mirror of https://github.com/explosion/spaCy.git
69 lines
1.8 KiB
Python
69 lines
1.8 KiB
Python
from spacy.lang.en import English
|
|
from spacy.training import Example
|
|
from spacy.util import load_config_from_str
|
|
|
|
|
|
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.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 = "*"
|
|
"""
|
|
|
|
|
|
TRAIN_DATA = [
|
|
("I like green eggs", {"tags": ["N", "V", "J", "N"]}),
|
|
("Eat blue ham", {"tags": ["V", "J", "N"]}),
|
|
]
|
|
|
|
|
|
def test_issue7029():
|
|
"""Test that an empty document doesn't mess up an entire batch.
|
|
"""
|
|
nlp = English.from_config(load_config_from_str(CONFIG))
|
|
train_examples = []
|
|
for t in TRAIN_DATA:
|
|
train_examples.append(Example.from_dict(nlp.make_doc(t[0]), t[1]))
|
|
optimizer = nlp.initialize(get_examples=lambda: train_examples)
|
|
for i in range(50):
|
|
losses = {}
|
|
nlp.update(train_examples, sgd=optimizer, losses=losses)
|
|
texts = ["first", "second", "thrid", "fourth", "and", "then", "some", ""]
|
|
nlp.select_pipes(enable=["tok2vec", "tagger"])
|
|
docs1 = list(nlp.pipe(texts, batch_size=1))
|
|
docs2 = list(nlp.pipe(texts, batch_size=4))
|
|
assert [doc[0].tag_ for doc in docs1[:-1]] == [doc[0].tag_ for doc in docs2[:-1]]
|