TrainingStep: Workflow TraingingStep class

In DyfanJones/sagemaker-r-workflow: sagemaker pipeline and workflows

Workflow TraingingStep class

Description

Training step for workflow.

Super classes

sagemaker.workflow::Entity -> sagemaker.workflow::Step -> sagemaker.workflow::ConfigurableRetryStep -> TrainingStep

Active bindings

arguments

The arguments dict that is used to call 'create_training_job'. NOTE: The CreateTrainingJob request is not quite the args list that workflow needs. The TrainingJobName and ExperimentConfig attributes cannot be included.

properties

A Properties object representing the DescribeTrainingJobResponse data model.

Methods

Public methods

• TrainingStep$new()

• TrainingStep$to_request()

• TrainingStep$clone()

Inherited methods

• sagemaker.workflow::Step$add_depends_on()

• sagemaker.workflow::Step$format()

• sagemaker.workflow::ConfigurableRetryStep$add_retry_policy()

---

Method new()

Construct a TrainingStep, given an 'EstimatorBase' instance. In addition to the estimator instance, the other arguments are those that are supplied to the 'fit' method of the 'sagemaker.estimator.Estimator'.

Usage

TrainingStep$new(
  name,
  estimator,
  display_name = NULL,
  description = NULL,
  inputs = NULL,
  cache_config = NULL,
  depends_on = NULL,
  retry_policies = NULL
)

Arguments

name

(str): The name of the training step.

estimator

(EstimatorBase): A 'sagemaker.estimator.EstimatorBase' instance.

display_name

(str): The display name of the training step.

description

(str): The description of the training step.

inputs

(str or dict or sagemaker.inputs.TrainingInput or sagemaker.inputs.FileSystemInput): Information about the training data. This can be one of three types:

• (str) the S3 location where training data is saved, or a file:// path in local mode.

• (dict[str, str] or dict[str, sagemaker.inputs.TrainingInput]) If using multiple channels for training data, you can specify a dict 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 as well as the path to the training dataset. See :func:'sagemaker.inputs.TrainingInput' for full details.

• (sagemaker.inputs.FileSystemInput) - channel configuration for a file system data source that can provide additional information as well as the path to the training dataset.

cache_config

(CacheConfig): A 'sagemaker.workflow.steps.CacheConfig' instance.

depends_on

(List[str]): A list of step names this 'sagemaker.workflow.steps.TrainingStep' depends on

retry_policies

(List[RetryPolicy]): A list of retry policy

---

Method to_request()

A Properties object representing the DescribeTrainingJobResponse data model.

Usage

TrainingStep$to_request()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

TrainingStep$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

DyfanJones/sagemaker-r-workflow documentation built on April 3, 2022, 11:28 p.m.