spaCy/spacy/tests/parser/test_preset_sbd.py
Matthew Honnibal 6f5e308d17
Support negative examples in partial NER annotations (#8106)
* Support a cfg field in transition system

* Make NER 'has gold' check use right alignment for span

* Pass 'negative_samples_key' property into NER transition system

* Add field for negative samples to NER transition system

* Check neg_key in NER has_gold

* Support negative examples in NER oracle

* Test for negative examples in NER

* Fix name of config variable in NER

* Remove vestiges of old-style partial annotation

* Remove obsolete tests

* Add comment noting lack of support for negative samples in parser

* Additions to "neg examples" PR (#8201)

* add custom error and test for deprecated format

* add test for unlearning an entity

* add break also for Begin's cost

* add negative_samples_key property on Parser

* rename

* extend docs & fix some older docs issues

* add subclass constructors, clean up tests, fix docs

* add flaky test with ValueError if gold parse was not found

* remove ValueError if n_gold == 0

* fix docstring

* Hack in environment variables to try out training

* Remove hack

* Remove NER hack, and support 'negative O' samples

* Fix O oracle

* Fix transition parser

* Remove 'not O' from oracle

* Fix NER oracle

* check for spans in both gold.ents and gold.spans and raise if so, to prevent memory access violation

* use set instead of list in consistency check

Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2021-06-17 17:33:00 +10:00

88 lines
2.5 KiB
Python

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
def test_no_sentences(parser):
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
doc = parser(doc)
assert len(list(doc.sents)) >= 1
def test_sents_1(parser):
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
doc[2].sent_start = True
doc = parser(doc)
assert len(list(doc.sents)) >= 2
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
doc[1].sent_start = False
doc[2].sent_start = True
doc[3].sent_start = False
doc = parser(doc)
assert len(list(doc.sents)) == 2
def test_sents_1_2(parser):
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
doc[1].sent_start = True
doc[2].sent_start = True
doc = parser(doc)
assert len(list(doc.sents)) >= 3
def test_sents_1_3(parser):
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
doc[0].is_sent_start = True
doc[1].is_sent_start = True
doc[2].is_sent_start = None
doc[3].is_sent_start = True
doc = parser(doc)
assert len(list(doc.sents)) >= 3
doc = Doc(parser.vocab, words=["a", "b", "c", "d"])
doc[0].is_sent_start = True
doc[1].is_sent_start = True
doc[2].is_sent_start = False
doc[3].is_sent_start = True
doc = parser(doc)
assert len(list(doc.sents)) == 3