Struct InferenceComponentSpecification

#[non_exhaustive]
pub struct InferenceComponentSpecification {
    pub model_name: Option<String>,
    pub container: Option<InferenceComponentContainerSpecification>,
    pub startup_parameters: Option<InferenceComponentStartupParameters>,
    pub compute_resource_requirements: Option<InferenceComponentComputeResourceRequirements>,
    pub base_inference_component_name: Option<String>,
}

Details about the resources to deploy with this inference component, including the model, container, and compute resources.

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.

model_name: Option<String>

The name of an existing SageMaker AI model object in your account that you want to deploy with the inference component.

container: Option<InferenceComponentContainerSpecification>

Defines a container that provides the runtime environment for a model that you deploy with an inference component.

startup_parameters: Option<InferenceComponentStartupParameters>

Settings that take effect while the model container starts up.

compute_resource_requirements: Option<InferenceComponentComputeResourceRequirements>

The compute resources allocated to run the model, plus any adapter models, that you assign to the inference component.

Omit this parameter if your request is meant to create an adapter inference component. An adapter inference component is loaded by a base inference component, and it uses the compute resources of the base inference component.

base_inference_component_name: Option<String>

The name of an existing inference component that is to contain the inference component that you're creating with your request.

Specify this parameter only if your request is meant to create an adapter inference component. An adapter inference component contains the path to an adapter model. The purpose of the adapter model is to tailor the inference output of a base foundation model, which is hosted by the base inference component. The adapter inference component uses the compute resources that you assigned to the base inference component.

When you create an adapter inference component, use the Container parameter to specify the location of the adapter artifacts. In the parameter value, use the ArtifactUrl parameter of the InferenceComponentContainerSpecification data type.

Before you can create an adapter inference component, you must have an existing inference component that contains the foundation model that you want to adapt.

Implementations

impl InferenceComponentSpecification

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

The name of an existing SageMaker AI model object in your account that you want to deploy with the inference component.

pub fn container(&self) -> Option<&InferenceComponentContainerSpecification>

Defines a container that provides the runtime environment for a model that you deploy with an inference component.

pub fn startup_parameters(&self) -> Option<&InferenceComponentStartupParameters>

Settings that take effect while the model container starts up.

pub fn compute_resource_requirements( &self, ) -> Option<&InferenceComponentComputeResourceRequirements>

The compute resources allocated to run the model, plus any adapter models, that you assign to the inference component.

Omit this parameter if your request is meant to create an adapter inference component. An adapter inference component is loaded by a base inference component, and it uses the compute resources of the base inference component.

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

The name of an existing inference component that is to contain the inference component that you're creating with your request.

Specify this parameter only if your request is meant to create an adapter inference component. An adapter inference component contains the path to an adapter model. The purpose of the adapter model is to tailor the inference output of a base foundation model, which is hosted by the base inference component. The adapter inference component uses the compute resources that you assigned to the base inference component.

When you create an adapter inference component, use the Container parameter to specify the location of the adapter artifacts. In the parameter value, use the ArtifactUrl parameter of the InferenceComponentContainerSpecification data type.

Before you can create an adapter inference component, you must have an existing inference component that contains the foundation model that you want to adapt.

impl InferenceComponentSpecification

pub fn builder() -> InferenceComponentSpecificationBuilder

Creates a new builder-style object to manufacture InferenceComponentSpecification.

Trait Implementations

impl Clone for InferenceComponentSpecification

fn clone(&self) -> InferenceComponentSpecification

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for InferenceComponentSpecification

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

Formats the value using the given formatter.

impl PartialEq for InferenceComponentSpecification

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for InferenceComponentSpecification