mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-10 19:57:17 +03:00
e2b70df012
* Use isort with Black profile * isort all the things * Fix import cycles as a result of import sorting * Add DOCBIN_ALL_ATTRS type definition * Add isort to requirements * Remove isort from build dependencies check * Typo
465 lines
16 KiB
Python
465 lines
16 KiB
Python
import pytest
|
|
from thinc.api import NumpyOps, get_current_ops
|
|
|
|
import spacy
|
|
from spacy import registry
|
|
from spacy.errors import MatchPatternError
|
|
from spacy.tests.util import make_tempdir
|
|
from spacy.tokens import Span
|
|
from spacy.training import Example
|
|
|
|
|
|
@pytest.fixture
|
|
@registry.misc("span_ruler_patterns")
|
|
def patterns():
|
|
return [
|
|
{"label": "HELLO", "pattern": "hello world", "id": "hello1"},
|
|
{"label": "BYE", "pattern": [{"LOWER": "bye"}, {"LOWER": "bye"}]},
|
|
{"label": "HELLO", "pattern": [{"ORTH": "HELLO"}], "id": "hello2"},
|
|
{"label": "COMPLEX", "pattern": [{"ORTH": "foo", "OP": "*"}]},
|
|
{"label": "TECH_ORG", "pattern": "Apple"},
|
|
{"label": "TECH_ORG", "pattern": "Microsoft"},
|
|
]
|
|
|
|
|
|
@pytest.fixture
|
|
def overlapping_patterns():
|
|
return [
|
|
{"label": "FOOBAR", "pattern": "foo bar"},
|
|
{"label": "BARBAZ", "pattern": "bar baz"},
|
|
]
|
|
|
|
|
|
@pytest.fixture
|
|
def person_org_patterns():
|
|
return [
|
|
{"label": "PERSON", "pattern": "Dina"},
|
|
{"label": "ORG", "pattern": "ACME"},
|
|
{"label": "ORG", "pattern": "ACM"},
|
|
]
|
|
|
|
|
|
@pytest.fixture
|
|
def person_org_date_patterns(person_org_patterns):
|
|
return person_org_patterns + [{"label": "DATE", "pattern": "June 14th"}]
|
|
|
|
|
|
def test_span_ruler_add_empty(patterns):
|
|
"""Test that patterns don't get added excessively."""
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler", config={"validate": True})
|
|
ruler.add_patterns(patterns)
|
|
pattern_count = sum(len(mm) for mm in ruler.matcher._patterns.values())
|
|
assert pattern_count > 0
|
|
ruler.add_patterns([])
|
|
after_count = sum(len(mm) for mm in ruler.matcher._patterns.values())
|
|
assert after_count == pattern_count
|
|
|
|
|
|
def test_span_ruler_init(patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(patterns)
|
|
assert len(ruler) == len(patterns)
|
|
assert len(ruler.labels) == 4
|
|
assert "HELLO" in ruler
|
|
assert "BYE" in ruler
|
|
doc = nlp("hello world bye bye")
|
|
assert len(doc.spans["ruler"]) == 2
|
|
assert doc.spans["ruler"][0].label_ == "HELLO"
|
|
assert doc.spans["ruler"][0].id_ == "hello1"
|
|
assert doc.spans["ruler"][1].label_ == "BYE"
|
|
assert doc.spans["ruler"][1].id_ == ""
|
|
|
|
|
|
def test_span_ruler_no_patterns_warns():
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
assert len(ruler) == 0
|
|
assert len(ruler.labels) == 0
|
|
assert nlp.pipe_names == ["span_ruler"]
|
|
with pytest.warns(UserWarning):
|
|
doc = nlp("hello world bye bye")
|
|
assert len(doc.spans["ruler"]) == 0
|
|
|
|
|
|
def test_span_ruler_init_patterns(patterns):
|
|
# initialize with patterns
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
assert len(ruler.labels) == 0
|
|
ruler.initialize(lambda: [], patterns=patterns)
|
|
assert len(ruler.labels) == 4
|
|
doc = nlp("hello world bye bye")
|
|
assert doc.spans["ruler"][0].label_ == "HELLO"
|
|
assert doc.spans["ruler"][1].label_ == "BYE"
|
|
nlp.remove_pipe("span_ruler")
|
|
# initialize with patterns from misc registry
|
|
nlp.config["initialize"]["components"]["span_ruler"] = {
|
|
"patterns": {"@misc": "span_ruler_patterns"}
|
|
}
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
assert len(ruler.labels) == 0
|
|
nlp.initialize()
|
|
assert len(ruler.labels) == 4
|
|
doc = nlp("hello world bye bye")
|
|
assert doc.spans["ruler"][0].label_ == "HELLO"
|
|
assert doc.spans["ruler"][1].label_ == "BYE"
|
|
|
|
|
|
def test_span_ruler_init_clear(patterns):
|
|
"""Test that initialization clears patterns."""
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(patterns)
|
|
assert len(ruler.labels) == 4
|
|
ruler.initialize(lambda: [])
|
|
assert len(ruler.labels) == 0
|
|
|
|
|
|
def test_span_ruler_clear(patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(patterns)
|
|
assert len(ruler.labels) == 4
|
|
doc = nlp("hello world")
|
|
assert len(doc.spans["ruler"]) == 1
|
|
ruler.clear()
|
|
assert len(ruler.labels) == 0
|
|
with pytest.warns(UserWarning):
|
|
doc = nlp("hello world")
|
|
assert len(doc.spans["ruler"]) == 0
|
|
|
|
|
|
def test_span_ruler_existing(patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler", config={"overwrite": False})
|
|
ruler.add_patterns(patterns)
|
|
doc = nlp.make_doc("OH HELLO WORLD bye bye")
|
|
doc.spans["ruler"] = [doc[0:2]]
|
|
doc = nlp(doc)
|
|
assert len(doc.spans["ruler"]) == 3
|
|
assert doc.spans["ruler"][0] == doc[0:2]
|
|
assert doc.spans["ruler"][1].label_ == "HELLO"
|
|
assert doc.spans["ruler"][1].id_ == "hello2"
|
|
assert doc.spans["ruler"][2].label_ == "BYE"
|
|
assert doc.spans["ruler"][2].id_ == ""
|
|
|
|
|
|
def test_span_ruler_existing_overwrite(patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler", config={"overwrite": True})
|
|
ruler.add_patterns(patterns)
|
|
doc = nlp.make_doc("OH HELLO WORLD bye bye")
|
|
doc.spans["ruler"] = [doc[0:2]]
|
|
doc = nlp(doc)
|
|
assert len(doc.spans["ruler"]) == 2
|
|
assert doc.spans["ruler"][0].label_ == "HELLO"
|
|
assert doc.spans["ruler"][0].text == "HELLO"
|
|
assert doc.spans["ruler"][1].label_ == "BYE"
|
|
|
|
|
|
def test_span_ruler_serialize_bytes(patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(patterns)
|
|
assert len(ruler) == len(patterns)
|
|
assert len(ruler.labels) == 4
|
|
ruler_bytes = ruler.to_bytes()
|
|
new_nlp = spacy.blank("xx")
|
|
new_ruler = new_nlp.add_pipe("span_ruler")
|
|
assert len(new_ruler) == 0
|
|
assert len(new_ruler.labels) == 0
|
|
new_ruler = new_ruler.from_bytes(ruler_bytes)
|
|
assert len(new_ruler) == len(patterns)
|
|
assert len(new_ruler.labels) == 4
|
|
assert len(new_ruler.patterns) == len(ruler.patterns)
|
|
for pattern in ruler.patterns:
|
|
assert pattern in new_ruler.patterns
|
|
assert sorted(new_ruler.labels) == sorted(ruler.labels)
|
|
|
|
|
|
def test_span_ruler_validate():
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
validated_ruler = nlp.add_pipe(
|
|
"span_ruler", name="validated_span_ruler", config={"validate": True}
|
|
)
|
|
|
|
valid_pattern = {"label": "HELLO", "pattern": [{"LOWER": "HELLO"}]}
|
|
invalid_pattern = {"label": "HELLO", "pattern": [{"ASDF": "HELLO"}]}
|
|
|
|
# invalid pattern raises error without validate
|
|
with pytest.raises(ValueError):
|
|
ruler.add_patterns([invalid_pattern])
|
|
|
|
# valid pattern is added without errors with validate
|
|
validated_ruler.add_patterns([valid_pattern])
|
|
|
|
# invalid pattern raises error with validate
|
|
with pytest.raises(MatchPatternError):
|
|
validated_ruler.add_patterns([invalid_pattern])
|
|
|
|
|
|
def test_span_ruler_properties(patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler", config={"overwrite": True})
|
|
ruler.add_patterns(patterns)
|
|
assert sorted(ruler.labels) == sorted(set([p["label"] for p in patterns]))
|
|
|
|
|
|
def test_span_ruler_overlapping_spans(overlapping_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(overlapping_patterns)
|
|
doc = ruler(nlp.make_doc("foo bar baz"))
|
|
assert len(doc.spans["ruler"]) == 2
|
|
assert doc.spans["ruler"][0].label_ == "FOOBAR"
|
|
assert doc.spans["ruler"][1].label_ == "BARBAZ"
|
|
|
|
|
|
def test_span_ruler_scorer(overlapping_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(overlapping_patterns)
|
|
text = "foo bar baz"
|
|
pred_doc = ruler(nlp.make_doc(text))
|
|
assert len(pred_doc.spans["ruler"]) == 2
|
|
assert pred_doc.spans["ruler"][0].label_ == "FOOBAR"
|
|
assert pred_doc.spans["ruler"][1].label_ == "BARBAZ"
|
|
|
|
ref_doc = nlp.make_doc(text)
|
|
ref_doc.spans["ruler"] = [Span(ref_doc, 0, 2, label="FOOBAR")]
|
|
scores = nlp.evaluate([Example(pred_doc, ref_doc)])
|
|
assert scores["spans_ruler_p"] == 0.5
|
|
assert scores["spans_ruler_r"] == 1.0
|
|
|
|
|
|
@pytest.mark.parametrize("n_process", [1, 2])
|
|
def test_span_ruler_multiprocessing(n_process):
|
|
if isinstance(get_current_ops, NumpyOps) or n_process < 2:
|
|
texts = ["I enjoy eating Pizza Hut pizza."]
|
|
|
|
patterns = [{"label": "FASTFOOD", "pattern": "Pizza Hut"}]
|
|
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(patterns)
|
|
|
|
for doc in nlp.pipe(texts, n_process=2):
|
|
for ent in doc.spans["ruler"]:
|
|
assert ent.label_ == "FASTFOOD"
|
|
|
|
|
|
def test_span_ruler_serialize_dir(patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(patterns)
|
|
with make_tempdir() as d:
|
|
ruler.to_disk(d / "test_ruler")
|
|
ruler.from_disk(d / "test_ruler") # read from an existing directory
|
|
with pytest.raises(ValueError):
|
|
ruler.from_disk(d / "non_existing_dir") # read from a bad directory
|
|
|
|
|
|
def test_span_ruler_remove_basic(person_org_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(person_org_patterns)
|
|
doc = ruler(nlp.make_doc("Dina went to school"))
|
|
assert len(ruler.patterns) == 3
|
|
assert len(doc.spans["ruler"]) == 1
|
|
assert doc.spans["ruler"][0].label_ == "PERSON"
|
|
assert doc.spans["ruler"][0].text == "Dina"
|
|
ruler.remove("PERSON")
|
|
doc = ruler(nlp.make_doc("Dina went to school"))
|
|
assert len(doc.spans["ruler"]) == 0
|
|
assert len(ruler.patterns) == 2
|
|
|
|
|
|
def test_span_ruler_remove_nonexisting_pattern(person_org_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(person_org_patterns)
|
|
assert len(ruler.patterns) == 3
|
|
with pytest.raises(ValueError):
|
|
ruler.remove("NE")
|
|
with pytest.raises(ValueError):
|
|
ruler.remove_by_id("NE")
|
|
|
|
|
|
def test_span_ruler_remove_several_patterns(person_org_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(person_org_patterns)
|
|
doc = ruler(nlp.make_doc("Dina founded the company ACME."))
|
|
assert len(ruler.patterns) == 3
|
|
assert len(doc.spans["ruler"]) == 2
|
|
assert doc.spans["ruler"][0].label_ == "PERSON"
|
|
assert doc.spans["ruler"][0].text == "Dina"
|
|
assert doc.spans["ruler"][1].label_ == "ORG"
|
|
assert doc.spans["ruler"][1].text == "ACME"
|
|
ruler.remove("PERSON")
|
|
doc = ruler(nlp.make_doc("Dina founded the company ACME"))
|
|
assert len(ruler.patterns) == 2
|
|
assert len(doc.spans["ruler"]) == 1
|
|
assert doc.spans["ruler"][0].label_ == "ORG"
|
|
assert doc.spans["ruler"][0].text == "ACME"
|
|
ruler.remove("ORG")
|
|
with pytest.warns(UserWarning):
|
|
doc = ruler(nlp.make_doc("Dina founded the company ACME"))
|
|
assert len(ruler.patterns) == 0
|
|
assert len(doc.spans["ruler"]) == 0
|
|
|
|
|
|
def test_span_ruler_remove_patterns_in_a_row(person_org_date_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(person_org_date_patterns)
|
|
doc = ruler(nlp.make_doc("Dina founded the company ACME on June 14th"))
|
|
assert len(doc.spans["ruler"]) == 3
|
|
assert doc.spans["ruler"][0].label_ == "PERSON"
|
|
assert doc.spans["ruler"][0].text == "Dina"
|
|
assert doc.spans["ruler"][1].label_ == "ORG"
|
|
assert doc.spans["ruler"][1].text == "ACME"
|
|
assert doc.spans["ruler"][2].label_ == "DATE"
|
|
assert doc.spans["ruler"][2].text == "June 14th"
|
|
ruler.remove("ORG")
|
|
ruler.remove("DATE")
|
|
doc = ruler(nlp.make_doc("Dina went to school"))
|
|
assert len(doc.spans["ruler"]) == 1
|
|
|
|
|
|
def test_span_ruler_remove_all_patterns(person_org_date_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
ruler.add_patterns(person_org_date_patterns)
|
|
assert len(ruler.patterns) == 4
|
|
ruler.remove("PERSON")
|
|
assert len(ruler.patterns) == 3
|
|
ruler.remove("ORG")
|
|
assert len(ruler.patterns) == 1
|
|
ruler.remove("DATE")
|
|
assert len(ruler.patterns) == 0
|
|
with pytest.warns(UserWarning):
|
|
doc = ruler(nlp.make_doc("Dina founded the company ACME on June 14th"))
|
|
assert len(doc.spans["ruler"]) == 0
|
|
|
|
|
|
def test_span_ruler_remove_and_add():
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler")
|
|
patterns1 = [{"label": "DATE1", "pattern": "last time"}]
|
|
ruler.add_patterns(patterns1)
|
|
doc = ruler(
|
|
nlp.make_doc("I saw him last time we met, this time he brought some flowers")
|
|
)
|
|
assert len(ruler.patterns) == 1
|
|
assert len(doc.spans["ruler"]) == 1
|
|
assert doc.spans["ruler"][0].label_ == "DATE1"
|
|
assert doc.spans["ruler"][0].text == "last time"
|
|
patterns2 = [{"label": "DATE2", "pattern": "this time"}]
|
|
ruler.add_patterns(patterns2)
|
|
doc = ruler(
|
|
nlp.make_doc("I saw him last time we met, this time he brought some flowers")
|
|
)
|
|
assert len(ruler.patterns) == 2
|
|
assert len(doc.spans["ruler"]) == 2
|
|
assert doc.spans["ruler"][0].label_ == "DATE1"
|
|
assert doc.spans["ruler"][0].text == "last time"
|
|
assert doc.spans["ruler"][1].label_ == "DATE2"
|
|
assert doc.spans["ruler"][1].text == "this time"
|
|
ruler.remove("DATE1")
|
|
doc = ruler(
|
|
nlp.make_doc("I saw him last time we met, this time he brought some flowers")
|
|
)
|
|
assert len(ruler.patterns) == 1
|
|
assert len(doc.spans["ruler"]) == 1
|
|
assert doc.spans["ruler"][0].label_ == "DATE2"
|
|
assert doc.spans["ruler"][0].text == "this time"
|
|
ruler.add_patterns(patterns1)
|
|
doc = ruler(
|
|
nlp.make_doc("I saw him last time we met, this time he brought some flowers")
|
|
)
|
|
assert len(ruler.patterns) == 2
|
|
assert len(doc.spans["ruler"]) == 2
|
|
patterns3 = [{"label": "DATE3", "pattern": "another time"}]
|
|
ruler.add_patterns(patterns3)
|
|
doc = ruler(
|
|
nlp.make_doc(
|
|
"I saw him last time we met, this time he brought some flowers, another time some chocolate."
|
|
)
|
|
)
|
|
assert len(ruler.patterns) == 3
|
|
assert len(doc.spans["ruler"]) == 3
|
|
ruler.remove("DATE3")
|
|
doc = ruler(
|
|
nlp.make_doc(
|
|
"I saw him last time we met, this time he brought some flowers, another time some chocolate."
|
|
)
|
|
)
|
|
assert len(ruler.patterns) == 2
|
|
assert len(doc.spans["ruler"]) == 2
|
|
|
|
|
|
def test_span_ruler_spans_filter(overlapping_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe(
|
|
"span_ruler",
|
|
config={"spans_filter": {"@misc": "spacy.first_longest_spans_filter.v1"}},
|
|
)
|
|
ruler.add_patterns(overlapping_patterns)
|
|
doc = ruler(nlp.make_doc("foo bar baz"))
|
|
assert len(doc.spans["ruler"]) == 1
|
|
assert doc.spans["ruler"][0].label_ == "FOOBAR"
|
|
|
|
|
|
def test_span_ruler_ents_default_filter(overlapping_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe("span_ruler", config={"annotate_ents": True})
|
|
ruler.add_patterns(overlapping_patterns)
|
|
doc = ruler(nlp.make_doc("foo bar baz"))
|
|
assert len(doc.ents) == 1
|
|
assert doc.ents[0].label_ == "FOOBAR"
|
|
|
|
|
|
def test_span_ruler_ents_overwrite_filter(overlapping_patterns):
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe(
|
|
"span_ruler",
|
|
config={
|
|
"annotate_ents": True,
|
|
"overwrite": False,
|
|
"ents_filter": {"@misc": "spacy.prioritize_new_ents_filter.v1"},
|
|
},
|
|
)
|
|
ruler.add_patterns(overlapping_patterns)
|
|
# overlapping ents are clobbered, non-overlapping ents are preserved
|
|
doc = nlp.make_doc("foo bar baz a b c")
|
|
doc.ents = [Span(doc, 1, 3, label="BARBAZ"), Span(doc, 3, 6, label="ABC")]
|
|
doc = ruler(doc)
|
|
assert len(doc.ents) == 2
|
|
assert doc.ents[0].label_ == "FOOBAR"
|
|
assert doc.ents[1].label_ == "ABC"
|
|
|
|
|
|
def test_span_ruler_ents_bad_filter(overlapping_patterns):
|
|
@registry.misc("test_pass_through_filter")
|
|
def make_pass_through_filter():
|
|
def pass_through_filter(spans1, spans2):
|
|
return spans1 + spans2
|
|
|
|
return pass_through_filter
|
|
|
|
nlp = spacy.blank("xx")
|
|
ruler = nlp.add_pipe(
|
|
"span_ruler",
|
|
config={
|
|
"annotate_ents": True,
|
|
"ents_filter": {"@misc": "test_pass_through_filter"},
|
|
},
|
|
)
|
|
ruler.add_patterns(overlapping_patterns)
|
|
with pytest.raises(ValueError):
|
|
ruler(nlp.make_doc("foo bar baz"))
|