CfnModelPackageProps

class aws_cdk.aws_sagemaker.CfnModelPackageProps(*, additional_inference_specification_definition=None, additional_inference_specifications=None, additional_inference_specifications_to_add=None, approval_description=None, certify_for_marketplace=None, client_token=None, created_by=None, customer_metadata_properties=None, domain=None, drift_check_baselines=None, environment=None, inference_specification=None, last_modified_by=None, last_modified_time=None, metadata_properties=None, model_approval_status=None, model_metrics=None, model_package_description=None, model_package_group_name=None, model_package_name=None, model_package_status_details=None, model_package_status_item=None, model_package_version=None, sample_payload_url=None, source_algorithm_specification=None, tags=None, task=None, validation_specification=None)

Bases: object

Properties for defining a CfnModelPackage.

Parameters
  • additional_inference_specification_definition (Union[IResolvable, AdditionalInferenceSpecificationDefinitionProperty, Dict[str, Any], None]) – 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

  • additional_inference_specifications (Union[IResolvable, Sequence[Union[IResolvable, AdditionalInferenceSpecificationDefinitionProperty, Dict[str, Any]]], None]) – An array of additional Inference Specification objects.

  • additional_inference_specifications_to_add (Union[IResolvable, Sequence[Union[IResolvable, AdditionalInferenceSpecificationDefinitionProperty, Dict[str, Any]]], None]) – 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.

  • approval_description (Optional[str]) – A description provided when the model approval is set.

  • certify_for_marketplace (Union[bool, IResolvable, None]) – Whether the model package is to be certified to be listed on AWS Marketplace. For information about listing model packages on AWS Marketplace, see List Your Algorithm or Model Package on AWS Marketplace .

  • client_token (Optional[str]) – A unique token that guarantees that the call to this API is idempotent.

  • created_by (Union[IResolvable, UserContextProperty, Dict[str, Any], None]) – Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.

  • customer_metadata_properties (Union[IResolvable, Mapping[str, str], None]) – The metadata properties for the model package.

  • domain (Optional[str]) – The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.

  • drift_check_baselines (Union[IResolvable, DriftCheckBaselinesProperty, Dict[str, Any], None]) – Represents the drift check baselines that can be used when the model monitor is set using the model package.

  • environment (Union[IResolvable, Mapping[str, str], None]) – The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.

  • inference_specification (Union[IResolvable, InferenceSpecificationProperty, Dict[str, Any], None]) – Defines how to perform inference generation after a training job is run.

  • last_modified_by (Union[IResolvable, UserContextProperty, Dict[str, Any], None]) – Information about the user who created or modified an experiment, trial, trial component, lineage group, or project.

  • last_modified_time (Optional[str]) – The last time the model package was modified.

  • metadata_properties (Union[IResolvable, MetadataPropertiesProperty, Dict[str, Any], None]) – Metadata properties of the tracking entity, trial, or trial component.

  • model_approval_status (Optional[str]) – 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.

  • model_metrics (Union[IResolvable, ModelMetricsProperty, Dict[str, Any], None]) – Metrics for the model.

  • model_package_description (Optional[str]) – The description of the model package.

  • model_package_group_name (Optional[str]) – The model group to which the model belongs.

  • model_package_name (Optional[str]) – The name of the model.

  • model_package_status_details (Union[IResolvable, ModelPackageStatusDetailsProperty, Dict[str, Any], None]) – Specifies the validation and image scan statuses of the model package.

  • model_package_status_item (Union[IResolvable, ModelPackageStatusItemProperty, Dict[str, Any], None]) – Represents the overall status of a model package.

  • model_package_version (Union[int, float, None]) – The version number of a versioned model.

  • sample_payload_url (Optional[str]) – 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).

  • source_algorithm_specification (Union[IResolvable, SourceAlgorithmSpecificationProperty, Dict[str, Any], None]) – A list of algorithms that were used to create a model package.

  • tags (Optional[Sequence[Union[CfnTag, Dict[str, Any]]]]) – A list of the tags associated with the model package. For more information, see Tagging AWS resources in the AWS General Reference Guide .

  • task (Optional[str]) – The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.

  • validation_specification (Union[IResolvable, ValidationSpecificationProperty, Dict[str, Any], None]) – Specifies batch transform jobs that SageMaker runs to validate your model package.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html

ExampleMetadata

fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
import aws_cdk.aws_sagemaker as sagemaker

# model_input: Any

cfn_model_package_props = sagemaker.CfnModelPackageProps(
    additional_inference_specification_definition=sagemaker.CfnModelPackage.AdditionalInferenceSpecificationDefinitionProperty(
        containers=[sagemaker.CfnModelPackage.ModelPackageContainerDefinitionProperty(
            image="image",

            # the properties below are optional
            container_hostname="containerHostname",
            environment={
                "environment_key": "environment"
            },
            framework="framework",
            framework_version="frameworkVersion",
            image_digest="imageDigest",
            model_data_url="modelDataUrl",
            model_input=model_input,
            nearest_model_name="nearestModelName",
            product_id="productId"
        )],
        name="name",

        # the properties below are optional
        description="description",
        supported_content_types=["supportedContentTypes"],
        supported_realtime_inference_instance_types=["supportedRealtimeInferenceInstanceTypes"],
        supported_response_mime_types=["supportedResponseMimeTypes"],
        supported_transform_instance_types=["supportedTransformInstanceTypes"]
    ),
    additional_inference_specifications=[sagemaker.CfnModelPackage.AdditionalInferenceSpecificationDefinitionProperty(
        containers=[sagemaker.CfnModelPackage.ModelPackageContainerDefinitionProperty(
            image="image",

            # the properties below are optional
            container_hostname="containerHostname",
            environment={
                "environment_key": "environment"
            },
            framework="framework",
            framework_version="frameworkVersion",
            image_digest="imageDigest",
            model_data_url="modelDataUrl",
            model_input=model_input,
            nearest_model_name="nearestModelName",
            product_id="productId"
        )],
        name="name",

        # the properties below are optional
        description="description",
        supported_content_types=["supportedContentTypes"],
        supported_realtime_inference_instance_types=["supportedRealtimeInferenceInstanceTypes"],
        supported_response_mime_types=["supportedResponseMimeTypes"],
        supported_transform_instance_types=["supportedTransformInstanceTypes"]
    )],
    additional_inference_specifications_to_add=[sagemaker.CfnModelPackage.AdditionalInferenceSpecificationDefinitionProperty(
        containers=[sagemaker.CfnModelPackage.ModelPackageContainerDefinitionProperty(
            image="image",

            # the properties below are optional
            container_hostname="containerHostname",
            environment={
                "environment_key": "environment"
            },
            framework="framework",
            framework_version="frameworkVersion",
            image_digest="imageDigest",
            model_data_url="modelDataUrl",
            model_input=model_input,
            nearest_model_name="nearestModelName",
            product_id="productId"
        )],
        name="name",

        # the properties below are optional
        description="description",
        supported_content_types=["supportedContentTypes"],
        supported_realtime_inference_instance_types=["supportedRealtimeInferenceInstanceTypes"],
        supported_response_mime_types=["supportedResponseMimeTypes"],
        supported_transform_instance_types=["supportedTransformInstanceTypes"]
    )],
    approval_description="approvalDescription",
    certify_for_marketplace=False,
    client_token="clientToken",
    created_by=sagemaker.CfnModelPackage.UserContextProperty(
        domain_id="domainId",
        user_profile_arn="userProfileArn",
        user_profile_name="userProfileName"
    ),
    customer_metadata_properties={
        "customer_metadata_properties_key": "customerMetadataProperties"
    },
    domain="domain",
    drift_check_baselines=sagemaker.CfnModelPackage.DriftCheckBaselinesProperty(
        bias=sagemaker.CfnModelPackage.DriftCheckBiasProperty(
            config_file=sagemaker.CfnModelPackage.FileSourceProperty(
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest",
                content_type="contentType"
            ),
            post_training_constraints=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            ),
            pre_training_constraints=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            )
        ),
        explainability=sagemaker.CfnModelPackage.DriftCheckExplainabilityProperty(
            config_file=sagemaker.CfnModelPackage.FileSourceProperty(
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest",
                content_type="contentType"
            ),
            constraints=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            )
        ),
        model_data_quality=sagemaker.CfnModelPackage.DriftCheckModelDataQualityProperty(
            constraints=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            ),
            statistics=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            )
        ),
        model_quality=sagemaker.CfnModelPackage.DriftCheckModelQualityProperty(
            constraints=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            ),
            statistics=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            )
        )
    ),
    environment={
        "environment_key": "environment"
    },
    inference_specification=sagemaker.CfnModelPackage.InferenceSpecificationProperty(
        containers=[sagemaker.CfnModelPackage.ModelPackageContainerDefinitionProperty(
            image="image",

            # the properties below are optional
            container_hostname="containerHostname",
            environment={
                "environment_key": "environment"
            },
            framework="framework",
            framework_version="frameworkVersion",
            image_digest="imageDigest",
            model_data_url="modelDataUrl",
            model_input=model_input,
            nearest_model_name="nearestModelName",
            product_id="productId"
        )],
        supported_content_types=["supportedContentTypes"],
        supported_response_mime_types=["supportedResponseMimeTypes"],

        # the properties below are optional
        supported_realtime_inference_instance_types=["supportedRealtimeInferenceInstanceTypes"],
        supported_transform_instance_types=["supportedTransformInstanceTypes"]
    ),
    last_modified_by=sagemaker.CfnModelPackage.UserContextProperty(
        domain_id="domainId",
        user_profile_arn="userProfileArn",
        user_profile_name="userProfileName"
    ),
    last_modified_time="lastModifiedTime",
    metadata_properties=sagemaker.CfnModelPackage.MetadataPropertiesProperty(
        commit_id="commitId",
        generated_by="generatedBy",
        project_id="projectId",
        repository="repository"
    ),
    model_approval_status="modelApprovalStatus",
    model_metrics=sagemaker.CfnModelPackage.ModelMetricsProperty(
        bias=sagemaker.CfnModelPackage.BiasProperty(
            post_training_report=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            ),
            pre_training_report=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            ),
            report=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            )
        ),
        explainability=sagemaker.CfnModelPackage.ExplainabilityProperty(
            report=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            )
        ),
        model_data_quality=sagemaker.CfnModelPackage.ModelDataQualityProperty(
            constraints=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            ),
            statistics=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            )
        ),
        model_quality=sagemaker.CfnModelPackage.ModelQualityProperty(
            constraints=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            ),
            statistics=sagemaker.CfnModelPackage.MetricsSourceProperty(
                content_type="contentType",
                s3_uri="s3Uri",

                # the properties below are optional
                content_digest="contentDigest"
            )
        )
    ),
    model_package_description="modelPackageDescription",
    model_package_group_name="modelPackageGroupName",
    model_package_name="modelPackageName",
    model_package_status_details=sagemaker.CfnModelPackage.ModelPackageStatusDetailsProperty(
        validation_statuses=[sagemaker.CfnModelPackage.ModelPackageStatusItemProperty(
            name="name",
            status="status",

            # the properties below are optional
            failure_reason="failureReason"
        )],

        # the properties below are optional
        image_scan_statuses=[sagemaker.CfnModelPackage.ModelPackageStatusItemProperty(
            name="name",
            status="status",

            # the properties below are optional
            failure_reason="failureReason"
        )]
    ),
    model_package_status_item=sagemaker.CfnModelPackage.ModelPackageStatusItemProperty(
        name="name",
        status="status",

        # the properties below are optional
        failure_reason="failureReason"
    ),
    model_package_version=123,
    sample_payload_url="samplePayloadUrl",
    source_algorithm_specification=sagemaker.CfnModelPackage.SourceAlgorithmSpecificationProperty(
        source_algorithms=[sagemaker.CfnModelPackage.SourceAlgorithmProperty(
            algorithm_name="algorithmName",

            # the properties below are optional
            model_data_url="modelDataUrl"
        )]
    ),
    tags=[CfnTag(
        key="key",
        value="value"
    )],
    task="task",
    validation_specification=sagemaker.CfnModelPackage.ValidationSpecificationProperty(
        validation_profiles=[sagemaker.CfnModelPackage.ValidationProfileProperty(
            profile_name="profileName",
            transform_job_definition=sagemaker.CfnModelPackage.TransformJobDefinitionProperty(
                transform_input=sagemaker.CfnModelPackage.TransformInputProperty(
                    data_source=sagemaker.CfnModelPackage.DataSourceProperty(
                        s3_data_source=sagemaker.CfnModelPackage.S3DataSourceProperty(
                            s3_data_type="s3DataType",
                            s3_uri="s3Uri"
                        )
                    ),

                    # the properties below are optional
                    compression_type="compressionType",
                    content_type="contentType",
                    split_type="splitType"
                ),
                transform_output=sagemaker.CfnModelPackage.TransformOutputProperty(
                    s3_output_path="s3OutputPath",

                    # the properties below are optional
                    accept="accept",
                    assemble_with="assembleWith",
                    kms_key_id="kmsKeyId"
                ),
                transform_resources=sagemaker.CfnModelPackage.TransformResourcesProperty(
                    instance_count=123,
                    instance_type="instanceType",

                    # the properties below are optional
                    volume_kms_key_id="volumeKmsKeyId"
                ),

                # the properties below are optional
                batch_strategy="batchStrategy",
                environment={
                    "environment_key": "environment"
                },
                max_concurrent_transforms=123,
                max_payload_in_mb=123
            )
        )],
        validation_role="validationRole"
    )
)

Attributes

additional_inference_specification_definition

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-additionalinferencespecificationdefinition

additional_inference_specifications

An array of additional Inference Specification objects.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-additionalinferencespecifications

additional_inference_specifications_to_add

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.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-additionalinferencespecificationstoadd

approval_description

A description provided when the model approval is set.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-approvaldescription

certify_for_marketplace

Whether the model package is to be certified to be listed on AWS Marketplace.

For information about listing model packages on AWS Marketplace, see List Your Algorithm or Model Package on AWS Marketplace .

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-certifyformarketplace

client_token

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-clienttoken

created_by

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-createdby

customer_metadata_properties

The metadata properties for the model package.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-customermetadataproperties

domain

The machine learning domain of your model package and its components.

Common machine learning domains include computer vision and natural language processing.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-domain

drift_check_baselines

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-driftcheckbaselines

environment

The environment variables to set in the Docker container.

Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-environment

inference_specification

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-inferencespecification

last_modified_by

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-lastmodifiedby

last_modified_time

The last time the model package was modified.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-lastmodifiedtime

metadata_properties

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-metadataproperties

model_approval_status

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.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-modelapprovalstatus

model_metrics

Metrics for the model.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-modelmetrics

model_package_description

The description of the model package.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-modelpackagedescription

model_package_group_name

The model group to which the model belongs.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-modelpackagegroupname

model_package_name

The name of the model.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-modelpackagename

model_package_status_details

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-modelpackagestatusdetails

model_package_status_item

Represents the overall status of a model package.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-modelpackagestatusitem

model_package_version

The version number of a versioned model.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-modelpackageversion

sample_payload_url

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).

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-samplepayloadurl

source_algorithm_specification

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-sourcealgorithmspecification

tags

A list of the tags associated with the model package.

For more information, see Tagging AWS resources in the AWS General Reference Guide .

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-tags

task

The machine learning task your model package accomplishes.

Common machine learning tasks include object detection and image classification.

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-task

validation_specification

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

Link

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-modelpackage.html#cfn-sagemaker-modelpackage-validationspecification