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negative tag annotation (#8731)

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* unit test to unlearn tag via negative annotation

* bump thinc to 8.0.8
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Sofie Van Landeghem 2021-07-19 14:39:11 +02:00 committed by GitHub
parent 0e4b96c97e
commit 83e27d262e
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5 changed files with 16 additions and 5 deletions
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2
pyproject.toml
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@ -5,7 +5,7 @@ requires = [
"cymem>=2.0.2,<2.1.0", "cymem>=2.0.2,<2.1.0",
"preshed>=3.0.2,<3.1.0", "preshed>=3.0.2,<3.1.0",
"murmurhash>=0.28.0,<1.1.0", "murmurhash>=0.28.0,<1.1.0",
"thinc>=8.0.7,<8.1.0", "thinc>=8.0.8,<8.1.0",
"blis>=0.4.0,<0.8.0", "blis>=0.4.0,<0.8.0",
"pathy", "pathy",
"numpy>=1.15.0", "numpy>=1.15.0",

2
requirements.txt
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@ -2,7 +2,7 @@
spacy-legacy>=3.0.7,<3.1.0 spacy-legacy>=3.0.7,<3.1.0
cymem>=2.0.2,<2.1.0 cymem>=2.0.2,<2.1.0
preshed>=3.0.2,<3.1.0 preshed>=3.0.2,<3.1.0
thinc>=8.0.7,<8.1.0 thinc>=8.0.8,<8.1.0
blis>=0.4.0,<0.8.0 blis>=0.4.0,<0.8.0
ml_datasets>=0.2.0,<0.3.0 ml_datasets>=0.2.0,<0.3.0
murmurhash>=0.28.0,<1.1.0 murmurhash>=0.28.0,<1.1.0

4
setup.cfg
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@ -37,14 +37,14 @@ setup_requires =
cymem>=2.0.2,<2.1.0 cymem>=2.0.2,<2.1.0
preshed>=3.0.2,<3.1.0 preshed>=3.0.2,<3.1.0
murmurhash>=0.28.0,<1.1.0 murmurhash>=0.28.0,<1.1.0
thinc>=8.0.7,<8.1.0 thinc>=8.0.8,<8.1.0
install_requires = install_requires =
# Our libraries # Our libraries
spacy-legacy>=3.0.7,<3.1.0 spacy-legacy>=3.0.7,<3.1.0
murmurhash>=0.28.0,<1.1.0 murmurhash>=0.28.0,<1.1.0
cymem>=2.0.2,<2.1.0 cymem>=2.0.2,<2.1.0
preshed>=3.0.2,<3.1.0 preshed>=3.0.2,<3.1.0
thinc>=8.0.7,<8.1.0 thinc>=8.0.8,<8.1.0
blis>=0.4.0,<0.8.0 blis>=0.4.0,<0.8.0
wasabi>=0.8.1,<1.1.0 wasabi>=0.8.1,<1.1.0
srsly>=2.4.1,<3.0.0 srsly>=2.4.1,<3.0.0

2
spacy/pipeline/tagger.pyx
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@ -222,7 +222,7 @@ class Tagger(TrainablePipe):
DOCS: https://spacy.io/api/tagger#get_loss DOCS: https://spacy.io/api/tagger#get_loss
""" """
validate_examples(examples, "Tagger.get_loss") validate_examples(examples, "Tagger.get_loss")
loss_func = SequenceCategoricalCrossentropy(names=self.labels, normalize=False) loss_func = SequenceCategoricalCrossentropy(names=self.labels, normalize=False, neg_prefix="!")
# Convert empty tag "" to missing value None so that both misaligned # Convert empty tag "" to missing value None so that both misaligned
# tokens and tokens with missing annotation have the default missing # tokens and tokens with missing annotation have the default missing
# value None. # value None.

11
spacy/tests/pipeline/test_tagger.py
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@ -182,6 +182,17 @@ def test_overfitting_IO():
assert_equal(batch_deps_1, batch_deps_2) assert_equal(batch_deps_1, batch_deps_2)
assert_equal(batch_deps_1, no_batch_deps) assert_equal(batch_deps_1, no_batch_deps)
# Try to unlearn the first 'N' tag with negative annotation
neg_ex = Example.from_dict(nlp.make_doc(test_text), {"tags": ["!N", "V", "J", "N"]})
for i in range(20):
losses = {}
nlp.update([neg_ex], sgd=optimizer, losses=losses)
# test the "untrained" tag
doc3 = nlp(test_text)
assert doc3[0].tag_ != "N"
def test_tagger_requires_labels(): def test_tagger_requires_labels():
nlp = English() nlp = English()