spaCy/spacy/tests/regression/test_issue6950.py

60 lines
1.3 KiB
Python

from spacy.lang.en import English
from spacy.training import Example
from spacy.util import load_config_from_str
import pickle
CONFIG = """
[nlp]
lang = "en"
pipeline = ["tok2vec", "tagger"]
[components]
[components.tok2vec]
factory = "tok2vec"
[components.tok2vec.model]
@architectures = "spacy.Tok2Vec.v1"
[components.tok2vec.model.embed]
@architectures = "spacy.MultiHashEmbed.v1"
width = ${components.tok2vec.model.encode:width}
attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
rows = [5000,2500,2500,2500]
include_static_vectors = false
[components.tok2vec.model.encode]
@architectures = "spacy.MaxoutWindowEncoder.v1"
width = 96
depth = 4
window_size = 1
maxout_pieces = 3
[components.ner]
factory = "ner"
[components.tagger]
factory = "tagger"
[components.tagger.model]
@architectures = "spacy.Tagger.v1"
nO = null
[components.tagger.model.tok2vec]
@architectures = "spacy.Tok2VecListener.v1"
width = ${components.tok2vec.model.encode:width}
upstream = "*"
"""
def test_issue6950():
"""Test that the nlp object with initialized tok2vec with listeners pickles
correctly (and doesn't have lambdas).
"""
nlp = English.from_config(load_config_from_str(CONFIG))
nlp.initialize(lambda: [Example.from_dict(nlp.make_doc("hello"), {"tags": ["V"]})])
pickle.dumps(nlp)
nlp("hello")
pickle.dumps(nlp)