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121 lines
3.7 KiB
Python
121 lines
3.7 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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from spacy.vocab import Vocab
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from spacy.tokens import Doc
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from ..util import get_doc
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def test_doc_split(en_tokenizer):
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text = "LosAngeles start."
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heads = [1, 1, 0]
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
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assert len(doc) == 3
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assert len(str(doc)) == 19
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assert doc[0].head.text == "start"
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assert doc[1].head.text == "."
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with doc.retokenize() as retokenizer:
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retokenizer.split(
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doc[0],
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["Los", "Angeles"],
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[1, 0],
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attrs={"tag": "NNP", "lemma": "Los Angeles", "ent_type": "GPE"},
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)
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assert len(doc) == 4
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assert doc[0].text == "Los"
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assert doc[0].head.text == "Angeles"
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assert doc[0].idx == 0
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assert doc[1].idx == 3
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assert doc[1].text == "Angeles"
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assert doc[1].head.text == "start"
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assert doc[2].text == "start"
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assert doc[2].head.text == "."
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assert doc[3].text == "."
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assert doc[3].head.text == "."
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assert len(str(doc)) == 19
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def test_split_dependencies(en_tokenizer):
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text = "LosAngeles start."
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, [t.text for t in tokens])
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dep1 = doc.vocab.strings.add("amod")
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dep2 = doc.vocab.strings.add("subject")
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [1, 0], [dep1, dep2])
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assert doc[0].dep == dep1
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assert doc[1].dep == dep2
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def test_split_heads_error(en_tokenizer):
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text = "LosAngeles start."
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, [t.text for t in tokens])
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# Not enough heads
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with pytest.raises(ValueError):
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [0])
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# Too many heads
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with pytest.raises(ValueError):
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [1, 1, 0])
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# No token head
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with pytest.raises(ValueError):
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [1, 1])
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# Several token heads
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with pytest.raises(ValueError):
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Los", "Angeles"], [0, 0])
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def test_spans_entity_merge_iob():
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# Test entity IOB stays consistent after merging
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words = ["abc", "d", "e"]
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doc = Doc(Vocab(), words=words)
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doc.ents = [(doc.vocab.strings.add("ent-abcd"), 0, 2)]
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assert doc[0].ent_iob_ == "B"
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assert doc[1].ent_iob_ == "I"
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["a", "b", "c"], [1, 1, 0])
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assert doc[0].ent_iob_ == "B"
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assert doc[1].ent_iob_ == "I"
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assert doc[2].ent_iob_ == "I"
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assert doc[3].ent_iob_ == "I"
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def test_spans_sentence_update_after_merge(en_tokenizer):
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# fmt: off
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text = "StewartLee is a stand up comedian. He lives in England and loves JoePasquale."
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heads = [1, 0, 1, 2, -1, -4, -5, 1, 0, -1, -1, -3, -4, 1, -2]
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deps = ["nsubj", "ROOT", "det", "amod", "prt", "attr", "punct", "nsubj",
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"ROOT", "prep", "pobj", "cc", "conj", "compound", "punct"]
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# fmt: on
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, deps=deps)
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sent1, sent2 = list(doc.sents)
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init_len = len(sent1)
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init_len2 = len(sent2)
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with doc.retokenize() as retokenizer:
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retokenizer.split(doc[0], ["Stewart", "Lee"], [1, 0])
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retokenizer.split(doc[14], ["Joe", "Pasquale"], [1, 0])
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sent1, sent2 = list(doc.sents)
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assert len(sent1) == init_len + 1
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assert len(sent2) == init_len2 + 1
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