Class: Aws::CleanRoomsML::Types::CreateTrainedModelRequest

Inherits:

Struct

• Object
• Struct
• Aws::CleanRoomsML::Types::CreateTrainedModelRequest

Defined in:

gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb

Overview

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #configured_model_algorithm_association_arn ⇒ String

  The associated configured model algorithm used to train this model.

• #data_channels ⇒ Array<Types::ModelTrainingDataChannel>

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

• #description ⇒ String

  The description of the trained model.

• #environment ⇒ Hash<String,String>

  The environment variables to set in the Docker container.

• #hyperparameters ⇒ Hash<String,String>

  Algorithm-specific parameters that influence the quality of the model.

• #incremental_training_data_channels ⇒ Array<Types::IncrementalTrainingDataChannel>

  Specifies the incremental training data channels for the trained model.

• #kms_key_arn ⇒ String

  The Amazon Resource Name (ARN) of the KMS key.

• #membership_identifier ⇒ String

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

• #name ⇒ String

  The name of the trained model.

• #resource_config ⇒ Types::ResourceConfig

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

• #stopping_condition ⇒ Types::StoppingCondition

  The criteria that is used to stop model training.

• #tags ⇒ Hash<String,String>

  The optional metadata that you apply to the resource to help you categorize and organize them.

• #training_input_mode ⇒ String

  The input mode for accessing the training data.

Instance Attribute Details

#configured_model_algorithm_association_arn ⇒ String

The associated configured model algorithm used to train this model.

Returns:

• (String)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#data_channels ⇒ Array<Types::ModelTrainingDataChannel>

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:

• (Array<Types::ModelTrainingDataChannel>)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#description ⇒ String

The description of the trained model.

Returns:

• (String)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#environment ⇒ Hash<String,String>

The environment variables to set in the Docker container.

Returns:

• (Hash<String,String>)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#hyperparameters ⇒ Hash<String,String>

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

Returns:

• (Hash<String,String>)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#incremental_training_data_channels ⇒ Array<Types::IncrementalTrainingDataChannel>

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:

• (Array<Types::IncrementalTrainingDataChannel>)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#kms_key_arn ⇒ String

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:

• (String)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#membership_identifier ⇒ String

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

Returns:

• (String)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#name ⇒ String

The name of the trained model.

Returns:

• (String)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#resource_config ⇒ Types::ResourceConfig

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

Returns:

• (Types::ResourceConfig)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#stopping_condition ⇒ Types::StoppingCondition

The criteria that is used to stop model training.

Returns:

• (Types::StoppingCondition)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#tags ⇒ Hash<String,String>

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:

• (Hash<String,String>)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end

#training_input_mode ⇒ String

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:

• (String)

# File 'gems/aws-sdk-cleanroomsml/lib/aws-sdk-cleanroomsml/types.rb', line 1594

class CreateTrainedModelRequest < Struct.new(
  :membership_identifier,
  :name,
  :configured_model_algorithm_association_arn,
  :hyperparameters,
  :environment,
  :resource_config,
  :stopping_condition,
  :incremental_training_data_channels,
  :data_channels,
  :training_input_mode,
  :description,
  :kms_key_arn,
  :tags)
  SENSITIVE = []
  include Aws::Structure
end