Values.CreateTrainedModelRequestSourceCreates a trained model from an associated configured model algorithm using data from any member of the collaboration.
type nonrec t = {membershipIdentifier : UUID.t;The membership ID of the member that is creating the trained model.
*)name : NameString.t;The name of the trained model.
*)configuredModelAlgorithmAssociationArn : ConfiguredModelAlgorithmAssociationArn.t;The associated configured model algorithm used to train this model.
*)hyperparameters : HyperParameters.t option;Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process.
*)environment : Environment.t option;The environment variables to set in the Docker container.
*)resourceConfig : ResourceConfig.t;Information about the EC2 resources that are used to train this model.
*)stoppingCondition : StoppingCondition.t option;The criteria that is used to stop model training.
*)incrementalTrainingDataChannels : IncrementalTrainingDataChannels.t option;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).
*)dataChannels : ModelTrainingDataChannels.t;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).
*)trainingInputMode : TrainingInputMode.t option;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.
*)description : ResourceDescription.t option;The description of the trained model.
*)kmsKeyArn : KmsKeyArn.t option;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.
*)}val make :
?hyperparameters:??? ->
?environment:??? ->
?stoppingCondition:??? ->
?incrementalTrainingDataChannels:??? ->
?trainingInputMode:??? ->
?description:??? ->
?kmsKeyArn:??? ->
?tags:??? ->
membershipIdentifier:UUID.t ->
name:NameString.t ->
configuredModelAlgorithmAssociationArn:
ConfiguredModelAlgorithmAssociationArn.t ->
resourceConfig:ResourceConfig.t ->
dataChannels:ModelTrainingDataChannels.t ->
unit ->
tval to_value :
t ->
[> `Structure of
(string
* [> `Enum of string
| `List of
[> `Structure of
(string * [> `Enum of string | `String of TrainedModelArn.t ])
list ]
list
| `Map of
([> `String of HyperParametersKeyString.t ]
* [> `String of HyperParametersValueString.t ])
list
| `String of UUID.t
| `Structure of
(string
* [> `Enum of string
| `Integer of ResourceConfigInstanceCountInteger.t ])
list ])
list ]