mirror of https://github.com/explosion/spaCy.git
115 lines
3.7 KiB
Python
115 lines
3.7 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import pytest
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from spacy.pipeline import Tagger, DependencyParser, EntityRecognizer, Tensorizer, TextCategorizer
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from ..util import make_tempdir
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test_parsers = [DependencyParser, EntityRecognizer]
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@pytest.fixture
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def parser(en_vocab):
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parser = DependencyParser(en_vocab)
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parser.add_label('nsubj')
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parser.model, cfg = parser.Model(parser.moves.n_moves)
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parser.cfg.update(cfg)
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return parser
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@pytest.fixture
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def blank_parser(en_vocab):
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parser = DependencyParser(en_vocab)
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return parser
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@pytest.fixture
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def taggers(en_vocab):
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tagger1 = Tagger(en_vocab)
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tagger2 = Tagger(en_vocab)
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tagger1.model = tagger1.Model(8)
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tagger2.model = tagger1.model
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return (tagger1, tagger2)
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@pytest.mark.parametrize('Parser', test_parsers)
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def test_serialize_parser_roundtrip_bytes(en_vocab, Parser):
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parser = Parser(en_vocab)
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parser.model, _ = parser.Model(10)
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new_parser = Parser(en_vocab)
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new_parser.model, _ = new_parser.Model(10)
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new_parser = new_parser.from_bytes(parser.to_bytes())
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assert new_parser.to_bytes() == parser.to_bytes()
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@pytest.mark.parametrize('Parser', test_parsers)
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def test_serialize_parser_roundtrip_disk(en_vocab, Parser):
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parser = Parser(en_vocab)
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parser.model, _ = parser.Model(0)
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with make_tempdir() as d:
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file_path = d / 'parser'
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parser.to_disk(file_path)
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parser_d = Parser(en_vocab)
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parser_d.model, _ = parser_d.Model(0)
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parser_d = parser_d.from_disk(file_path)
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assert parser.to_bytes(model=False) == parser_d.to_bytes(model=False)
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def test_to_from_bytes(parser, blank_parser):
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assert parser.model is not True
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assert blank_parser.model is True
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assert blank_parser.moves.n_moves != parser.moves.n_moves
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bytes_data = parser.to_bytes()
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blank_parser.from_bytes(bytes_data)
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assert blank_parser.model is not True
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assert blank_parser.moves.n_moves == parser.moves.n_moves
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@pytest.mark.skip(reason="This seems to be a dict ordering bug somewhere. Only failing on some platforms.")
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def test_serialize_tagger_roundtrip_bytes(en_vocab, taggers):
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tagger1, tagger2 = taggers
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tagger1_b = tagger1.to_bytes()
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tagger2_b = tagger2.to_bytes()
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tagger1 = tagger1.from_bytes(tagger1_b)
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assert tagger1.to_bytes() == tagger1_b
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new_tagger1 = Tagger(en_vocab).from_bytes(tagger1_b)
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assert new_tagger1.to_bytes() == tagger1_b
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def test_serialize_tagger_roundtrip_disk(en_vocab, taggers):
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tagger1, tagger2 = taggers
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with make_tempdir() as d:
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file_path1 = d / 'tagger1'
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file_path2 = d / 'tagger2'
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tagger1.to_disk(file_path1)
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tagger2.to_disk(file_path2)
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tagger1_d = Tagger(en_vocab).from_disk(file_path1)
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tagger2_d = Tagger(en_vocab).from_disk(file_path2)
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assert tagger1_d.to_bytes() == tagger2_d.to_bytes()
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def test_serialize_tensorizer_roundtrip_bytes(en_vocab):
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tensorizer = Tensorizer(en_vocab)
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tensorizer.model = tensorizer.Model()
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tensorizer_b = tensorizer.to_bytes()
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new_tensorizer = Tensorizer(en_vocab).from_bytes(tensorizer_b)
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assert new_tensorizer.to_bytes() == tensorizer_b
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def test_serialize_tensorizer_roundtrip_disk(en_vocab):
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tensorizer = Tensorizer(en_vocab)
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tensorizer.model = tensorizer.Model()
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with make_tempdir() as d:
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file_path = d / 'tensorizer'
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tensorizer.to_disk(file_path)
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tensorizer_d = Tensorizer(en_vocab).from_disk(file_path)
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assert tensorizer.to_bytes() == tensorizer_d.to_bytes()
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def test_serialize_textcat_empty(en_vocab):
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# See issue #1105
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textcat = TextCategorizer(en_vocab, labels=['ENTITY', 'ACTION', 'MODIFIER'])
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textcat_bytes = textcat.to_bytes()
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