Interface StartTrainedModelInferenceJobRequest.Builder

All Superinterfaces:
AwsRequest.Builder, Buildable, CleanRoomsMlRequest.Builder, CopyableBuilder<StartTrainedModelInferenceJobRequest.Builder,StartTrainedModelInferenceJobRequest>, SdkBuilder<StartTrainedModelInferenceJobRequest.Builder,StartTrainedModelInferenceJobRequest>, SdkPojo, SdkRequest.Builder
Enclosing class:
StartTrainedModelInferenceJobRequest
@Mutable @NotThreadSafe public static interface StartTrainedModelInferenceJobRequest.Builder extends CleanRoomsMlRequest.Builder, SdkPojo, CopyableBuilder<StartTrainedModelInferenceJobRequest.Builder,StartTrainedModelInferenceJobRequest>

  • Method Details

    • 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.

    • trainedModelVersionIdentifier

      StartTrainedModelInferenceJobRequest.Builder trainedModelVersionIdentifier(String trainedModelVersionIdentifier)

      The version identifier of the trained model to use for inference. This specifies which version of the trained model should be used to generate predictions on the input data.

      Parameters:
      trainedModelVersionIdentifier - The version identifier of the trained model to use for inference. This specifies which version of the trained model should be used to generate predictions on the input data.
      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:

    • 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:

    • 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:

    • 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:

    • 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)
      Description copied from interface: AwsRequest.Builder
      Add an optional request override configuration.
      Specified by:
      overrideConfiguration in interface AwsRequest.Builder
      Parameters:
      overrideConfiguration - The override configuration.
      Returns:
      This object for method chaining.

    • overrideConfiguration

      StartTrainedModelInferenceJobRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)
      Description copied from interface: AwsRequest.Builder
      Add an optional request override configuration.
      Specified by:
      overrideConfiguration in interface AwsRequest.Builder
      Parameters:
      builderConsumer - A Consumer to which an empty AwsRequestOverrideConfiguration.Builder will be given.
      Returns:
      This object for method chaining.