Interface CreateTrainedModelRequest.Builder

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

  • Method Details

    • membershipIdentifier

      CreateTrainedModelRequest.Builder membershipIdentifier(String membershipIdentifier)

      The membership ID of the member that is creating the trained model.

      Parameters:
      membershipIdentifier - The membership ID of the member that is creating the trained model.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • name

      CreateTrainedModelRequest.Builder name(String name)

      The name of the trained model.

      Parameters:
      name - The name of the trained model.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • configuredModelAlgorithmAssociationArn

      CreateTrainedModelRequest.Builder configuredModelAlgorithmAssociationArn(String configuredModelAlgorithmAssociationArn)

      The associated configured model algorithm used to train this model.

      Parameters:
      configuredModelAlgorithmAssociationArn - The associated configured model algorithm used to train this model.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • hyperparameters

      CreateTrainedModelRequest.Builder hyperparameters(Map<String,String> hyperparameters)

      Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process.

      Parameters:
      hyperparameters - Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • environment

      CreateTrainedModelRequest.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.

    • resourceConfig

      CreateTrainedModelRequest.Builder resourceConfig(ResourceConfig resourceConfig)

      Information about the EC2 resources that are used to train this model.

      Parameters:
      resourceConfig - Information about the EC2 resources that are used to train this model.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • resourceConfig

      default CreateTrainedModelRequest.Builder resourceConfig(Consumer<ResourceConfig.Builder> resourceConfig)

      Information about the EC2 resources that are used to train this model.

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

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

      Parameters:
      resourceConfig - a consumer that will call methods on ResourceConfig.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:

    • stoppingCondition

      CreateTrainedModelRequest.Builder stoppingCondition(StoppingCondition stoppingCondition)

      The criteria that is used to stop model training.

      Parameters:
      stoppingCondition - The criteria that is used to stop model training.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • stoppingCondition

      default CreateTrainedModelRequest.Builder stoppingCondition(Consumer<StoppingCondition.Builder> stoppingCondition)

      The criteria that is used to stop model training.

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

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

      Parameters:
      stoppingCondition - a consumer that will call methods on StoppingCondition.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:

    • incrementalTrainingDataChannels

      CreateTrainedModelRequest.Builder incrementalTrainingDataChannels(Collection<IncrementalTrainingDataChannel> incrementalTrainingDataChannels)

      Specifies the incremental training data channels for the trained model.

      Incremental training allows you to create a new trained model with updates without retraining from scratch. You can specify up to one incremental training data channel that references a previously trained model and its version.

      Limit: Maximum of 20 channels total (including both incrementalTrainingDataChannels and dataChannels).

      Parameters:
      incrementalTrainingDataChannels - Specifies the incremental training data channels for the trained model.

      Incremental training allows you to create a new trained model with updates without retraining from scratch. You can specify up to one incremental training data channel that references a previously trained model and its version.

      Limit: Maximum of 20 channels total (including both incrementalTrainingDataChannels and dataChannels).

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

    • incrementalTrainingDataChannels

      CreateTrainedModelRequest.Builder incrementalTrainingDataChannels(IncrementalTrainingDataChannel... incrementalTrainingDataChannels)

      Specifies the incremental training data channels for the trained model.

      Incremental training allows you to create a new trained model with updates without retraining from scratch. You can specify up to one incremental training data channel that references a previously trained model and its version.

      Limit: Maximum of 20 channels total (including both incrementalTrainingDataChannels and dataChannels).

      Parameters:
      incrementalTrainingDataChannels - Specifies the incremental training data channels for the trained model.

      Incremental training allows you to create a new trained model with updates without retraining from scratch. You can specify up to one incremental training data channel that references a previously trained model and its version.

      Limit: Maximum of 20 channels total (including both incrementalTrainingDataChannels and dataChannels).

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

    • incrementalTrainingDataChannels

      CreateTrainedModelRequest.Builder incrementalTrainingDataChannels(Consumer<IncrementalTrainingDataChannel.Builder>... incrementalTrainingDataChannels)

      Specifies the incremental training data channels for the trained model.

      Incremental training allows you to create a new trained model with updates without retraining from scratch. You can specify up to one incremental training data channel that references a previously trained model and its version.

      Limit: Maximum of 20 channels total (including both incrementalTrainingDataChannels and dataChannels).

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

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to incrementalTrainingDataChannels(List<IncrementalTrainingDataChannel>).

      Parameters:
      incrementalTrainingDataChannels - a consumer that will call methods on IncrementalTrainingDataChannel.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:

    • dataChannels

      CreateTrainedModelRequest.Builder dataChannels(Collection<ModelTrainingDataChannel> dataChannels)

      Defines the data channels that are used as input for the trained model request.

      Limit: Maximum of 20 channels total (including both dataChannels and incrementalTrainingDataChannels).

      Parameters:
      dataChannels - Defines the data channels that are used as input for the trained model request.

      Limit: Maximum of 20 channels total (including both dataChannels and incrementalTrainingDataChannels).

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

    • dataChannels

      CreateTrainedModelRequest.Builder dataChannels(ModelTrainingDataChannel... dataChannels)

      Defines the data channels that are used as input for the trained model request.

      Limit: Maximum of 20 channels total (including both dataChannels and incrementalTrainingDataChannels).

      Parameters:
      dataChannels - Defines the data channels that are used as input for the trained model request.

      Limit: Maximum of 20 channels total (including both dataChannels and incrementalTrainingDataChannels).

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

    • dataChannels

      CreateTrainedModelRequest.Builder dataChannels(Consumer<ModelTrainingDataChannel.Builder>... dataChannels)

      Defines the data channels that are used as input for the trained model request.

      Limit: Maximum of 20 channels total (including both dataChannels and incrementalTrainingDataChannels).

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

      When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to dataChannels(List<ModelTrainingDataChannel>).

      Parameters:
      dataChannels - a consumer that will call methods on ModelTrainingDataChannel.Builder
      Returns:
      Returns a reference to this object so that method calls can be chained together.
      See Also:

    • trainingInputMode

      CreateTrainedModelRequest.Builder trainingInputMode(String trainingInputMode)

      The input mode for accessing the training data. This parameter determines how the training data is made available to the training algorithm. Valid values are:

      • File - The training data is downloaded to the training instance and made available as files.

      • FastFile - The training data is streamed directly from Amazon S3 to the training algorithm, providing faster access for large datasets.

      • Pipe - The training data is streamed to the training algorithm using named pipes, which can improve performance for certain algorithms.

      Parameters:
      trainingInputMode - The input mode for accessing the training data. This parameter determines how the training data is made available to the training algorithm. Valid values are:

      • File - The training data is downloaded to the training instance and made available as files.

      • FastFile - The training data is streamed directly from Amazon S3 to the training algorithm, providing faster access for large datasets.

      • Pipe - The training data is streamed to the training algorithm using named pipes, which can improve performance for certain algorithms.

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

    • trainingInputMode

      CreateTrainedModelRequest.Builder trainingInputMode(TrainingInputMode trainingInputMode)

      The input mode for accessing the training data. This parameter determines how the training data is made available to the training algorithm. Valid values are:

      • File - The training data is downloaded to the training instance and made available as files.

      • FastFile - The training data is streamed directly from Amazon S3 to the training algorithm, providing faster access for large datasets.

      • Pipe - The training data is streamed to the training algorithm using named pipes, which can improve performance for certain algorithms.

      Parameters:
      trainingInputMode - The input mode for accessing the training data. This parameter determines how the training data is made available to the training algorithm. Valid values are:

      • File - The training data is downloaded to the training instance and made available as files.

      • FastFile - The training data is streamed directly from Amazon S3 to the training algorithm, providing faster access for large datasets.

      • Pipe - The training data is streamed to the training algorithm using named pipes, which can improve performance for certain algorithms.

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

    • description

      CreateTrainedModelRequest.Builder description(String description)

      The description of the trained model.

      Parameters:
      description - The description of the trained model.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • kmsKeyArn

      CreateTrainedModelRequest.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 trained ML model and the 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 trained ML model and the associated data.
      Returns:
      Returns a reference to this object so that method calls can be chained together.

    • tags

      CreateTrainedModelRequest.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

      CreateTrainedModelRequest.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

      CreateTrainedModelRequest.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.