Builder
Properties
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.
Whether to certify the model package for listing on Amazon Web Services Marketplace.
A unique token that guarantees that the call to this API is idempotent.
The metadata properties associated with the model package versions.
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 in the Amazon SageMaker Developer Guide.
Specifies details about inference jobs that you can run with models based on this model package, including the following information:
Metadata properties of the tracking entity, trial, or trial component.
Whether the model is approved for deployment.
The model card associated with the model package. Since ModelPackageModelCard
is tied to a model package, it is a specific usage of a model card and its schema is simplified compared to the schema of ModelCard
. The ModelPackageModelCard
schema does not include model_package_details
, and model_overview
is composed of the model_creator
and model_artifact
properties. For more information about the model package model card schema, see Model package model card schema. For more information about the model card associated with the model package, see View the Details of a Model Version.
A structure describing the current state of the model in its life cycle.
A structure that contains model metrics reports.
A description of the model package.
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
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).
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 call.
The KMS Key ID (KMSKeyId
) used for encryption of model package information.
Indicates if you want to skip model validation.
Details about the algorithm that was used to create the model package.
A list of key value pairs associated with the model. 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. The following tasks are supported by Inference Recommender: "IMAGE_CLASSIFICATION"
| "OBJECT_DETECTION"
| "TEXT_GENERATION"
|"IMAGE_SEGMENTATION"
| "FILL_MASK"
| "CLASSIFICATION"
| "REGRESSION"
| "OTHER"
.
Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
Functions
construct an aws.sdk.kotlin.services.sagemaker.model.DriftCheckBaselines inside the given block
construct an aws.sdk.kotlin.services.sagemaker.model.InferenceSpecification inside the given block
construct an aws.sdk.kotlin.services.sagemaker.model.MetadataProperties inside the given block
construct an aws.sdk.kotlin.services.sagemaker.model.ModelPackageModelCard inside the given block
construct an aws.sdk.kotlin.services.sagemaker.model.ModelLifeCycle inside the given block
construct an aws.sdk.kotlin.services.sagemaker.model.ModelMetrics inside the given block
construct an aws.sdk.kotlin.services.sagemaker.model.ModelPackageSecurityConfig inside the given block
construct an aws.sdk.kotlin.services.sagemaker.model.SourceAlgorithmSpecification inside the given block
construct an aws.sdk.kotlin.services.sagemaker.model.ModelPackageValidationSpecification inside the given block