software.amazon.awscdk.services.stepfunctions.tasks

Interface SagemakerTransformProps

All Superinterfaces:

software.amazon.jsii.JsiiSerializable

All Known Implementing Classes:

SagemakerTransformProps.Jsii$Proxy

@Generated(value="jsii-pacmak/0.20.6 (build 17f281e)",
           date="2019-11-19T17:18:14.536Z")
 @Stability(value=Experimental)
public interface SagemakerTransformProps
extends software.amazon.jsii.JsiiSerializable

EXPERIMENTAL

Nested Class Summary

Nested Classes

Modifier and Type	Interface and Description
static class	SagemakerTransformProps.Builder A builder for SagemakerTransformProps
static class	SagemakerTransformProps.Jsii$Proxy An implementation for SagemakerTransformProps

Method Summary

Modifier and Type	Method and Description
static SagemakerTransformProps.Builder	builder()
default BatchStrategy	getBatchStrategy() Number of records to include in a mini-batch for an HTTP inference request.
default Map<String,String>	getEnvironment() Environment variables to set in the Docker container.
default ServiceIntegrationPattern	getIntegrationPattern() The service integration pattern indicates different ways to call SageMaker APIs.
default Number	getMaxConcurrentTransforms() Maximum number of parallel requests that can be sent to each instance in a transform job.
default Number	getMaxPayloadInMb() Maximum allowed size of the payload, in MB.
String	getModelName() Name of the model that you want to use for the transform job.
default IRole	getRole() Role for thte Training Job.
default Map<String,String>	getTags() Tags to be applied to the train job.
TransformInput	getTransformInput() Dataset to be transformed and the Amazon S3 location where it is stored.
String	getTransformJobName() Training Job Name.
TransformOutput	getTransformOutput() S3 location where you want Amazon SageMaker to save the results from the transform job.
default TransformResources	getTransformResources() ML compute instances for the transform job.

Methods inherited from interface software.amazon.jsii.JsiiSerializable

$jsii$toJson

Method Detail

getModelName

@Stability(value=Experimental)
String getModelName()

Name of the model that you want to use for the transform job. EXPERIMENTAL

getTransformInput

@Stability(value=Experimental)
TransformInput getTransformInput()

Dataset to be transformed and the Amazon S3 location where it is stored. EXPERIMENTAL

getTransformJobName

@Stability(value=Experimental)
String getTransformJobName()

Training Job Name. EXPERIMENTAL

getTransformOutput

@Stability(value=Experimental)
TransformOutput getTransformOutput()

S3 location where you want Amazon SageMaker to save the results from the transform job. EXPERIMENTAL

getBatchStrategy

@Stability(value=Experimental)
default BatchStrategy getBatchStrategy()

Number of records to include in a mini-batch for an HTTP inference request. EXPERIMENTAL

getEnvironment

@Stability(value=Experimental)
default Map<String,String> getEnvironment()

Environment variables to set in the Docker container. EXPERIMENTAL

getIntegrationPattern

@Stability(value=Experimental)
default ServiceIntegrationPattern getIntegrationPattern()

The service integration pattern indicates different ways to call SageMaker APIs. The valid value is either FIRE_AND_FORGET or SYNC. Default: FIRE_AND_FORGET EXPERIMENTAL

getMaxConcurrentTransforms

@Stability(value=Experimental)
default Number getMaxConcurrentTransforms()

Maximum number of parallel requests that can be sent to each instance in a transform job. EXPERIMENTAL

getMaxPayloadInMb

@Stability(value=Experimental)
default Number getMaxPayloadInMb()

Maximum allowed size of the payload, in MB. EXPERIMENTAL

getRole

@Stability(value=Experimental)
default IRole getRole()

Role for thte Training Job. EXPERIMENTAL

getTags

@Stability(value=Experimental)
default Map<String,String> getTags()

Tags to be applied to the train job. EXPERIMENTAL

getTransformResources

@Stability(value=Experimental)
default TransformResources getTransformResources()

ML compute instances for the transform job. EXPERIMENTAL

builder

@Stability(value=Experimental)
static SagemakerTransformProps.Builder builder()

Returns:

a SagemakerTransformProps.Builder of SagemakerTransformProps