mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-15 14:17:58 +03:00
fe0bae9159
* Cast to uint64 for all array-based doc representations
* Update images and versions in CI
* Temporarily test with prerelease numpy
* Convert specifically from int32 to uint64
* Use int32 in array tests
* Revert "Temporarily test with prerelease numpy"
This reverts commit 02f2cc7e29.
* Update remaining tests to use int32
55 lines
1.8 KiB
Python
55 lines
1.8 KiB
Python
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
import numpy
|
|
from spacy.attrs import HEAD, DEP
|
|
from spacy.symbols import nsubj, dobj, amod, nmod, conj, cc, root
|
|
from spacy.lang.en.syntax_iterators import SYNTAX_ITERATORS
|
|
|
|
import pytest
|
|
|
|
|
|
from ...util import get_doc
|
|
|
|
|
|
def test_noun_chunks_is_parsed(en_tokenizer):
|
|
"""Test that noun_chunks raises Value Error for 'en' language if Doc is not parsed.
|
|
To check this test, we're constructing a Doc
|
|
with a new Vocab here and forcing is_parsed to 'False'
|
|
to make sure the noun chunks don't run.
|
|
"""
|
|
doc = en_tokenizer("This is a sentence")
|
|
doc.is_parsed = False
|
|
with pytest.raises(ValueError):
|
|
list(doc.noun_chunks)
|
|
|
|
|
|
def test_en_noun_chunks_not_nested(en_vocab):
|
|
words = ["Peter", "has", "chronic", "command", "and", "control", "issues"]
|
|
heads = [1, 0, 4, 3, -1, -2, -5]
|
|
deps = ["nsubj", "ROOT", "amod", "nmod", "cc", "conj", "dobj"]
|
|
doc = get_doc(en_vocab, words=words, heads=heads, deps=deps)
|
|
doc.from_array(
|
|
[HEAD, DEP],
|
|
numpy.asarray(
|
|
[
|
|
[1, nsubj],
|
|
[0, root],
|
|
[4, amod],
|
|
[3, nmod],
|
|
[numpy.int32(-1).astype(numpy.uint64), cc],
|
|
[numpy.int32(-2).astype(numpy.uint64), conj],
|
|
[numpy.int32(-5).astype(numpy.uint64), dobj],
|
|
],
|
|
dtype="uint64",
|
|
),
|
|
)
|
|
doc.noun_chunks_iterator = SYNTAX_ITERATORS["noun_chunks"]
|
|
word_occurred = {}
|
|
for chunk in doc.noun_chunks:
|
|
for word in chunk:
|
|
word_occurred.setdefault(word.text, 0)
|
|
word_occurred[word.text] += 1
|
|
for word, freq in word_occurred.items():
|
|
assert freq == 1, (word, [chunk.text for chunk in doc.noun_chunks])
|