import type { MetadataBearer as __MetadataBearer } from "@smithy/types";
import type { GetEvaluationInput, GetEvaluationOutput } from "../models/models_0";
/**
 * @public
 */
export type { __MetadataBearer };
/**
 * @public
 *
 * The input for {@link GetEvaluationCommand}.
 */
export interface GetEvaluationCommandInput extends GetEvaluationInput {
}
/**
 * @public
 *
 * The output of {@link GetEvaluationCommand}.
 */
export interface GetEvaluationCommandOutput extends GetEvaluationOutput, __MetadataBearer {
}
declare const GetEvaluationCommand_base: {
    new (input: GetEvaluationCommandInput): import("@smithy/core/client").CommandImpl<GetEvaluationCommandInput, GetEvaluationCommandOutput, import("..").MachineLearningClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    new (input: GetEvaluationCommandInput): import("@smithy/core/client").CommandImpl<GetEvaluationCommandInput, GetEvaluationCommandOutput, import("..").MachineLearningClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    getEndpointParameterInstructions(): import("@smithy/types").EndpointParameterInstructions;
};
/**
 * <p>Returns an <code>Evaluation</code> that includes metadata as well as the current status of the <code>Evaluation</code>.</p>
 * @example
 * Use a bare-bones client and the command you need to make an API call.
 * ```javascript
 * import { MachineLearningClient, GetEvaluationCommand } from "@aws-sdk/client-machine-learning"; // ES Modules import
 * // const { MachineLearningClient, GetEvaluationCommand } = require("@aws-sdk/client-machine-learning"); // CommonJS import
 * // import type { MachineLearningClientConfig } from "@aws-sdk/client-machine-learning";
 * const config = {}; // type is MachineLearningClientConfig
 * const client = new MachineLearningClient(config);
 * const input = { // GetEvaluationInput
 *   EvaluationId: "STRING_VALUE", // required
 * };
 * const command = new GetEvaluationCommand(input);
 * const response = await client.send(command);
 * // { // GetEvaluationOutput
 * //   EvaluationId: "STRING_VALUE",
 * //   MLModelId: "STRING_VALUE",
 * //   EvaluationDataSourceId: "STRING_VALUE",
 * //   InputDataLocationS3: "STRING_VALUE",
 * //   CreatedByIamUser: "STRING_VALUE",
 * //   CreatedAt: new Date("TIMESTAMP"),
 * //   LastUpdatedAt: new Date("TIMESTAMP"),
 * //   Name: "STRING_VALUE",
 * //   Status: "PENDING" || "INPROGRESS" || "FAILED" || "COMPLETED" || "DELETED",
 * //   PerformanceMetrics: { // PerformanceMetrics
 * //     Properties: { // PerformanceMetricsProperties
 * //       "<keys>": "STRING_VALUE",
 * //     },
 * //   },
 * //   LogUri: "STRING_VALUE",
 * //   Message: "STRING_VALUE",
 * //   ComputeTime: Number("long"),
 * //   FinishedAt: new Date("TIMESTAMP"),
 * //   StartedAt: new Date("TIMESTAMP"),
 * // };
 *
 * ```
 *
 * @param GetEvaluationCommandInput - {@link GetEvaluationCommandInput}
 * @returns {@link GetEvaluationCommandOutput}
 * @see {@link GetEvaluationCommandInput} for command's `input` shape.
 * @see {@link GetEvaluationCommandOutput} for command's `response` shape.
 * @see {@link MachineLearningClientResolvedConfig | config} for MachineLearningClient's `config` shape.
 *
 * @throws {@link InternalServerException} (server fault)
 *  <p>An error on the server occurred when trying to process a request.</p>
 *
 * @throws {@link InvalidInputException} (client fault)
 *  <p>An error on the client occurred. Typically, the cause is an invalid input value.</p>
 *
 * @throws {@link ResourceNotFoundException} (client fault)
 *  <p>A specified resource cannot be located.</p>
 *
 * @throws {@link MachineLearningServiceException}
 * <p>Base exception class for all service exceptions from MachineLearning service.</p>
 *
 *
 * @public
 */
export declare class GetEvaluationCommand extends GetEvaluationCommand_base {
    /** @internal type navigation helper, not in runtime. */
    protected static __types: {
        api: {
            input: GetEvaluationInput;
            output: GetEvaluationOutput;
        };
        sdk: {
            input: GetEvaluationCommandInput;
            output: GetEvaluationCommandOutput;
        };
    };
}