mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-14 13:47:13 +03:00
37 lines
907 B
Python
37 lines
907 B
Python
'''Test issue that arises when too many labels are added to NER model.'''
|
|
from __future__ import unicode_literals
|
|
|
|
import random
|
|
from ...lang.en import English
|
|
|
|
def train_model(train_data, entity_types):
|
|
nlp = English(pipeline=[])
|
|
|
|
ner = nlp.create_pipe("ner")
|
|
nlp.add_pipe(ner)
|
|
|
|
for entity_type in list(entity_types):
|
|
ner.add_label(entity_type)
|
|
|
|
optimizer = nlp.begin_training()
|
|
|
|
# Start training
|
|
for i in range(20):
|
|
losses = {}
|
|
index = 0
|
|
random.shuffle(train_data)
|
|
|
|
for statement, entities in train_data:
|
|
nlp.update([statement], [entities], sgd=optimizer, losses=losses, drop=0.5)
|
|
return nlp
|
|
|
|
|
|
def test_train_with_many_entity_types():
|
|
train_data = []
|
|
train_data.extend([("One sentence", {"entities": []})])
|
|
entity_types = [str(i) for i in range(1000)]
|
|
|
|
model = train_model(train_data, entity_types)
|
|
|
|
|