import type { MetadataBearer as __MetadataBearer } from "@smithy/types"; import type { DescribeAIWorkloadConfigRequest, DescribeAIWorkloadConfigResponse } from "../models/models_2"; /** * @public */ export type { __MetadataBearer }; /** * @public * * The input for {@link DescribeAIWorkloadConfigCommand}. */ export interface DescribeAIWorkloadConfigCommandInput extends DescribeAIWorkloadConfigRequest { } /** * @public * * The output of {@link DescribeAIWorkloadConfigCommand}. */ export interface DescribeAIWorkloadConfigCommandOutput extends DescribeAIWorkloadConfigResponse, __MetadataBearer { } declare const DescribeAIWorkloadConfigCommand_base: { new (input: DescribeAIWorkloadConfigCommandInput): import("@smithy/core/client").CommandImpl; new (input: DescribeAIWorkloadConfigCommandInput): import("@smithy/core/client").CommandImpl; getEndpointParameterInstructions(): import("@smithy/types").EndpointParameterInstructions; }; /** *

Returns details of an AI workload configuration, including the dataset configuration, benchmark tool settings, tags, and creation time.

* @example * Use a bare-bones client and the command you need to make an API call. * ```javascript * import { SageMakerClient, DescribeAIWorkloadConfigCommand } from "@aws-sdk/client-sagemaker"; // ES Modules import * // const { SageMakerClient, DescribeAIWorkloadConfigCommand } = require("@aws-sdk/client-sagemaker"); // CommonJS import * // import type { SageMakerClientConfig } from "@aws-sdk/client-sagemaker"; * const config = {}; // type is SageMakerClientConfig * const client = new SageMakerClient(config); * const input = { // DescribeAIWorkloadConfigRequest * AIWorkloadConfigName: "STRING_VALUE", // required * }; * const command = new DescribeAIWorkloadConfigCommand(input); * const response = await client.send(command); * // { // DescribeAIWorkloadConfigResponse * // AIWorkloadConfigName: "STRING_VALUE", // required * // AIWorkloadConfigArn: "STRING_VALUE", // required * // DatasetConfig: { // AIDatasetConfig Union: only one key present * // InputDataConfig: [ // AIWorkloadInputDataConfigList * // { // AIWorkloadInputDataConfig * // ChannelName: "STRING_VALUE", // required * // DataSource: { // AIWorkloadDataSource * // S3DataSource: { // AIWorkloadS3DataSource * // S3Uri: "STRING_VALUE", // required * // }, * // }, * // }, * // ], * // }, * // AIWorkloadConfigs: { // AIWorkloadConfigs * // WorkloadSpec: { // WorkloadSpec Union: only one key present * // Inline: "STRING_VALUE", * // }, * // }, * // Tags: [ // TagList * // { // Tag * // Key: "STRING_VALUE", // required * // Value: "STRING_VALUE", // required * // }, * // ], * // CreationTime: new Date("TIMESTAMP"), // required * // }; * * ``` * * @param DescribeAIWorkloadConfigCommandInput - {@link DescribeAIWorkloadConfigCommandInput} * @returns {@link DescribeAIWorkloadConfigCommandOutput} * @see {@link DescribeAIWorkloadConfigCommandInput} for command's `input` shape. * @see {@link DescribeAIWorkloadConfigCommandOutput} for command's `response` shape. * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape. * * @throws {@link ResourceNotFound} (client fault) *

Resource being access is not found.

* * @throws {@link SageMakerServiceException} *

Base exception class for all service exceptions from SageMaker service.

* * * @public */ export declare class DescribeAIWorkloadConfigCommand extends DescribeAIWorkloadConfigCommand_base { /** @internal type navigation helper, not in runtime. */ protected static __types: { api: { input: DescribeAIWorkloadConfigRequest; output: DescribeAIWorkloadConfigResponse; }; sdk: { input: DescribeAIWorkloadConfigCommandInput; output: DescribeAIWorkloadConfigCommandOutput; }; }; }