TrainingJobDefinition class

Defines the input needed to run a training job using the algorithm.

Constructors

TrainingJobDefinition({required List<Channel> inputDataConfig, required OutputDataConfig outputDataConfig, required ResourceConfig resourceConfig, required StoppingCondition stoppingCondition, required TrainingInputMode trainingInputMode, Map<String, String>? hyperParameters})

TrainingJobDefinition.fromJson(Map<String, dynamic> json)

factory

Properties

hashCode → int

The hash code for this object.

no setter, inherited

hyperParameters → Map<String, String>?

The hyperparameters used for the training job.

final

inputDataConfig → List<Channel>

An array of Channel objects, each of which specifies an input source.

final

outputDataConfig → OutputDataConfig

the path to the S3 bucket where you want to store model artifacts. Amazon SageMaker creates subfolders for the artifacts.

final

resourceConfig → ResourceConfig

The resources, including the ML compute instances and ML storage volumes, to use for model training.

final

runtimeType → Type

A representation of the runtime type of the object.

no setter, inherited

stoppingCondition → StoppingCondition

Specifies a limit to how long a model training job can run. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

final

trainingInputMode → TrainingInputMode

The input mode used by the algorithm for the training job. For the input modes that Amazon SageMaker algorithms support, see Algorithms.

final

Methods

noSuchMethod(Invocation invocation) → dynamic

Invoked when a nonexistent method or property is accessed.

inherited

toJson() → Map<String, dynamic>

toString() → String

A string representation of this object.

inherited

Operators

operator ==(Object other) → bool

The equality operator.

inherited