create_transfer_learning_tuner: Creates a new "HyperParameterTuner" instance from the parent.

In DyfanJones/sagemaker-r-mlcore: sagemaker machine learning core classes and methods

Creates a new “HyperParameterTuner“ instance from the parent.

Description

It creates the new tuner by copying the request fields from the provided parent to the new instance of “HyperparameterTuner“ followed by addition of warm start configuration with the type as "TransferLearning" and “parents“ as the union of provided list of “additional_parents“ and the “parent“.

Usage

create_transfer_learning_tuner(
  parent,
  additional_parents = NULL,
  estimator = NULL,
  sagemaker_session = NULL
)

Arguments

parent	(str): Primary parent tuning job's name from which the Tuner and Estimator configuration has to be copied
additional_parents	(setstr): Set of additional parent tuning job's names along with the primary parent tuning job name to be used in warm starting the identical dataset and algorithm tuner.
estimator	(sagemaker.estimator.EstimatorBase): An estimator object that has been initialized with the desired configuration. There does not need to be a training job associated with this instance.
sagemaker_session	(sagemaker.session.Session): Session object which manages interactions with Amazon SageMaker APIs and any other AWS services needed. If not specified, one is created using the default AWS configuration chain.

Value

sagemaker.tuner.HyperparameterTuner: New instance of warm started HyperparameterTuner

DyfanJones/sagemaker-r-mlcore documentation built on May 3, 2022, 10:08 a.m.