software.amazon.awscdk.services.stepfunctions.tasks

Class SagemakerTrainTask.Builder

java.lang.Object

software.amazon.awscdk.services.stepfunctions.tasks.SagemakerTrainTask.Builder

Enclosing class:

SagemakerTrainTask

@Stability(value=Experimental)
public static final class SagemakerTrainTask.Builder
extends Object

A fluent builder for SagemakerTrainTask.

Method Summary

Modifier and Type	Method and Description
SagemakerTrainTask.Builder	algorithmSpecification(AlgorithmSpecification algorithmSpecification) EXPERIMENTAL
SagemakerTrainTask	build()
static SagemakerTrainTask.Builder	create() EXPERIMENTAL
SagemakerTrainTask.Builder	hyperparameters(Map<String,Object> hyperparameters) EXPERIMENTAL
SagemakerTrainTask.Builder	inputDataConfig(List<Channel> inputDataConfig) EXPERIMENTAL
SagemakerTrainTask.Builder	integrationPattern(ServiceIntegrationPattern integrationPattern) EXPERIMENTAL
SagemakerTrainTask.Builder	outputDataConfig(OutputDataConfig outputDataConfig) EXPERIMENTAL
SagemakerTrainTask.Builder	resourceConfig(ResourceConfig resourceConfig) EXPERIMENTAL
SagemakerTrainTask.Builder	role(IRole role) EXPERIMENTAL
SagemakerTrainTask.Builder	stoppingCondition(StoppingCondition stoppingCondition) EXPERIMENTAL
SagemakerTrainTask.Builder	tags(Map<String,String> tags) EXPERIMENTAL
SagemakerTrainTask.Builder	trainingJobName(String trainingJobName) EXPERIMENTAL
SagemakerTrainTask.Builder	vpcConfig(VpcConfig vpcConfig) EXPERIMENTAL

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Detail

create

@Stability(value=Experimental)
public static SagemakerTrainTask.Builder create()

EXPERIMENTAL

Returns:

a new instance of SagemakerTrainTask.Builder.

algorithmSpecification

@Stability(value=Experimental)
public SagemakerTrainTask.Builder algorithmSpecification(AlgorithmSpecification algorithmSpecification)

EXPERIMENTAL

Parameters:

algorithmSpecification - Identifies the training algorithm to use. This parameter is required.

Returns:

this

inputDataConfig

@Stability(value=Experimental)
public SagemakerTrainTask.Builder inputDataConfig(List<Channel> inputDataConfig)

EXPERIMENTAL

Parameters:

inputDataConfig - Describes the various datasets (e.g. train, validation, test) and the Amazon S3 location where stored. This parameter is required.

Returns:

this

outputDataConfig

@Stability(value=Experimental)
public SagemakerTrainTask.Builder outputDataConfig(OutputDataConfig outputDataConfig)

EXPERIMENTAL

Parameters:

outputDataConfig - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training. This parameter is required.

Returns:

this

trainingJobName

@Stability(value=Experimental)
public SagemakerTrainTask.Builder trainingJobName(String trainingJobName)

EXPERIMENTAL

Parameters:

trainingJobName - Training Job Name. This parameter is required.

Returns:

this

hyperparameters

@Stability(value=Experimental)
public SagemakerTrainTask.Builder hyperparameters(Map<String,Object> hyperparameters)

EXPERIMENTAL

Parameters:

hyperparameters - Hyperparameters to be used for the train job. This parameter is required.

Returns:

this

integrationPattern

@Stability(value=Experimental)
public SagemakerTrainTask.Builder integrationPattern(ServiceIntegrationPattern integrationPattern)

EXPERIMENTAL

Parameters:

integrationPattern - The service integration pattern indicates different ways to call SageMaker APIs. This parameter is required.

Returns:

this

resourceConfig

@Stability(value=Experimental)
public SagemakerTrainTask.Builder resourceConfig(ResourceConfig resourceConfig)

EXPERIMENTAL

Parameters:

resourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. This parameter is required.

Returns:

this

role

@Stability(value=Experimental)
public SagemakerTrainTask.Builder role(IRole role)

EXPERIMENTAL

Parameters:

role - Role for the Training Job. This parameter is required.

Returns:

this

stoppingCondition

@Stability(value=Experimental)
public SagemakerTrainTask.Builder stoppingCondition(StoppingCondition stoppingCondition)

EXPERIMENTAL

Parameters:

stoppingCondition - Sets a time limit for training. This parameter is required.

Returns:

this

tags

@Stability(value=Experimental)
public SagemakerTrainTask.Builder tags(Map<String,String> tags)

EXPERIMENTAL

Parameters:

tags - Tags to be applied to the train job. This parameter is required.

Returns:

this

vpcConfig

@Stability(value=Experimental)
public SagemakerTrainTask.Builder vpcConfig(VpcConfig vpcConfig)

EXPERIMENTAL

Parameters:

vpcConfig - Specifies the VPC that you want your training job to connect to. This parameter is required.

Returns:

this

build

@Stability(value=Experimental)
public SagemakerTrainTask build()