software.amazon.awssdk.services.neptunedata.model

Interface StartMlModelTransformJobRequest.Builder

All Superinterfaces:

AwsRequest.Builder, Buildable, CopyableBuilder<StartMlModelTransformJobRequest.Builder,StartMlModelTransformJobRequest>, NeptunedataRequest.Builder, SdkBuilder<StartMlModelTransformJobRequest.Builder,StartMlModelTransformJobRequest>, SdkPojo, SdkRequest.Builder

Enclosing class:

StartMlModelTransformJobRequest

public static interface StartMlModelTransformJobRequest.Builder
extends NeptunedataRequest.Builder, SdkPojo, CopyableBuilder<StartMlModelTransformJobRequest.Builder,StartMlModelTransformJobRequest>

Method Summary

Modifier and Type	Method and Description
StartMlModelTransformJobRequest.Builder	baseProcessingInstanceType(String baseProcessingInstanceType) The type of ML instance used in preparing and managing training of ML models.
StartMlModelTransformJobRequest.Builder	baseProcessingInstanceVolumeSizeInGB(Integer baseProcessingInstanceVolumeSizeInGB) The disk volume size of the training instance in gigabytes.
default StartMlModelTransformJobRequest.Builder	customModelTransformParameters(Consumer<CustomModelTransformParameters.Builder> customModelTransformParameters) Configuration information for a model transform using a custom model.
StartMlModelTransformJobRequest.Builder	customModelTransformParameters(CustomModelTransformParameters customModelTransformParameters) Configuration information for a model transform using a custom model.
StartMlModelTransformJobRequest.Builder	dataProcessingJobId(String dataProcessingJobId) The job ID of a completed data-processing job.
StartMlModelTransformJobRequest.Builder	id(String id) A unique identifier for the new job.
StartMlModelTransformJobRequest.Builder	mlModelTrainingJobId(String mlModelTrainingJobId) The job ID of a completed model-training job.
StartMlModelTransformJobRequest.Builder	modelTransformOutputS3Location(String modelTransformOutputS3Location) The location in Amazon S3 where the model artifacts are to be stored.
StartMlModelTransformJobRequest.Builder	neptuneIamRoleArn(String neptuneIamRoleArn) The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources.
StartMlModelTransformJobRequest.Builder	overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)
StartMlModelTransformJobRequest.Builder	overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)
StartMlModelTransformJobRequest.Builder	s3OutputEncryptionKMSKey(String s3OutputEncryptionKMSKey) The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job.
StartMlModelTransformJobRequest.Builder	sagemakerIamRoleArn(String sagemakerIamRoleArn) The ARN of an IAM role for SageMaker execution.
StartMlModelTransformJobRequest.Builder	securityGroupIds(Collection<String> securityGroupIds) The VPC security group IDs.
StartMlModelTransformJobRequest.Builder	securityGroupIds(String... securityGroupIds) The VPC security group IDs.
StartMlModelTransformJobRequest.Builder	subnets(Collection<String> subnets) The IDs of the subnets in the Neptune VPC.
StartMlModelTransformJobRequest.Builder	subnets(String... subnets) The IDs of the subnets in the Neptune VPC.
StartMlModelTransformJobRequest.Builder	trainingJobName(String trainingJobName) The name of a completed SageMaker training job.
StartMlModelTransformJobRequest.Builder	volumeEncryptionKMSKey(String volumeEncryptionKMSKey) The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job.

Methods inherited from interface software.amazon.awssdk.services.neptunedata.model.NeptunedataRequest.Builder

build

Methods inherited from interface software.amazon.awssdk.awscore.AwsRequest.Builder

overrideConfiguration

Methods inherited from interface software.amazon.awssdk.core.SdkPojo

equalsBySdkFields, sdkFields

Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder

copy

Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder

applyMutation, build

Method Detail

id

StartMlModelTransformJobRequest.Builder id(String id)

A unique identifier for the new job. The default is an autogenerated UUID.

Parameters:

id - A unique identifier for the new job. The default is an autogenerated UUID.

Returns:

Returns a reference to this object so that method calls can be chained together.

dataProcessingJobId

StartMlModelTransformJobRequest.Builder dataProcessingJobId(String dataProcessingJobId)

The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Parameters:

dataProcessingJobId - The job ID of a completed data-processing job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Returns:

Returns a reference to this object so that method calls can be chained together.

mlModelTrainingJobId

StartMlModelTransformJobRequest.Builder mlModelTrainingJobId(String mlModelTrainingJobId)

The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Parameters:

mlModelTrainingJobId - The job ID of a completed model-training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Returns:

Returns a reference to this object so that method calls can be chained together.

trainingJobName

StartMlModelTransformJobRequest.Builder trainingJobName(String trainingJobName)

The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Parameters:

trainingJobName - The name of a completed SageMaker training job. You must include either dataProcessingJobId and a mlModelTrainingJobId, or a trainingJobName.

Returns:

Returns a reference to this object so that method calls can be chained together.

modelTransformOutputS3Location

StartMlModelTransformJobRequest.Builder modelTransformOutputS3Location(String modelTransformOutputS3Location)

The location in Amazon S3 where the model artifacts are to be stored.

Parameters:

modelTransformOutputS3Location - The location in Amazon S3 where the model artifacts are to be stored.

Returns:

Returns a reference to this object so that method calls can be chained together.

sagemakerIamRoleArn

StartMlModelTransformJobRequest.Builder sagemakerIamRoleArn(String sagemakerIamRoleArn)

The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.

Parameters:

sagemakerIamRoleArn - The ARN of an IAM role for SageMaker execution. This must be listed in your DB cluster parameter group or an error will occur.

Returns:

Returns a reference to this object so that method calls can be chained together.

neptuneIamRoleArn

StartMlModelTransformJobRequest.Builder neptuneIamRoleArn(String neptuneIamRoleArn)

The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.

Parameters:

neptuneIamRoleArn - The ARN of an IAM role that provides Neptune access to SageMaker and Amazon S3 resources. This must be listed in your DB cluster parameter group or an error will occur.

Returns:

Returns a reference to this object so that method calls can be chained together.

customModelTransformParameters

StartMlModelTransformJobRequest.Builder customModelTransformParameters(CustomModelTransformParameters customModelTransformParameters)

Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:

Parameters:

customModelTransformParameters - Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:

Returns:

Returns a reference to this object so that method calls can be chained together.

customModelTransformParameters

default StartMlModelTransformJobRequest.Builder customModelTransformParameters(Consumer<CustomModelTransformParameters.Builder> customModelTransformParameters)

Configuration information for a model transform using a custom model. The customModelTransformParameters object contains the following fields, which must have values compatible with the saved model parameters from the training job:

This is a convenience method that creates an instance of the CustomModelTransformParameters.Builder avoiding the need to create one manually via CustomModelTransformParameters.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to customModelTransformParameters(CustomModelTransformParameters).

Parameters:

customModelTransformParameters - a consumer that will call methods on CustomModelTransformParameters.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

customModelTransformParameters(CustomModelTransformParameters)

baseProcessingInstanceType

StartMlModelTransformJobRequest.Builder baseProcessingInstanceType(String baseProcessingInstanceType)

The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.

Parameters:

baseProcessingInstanceType - The type of ML instance used in preparing and managing training of ML models. This is an ML compute instance chosen based on memory requirements for processing the training data and model.

Returns:

Returns a reference to this object so that method calls can be chained together.

baseProcessingInstanceVolumeSizeInGB

StartMlModelTransformJobRequest.Builder baseProcessingInstanceVolumeSizeInGB(Integer baseProcessingInstanceVolumeSizeInGB)

The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.

Parameters:

baseProcessingInstanceVolumeSizeInGB - The disk volume size of the training instance in gigabytes. The default is 0. Both input data and the output model are stored on disk, so the volume size must be large enough to hold both data sets. If not specified or 0, Neptune ML selects a disk volume size based on the recommendation generated in the data processing step.

Returns:

Returns a reference to this object so that method calls can be chained together.

subnets

StartMlModelTransformJobRequest.Builder subnets(Collection<String> subnets)

The IDs of the subnets in the Neptune VPC. The default is None.

Parameters:

subnets - The IDs of the subnets in the Neptune VPC. The default is None.

Returns:

Returns a reference to this object so that method calls can be chained together.

subnets

StartMlModelTransformJobRequest.Builder subnets(String... subnets)

The IDs of the subnets in the Neptune VPC. The default is None.

Parameters:

subnets - The IDs of the subnets in the Neptune VPC. The default is None.

Returns:

Returns a reference to this object so that method calls can be chained together.

securityGroupIds

StartMlModelTransformJobRequest.Builder securityGroupIds(Collection<String> securityGroupIds)

The VPC security group IDs. The default is None.

Parameters:

securityGroupIds - The VPC security group IDs. The default is None.

Returns:

Returns a reference to this object so that method calls can be chained together.

securityGroupIds

StartMlModelTransformJobRequest.Builder securityGroupIds(String... securityGroupIds)

The VPC security group IDs. The default is None.

Parameters:

securityGroupIds - The VPC security group IDs. The default is None.

Returns:

Returns a reference to this object so that method calls can be chained together.

volumeEncryptionKMSKey

StartMlModelTransformJobRequest.Builder volumeEncryptionKMSKey(String volumeEncryptionKMSKey)

The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.

Parameters:

volumeEncryptionKMSKey - The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt data on the storage volume attached to the ML compute instances that run the training job. The default is None.

Returns:

Returns a reference to this object so that method calls can be chained together.

s3OutputEncryptionKMSKey

StartMlModelTransformJobRequest.Builder s3OutputEncryptionKMSKey(String s3OutputEncryptionKMSKey)

The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.

Parameters:

s3OutputEncryptionKMSKey - The Amazon Key Management Service (KMS) key that SageMaker uses to encrypt the output of the processing job. The default is none.

Returns:

Returns a reference to this object so that method calls can be chained together.

overrideConfiguration

StartMlModelTransformJobRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)

Specified by:

overrideConfiguration in interface AwsRequest.Builder

overrideConfiguration

StartMlModelTransformJobRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)

Specified by:

overrideConfiguration in interface AwsRequest.Builder