TimeSeriesEndpoint

class autogluon.cloud.TimeSeriesEndpoint(endpoint_name: str, session: Session | None = None)

High-level handle for an AutoGluon-Cloud time series endpoint.

Returned by autogluon.cloud.TimeSeriesCloudPredictor.deploy() and autogluon.cloud.TimeSeriesFoundationModel.deploy(). Construct it directly to attach to an existing endpoint by name.

• Trained predictor endpoints (TimeSeriesCloudPredictor.deploy()) use the prediction_length, quantile_levels, and target set at fit time, and reject requests that set them to different values.

• Foundation model endpoints (TimeSeriesFoundationModel.deploy()) read them from each request.

Parameters:

• endpoint_name (str) – Name of an existing SageMaker endpoint deployed through AutoGluon-Cloud, either with deploy() of a cloud predictor (e.g. autogluon.cloud.TabularCloudPredictor.deploy()) or of a foundation model (e.g. autogluon.cloud.TabularFoundationModel.deploy()).

• session (boto3.Session | None, default = None) – boto3.Session used to invoke and delete the endpoint. If None, the default ambient session is used.

Methods

delete_endpoint	Delete the endpoint along with the endpoint config and model created with it.
predict	Forecast the future values of data with the deployed endpoint.

Attributes

endpoint_name

Name of the SageMaker endpoint.