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spaCy/spacy/matcher/phrasematcher.pxd

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Replace PhraseMatcher with trie-based search (#4309) * Replace PhraseMatcher with Aho-Corasick Replace PhraseMatcher with the Aho-Corasick algorithm over numpy arrays of the hash values for the relevant attribute. The implementation is based on FlashText. The speed should be similar to the previous PhraseMatcher. It is now possible to easily remove match IDs and matches don't go missing with large keyword lists / vocabularies. Fixes #4308. * Restore support for pickling * Fix internal keyword add/remove for numpy arrays * Add missing loop for match ID set in search loop * Remove cruft in matching loop for partial matches There was a bit of unnecessary code left over from FlashText in the matching loop to handle partial token matches, which we don't have with PhraseMatcher. * Replace dict trie with MapStruct trie * Fix how match ID hash is stored/added * Update fix for match ID vocab * Switch from map_get_unless_missing to map_get * Switch from numpy array to Token.get_struct_attr Access token attributes directly in Doc instead of making a copy of the relevant values in a numpy array. Add unsatisfactory warning for hash collision with reserved terminal hash key. (Ideally it would change the reserved terminal hash and redo the whole trie, but for now, I'm hoping there won't be collisions.) * Restructure imports to export find_matches * Implement full remove() Remove unnecessary trie paths and free unused maps. Parallel to Matcher, raise KeyError when attempting to remove a match ID that has not been added. * Store docs internally only as attr lists * Reduces size for pickle * Remove duplicate keywords store Now that docs are stored as lists of attr hashes, there's no need to have the duplicate _keywords store.
2019-09-27 17:22:34 +03:00
from cymem.cymem cimport Pool
isort all the things
2023-06-26 12:41:03 +03:00
from libcpp.vector cimport vector
from preshed.maps cimport MapStruct, key_t
Matcher ID fixes (#4179) * allow phrasematcher to link one match to multiple original patterns * small fix for defining ent_id in the matcher (anti-ghost prevention) * cleanup * formatting
2019-08-22 18:17:07 +03:00
Replace PhraseMatcher with trie-based search (#4309) * Replace PhraseMatcher with Aho-Corasick Replace PhraseMatcher with the Aho-Corasick algorithm over numpy arrays of the hash values for the relevant attribute. The implementation is based on FlashText. The speed should be similar to the previous PhraseMatcher. It is now possible to easily remove match IDs and matches don't go missing with large keyword lists / vocabularies. Fixes #4308. * Restore support for pickling * Fix internal keyword add/remove for numpy arrays * Add missing loop for match ID set in search loop * Remove cruft in matching loop for partial matches There was a bit of unnecessary code left over from FlashText in the matching loop to handle partial token matches, which we don't have with PhraseMatcher. * Replace dict trie with MapStruct trie * Fix how match ID hash is stored/added * Update fix for match ID vocab * Switch from map_get_unless_missing to map_get * Switch from numpy array to Token.get_struct_attr Access token attributes directly in Doc instead of making a copy of the relevant values in a numpy array. Add unsatisfactory warning for hash collision with reserved terminal hash key. (Ideally it would change the reserved terminal hash and redo the whole trie, but for now, I'm hoping there won't be collisions.) * Restructure imports to export find_matches * Implement full remove() Remove unnecessary trie paths and free unused maps. Parallel to Matcher, raise KeyError when attempting to remove a match ID that has not been added. * Store docs internally only as attr lists * Reduces size for pickle * Remove duplicate keywords store Now that docs are stored as lists of attr hashes, there's no need to have the duplicate _keywords store.
2019-09-27 17:22:34 +03:00
from ..attrs cimport attr_id_t
Replace Entity/MatchStruct with SpanC (#4459) * Replace MatchStruct with Entity Replace MatchStruct with Entity since the existing Entity struct is nearly identical. * Replace Entity with more general SpanC
2019-10-18 12:01:47 +03:00
from ..structs cimport SpanC
Replace PhraseMatcher with trie-based search (#4309) * Replace PhraseMatcher with Aho-Corasick Replace PhraseMatcher with the Aho-Corasick algorithm over numpy arrays of the hash values for the relevant attribute. The implementation is based on FlashText. The speed should be similar to the previous PhraseMatcher. It is now possible to easily remove match IDs and matches don't go missing with large keyword lists / vocabularies. Fixes #4308. * Restore support for pickling * Fix internal keyword add/remove for numpy arrays * Add missing loop for match ID set in search loop * Remove cruft in matching loop for partial matches There was a bit of unnecessary code left over from FlashText in the matching loop to handle partial token matches, which we don't have with PhraseMatcher. * Replace dict trie with MapStruct trie * Fix how match ID hash is stored/added * Update fix for match ID vocab * Switch from map_get_unless_missing to map_get * Switch from numpy array to Token.get_struct_attr Access token attributes directly in Doc instead of making a copy of the relevant values in a numpy array. Add unsatisfactory warning for hash collision with reserved terminal hash key. (Ideally it would change the reserved terminal hash and redo the whole trie, but for now, I'm hoping there won't be collisions.) * Restructure imports to export find_matches * Implement full remove() Remove unnecessary trie paths and free unused maps. Parallel to Matcher, raise KeyError when attempting to remove a match ID that has not been added. * Store docs internally only as attr lists * Reduces size for pickle * Remove duplicate keywords store Now that docs are stored as lists of attr hashes, there's no need to have the duplicate _keywords store.
2019-09-27 17:22:34 +03:00
from ..tokens.doc cimport Doc
from ..vocab cimport Vocab
cdef class PhraseMatcher:
Make PhraseMatcher.vocab consistent with Matcher.vocab (closes #4373)
2019-10-04 13:18:41 +03:00
cdef readonly Vocab vocab
Replace PhraseMatcher with trie-based search (#4309) * Replace PhraseMatcher with Aho-Corasick Replace PhraseMatcher with the Aho-Corasick algorithm over numpy arrays of the hash values for the relevant attribute. The implementation is based on FlashText. The speed should be similar to the previous PhraseMatcher. It is now possible to easily remove match IDs and matches don't go missing with large keyword lists / vocabularies. Fixes #4308. * Restore support for pickling * Fix internal keyword add/remove for numpy arrays * Add missing loop for match ID set in search loop * Remove cruft in matching loop for partial matches There was a bit of unnecessary code left over from FlashText in the matching loop to handle partial token matches, which we don't have with PhraseMatcher. * Replace dict trie with MapStruct trie * Fix how match ID hash is stored/added * Update fix for match ID vocab * Switch from map_get_unless_missing to map_get * Switch from numpy array to Token.get_struct_attr Access token attributes directly in Doc instead of making a copy of the relevant values in a numpy array. Add unsatisfactory warning for hash collision with reserved terminal hash key. (Ideally it would change the reserved terminal hash and redo the whole trie, but for now, I'm hoping there won't be collisions.) * Restructure imports to export find_matches * Implement full remove() Remove unnecessary trie paths and free unused maps. Parallel to Matcher, raise KeyError when attempting to remove a match ID that has not been added. * Store docs internally only as attr lists * Reduces size for pickle * Remove duplicate keywords store Now that docs are stored as lists of attr hashes, there's no need to have the duplicate _keywords store.
2019-09-27 17:22:34 +03:00
cdef attr_id_t attr
cdef object _callbacks
cdef object _docs
cdef bint _validate
cdef MapStruct* c_map
cdef Pool mem
cdef key_t _terminal_hash
Run PhraseMatcher on Spans (#6918) * Add regression test * Run PhraseMatcher on Spans * Add test for PhraseMatcher on Spans and Docs * Add SCA * Add test with 3 matches in Doc, 1 match in Span * Update docs * Use doc.length for find_matches in tokenizer Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
2021-02-10 15:43:32 +03:00
cdef void find_matches(self, Doc doc, int start_idx, int end_idx, vector[SpanC] *matches) nogil
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