def train_nfold(self, x_train, y_train, vocab_init=None):
self.models = train_folds(x_train, y_train, self.model_config,
self.training_config, self.embeddings)
if self.embeddings.use_ELMo:
self.embeddings.clean_ELMo_cache()
if self.embeddings.use_BERT:
self.embeddings.clean_BERT_cache()
def train_nfold(self, x_train, y_train, vocab_init=None, callbacks=None):
# bert models
if self.model_config.model_type.find("bert") != -1:
self.model = getModel(self.model_config, self.training_config)
self.model.processor = BERT_classifier_processor(labels=self.model_config.list_classes, x_train=x_train, y_train=y_train)
self.model.train()
return
self.models = train_folds(x_train, y_train, self.model_config, self.training_config, self.embeddings, callbacks=callbacks)
if self.embeddings.use_ELMo:
self.embeddings.clean_ELMo_cache()
if self.embeddings.use_BERT:
self.embeddings.clean_BERT_cache()
def train_nfold(self, x_train, y_train, vocab_init=None, callbacks=None):
self.models = train_folds(x_train, y_train, self.model_config, self.training_config, self.embeddings, callbacks=callbacks)