Struct aws_sdk_sagemaker::operation::describe_inference_experiment::builders::DescribeInferenceExperimentOutputBuilder

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

A builder for DescribeInferenceExperimentOutput.

Implementations

impl DescribeInferenceExperimentOutputBuilder

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

The ARN of the inference experiment being described.

This field is required.

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

The ARN of the inference experiment being described.

pub fn get_arn(&self) -> &Option<String>

The ARN of the inference experiment being described.

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

The name of the inference experiment.

This field is required.

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

The name of the inference experiment.

pub fn get_name(&self) -> &Option<String>

The name of the inference experiment.

pub fn type(self, input: InferenceExperimentType) -> Self

The type of the inference experiment.

This field is required.

pub fn set_type(self, input: Option<InferenceExperimentType>) -> Self

The type of the inference experiment.

pub fn get_type(&self) -> &Option<InferenceExperimentType>

The type of the inference experiment.

pub fn schedule(self, input: InferenceExperimentSchedule) -> Self

The duration for which the inference experiment ran or will run.

pub fn set_schedule(self, input: Option<InferenceExperimentSchedule>) -> Self

The duration for which the inference experiment ran or will run.

pub fn get_schedule(&self) -> &Option<InferenceExperimentSchedule>

The duration for which the inference experiment ran or will run.

pub fn status(self, input: InferenceExperimentStatus) -> Self

The status of the inference experiment. The following are the possible statuses for an inference experiment:

• Creating - Amazon SageMaker is creating your experiment.

• Created - Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.

• Updating - When you make changes to your experiment, your experiment shows as updating.

• Starting - Amazon SageMaker is beginning your experiment.

• Running - Your experiment is in progress.

• Stopping - Amazon SageMaker is stopping your experiment.

• Completed - Your experiment has completed.

• Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.

This field is required.

pub fn set_status(self, input: Option<InferenceExperimentStatus>) -> Self

The status of the inference experiment. The following are the possible statuses for an inference experiment:

• Creating - Amazon SageMaker is creating your experiment.

• Created - Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.

• Updating - When you make changes to your experiment, your experiment shows as updating.

• Starting - Amazon SageMaker is beginning your experiment.

• Running - Your experiment is in progress.

• Stopping - Amazon SageMaker is stopping your experiment.

• Completed - Your experiment has completed.

• Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.

pub fn get_status(&self) -> &Option<InferenceExperimentStatus>

The status of the inference experiment. The following are the possible statuses for an inference experiment:

• Creating - Amazon SageMaker is creating your experiment.

• Created - Amazon SageMaker has finished the creation of your experiment and will begin the experiment at the scheduled time.

• Updating - When you make changes to your experiment, your experiment shows as updating.

• Starting - Amazon SageMaker is beginning your experiment.

• Running - Your experiment is in progress.

• Stopping - Amazon SageMaker is stopping your experiment.

• Completed - Your experiment has completed.

• Cancelled - When you conclude your experiment early using the StopInferenceExperiment API, or if any operation fails with an unexpected error, it shows as cancelled.

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

The error message or client-specified Reason from the StopInferenceExperiment API, that explains the status of the inference experiment.

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

The error message or client-specified Reason from the StopInferenceExperiment API, that explains the status of the inference experiment.

pub fn get_status_reason(&self) -> &Option<String>

The error message or client-specified Reason from the StopInferenceExperiment API, that explains the status of the inference experiment.

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

The description of the inference experiment.

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

The description of the inference experiment.

pub fn get_description(&self) -> &Option<String>

The description of the inference experiment.

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

The timestamp at which you created the inference experiment.

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

The timestamp at which you created the inference experiment.

pub fn get_creation_time(&self) -> &Option<DateTime>

The timestamp at which you created the inference experiment.

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

The timestamp at which the inference experiment was completed.

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

The timestamp at which the inference experiment was completed.

pub fn get_completion_time(&self) -> &Option<DateTime>

The timestamp at which the inference experiment was completed.

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

The timestamp at which you last modified the inference experiment.

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

The timestamp at which you last modified the inference experiment.

pub fn get_last_modified_time(&self) -> &Option<DateTime>

The timestamp at which you last modified the inference experiment.

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

The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.

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

The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.

pub fn get_role_arn(&self) -> &Option<String>

The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.

pub fn endpoint_metadata(self, input: EndpointMetadata) -> Self

The metadata of the endpoint on which the inference experiment ran.

This field is required.

pub fn set_endpoint_metadata(self, input: Option<EndpointMetadata>) -> Self

The metadata of the endpoint on which the inference experiment ran.

pub fn get_endpoint_metadata(&self) -> &Option<EndpointMetadata>

The metadata of the endpoint on which the inference experiment ran.

pub fn model_variants(self, input: ModelVariantConfigSummary) -> Self

Appends an item to model_variants.

To override the contents of this collection use set_model_variants.

An array of ModelVariantConfigSummary objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure configuration for deploying the corresponding variant.

pub fn set_model_variants( self, input: Option<Vec<ModelVariantConfigSummary>> ) -> Self

An array of ModelVariantConfigSummary objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure configuration for deploying the corresponding variant.

pub fn get_model_variants(&self) -> &Option<Vec<ModelVariantConfigSummary>>

An array of ModelVariantConfigSummary objects. There is one for each variant in the inference experiment. Each ModelVariantConfigSummary object in the array describes the infrastructure configuration for deploying the corresponding variant.

pub fn data_storage_config( self, input: InferenceExperimentDataStorageConfig ) -> Self

The Amazon S3 location and configuration for storing inference request and response data.

pub fn set_data_storage_config( self, input: Option<InferenceExperimentDataStorageConfig> ) -> Self

The Amazon S3 location and configuration for storing inference request and response data.

pub fn get_data_storage_config( &self ) -> &Option<InferenceExperimentDataStorageConfig>

The Amazon S3 location and configuration for storing inference request and response data.

pub fn shadow_mode_config(self, input: ShadowModeConfig) -> Self

The configuration of ShadowMode inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.

pub fn set_shadow_mode_config(self, input: Option<ShadowModeConfig>) -> Self

The configuration of ShadowMode inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.

pub fn get_shadow_mode_config(&self) -> &Option<ShadowModeConfig>

The configuration of ShadowMode inference experiment type, which shows the production variant that takes all the inference requests, and the shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant it also shows the percentage of requests that Amazon SageMaker replicates.

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

The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.

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

The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.

pub fn get_kms_key(&self) -> &Option<String>

The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. For more information, see CreateInferenceExperiment.

pub fn build(self) -> DescribeInferenceExperimentOutput

Consumes the builder and constructs a DescribeInferenceExperimentOutput.

Trait Implementations

impl Clone for DescribeInferenceExperimentOutputBuilder

fn clone(&self) -> DescribeInferenceExperimentOutputBuilder

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for DescribeInferenceExperimentOutputBuilder

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

Formats the value using the given formatter.

impl Default for DescribeInferenceExperimentOutputBuilder

fn default() -> DescribeInferenceExperimentOutputBuilder

Returns the “default value” for a type.

impl PartialEq for DescribeInferenceExperimentOutputBuilder

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