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fix formatting

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This commit is contained in:
svlandeg 2024-03-27 18:45:34 +01:00
parent ff88ab341a
commit a1cde9d021
2 changed files with 15 additions and 9 deletions
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12
spacy/pipeline/entity_linker.py
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@ -258,14 +258,16 @@ class EntityLinker(TrainablePipe):
self.scorer = _score_augmented self.scorer = _score_augmented
def _augment_examples(self, examples: Iterable[Example]) -> Iterable[Example]: def _augment_examples(self, examples: Iterable[Example]) -> Iterable[Example]:
"""If use_gold_ents is true, set the gold entities to eg.predicted. """If use_gold_ents is true, set the gold entities to (a copy of) eg.predicted."""
""" if not self.use_gold_ents:
return examples
new_examples = [] new_examples = []
for eg in examples: for eg in examples:
if self.use_gold_ents:
ents, _ = eg.get_aligned_ents_and_ner() ents, _ = eg.get_aligned_ents_and_ner()
eg.predicted.ents = ents new_eg = eg.copy()
new_examples.append(eg) new_eg.predicted.ents = ents
new_examples.append(new_eg)
return new_examples return new_examples
def set_kb(self, kb_loader: Callable[[Vocab], KnowledgeBase]): def set_kb(self, kb_loader: Callable[[Vocab], KnowledgeBase]):

8
spacy/tests/pipeline/test_entity_linker.py
View File

@ -744,7 +744,9 @@ def test_overfitting_IO_gold_entities():
return mykb return mykb
# Create the Entity Linker component and add it to the pipeline # Create the Entity Linker component and add it to the pipeline
entity_linker = nlp.add_pipe("entity_linker", last=True, config={"use_gold_ents": True}) entity_linker = nlp.add_pipe(
"entity_linker", last=True, config={"use_gold_ents": True}
)
assert isinstance(entity_linker, EntityLinker) assert isinstance(entity_linker, EntityLinker)
entity_linker.set_kb(create_kb) entity_linker.set_kb(create_kb)
assert "Q2146908" in entity_linker.vocab.strings assert "Q2146908" in entity_linker.vocab.strings
@ -849,7 +851,9 @@ def test_overfitting_IO_with_ner():
# Create the NER and EL components and add them to the pipeline # Create the NER and EL components and add them to the pipeline
ner = nlp.add_pipe("ner", first=True) ner = nlp.add_pipe("ner", first=True)
entity_linker = nlp.add_pipe("entity_linker", last=True, config={"use_gold_ents": False}) entity_linker = nlp.add_pipe(
"entity_linker", last=True, config={"use_gold_ents": False}
)
entity_linker.set_kb(create_kb) entity_linker.set_kb(create_kb)
train_examples = [] train_examples = []