Struct aws_sdk_sagemaker::operation::update_inference_experiment::builders::UpdateInferenceExperimentInputBuilder

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

A builder for UpdateInferenceExperimentInput.

Implementations

impl UpdateInferenceExperimentInputBuilder

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

The name of the inference experiment to be updated.

This field is required.

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

The name of the inference experiment to be updated.

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

The name of the inference experiment to be updated.

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

The duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running, then you can update only the end date.

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

The duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running, then you can update only the end date.

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

The duration for which the inference experiment will run. If the status of the inference experiment is Created, then you can update both the start and end dates. If the status of the inference experiment is Running, then you can update only the end date.

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 model_variants(self, input: ModelVariantConfig) -> Self

Appends an item to model_variants.

To override the contents of this collection use set_model_variants.

An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.

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

An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.

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

An array of ModelVariantConfig objects. There is one for each variant, whose infrastructure configuration you want to update.

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. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify 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. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.

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

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

pub fn build(self) -> Result<UpdateInferenceExperimentInput, BuildError>

Consumes the builder and constructs a UpdateInferenceExperimentInput.

impl UpdateInferenceExperimentInputBuilder

pub async fn send_with( self, client: &Client, ) -> Result<UpdateInferenceExperimentOutput, SdkError<UpdateInferenceExperimentError, HttpResponse>>

Sends a request with this input using the given client.

Trait Implementations

impl Clone for UpdateInferenceExperimentInputBuilder

fn clone(&self) -> UpdateInferenceExperimentInputBuilder

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for UpdateInferenceExperimentInputBuilder

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

Formats the value using the given formatter.

impl Default for UpdateInferenceExperimentInputBuilder

fn default() -> UpdateInferenceExperimentInputBuilder

Returns the “default value” for a type.

impl PartialEq for UpdateInferenceExperimentInputBuilder

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