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Show warning if phrase pattern Doc was overprocessed (#3255)
In most cases, the PhraseMatcher will match on the verbatim token text or as of v2.1, sometimes the lowercase text. This means that we only need a tokenized Doc, without any other attributes. If phrase patterns are created by processing large terminology lists with the full `nlp` object, this easily can make things a lot slower, because all components will be applied, even if we don't actually need the attributes they set (like part-of-speech tags, dependency labels). The warning message also includes a suggestion to use nlp.make_doc or nlp.tokenizer.pipe for even faster processing. For now, the validation has to be enabled explicitly by setting validate=True.
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@ -60,6 +60,13 @@ class Warnings(object):
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"make displaCy start another one. Instead, you should be able to "
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"make displaCy start another one. Instead, you should be able to "
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"replace displacy.serve with displacy.render to show the "
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"replace displacy.serve with displacy.render to show the "
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"visualization.")
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"visualization.")
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W012 = ("A Doc object you're adding to the PhraseMatcher for pattern "
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"'{key}' is parsed and/or tagged, but to match on '{attr}', you "
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"don't actually need this information. This means that creating "
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"the patterns is potentially much slower, because all pipeline "
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"components are applied. To only create tokenized Doc objects, "
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"try using `nlp.make_doc(text)` or process all texts as a stream "
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"using `list(nlp.tokenizer.pipe(all_texts))`.")
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@add_codes
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@add_codes
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@ -7,12 +7,12 @@ from murmurhash.mrmr cimport hash64
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from preshed.maps cimport PreshMap
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from preshed.maps cimport PreshMap
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from .matcher cimport Matcher
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from .matcher cimport Matcher
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from ..attrs cimport ORTH, attr_id_t
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from ..attrs cimport ORTH, POS, TAG, DEP, LEMMA, attr_id_t
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from ..vocab cimport Vocab
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from ..vocab cimport Vocab
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from ..tokens.doc cimport Doc, get_token_attr
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from ..tokens.doc cimport Doc, get_token_attr
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from ..typedefs cimport attr_t, hash_t
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from ..typedefs cimport attr_t, hash_t
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from ..errors import Warnings, deprecation_warning
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from ..errors import Warnings, deprecation_warning, user_warning
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from ..attrs import FLAG61 as U_ENT
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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 FLAG60 as B2_ENT
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from ..attrs import FLAG59 as B3_ENT
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from ..attrs import FLAG59 as B3_ENT
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@ -33,8 +33,9 @@ cdef class PhraseMatcher:
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cdef attr_id_t attr
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cdef attr_id_t attr
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cdef public object _callbacks
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cdef public object _callbacks
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cdef public object _patterns
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cdef public object _patterns
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cdef public object _validate
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def __init__(self, Vocab vocab, max_length=0, attr='ORTH'):
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def __init__(self, Vocab vocab, max_length=0, attr='ORTH', validate=False):
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if max_length != 0:
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if max_length != 0:
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deprecation_warning(Warnings.W010)
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deprecation_warning(Warnings.W010)
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self.mem = Pool()
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self.mem = Pool()
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@ -54,6 +55,7 @@ cdef class PhraseMatcher:
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]
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]
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self.matcher.add('Candidate', None, *abstract_patterns)
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self.matcher.add('Candidate', None, *abstract_patterns)
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self._callbacks = {}
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self._callbacks = {}
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self._validate = validate
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def __len__(self):
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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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"""Get the number of rules added to the matcher. Note that this only
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@ -95,6 +97,10 @@ cdef class PhraseMatcher:
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length = doc.length
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length = doc.length
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if length == 0:
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if length == 0:
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continue
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continue
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if self._validate and (doc.is_tagged or doc.is_parsed) \
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and self.attr not in (DEP, POS, TAG, LEMMA):
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string_attr = self.vocab.strings[self.attr]
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user_warning(Warnings.W012.format(key=key, attr=string_attr))
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tags = get_bilou(length)
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tags = get_bilou(length)
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phrase_key = <attr_t*>mem.alloc(length, sizeof(attr_t))
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phrase_key = <attr_t*>mem.alloc(length, sizeof(attr_t))
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for i, tag in enumerate(tags):
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for i, tag in enumerate(tags):
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@ -1,6 +1,7 @@
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# coding: utf-8
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# coding: utf-8
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from __future__ import unicode_literals
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from __future__ import unicode_literals
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import pytest
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from spacy.matcher import PhraseMatcher
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from spacy.matcher import PhraseMatcher
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from spacy.tokens import Doc
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from spacy.tokens import Doc
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from ..util import get_doc
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from ..util import get_doc
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@ -78,3 +79,23 @@ def test_phrase_matcher_bool_attrs(en_vocab):
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assert end1 == 3
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assert end1 == 3
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assert start2 == 3
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assert start2 == 3
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assert end2 == 6
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assert end2 == 6
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def test_phrase_matcher_validation(en_vocab):
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doc1 = Doc(en_vocab, words=["Test"])
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doc1.is_parsed = True
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doc2 = Doc(en_vocab, words=["Test"])
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doc2.is_tagged = True
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doc3 = Doc(en_vocab, words=["Test"])
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matcher = PhraseMatcher(en_vocab, validate=True)
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with pytest.warns(UserWarning):
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matcher.add("TEST1", None, doc1)
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with pytest.warns(UserWarning):
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matcher.add("TEST2", None, doc2)
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with pytest.warns(None) as record:
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matcher.add("TEST3", None, doc3)
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assert not record.list
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matcher = PhraseMatcher(en_vocab, attr="POS", validate=True)
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with pytest.warns(None) as record:
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matcher.add("TEST4", None, doc2)
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assert not record.list
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