TimeSeriesEndpoint¶

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

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 and its backing model + endpoint config.
`predict`	Run real-time prediction on the deployed endpoint.

Attributes

endpoint_name