Struct aws_sdk_sagemaker::model::model_package::Builder

pub struct Builder { /* private fields */ }

A builder for ModelPackage.

Implementations

impl Builder

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

The name of the model.

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

The name of the model.

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

The model group to which the model belongs.

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

The model group to which the model belongs.

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

The version number of a versioned model.

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

The version number of a versioned model.

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

The description of the model package.

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

The description of the model package.

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

The time that the model package was created.

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

The time that the model package was created.

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

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

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

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

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

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

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

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

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

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

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

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

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

The status of the model package. This can be one of the following values.

• PENDING - The model package is pending being created.

• IN_PROGRESS - The model package is in the process of being created.

• COMPLETED - The model package was successfully created.

• FAILED - The model package failed.

• DELETING - The model package is in the process of being deleted.

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

The status of the model package. This can be one of the following values.

• PENDING - The model package is pending being created.

• IN_PROGRESS - The model package is in the process of being created.

• COMPLETED - The model package was successfully created.

• FAILED - The model package failed.

• DELETING - The model package is in the process of being deleted.

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

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

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

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

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

Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.

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

Whether the model package is to be certified to be listed on Amazon Web Services Marketplace. For information about listing model packages on Amazon Web Services Marketplace, see List Your Algorithm or Model Package on Amazon Web Services Marketplace.

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

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.

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

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.

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

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

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, or project.

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 the model package was modified.

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

The last time 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, or project.

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, or project.

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

A description provided when the model approval is set.

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

A description provided when the model approval is set.

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

The machine learning domain of your model package and its components. 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 your model package and its components. Common machine learning domains include computer vision and natural language processing.

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

The machine learning task 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 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 path where the sample payload are stored. This path must point 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 path where the sample payload are stored. This path must point 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.

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

An array of additional Inference Specification objects.

pub fn tags(self, input: Tag) -> Self

Appends an item to tags.

To override the contents of this collection use set_tags.

A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.

pub fn set_tags(self, input: Option<Vec<Tag>>) -> Self

A list of the tags associated with the model package. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.

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 for the model package.

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

The metadata properties for the model package.

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.

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.

pub fn build(self) -> ModelPackage

Consumes the builder and constructs a ModelPackage.

Trait Implementations

impl Clone for Builder

fn clone(&self) -> Builder

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for Builder

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

Formats the value using the given formatter.

impl Default for Builder

fn default() -> Builder

Returns the “default value” for a type.

impl PartialEq<Builder> for Builder

fn eq(&self, other: &Builder) -> 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 Builder