ModelPackage ¶

class ModelPackage(TypedDict, closed=True):
    model_package_name: NotRequired["capo_sagemaker.types.entity_name.EntityName"]
    """<p>The name of the model package. The name can be as follows:</p> <ul> <li> <p>For a versioned model, the name is automatically generated by SageMaker Model Registry and follows the format '<code>ModelPackageGroupName/ModelPackageVersion</code>'.</p> </li> <li> <p>For an unversioned model, you must provide the name.</p> </li> </ul>"""
    model_package_group_name: NotRequired["capo_sagemaker.types.entity_name.EntityName"]
    """<p>The model group to which the model belongs.</p>"""
    model_package_version: NotRequired[
        "capo_sagemaker.types.model_package_version.ModelPackageVersion"
    ]
    """<p>The version number of a versioned model.</p>"""
    model_package_registration_type: NotRequired[
        "capo_sagemaker.types.model_package_registration_type.ModelPackageRegistrationType"
    ]
    """<p> The package registration type of the model package. </p>"""
    model_package_arn: NotRequired[
        "capo_sagemaker.types.model_package_arn.ModelPackageArn"
    ]
    """<p>The Amazon Resource Name (ARN) of the model package.</p>"""
    model_package_description: NotRequired[
        "capo_sagemaker.types.entity_description.EntityDescription"
    ]
    """<p>The description of the model package.</p>"""
    creation_time: NotRequired["capo_sagemaker.types.creation_time.CreationTime"]
    """<p>The time that the model package was created.</p>"""
    inference_specification: NotRequired[
        "capo_sagemaker.types.inference_specification.InferenceSpecification"
    ]
    """<p>Defines how to perform inference generation after a training job is run.</p>"""
    source_algorithm_specification: NotRequired[
        "capo_sagemaker.types.source_algorithm_specification.SourceAlgorithmSpecification"
    ]
    """<p>A list of algorithms that were used to create a model package.</p>"""
    validation_specification: NotRequired[
        "capo_sagemaker.types.model_package_validation_specification.ModelPackageValidationSpecification"
    ]
    """<p>Specifies batch transform jobs that SageMaker runs to validate your model package.</p>"""
    model_package_status: NotRequired[
        "capo_sagemaker.types.model_package_status.ModelPackageStatus"
    ]
    """<p>The status of the model package. This can be one of the following values.</p> <ul> <li> <p> <code>PENDING</code> - The model package is pending being created.</p> </li> <li> <p> <code>IN_PROGRESS</code> - The model package is in the process of being created.</p> </li> <li> <p> <code>COMPLETED</code> - The model package was successfully created.</p> </li> <li> <p> <code>FAILED</code> - The model package failed.</p> </li> <li> <p> <code>DELETING</code> - The model package is in the process of being deleted.</p> </li> </ul>"""
    model_package_status_details: NotRequired[
        "capo_sagemaker.types.model_package_status_details.ModelPackageStatusDetails"
    ]
    """<p>Specifies the validation and image scan statuses of the model package.</p>"""
    certify_for_marketplace: NotRequired[
        "capo_sagemaker.types.certify_for_marketplace.CertifyForMarketplace"
    ]
    """<p>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 <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-mkt-list.html">List Your Algorithm or Model Package on Amazon Web Services Marketplace</a>.</p>"""
    model_approval_status: NotRequired[
        "capo_sagemaker.types.model_approval_status.ModelApprovalStatus"
    ]
    """<p>The approval status of the model. This can be one of the following values.</p> <ul> <li> <p> <code>APPROVED</code> - The model is approved</p> </li> <li> <p> <code>REJECTED</code> - The model is rejected.</p> </li> <li> <p> <code>PENDING_MANUAL_APPROVAL</code> - The model is waiting for manual approval.</p> </li> </ul>"""
    created_by: NotRequired["capo_sagemaker.types.user_context.UserContext"]
    """<p>Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.</p>"""
    metadata_properties: NotRequired[
        "capo_sagemaker.types.metadata_properties.MetadataProperties"
    ]
    """<p>Metadata properties of the tracking entity, trial, or trial component.</p>"""
    model_metrics: NotRequired["capo_sagemaker.types.model_metrics.ModelMetrics"]
    """<p>Metrics for the model.</p>"""
    last_modified_time: NotRequired["capo_sagemaker.types.timestamp.Timestamp"]
    """<p>The last time the model package was modified.</p>"""
    last_modified_by: NotRequired["capo_sagemaker.types.user_context.UserContext"]
    """<p>Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.</p>"""
    approval_description: NotRequired[
        "capo_sagemaker.types.approval_description.ApprovalDescription"
    ]
    """<p>A description provided when the model approval is set.</p>"""
    domain: NotRequired["capo_sagemaker.types.string.String"]
    """<p>The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.</p>"""
    task: NotRequired["capo_sagemaker.types.string.String"]
    """<p>The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.</p>"""
    sample_payload_url: NotRequired["capo_sagemaker.types.string.String"]
    """<p>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).</p>"""
    additional_inference_specifications: NotRequired[
        "capo_sagemaker.types.additional_inference_specifications.AdditionalInferenceSpecifications"
    ]
    """<p>An array of additional Inference Specification objects.</p>"""
    source_uri: NotRequired[
        "capo_sagemaker.types.model_package_source_uri.ModelPackageSourceUri"
    ]
    """<p>The URI of the source for the model package.</p>"""
    security_config: NotRequired[
        "capo_sagemaker.types.model_package_security_config.ModelPackageSecurityConfig"
    ]
    model_card: NotRequired[
        "capo_sagemaker.types.model_package_model_card.ModelPackageModelCard"
    ]
    model_life_cycle: NotRequired[
        "capo_sagemaker.types.model_life_cycle.ModelLifeCycle"
    ]
    """<p> A structure describing the current state of the model in its life cycle. </p>"""
    tags: NotRequired["capo_sagemaker.types.tag_list.TagList"]
    """<p>A list of the tags associated with the model package. For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a> in the <i>Amazon Web Services General Reference Guide</i>.</p>"""
    customer_metadata_properties: NotRequired[
        "capo_sagemaker.types.customer_metadata_map.CustomerMetadataMap"
    ]
    """<p>The metadata properties for the model package. </p>"""
    drift_check_baselines: NotRequired[
        "capo_sagemaker.types.drift_check_baselines.DriftCheckBaselines"
    ]
    """<p>Represents the drift check baselines that can be used when the model monitor is set using the model package.</p>"""
    skip_model_validation: NotRequired[
        "capo_sagemaker.types.skip_model_validation.SkipModelValidation"
    ]
    """<p>Indicates if you want to skip model validation.</p>"""