spaCy/spacy/tests/regression/test_issue7716.py

import pytest
from thinc.api import Adam
from spacy.attrs import NORM
from spacy.vocab import Vocab
from spacy import registry
from spacy.training import Example
from spacy.pipeline.dep_parser import DEFAULT_PARSER_MODEL
from spacy.tokens import Doc
from spacy.pipeline import DependencyParser


@pytest.fixture
def vocab():
    return Vocab(lex_attr_getters={NORM: lambda s: s})


def _parser_example(parser):
    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
    gold = {"heads": [1, 1, 3, 3], "deps": ["right", "ROOT", "left", "ROOT"]}
    return Example.from_dict(doc, gold)


@pytest.fixture
def parser(vocab):
    vocab.strings.add("ROOT")
    cfg = {"model": DEFAULT_PARSER_MODEL}
    model = registry.resolve(cfg, validate=True)["model"]
    parser = DependencyParser(vocab, model)
    parser.cfg["token_vector_width"] = 4
    parser.cfg["hidden_width"] = 32
    # parser.add_label('right')
    parser.add_label("left")
    parser.initialize(lambda: [_parser_example(parser)])
    sgd = Adam(0.001)

    for i in range(10):
        losses = {}
        doc = Doc(vocab, words=["a", "b", "c", "d"])
        example = Example.from_dict(
            doc, {"heads": [1, 1, 3, 3], "deps": ["left", "ROOT", "left", "ROOT"]}
        )
        parser.update([example], sgd=sgd, losses=losses)
    return parser


@pytest.mark.issue(7716)
@pytest.mark.xfail(reason="Not fixed yet")
def test_partial_annotation(parser):
    doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
    doc[2].is_sent_start = False
    # Note that if the following line is used, then doc[2].is_sent_start == False
    # doc[3].is_sent_start = False

    doc = parser(doc)
    assert doc[2].is_sent_start == False