import type { MetadataBearer as __MetadataBearer } from "@smithy/types";
import type { DescribeMLModelsInput, DescribeMLModelsOutput } from "../models/models_0";
/**
 * @public
 */
export type { __MetadataBearer };
/**
 * @public
 *
 * The input for {@link DescribeMLModelsCommand}.
 */
export interface DescribeMLModelsCommandInput extends DescribeMLModelsInput {
}
/**
 * @public
 *
 * The output of {@link DescribeMLModelsCommand}.
 */
export interface DescribeMLModelsCommandOutput extends DescribeMLModelsOutput, __MetadataBearer {
}
declare const DescribeMLModelsCommand_base: {
    new (input: DescribeMLModelsCommandInput): import("@smithy/core/client").CommandImpl<DescribeMLModelsCommandInput, DescribeMLModelsCommandOutput, import("..").MachineLearningClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    new (...[input]: [] | [DescribeMLModelsCommandInput]): import("@smithy/core/client").CommandImpl<DescribeMLModelsCommandInput, DescribeMLModelsCommandOutput, import("..").MachineLearningClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    getEndpointParameterInstructions(): import("@smithy/types").EndpointParameterInstructions;
};
/**
 * <p>Returns a list of <code>MLModel</code> that match the search criteria in the request.</p>
 * @example
 * Use a bare-bones client and the command you need to make an API call.
 * ```javascript
 * import { MachineLearningClient, DescribeMLModelsCommand } from "@aws-sdk/client-machine-learning"; // ES Modules import
 * // const { MachineLearningClient, DescribeMLModelsCommand } = 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 = { // DescribeMLModelsInput
 *   FilterVariable: "CreatedAt" || "LastUpdatedAt" || "Status" || "Name" || "IAMUser" || "TrainingDataSourceId" || "RealtimeEndpointStatus" || "MLModelType" || "Algorithm" || "TrainingDataURI",
 *   EQ: "STRING_VALUE",
 *   GT: "STRING_VALUE",
 *   LT: "STRING_VALUE",
 *   GE: "STRING_VALUE",
 *   LE: "STRING_VALUE",
 *   NE: "STRING_VALUE",
 *   Prefix: "STRING_VALUE",
 *   SortOrder: "asc" || "dsc",
 *   NextToken: "STRING_VALUE",
 *   Limit: Number("int"),
 * };
 * const command = new DescribeMLModelsCommand(input);
 * const response = await client.send(command);
 * // { // DescribeMLModelsOutput
 * //   Results: [ // MLModels
 * //     { // MLModel
 * //       MLModelId: "STRING_VALUE",
 * //       TrainingDataSourceId: "STRING_VALUE",
 * //       CreatedByIamUser: "STRING_VALUE",
 * //       CreatedAt: new Date("TIMESTAMP"),
 * //       LastUpdatedAt: new Date("TIMESTAMP"),
 * //       Name: "STRING_VALUE",
 * //       Status: "PENDING" || "INPROGRESS" || "FAILED" || "COMPLETED" || "DELETED",
 * //       SizeInBytes: Number("long"),
 * //       EndpointInfo: { // RealtimeEndpointInfo
 * //         PeakRequestsPerSecond: Number("int"),
 * //         CreatedAt: new Date("TIMESTAMP"),
 * //         EndpointUrl: "STRING_VALUE",
 * //         EndpointStatus: "NONE" || "READY" || "UPDATING" || "FAILED",
 * //       },
 * //       TrainingParameters: { // TrainingParameters
 * //         "<keys>": "STRING_VALUE",
 * //       },
 * //       InputDataLocationS3: "STRING_VALUE",
 * //       Algorithm: "sgd",
 * //       MLModelType: "REGRESSION" || "BINARY" || "MULTICLASS",
 * //       ScoreThreshold: Number("float"),
 * //       ScoreThresholdLastUpdatedAt: new Date("TIMESTAMP"),
 * //       Message: "STRING_VALUE",
 * //       ComputeTime: Number("long"),
 * //       FinishedAt: new Date("TIMESTAMP"),
 * //       StartedAt: new Date("TIMESTAMP"),
 * //     },
 * //   ],
 * //   NextToken: "STRING_VALUE",
 * // };
 *
 * ```
 *
 * @param DescribeMLModelsCommandInput - {@link DescribeMLModelsCommandInput}
 * @returns {@link DescribeMLModelsCommandOutput}
 * @see {@link DescribeMLModelsCommandInput} for command's `input` shape.
 * @see {@link DescribeMLModelsCommandOutput} 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 MachineLearningServiceException}
 * <p>Base exception class for all service exceptions from MachineLearning service.</p>
 *
 *
 * @public
 */
export declare class DescribeMLModelsCommand extends DescribeMLModelsCommand_base {
    /** @internal type navigation helper, not in runtime. */
    protected static __types: {
        api: {
            input: DescribeMLModelsInput;
            output: DescribeMLModelsOutput;
        };
        sdk: {
            input: DescribeMLModelsCommandInput;
            output: DescribeMLModelsCommandOutput;
        };
    };
}