spaCy/spacy/tests/parser/test_space_attachment.py
Matthew Honnibal 8cf097ca88 Redesign training to integrate NN components
* Obsolete .parser, .entity etc names in favour of .pipeline
* Components no longer create models on initialization
* Models created by loading method (from_disk(), from_bytes() etc), or
    .begin_training()
* Add .predict(), .set_annotations() methods in components
* Pass state through pipeline, to allow components to share information
    more flexibly.
2017-05-16 16:17:30 +02:00

79 lines
2.7 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
from ...tokens.doc import Doc
from ...attrs import HEAD
from ..util import get_doc, apply_transition_sequence
import pytest
def test_parser_space_attachment(en_tokenizer):
text = "This is a test.\nTo ensure spaces are attached well."
heads = [1, 0, 1, -2, -3, -1, 1, 4, -1, 2, 1, 0, -1, -2]
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads)
for sent in doc.sents:
if len(sent) == 1:
assert not sent[-1].is_space
def test_parser_sentence_space(en_tokenizer):
text = "I look forward to using Thingamajig. I've been told it will make my life easier..."
heads = [1, 0, -1, -2, -1, -1, -5, -1, 3, 2, 1, 0, 2, 1, -3, 1, 1, -3, -7]
deps = ['nsubj', 'ROOT', 'advmod', 'prep', 'pcomp', 'dobj', 'punct', '',
'nsubjpass', 'aux', 'auxpass', 'ROOT', 'nsubj', 'aux', 'ccomp',
'poss', 'nsubj', 'ccomp', 'punct']
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, [t.text for t in tokens], heads=heads, deps=deps)
assert len(list(doc.sents)) == 2
@pytest.mark.xfail
def test_parser_space_attachment_leading(en_tokenizer, en_parser):
text = "\t \n This is a sentence ."
heads = [1, 1, 0, 1, -2, -3]
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, text.split(' '), heads=heads)
assert doc[0].is_space
assert doc[1].is_space
assert doc[2].text == 'This'
with en_parser.step_through(doc) as stepwise:
pass
assert doc[0].head.i == 2
assert doc[1].head.i == 2
assert stepwise.stack == set([2])
@pytest.mark.xfail
def test_parser_space_attachment_intermediate_trailing(en_tokenizer, en_parser):
text = "This is \t a \t\n \n sentence . \n\n \n"
heads = [1, 0, -1, 2, -1, -4, -5, -1]
transition = ['L-nsubj', 'S', 'L-det', 'R-attr', 'D', 'R-punct']
tokens = en_tokenizer(text)
doc = get_doc(tokens.vocab, text.split(' '), heads=heads)
assert doc[2].is_space
assert doc[4].is_space
assert doc[5].is_space
assert doc[8].is_space
assert doc[9].is_space
apply_transition_sequence(en_parser, doc, transition)
for token in doc:
assert token.dep != 0 or token.is_space
assert [token.head.i for token in doc] == [1, 1, 1, 6, 3, 3, 1, 1, 7, 7]
@pytest.mark.parametrize('text,length', [(['\n'], 1),
(['\n', '\t', '\n\n', '\t'], 4)])
@pytest.mark.xfail
def test_parser_space_attachment_space(en_tokenizer, en_parser, text, length):
doc = Doc(en_parser.vocab, words=text)
assert len(doc) == length
with en_parser.step_through(doc) as _:
pass
assert doc[0].is_space
for token in doc:
assert token.head.i == length-1