ModelPackage

sagemaker.services.k8s.aws/v1alpha1

Type	Link
GoDoc	sagemaker-controller/apis/v1alpha1#ModelPackage

Metadata

Property	Value
Scope	Namespaced
Kind	`ModelPackage`
ListKind	`ModelPackageList`
Plural	`modelpackages`
Singular	`modelpackage`

A versioned model that can be deployed for SageMaker inference.

Spec

additionalInferenceSpecifications:
  containers:
    additionalS3DataSource: 
      compressionType: string
      s3DataType: string
      s3URI: string
    containerHostname: string
    environment: {}
    framework: string
    frameworkVersion: string
    image: string
    imageDigest: string
    modelDataURL: string
    modelInput: 
      dataInputConfig: string
    nearestModelName: string
    productID: string
  description: string
  name: string
  supportedContentTypes:
  - string
  supportedRealtimeInferenceInstanceTypes:
  - string
  supportedResponseMIMETypes:
  - string
  supportedTransformInstanceTypes:
  - string
approvalDescription: string
certifyForMarketplace: boolean
clientToken: string
customerMetadataProperties: {}
domain: string
driftCheckBaselines: 
  bias: 
    configFile: 
      contentDigest: string
      contentType: string
      s3URI: string
    postTrainingConstraints: 
      contentDigest: string
      contentType: string
      s3URI: string
    preTrainingConstraints: 
      contentDigest: string
      contentType: string
      s3URI: string
  explainability: 
    configFile: 
      contentDigest: string
      contentType: string
      s3URI: string
    constraints: 
      contentDigest: string
      contentType: string
      s3URI: string
  modelDataQuality: 
    constraints: 
      contentDigest: string
      contentType: string
      s3URI: string
    statistics: 
      contentDigest: string
      contentType: string
      s3URI: string
  modelQuality: 
    constraints: 
      contentDigest: string
      contentType: string
      s3URI: string
    statistics: 
      contentDigest: string
      contentType: string
      s3URI: string
inferenceSpecification: 
  containers:
    additionalS3DataSource: 
      compressionType: string
      s3DataType: string
      s3URI: string
    containerHostname: string
    environment: {}
    framework: string
    frameworkVersion: string
    image: string
    imageDigest: string
    modelDataURL: string
    modelInput: 
      dataInputConfig: string
    nearestModelName: string
    productID: string
  supportedContentTypes:
  - string
  supportedRealtimeInferenceInstanceTypes:
  - string
  supportedResponseMIMETypes:
  - string
  supportedTransformInstanceTypes:
  - string
metadataProperties: 
  commitID: string
  generatedBy: string
  projectID: string
  repository: string
modelApprovalStatus: string
modelMetrics: 
  bias: 
    postTrainingReport: 
      contentDigest: string
      contentType: string
      s3URI: string
    preTrainingReport: 
      contentDigest: string
      contentType: string
      s3URI: string
    report: 
      contentDigest: string
      contentType: string
      s3URI: string
  explainability: 
    report: 
      contentDigest: string
      contentType: string
      s3URI: string
  modelDataQuality: 
    constraints: 
      contentDigest: string
      contentType: string
      s3URI: string
    statistics: 
      contentDigest: string
      contentType: string
      s3URI: string
  modelQuality: 
    constraints: 
      contentDigest: string
      contentType: string
      s3URI: string
    statistics: 
      contentDigest: string
      contentType: string
      s3URI: string
modelPackageDescription: string
modelPackageGroupName: string
modelPackageName: string
samplePayloadURL: string
skipModelValidation: string
sourceAlgorithmSpecification: 
  sourceAlgorithms:
  - algorithmName: string
    modelDataURL: string
tags:
- key: string
  value: string
task: string
validationSpecification: 
  validationProfiles:
  - profileName: string
    transformJobDefinition: 
      batchStrategy: string
      environment: {}
      maxConcurrentTransforms: integer
      maxPayloadInMB: integer
      transformInput: 
        compressionType: string
        contentType: string
        dataSource: 
          s3DataSource: 
            s3DataType: string
            s3URI: string
        splitType: string
      transformOutput: 
        accept: string
        assembleWith: string
        kmsKeyID: string
        s3OutputPath: string
      transformResources: 
        instanceCount: integer
        instanceType: string
        volumeKMSKeyID: string
  validationRole: string

Field	Description
additionalInferenceSpecifications Optional	array An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
additionalInferenceSpecifications.[] Required	object A structure of additional Inference Specification. Additional Inference Specification
specifies details about inference jobs that can be run with models based
on this model package
additionalInferenceSpecifications.[].containers.[] Required	object Describes the Docker container for the model package.
additionalInferenceSpecifications.[].containers.[].additionalS3DataSource.compressionType Optional	string
additionalInferenceSpecifications.[].containers.[].additionalS3DataSource.s3DataType Optional	string
additionalInferenceSpecifications.[].containers.[].additionalS3DataSource.s3URI Optional	string
additionalInferenceSpecifications.[].containers.[].containerHostname Optional	string
additionalInferenceSpecifications.[].containers.[].environment Optional	object
additionalInferenceSpecifications.[].containers.[].framework Optional	string
additionalInferenceSpecifications.[].containers.[].frameworkVersion Optional	string
additionalInferenceSpecifications.[].containers.[].image Optional	string
additionalInferenceSpecifications.[].containers.[].imageDigest Optional	string
additionalInferenceSpecifications.[].containers.[].modelDataURL Optional	string
additionalInferenceSpecifications.[].containers.[].modelInput Optional	object Input object for the model.
additionalInferenceSpecifications.[].containers.[].modelInput.dataInputConfig Optional	string
additionalInferenceSpecifications.[].containers.[].nearestModelName Optional	string
additionalInferenceSpecifications.[].containers.[].productID Optional	string
additionalInferenceSpecifications.[].description Optional	string
additionalInferenceSpecifications.[].name Optional	string
additionalInferenceSpecifications.[].supportedContentTypes Optional	array
additionalInferenceSpecifications.[].supportedContentTypes.[] Required	string
additionalInferenceSpecifications.[].supportedRealtimeInferenceInstanceTypes.[] Required	string
additionalInferenceSpecifications.[].supportedResponseMIMETypes.[] Required	string
additionalInferenceSpecifications.[].supportedTransformInstanceTypes.[] Required	string
certifyForMarketplace Optional	boolean Whether to certify the model package for listing on Amazon Web Services Marketplace. This parameter is optional for unversioned models, and does not apply to versioned models.
clientToken Optional	string A unique token that guarantees that the call to this API is idempotent.
customerMetadataProperties Optional	object The metadata properties associated with the model package versions.
domain Optional	string The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
driftCheckBaselines Optional	object Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines (https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detection) in the Amazon SageMaker Developer Guide.
driftCheckBaselines.bias Optional	object Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
driftCheckBaselines.bias.configFile Optional	object Contains details regarding the file source.
driftCheckBaselines.bias.configFile.contentDigest Optional	string
driftCheckBaselines.bias.configFile.contentType Optional	string
driftCheckBaselines.bias.configFile.s3URI Optional	string
driftCheckBaselines.bias.postTrainingConstraints Optional	object Details about the metrics source.
driftCheckBaselines.bias.postTrainingConstraints.contentDigest Optional	string
driftCheckBaselines.bias.postTrainingConstraints.contentType Optional	string
driftCheckBaselines.bias.postTrainingConstraints.s3URI Optional	string
driftCheckBaselines.bias.preTrainingConstraints Optional	object Details about the metrics source.
driftCheckBaselines.bias.preTrainingConstraints.contentDigest Optional	string
driftCheckBaselines.bias.preTrainingConstraints.contentType Optional	string
driftCheckBaselines.bias.preTrainingConstraints.s3URI Optional	string
driftCheckBaselines.explainability Optional	object Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
driftCheckBaselines.explainability.configFile Optional	object Contains details regarding the file source.
driftCheckBaselines.explainability.configFile.contentDigest Optional	string
driftCheckBaselines.explainability.configFile.contentType Optional	string
driftCheckBaselines.explainability.configFile.s3URI Optional	string
driftCheckBaselines.explainability.constraints Optional	object Details about the metrics source.
driftCheckBaselines.explainability.constraints.contentDigest Optional	string
driftCheckBaselines.explainability.constraints.contentType Optional	string
driftCheckBaselines.explainability.constraints.s3URI Optional	string
driftCheckBaselines.modelDataQuality Optional	object Represents the drift check data quality baselines that can be used when the model monitor is set using the model package.
driftCheckBaselines.modelDataQuality.constraints Optional	object Details about the metrics source.
driftCheckBaselines.modelDataQuality.constraints.contentDigest Optional	string
driftCheckBaselines.modelDataQuality.constraints.contentType Optional	string
driftCheckBaselines.modelDataQuality.constraints.s3URI Optional	string
driftCheckBaselines.modelDataQuality.statistics Optional	object Details about the metrics source.
driftCheckBaselines.modelDataQuality.statistics.contentDigest Optional	string
driftCheckBaselines.modelDataQuality.statistics.contentType Optional	string
driftCheckBaselines.modelDataQuality.statistics.s3URI Optional	string
driftCheckBaselines.modelQuality Optional	object Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
driftCheckBaselines.modelQuality.constraints Optional	object Details about the metrics source.
driftCheckBaselines.modelQuality.constraints.contentDigest Optional	string
driftCheckBaselines.modelQuality.constraints.contentType Optional	string
driftCheckBaselines.modelQuality.constraints.s3URI Optional	string
driftCheckBaselines.modelQuality.statistics Optional	object Details about the metrics source.
driftCheckBaselines.modelQuality.statistics.contentDigest Optional	string
driftCheckBaselines.modelQuality.statistics.contentType Optional	string
driftCheckBaselines.modelQuality.statistics.s3URI Optional	string
inferenceSpecification Optional	object Specifies details about inference jobs that can be run with models based on this model package, including the following: * The Amazon ECR paths of containers that contain the inference code and model artifacts. * The instance types that the model package supports for transform jobs and real-time endpoints used for inference. * The input and output content formats that the model package supports for inference.
inferenceSpecification.containers Optional	array
inferenceSpecification.containers.[] Required	object Describes the Docker container for the model package.
inferenceSpecification.containers.[].additionalS3DataSource.compressionType Optional	string
inferenceSpecification.containers.[].additionalS3DataSource.s3DataType Optional	string
inferenceSpecification.containers.[].additionalS3DataSource.s3URI Optional	string
inferenceSpecification.containers.[].containerHostname Optional	string
inferenceSpecification.containers.[].environment Optional	object
inferenceSpecification.containers.[].framework Optional	string
inferenceSpecification.containers.[].frameworkVersion Optional	string
inferenceSpecification.containers.[].image Optional	string
inferenceSpecification.containers.[].imageDigest Optional	string
inferenceSpecification.containers.[].modelDataURL Optional	string
inferenceSpecification.containers.[].modelInput Optional	object Input object for the model.
inferenceSpecification.containers.[].modelInput.dataInputConfig Optional	string
inferenceSpecification.containers.[].nearestModelName Optional	string
inferenceSpecification.containers.[].productID Optional	string
inferenceSpecification.supportedContentTypes Optional	array
inferenceSpecification.supportedContentTypes.[] Required	string
inferenceSpecification.supportedRealtimeInferenceInstanceTypes.[] Required	string
inferenceSpecification.supportedResponseMIMETypes.[] Required	string
inferenceSpecification.supportedTransformInstanceTypes.[] Required	string
metadataProperties.commitID Optional	string
metadataProperties.generatedBy Optional	string
metadataProperties.projectID Optional	string
metadataProperties.repository Optional	string
modelApprovalStatus Optional	string Whether the model is approved for deployment. This parameter is optional for versioned models, and does not apply to unversioned models. For versioned models, the value of this parameter must be set to Approved to deploy the model.
modelMetrics Optional	object A structure that contains model metrics reports.
modelMetrics.bias Optional	object Contains bias metrics for a model.
modelMetrics.bias.postTrainingReport Optional	object Details about the metrics source.
modelMetrics.bias.postTrainingReport.contentDigest Optional	string
modelMetrics.bias.postTrainingReport.contentType Optional	string
modelMetrics.bias.postTrainingReport.s3URI Optional	string
modelMetrics.bias.preTrainingReport Optional	object Details about the metrics source.
modelMetrics.bias.preTrainingReport.contentDigest Optional	string
modelMetrics.bias.preTrainingReport.contentType Optional	string
modelMetrics.bias.preTrainingReport.s3URI Optional	string
modelMetrics.bias.report Optional	object Details about the metrics source.
modelMetrics.bias.report.contentDigest Optional	string
modelMetrics.bias.report.contentType Optional	string
modelMetrics.bias.report.s3URI Optional	string
modelMetrics.explainability Optional	object Contains explainability metrics for a model.
modelMetrics.explainability.report Optional	object Details about the metrics source.
modelMetrics.explainability.report.contentDigest Optional	string
modelMetrics.explainability.report.contentType Optional	string
modelMetrics.explainability.report.s3URI Optional	string
modelMetrics.modelDataQuality Optional	object Data quality constraints and statistics for a model.
modelMetrics.modelDataQuality.constraints Optional	object Details about the metrics source.
modelMetrics.modelDataQuality.constraints.contentDigest Optional	string
modelMetrics.modelDataQuality.constraints.contentType Optional	string
modelMetrics.modelDataQuality.constraints.s3URI Optional	string
modelMetrics.modelDataQuality.statistics Optional	object Details about the metrics source.
modelMetrics.modelDataQuality.statistics.contentDigest Optional	string
modelMetrics.modelDataQuality.statistics.contentType Optional	string
modelMetrics.modelDataQuality.statistics.s3URI Optional	string
modelMetrics.modelQuality Optional	object Model quality statistics and constraints.
modelMetrics.modelQuality.constraints Optional	object Details about the metrics source.
modelMetrics.modelQuality.constraints.contentDigest Optional	string
modelMetrics.modelQuality.constraints.contentType Optional	string
modelMetrics.modelQuality.constraints.s3URI Optional	string
modelMetrics.modelQuality.statistics Optional	object Details about the metrics source.
modelMetrics.modelQuality.statistics.contentDigest Optional	string
modelMetrics.modelQuality.statistics.contentType Optional	string
modelMetrics.modelQuality.statistics.s3URI Optional	string
modelPackageDescription Optional	string A description of the model package.
modelPackageGroupName Optional	string The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to. This parameter is required for versioned models, and does not apply to unversioned models.
modelPackageName Optional	string The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen). This parameter is required for unversioned models. It is not applicable to versioned models.
samplePayloadURL Optional	string The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint (https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_runtime_InvokeEndpoint.html#API_runtime_InvokeEndpoint_RequestSyntax) call.
skipModelValidation Optional	string Indicates if you want to skip model validation.
sourceAlgorithmSpecification Optional	object Details about the algorithm that was used to create the model package.
sourceAlgorithmSpecification.sourceAlgorithms Optional	array
sourceAlgorithmSpecification.sourceAlgorithms.[] Required	object Specifies an algorithm that was used to create the model package. The algorithm
must be either an algorithm resource in your SageMaker account or an algorithm
in Amazon Web Services Marketplace that you are subscribed to.
sourceAlgorithmSpecification.sourceAlgorithms.[].modelDataURL Optional	string
tags Optional	array A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html) in the Amazon Web Services General Reference Guide. If you supply ModelPackageGroupName, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply a tag argument.
tags.[] Required	object A tag object that consists of a key and an optional value, used to manage
metadata for SageMaker Amazon Web Services resources.

You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags (https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AddTags.html).

For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy (https://d1.awsstatic.com/whitepapers/aws-tagging-best-practices.pdf). || tags.[].key
Optional | string
| | tags.[].value
Optional | string
| | task
Optional | string
The machine learning task your model package accomplishes. Common machine
learning tasks include object detection and image classification. The following
tasks are supported by Inference Recommender: “IMAGE_CLASSIFICATION” | “OBJECT_DETECTION”
| “TEXT_GENERATION” |“IMAGE_SEGMENTATION” | “FILL_MASK” | “CLASSIFICATION”
| “REGRESSION” | “OTHER”.

Specify “OTHER” if none of the tasks listed fit your use case. | | validationSpecification
Optional | object
Specifies configurations for one or more transform jobs that SageMaker runs
to test the model package. | | validationSpecification.validationProfiles
Optional | array
| | validationSpecification.validationProfiles.[]
Required | object
Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.

The data provided in the validation profile is made available to your buyers on Amazon Web Services Marketplace. || validationSpecification.validationProfiles.[].profileName
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition
Optional | object
Defines the input needed to run a transform job using the inference specification
specified in the algorithm. | | validationSpecification.validationProfiles.[].transformJobDefinition.batchStrategy
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.environment
Optional | object
| | validationSpecification.validationProfiles.[].transformJobDefinition.maxConcurrentTransforms
Optional | integer
| | validationSpecification.validationProfiles.[].transformJobDefinition.maxPayloadInMB
Optional | integer
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformInput
Optional | object
Describes the input source of a transform job and the way the transform job
consumes it. | | validationSpecification.validationProfiles.[].transformJobDefinition.transformInput.compressionType
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformInput.contentType
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformInput.dataSource
Optional | object
Describes the location of the channel data. | | validationSpecification.validationProfiles.[].transformJobDefinition.transformInput.dataSource.s3DataSource
Optional | object
Describes the S3 data source. | | validationSpecification.validationProfiles.[].transformJobDefinition.transformInput.dataSource.s3DataSource.s3DataType
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformInput.dataSource.s3DataSource.s3URI
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformInput.splitType
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformOutput
Optional | object
Describes the results of a transform job. | | validationSpecification.validationProfiles.[].transformJobDefinition.transformOutput.accept
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformOutput.assembleWith
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformOutput.kmsKeyID
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformOutput.s3OutputPath
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformResources
Optional | object
Describes the resources, including ML instance types and ML instance count,
to use for transform job. | | validationSpecification.validationProfiles.[].transformJobDefinition.transformResources.instanceCount
Optional | integer
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformResources.instanceType
Optional | string
| | validationSpecification.validationProfiles.[].transformJobDefinition.transformResources.volumeKMSKeyID
Optional | string
| | validationSpecification.validationRole
Optional | string
|

Status

ackResourceMetadata: 
  arn: string
  ownerAccountID: string
  region: string
conditions:
- lastTransitionTime: string
  message: string
  reason: string
  status: string
  type: string
creationTime: string
lastModifiedTime: string
modelPackageStatus: string
modelPackageStatusDetails: 
  imageScanStatuses:
  - failureReason: string
    name: string
    status: string
  validationStatuses:
  - failureReason: string
    name: string
    status: string

Field	Description
ackResourceMetadata Optional	object All CRs managed by ACK have a common `Status.ACKResourceMetadata` member that is used to contain resource sync state, account ownership, constructed ARN for the resource
ackResourceMetadata.arn Optional	string ARN is the Amazon Resource Name for the resource. This is a globally-unique identifier and is set only by the ACK service controller once the controller has orchestrated the creation of the resource OR when it has verified that an “adopted” resource (a resource where the ARN annotation was set by the Kubernetes user on the CR) exists and matches the supplied CR’s Spec field values. TODO(vijat@): Find a better strategy for resources that do not have ARN in CreateOutputResponse https://github.com/aws/aws-controllers-k8s/issues/270
ackResourceMetadata.ownerAccountID Required	string OwnerAccountID is the AWS Account ID of the account that owns the backend AWS service API resource.
ackResourceMetadata.region Required	string Region is the AWS region in which the resource exists or will exist.
conditions Optional	array All CRS managed by ACK have a common `Status.Conditions` member that contains a collection of `ackv1alpha1.Condition` objects that describe the various terminal states of the CR and its backend AWS service API resource
conditions.[] Required	object Condition is the common struct used by all CRDs managed by ACK service
controllers to indicate terminal states of the CR and its backend AWS
service API resource
conditions.[].message Optional	string A human readable message indicating details about the transition.
conditions.[].reason Optional	string The reason for the condition’s last transition.
conditions.[].status Optional	string Status of the condition, one of True, False, Unknown.
conditions.[].type Optional	string Type is the type of the Condition
creationTime Optional	string A timestamp specifying when the model package was created.
lastModifiedTime Optional	string The last time that the model package was modified.
modelPackageStatus Optional	string The current status of the model package.
modelPackageStatusDetails Optional	object Details about the current status of the model package.
modelPackageStatusDetails.imageScanStatuses Optional	array
modelPackageStatusDetails.imageScanStatuses.[] Required	object Represents the overall status of a model package.
modelPackageStatusDetails.imageScanStatuses.[].name Optional	string
modelPackageStatusDetails.imageScanStatuses.[].status Optional	string
modelPackageStatusDetails.validationStatuses Optional	array
modelPackageStatusDetails.validationStatuses.[] Required	object Represents the overall status of a model package.
modelPackageStatusDetails.validationStatuses.[].name Optional	string
modelPackageStatusDetails.validationStatuses.[].status Optional	string

ModelPackage

Metadata#

Spec#

Status#

Metadata

Spec

Status