mirror of https://github.com/explosion/spaCy.git
102 lines
3.1 KiB
Python
102 lines
3.1 KiB
Python
import pytest
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from spacy.pipeline.functions import merge_subtokens
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from spacy.language import Language
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from spacy.tokens import Span, Doc
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from ..doc.test_underscore import clean_underscore # noqa: F401
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@pytest.fixture
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def doc(en_vocab):
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# fmt: off
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words = ["This", "is", "a", "sentence", ".", "This", "is", "another", "sentence", ".", "And", "a", "third", "."]
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heads = [1, 1, 3, 1, 1, 6, 6, 8, 6, 6, 11, 12, 13, 13]
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deps = ["nsubj", "ROOT", "subtok", "attr", "punct", "nsubj", "ROOT",
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"subtok", "attr", "punct", "subtok", "subtok", "subtok", "ROOT"]
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# fmt: on
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return Doc(en_vocab, words=words, heads=heads, deps=deps)
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@pytest.fixture
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def doc2(en_vocab):
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words = ["I", "like", "New", "York", "in", "Autumn", "."]
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heads = [1, 1, 3, 1, 1, 4, 1]
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tags = ["PRP", "IN", "NNP", "NNP", "IN", "NNP", "."]
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pos = ["PRON", "VERB", "PROPN", "PROPN", "ADP", "PROPN", "PUNCT"]
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deps = ["ROOT", "prep", "compound", "pobj", "prep", "pobj", "punct"]
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doc = Doc(en_vocab, words=words, heads=heads, tags=tags, pos=pos, deps=deps)
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doc.ents = [Span(doc, 2, 4, label="GPE")]
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return doc
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def test_merge_subtokens(doc):
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doc = merge_subtokens(doc)
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# Doc doesn't have spaces, so the result is "And a third ."
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# fmt: off
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assert [t.text for t in doc] == ["This", "is", "a sentence", ".", "This", "is", "another sentence", ".", "And a third ."]
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# fmt: on
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def test_factories_merge_noun_chunks(doc2):
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assert len(doc2) == 7
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nlp = Language()
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merge_noun_chunks = nlp.create_pipe("merge_noun_chunks")
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merge_noun_chunks(doc2)
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assert len(doc2) == 6
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assert doc2[2].text == "New York"
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def test_factories_merge_ents(doc2):
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assert len(doc2) == 7
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assert len(list(doc2.ents)) == 1
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nlp = Language()
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merge_entities = nlp.create_pipe("merge_entities")
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merge_entities(doc2)
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assert len(doc2) == 6
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assert len(list(doc2.ents)) == 1
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assert doc2[2].text == "New York"
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def test_token_splitter():
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nlp = Language()
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config = {"min_length": 20, "split_length": 5}
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token_splitter = nlp.add_pipe("token_splitter", config=config)
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doc = nlp("aaaaabbbbbcccccdddd e f g")
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assert [t.text for t in doc] == ["aaaaabbbbbcccccdddd", "e", "f", "g"]
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doc = nlp("aaaaabbbbbcccccdddddeeeeeff g h i")
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assert [t.text for t in doc] == [
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"aaaaa",
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"bbbbb",
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"ccccc",
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"ddddd",
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"eeeee",
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"ff",
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"g",
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"h",
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"i",
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]
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assert all(len(t.text) <= token_splitter.split_length for t in doc)
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@pytest.mark.usefixtures("clean_underscore")
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def test_factories_doc_cleaner():
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nlp = Language()
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nlp.add_pipe("doc_cleaner")
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doc = nlp.make_doc("text")
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doc.tensor = [1, 2, 3]
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doc = nlp(doc)
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assert doc.tensor is None
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nlp = Language()
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nlp.add_pipe("doc_cleaner", config={"silent": False})
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with pytest.warns(UserWarning):
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doc = nlp("text")
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Doc.set_extension("test_attr", default=-1)
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nlp = Language()
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nlp.add_pipe("doc_cleaner", config={"attrs": {"_.test_attr": 0}})
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doc = nlp.make_doc("text")
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doc._.test_attr = 100
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doc = nlp(doc)
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assert doc._.test_attr == 0
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