import { Command as $Command } from "@smithy/smithy-client";
import { MetadataBearer as __MetadataBearer } from "@smithy/types";
import { UpdateInferenceComponentRuntimeConfigInput, UpdateInferenceComponentRuntimeConfigOutput } from "../models/models_5";
import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient";
/**
 * @public
 */
export type { __MetadataBearer };
export { $Command };
/**
 * @public
 *
 * The input for {@link UpdateInferenceComponentRuntimeConfigCommand}.
 */
export interface UpdateInferenceComponentRuntimeConfigCommandInput extends UpdateInferenceComponentRuntimeConfigInput {
}
/**
 * @public
 *
 * The output of {@link UpdateInferenceComponentRuntimeConfigCommand}.
 */
export interface UpdateInferenceComponentRuntimeConfigCommandOutput extends UpdateInferenceComponentRuntimeConfigOutput, __MetadataBearer {
}
declare const UpdateInferenceComponentRuntimeConfigCommand_base: {
    new (input: UpdateInferenceComponentRuntimeConfigCommandInput): import("@smithy/smithy-client").CommandImpl<UpdateInferenceComponentRuntimeConfigCommandInput, UpdateInferenceComponentRuntimeConfigCommandOutput, SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes>;
    new (input: UpdateInferenceComponentRuntimeConfigCommandInput): import("@smithy/smithy-client").CommandImpl<UpdateInferenceComponentRuntimeConfigCommandInput, UpdateInferenceComponentRuntimeConfigCommandOutput, SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes>;
    getEndpointParameterInstructions(): import("@smithy/middleware-endpoint").EndpointParameterInstructions;
};
/**
 * <p>Runtime settings for a model that is deployed with an inference component.</p>
 * @example
 * Use a bare-bones client and the command you need to make an API call.
 * ```javascript
 * import { SageMakerClient, UpdateInferenceComponentRuntimeConfigCommand } from "@aws-sdk/client-sagemaker"; // ES Modules import
 * // const { SageMakerClient, UpdateInferenceComponentRuntimeConfigCommand } = require("@aws-sdk/client-sagemaker"); // CommonJS import
 * const client = new SageMakerClient(config);
 * const input = { // UpdateInferenceComponentRuntimeConfigInput
 *   InferenceComponentName: "STRING_VALUE", // required
 *   DesiredRuntimeConfig: { // InferenceComponentRuntimeConfig
 *     CopyCount: Number("int"), // required
 *   },
 * };
 * const command = new UpdateInferenceComponentRuntimeConfigCommand(input);
 * const response = await client.send(command);
 * // { // UpdateInferenceComponentRuntimeConfigOutput
 * //   InferenceComponentArn: "STRING_VALUE", // required
 * // };
 *
 * ```
 *
 * @param UpdateInferenceComponentRuntimeConfigCommandInput - {@link UpdateInferenceComponentRuntimeConfigCommandInput}
 * @returns {@link UpdateInferenceComponentRuntimeConfigCommandOutput}
 * @see {@link UpdateInferenceComponentRuntimeConfigCommandInput} for command's `input` shape.
 * @see {@link UpdateInferenceComponentRuntimeConfigCommandOutput} for command's `response` shape.
 * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape.
 *
 * @throws {@link ResourceLimitExceeded} (client fault)
 *  <p> You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. </p>
 *
 * @throws {@link SageMakerServiceException}
 * <p>Base exception class for all service exceptions from SageMaker service.</p>
 *
 *
 * @public
 */
export declare class UpdateInferenceComponentRuntimeConfigCommand extends UpdateInferenceComponentRuntimeConfigCommand_base {
    /** @internal type navigation helper, not in runtime. */
    protected static __types: {
        api: {
            input: UpdateInferenceComponentRuntimeConfigInput;
            output: UpdateInferenceComponentRuntimeConfigOutput;
        };
        sdk: {
            input: UpdateInferenceComponentRuntimeConfigCommandInput;
            output: UpdateInferenceComponentRuntimeConfigCommandOutput;
        };
    };
}