import { Command as $Command } from "@smithy/smithy-client";
import { MetadataBearer as __MetadataBearer } from "@smithy/types";
import { CreateTransformJobRequest, CreateTransformJobResponse } from "../models/models_2";
import { SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes } from "../SageMakerClient";
/**
 * @public
 */
export type { __MetadataBearer };
export { $Command };
/**
 * @public
 *
 * The input for {@link CreateTransformJobCommand}.
 */
export interface CreateTransformJobCommandInput extends CreateTransformJobRequest {
}
/**
 * @public
 *
 * The output of {@link CreateTransformJobCommand}.
 */
export interface CreateTransformJobCommandOutput extends CreateTransformJobResponse, __MetadataBearer {
}
declare const CreateTransformJobCommand_base: {
    new (input: CreateTransformJobCommandInput): import("@smithy/smithy-client").CommandImpl<CreateTransformJobCommandInput, CreateTransformJobCommandOutput, SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes>;
    new (input: CreateTransformJobCommandInput): import("@smithy/smithy-client").CommandImpl<CreateTransformJobCommandInput, CreateTransformJobCommandOutput, SageMakerClientResolvedConfig, ServiceInputTypes, ServiceOutputTypes>;
    getEndpointParameterInstructions(): import("@smithy/middleware-endpoint").EndpointParameterInstructions;
};
/**
 * <p>Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.</p> <p>To perform batch transformations, you create a transform job and use the data that you have readily available.</p> <p>In the request body, you provide the following:</p> <ul> <li> <p> <code>TransformJobName</code> - Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.</p> </li> <li> <p> <code>ModelName</code> - Identifies the model to use. <code>ModelName</code> must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html">CreateModel</a>.</p> </li> <li> <p> <code>TransformInput</code> - Describes the dataset to be transformed and the Amazon S3 location where it is stored.</p> </li> <li> <p> <code>TransformOutput</code> - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.</p> </li> <li> <p> <code>TransformResources</code> - Identifies the ML compute instances and AMI image versions for the transform job.</p> </li> </ul> <p>For more information about how batch transformation works, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html">Batch Transform</a>.</p>
 * @example
 * Use a bare-bones client and the command you need to make an API call.
 * ```javascript
 * import { SageMakerClient, CreateTransformJobCommand } from "@aws-sdk/client-sagemaker"; // ES Modules import
 * // const { SageMakerClient, CreateTransformJobCommand } = require("@aws-sdk/client-sagemaker"); // CommonJS import
 * const client = new SageMakerClient(config);
 * const input = { // CreateTransformJobRequest
 *   TransformJobName: "STRING_VALUE", // required
 *   ModelName: "STRING_VALUE", // required
 *   MaxConcurrentTransforms: Number("int"),
 *   ModelClientConfig: { // ModelClientConfig
 *     InvocationsTimeoutInSeconds: Number("int"),
 *     InvocationsMaxRetries: Number("int"),
 *   },
 *   MaxPayloadInMB: Number("int"),
 *   BatchStrategy: "MultiRecord" || "SingleRecord",
 *   Environment: { // TransformEnvironmentMap
 *     "<keys>": "STRING_VALUE",
 *   },
 *   TransformInput: { // TransformInput
 *     DataSource: { // TransformDataSource
 *       S3DataSource: { // TransformS3DataSource
 *         S3DataType: "ManifestFile" || "S3Prefix" || "AugmentedManifestFile" || "Converse", // required
 *         S3Uri: "STRING_VALUE", // required
 *       },
 *     },
 *     ContentType: "STRING_VALUE",
 *     CompressionType: "None" || "Gzip",
 *     SplitType: "None" || "Line" || "RecordIO" || "TFRecord",
 *   },
 *   TransformOutput: { // TransformOutput
 *     S3OutputPath: "STRING_VALUE", // required
 *     Accept: "STRING_VALUE",
 *     AssembleWith: "None" || "Line",
 *     KmsKeyId: "STRING_VALUE",
 *   },
 *   DataCaptureConfig: { // BatchDataCaptureConfig
 *     DestinationS3Uri: "STRING_VALUE", // required
 *     KmsKeyId: "STRING_VALUE",
 *     GenerateInferenceId: true || false,
 *   },
 *   TransformResources: { // TransformResources
 *     InstanceType: "ml.m4.xlarge" || "ml.m4.2xlarge" || "ml.m4.4xlarge" || "ml.m4.10xlarge" || "ml.m4.16xlarge" || "ml.c4.xlarge" || "ml.c4.2xlarge" || "ml.c4.4xlarge" || "ml.c4.8xlarge" || "ml.p2.xlarge" || "ml.p2.8xlarge" || "ml.p2.16xlarge" || "ml.p3.2xlarge" || "ml.p3.8xlarge" || "ml.p3.16xlarge" || "ml.c5.xlarge" || "ml.c5.2xlarge" || "ml.c5.4xlarge" || "ml.c5.9xlarge" || "ml.c5.18xlarge" || "ml.m5.large" || "ml.m5.xlarge" || "ml.m5.2xlarge" || "ml.m5.4xlarge" || "ml.m5.12xlarge" || "ml.m5.24xlarge" || "ml.m6i.large" || "ml.m6i.xlarge" || "ml.m6i.2xlarge" || "ml.m6i.4xlarge" || "ml.m6i.8xlarge" || "ml.m6i.12xlarge" || "ml.m6i.16xlarge" || "ml.m6i.24xlarge" || "ml.m6i.32xlarge" || "ml.c6i.large" || "ml.c6i.xlarge" || "ml.c6i.2xlarge" || "ml.c6i.4xlarge" || "ml.c6i.8xlarge" || "ml.c6i.12xlarge" || "ml.c6i.16xlarge" || "ml.c6i.24xlarge" || "ml.c6i.32xlarge" || "ml.r6i.large" || "ml.r6i.xlarge" || "ml.r6i.2xlarge" || "ml.r6i.4xlarge" || "ml.r6i.8xlarge" || "ml.r6i.12xlarge" || "ml.r6i.16xlarge" || "ml.r6i.24xlarge" || "ml.r6i.32xlarge" || "ml.m7i.large" || "ml.m7i.xlarge" || "ml.m7i.2xlarge" || "ml.m7i.4xlarge" || "ml.m7i.8xlarge" || "ml.m7i.12xlarge" || "ml.m7i.16xlarge" || "ml.m7i.24xlarge" || "ml.m7i.48xlarge" || "ml.c7i.large" || "ml.c7i.xlarge" || "ml.c7i.2xlarge" || "ml.c7i.4xlarge" || "ml.c7i.8xlarge" || "ml.c7i.12xlarge" || "ml.c7i.16xlarge" || "ml.c7i.24xlarge" || "ml.c7i.48xlarge" || "ml.r7i.large" || "ml.r7i.xlarge" || "ml.r7i.2xlarge" || "ml.r7i.4xlarge" || "ml.r7i.8xlarge" || "ml.r7i.12xlarge" || "ml.r7i.16xlarge" || "ml.r7i.24xlarge" || "ml.r7i.48xlarge" || "ml.g4dn.xlarge" || "ml.g4dn.2xlarge" || "ml.g4dn.4xlarge" || "ml.g4dn.8xlarge" || "ml.g4dn.12xlarge" || "ml.g4dn.16xlarge" || "ml.g5.xlarge" || "ml.g5.2xlarge" || "ml.g5.4xlarge" || "ml.g5.8xlarge" || "ml.g5.12xlarge" || "ml.g5.16xlarge" || "ml.g5.24xlarge" || "ml.g5.48xlarge" || "ml.trn1.2xlarge" || "ml.trn1.32xlarge" || "ml.inf2.xlarge" || "ml.inf2.8xlarge" || "ml.inf2.24xlarge" || "ml.inf2.48xlarge", // required
 *     InstanceCount: Number("int"), // required
 *     VolumeKmsKeyId: "STRING_VALUE",
 *     TransformAmiVersion: "STRING_VALUE",
 *   },
 *   DataProcessing: { // DataProcessing
 *     InputFilter: "STRING_VALUE",
 *     OutputFilter: "STRING_VALUE",
 *     JoinSource: "Input" || "None",
 *   },
 *   Tags: [ // TagList
 *     { // Tag
 *       Key: "STRING_VALUE", // required
 *       Value: "STRING_VALUE", // required
 *     },
 *   ],
 *   ExperimentConfig: { // ExperimentConfig
 *     ExperimentName: "STRING_VALUE",
 *     TrialName: "STRING_VALUE",
 *     TrialComponentDisplayName: "STRING_VALUE",
 *     RunName: "STRING_VALUE",
 *   },
 * };
 * const command = new CreateTransformJobCommand(input);
 * const response = await client.send(command);
 * // { // CreateTransformJobResponse
 * //   TransformJobArn: "STRING_VALUE", // required
 * // };
 *
 * ```
 *
 * @param CreateTransformJobCommandInput - {@link CreateTransformJobCommandInput}
 * @returns {@link CreateTransformJobCommandOutput}
 * @see {@link CreateTransformJobCommandInput} for command's `input` shape.
 * @see {@link CreateTransformJobCommandOutput} for command's `response` shape.
 * @see {@link SageMakerClientResolvedConfig | config} for SageMakerClient's `config` shape.
 *
 * @throws {@link ResourceInUse} (client fault)
 *  <p>Resource being accessed is in use.</p>
 *
 * @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 ResourceNotFound} (client fault)
 *  <p>Resource being access is not found.</p>
 *
 * @throws {@link SageMakerServiceException}
 * <p>Base exception class for all service exceptions from SageMaker service.</p>
 *
 *
 * @public
 */
export declare class CreateTransformJobCommand extends CreateTransformJobCommand_base {
    /** @internal type navigation helper, not in runtime. */
    protected static __types: {
        api: {
            input: CreateTransformJobRequest;
            output: CreateTransformJobResponse;
        };
        sdk: {
            input: CreateTransformJobCommandInput;
            output: CreateTransformJobCommandOutput;
        };
    };
}