Documentation

A versioned model that can be deployed for SageMaker inference.

See: newModelPackage smart constructor.

Create a value of ModelPackage with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:additionalInferenceSpecifications:ModelPackage', modelPackage_additionalInferenceSpecifications - An array of additional Inference Specification objects.

$sel:approvalDescription:ModelPackage', modelPackage_approvalDescription - A description provided when the model approval is set.

$sel:certifyForMarketplace:ModelPackage', modelPackage_certifyForMarketplace - Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.

$sel:createdBy:ModelPackage', modelPackage_createdBy - Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.

$sel:creationTime:ModelPackage', modelPackage_creationTime - The time that the model package was created.

$sel:customerMetadataProperties:ModelPackage', modelPackage_customerMetadataProperties - The metadata properties for the model package.

$sel:domain:ModelPackage', modelPackage_domain - The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.

$sel:driftCheckBaselines:ModelPackage', modelPackage_driftCheckBaselines - Represents the drift check baselines that can be used when the model monitor is set using the model package.

$sel:inferenceSpecification:ModelPackage', modelPackage_inferenceSpecification - Defines how to perform inference generation after a training job is run.

$sel:lastModifiedBy:ModelPackage', modelPackage_lastModifiedBy - Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.

$sel:lastModifiedTime:ModelPackage', modelPackage_lastModifiedTime - The last time the model package was modified.

$sel:metadataProperties:ModelPackage', modelPackage_metadataProperties - Metadata properties of the tracking entity, trial, or trial component.

$sel:modelApprovalStatus:ModelPackage', modelPackage_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.

$sel:modelMetrics:ModelPackage', modelPackage_modelMetrics - Metrics for the model.

$sel:modelPackageArn:ModelPackage', modelPackage_modelPackageArn - The Amazon Resource Name (ARN) of the model package.

$sel:modelPackageDescription:ModelPackage', modelPackage_modelPackageDescription - The description of the model package.

$sel:modelPackageGroupName:ModelPackage', modelPackage_modelPackageGroupName - The model group to which the model belongs.

$sel:modelPackageName:ModelPackage', modelPackage_modelPackageName - The name of the model.

$sel:modelPackageStatus:ModelPackage', modelPackage_modelPackageStatus - The status of the model package. This can be one of the following values.

• PENDING - The model package is pending being created.
• IN_PROGRESS - The model package is in the process of being created.
• COMPLETED - The model package was successfully created.
• FAILED - The model package failed.
• DELETING - The model package is in the process of being deleted.

$sel:modelPackageStatusDetails:ModelPackage', modelPackage_modelPackageStatusDetails - Specifies the validation and image scan statuses of the model package.

$sel:modelPackageVersion:ModelPackage', modelPackage_modelPackageVersion - The version number of a versioned model.

$sel:samplePayloadUrl:ModelPackage', modelPackage_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).

$sel:sourceAlgorithmSpecification:ModelPackage', modelPackage_sourceAlgorithmSpecification - A list of algorithms that were used to create a model package.

$sel:tags:ModelPackage', modelPackage_tags - A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.

$sel:task:ModelPackage', modelPackage_task - The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.

$sel:validationSpecification:ModelPackage', modelPackage_validationSpecification - Specifies batch transform jobs that SageMaker runs to validate your model package.

An array of additional Inference Specification objects.

A description provided when the model approval is set.

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

Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.

The time that the model package was created.

The metadata properties for the model package.

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

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

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

Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.

The last time the model package was modified.

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

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.

Metrics for the model.

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

The description of the model package.

The model group to which the model belongs.

The name of the model.

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

• PENDING - The model package is pending being created.
• IN_PROGRESS - The model package is in the process of being created.
• COMPLETED - The model package was successfully created.
• FAILED - The model package failed.
• DELETING - The model package is in the process of being deleted.

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

The version number of a versioned model.

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).

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

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

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

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