def on_train_end(self, logs=None):
if self.stopped_epoch > 0:
logging.info('Epoch %05d: early stopping', self.stopped_epoch + 1)
try:
from cnn import semantic_similarity_layer, ranking_loss
from keras.models import load_model
self.model = load_model(self.model_path,
custom_objects={
'semantic_similarity_layer':
semantic_similarity_layer,
'ranking_loss': ranking_loss
})
except OSError:
pass
predict(self.conf,
self.concept,
self.positives,
self.vocab,
self.entity_model,
self.concept_model,
self.model,
self.val_data,
result=self.history)
if self.conf.getint('model', 'save'):
callback.save_model(self.model, self.conf['model']['path'],
self.now)
return
def on_train_end(self, logs=None):
if self.stopped_epoch > 0:
logger.info('Epoch %05d: early stopping', self.stopped_epoch + 1)
try:
self.original_model.load_weights(self.model_path)
logger.info('Best model reloaded.')
except OSError:
pass
predict(self.conf, self.concept, self.positives, self.vocab, self.entity_model, self.concept_model,self.original_model, self.val_data, result=self.history)
if self.conf.getint('model','save'):
callback.save_model(self.original_model, self.conf['model']['path'],self.now)
return