Feature store's built-in steps

Feature store's built-in steps#

A step runs a function or class handler or a REST API call: MLRun comes with pre-built steps that include data manipulation, readers, writers and model serving. All steps are supported by the storey engine.

See full details on built-in steps in Building graphs.

Class name

Description

EnrichmentModelRouter

Auto enrich the request with data from the feature store. The router input accepts a list of inference requests (each request can be a dict or a list of incoming features/keys). It enriches the request with data from the specified feature vector (feature_vector_uri).

EnrichmentVotingEnsemble

Auto enrich the request with data from the feature store. The router input accepts a list of inference requests (each request can be a dict or a list of incoming features/keys). It enriches the request with data from the specified feature vector (feature_vector_uri).

FeaturesetValidator

Validate feature values according to the feature set validation policy. Supported also by the Pandas engines.