mirror of https://github.com/explosion/spaCy.git
62 lines
2.4 KiB
Python
62 lines
2.4 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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from spacy.lemmatizer import Lemmatizer
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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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def test_lemmatizer_without_is_base_form_implementation():
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# Norwegian example from #5658
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lookups = Lookups()
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lookups.add_table("lemma_rules", {"noun": []})
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lookups.add_table("lemma_index", {"noun": {}})
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lookups.add_table("lemma_exc", {"noun": {"formuesskatten": ["formuesskatt"]}})
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lemmatizer = Lemmatizer(lookups, is_base_form=None)
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assert lemmatizer("Formuesskatten", "noun", {'Definite': 'def', 'Gender': 'masc', 'Number': 'sing'}) == ["formuesskatt"]
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