Update NER training example

This commit is contained in:
Matthew Honnibal 2017-01-27 12:27:10 +01:00
parent 63adcb8141
commit ab70f6e18d

View File

@ -8,6 +8,12 @@ from spacy.pipeline import EntityRecognizer
from spacy.gold import GoldParse
from spacy.tagger import Tagger
try:
unicode
except:
unicode = str
def train_ner(nlp, train_data, entity_types):
# Add new words to vocab.
@ -24,7 +30,6 @@ def train_ner(nlp, train_data, entity_types):
doc = nlp.make_doc(raw_text)
gold = GoldParse(doc, entities=entity_offsets)
ner.update(doc, gold)
ner.model.end_training()
return ner
def save_model(ner, model_dir):
@ -33,8 +38,11 @@ def save_model(ner, model_dir):
model_dir.mkdir()
assert model_dir.is_dir()
with (model_dir / 'config.json').open('w') as file_:
json.dump(ner.cfg, file_)
with (model_dir / 'config.json').open('wb') as file_:
data = json.dumps(ner.cfg)
if isinstance(data, unicode):
data = data.encode('utf8')
file_.write(data)
ner.model.dump(str(model_dir / 'model'))
if not (model_dir / 'vocab').exists():
(model_dir / 'vocab').mkdir()