Struct aws_sdk_sagemakerruntime::operation::invoke_endpoint_async::InvokeEndpointAsyncInput

#[non_exhaustive]
pub struct InvokeEndpointAsyncInput {
    pub endpoint_name: Option<String>,
    pub content_type: Option<String>,
    pub accept: Option<String>,
    pub custom_attributes: Option<String>,
    pub inference_id: Option<String>,
    pub input_location: Option<String>,
    pub request_ttl_seconds: Option<i32>,
    pub invocation_timeout_seconds: Option<i32>,
}

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.

endpoint_name: Option<String>

The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API.

content_type: Option<String>

The MIME type of the input data in the request body.

accept: Option<String>

The desired MIME type of the inference response from the model container.

custom_attributes: Option<String>

Provides additional information about a request for an inference submitted to a model hosted at an Amazon SageMaker endpoint. The information is an opaque value that is forwarded verbatim. You could use this value, for example, to provide an ID that you can use to track a request or to provide other metadata that a service endpoint was programmed to process. The value must consist of no more than 1024 visible US-ASCII characters as specified in Section 3.3.6. Field Value Components of the Hypertext Transfer Protocol (HTTP/1.1).

The code in your model is responsible for setting or updating any custom attributes in the response. If your code does not set this value in the response, an empty value is returned. For example, if a custom attribute represents the trace ID, your model can prepend the custom attribute with Trace ID: in your post-processing function.

This feature is currently supported in the Amazon Web Services SDKs but not in the Amazon SageMaker Python SDK.

inference_id: Option<String>

The identifier for the inference request. Amazon SageMaker will generate an identifier for you if none is specified.

input_location: Option<String>

The Amazon S3 URI where the inference request payload is stored.

request_ttl_seconds: Option<i32>

Maximum age in seconds a request can be in the queue before it is marked as expired. The default is 6 hours, or 21,600 seconds.

invocation_timeout_seconds: Option<i32>

Maximum amount of time in seconds a request can be processed before it is marked as expired. The default is 15 minutes, or 900 seconds.

Implementations

impl InvokeEndpointAsyncInput

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

The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API.

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

The MIME type of the input data in the request body.

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

The desired MIME type of the inference response from the model container.

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

Provides additional information about a request for an inference submitted to a model hosted at an Amazon SageMaker endpoint. The information is an opaque value that is forwarded verbatim. You could use this value, for example, to provide an ID that you can use to track a request or to provide other metadata that a service endpoint was programmed to process. The value must consist of no more than 1024 visible US-ASCII characters as specified in Section 3.3.6. Field Value Components of the Hypertext Transfer Protocol (HTTP/1.1).

The code in your model is responsible for setting or updating any custom attributes in the response. If your code does not set this value in the response, an empty value is returned. For example, if a custom attribute represents the trace ID, your model can prepend the custom attribute with Trace ID: in your post-processing function.

This feature is currently supported in the Amazon Web Services SDKs but not in the Amazon SageMaker Python SDK.

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

The identifier for the inference request. Amazon SageMaker will generate an identifier for you if none is specified.

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

The Amazon S3 URI where the inference request payload is stored.

pub fn request_ttl_seconds(&self) -> Option<i32>

Maximum age in seconds a request can be in the queue before it is marked as expired. The default is 6 hours, or 21,600 seconds.

pub fn invocation_timeout_seconds(&self) -> Option<i32>

Maximum amount of time in seconds a request can be processed before it is marked as expired. The default is 15 minutes, or 900 seconds.

impl InvokeEndpointAsyncInput

pub fn builder() -> InvokeEndpointAsyncInputBuilder

Creates a new builder-style object to manufacture InvokeEndpointAsyncInput.

Trait Implementations

impl Clone for InvokeEndpointAsyncInput

fn clone(&self) -> InvokeEndpointAsyncInput

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for InvokeEndpointAsyncInput

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

Formats the value using the given formatter.

impl PartialEq for InvokeEndpointAsyncInput

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