mirror of
https://github.com/explosion/spaCy.git
synced 2024-09-21 19:39:13 +03:00
108 lines
3.3 KiB
Python
108 lines
3.3 KiB
Python
# coding: utf-8
|
|
from __future__ import unicode_literals
|
|
|
|
from ..tokens import Doc
|
|
from ..attrs import ORTH, POS, HEAD, DEP
|
|
from ..compat import path2str
|
|
|
|
import pytest
|
|
import numpy
|
|
import tempfile
|
|
import shutil
|
|
import contextlib
|
|
from pathlib import Path
|
|
|
|
|
|
MODELS = {}
|
|
|
|
|
|
def load_test_model(model):
|
|
"""Load a model if it's installed as a package, otherwise skip."""
|
|
if model not in MODELS:
|
|
module = pytest.importorskip(model)
|
|
MODELS[model] = module.load()
|
|
return MODELS[model]
|
|
|
|
|
|
@contextlib.contextmanager
|
|
def make_tempfile(mode='r'):
|
|
f = tempfile.TemporaryFile(mode=mode)
|
|
yield f
|
|
f.close()
|
|
|
|
|
|
@contextlib.contextmanager
|
|
def make_tempdir():
|
|
d = Path(tempfile.mkdtemp())
|
|
yield d
|
|
shutil.rmtree(path2str(d))
|
|
|
|
|
|
def get_doc(vocab, words=[], pos=None, heads=None, deps=None, tags=None, ents=None):
|
|
"""Create Doc object from given vocab, words and annotations."""
|
|
pos = pos or [''] * len(words)
|
|
tags = tags or [''] * len(words)
|
|
heads = heads or [0] * len(words)
|
|
deps = deps or [''] * len(words)
|
|
for value in (deps+tags+pos):
|
|
vocab.strings.add(value)
|
|
|
|
doc = Doc(vocab, words=words)
|
|
attrs = doc.to_array([POS, HEAD, DEP])
|
|
for i, (p, head, dep) in enumerate(zip(pos, heads, deps)):
|
|
attrs[i, 0] = doc.vocab.strings[p]
|
|
attrs[i, 1] = head
|
|
attrs[i, 2] = doc.vocab.strings[dep]
|
|
doc.from_array([POS, HEAD, DEP], attrs)
|
|
if ents:
|
|
doc.ents = [(ent_id, doc.vocab.strings[label], start, end) for ent_id, label, start, end in ents]
|
|
if tags:
|
|
for token in doc:
|
|
token.tag_ = tags[token.i]
|
|
return doc
|
|
|
|
|
|
def apply_transition_sequence(parser, doc, sequence):
|
|
"""Perform a series of pre-specified transitions, to put the parser in a
|
|
desired state."""
|
|
for action_name in sequence:
|
|
if '-' in action_name:
|
|
move, label = action_name.split('-')
|
|
parser.add_label(label)
|
|
with parser.step_through(doc) as stepwise:
|
|
for transition in sequence:
|
|
stepwise.transition(transition)
|
|
|
|
|
|
def add_vecs_to_vocab(vocab, vectors):
|
|
"""Add list of vector tuples to given vocab. All vectors need to have the
|
|
same length. Format: [("text", [1, 2, 3])]"""
|
|
length = len(vectors[0][1])
|
|
vocab.resize_vectors(length)
|
|
for word, vec in vectors:
|
|
vocab[word].vector = vec
|
|
return vocab
|
|
|
|
|
|
def get_cosine(vec1, vec2):
|
|
"""Get cosine for two given vectors"""
|
|
return numpy.dot(vec1, vec2) / (numpy.linalg.norm(vec1) * numpy.linalg.norm(vec2))
|
|
|
|
|
|
def assert_docs_equal(doc1, doc2):
|
|
"""Compare two Doc objects and assert that they're equal. Tests for tokens,
|
|
tags, dependencies and entities."""
|
|
assert [ t.orth for t in doc1 ] == [ t.orth for t in doc2 ]
|
|
|
|
assert [ t.pos for t in doc1 ] == [ t.pos for t in doc2 ]
|
|
assert [ t.tag for t in doc1 ] == [ t.tag for t in doc2 ]
|
|
|
|
assert [ t.head.i for t in doc1 ] == [ t.head.i for t in doc2 ]
|
|
assert [ t.dep for t in doc1 ] == [ t.dep for t in doc2 ]
|
|
if doc1.is_parsed and doc2.is_parsed:
|
|
assert [ s for s in doc1.sents ] == [ s for s in doc2.sents ]
|
|
|
|
assert [ t.ent_type for t in doc1 ] == [ t.ent_type for t in doc2 ]
|
|
assert [ t.ent_iob for t in doc1 ] == [ t.ent_iob for t in doc2 ]
|
|
assert [ ent for ent in doc1.ents ] == [ ent for ent in doc2.ents ]
|