notice
This is documentation for Rasa Open Source Documentation v2.0.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (2.3.x).
Version: 2.0.x
rasa.train
train_async
async train_async(domain: Union[Domain, Text], config: Text, training_files: Optional[Union[Text, List[Text]]], output_path: Text = DEFAULT_MODELS_PATH, force_training: bool = False, fixed_model_name: Optional[Text] = None, persist_nlu_training_data: bool = False, core_additional_arguments: Optional[Dict] = None, nlu_additional_arguments: Optional[Dict] = None) -> Optional[Text]
Trains a Rasa model (Core and NLU).
Arguments:
domain
- Path to the domain file.config
- Path to the config for Core and NLU.training_files
- Paths to the training data for Core and NLU.output_path
- Output path.force_training
- IfTrue
retrain model even if data has not changed.fixed_model_name
- Name of model to be stored.persist_nlu_training_data
-True
if the NLU training data should be persisted with the model.core_additional_arguments
- Additional training parameters for core training.nlu_additional_arguments
- Additional training parameters forwarded to training method of each NLU component.
Returns:
Path of the trained model archive.
train_core_async
async train_core_async(domain: Union[Domain, Text], config: Text, stories: Text, output: Text, train_path: Optional[Text] = None, fixed_model_name: Optional[Text] = None, additional_arguments: Optional[Dict] = None) -> Optional[Text]
Trains a Core model.
Arguments:
domain
- Path to the domain file.config
- Path to the config file for Core.stories
- Path to the Core training data.output
- Output path.train_path
- IfNone
the model will be trained in a temporary directory, otherwise in the provided directory.fixed_model_name
- Name of model to be stored.additional_arguments
- Additional training parameters.
Returns:
If train_path
is given it returns the path to the model archive,
otherwise the path to the directory with the trained model files.
train_nlu
train_nlu(config: Text, nlu_data: Text, output: Text, train_path: Optional[Text] = None, fixed_model_name: Optional[Text] = None, persist_nlu_training_data: bool = False, additional_arguments: Optional[Dict] = None, domain: Optional[Union[Domain, Text]] = None) -> Optional[Text]
Trains an NLU model.
Arguments:
config
- Path to the config file for NLU.nlu_data
- Path to the NLU training data.output
- Output path.train_path
- IfNone
the model will be trained in a temporary directory, otherwise in the provided directory.fixed_model_name
- Name of the model to be stored.persist_nlu_training_data
-True
if the NLU training data should be persisted with the model.additional_arguments
- Additional training parameters which will be passed to thetrain
method of each component.domain
- Path to the optional domain file/Domain object.
Returns:
If train_path
is given it returns the path to the model archive,
otherwise the path to the directory with the trained model files.