mirror of
				https://github.com/explosion/spaCy.git
				synced 2025-11-04 01:48:04 +03:00 
			
		
		
		
	
		
			
				
	
	
		
			117 lines
		
	
	
		
			3.7 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			117 lines
		
	
	
		
			3.7 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
# coding: utf-8
 | 
						|
from __future__ import unicode_literals
 | 
						|
 | 
						|
import pytest
 | 
						|
from spacy.pipeline import Tagger, DependencyParser, EntityRecognizer
 | 
						|
from spacy.pipeline import Tensorizer, TextCategorizer
 | 
						|
 | 
						|
from ..util import make_tempdir
 | 
						|
 | 
						|
 | 
						|
test_parsers = [DependencyParser, EntityRecognizer]
 | 
						|
 | 
						|
 | 
						|
@pytest.fixture
 | 
						|
def parser(en_vocab):
 | 
						|
    parser = DependencyParser(en_vocab)
 | 
						|
    parser.add_label("nsubj")
 | 
						|
    parser.model, cfg = parser.Model(parser.moves.n_moves)
 | 
						|
    parser.cfg.update(cfg)
 | 
						|
    return parser
 | 
						|
 | 
						|
 | 
						|
@pytest.fixture
 | 
						|
def blank_parser(en_vocab):
 | 
						|
    parser = DependencyParser(en_vocab)
 | 
						|
    return parser
 | 
						|
 | 
						|
 | 
						|
@pytest.fixture
 | 
						|
def taggers(en_vocab):
 | 
						|
    tagger1 = Tagger(en_vocab)
 | 
						|
    tagger2 = Tagger(en_vocab)
 | 
						|
    tagger1.model = tagger1.Model(8)
 | 
						|
    tagger2.model = tagger1.model
 | 
						|
    return (tagger1, tagger2)
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("Parser", test_parsers)
 | 
						|
def test_serialize_parser_roundtrip_bytes(en_vocab, Parser):
 | 
						|
    parser = Parser(en_vocab)
 | 
						|
    parser.model, _ = parser.Model(10)
 | 
						|
    new_parser = Parser(en_vocab)
 | 
						|
    new_parser.model, _ = new_parser.Model(10)
 | 
						|
    new_parser = new_parser.from_bytes(parser.to_bytes())
 | 
						|
    assert new_parser.to_bytes() == parser.to_bytes()
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.parametrize("Parser", test_parsers)
 | 
						|
def test_serialize_parser_roundtrip_disk(en_vocab, Parser):
 | 
						|
    parser = Parser(en_vocab)
 | 
						|
    parser.model, _ = parser.Model(0)
 | 
						|
    with make_tempdir() as d:
 | 
						|
        file_path = d / "parser"
 | 
						|
        parser.to_disk(file_path)
 | 
						|
        parser_d = Parser(en_vocab)
 | 
						|
        parser_d.model, _ = parser_d.Model(0)
 | 
						|
        parser_d = parser_d.from_disk(file_path)
 | 
						|
        assert parser.to_bytes(model=False) == parser_d.to_bytes(model=False)
 | 
						|
 | 
						|
 | 
						|
def test_to_from_bytes(parser, blank_parser):
 | 
						|
    assert parser.model is not True
 | 
						|
    assert blank_parser.model is True
 | 
						|
    assert blank_parser.moves.n_moves != parser.moves.n_moves
 | 
						|
    bytes_data = parser.to_bytes()
 | 
						|
    blank_parser.from_bytes(bytes_data)
 | 
						|
    assert blank_parser.model is not True
 | 
						|
    assert blank_parser.moves.n_moves == parser.moves.n_moves
 | 
						|
 | 
						|
 | 
						|
@pytest.mark.skip(
 | 
						|
    reason="This seems to be a dict ordering bug somewhere. Only failing on some platforms."
 | 
						|
)
 | 
						|
def test_serialize_tagger_roundtrip_bytes(en_vocab, taggers):
 | 
						|
    tagger1 = taggers[0]
 | 
						|
    tagger1_b = tagger1.to_bytes()
 | 
						|
    tagger1 = tagger1.from_bytes(tagger1_b)
 | 
						|
    assert tagger1.to_bytes() == tagger1_b
 | 
						|
    new_tagger1 = Tagger(en_vocab).from_bytes(tagger1_b)
 | 
						|
    assert new_tagger1.to_bytes() == tagger1_b
 | 
						|
 | 
						|
 | 
						|
def test_serialize_tagger_roundtrip_disk(en_vocab, taggers):
 | 
						|
    tagger1, tagger2 = taggers
 | 
						|
    with make_tempdir() as d:
 | 
						|
        file_path1 = d / "tagger1"
 | 
						|
        file_path2 = d / "tagger2"
 | 
						|
        tagger1.to_disk(file_path1)
 | 
						|
        tagger2.to_disk(file_path2)
 | 
						|
        tagger1_d = Tagger(en_vocab).from_disk(file_path1)
 | 
						|
        tagger2_d = Tagger(en_vocab).from_disk(file_path2)
 | 
						|
        assert tagger1_d.to_bytes() == tagger2_d.to_bytes()
 | 
						|
 | 
						|
 | 
						|
def test_serialize_tensorizer_roundtrip_bytes(en_vocab):
 | 
						|
    tensorizer = Tensorizer(en_vocab)
 | 
						|
    tensorizer.model = tensorizer.Model()
 | 
						|
    tensorizer_b = tensorizer.to_bytes()
 | 
						|
    new_tensorizer = Tensorizer(en_vocab).from_bytes(tensorizer_b)
 | 
						|
    assert new_tensorizer.to_bytes() == tensorizer_b
 | 
						|
 | 
						|
 | 
						|
def test_serialize_tensorizer_roundtrip_disk(en_vocab):
 | 
						|
    tensorizer = Tensorizer(en_vocab)
 | 
						|
    tensorizer.model = tensorizer.Model()
 | 
						|
    with make_tempdir() as d:
 | 
						|
        file_path = d / "tensorizer"
 | 
						|
        tensorizer.to_disk(file_path)
 | 
						|
        tensorizer_d = Tensorizer(en_vocab).from_disk(file_path)
 | 
						|
        assert tensorizer.to_bytes() == tensorizer_d.to_bytes()
 | 
						|
 | 
						|
 | 
						|
def test_serialize_textcat_empty(en_vocab):
 | 
						|
    # See issue #1105
 | 
						|
    textcat = TextCategorizer(en_vocab, labels=["ENTITY", "ACTION", "MODIFIER"])
 | 
						|
    textcat.to_bytes()
 |