Package software.amazon.awssdk.services.cleanroomsml.model

Interface StartTrainedModelInferenceJobRequest.Builder

All Superinterfaces:

AwsRequest.Builder, Buildable, CleanRoomsMlRequest.Builder, CopyableBuilder<StartTrainedModelInferenceJobRequest.Builder,StartTrainedModelInferenceJobRequest>, SdkBuilder<StartTrainedModelInferenceJobRequest.Builder,StartTrainedModelInferenceJobRequest>, SdkPojo, SdkRequest.Builder

Enclosing class:

StartTrainedModelInferenceJobRequest

public static interface StartTrainedModelInferenceJobRequest.Builder
extends CleanRoomsMlRequest.Builder, SdkPojo, CopyableBuilder<StartTrainedModelInferenceJobRequest.Builder,StartTrainedModelInferenceJobRequest>

Method Summary

Modifier and Type	Method	Description
StartTrainedModelInferenceJobRequest.Builder	configuredModelAlgorithmAssociationArn(String configuredModelAlgorithmAssociationArn)	The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model inference job.
default StartTrainedModelInferenceJobRequest.Builder	containerExecutionParameters(Consumer<InferenceContainerExecutionParameters.Builder> containerExecutionParameters)	The execution parameters for the container.
StartTrainedModelInferenceJobRequest.Builder	containerExecutionParameters(InferenceContainerExecutionParameters containerExecutionParameters)	The execution parameters for the container.
default StartTrainedModelInferenceJobRequest.Builder	dataSource(Consumer<ModelInferenceDataSource.Builder> dataSource)	Defines the data source that is used for the trained model inference job.
StartTrainedModelInferenceJobRequest.Builder	dataSource(ModelInferenceDataSource dataSource)	Defines the data source that is used for the trained model inference job.
StartTrainedModelInferenceJobRequest.Builder	description(String description)	The description of the trained model inference job.
StartTrainedModelInferenceJobRequest.Builder	environment(Map<String,String> environment)	The environment variables to set in the Docker container.
StartTrainedModelInferenceJobRequest.Builder	kmsKeyArn(String kmsKeyArn)	The Amazon Resource Name (ARN) of the KMS key.
StartTrainedModelInferenceJobRequest.Builder	membershipIdentifier(String membershipIdentifier)	The membership ID of the membership that contains the trained model inference job.
StartTrainedModelInferenceJobRequest.Builder	name(String name)	The name of the trained model inference job.
default StartTrainedModelInferenceJobRequest.Builder	outputConfiguration(Consumer<InferenceOutputConfiguration.Builder> outputConfiguration)	Defines the output configuration information for the trained model inference job.
StartTrainedModelInferenceJobRequest.Builder	outputConfiguration(InferenceOutputConfiguration outputConfiguration)	Defines the output configuration information for the trained model inference job.
StartTrainedModelInferenceJobRequest.Builder	overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)
StartTrainedModelInferenceJobRequest.Builder	overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)
default StartTrainedModelInferenceJobRequest.Builder	resourceConfig(Consumer<InferenceResourceConfig.Builder> resourceConfig)	Defines the resource configuration for the trained model inference job.
StartTrainedModelInferenceJobRequest.Builder	resourceConfig(InferenceResourceConfig resourceConfig)	Defines the resource configuration for the trained model inference job.
StartTrainedModelInferenceJobRequest.Builder	tags(Map<String,String> tags)	The optional metadata that you apply to the resource to help you categorize and organize them.
StartTrainedModelInferenceJobRequest.Builder	trainedModelArn(String trainedModelArn)	The Amazon Resource Name (ARN) of the trained model that is used for this trained model inference job.

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

overrideConfiguration

Methods inherited from interface software.amazon.awssdk.services.cleanroomsml.model.CleanRoomsMlRequest.Builder

build

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

copy

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

applyMutation, build

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

equalsBySdkFields, sdkFieldNameToField, sdkFields

Method Detail

membershipIdentifier

StartTrainedModelInferenceJobRequest.Builder membershipIdentifier(String membershipIdentifier)

The membership ID of the membership that contains the trained model inference job.

Parameters:

membershipIdentifier - The membership ID of the membership that contains the trained model inference job.

Returns:

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

name

StartTrainedModelInferenceJobRequest.Builder name(String name)

The name of the trained model inference job.

Parameters:

name - The name of the trained model inference job.

Returns:

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

trainedModelArn

StartTrainedModelInferenceJobRequest.Builder trainedModelArn(String trainedModelArn)

The Amazon Resource Name (ARN) of the trained model that is used for this trained model inference job.

Parameters:

trainedModelArn - The Amazon Resource Name (ARN) of the trained model that is used for this trained model inference job.

Returns:

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

configuredModelAlgorithmAssociationArn

StartTrainedModelInferenceJobRequest.Builder configuredModelAlgorithmAssociationArn(String configuredModelAlgorithmAssociationArn)

The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model inference job.

Parameters:

configuredModelAlgorithmAssociationArn - The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model inference job.

Returns:

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

resourceConfig

StartTrainedModelInferenceJobRequest.Builder resourceConfig(InferenceResourceConfig resourceConfig)

Defines the resource configuration for the trained model inference job.

Parameters:

resourceConfig - Defines the resource configuration for the trained model inference job.

Returns:

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

resourceConfig

default StartTrainedModelInferenceJobRequest.Builder resourceConfig(Consumer<InferenceResourceConfig.Builder> resourceConfig)

Defines the resource configuration for the trained model inference job.

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

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

Parameters:

resourceConfig - a consumer that will call methods on InferenceResourceConfig.Builder

Returns:

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

See Also:

resourceConfig(InferenceResourceConfig)

outputConfiguration

StartTrainedModelInferenceJobRequest.Builder outputConfiguration(InferenceOutputConfiguration outputConfiguration)

Defines the output configuration information for the trained model inference job.

Parameters:

outputConfiguration - Defines the output configuration information for the trained model inference job.

Returns:

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

outputConfiguration

default StartTrainedModelInferenceJobRequest.Builder outputConfiguration(Consumer<InferenceOutputConfiguration.Builder> outputConfiguration)

Defines the output configuration information for the trained model inference job.

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

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

Parameters:

outputConfiguration - a consumer that will call methods on InferenceOutputConfiguration.Builder

Returns:

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

See Also:

outputConfiguration(InferenceOutputConfiguration)

dataSource

StartTrainedModelInferenceJobRequest.Builder dataSource(ModelInferenceDataSource dataSource)

Defines the data source that is used for the trained model inference job.

Parameters:

dataSource - Defines the data source that is used for the trained model inference job.

Returns:

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

dataSource

default StartTrainedModelInferenceJobRequest.Builder dataSource(Consumer<ModelInferenceDataSource.Builder> dataSource)

Defines the data source that is used for the trained model inference job.

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

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

Parameters:

dataSource - a consumer that will call methods on ModelInferenceDataSource.Builder

Returns:

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

See Also:

dataSource(ModelInferenceDataSource)

description

StartTrainedModelInferenceJobRequest.Builder description(String description)

The description of the trained model inference job.

Parameters:

description - The description of the trained model inference job.

Returns:

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

containerExecutionParameters

StartTrainedModelInferenceJobRequest.Builder containerExecutionParameters(InferenceContainerExecutionParameters containerExecutionParameters)

The execution parameters for the container.

Parameters:

containerExecutionParameters - The execution parameters for the container.

Returns:

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

containerExecutionParameters

default StartTrainedModelInferenceJobRequest.Builder containerExecutionParameters(Consumer<InferenceContainerExecutionParameters.Builder> containerExecutionParameters)

The execution parameters for the container.

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

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

Parameters:

containerExecutionParameters - a consumer that will call methods on InferenceContainerExecutionParameters.Builder

Returns:

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

See Also:

containerExecutionParameters(InferenceContainerExecutionParameters)

environment

StartTrainedModelInferenceJobRequest.Builder environment(Map<String,String> environment)

The environment variables to set in the Docker container.

Parameters:

environment - The environment variables to set in the Docker container.

Returns:

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

kmsKeyArn

StartTrainedModelInferenceJobRequest.Builder kmsKeyArn(String kmsKeyArn)

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.

Parameters:

kmsKeyArn - The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.

Returns:

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

tags

StartTrainedModelInferenceJobRequest.Builder tags(Map<String,String> tags)

The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

• Maximum number of tags per resource - 50.

• For each resource, each tag key must be unique, and each tag key can have only one value.

• Maximum key length - 128 Unicode characters in UTF-8.

• Maximum value length - 256 Unicode characters in UTF-8.

• If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

• Tag keys and values are case sensitive.

• Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

Parameters:

tags - The optional metadata that you apply to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

• Maximum number of tags per resource - 50.

• For each resource, each tag key must be unique, and each tag key can have only one value.

• Maximum key length - 128 Unicode characters in UTF-8.

• Maximum value length - 256 Unicode characters in UTF-8.

• If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.

• Tag keys and values are case sensitive.

• Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

Returns:

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

overrideConfiguration

StartTrainedModelInferenceJobRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)

Specified by:

overrideConfiguration in interface AwsRequest.Builder

overrideConfiguration

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

Specified by:

overrideConfiguration in interface AwsRequest.Builder