import type { MetadataBearer as __MetadataBearer } from "@smithy/types";
import type { DistributeDatasetEntriesRequest, DistributeDatasetEntriesResponse } from "../models/models_0";
/**
 * @public
 */
export type { __MetadataBearer };
/**
 * @public
 *
 * The input for {@link DistributeDatasetEntriesCommand}.
 */
export interface DistributeDatasetEntriesCommandInput extends DistributeDatasetEntriesRequest {
}
/**
 * @public
 *
 * The output of {@link DistributeDatasetEntriesCommand}.
 */
export interface DistributeDatasetEntriesCommandOutput extends DistributeDatasetEntriesResponse, __MetadataBearer {
}
declare const DistributeDatasetEntriesCommand_base: {
    new (input: DistributeDatasetEntriesCommandInput): import("@smithy/core/client").CommandImpl<DistributeDatasetEntriesCommandInput, DistributeDatasetEntriesCommandOutput, import("..").RekognitionClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    new (input: DistributeDatasetEntriesCommandInput): import("@smithy/core/client").CommandImpl<DistributeDatasetEntriesCommandInput, DistributeDatasetEntriesCommandOutput, import("..").RekognitionClientResolvedConfig, import("..").ServiceInputTypes, import("..").ServiceOutputTypes>;
    getEndpointParameterInstructions(): import("@smithy/types").EndpointParameterInstructions;
};
/**
 * <note>
 *             <p>This operation applies only to Amazon Rekognition Custom Labels.</p>
 *          </note>
 *          <p>Distributes the entries (images) in a training dataset across the training dataset and the test dataset for a project.
 *          <code>DistributeDatasetEntries</code> moves 20% of the training dataset images to the test dataset.
 *          An entry is a JSON Line that describes an image.
 *       </p>
 *          <p>You supply the Amazon Resource Names (ARN) of a project's training dataset and test dataset.
 *          The training dataset must contain the images that you want to split. The test dataset
 *       must be empty. The datasets must belong to the same project. To create training and test datasets for a project, call <a>CreateDataset</a>.</p>
 *          <p>Distributing a dataset takes a while to complete. To check the status call <code>DescribeDataset</code>. The operation
 *          is complete when the <code>Status</code> field for the training dataset and the test dataset is <code>UPDATE_COMPLETE</code>.
 *          If the dataset split fails, the value of <code>Status</code> is <code>UPDATE_FAILED</code>.</p>
 *          <p>This operation requires permissions to perform the <code>rekognition:DistributeDatasetEntries</code> action.</p>
 * @example
 * Use a bare-bones client and the command you need to make an API call.
 * ```javascript
 * import { RekognitionClient, DistributeDatasetEntriesCommand } from "@aws-sdk/client-rekognition"; // ES Modules import
 * // const { RekognitionClient, DistributeDatasetEntriesCommand } = require("@aws-sdk/client-rekognition"); // CommonJS import
 * // import type { RekognitionClientConfig } from "@aws-sdk/client-rekognition";
 * const config = {}; // type is RekognitionClientConfig
 * const client = new RekognitionClient(config);
 * const input = { // DistributeDatasetEntriesRequest
 *   Datasets: [ // DistributeDatasetMetadataList // required
 *     { // DistributeDataset
 *       Arn: "STRING_VALUE", // required
 *     },
 *   ],
 * };
 * const command = new DistributeDatasetEntriesCommand(input);
 * const response = await client.send(command);
 * // {};
 *
 * ```
 *
 * @param DistributeDatasetEntriesCommandInput - {@link DistributeDatasetEntriesCommandInput}
 * @returns {@link DistributeDatasetEntriesCommandOutput}
 * @see {@link DistributeDatasetEntriesCommandInput} for command's `input` shape.
 * @see {@link DistributeDatasetEntriesCommandOutput} for command's `response` shape.
 * @see {@link RekognitionClientResolvedConfig | config} for RekognitionClient's `config` shape.
 *
 * @throws {@link AccessDeniedException} (client fault)
 *  <p>You are not authorized to perform the action.</p>
 *
 * @throws {@link InternalServerError} (server fault)
 *  <p>Amazon Rekognition experienced a service issue. Try your call again.</p>
 *
 * @throws {@link InvalidParameterException} (client fault)
 *  <p>Input parameter violated a constraint. Validate your parameter before calling the API
 *       operation again.</p>
 *
 * @throws {@link ProvisionedThroughputExceededException} (client fault)
 *  <p>The number of requests exceeded your throughput limit. If you want to increase this
 *       limit, contact Amazon Rekognition.</p>
 *
 * @throws {@link ResourceNotFoundException} (client fault)
 *  <p>The resource specified in the request cannot be found.</p>
 *
 * @throws {@link ResourceNotReadyException} (client fault)
 *  <p>The requested resource isn't ready. For example,
 *          this exception occurs when you call <code>DetectCustomLabels</code> with a
 *          model version that isn't deployed. </p>
 *
 * @throws {@link ThrottlingException} (server fault)
 *  <p>Amazon Rekognition is temporarily unable to process the request. Try your call again.</p>
 *
 * @throws {@link RekognitionServiceException}
 * <p>Base exception class for all service exceptions from Rekognition service.</p>
 *
 *
 * @example To distribute an Amazon Rekognition Custom Labels dataset
 * ```javascript
 * // Distributes an Amazon Rekognition Custom Labels training dataset to a test dataset.
 * const input = {
 *   Datasets: [
 *     {
 *       Arn: "arn:aws:rekognition:us-east-1:111122223333:project/my-proj-2/dataset/train/1690564858106"
 *     },
 *     {
 *       Arn: "arn:aws:rekognition:us-east-1:111122223333:project/my-proj-2/dataset/test/1690564858106"
 *     }
 *   ]
 * };
 * const command = new DistributeDatasetEntriesCommand(input);
 * const response = await client.send(command);
 * /* response is
 * { /* empty *\/ }
 * *\/
 * ```
 *
 * @public
 */
export declare class DistributeDatasetEntriesCommand extends DistributeDatasetEntriesCommand_base {
    /** @internal type navigation helper, not in runtime. */
    protected static __types: {
        api: {
            input: DistributeDatasetEntriesRequest;
            output: {};
        };
        sdk: {
            input: DistributeDatasetEntriesCommandInput;
            output: DistributeDatasetEntriesCommandOutput;
        };
    };
}