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AWS::SageMaker::HyperParameterTuningJob TrainingJobDefinition - AWS CloudFormation

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AWS::SageMaker::HyperParameterTuningJob TrainingJobDefinition

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

Syntax

To declare this entity in your CloudFormation template, use the following syntax:

Properties

AlgorithmSpecification

Property description not available.

Required: Yes

Type: AlgorithmSpecification

Update requires: Replacement

CheckpointConfig

Property description not available.

Required: No

Type: CheckpointConfig

Update requires: Replacement

DefinitionName

Property description not available.

Required: No

Type: String

Pattern: [a-zA-Z0-9](-*[a-zA-Z0-9]){0,63}

Minimum: 1

Maximum: 64

Update requires: Replacement

EnableInterContainerTrafficEncryption

Property description not available.

Required: No

Type: Boolean

Update requires: Replacement

EnableManagedSpotTraining

Property description not available.

Required: No

Type: Boolean

Update requires: Replacement

EnableNetworkIsolation

Property description not available.

Required: No

Type: Boolean

Update requires: Replacement

Environment

Property description not available.

Required: No

Type: Object of String

Pattern: ^[a-zA-Z_][a-zA-Z0-9_]*$

Minimum: 0

Maximum: 512

Update requires: Replacement

HyperParameterRanges

Property description not available.

Required: No

Type: ParameterRanges

Update requires: Replacement

InputDataConfig

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

Required: No

Type: Array of InputDataConfigItems

Minimum: 1

Maximum: 20

Update requires: Replacement

OutputDataConfig

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

Required: Yes

Type: OutputDataConfig

Update requires: Replacement

ResourceConfig

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

Required: No

Type: ResourceConfig

Update requires: Replacement

RetryStrategy

Property description not available.

Required: No

Type: RetryStrategy

Update requires: Replacement

RoleArn

Property description not available.

Required: Yes

Type: String

Pattern: ^arn:aws[a-z\-]*:iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+$

Minimum: 20

Maximum: 2048

Update requires: Replacement

StaticHyperParameters

Property description not available.

Required: No

Type: Object of String

Pattern: .*

Minimum: 0

Maximum: 2500

Update requires: Replacement

StoppingCondition

Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.

To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts.

Required: Yes

Type: StoppingCondition

Update requires: Replacement

TuningObjective

Property description not available.

Required: No

Type: TuningObjective

Update requires: Replacement

VpcConfig

Property description not available.

Required: No

Type: VpcConfig

Update requires: Replacement