spaCy/spacy/tests/pipeline/test_pipe_methods.py
2019-09-29 17:32:12 +02:00

147 lines
4.3 KiB
Python

# coding: utf8
from __future__ import unicode_literals
import pytest
from spacy.language import Language
@pytest.fixture
def nlp():
return Language()
def new_pipe(doc):
return doc
def test_add_pipe_no_name(nlp):
nlp.add_pipe(new_pipe)
assert "new_pipe" in nlp.pipe_names
def test_add_pipe_duplicate_name(nlp):
nlp.add_pipe(new_pipe, name="duplicate_name")
with pytest.raises(ValueError):
nlp.add_pipe(new_pipe, name="duplicate_name")
@pytest.mark.parametrize("name", ["parser"])
def test_add_pipe_first(nlp, name):
nlp.add_pipe(new_pipe, name=name, first=True)
assert nlp.pipeline[0][0] == name
@pytest.mark.parametrize("name1,name2", [("parser", "lambda_pipe")])
def test_add_pipe_last(nlp, name1, name2):
nlp.add_pipe(lambda doc: doc, name=name2)
nlp.add_pipe(new_pipe, name=name1, last=True)
assert nlp.pipeline[0][0] != name1
assert nlp.pipeline[-1][0] == name1
def test_cant_add_pipe_first_and_last(nlp):
with pytest.raises(ValueError):
nlp.add_pipe(new_pipe, first=True, last=True)
@pytest.mark.parametrize("name", ["my_component"])
def test_get_pipe(nlp, name):
with pytest.raises(KeyError):
nlp.get_pipe(name)
nlp.add_pipe(new_pipe, name=name)
assert nlp.get_pipe(name) == new_pipe
@pytest.mark.parametrize(
"name,replacement,not_callable", [("my_component", lambda doc: doc, {})]
)
def test_replace_pipe(nlp, name, replacement, not_callable):
with pytest.raises(ValueError):
nlp.replace_pipe(name, new_pipe)
nlp.add_pipe(new_pipe, name=name)
with pytest.raises(ValueError):
nlp.replace_pipe(name, not_callable)
nlp.replace_pipe(name, replacement)
assert nlp.get_pipe(name) != new_pipe
assert nlp.get_pipe(name) == replacement
@pytest.mark.parametrize("old_name,new_name", [("old_pipe", "new_pipe")])
def test_rename_pipe(nlp, old_name, new_name):
with pytest.raises(ValueError):
nlp.rename_pipe(old_name, new_name)
nlp.add_pipe(new_pipe, name=old_name)
nlp.rename_pipe(old_name, new_name)
assert nlp.pipeline[0][0] == new_name
@pytest.mark.parametrize("name", ["my_component"])
def test_remove_pipe(nlp, name):
with pytest.raises(ValueError):
nlp.remove_pipe(name)
nlp.add_pipe(new_pipe, name=name)
assert len(nlp.pipeline) == 1
removed_name, removed_component = nlp.remove_pipe(name)
assert not len(nlp.pipeline)
assert removed_name == name
assert removed_component == new_pipe
@pytest.mark.parametrize("name", ["my_component"])
def test_disable_pipes_method(nlp, name):
nlp.add_pipe(new_pipe, name=name)
assert nlp.has_pipe(name)
disabled = nlp.disable_pipes(name)
assert not nlp.has_pipe(name)
disabled.restore()
@pytest.mark.parametrize("name", ["my_component"])
def test_disable_pipes_context(nlp, name):
nlp.add_pipe(new_pipe, name=name)
assert nlp.has_pipe(name)
with nlp.disable_pipes(name):
assert not nlp.has_pipe(name)
assert nlp.has_pipe(name)
@pytest.mark.parametrize("n_pipes", [100])
def test_add_lots_of_pipes(nlp, n_pipes):
for i in range(n_pipes):
nlp.add_pipe(lambda doc: doc, name="pipe_%d" % i)
assert len(nlp.pipe_names) == n_pipes
@pytest.mark.parametrize("component", ["ner", {"hello": "world"}])
def test_raise_for_invalid_components(nlp, component):
with pytest.raises(ValueError):
nlp.add_pipe(component)
@pytest.mark.parametrize("component", ["ner", "tagger", "parser", "textcat"])
def test_pipe_base_class_add_label(nlp, component):
label = "TEST"
pipe = nlp.create_pipe(component)
pipe.add_label(label)
if component == "tagger":
# Tagger always has the default coarse-grained label scheme
assert label in pipe.labels
else:
assert pipe.labels == (label,)
def test_pipe_labels(nlp):
input_labels = {
"ner": ["PERSON", "ORG", "GPE"],
"textcat": ["POSITIVE", "NEGATIVE"],
}
for name, labels in input_labels.items():
pipe = nlp.create_pipe(name)
for label in labels:
pipe.add_label(label)
assert len(pipe.labels) == len(labels)
nlp.add_pipe(pipe)
assert len(nlp.pipe_labels) == len(input_labels)
for name, labels in nlp.pipe_labels.items():
assert sorted(input_labels[name]) == sorted(labels)