mirror of https://github.com/explosion/spaCy.git
Modernise space attachment parser tests and don't depend on models
This commit is contained in:
Ines Montani
parent
69778924c8
commit
19c4132097
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@ -1,90 +1,75 @@
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# coding: utf-8
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from __future__ import unicode_literals
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from ...tokens.doc import Doc
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from ...attrs import HEAD
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from ..util import get_doc, apply_transition_sequence
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import pytest
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import numpy
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from spacy.attrs import HEAD
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def make_doc(EN, sentstr):
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sent = sentstr.split(' ')
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doc = EN.tokenizer.tokens_from_list(sent)
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EN.tagger(doc)
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return doc
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@pytest.mark.models
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def test_space_attachment(EN):
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sentence = 'This is a test.\nTo ensure spaces are attached well.'
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doc = EN(sentence)
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def test_parser_space_attachment(en_tokenizer):
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text = "This is a test.\nTo ensure spaces are attached well."
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heads = [1, 0, 1, -2, -3, -1, 1, 4, -1, 2, 1, 0, -1, -2]
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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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for sent in doc.sents:
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if len(sent) == 1:
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assert not sent[-1].is_space
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@pytest.mark.models
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def test_sentence_space(EN):
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text = ('''I look forward to using Thingamajig. I've been told it will '''
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'''make my life easier...''')
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doc = EN(text)
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def test_parser_sentence_space(en_tokenizer):
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text = "I look forward to using Thingamajig. I've been told it will make my life easier..."
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heads = [1, 0, -1, -2, -1, -1, -5, -1, 3, 2, 1, 0, 2, 1, -3, 1, 1, -3, -7]
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deps = ['nsubj', 'ROOT', 'advmod', 'prep', 'pcomp', 'dobj', 'punct', '',
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'nsubjpass', 'aux', 'auxpass', 'ROOT', 'nsubj', 'aux', 'ccomp',
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'poss', 'nsubj', 'ccomp', 'punct']
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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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assert len(list(doc.sents)) == 2
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@pytest.mark.models
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def test_space_attachment_leading_space(EN):
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# leading space token
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doc = make_doc(EN, '\t \n This is a sentence .')
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def test_parser_space_attachment_leading(en_tokenizer, en_parser):
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text = "\t \n This is a sentence ."
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heads = [1, 1, 0, 1, -2, -3]
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, text.split(' '), heads=heads)
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assert doc[0].is_space
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assert doc[1].is_space
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assert doc[2].orth_ == 'This'
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with EN.parser.step_through(doc) as stepwise:
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assert doc[2].text == 'This'
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with en_parser.step_through(doc) as stepwise:
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pass
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assert doc[0].head.i == 2
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assert doc[1].head.i == 2
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assert stepwise.stack == set([2])
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@pytest.mark.models
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def test_space_attachment_intermediate_and_trailing_space(EN):
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# intermediate and trailing space tokens
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doc = make_doc(EN, 'This is \t a \t\n \n sentence . \n\n \n')
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def test_parser_space_attachment_intermediate_trailing(en_tokenizer, en_parser):
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text = "This is \t a \t\n \n sentence . \n\n \n"
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heads = [1, 0, -1, 2, -1, -4, -5, -1]
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transition = ['L-nsubj', 'S', 'L-det', 'R-attr', 'D', 'R-punct']
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tokens = en_tokenizer(text)
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doc = get_doc(tokens.vocab, text.split(' '), heads=heads)
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assert doc[2].is_space
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assert doc[4].is_space
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assert doc[5].is_space
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assert doc[8].is_space
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assert doc[9].is_space
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with EN.parser.step_through(doc) as stepwise:
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stepwise.transition('L-nsubj')
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stepwise.transition('S')
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stepwise.transition('L-det')
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stepwise.transition('R-attr')
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stepwise.transition('D')
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stepwise.transition('R-punct')
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assert stepwise.stack == set([])
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for tok in doc:
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assert tok.dep != 0 or tok.is_space
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assert [ tok.head.i for tok in doc ] == [1,1,1,6,3,3,1,1,7,7]
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apply_transition_sequence(en_parser, doc, transition)
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for token in doc:
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assert token.dep != 0 or token.is_space
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assert [token.head.i for token in doc] == [1, 1, 1, 6, 3, 3, 1, 1, 7, 7]
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@pytest.mark.models
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def test_space_attachment_one_space_sentence(EN):
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# one space token sentence
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doc = make_doc(EN, '\n')
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assert len(doc) == 1
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with EN.parser.step_through(doc) as _:
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@pytest.mark.parametrize('text,length', [(['\n'], 1),
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(['\n', '\t', '\n\n', '\t'], 4)])
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def test_parser_space_attachment_space(en_tokenizer, en_parser, text, length):
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doc = Doc(en_parser.vocab, words=text)
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assert len(doc) == length
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with en_parser.step_through(doc) as _:
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pass
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assert doc[0].is_space
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assert doc[0].head.i == 0
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@pytest.mark.models
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def test_space_attachment_only_space_sentence(EN):
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# space-exclusive sentence
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doc = make_doc(EN, '\n \t \n\n \t')
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assert len(doc) == 4
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for tok in doc:
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assert tok.is_space
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with EN.parser.step_through(doc) as _:
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pass
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# all tokens are attached to the last one
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for tok in doc:
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assert tok.head.i == 3
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for token in doc:
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assert token.head.i == length-1
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