spaCy/spacy/tests/test_misc.py
2017-05-29 12:26:02 +02:00

94 lines
3.2 KiB
Python

# coding: utf-8
from __future__ import unicode_literals
from ..util import ensure_path
from ..util import model_to_bytes, model_from_bytes
from .. import util
from ..displacy import parse_deps, parse_ents
from ..tokens import Span
from .util import get_doc
from pathlib import Path
import pytest
from thinc.neural import Maxout, Softmax
from thinc.api import chain
@pytest.mark.parametrize('text', ['hello/world', 'hello world'])
def test_util_ensure_path_succeeds(text):
path = util.ensure_path(text)
assert isinstance(path, Path)
def test_simple_model_roundtrip_bytes():
model = Maxout(5, 10, pieces=2)
model.b += 1
data = model_to_bytes(model)
model.b -= 1
model_from_bytes(model, data)
assert model.b[0, 0] == 1
def test_multi_model_roundtrip_bytes():
model = chain(Maxout(5, 10, pieces=2), Maxout(2, 3))
model._layers[0].b += 1
model._layers[1].b += 2
data = model_to_bytes(model)
model._layers[0].b -= 1
model._layers[1].b -= 2
model_from_bytes(model, data)
assert model._layers[0].b[0, 0] == 1
assert model._layers[1].b[0, 0] == 2
def test_multi_model_load_missing_dims():
model = chain(Maxout(5, 10, pieces=2), Maxout(2, 3))
model._layers[0].b += 1
model._layers[1].b += 2
data = model_to_bytes(model)
model2 = chain(Maxout(5), Maxout())
model_from_bytes(model2, data)
assert model2._layers[0].b[0, 0] == 1
assert model2._layers[1].b[0, 0] == 2
@pytest.mark.parametrize('package', ['thinc'])
def test_util_is_package(package):
"""Test that an installed package via pip is recognised by util.is_package."""
assert util.is_package(package)
@pytest.mark.parametrize('package', ['thinc'])
def test_util_get_package_path(package):
"""Test that a Path object is returned for a package name."""
path = util.get_package_path(package)
assert isinstance(path, Path)
def test_displacy_parse_ents(en_vocab):
"""Test that named entities on a Doc are converted into displaCy's format."""
doc = get_doc(en_vocab, words=["But", "Google", "is", "starting", "from", "behind"])
doc.ents = [Span(doc, 1, 2, label=doc.vocab.strings[u'ORG'])]
ents = parse_ents(doc)
assert isinstance(ents, dict)
assert ents['text'] == 'But Google is starting from behind '
assert ents['ents'] == [{'start': 4, 'end': 10, 'label': 'ORG'}]
def test_displacy_parse_deps(en_vocab):
"""Test that deps and tags on a Doc are converted into displaCy's format."""
words = ["This", "is", "a", "sentence"]
heads = [1, 0, 1, -2]
tags = ['DT', 'VBZ', 'DT', 'NN']
deps = ['nsubj', 'ROOT', 'det', 'attr']
doc = get_doc(en_vocab, words=words, heads=heads, tags=tags, deps=deps)
deps = parse_deps(doc)
assert isinstance(deps, dict)
assert deps['words'] == [{'text': 'This', 'tag': 'DT'},
{'text': 'is', 'tag': 'VBZ'},
{'text': 'a', 'tag': 'DT'},
{'text': 'sentence', 'tag': 'NN'}]
assert deps['arcs'] == [{'start': 0, 'end': 1, 'label': 'nsubj', 'dir': 'left'},
{'start': 2, 'end': 3, 'label': 'det', 'dir': 'left'},
{'start': 1, 'end': 3, 'label': 'attr', 'dir': 'right'}]