Struct aws_sdk_sagemaker::operation::describe_model_package::builders::DescribeModelPackageOutputBuilder

#[non_exhaustive]
pub struct DescribeModelPackageOutputBuilder { /* private fields */ }

A builder for DescribeModelPackageOutput.

Implementations

impl DescribeModelPackageOutputBuilder

pub fn model_package_name(self, input: impl Into<String>) -> Self

The name of the model package being described.

pub fn set_model_package_name(self, input: Option<String>) -> Self

The name of the model package being described.

pub fn model_package_group_name(self, input: impl Into<String>) -> Self

If the model is a versioned model, the name of the model group that the versioned model belongs to.

pub fn set_model_package_group_name(self, input: Option<String>) -> Self

If the model is a versioned model, the name of the model group that the versioned model belongs to.

pub fn model_package_version(self, input: i32) -> Self

The version of the model package.

pub fn set_model_package_version(self, input: Option<i32>) -> Self

The version of the model package.

pub fn model_package_arn(self, input: impl Into<String>) -> Self

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

pub fn set_model_package_arn(self, input: Option<String>) -> Self

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

pub fn model_package_description(self, input: impl Into<String>) -> Self

A brief summary of the model package.

pub fn set_model_package_description(self, input: Option<String>) -> Self

A brief summary of the model package.

pub fn creation_time(self, input: DateTime) -> Self

A timestamp specifying when the model package was created.

pub fn set_creation_time(self, input: Option<DateTime>) -> Self

A timestamp specifying when the model package was created.

pub fn inference_specification(self, input: InferenceSpecification) -> Self

Details about inference jobs that can be run with models based on this model package.

pub fn set_inference_specification( self, input: Option<InferenceSpecification> ) -> Self

Details about inference jobs that can be run with models based on this model package.

pub fn source_algorithm_specification( self, input: SourceAlgorithmSpecification ) -> Self

Details about the algorithm that was used to create the model package.

pub fn set_source_algorithm_specification( self, input: Option<SourceAlgorithmSpecification> ) -> Self

Details about the algorithm that was used to create the model package.

pub fn validation_specification( self, input: ModelPackageValidationSpecification ) -> Self

Configurations for one or more transform jobs that SageMaker runs to test the model package.

pub fn set_validation_specification( self, input: Option<ModelPackageValidationSpecification> ) -> Self

Configurations for one or more transform jobs that SageMaker runs to test the model package.

pub fn model_package_status(self, input: ModelPackageStatus) -> Self

The current status of the model package.

pub fn set_model_package_status(self, input: Option<ModelPackageStatus>) -> Self

The current status of the model package.

pub fn model_package_status_details( self, input: ModelPackageStatusDetails ) -> Self

Details about the current status of the model package.

pub fn set_model_package_status_details( self, input: Option<ModelPackageStatusDetails> ) -> Self

Details about the current status of the model package.

pub fn certify_for_marketplace(self, input: bool) -> Self

Whether the model package is certified for listing on Amazon Web Services Marketplace.

pub fn set_certify_for_marketplace(self, input: Option<bool>) -> Self

Whether the model package is certified for listing on Amazon Web Services Marketplace.

pub fn model_approval_status(self, input: ModelApprovalStatus) -> Self

The approval status of the model package.

pub fn set_model_approval_status( self, input: Option<ModelApprovalStatus> ) -> Self

The approval status of the model package.

pub fn created_by(self, input: UserContext) -> Self

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

pub fn set_created_by(self, input: Option<UserContext>) -> Self

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

pub fn metadata_properties(self, input: MetadataProperties) -> Self

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

pub fn set_metadata_properties(self, input: Option<MetadataProperties>) -> Self

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

pub fn model_metrics(self, input: ModelMetrics) -> Self

Metrics for the model.

pub fn set_model_metrics(self, input: Option<ModelMetrics>) -> Self

Metrics for the model.

pub fn last_modified_time(self, input: DateTime) -> Self

The last time that the model package was modified.

pub fn set_last_modified_time(self, input: Option<DateTime>) -> Self

The last time that the model package was modified.

pub fn last_modified_by(self, input: UserContext) -> Self

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

pub fn set_last_modified_by(self, input: Option<UserContext>) -> Self

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

pub fn approval_description(self, input: impl Into<String>) -> Self

A description provided for the model approval.

pub fn set_approval_description(self, input: Option<String>) -> Self

A description provided for the model approval.

pub fn customer_metadata_properties( self, k: impl Into<String>, v: impl Into<String> ) -> Self

Adds a key-value pair to customer_metadata_properties.

To override the contents of this collection use set_customer_metadata_properties.

The metadata properties associated with the model package versions.

pub fn set_customer_metadata_properties( self, input: Option<HashMap<String, String>> ) -> Self

The metadata properties associated with the model package versions.

pub fn drift_check_baselines(self, input: DriftCheckBaselines) -> Self

Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.

pub fn set_drift_check_baselines( self, input: Option<DriftCheckBaselines> ) -> Self

Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.

pub fn domain(self, input: impl Into<String>) -> Self

The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.

pub fn set_domain(self, input: Option<String>) -> Self

The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.

pub fn task(self, input: impl Into<String>) -> Self

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

pub fn set_task(self, input: Option<String>) -> Self

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

pub fn sample_payload_url(self, input: impl Into<String>) -> Self

The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).

pub fn set_sample_payload_url(self, input: Option<String>) -> Self

The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).

pub fn additional_inference_specifications( self, input: AdditionalInferenceSpecificationDefinition ) -> Self

Appends an item to additional_inference_specifications.

To override the contents of this collection use set_additional_inference_specifications.

An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.

pub fn set_additional_inference_specifications( self, input: Option<Vec<AdditionalInferenceSpecificationDefinition>> ) -> Self

An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.

pub fn build(self) -> DescribeModelPackageOutput

Consumes the builder and constructs a DescribeModelPackageOutput.

Trait Implementations

impl Clone for DescribeModelPackageOutputBuilder

fn clone(&self) -> DescribeModelPackageOutputBuilder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for DescribeModelPackageOutputBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for DescribeModelPackageOutputBuilder

fn default() -> DescribeModelPackageOutputBuilder

Returns the “default value” for a type.

impl PartialEq<DescribeModelPackageOutputBuilder> for DescribeModelPackageOutputBuilder

fn eq(&self, other: &DescribeModelPackageOutputBuilder) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for DescribeModelPackageOutputBuilder