Struct aws_sdk_sagemaker::operation::update_inference_experiment::UpdateInferenceExperimentInput

#[non_exhaustive]
pub struct UpdateInferenceExperimentInput {
    pub name: Option<String>,
    pub schedule: Option<InferenceExperimentSchedule>,
    pub description: Option<String>,
    pub model_variants: Option<Vec<ModelVariantConfig>>,
    pub data_storage_config: Option<InferenceExperimentDataStorageConfig>,
    pub shadow_mode_config: Option<ShadowModeConfig>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

name: Option<String>

The name of the inference experiment to be updated.

schedule: 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.

description: Option<String>

The description of the inference experiment.

model_variants: Option<Vec<ModelVariantConfig>>

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

data_storage_config: Option<InferenceExperimentDataStorageConfig>

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

shadow_mode_config: 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.

Implementations

impl UpdateInferenceExperimentInput

pub fn name(&self) -> Option<&str>

The name of the inference experiment to be updated.

pub fn 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) -> Option<&str>

The description of the inference experiment.

pub fn model_variants(&self) -> &[ModelVariantConfig]

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

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .model_variants.is_none().

pub fn 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) -> 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.

impl UpdateInferenceExperimentInput

pub fn builder() -> UpdateInferenceExperimentInputBuilder

Creates a new builder-style object to manufacture UpdateInferenceExperimentInput.

Trait Implementations

impl Clone for UpdateInferenceExperimentInput

fn clone(&self) -> UpdateInferenceExperimentInput

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for UpdateInferenceExperimentInput

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

Formats the value using the given formatter.

impl PartialEq for UpdateInferenceExperimentInput

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