Sagemaker TuningStep task class

Creates a Task State to execute a SageMaker HyperParameterTuning Job.

Super classes

stepfunctions::Block -> stepfunctions::State -> stepfunctions::Task -> TuningStep

Methods

Public methods

• TuningStep$new()

• TuningStep$clone()

Inherited methods

• stepfunctions::Block$is_field_allowed()

• stepfunctions::Block$to_json()

• stepfunctions::State$.next()

• stepfunctions::State$accept()

• stepfunctions::State$add_catch()

• stepfunctions::State$add_retry()

• stepfunctions::State$format()

• stepfunctions::State$output()

• stepfunctions::State$to_list()

• stepfunctions::State$update_parameters()

• stepfunctions::Task$allowed_fields()

---

Method new()

Initialize TuningStep class

Usage

TuningStep$new(
  state_id,
  tuner,
  job_name,
  data,
  wait_for_completion = TRUE,
  tags = NULL,
  ...
)

Arguments

state_id

(str): State name whose length **must be** less than or equal to 128 unicode characters. State names **must be** unique within the scope of the whole state machine.

tuner

(sagemaker.tuner.HyperparameterTuner): The tuner to use in the TuningStep.

job_name

(str or Placeholder): Specify a tuning job name. We recommend to use :py:class:`~stepfunctions.inputs.ExecutionInput` placeholder collection to pass the value dynamically in each execution.

data

: Information about the training data. Please refer to the ``fit()`` method of the associated estimator in the tuner, as this can take any of the following forms:

• (str) - The S3 location where training data is saved.

• (list[str, str] or list[str, sagemaker.inputs.TrainingInput]) - If using multiple channels for training data, you can specify a list mapping channel names to strings or :func:`~sagemaker.inputs.TrainingInput` objects.

• (sagemaker.inputs.TrainingInput) - Channel configuration for S3 data sources that can provide additional information about the training dataset. See :func:`sagemaker.inputs.TrainingInput` for full details.

• (sagemaker.amazon.amazon_estimator.RecordSet) - A collection of Amazon :class:`Record` objects serialized and stored in S3. For use with an estimator for an Amazon algorithm.

• (list[sagemaker.amazon.amazon_estimator.RecordSet]) - A list of :class:`sagemaker.amazon.amazon_estimator.RecordSet` objects, where each instance is a different channel of training data.

wait_for_completion

(bool, optional): Boolean value set to `True` if the Task state should wait for the tuning job to complete before proceeding to the next step in the workflow. Set to `False` if the Task state should submit the tuning job and proceed to the next step. (default: True)

tags

(list[list], optional): List to tags https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html to associate with the resource.

...

: Extra Fields passed to Task class

---

Method clone()

The objects of this class are cloneable with this method.

Usage

TuningStep$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.