AWS::SageMaker::ModelPackage - Amazon CloudFormation
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AWS::SageMaker::ModelPackage

A versioned model that can be deployed for SageMaker inference.

Syntax

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

Properties

AdditionalInferenceSpecifications

An array of additional Inference Specification objects.

Required: No

Type: Array of AdditionalInferenceSpecificationDefinition

Minimum: 1

Maximum: 15

Update requires: No interruption

AdditionalInferenceSpecificationsToAdd

An array of additional Inference Specification objects to be added to the existing array. The total number of additional Inference Specification objects cannot exceed 15. Each additional Inference Specification object specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.

Required: No

Type: Array of AdditionalInferenceSpecificationDefinition

Minimum: 1

Maximum: 15

Update requires: No interruption

ApprovalDescription

A description provided when the model approval is set.

Required: No

Type: String

Pattern: .*

Maximum: 1024

Update requires: No interruption

CertifyForMarketplace

Whether the model package is to be certified to be listed on Amazon Marketplace. For information about listing model packages on Amazon Marketplace, see List Your Algorithm or Model Package on Amazon Marketplace.

Required: No

Type: Boolean

Update requires: No interruption

ClientToken

A unique token that guarantees that the call to this API is idempotent.

Required: No

Type: String

Pattern: ^[a-zA-Z0-9-]+$

Minimum: 1

Maximum: 36

Update requires: Replacement

CustomerMetadataProperties

The metadata properties for the model package.

Required: No

Type: Object of String

Pattern: ^([\p{L}\p{Z}\p{N}_.:\/=+\-@]*)${1,128}

Minimum: 1

Maximum: 128

Update requires: No interruption

Domain

The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.

Required: No

Type: String

Update requires: Replacement

DriftCheckBaselines

Represents the drift check baselines that can be used when the model monitor is set using the model package.

Required: No

Type: DriftCheckBaselines

Update requires: Replacement

InferenceSpecification

Defines how to perform inference generation after a training job is run.

Required: No

Type: InferenceSpecification

Update requires: Replacement

LastModifiedTime

The last time the model package was modified.

Required: No

Type: String

Update requires: No interruption

MetadataProperties

Metadata properties of the tracking entity, trial, or trial component.

Required: No

Type: MetadataProperties

Update requires: Replacement

ModelApprovalStatus

The approval status of the model. This can be one of the following values.

  • APPROVED - The model is approved

  • REJECTED - The model is rejected.

  • PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.

Required: No

Type: String

Allowed values: Approved | Rejected | PendingManualApproval

Update requires: No interruption

ModelMetrics

Metrics for the model.

Required: No

Type: ModelMetrics

Update requires: Replacement

ModelPackageDescription

The description of the model package.

Required: No

Type: String

Pattern: [\p{L}\p{M}\p{Z}\p{S}\p{N}\p{P}]*

Maximum: 1024

Update requires: Replacement

ModelPackageGroupName

The model group to which the model belongs.

Required: No

Type: String

Pattern: (arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:[a-z\-]*\/)?([a-zA-Z0-9]([a-zA-Z0-9-]){0,62})(?<!-)$

Minimum: 1

Maximum: 170

Update requires: Replacement

ModelPackageName

The name of the model.

Required: No

Type: String

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}$

Minimum: 1

Maximum: 63

Update requires: No interruption

ModelPackageStatusDetails

Specifies the validation and image scan statuses of the model package.

Required: No

Type: ModelPackageStatusDetails

Update requires: No interruption

ModelPackageVersion

The version number of a versioned model.

Required: No

Type: Integer

Minimum: 1

Update requires: No interruption

SamplePayloadUrl

The Amazon Simple Storage Service path where the sample payload are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).

Required: No

Type: String

Pattern: ^(https|s3)://([^/]+)/?(.*)$

Maximum: 1024

Update requires: Replacement

SkipModelValidation

Indicates if you want to skip model validation.

Required: No

Type: String

Allowed values: None | All

Update requires: No interruption

SourceAlgorithmSpecification

A list of algorithms that were used to create a model package.

Required: No

Type: SourceAlgorithmSpecification

Update requires: Replacement

Tags

A list of the tags associated with the model package. For more information, see Tagging Amazon resources in the Amazon General Reference Guide.

Required: No

Type: Array of Tag

Maximum: 50

Update requires: No interruption

Task

The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.

Required: No

Type: String

Update requires: Replacement

ValidationSpecification

Specifies batch transform jobs that SageMaker runs to validate your model package.

Required: No

Type: ValidationSpecification

Update requires: Replacement

Return values

Ref


When you pass the logical ID of this resource to the intrinsic Ref function, Ref returns the Amazon Resource Name (ARN) of the model package group.

For more information about using the Ref function, see Ref.

Fn::GetAtt

The Fn::GetAtt intrinsic function returns a value for a specified attribute of this type. The following are the available attributes and sample return values.

For more information about using the Fn::GetAtt intrinsic function, see Fn::GetAtt.

CreationTime

The time that the model package was created.

ModelPackageArn

The Amazon Resource Name (ARN) of the model package.

ModelPackageStatus

The status of the model package. This can be one of the following values.

  • PENDING - The model package creation is pending.

  • IN_PROGRESS - The model package is in the process of being created.

  • COMPLETED - The model package was successfully created.

  • FAILED - The model package creation failed.

  • DELETING - The model package is in the process of being deleted.