aws-sdk/clients/sagemakerruntime.d.ts

import {Request} from '../lib/request';
import {Response} from '../lib/response';
import {AWSError} from '../lib/error';
import {Service} from '../lib/service';
import {ServiceConfigurationOptions} from '../lib/service';
import {ConfigBase as Config} from '../lib/config';
interface Blob {}
declare class SageMakerRuntime extends Service {
  /**
   * Constructs a service object. This object has one method for each API operation.
   */
  constructor(options?: SageMakerRuntime.Types.ClientConfiguration)
  config: Config & SageMakerRuntime.Types.ClientConfiguration;
  /**
   * After you deploy a model into production using Amazon SageMaker hosting services, your client applications use this API to get inferences from the model hosted at the specified endpoint.  For an overview of Amazon SageMaker, see How It Works.  Amazon SageMaker strips all POST headers except those supported by the API. Amazon SageMaker might add additional headers. You should not rely on the behavior of headers outside those enumerated in the request syntax.  Calls to InvokeEndpoint are authenticated by using AWS Signature Version 4. For information, see Authenticating Requests (AWS Signature Version 4) in the Amazon S3 API Reference. A customer's model containers must respond to requests within 60 seconds. The model itself can have a maximum processing time of 60 seconds before responding to the /invocations. If your model is going to take 50-60 seconds of processing time, the SDK socket timeout should be set to be 70 seconds.  Endpoints are scoped to an individual account, and are not public. The URL does not contain the account ID, but Amazon SageMaker determines the account ID from the authentication token that is supplied by the caller. 
   */
  invokeEndpoint(params: SageMakerRuntime.Types.InvokeEndpointInput, callback?: (err: AWSError, data: SageMakerRuntime.Types.InvokeEndpointOutput) => void): Request<SageMakerRuntime.Types.InvokeEndpointOutput, AWSError>;
  /**
   * After you deploy a model into production using Amazon SageMaker hosting services, your client applications use this API to get inferences from the model hosted at the specified endpoint.  For an overview of Amazon SageMaker, see How It Works.  Amazon SageMaker strips all POST headers except those supported by the API. Amazon SageMaker might add additional headers. You should not rely on the behavior of headers outside those enumerated in the request syntax.  Calls to InvokeEndpoint are authenticated by using AWS Signature Version 4. For information, see Authenticating Requests (AWS Signature Version 4) in the Amazon S3 API Reference. A customer's model containers must respond to requests within 60 seconds. The model itself can have a maximum processing time of 60 seconds before responding to the /invocations. If your model is going to take 50-60 seconds of processing time, the SDK socket timeout should be set to be 70 seconds.  Endpoints are scoped to an individual account, and are not public. The URL does not contain the account ID, but Amazon SageMaker determines the account ID from the authentication token that is supplied by the caller. 
   */
  invokeEndpoint(callback?: (err: AWSError, data: SageMakerRuntime.Types.InvokeEndpointOutput) => void): Request<SageMakerRuntime.Types.InvokeEndpointOutput, AWSError>;
}
declare namespace SageMakerRuntime {
  export type BodyBlob = Buffer|Uint8Array|Blob|string;
  export type CustomAttributesHeader = string;
  export type EndpointName = string;
  export type Header = string;
  export interface InvokeEndpointInput {
    /**
     * The name of the endpoint that you specified when you created the endpoint using the CreateEndpoint API. 
     */
    EndpointName: EndpointName;
    /**
     * Provides input data, in the format specified in the ContentType request header. Amazon SageMaker passes all of the data in the body to the model.  For information about the format of the request body, see Common Data Formats—Inference.
     */
    Body: BodyBlob;
    /**
     * The MIME type of the input data in the request body.
     */
    ContentType?: Header;
    /**
     * The desired MIME type of the inference in the response.
     */
    Accept?: Header;
    /**
     * 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). This feature is currently supported in the AWS SDKs but not in the Amazon SageMaker Python SDK.
     */
    CustomAttributes?: CustomAttributesHeader;
    /**
     * Specifies the model to be requested for an inference when invoking a multi-model endpoint. 
     */
    TargetModel?: TargetModelHeader;
  }
  export interface InvokeEndpointOutput {
    /**
     * Includes the inference provided by the model. For information about the format of the response body, see Common Data Formats—Inference.
     */
    Body: BodyBlob;
    /**
     * The MIME type of the inference returned in the response body.
     */
    ContentType?: Header;
    /**
     * Identifies the production variant that was invoked.
     */
    InvokedProductionVariant?: Header;
    /**
     * Provides additional information in the response about the inference returned by 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 return an ID received in the CustomAttributes header of a request or other metadata that a service endpoint was programmed to produce. 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). If the customer wants the custom attribute returned, the model must set the custom attribute to be included on the way back.  This feature is currently supported in the AWS SDKs but not in the Amazon SageMaker Python SDK.
     */
    CustomAttributes?: CustomAttributesHeader;
  }
  export type TargetModelHeader = string;
  /**
   * A string in YYYY-MM-DD format that represents the latest possible API version that can be used in this service. Specify 'latest' to use the latest possible version.
   */
  export type apiVersion = "2017-05-13"|"latest"|string;
  export interface ClientApiVersions {
    /**
     * A string in YYYY-MM-DD format that represents the latest possible API version that can be used in this service. Specify 'latest' to use the latest possible version.
     */
    apiVersion?: apiVersion;
  }
  export type ClientConfiguration = ServiceConfigurationOptions & ClientApiVersions;
  /**
   * Contains interfaces for use with the SageMakerRuntime client.
   */
  export import Types = SageMakerRuntime;
}
export = SageMakerRuntime;