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https://github.com/explosion/spaCy.git
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c482f20778
* Fix warning message for lemmatization tables * Add a warning when the `lexeme_norm` table is empty. (Given the relatively lang-specific loading for `Lookups`, it seemed like too much overhead to dynamically extract the list of languages, so for now it's hard-coded.)
50 lines
1.9 KiB
Python
50 lines
1.9 KiB
Python
# coding: utf8
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from __future__ import unicode_literals
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import pytest
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from spacy.tokens import Doc
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from spacy.language import Language
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from spacy.lookups import Lookups
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def test_lemmatizer_reflects_lookups_changes():
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"""Test for an issue that'd cause lookups available in a model loaded from
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disk to not be reflected in the lemmatizer."""
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nlp = Language()
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assert Doc(nlp.vocab, words=["foo"])[0].lemma_ == "foo"
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table = nlp.vocab.lookups.add_table("lemma_lookup")
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table["foo"] = "bar"
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assert Doc(nlp.vocab, words=["foo"])[0].lemma_ == "bar"
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table = nlp.vocab.lookups.get_table("lemma_lookup")
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table["hello"] = "world"
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# The update to the table should be reflected in the lemmatizer
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assert Doc(nlp.vocab, words=["hello"])[0].lemma_ == "world"
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new_nlp = Language()
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table = new_nlp.vocab.lookups.add_table("lemma_lookup")
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table["hello"] = "hi"
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assert Doc(new_nlp.vocab, words=["hello"])[0].lemma_ == "hi"
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nlp_bytes = nlp.to_bytes()
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new_nlp.from_bytes(nlp_bytes)
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# Make sure we have the previously saved lookup table
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assert "lemma_lookup" in new_nlp.vocab.lookups
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assert len(new_nlp.vocab.lookups.get_table("lemma_lookup")) == 2
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assert new_nlp.vocab.lookups.get_table("lemma_lookup")["hello"] == "world"
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assert Doc(new_nlp.vocab, words=["foo"])[0].lemma_ == "bar"
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assert Doc(new_nlp.vocab, words=["hello"])[0].lemma_ == "world"
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def test_tagger_warns_no_lookups():
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nlp = Language()
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nlp.vocab.lookups = Lookups()
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assert not len(nlp.vocab.lookups)
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tagger = nlp.create_pipe("tagger")
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nlp.add_pipe(tagger)
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with pytest.warns(UserWarning):
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nlp.begin_training()
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nlp.vocab.lookups.add_table("lemma_lookup")
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nlp.vocab.lookups.add_table("lexeme_norm")
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nlp.vocab.lookups.get_table("lexeme_norm")["a"] = "A"
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with pytest.warns(None) as record:
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nlp.begin_training()
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assert not record.list
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