def do_train(config, component_builder=None):
# type: (RasaNLUConfig, Optional[ComponentBuilder]) -> Tuple[Trainer, Text]
"""Loads the trainer and the data and runs the training of the specified model."""
trainer = Trainer(config, component_builder)
persistor = create_persistor(config)
training_data = load_data(config['data'])
trainer.validate()
trainer.train(training_data)
persisted_path = trainer.persist(config['path'], persistor)
return trainer, persisted_path
def do_train(config):
# type: (RasaNLUConfig) -> (Trainer, str)
"""Loads the trainer and the data and runs the training of the specified model."""
trainer = Trainer(config)
persistor = create_persistor(config)
training_data = load_data(config['data'], config['language'], luis_data_tokenizer=config['luis_data_tokenizer'])
trainer.validate()
trainer.train(training_data)
persisted_path = trainer.persist(config['path'], persistor)
return trainer, persisted_path
def train(cfg_name, model_name):
from rasa_nlu.train import create_persistor
from rasa_nlu.converters import load_data
config = RasaNLUConfig(cfg_name)
trainer = Trainer(config)
training_data = load_data(config['data'], config['language'])
trainer.validate()
trainer.train(training_data)
persistor = create_persistor(config)
trainer.persist(os.path.join("test_models", model_name),
persistor,
create_unique_subfolder=False)