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AWS Native v0.109.0 published on Wednesday, Jun 26, 2024 by Pulumi
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aws-native.sagemaker.ModelPackage

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AWS Native is in preview. AWS Classic is fully supported.

AWS Native v0.109.0 published on Wednesday, Jun 26, 2024 by Pulumi
pulumi/pulumi-aws-native

    Resource Type definition for AWS::SageMaker::ModelPackage

    Create ModelPackage Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new ModelPackage(name: string, args?: ModelPackageArgs, opts?: CustomResourceOptions);
    @overload
def ModelPackage(resource_name: str,
                 args: Optional[ModelPackageArgs] = None,
                 opts: Optional[ResourceOptions] = None)

@overload
def ModelPackage(resource_name: str,
                 opts: Optional[ResourceOptions] = None,
                 additional_inference_specifications: Optional[Sequence[ModelPackageAdditionalInferenceSpecificationDefinitionArgs]] = None,
                 additional_inference_specifications_to_add: Optional[Sequence[ModelPackageAdditionalInferenceSpecificationDefinitionArgs]] = None,
                 approval_description: Optional[str] = None,
                 certify_for_marketplace: Optional[bool] = None,
                 client_token: Optional[str] = None,
                 customer_metadata_properties: Optional[ModelPackageCustomerMetadataPropertiesArgs] = None,
                 domain: Optional[str] = None,
                 drift_check_baselines: Optional[ModelPackageDriftCheckBaselinesArgs] = None,
                 inference_specification: Optional[ModelPackageInferenceSpecificationArgs] = None,
                 last_modified_time: Optional[str] = None,
                 metadata_properties: Optional[ModelPackageMetadataPropertiesArgs] = None,
                 model_approval_status: Optional[ModelPackageModelApprovalStatus] = None,
                 model_metrics: Optional[ModelPackageModelMetricsArgs] = None,
                 model_package_description: Optional[str] = None,
                 model_package_group_name: Optional[str] = None,
                 model_package_name: Optional[str] = None,
                 model_package_status_details: Optional[ModelPackageStatusDetailsArgs] = None,
                 model_package_version: Optional[int] = None,
                 sample_payload_url: Optional[str] = None,
                 skip_model_validation: Optional[ModelPackageSkipModelValidation] = None,
                 source_algorithm_specification: Optional[ModelPackageSourceAlgorithmSpecificationArgs] = None,
                 tags: Optional[Sequence[_root_inputs.TagArgs]] = None,
                 task: Optional[str] = None,
                 validation_specification: Optional[ModelPackageValidationSpecificationArgs] = None)
    func NewModelPackage(ctx *Context, name string, args *ModelPackageArgs, opts ...ResourceOption) (*ModelPackage, error)
    public ModelPackage(string name, ModelPackageArgs? args = null, CustomResourceOptions? opts = null)
    public ModelPackage(String name, ModelPackageArgs args)
public ModelPackage(String name, ModelPackageArgs args, CustomResourceOptions options)

    type: aws-native:sagemaker:ModelPackage
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args ModelPackageArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args ModelPackageArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args ModelPackageArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ModelPackageArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ModelPackageArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    ModelPackage Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    The ModelPackage resource accepts the following input properties:

    AdditionalInferenceSpecifications List<Pulumi.AwsNative.SageMaker.Inputs.ModelPackageAdditionalInferenceSpecificationDefinition>
    An array of additional Inference Specification objects.
    AdditionalInferenceSpecificationsToAdd List<Pulumi.AwsNative.SageMaker.Inputs.ModelPackageAdditionalInferenceSpecificationDefinition>
    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.
    ApprovalDescription string
    A description provided when the model approval is set.
    CertifyForMarketplace bool
    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 .
    ClientToken string
    A unique token that guarantees that the call to this API is idempotent.
    CustomerMetadataProperties Pulumi.AwsNative.SageMaker.Inputs.ModelPackageCustomerMetadataProperties
    The metadata properties for the model package.
    Domain string
    The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
    DriftCheckBaselines Pulumi.AwsNative.SageMaker.Inputs.ModelPackageDriftCheckBaselines
    Represents the drift check baselines that can be used when the model monitor is set using the model package.
    InferenceSpecification Pulumi.AwsNative.SageMaker.Inputs.ModelPackageInferenceSpecification
    Defines how to perform inference generation after a training job is run.
    LastModifiedTime string
    The last time the model package was modified.
    MetadataProperties Pulumi.AwsNative.SageMaker.Inputs.ModelPackageMetadataProperties
    Metadata properties of the tracking entity, trial, or trial component.
    ModelApprovalStatus Pulumi.AwsNative.SageMaker.ModelPackageModelApprovalStatus
    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.
    ModelMetrics Pulumi.AwsNative.SageMaker.Inputs.ModelPackageModelMetrics
    Metrics for the model.
    ModelPackageDescription string
    The description of the model package.
    ModelPackageGroupName string
    The model group to which the model belongs.
    ModelPackageName string
    The name of the model.
    ModelPackageStatusDetails Pulumi.AwsNative.SageMaker.Inputs.ModelPackageStatusDetails
    Specifies the validation and image scan statuses of the model package.
    ModelPackageVersion int
    The version number of a versioned model.
    SamplePayloadUrl string
    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).
    SkipModelValidation Pulumi.AwsNative.SageMaker.ModelPackageSkipModelValidation
    Indicates if you want to skip model validation.
    SourceAlgorithmSpecification Pulumi.AwsNative.SageMaker.Inputs.ModelPackageSourceAlgorithmSpecification
    A list of algorithms that were used to create a model package.
    Tags List<Pulumi.AwsNative.Inputs.Tag>
    An array of key-value pairs to apply to this resource.
    Task string
    The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
    ValidationSpecification Pulumi.AwsNative.SageMaker.Inputs.ModelPackageValidationSpecification
    Specifies batch transform jobs that SageMaker runs to validate your model package.
    AdditionalInferenceSpecifications []ModelPackageAdditionalInferenceSpecificationDefinitionArgs
    An array of additional Inference Specification objects.
    AdditionalInferenceSpecificationsToAdd []ModelPackageAdditionalInferenceSpecificationDefinitionArgs
    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.
    ApprovalDescription string
    A description provided when the model approval is set.
    CertifyForMarketplace bool
    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 .
    ClientToken string
    A unique token that guarantees that the call to this API is idempotent.
    CustomerMetadataProperties ModelPackageCustomerMetadataPropertiesArgs
    The metadata properties for the model package.
    Domain string
    The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
    DriftCheckBaselines ModelPackageDriftCheckBaselinesArgs
    Represents the drift check baselines that can be used when the model monitor is set using the model package.
    InferenceSpecification ModelPackageInferenceSpecificationArgs
    Defines how to perform inference generation after a training job is run.
    LastModifiedTime string
    The last time the model package was modified.
    MetadataProperties ModelPackageMetadataPropertiesArgs
    Metadata properties of the tracking entity, trial, or trial component.
    ModelApprovalStatus ModelPackageModelApprovalStatus
    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.
    ModelMetrics ModelPackageModelMetricsArgs
    Metrics for the model.
    ModelPackageDescription string
    The description of the model package.
    ModelPackageGroupName string
    The model group to which the model belongs.
    ModelPackageName string
    The name of the model.
    ModelPackageStatusDetails ModelPackageStatusDetailsArgs
    Specifies the validation and image scan statuses of the model package.
    ModelPackageVersion int
    The version number of a versioned model.
    SamplePayloadUrl string
    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).
    SkipModelValidation ModelPackageSkipModelValidation
    Indicates if you want to skip model validation.
    SourceAlgorithmSpecification ModelPackageSourceAlgorithmSpecificationArgs
    A list of algorithms that were used to create a model package.
    Tags TagArgs
    An array of key-value pairs to apply to this resource.
    Task string
    The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
    ValidationSpecification ModelPackageValidationSpecificationArgs
    Specifies batch transform jobs that SageMaker runs to validate your model package.
    additionalInferenceSpecifications List<ModelPackageAdditionalInferenceSpecificationDefinition>
    An array of additional Inference Specification objects.
    additionalInferenceSpecificationsToAdd List<ModelPackageAdditionalInferenceSpecificationDefinition>
    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.
    approvalDescription String
    A description provided when the model approval is set.
    certifyForMarketplace Boolean
    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 .
    clientToken String
    A unique token that guarantees that the call to this API is idempotent.
    customerMetadataProperties ModelPackageCustomerMetadataProperties
    The metadata properties for the model package.
    domain String
    The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
    driftCheckBaselines ModelPackageDriftCheckBaselines
    Represents the drift check baselines that can be used when the model monitor is set using the model package.
    inferenceSpecification ModelPackageInferenceSpecification
    Defines how to perform inference generation after a training job is run.
    lastModifiedTime String
    The last time the model package was modified.
    metadataProperties ModelPackageMetadataProperties
    Metadata properties of the tracking entity, trial, or trial component.
    modelApprovalStatus ModelPackageModelApprovalStatus
    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.
    modelMetrics ModelPackageModelMetrics
    Metrics for the model.
    modelPackageDescription String
    The description of the model package.
    modelPackageGroupName String
    The model group to which the model belongs.
    modelPackageName String
    The name of the model.
    modelPackageStatusDetails ModelPackageStatusDetails
    Specifies the validation and image scan statuses of the model package.
    modelPackageVersion Integer
    The version number of a versioned model.
    samplePayloadUrl String
    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).
    skipModelValidation ModelPackageSkipModelValidation
    Indicates if you want to skip model validation.
    sourceAlgorithmSpecification ModelPackageSourceAlgorithmSpecification
    A list of algorithms that were used to create a model package.
    tags List<Tag>
    An array of key-value pairs to apply to this resource.
    task String
    The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
    validationSpecification ModelPackageValidationSpecification
    Specifies batch transform jobs that SageMaker runs to validate your model package.
    additionalInferenceSpecifications ModelPackageAdditionalInferenceSpecificationDefinition[]
    An array of additional Inference Specification objects.
    additionalInferenceSpecificationsToAdd ModelPackageAdditionalInferenceSpecificationDefinition[]
    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.
    approvalDescription string
    A description provided when the model approval is set.
    certifyForMarketplace boolean
    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 .
    clientToken string
    A unique token that guarantees that the call to this API is idempotent.
    customerMetadataProperties ModelPackageCustomerMetadataProperties
    The metadata properties for the model package.
    domain string
    The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
    driftCheckBaselines ModelPackageDriftCheckBaselines
    Represents the drift check baselines that can be used when the model monitor is set using the model package.
    inferenceSpecification ModelPackageInferenceSpecification
    Defines how to perform inference generation after a training job is run.
    lastModifiedTime string
    The last time the model package was modified.
    metadataProperties ModelPackageMetadataProperties
    Metadata properties of the tracking entity, trial, or trial component.
    modelApprovalStatus ModelPackageModelApprovalStatus
    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.
    modelMetrics ModelPackageModelMetrics
    Metrics for the model.
    modelPackageDescription string
    The description of the model package.
    modelPackageGroupName string
    The model group to which the model belongs.
    modelPackageName string
    The name of the model.
    modelPackageStatusDetails ModelPackageStatusDetails
    Specifies the validation and image scan statuses of the model package.
    modelPackageVersion number
    The version number of a versioned model.
    samplePayloadUrl string
    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).
    skipModelValidation ModelPackageSkipModelValidation
    Indicates if you want to skip model validation.
    sourceAlgorithmSpecification ModelPackageSourceAlgorithmSpecification
    A list of algorithms that were used to create a model package.
    tags Tag[]
    An array of key-value pairs to apply to this resource.
    task string
    The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
    validationSpecification ModelPackageValidationSpecification
    Specifies batch transform jobs that SageMaker runs to validate your model package.
    additional_inference_specifications Sequence[ModelPackageAdditionalInferenceSpecificationDefinitionArgs]
    An array of additional Inference Specification objects.
    additional_inference_specifications_to_add Sequence[ModelPackageAdditionalInferenceSpecificationDefinitionArgs]
    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 str
    A description provided when the model approval is set.
    certify_for_marketplace bool
    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 str
    A unique token that guarantees that the call to this API is idempotent.
    customer_metadata_properties ModelPackageCustomerMetadataPropertiesArgs
    The metadata properties for the model package.
    domain 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 ModelPackageDriftCheckBaselinesArgs
    Represents the drift check baselines that can be used when the model monitor is set using the model package.
    inference_specification ModelPackageInferenceSpecificationArgs
    Defines how to perform inference generation after a training job is run.
    last_modified_time str
    The last time the model package was modified.
    metadata_properties ModelPackageMetadataPropertiesArgs
    Metadata properties of the tracking entity, trial, or trial component.
    model_approval_status ModelPackageModelApprovalStatus
    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 ModelPackageModelMetricsArgs
    Metrics for the model.
    model_package_description str
    The description of the model package.
    model_package_group_name str
    The model group to which the model belongs.
    model_package_name str
    The name of the model.
    model_package_status_details ModelPackageStatusDetailsArgs
    Specifies the validation and image scan statuses of the model package.
    model_package_version int
    The version number of a versioned model.
    sample_payload_url 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).
    skip_model_validation ModelPackageSkipModelValidation
    Indicates if you want to skip model validation.
    source_algorithm_specification ModelPackageSourceAlgorithmSpecificationArgs
    A list of algorithms that were used to create a model package.
    tags Sequence[TagArgs]
    An array of key-value pairs to apply to this resource.
    task str
    The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
    validation_specification ModelPackageValidationSpecificationArgs
    Specifies batch transform jobs that SageMaker runs to validate your model package.
    additionalInferenceSpecifications List<Property Map>
    An array of additional Inference Specification objects.
    additionalInferenceSpecificationsToAdd List<Property Map>
    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.
    approvalDescription String
    A description provided when the model approval is set.
    certifyForMarketplace Boolean
    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 .
    clientToken String
    A unique token that guarantees that the call to this API is idempotent.
    customerMetadataProperties Property Map
    The metadata properties for the model package.
    domain String
    The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
    driftCheckBaselines Property Map
    Represents the drift check baselines that can be used when the model monitor is set using the model package.
    inferenceSpecification Property Map
    Defines how to perform inference generation after a training job is run.
    lastModifiedTime String
    The last time the model package was modified.
    metadataProperties Property Map
    Metadata properties of the tracking entity, trial, or trial component.
    modelApprovalStatus "Approved" | "Rejected" | "PendingManualApproval"
    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.
    modelMetrics Property Map
    Metrics for the model.
    modelPackageDescription String
    The description of the model package.
    modelPackageGroupName String
    The model group to which the model belongs.
    modelPackageName String
    The name of the model.
    modelPackageStatusDetails Property Map
    Specifies the validation and image scan statuses of the model package.
    modelPackageVersion Number
    The version number of a versioned model.
    samplePayloadUrl String
    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).
    skipModelValidation "None" | "All"
    Indicates if you want to skip model validation.
    sourceAlgorithmSpecification Property Map
    A list of algorithms that were used to create a model package.
    tags List<Property Map>
    An array of key-value pairs to apply to this resource.
    task String
    The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification.
    validationSpecification Property Map
    Specifies batch transform jobs that SageMaker runs to validate your model package.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the ModelPackage resource produces the following output properties:

    CreationTime string
    The time that the model package was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    ModelPackageArn string
    The Amazon Resource Name (ARN) of the model package.
    ModelPackageStatus Pulumi.AwsNative.SageMaker.ModelPackageStatus
    The status of the model package. This can be one of the following values.

    • PENDING - The model package creation is pending.
    • IN_PROGRESS - The model package is in the process of being created.
    • COMPLETED - The model package was successfully created.
    • FAILED - The model package creation failed.
    • DELETING - The model package is in the process of being deleted.
    CreationTime string
    The time that the model package was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    ModelPackageArn string
    The Amazon Resource Name (ARN) of the model package.
    ModelPackageStatus ModelPackageStatus
    The status of the model package. This can be one of the following values.

    • PENDING - The model package creation is pending.
    • IN_PROGRESS - The model package is in the process of being created.
    • COMPLETED - The model package was successfully created.
    • FAILED - The model package creation failed.
    • DELETING - The model package is in the process of being deleted.
    creationTime String
    The time that the model package was created.
    id String
    The provider-assigned unique ID for this managed resource.
    modelPackageArn String
    The Amazon Resource Name (ARN) of the model package.
    modelPackageStatus ModelPackageStatus
    The status of the model package. This can be one of the following values.

    • PENDING - The model package creation is pending.
    • IN_PROGRESS - The model package is in the process of being created.
    • COMPLETED - The model package was successfully created.
    • FAILED - The model package creation failed.
    • DELETING - The model package is in the process of being deleted.
    creationTime string
    The time that the model package was created.
    id string
    The provider-assigned unique ID for this managed resource.
    modelPackageArn string
    The Amazon Resource Name (ARN) of the model package.
    modelPackageStatus ModelPackageStatus
    The status of the model package. This can be one of the following values.

    • PENDING - The model package creation is pending.
    • IN_PROGRESS - The model package is in the process of being created.
    • COMPLETED - The model package was successfully created.
    • FAILED - The model package creation failed.
    • DELETING - The model package is in the process of being deleted.
    creation_time str
    The time that the model package was created.
    id str
    The provider-assigned unique ID for this managed resource.
    model_package_arn str
    The Amazon Resource Name (ARN) of the model package.
    model_package_status ModelPackageStatus
    The status of the model package. This can be one of the following values.

    • PENDING - The model package creation is pending.
    • IN_PROGRESS - The model package is in the process of being created.
    • COMPLETED - The model package was successfully created.
    • FAILED - The model package creation failed.
    • DELETING - The model package is in the process of being deleted.
    creationTime String
    The time that the model package was created.
    id String
    The provider-assigned unique ID for this managed resource.
    modelPackageArn String
    The Amazon Resource Name (ARN) of the model package.
    modelPackageStatus "Pending" | "Deleting" | "InProgress" | "Completed" | "Failed"
    The status of the model package. This can be one of the following values.

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

    Supporting Types

    ModelPackageAdditionalInferenceSpecificationDefinition, ModelPackageAdditionalInferenceSpecificationDefinitionArgs

    Containers List<Pulumi.AwsNative.SageMaker.Inputs.ModelPackageContainerDefinition>
    The Amazon ECR registry path of the Docker image that contains the inference code.
    Name string
    A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
    Description string
    A description of the additional Inference specification.
    SupportedContentTypes List<string>
    The supported MIME types for the input data.
    SupportedRealtimeInferenceInstanceTypes List<string>
    A list of the instance types that are used to generate inferences in real-time
    SupportedResponseMimeTypes List<string>
    The supported MIME types for the output data.
    SupportedTransformInstanceTypes List<string>
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    Containers []ModelPackageContainerDefinition
    The Amazon ECR registry path of the Docker image that contains the inference code.
    Name string
    A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
    Description string
    A description of the additional Inference specification.
    SupportedContentTypes []string
    The supported MIME types for the input data.
    SupportedRealtimeInferenceInstanceTypes []string
    A list of the instance types that are used to generate inferences in real-time
    SupportedResponseMimeTypes []string
    The supported MIME types for the output data.
    SupportedTransformInstanceTypes []string
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    containers List<ModelPackageContainerDefinition>
    The Amazon ECR registry path of the Docker image that contains the inference code.
    name String
    A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
    description String
    A description of the additional Inference specification.
    supportedContentTypes List<String>
    The supported MIME types for the input data.
    supportedRealtimeInferenceInstanceTypes List<String>
    A list of the instance types that are used to generate inferences in real-time
    supportedResponseMimeTypes List<String>
    The supported MIME types for the output data.
    supportedTransformInstanceTypes List<String>
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    containers ModelPackageContainerDefinition[]
    The Amazon ECR registry path of the Docker image that contains the inference code.
    name string
    A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
    description string
    A description of the additional Inference specification.
    supportedContentTypes string[]
    The supported MIME types for the input data.
    supportedRealtimeInferenceInstanceTypes string[]
    A list of the instance types that are used to generate inferences in real-time
    supportedResponseMimeTypes string[]
    The supported MIME types for the output data.
    supportedTransformInstanceTypes string[]
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    containers Sequence[ModelPackageContainerDefinition]
    The Amazon ECR registry path of the Docker image that contains the inference code.
    name str
    A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
    description str
    A description of the additional Inference specification.
    supported_content_types Sequence[str]
    The supported MIME types for the input data.
    supported_realtime_inference_instance_types Sequence[str]
    A list of the instance types that are used to generate inferences in real-time
    supported_response_mime_types Sequence[str]
    The supported MIME types for the output data.
    supported_transform_instance_types Sequence[str]
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    containers List<Property Map>
    The Amazon ECR registry path of the Docker image that contains the inference code.
    name String
    A unique name to identify the additional inference specification. The name must be unique within the list of your additional inference specifications for a particular model package.
    description String
    A description of the additional Inference specification.
    supportedContentTypes List<String>
    The supported MIME types for the input data.
    supportedRealtimeInferenceInstanceTypes List<String>
    A list of the instance types that are used to generate inferences in real-time
    supportedResponseMimeTypes List<String>
    The supported MIME types for the output data.
    supportedTransformInstanceTypes List<String>
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.

    ModelPackageBias, ModelPackageBiasArgs

    PostTrainingReport ModelPackageMetricsSource
    The post-training bias report for a model.
    PreTrainingReport ModelPackageMetricsSource
    The pre-training bias report for a model.
    Report ModelPackageMetricsSource
    The bias report for a model
    postTrainingReport ModelPackageMetricsSource
    The post-training bias report for a model.
    preTrainingReport ModelPackageMetricsSource
    The pre-training bias report for a model.
    report ModelPackageMetricsSource
    The bias report for a model
    postTrainingReport ModelPackageMetricsSource
    The post-training bias report for a model.
    preTrainingReport ModelPackageMetricsSource
    The pre-training bias report for a model.
    report ModelPackageMetricsSource
    The bias report for a model
    post_training_report ModelPackageMetricsSource
    The post-training bias report for a model.
    pre_training_report ModelPackageMetricsSource
    The pre-training bias report for a model.
    report ModelPackageMetricsSource
    The bias report for a model
    postTrainingReport Property Map
    The post-training bias report for a model.
    preTrainingReport Property Map
    The pre-training bias report for a model.
    report Property Map
    The bias report for a model

    ModelPackageContainerDefinition, ModelPackageContainerDefinitionArgs

    Image string
    The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
    ContainerHostname string
    The DNS host name for the Docker container.
    Environment Pulumi.AwsNative.SageMaker.Inputs.ModelPackageEnvironment
    Framework string
    The machine learning framework of the model package container image.
    FrameworkVersion string
    The framework version of the Model Package Container Image.
    ImageDigest string
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    ModelDataUrl string
    A structure with Model Input details.
    ModelInput Pulumi.AwsNative.SageMaker.Inputs.ModelPackageContainerDefinitionModelInputProperties
    NearestModelName string
    The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.
    Image string
    The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
    ContainerHostname string
    The DNS host name for the Docker container.
    Environment ModelPackageEnvironment
    Framework string
    The machine learning framework of the model package container image.
    FrameworkVersion string
    The framework version of the Model Package Container Image.
    ImageDigest string
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    ModelDataUrl string
    A structure with Model Input details.
    ModelInput ModelPackageContainerDefinitionModelInputProperties
    NearestModelName string
    The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.
    image String
    The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
    containerHostname String
    The DNS host name for the Docker container.
    environment ModelPackageEnvironment
    framework String
    The machine learning framework of the model package container image.
    frameworkVersion String
    The framework version of the Model Package Container Image.
    imageDigest String
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    modelDataUrl String
    A structure with Model Input details.
    modelInput ModelPackageContainerDefinitionModelInputProperties
    nearestModelName String
    The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.
    image string
    The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
    containerHostname string
    The DNS host name for the Docker container.
    environment ModelPackageEnvironment
    framework string
    The machine learning framework of the model package container image.
    frameworkVersion string
    The framework version of the Model Package Container Image.
    imageDigest string
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    modelDataUrl string
    A structure with Model Input details.
    modelInput ModelPackageContainerDefinitionModelInputProperties
    nearestModelName string
    The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.
    image str
    The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
    container_hostname str
    The DNS host name for the Docker container.
    environment ModelPackageEnvironment
    framework str
    The machine learning framework of the model package container image.
    framework_version str
    The framework version of the Model Package Container Image.
    image_digest str
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    model_data_url str
    A structure with Model Input details.
    model_input ModelPackageContainerDefinitionModelInputProperties
    nearest_model_name str
    The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.
    image String
    The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
    containerHostname String
    The DNS host name for the Docker container.
    environment Property Map
    framework String
    The machine learning framework of the model package container image.
    frameworkVersion String
    The framework version of the Model Package Container Image.
    imageDigest String
    An MD5 hash of the training algorithm that identifies the Docker image used for training.
    modelDataUrl String
    A structure with Model Input details.
    modelInput Property Map
    nearestModelName String
    The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.

    ModelPackageContainerDefinitionModelInputProperties, ModelPackageContainerDefinitionModelInputPropertiesArgs

    DataInputConfig string
    The input configuration object for the model.
    DataInputConfig string
    The input configuration object for the model.
    dataInputConfig String
    The input configuration object for the model.
    dataInputConfig string
    The input configuration object for the model.
    data_input_config str
    The input configuration object for the model.
    dataInputConfig String
    The input configuration object for the model.

    ModelPackageDataSource, ModelPackageDataSourceArgs

    S3DataSource Pulumi.AwsNative.SageMaker.Inputs.ModelPackageS3DataSource
    The S3 location of the data source that is associated with a channel.
    S3DataSource ModelPackageS3DataSource
    The S3 location of the data source that is associated with a channel.
    s3DataSource ModelPackageS3DataSource
    The S3 location of the data source that is associated with a channel.
    s3DataSource ModelPackageS3DataSource
    The S3 location of the data source that is associated with a channel.
    s3_data_source ModelPackageS3DataSource
    The S3 location of the data source that is associated with a channel.
    s3DataSource Property Map
    The S3 location of the data source that is associated with a channel.

    ModelPackageDriftCheckBaselines, ModelPackageDriftCheckBaselinesArgs

    Bias Pulumi.AwsNative.SageMaker.Inputs.ModelPackageDriftCheckBias
    Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
    Explainability Pulumi.AwsNative.SageMaker.Inputs.ModelPackageDriftCheckExplainability
    Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
    ModelDataQuality Pulumi.AwsNative.SageMaker.Inputs.ModelPackageDriftCheckModelDataQuality
    Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
    ModelQuality Pulumi.AwsNative.SageMaker.Inputs.ModelPackageDriftCheckModelQuality
    Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
    Bias ModelPackageDriftCheckBias
    Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
    Explainability ModelPackageDriftCheckExplainability
    Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
    ModelDataQuality ModelPackageDriftCheckModelDataQuality
    Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
    ModelQuality ModelPackageDriftCheckModelQuality
    Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
    bias ModelPackageDriftCheckBias
    Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
    explainability ModelPackageDriftCheckExplainability
    Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
    modelDataQuality ModelPackageDriftCheckModelDataQuality
    Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
    modelQuality ModelPackageDriftCheckModelQuality
    Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
    bias ModelPackageDriftCheckBias
    Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
    explainability ModelPackageDriftCheckExplainability
    Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
    modelDataQuality ModelPackageDriftCheckModelDataQuality
    Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
    modelQuality ModelPackageDriftCheckModelQuality
    Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
    bias ModelPackageDriftCheckBias
    Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
    explainability ModelPackageDriftCheckExplainability
    Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
    model_data_quality ModelPackageDriftCheckModelDataQuality
    Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
    model_quality ModelPackageDriftCheckModelQuality
    Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.
    bias Property Map
    Represents the drift check bias baselines that can be used when the model monitor is set using the model package.
    explainability Property Map
    Represents the drift check explainability baselines that can be used when the model monitor is set using the model package.
    modelDataQuality Property Map
    Represents the drift check model data quality baselines that can be used when the model monitor is set using the model package.
    modelQuality Property Map
    Represents the drift check model quality baselines that can be used when the model monitor is set using the model package.

    ModelPackageDriftCheckBias, ModelPackageDriftCheckBiasArgs

    ConfigFile ModelPackageFileSource
    The bias config file for a model.
    PostTrainingConstraints ModelPackageMetricsSource
    The post-training constraints.
    PreTrainingConstraints ModelPackageMetricsSource
    The pre-training constraints.
    configFile ModelPackageFileSource
    The bias config file for a model.
    postTrainingConstraints ModelPackageMetricsSource
    The post-training constraints.
    preTrainingConstraints ModelPackageMetricsSource
    The pre-training constraints.
    configFile ModelPackageFileSource
    The bias config file for a model.
    postTrainingConstraints ModelPackageMetricsSource
    The post-training constraints.
    preTrainingConstraints ModelPackageMetricsSource
    The pre-training constraints.
    config_file ModelPackageFileSource
    The bias config file for a model.
    post_training_constraints ModelPackageMetricsSource
    The post-training constraints.
    pre_training_constraints ModelPackageMetricsSource
    The pre-training constraints.
    configFile Property Map
    The bias config file for a model.
    postTrainingConstraints Property Map
    The post-training constraints.
    preTrainingConstraints Property Map
    The pre-training constraints.

    ModelPackageDriftCheckExplainability, ModelPackageDriftCheckExplainabilityArgs

    ConfigFile ModelPackageFileSource
    The explainability config file for the model.
    Constraints ModelPackageMetricsSource
    The drift check explainability constraints.
    configFile ModelPackageFileSource
    The explainability config file for the model.
    constraints ModelPackageMetricsSource
    The drift check explainability constraints.
    configFile ModelPackageFileSource
    The explainability config file for the model.
    constraints ModelPackageMetricsSource
    The drift check explainability constraints.
    config_file ModelPackageFileSource
    The explainability config file for the model.
    constraints ModelPackageMetricsSource
    The drift check explainability constraints.
    configFile Property Map
    The explainability config file for the model.
    constraints Property Map
    The drift check explainability constraints.

    ModelPackageDriftCheckModelDataQuality, ModelPackageDriftCheckModelDataQualityArgs

    Constraints Pulumi.AwsNative.SageMaker.Inputs.ModelPackageMetricsSource
    The drift check model data quality constraints.
    Statistics Pulumi.AwsNative.SageMaker.Inputs.ModelPackageMetricsSource
    The drift check model data quality statistics.
    Constraints ModelPackageMetricsSource
    The drift check model data quality constraints.
    Statistics ModelPackageMetricsSource
    The drift check model data quality statistics.
    constraints ModelPackageMetricsSource
    The drift check model data quality constraints.
    statistics ModelPackageMetricsSource
    The drift check model data quality statistics.
    constraints ModelPackageMetricsSource
    The drift check model data quality constraints.
    statistics ModelPackageMetricsSource
    The drift check model data quality statistics.
    constraints ModelPackageMetricsSource
    The drift check model data quality constraints.
    statistics ModelPackageMetricsSource
    The drift check model data quality statistics.
    constraints Property Map
    The drift check model data quality constraints.
    statistics Property Map
    The drift check model data quality statistics.

    ModelPackageDriftCheckModelQuality, ModelPackageDriftCheckModelQualityArgs

    Constraints ModelPackageMetricsSource
    The drift check model quality constraints.
    Statistics ModelPackageMetricsSource
    The drift check model quality statistics.
    constraints ModelPackageMetricsSource
    The drift check model quality constraints.
    statistics ModelPackageMetricsSource
    The drift check model quality statistics.
    constraints ModelPackageMetricsSource
    The drift check model quality constraints.
    statistics ModelPackageMetricsSource
    The drift check model quality statistics.
    constraints ModelPackageMetricsSource
    The drift check model quality constraints.
    statistics ModelPackageMetricsSource
    The drift check model quality statistics.
    constraints Property Map
    The drift check model quality constraints.
    statistics Property Map
    The drift check model quality statistics.

    ModelPackageExplainability, ModelPackageExplainabilityArgs

    Report ModelPackageMetricsSource
    The explainability report for a model.
    report ModelPackageMetricsSource
    The explainability report for a model.
    report ModelPackageMetricsSource
    The explainability report for a model.
    report ModelPackageMetricsSource
    The explainability report for a model.
    report Property Map
    The explainability report for a model.

    ModelPackageFileSource, ModelPackageFileSourceArgs

    S3Uri string
    The Amazon S3 URI for the file source.
    ContentDigest string
    The digest of the file source.
    ContentType string
    The type of content stored in the file source.
    S3Uri string
    The Amazon S3 URI for the file source.
    ContentDigest string
    The digest of the file source.
    ContentType string
    The type of content stored in the file source.
    s3Uri String
    The Amazon S3 URI for the file source.
    contentDigest String
    The digest of the file source.
    contentType String
    The type of content stored in the file source.
    s3Uri string
    The Amazon S3 URI for the file source.
    contentDigest string
    The digest of the file source.
    contentType string
    The type of content stored in the file source.
    s3_uri str
    The Amazon S3 URI for the file source.
    content_digest str
    The digest of the file source.
    content_type str
    The type of content stored in the file source.
    s3Uri String
    The Amazon S3 URI for the file source.
    contentDigest String
    The digest of the file source.
    contentType String
    The type of content stored in the file source.

    ModelPackageInferenceSpecification, ModelPackageInferenceSpecificationArgs

    Containers List<Pulumi.AwsNative.SageMaker.Inputs.ModelPackageContainerDefinition>
    The Amazon ECR registry path of the Docker image that contains the inference code.
    SupportedContentTypes List<string>
    The supported MIME types for the input data.
    SupportedResponseMimeTypes List<string>
    The supported MIME types for the output data.
    SupportedRealtimeInferenceInstanceTypes List<string>
    A list of the instance types that are used to generate inferences in real-time
    SupportedTransformInstanceTypes List<string>
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    Containers []ModelPackageContainerDefinition
    The Amazon ECR registry path of the Docker image that contains the inference code.
    SupportedContentTypes []string
    The supported MIME types for the input data.
    SupportedResponseMimeTypes []string
    The supported MIME types for the output data.
    SupportedRealtimeInferenceInstanceTypes []string
    A list of the instance types that are used to generate inferences in real-time
    SupportedTransformInstanceTypes []string
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    containers List<ModelPackageContainerDefinition>
    The Amazon ECR registry path of the Docker image that contains the inference code.
    supportedContentTypes List<String>
    The supported MIME types for the input data.
    supportedResponseMimeTypes List<String>
    The supported MIME types for the output data.
    supportedRealtimeInferenceInstanceTypes List<String>
    A list of the instance types that are used to generate inferences in real-time
    supportedTransformInstanceTypes List<String>
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    containers ModelPackageContainerDefinition[]
    The Amazon ECR registry path of the Docker image that contains the inference code.
    supportedContentTypes string[]
    The supported MIME types for the input data.
    supportedResponseMimeTypes string[]
    The supported MIME types for the output data.
    supportedRealtimeInferenceInstanceTypes string[]
    A list of the instance types that are used to generate inferences in real-time
    supportedTransformInstanceTypes string[]
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    containers Sequence[ModelPackageContainerDefinition]
    The Amazon ECR registry path of the Docker image that contains the inference code.
    supported_content_types Sequence[str]
    The supported MIME types for the input data.
    supported_response_mime_types Sequence[str]
    The supported MIME types for the output data.
    supported_realtime_inference_instance_types Sequence[str]
    A list of the instance types that are used to generate inferences in real-time
    supported_transform_instance_types Sequence[str]
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
    containers List<Property Map>
    The Amazon ECR registry path of the Docker image that contains the inference code.
    supportedContentTypes List<String>
    The supported MIME types for the input data.
    supportedResponseMimeTypes List<String>
    The supported MIME types for the output data.
    supportedRealtimeInferenceInstanceTypes List<String>
    A list of the instance types that are used to generate inferences in real-time
    supportedTransformInstanceTypes List<String>
    A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.

    ModelPackageMetadataProperties, ModelPackageMetadataPropertiesArgs

    CommitId string
    The commit ID.
    GeneratedBy string
    The entity this entity was generated by.
    ProjectId string
    The project ID metadata.
    Repository string
    The repository metadata.
    CommitId string
    The commit ID.
    GeneratedBy string
    The entity this entity was generated by.
    ProjectId string
    The project ID metadata.
    Repository string
    The repository metadata.
    commitId String
    The commit ID.
    generatedBy String
    The entity this entity was generated by.
    projectId String
    The project ID metadata.
    repository String
    The repository metadata.
    commitId string
    The commit ID.
    generatedBy string
    The entity this entity was generated by.
    projectId string
    The project ID metadata.
    repository string
    The repository metadata.
    commit_id str
    The commit ID.
    generated_by str
    The entity this entity was generated by.
    project_id str
    The project ID metadata.
    repository str
    The repository metadata.
    commitId String
    The commit ID.
    generatedBy String
    The entity this entity was generated by.
    projectId String
    The project ID metadata.
    repository String
    The repository metadata.

    ModelPackageMetricsSource, ModelPackageMetricsSourceArgs

    ContentType string
    The type of content stored in the metric source.
    S3Uri string
    The Amazon S3 URI for the metric source.
    ContentDigest string
    The digest of the metric source.
    ContentType string
    The type of content stored in the metric source.
    S3Uri string
    The Amazon S3 URI for the metric source.
    ContentDigest string
    The digest of the metric source.
    contentType String
    The type of content stored in the metric source.
    s3Uri String
    The Amazon S3 URI for the metric source.
    contentDigest String
    The digest of the metric source.
    contentType string
    The type of content stored in the metric source.
    s3Uri string
    The Amazon S3 URI for the metric source.
    contentDigest string
    The digest of the metric source.
    content_type str
    The type of content stored in the metric source.
    s3_uri str
    The Amazon S3 URI for the metric source.
    content_digest str
    The digest of the metric source.
    contentType String
    The type of content stored in the metric source.
    s3Uri String
    The Amazon S3 URI for the metric source.
    contentDigest String
    The digest of the metric source.

    ModelPackageModelApprovalStatus, ModelPackageModelApprovalStatusArgs

    Approved
    Approved
    Rejected
    Rejected
    PendingManualApproval
    PendingManualApproval
    ModelPackageModelApprovalStatusApproved
    Approved
    ModelPackageModelApprovalStatusRejected
    Rejected
    ModelPackageModelApprovalStatusPendingManualApproval
    PendingManualApproval
    Approved
    Approved
    Rejected
    Rejected
    PendingManualApproval
    PendingManualApproval
    Approved
    Approved
    Rejected
    Rejected
    PendingManualApproval
    PendingManualApproval
    APPROVED
    Approved
    REJECTED
    Rejected
    PENDING_MANUAL_APPROVAL
    PendingManualApproval
    "Approved"
    Approved
    "Rejected"
    Rejected
    "PendingManualApproval"
    PendingManualApproval

    ModelPackageModelDataQuality, ModelPackageModelDataQualityArgs

    Constraints ModelPackageMetricsSource
    Data quality constraints for a model.
    Statistics ModelPackageMetricsSource
    Data quality statistics for a model.
    constraints ModelPackageMetricsSource
    Data quality constraints for a model.
    statistics ModelPackageMetricsSource
    Data quality statistics for a model.
    constraints ModelPackageMetricsSource
    Data quality constraints for a model.
    statistics ModelPackageMetricsSource
    Data quality statistics for a model.
    constraints ModelPackageMetricsSource
    Data quality constraints for a model.
    statistics ModelPackageMetricsSource
    Data quality statistics for a model.
    constraints Property Map
    Data quality constraints for a model.
    statistics Property Map
    Data quality statistics for a model.

    ModelPackageModelMetrics, ModelPackageModelMetricsArgs

    Bias ModelPackageBias
    Metrics that measure bias in a model.
    Explainability ModelPackageExplainability
    Metrics that help explain a model.
    ModelDataQuality ModelPackageModelDataQuality
    Metrics that measure the quality of the input data for a model.
    ModelQuality ModelPackageModelQuality
    Metrics that measure the quality of a model.
    bias ModelPackageBias
    Metrics that measure bias in a model.
    explainability ModelPackageExplainability
    Metrics that help explain a model.
    modelDataQuality ModelPackageModelDataQuality
    Metrics that measure the quality of the input data for a model.
    modelQuality ModelPackageModelQuality
    Metrics that measure the quality of a model.
    bias ModelPackageBias
    Metrics that measure bias in a model.
    explainability ModelPackageExplainability
    Metrics that help explain a model.
    modelDataQuality ModelPackageModelDataQuality
    Metrics that measure the quality of the input data for a model.
    modelQuality ModelPackageModelQuality
    Metrics that measure the quality of a model.
    bias ModelPackageBias
    Metrics that measure bias in a model.
    explainability ModelPackageExplainability
    Metrics that help explain a model.
    model_data_quality ModelPackageModelDataQuality
    Metrics that measure the quality of the input data for a model.
    model_quality ModelPackageModelQuality
    Metrics that measure the quality of a model.
    bias Property Map
    Metrics that measure bias in a model.
    explainability Property Map
    Metrics that help explain a model.
    modelDataQuality Property Map
    Metrics that measure the quality of the input data for a model.
    modelQuality Property Map
    Metrics that measure the quality of a model.

    ModelPackageModelQuality, ModelPackageModelQualityArgs

    Constraints ModelPackageMetricsSource
    Model quality constraints.
    Statistics ModelPackageMetricsSource
    Model quality statistics.
    constraints ModelPackageMetricsSource
    Model quality constraints.
    statistics ModelPackageMetricsSource
    Model quality statistics.
    constraints ModelPackageMetricsSource
    Model quality constraints.
    statistics ModelPackageMetricsSource
    Model quality statistics.
    constraints ModelPackageMetricsSource
    Model quality constraints.
    statistics ModelPackageMetricsSource
    Model quality statistics.
    constraints Property Map
    Model quality constraints.
    statistics Property Map
    Model quality statistics.

    ModelPackageS3DataSource, ModelPackageS3DataSourceArgs

    S3DataType Pulumi.AwsNative.SageMaker.ModelPackageS3DataSourceS3DataType
    The S3 Data Source Type
    S3Uri string
    Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest.
    S3DataType ModelPackageS3DataSourceS3DataType
    The S3 Data Source Type
    S3Uri string
    Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest.
    s3DataType ModelPackageS3DataSourceS3DataType
    The S3 Data Source Type
    s3Uri String
    Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest.
    s3DataType ModelPackageS3DataSourceS3DataType
    The S3 Data Source Type
    s3Uri string
    Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest.
    s3_data_type ModelPackageS3DataSourceS3DataType
    The S3 Data Source Type
    s3_uri str
    Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest.
    s3DataType "ManifestFile" | "S3Prefix" | "AugmentedManifestFile"
    The S3 Data Source Type
    s3Uri String
    Depending on the value specified for the S3DataType, identifies either a key name prefix or a manifest.

    ModelPackageS3DataSourceS3DataType, ModelPackageS3DataSourceS3DataTypeArgs

    ManifestFile
    ManifestFile
    S3Prefix
    S3Prefix
    AugmentedManifestFile
    AugmentedManifestFile
    ModelPackageS3DataSourceS3DataTypeManifestFile
    ManifestFile
    ModelPackageS3DataSourceS3DataTypeS3Prefix
    S3Prefix
    ModelPackageS3DataSourceS3DataTypeAugmentedManifestFile
    AugmentedManifestFile
    ManifestFile
    ManifestFile
    S3Prefix
    S3Prefix
    AugmentedManifestFile
    AugmentedManifestFile
    ManifestFile
    ManifestFile
    S3Prefix
    S3Prefix
    AugmentedManifestFile
    AugmentedManifestFile
    MANIFEST_FILE
    ManifestFile
    S3_PREFIX
    S3Prefix
    AUGMENTED_MANIFEST_FILE
    AugmentedManifestFile
    "ManifestFile"
    ManifestFile
    "S3Prefix"
    S3Prefix
    "AugmentedManifestFile"
    AugmentedManifestFile

    ModelPackageSkipModelValidation, ModelPackageSkipModelValidationArgs

    None
    None
    All
    All
    ModelPackageSkipModelValidationNone
    None
    ModelPackageSkipModelValidationAll
    All
    None
    None
    All
    All
    None
    None
    All
    All
    NONE
    None
    ALL
    All
    "None"
    None
    "All"
    All

    ModelPackageSourceAlgorithm, ModelPackageSourceAlgorithmArgs

    AlgorithmName string
    The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your Amazon SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.
    ModelDataUrl string
    The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
    AlgorithmName string
    The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your Amazon SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.
    ModelDataUrl string
    The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
    algorithmName String
    The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your Amazon SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.
    modelDataUrl String
    The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
    algorithmName string
    The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your Amazon SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.
    modelDataUrl string
    The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
    algorithm_name str
    The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your Amazon SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.
    model_data_url str
    The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).
    algorithmName String
    The name of an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your Amazon SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.
    modelDataUrl String
    The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).

    ModelPackageSourceAlgorithmSpecification, ModelPackageSourceAlgorithmSpecificationArgs

    SourceAlgorithms List<Pulumi.AwsNative.SageMaker.Inputs.ModelPackageSourceAlgorithm>
    A list of algorithms that were used to create a model package.
    SourceAlgorithms []ModelPackageSourceAlgorithm
    A list of algorithms that were used to create a model package.
    sourceAlgorithms List<ModelPackageSourceAlgorithm>
    A list of algorithms that were used to create a model package.
    sourceAlgorithms ModelPackageSourceAlgorithm[]
    A list of algorithms that were used to create a model package.
    source_algorithms Sequence[ModelPackageSourceAlgorithm]
    A list of algorithms that were used to create a model package.
    sourceAlgorithms List<Property Map>
    A list of algorithms that were used to create a model package.

    ModelPackageStatus, ModelPackageStatusArgs

    Pending
    Pending
    Deleting
    Deleting
    InProgress
    InProgress
    Completed
    Completed
    Failed
    Failed
    ModelPackageStatusPending
    Pending
    ModelPackageStatusDeleting
    Deleting
    ModelPackageStatusInProgress
    InProgress
    ModelPackageStatusCompleted
    Completed
    ModelPackageStatusFailed
    Failed
    Pending
    Pending
    Deleting
    Deleting
    InProgress
    InProgress
    Completed
    Completed
    Failed
    Failed
    Pending
    Pending
    Deleting
    Deleting
    InProgress
    InProgress
    Completed
    Completed
    Failed
    Failed
    PENDING
    Pending
    DELETING
    Deleting
    IN_PROGRESS
    InProgress
    COMPLETED
    Completed
    FAILED
    Failed
    "Pending"
    Pending
    "Deleting"
    Deleting
    "InProgress"
    InProgress
    "Completed"
    Completed
    "Failed"
    Failed

    ModelPackageStatusDetails, ModelPackageStatusDetailsArgs

    ValidationStatuses []ModelPackageStatusItem
    The validation status of the model package.
    validationStatuses List<ModelPackageStatusItem>
    The validation status of the model package.
    validationStatuses ModelPackageStatusItem[]
    The validation status of the model package.
    validation_statuses Sequence[ModelPackageStatusItem]
    The validation status of the model package.
    validationStatuses List<Property Map>
    The validation status of the model package.

    ModelPackageStatusItem, ModelPackageStatusItemArgs

    Name string
    The name of the model package for which the overall status is being reported.
    Status Pulumi.AwsNative.SageMaker.ModelPackageStatusItemStatus
    The current status.
    FailureReason string
    If the overall status is Failed, the reason for the failure.
    Name string
    The name of the model package for which the overall status is being reported.
    Status ModelPackageStatusItemStatus
    The current status.
    FailureReason string
    If the overall status is Failed, the reason for the failure.
    name String
    The name of the model package for which the overall status is being reported.
    status ModelPackageStatusItemStatus
    The current status.
    failureReason String
    If the overall status is Failed, the reason for the failure.
    name string
    The name of the model package for which the overall status is being reported.
    status ModelPackageStatusItemStatus
    The current status.
    failureReason string
    If the overall status is Failed, the reason for the failure.
    name str
    The name of the model package for which the overall status is being reported.
    status ModelPackageStatusItemStatus
    The current status.
    failure_reason str
    If the overall status is Failed, the reason for the failure.
    name String
    The name of the model package for which the overall status is being reported.
    status "NotStarted" | "Failed" | "InProgress" | "Completed"
    The current status.
    failureReason String
    If the overall status is Failed, the reason for the failure.

    ModelPackageStatusItemStatus, ModelPackageStatusItemStatusArgs

    NotStarted
    NotStarted
    Failed
    Failed
    InProgress
    InProgress
    Completed
    Completed
    ModelPackageStatusItemStatusNotStarted
    NotStarted
    ModelPackageStatusItemStatusFailed
    Failed
    ModelPackageStatusItemStatusInProgress
    InProgress
    ModelPackageStatusItemStatusCompleted
    Completed
    NotStarted
    NotStarted
    Failed
    Failed
    InProgress
    InProgress
    Completed
    Completed
    NotStarted
    NotStarted
    Failed
    Failed
    InProgress
    InProgress
    Completed
    Completed
    NOT_STARTED
    NotStarted
    FAILED
    Failed
    IN_PROGRESS
    InProgress
    COMPLETED
    Completed
    "NotStarted"
    NotStarted
    "Failed"
    Failed
    "InProgress"
    InProgress
    "Completed"
    Completed

    ModelPackageTransformInput, ModelPackageTransformInputArgs

    DataSource Pulumi.AwsNative.SageMaker.Inputs.ModelPackageDataSource
    Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
    CompressionType Pulumi.AwsNative.SageMaker.ModelPackageTransformInputCompressionType
    If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
    ContentType string
    The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
    SplitType Pulumi.AwsNative.SageMaker.ModelPackageTransformInputSplitType
    The method to use to split the transform job's data files into smaller batches.
    DataSource ModelPackageDataSource
    Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
    CompressionType ModelPackageTransformInputCompressionType
    If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
    ContentType string
    The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
    SplitType ModelPackageTransformInputSplitType
    The method to use to split the transform job's data files into smaller batches.
    dataSource ModelPackageDataSource
    Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
    compressionType ModelPackageTransformInputCompressionType
    If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
    contentType String
    The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
    splitType ModelPackageTransformInputSplitType
    The method to use to split the transform job's data files into smaller batches.
    dataSource ModelPackageDataSource
    Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
    compressionType ModelPackageTransformInputCompressionType
    If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
    contentType string
    The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
    splitType ModelPackageTransformInputSplitType
    The method to use to split the transform job's data files into smaller batches.
    data_source ModelPackageDataSource
    Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
    compression_type ModelPackageTransformInputCompressionType
    If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
    content_type str
    The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
    split_type ModelPackageTransformInputSplitType
    The method to use to split the transform job's data files into smaller batches.
    dataSource Property Map
    Describes the location of the channel data, which is, the S3 location of the input data that the model can consume.
    compressionType "None" | "Gzip"
    If your transform data is compressed, specify the compression type. Amazon SageMaker automatically decompresses the data for the transform job accordingly. The default value is None.
    contentType String
    The multipurpose internet mail extension (MIME) type of the data. Amazon SageMaker uses the MIME type with each http call to transfer data to the transform job.
    splitType "None" | "TFRecord" | "Line" | "RecordIO"
    The method to use to split the transform job's data files into smaller batches.

    ModelPackageTransformInputCompressionType, ModelPackageTransformInputCompressionTypeArgs

    None
    None
    Gzip
    Gzip
    ModelPackageTransformInputCompressionTypeNone
    None
    ModelPackageTransformInputCompressionTypeGzip
    Gzip
    None
    None
    Gzip
    Gzip
    None
    None
    Gzip
    Gzip
    NONE
    None
    GZIP
    Gzip
    "None"
    None
    "Gzip"
    Gzip

    ModelPackageTransformInputSplitType, ModelPackageTransformInputSplitTypeArgs

    None
    None
    TfRecord
    TFRecord
    Line
    Line
    RecordIo
    RecordIO
    ModelPackageTransformInputSplitTypeNone
    None
    ModelPackageTransformInputSplitTypeTfRecord
    TFRecord
    ModelPackageTransformInputSplitTypeLine
    Line
    ModelPackageTransformInputSplitTypeRecordIo
    RecordIO
    None
    None
    TfRecord
    TFRecord
    Line
    Line
    RecordIo
    RecordIO
    None
    None
    TfRecord
    TFRecord
    Line
    Line
    RecordIo
    RecordIO
    NONE
    None
    TF_RECORD
    TFRecord
    LINE
    Line
    RECORD_IO
    RecordIO
    "None"
    None
    "TFRecord"
    TFRecord
    "Line"
    Line
    "RecordIO"
    RecordIO

    ModelPackageTransformJobDefinition, ModelPackageTransformJobDefinitionArgs

    TransformInput Pulumi.AwsNative.SageMaker.Inputs.ModelPackageTransformInput
    A description of the input source and the way the transform job consumes it.
    TransformOutput Pulumi.AwsNative.SageMaker.Inputs.ModelPackageTransformOutput
    Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
    TransformResources Pulumi.AwsNative.SageMaker.Inputs.ModelPackageTransformResources
    Identifies the ML compute instances for the transform job.
    BatchStrategy Pulumi.AwsNative.SageMaker.ModelPackageTransformJobDefinitionBatchStrategy
    A string that determines the number of records included in a single mini-batch.
    Environment Pulumi.AwsNative.SageMaker.Inputs.ModelPackageEnvironment
    The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
    MaxConcurrentTransforms int
    The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
    MaxPayloadInMb int
    The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
    TransformInput ModelPackageTransformInput
    A description of the input source and the way the transform job consumes it.
    TransformOutput ModelPackageTransformOutput
    Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
    TransformResources ModelPackageTransformResources
    Identifies the ML compute instances for the transform job.
    BatchStrategy ModelPackageTransformJobDefinitionBatchStrategy
    A string that determines the number of records included in a single mini-batch.
    Environment ModelPackageEnvironment
    The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
    MaxConcurrentTransforms int
    The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
    MaxPayloadInMb int
    The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
    transformInput ModelPackageTransformInput
    A description of the input source and the way the transform job consumes it.
    transformOutput ModelPackageTransformOutput
    Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
    transformResources ModelPackageTransformResources
    Identifies the ML compute instances for the transform job.
    batchStrategy ModelPackageTransformJobDefinitionBatchStrategy
    A string that determines the number of records included in a single mini-batch.
    environment ModelPackageEnvironment
    The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
    maxConcurrentTransforms Integer
    The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
    maxPayloadInMb Integer
    The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
    transformInput ModelPackageTransformInput
    A description of the input source and the way the transform job consumes it.
    transformOutput ModelPackageTransformOutput
    Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
    transformResources ModelPackageTransformResources
    Identifies the ML compute instances for the transform job.
    batchStrategy ModelPackageTransformJobDefinitionBatchStrategy
    A string that determines the number of records included in a single mini-batch.
    environment ModelPackageEnvironment
    The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
    maxConcurrentTransforms number
    The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
    maxPayloadInMb number
    The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
    transform_input ModelPackageTransformInput
    A description of the input source and the way the transform job consumes it.
    transform_output ModelPackageTransformOutput
    Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
    transform_resources ModelPackageTransformResources
    Identifies the ML compute instances for the transform job.
    batch_strategy ModelPackageTransformJobDefinitionBatchStrategy
    A string that determines the number of records included in a single mini-batch.
    environment ModelPackageEnvironment
    The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
    max_concurrent_transforms int
    The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
    max_payload_in_mb int
    The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).
    transformInput Property Map
    A description of the input source and the way the transform job consumes it.
    transformOutput Property Map
    Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.
    transformResources Property Map
    Identifies the ML compute instances for the transform job.
    batchStrategy "MultiRecord" | "SingleRecord"
    A string that determines the number of records included in a single mini-batch.
    environment Property Map
    The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.
    maxConcurrentTransforms Number
    The maximum number of parallel requests that can be sent to each instance in a transform job. The default value is 1.
    maxPayloadInMb Number
    The maximum payload size allowed, in MB. A payload is the data portion of a record (without metadata).

    ModelPackageTransformJobDefinitionBatchStrategy, ModelPackageTransformJobDefinitionBatchStrategyArgs

    MultiRecord
    MultiRecord
    SingleRecord
    SingleRecord
    ModelPackageTransformJobDefinitionBatchStrategyMultiRecord
    MultiRecord
    ModelPackageTransformJobDefinitionBatchStrategySingleRecord
    SingleRecord
    MultiRecord
    MultiRecord
    SingleRecord
    SingleRecord
    MultiRecord
    MultiRecord
    SingleRecord
    SingleRecord
    MULTI_RECORD
    MultiRecord
    SINGLE_RECORD
    SingleRecord
    "MultiRecord"
    MultiRecord
    "SingleRecord"
    SingleRecord

    ModelPackageTransformOutput, ModelPackageTransformOutputArgs

    S3OutputPath string
    The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job.
    Accept string
    The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
    AssembleWith Pulumi.AwsNative.SageMaker.ModelPackageTransformOutputAssembleWith
    Defines how to assemble the results of the transform job as a single S3 object.
    KmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    S3OutputPath string
    The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job.
    Accept string
    The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
    AssembleWith ModelPackageTransformOutputAssembleWith
    Defines how to assemble the results of the transform job as a single S3 object.
    KmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    s3OutputPath String
    The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job.
    accept String
    The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
    assembleWith ModelPackageTransformOutputAssembleWith
    Defines how to assemble the results of the transform job as a single S3 object.
    kmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    s3OutputPath string
    The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job.
    accept string
    The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
    assembleWith ModelPackageTransformOutputAssembleWith
    Defines how to assemble the results of the transform job as a single S3 object.
    kmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    s3_output_path str
    The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job.
    accept str
    The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
    assemble_with ModelPackageTransformOutputAssembleWith
    Defines how to assemble the results of the transform job as a single S3 object.
    kms_key_id str
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    s3OutputPath String
    The Amazon S3 path where you want Amazon SageMaker to store the results of the transform job.
    accept String
    The MIME type used to specify the output data. Amazon SageMaker uses the MIME type with each http call to transfer data from the transform job.
    assembleWith "None" | "Line"
    Defines how to assemble the results of the transform job as a single S3 object.
    kmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.

    ModelPackageTransformOutputAssembleWith, ModelPackageTransformOutputAssembleWithArgs

    None
    None
    Line
    Line
    ModelPackageTransformOutputAssembleWithNone
    None
    ModelPackageTransformOutputAssembleWithLine
    Line
    None
    None
    Line
    Line
    None
    None
    Line
    Line
    NONE
    None
    LINE
    Line
    "None"
    None
    "Line"
    Line

    ModelPackageTransformResources, ModelPackageTransformResourcesArgs

    InstanceCount int
    The number of ML compute instances to use in the transform job. For distributed transform jobs, specify a value greater than 1. The default value is 1.
    InstanceType string
    The ML compute instance type for the transform job.
    VolumeKmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
    InstanceCount int
    The number of ML compute instances to use in the transform job. For distributed transform jobs, specify a value greater than 1. The default value is 1.
    InstanceType string
    The ML compute instance type for the transform job.
    VolumeKmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
    instanceCount Integer
    The number of ML compute instances to use in the transform job. For distributed transform jobs, specify a value greater than 1. The default value is 1.
    instanceType String
    The ML compute instance type for the transform job.
    volumeKmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
    instanceCount number
    The number of ML compute instances to use in the transform job. For distributed transform jobs, specify a value greater than 1. The default value is 1.
    instanceType string
    The ML compute instance type for the transform job.
    volumeKmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
    instance_count int
    The number of ML compute instances to use in the transform job. For distributed transform jobs, specify a value greater than 1. The default value is 1.
    instance_type str
    The ML compute instance type for the transform job.
    volume_kms_key_id str
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.
    instanceCount Number
    The number of ML compute instances to use in the transform job. For distributed transform jobs, specify a value greater than 1. The default value is 1.
    instanceType String
    The ML compute instance type for the transform job.
    volumeKmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt model data on the storage volume attached to the ML compute instance(s) that run the batch transform job.

    ModelPackageValidationProfile, ModelPackageValidationProfileArgs

    ProfileName string
    The name of the profile for the model package.
    TransformJobDefinition Pulumi.AwsNative.SageMaker.Inputs.ModelPackageTransformJobDefinition
    The TransformJobDefinition object that describes the transform job used for the validation of the model package.
    ProfileName string
    The name of the profile for the model package.
    TransformJobDefinition ModelPackageTransformJobDefinition
    The TransformJobDefinition object that describes the transform job used for the validation of the model package.
    profileName String
    The name of the profile for the model package.
    transformJobDefinition ModelPackageTransformJobDefinition
    The TransformJobDefinition object that describes the transform job used for the validation of the model package.
    profileName string
    The name of the profile for the model package.
    transformJobDefinition ModelPackageTransformJobDefinition
    The TransformJobDefinition object that describes the transform job used for the validation of the model package.
    profile_name str
    The name of the profile for the model package.
    transform_job_definition ModelPackageTransformJobDefinition
    The TransformJobDefinition object that describes the transform job used for the validation of the model package.
    profileName String
    The name of the profile for the model package.
    transformJobDefinition Property Map
    The TransformJobDefinition object that describes the transform job used for the validation of the model package.

    ModelPackageValidationSpecification, ModelPackageValidationSpecificationArgs

    ValidationProfiles List<Pulumi.AwsNative.SageMaker.Inputs.ModelPackageValidationProfile>
    An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
    ValidationRole string
    The IAM roles to be used for the validation of the model package.
    ValidationProfiles []ModelPackageValidationProfile
    An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
    ValidationRole string
    The IAM roles to be used for the validation of the model package.
    validationProfiles List<ModelPackageValidationProfile>
    An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
    validationRole String
    The IAM roles to be used for the validation of the model package.
    validationProfiles ModelPackageValidationProfile[]
    An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
    validationRole string
    The IAM roles to be used for the validation of the model package.
    validation_profiles Sequence[ModelPackageValidationProfile]
    An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
    validation_role str
    The IAM roles to be used for the validation of the model package.
    validationProfiles List<Property Map>
    An array of ModelPackageValidationProfile objects, each of which specifies a batch transform job that SageMaker runs to validate your model package.
    validationRole String
    The IAM roles to be used for the validation of the model package.

    Tag, TagArgs

    Key string
    The key name of the tag
    Value string
    The value of the tag
    Key string
    The key name of the tag
    Value string
    The value of the tag
    key String
    The key name of the tag
    value String
    The value of the tag
    key string
    The key name of the tag
    value string
    The value of the tag
    key str
    The key name of the tag
    value str
    The value of the tag
    key String
    The key name of the tag
    value String
    The value of the tag

    Package Details

    Repository
    AWS Native pulumi/pulumi-aws-native
    License
    Apache-2.0
    aws-native logo

    AWS Native is in preview. AWS Classic is fully supported.

    AWS Native v0.109.0 published on Wednesday, Jun 26, 2024 by Pulumi
    pulumi/pulumi-aws-native