apache_beam.ml.anomaly.detectors.offline module
- class apache_beam.ml.anomaly.detectors.offline.OfflineDetector(*args, **kwargs)[source]
Bases:
AnomalyDetectorA offline anomaly detector that uses a provided model handler for scoring.
- Parameters:
keyed_model_handler – The model handler to use for inference. Requires a KeyModelHandler[Any, Row, float, Any] instance.
run_inference_args – Optional arguments to pass to RunInference
**kwargs – Additional keyword arguments to pass to the base AnomalyDetector class.
- learn_one(x: Row) None[source]
Not implemented since OfflineDetector invokes RunInference directly.
- score_one(x: Row) float | None[source]
Not implemented since OfflineDetector invokes RunInference directly.
- OfflineDetector__spec_type = 'OfflineDetector'
- classmethod from_spec(spec: Spec, _run_init: bool = True) Self | type[Self]
Generate a Specifiable subclass object based on a spec.
- Parameters:
spec – the specification of a Specifiable subclass object
_run_init – whether to call __init__ or not for the initial instantiation
- Returns:
the Specifiable subclass object
- Return type:
Self
- run_original_init() None
Execute the original __init__ method with its saved arguments.
For instances of the Specifiable class, initialization is deferred (lazy initialization). This function forces the execution of the original __init__ method using the arguments captured during the object’s initial instantiation.
- classmethod spec_type()
- to_spec() Spec
Generate a spec from a Specifiable subclass object.
- Returns:
The specification of the instance.
- Return type:
- classmethod unspecifiable()