gluonts.nursery.sagemaker_sdk.model module¶
-
class
gluonts.nursery.sagemaker_sdk.model.
GluonTSModel
(model_data, role, entry_point, image: str = None, framework_version: str = '0.4.1', predictor_cls=<class 'gluonts.nursery.sagemaker_sdk.model.GluonTSPredictor'>, model_server_workers: int = None, **kwargs)[source]¶ Bases:
sagemaker.model.FrameworkModel
An GluonTS SageMaker
Model
that can be deployed to a SageMakerEndpoint
.-
prepare_container_def
(instance_type, accelerator_type=None) → Dict[str, str][source]¶ Return a container definition with framework configuration set in model environment variables.
- Parameters
instance_type –
The EC2 instance type to deploy this Model to. Example:
'ml.c5.xlarge' # CPU, 'ml.p2.xlarge' # GPU.
accelerator_type –
The Elastic Inference accelerator type to deploy to the instance for loading and making inferences to the model. Example:
"ml.eia1.medium"
- Returns
A container definition object usable with the CreateModel API.
- Return type
Dict[str, str]
-
-
class
gluonts.nursery.sagemaker_sdk.model.
GluonTSPredictor
(endpoint_name: str, sagemaker_session: sagemaker.session.Session = None)[source]¶ Bases:
sagemaker.deprecations.DeprecatedClass
A RealTimePredictor for inference against GluonTS Endpoints. This is able to serialize and deserialize datasets in the gluonts data format.