caikit.runtime.servicers.global_train_servicer
Attributes
Classes
Something something about the train servicer |
Module Contents
- caikit.runtime.servicers.global_train_servicer.error
- caikit.runtime.servicers.global_train_servicer.NON_PRIMITIVE_TYPES
- class caikit.runtime.servicers.global_train_servicer.GlobalTrainServicer(training_service: caikit.runtime.service_factory.ServicePackage)[source]
Something something about the train servicer
- _training_service
- _model_manager = None
- cdm
- library
- property training_output_dir: str
- property save_with_id: str
- Train(request: google.protobuf.message.Message, context: grpc.ServicerContext, *_, **__) caikit.interfaces.runtime.data_model.TrainingJob[source]
Global train RPC – Mocks the invocation of a Caikit Library module.train() method for a loaded Caikit Library model
- Args:
request (object): A deserialized RPC request message context (ServicerContext): Context object (contains request metadata, etc)
- Returns:
- caikit.interfaces.runtime.data_model.TrainingJob:
A TrainingJob data model response object
- run_training_job(request: google.protobuf.message.Message, module: Type[caikit.core.ModuleBase], training_output_dir: str | None = None, *, context: grpc.ServicerContext | None = None, wait: bool = False, **kwargs) caikit.interfaces.runtime.data_model.TrainingJob[source]
Builds the request dict for calling the train function asynchronously, then returns the thread id
- Args:
request (ProtoMessageType): The message that stimulated this request module (Type[ModuleBase]): The module class to train training_output_dir (Optional[str]): The base directory where
the trained model should be saved, falling back to the configured output dir if not given.
- Kwargs:
- context (Optional[ServicerContext]): The grpc context for the
request if called from a grpc handler
wait (bool): Whether or not to block until the training is complete
- Returns:
- training_job (TrainingJob): The job handle for the training with the
job’s ID and the model’s name