = ', '.join(operators.keys())
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raise KeyError(Errors.E011.format(op=value, opts=keys))
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if isinstance(attr, basestring):
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attr = IDS.get(attr.upper())
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if isinstance(value, basestring):
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value = string_store.add(value)
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if isinstance(value, bool):
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value = int(value)
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if attr is not None:
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token.append((attr, value))
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for op in ops:
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tokens.append((op, token))
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return tokens
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cdef class Matcher:
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"""Match sequences of tokens, based on pattern rules."""
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cdef Pool mem
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cdef vector[TokenPatternC*] patterns
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cdef readonly Vocab vocab
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cdef public object _patterns
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cdef public object _entities
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cdef public object _callbacks
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def __init__(self, vocab):
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"""Create the Matcher.
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vocab (Vocab): The vocabulary object, which must be shared with the
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documents the matcher will operate on.
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RETURNS (Matcher): The newly constructed object.
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"""
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self._patterns = {}
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self._entities = {}
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self._callbacks = {}
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self.vocab = vocab
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self.mem = Pool()
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def __reduce__(self):
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data = (self.vocab, self._patterns, self._callbacks)
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return (unpickle_matcher, data, None, None)
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def __len__(self):
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"""Get the number of rules added to the matcher. Note that this only
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returns the number of rules (identical with the number of IDs), not the
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number of individual patterns.
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RETURNS (int): The number of rules.
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"""
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return len(self._patterns)
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def __contains__(self, key):
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"""Check whether the matcher contains rules for a match ID.
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key (unicode): The match ID.
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RETURNS (bool): Whether the matcher contains rules for this match ID.
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"""
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return self._normalize_key(key) in self._patterns
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def add(self, key, on_match, *patterns):
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"""Add a match-rule to the matcher. A match-rule consists of: an ID
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key, an on_match callback, and one or more patterns.
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If the key exists, the patterns are appended to the previous ones, and
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the previous on_match callback is replaced. The `on_match` callback
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will receive the arguments `(matcher, doc, i, matches)`. You can also
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set `on_match` to `None` to not perform any actions.
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A pattern consists of one or more `token_specs`, where a `token_spec`
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is a dictionary mapping attribute IDs to values, and optionally a
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quantifier operator under the key "op". The available quantifiers are:
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'!': Negate the pattern, by requiring it to match exactly 0 times.
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'?': Make the pattern optional, by allowing it to match 0 or 1 times.
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'+': Require the pattern to match 1 or more times.
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'*': Allow the pattern to zero or more times.
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The + and * operators are usually interpretted "greedily", i.e. longer
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matches are returned where possible. However, if you specify two '+'
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and '*' patterns in a row and their matches overlap, the first
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operator will behave non-greedily. This quirk in the semantics makes
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the matcher more efficient, by avoiding the need for back-tracking.
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key (unicode): The match ID.
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on_match (callable): Callback executed on match.
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*patterns (list): List of token descritions.
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"""
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for pattern in patterns:
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if len(pattern) == 0:
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raise ValueError(Errors.E012.format(key=key))
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key = self._normalize_key(key)
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for pattern in patterns:
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specs = _convert_strings(pattern, self.vocab.strings)
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self.patterns.push_back(init_pattern(self.mem, key, specs))
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self._patterns.setdefault(key, [])
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self._callbacks[key] = on_match
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self._patterns[key].extend(patterns)
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def remove(self, key):
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"""Remove a rule from the matcher. A KeyError is raised if the key does
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not exist.
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key (unicode): The ID of the match rule.
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"""
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key = self._normalize_key(key)
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self._patterns.pop(key)
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self._callbacks.pop(key)
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cdef int i = 0
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while i < self.patterns.size():
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pattern_key = get_pattern_key(self.patterns.at(i))
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if pattern_key == key:
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self.patterns.erase(self.patterns.begin()+i)
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else:
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i += 1
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def has_key(self, key):
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"""Check whether the matcher has a rule with a given key.
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key (string or int): The key to check.
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RETURNS (bool): Whether the matcher has the rule.
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"""
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key = self._normalize_key(key)
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return key in self._patterns
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def get(self, key, default=None):
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"""Retrieve the pattern stored for a key.
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key (unicode or int): The key to retrieve.
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RETURNS (tuple): The rule, as an (on_match, patterns) tuple.
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"""
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key = self._normalize_key(key)
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if key not in self._patterns:
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return default
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return (self._callbacks[key], self._patterns[key])
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def pipe(self, docs, batch_size=1000, n_threads=2):
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"""Match a stream of documents, yielding them in turn.
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docs (iterable): A stream of documents.
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batch_size (int): Number of documents to accumulate into a working set.
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n_threads (int): The number of threads with which to work on the buffer
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in parallel, if the implementation supports multi-threading.
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YIELDS (Doc): Documents, in order.
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"""
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for doc in docs:
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self(doc)
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yield doc
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def __call__(self, Doc doc):
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"""Find all token sequences matching the supplied pattern.
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doc (Doc): The document to match over.
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RETURNS (list): A list of `(key, start, end)` tuples,
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describing the matches. A match tuple describes a span
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`doc[start:end]`. The `label_id` and `key` are both integers.
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"""
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matches = find_matches(&self.patterns[0], self.patterns.size(), doc)
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for i, (key, start, end) in enumerate(matches):
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on_match = self._callbacks.get(key, None)
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if on_match is not None:
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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 = <attr_t*>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, <void*>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 = <attr_t*>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 = <hash_t>self.phrase_ids.get(key)
|
|
if ent_id == 0:
|
|
return None
|
|
else:
|
|
return ent_id
|