agent-claw: automated task changes

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/base-types.d.ts

@@ -0,0 +1,771 @@
+import type { Construct } from 'constructs';
+import type * as ec2 from '../../../aws-ec2';
+import type * as ecr from '../../../aws-ecr';
+import type { DockerImageAssetProps } from '../../../aws-ecr-assets';
+import * as iam from '../../../aws-iam';
+import type * as kms from '../../../aws-kms';
+import type * as s3 from '../../../aws-s3';
+import * as sfn from '../../../aws-stepfunctions';
+import type { Duration, Size } from '../../../core';
+/**
+ * Task to train a machine learning model using Amazon SageMaker
+ */
+export interface ISageMakerTask extends iam.IGrantable {
+}
+/**
+ * Specify the training algorithm and algorithm-specific metadata
+ */
+export interface AlgorithmSpecification {
+    /**
+     * Name of the algorithm resource to use for the training job.
+     * This must be an algorithm resource that you created or subscribe to on AWS Marketplace.
+     * If you specify a value for this parameter, you can't specify a value for TrainingImage.
+     *
+     * @default - No algorithm is specified
+     */
+    readonly algorithmName?: string;
+    /**
+     * List of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs.
+     *
+     * @default - No metrics
+     */
+    readonly metricDefinitions?: MetricDefinition[];
+    /**
+     * Registry path of the Docker image that contains the training algorithm.
+     *
+     * @default - No Docker image is specified
+     */
+    readonly trainingImage?: DockerImage;
+    /**
+     * Input mode that the algorithm supports.
+     *
+     * @default 'File' mode
+     */
+    readonly trainingInputMode?: InputMode;
+}
+/**
+ *  Describes the training, validation or test dataset and the Amazon S3 location where it is stored.
+ *
+ */
+export interface Channel {
+    /**
+     * Name of the channel
+     */
+    readonly channelName: string;
+    /**
+     * Compression type if training data is compressed
+     *
+     * @default - None
+     */
+    readonly compressionType?: CompressionType;
+    /**
+     * The MIME type of the data.
+     *
+     * @default - None
+     */
+    readonly contentType?: string;
+    /**
+     * Location of the channel data.
+     */
+    readonly dataSource: DataSource;
+    /**
+     * Input mode to use for the data channel in a training job.
+     *
+     * @default - None
+     */
+    readonly inputMode?: InputMode;
+    /**
+     * Specify RecordIO as the value when input data is in raw format but the training algorithm requires the RecordIO format.
+     * In this case, Amazon SageMaker wraps each individual S3 object in a RecordIO record.
+     * If the input data is already in RecordIO format, you don't need to set this attribute.
+     *
+     * @default - None
+     */
+    readonly recordWrapperType?: RecordWrapperType;
+    /**
+     * Shuffle config option for input data in a channel.
+     *
+     * @default - None
+     */
+    readonly shuffleConfig?: ShuffleConfig;
+}
+/**
+ * Configuration for a shuffle option for input data in a channel.
+ *
+ */
+export interface ShuffleConfig {
+    /**
+     * Determines the shuffling order.
+     */
+    readonly seed: number;
+}
+/**
+ * Location of the channel data.
+ *
+ */
+export interface DataSource {
+    /**
+     * S3 location of the data source that is associated with a channel.
+     */
+    readonly s3DataSource: S3DataSource;
+}
+/**
+ * S3 location of the channel data.
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_S3DataSource.html
+ *
+ */
+export interface S3DataSource {
+    /**
+     * List of one or more attribute names to use that are found in a specified augmented manifest file.
+     *
+     * @default - No attribute names
+     */
+    readonly attributeNames?: string[];
+    /**
+     * S3 Data Distribution Type
+     *
+     * @default - None
+     */
+    readonly s3DataDistributionType?: S3DataDistributionType;
+    /**
+     * S3 Data Type
+     *
+     * @default S3_PREFIX
+     */
+    readonly s3DataType?: S3DataType;
+    /**
+     * S3 Uri
+     */
+    readonly s3Location: S3Location;
+}
+/**
+ * Configures the S3 bucket where SageMaker will save the result of model training
+ */
+export interface OutputDataConfig {
+    /**
+     * Optional KMS encryption key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
+     *
+     * @default - Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account
+     */
+    readonly encryptionKey?: kms.IKey;
+    /**
+     * Identifies the S3 path where you want Amazon SageMaker to store the model artifacts.
+     */
+    readonly s3OutputLocation: S3Location;
+}
+/**
+ * Specifies a limit to how long a model training job can run.
+ * When the job reaches the time limit, Amazon SageMaker ends the training job.
+ *
+ */
+export interface StoppingCondition {
+    /**
+     * The maximum length of time, in seconds, that the training or compilation job can run.
+     *
+     * @default - 1 hour
+     */
+    readonly maxRuntime?: Duration;
+}
+/**
+ * Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training.
+ *
+ */
+export interface ResourceConfig {
+    /**
+     * The number of ML compute instances to use.
+     *
+     * @default 1 instance.
+     */
+    readonly instanceCount: number;
+    /**
+     * ML compute instance type.
+     *
+     * To provide an instance type from the task input, supply an instance type in the following way
+     * where the value in the task input is an EC2 instance type prepended with "ml.":
+     *
+     * ```ts
+     * new ec2.InstanceType(sfn.JsonPath.stringAt('$.path.to.instanceType'));
+     * ```
+     * @see https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ResourceConfig.html#sagemaker-Type-ResourceConfig-InstanceType
+     *
+     * @default ec2.InstanceType(ec2.InstanceClass.M4, ec2.InstanceType.XLARGE)
+     */
+    readonly instanceType: ec2.InstanceType;
+    /**
+     * KMS key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the training job.
+     *
+     * @default - Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account
+     */
+    readonly volumeEncryptionKey?: kms.IKey;
+    /**
+     * Size of the ML storage volume that you want to provision.
+     *
+     * @default 10 GB EBS volume.
+     */
+    readonly volumeSize: Size;
+}
+/**
+ * Specifies the VPC that you want your Amazon SageMaker training job to connect to.
+ *
+ */
+export interface VpcConfig {
+    /**
+     * VPC
+     */
+    readonly vpc: ec2.IVpc;
+    /**
+     * VPC subnets.
+     *
+     * @default - Private Subnets are selected
+     */
+    readonly subnets?: ec2.SubnetSelection;
+}
+/**
+ * Specifies the metric name and regular expressions used to parse algorithm logs.
+ *
+ */
+export interface MetricDefinition {
+    /**
+     * Name of the metric.
+     */
+    readonly name: string;
+    /**
+     * Regular expression that searches the output of a training job and gets the value of the metric.
+     */
+    readonly regex: string;
+}
+/**
+ * Stores information about the location of an object in Amazon S3
+ *
+ */
+export interface S3LocationConfig {
+    /**
+     * Uniquely identifies the resource in Amazon S3
+     */
+    readonly uri: string;
+}
+/**
+ * Constructs `IS3Location` objects.
+ *
+ */
+export declare abstract class S3Location {
+    /**
+     * An `IS3Location` built with a determined bucket and key prefix.
+     *
+     * @param bucket    is the bucket where the objects are to be stored.
+     * @param keyPrefix is the key prefix used by the location.
+     */
+    static fromBucket(bucket: s3.IBucket, keyPrefix: string): S3Location;
+    /**
+     * An `IS3Location` determined fully by a JSONata expression or JSON Path from the task input.
+     *
+     * Due to the dynamic nature of those locations, the IAM grants that will be set by `grantRead` and `grantWrite`
+     * apply to the `*` resource.
+     *
+     * @param expression the JSON expression resolving to an S3 location URI.
+     */
+    static fromJsonExpression(expression: string): S3Location;
+    /**
+     * Called when the S3Location is bound to a StepFunctions task.
+     */
+    abstract bind(task: ISageMakerTask, opts: S3LocationBindOptions): S3LocationConfig;
+}
+/**
+ * Options for binding an S3 Location.
+ *
+ */
+export interface S3LocationBindOptions {
+    /**
+     * Allow reading from the S3 Location.
+     *
+     * @default false
+     */
+    readonly forReading?: boolean;
+    /**
+     * Allow writing to the S3 Location.
+     *
+     * @default false
+     */
+    readonly forWriting?: boolean;
+}
+/**
+ * Configuration for a using Docker image.
+ *
+ */
+export interface DockerImageConfig {
+    /**
+     * The fully qualified URI of the Docker image.
+     */
+    readonly imageUri: string;
+}
+/**
+ * Creates `IDockerImage` instances.
+ *
+ */
+export declare abstract class DockerImage {
+    /**
+     * Reference a Docker image stored in an ECR repository.
+     *
+     * @param repository the ECR repository where the image is hosted.
+     * @param tagOrDigest an optional tag or digest (digests must start with `sha256:`)
+     */
+    static fromEcrRepository(repository: ecr.IRepository, tagOrDigest?: string): DockerImage;
+    /**
+     * Reference a Docker image which URI is obtained from the task's input.
+     *
+     * @param expression           the JSONata or JSON path expression with the task input.
+     * @param allowAnyEcrImagePull whether ECR access should be permitted (set to `false` if the image will never be in ECR).
+     */
+    static fromJsonExpression(expression: string, allowAnyEcrImagePull?: boolean): DockerImage;
+    /**
+     * Reference a Docker image by it's URI.
+     *
+     * When referencing ECR images, prefer using `inEcr`.
+     *
+     * @param imageUri the URI to the docker image.
+     */
+    static fromRegistry(imageUri: string): DockerImage;
+    /**
+     * Reference a Docker image that is provided as an Asset in the current app.
+     *
+     * @param scope the scope in which to create the Asset.
+     * @param id    the ID for the asset in the construct tree.
+     * @param props the configuration props of the asset.
+     */
+    static fromAsset(scope: Construct, id: string, props: DockerImageAssetProps): DockerImage;
+    /**
+     * Called when the image is used by a SageMaker task.
+     */
+    abstract bind(task: ISageMakerTask): DockerImageConfig;
+}
+/**
+ * S3 Data Type.
+ *
+ */
+export declare enum S3DataType {
+    /**
+     * Manifest File Data Type
+     */
+    MANIFEST_FILE = "ManifestFile",
+    /**
+     * S3 Prefix Data Type
+     */
+    S3_PREFIX = "S3Prefix",
+    /**
+     * Augmented Manifest File Data Type
+     */
+    AUGMENTED_MANIFEST_FILE = "AugmentedManifestFile"
+}
+/**
+ * S3 Data Distribution Type.
+ *
+ */
+export declare enum S3DataDistributionType {
+    /**
+     * Fully replicated S3 Data Distribution Type
+     */
+    FULLY_REPLICATED = "FullyReplicated",
+    /**
+     * Sharded By S3 Key Data Distribution Type
+     */
+    SHARDED_BY_S3_KEY = "ShardedByS3Key"
+}
+/**
+ * Define the format of the input data.
+ *
+ */
+export declare enum RecordWrapperType {
+    /**
+     * None record wrapper type
+     */
+    NONE = "None",
+    /**
+     * RecordIO record wrapper type
+     */
+    RECORD_IO = "RecordIO"
+}
+/**
+ *  Input mode that the algorithm supports.
+ *
+ */
+export declare enum InputMode {
+    /**
+     * Pipe mode
+     */
+    PIPE = "Pipe",
+    /**
+     * File mode.
+     */
+    FILE = "File",
+    /**
+     * FastFile mode.
+     */
+    FAST_FILE = "FastFile"
+}
+/**
+ * Compression type of the data.
+ *
+ */
+export declare enum CompressionType {
+    /**
+     * None compression type
+     */
+    NONE = "None",
+    /**
+     * Gzip compression type
+     */
+    GZIP = "Gzip"
+}
+/**
+ * Configures the timeout and maximum number of retries for processing a transform job invocation.
+ *
+ */
+export interface ModelClientOptions {
+    /**
+     * The maximum number of retries when invocation requests are failing.
+     *
+     * @default 0
+     */
+    readonly invocationsMaxRetries?: number;
+    /**
+     * The timeout duration for an invocation request.
+     *
+     * @default Duration.minutes(1)
+     */
+    readonly invocationsTimeout?: Duration;
+}
+/**
+ *  Dataset to be transformed and the Amazon S3 location where it is stored.
+ *
+ */
+export interface TransformInput {
+    /**
+     * The compression type of the transform data.
+     *
+     * @default NONE
+     */
+    readonly compressionType?: CompressionType;
+    /**
+     * Multipurpose internet mail extension (MIME) type of the data.
+     *
+     * @default - None
+     */
+    readonly contentType?: string;
+    /**
+     * S3 location of the channel data
+     */
+    readonly transformDataSource: TransformDataSource;
+    /**
+     * Method to use to split the transform job's data files into smaller batches.
+     *
+     * @default NONE
+     */
+    readonly splitType?: SplitType;
+}
+/**
+ * S3 location of the input data that the model can consume.
+ *
+ */
+export interface TransformDataSource {
+    /**
+     * S3 location of the input data
+     */
+    readonly s3DataSource: TransformS3DataSource;
+}
+/**
+ * Location of the channel data.
+ *
+ */
+export interface TransformS3DataSource {
+    /**
+     * S3 Data Type
+     *
+     * @default 'S3Prefix'
+     */
+    readonly s3DataType?: S3DataType;
+    /**
+     * Identifies either a key name prefix or a manifest.
+     */
+    readonly s3Uri: string;
+}
+/**
+ * S3 location where you want Amazon SageMaker to save the results from the transform job.
+ *
+ */
+export interface TransformOutput {
+    /**
+     * MIME type used to specify the output data.
+     *
+     * @default - None
+     */
+    readonly accept?: string;
+    /**
+     * Defines how to assemble the results of the transform job as a single S3 object.
+     *
+     * @default - None
+     */
+    readonly assembleWith?: AssembleWith;
+    /**
+     * AWS KMS key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
+     *
+     * @default - default KMS key for Amazon S3 for your role's account.
+     */
+    readonly encryptionKey?: kms.IKeyRef;
+    /**
+     * S3 path where you want Amazon SageMaker to store the results of the transform job.
+     */
+    readonly s3OutputPath: string;
+}
+/**
+ * ML compute instances for the transform job.
+ *
+ */
+export interface TransformResources {
+    /**
+     * Number of ML compute instances to use in the transform job
+     */
+    readonly instanceCount: number;
+    /**
+     * ML compute instance type for the transform job.
+     */
+    readonly instanceType: ec2.InstanceType;
+    /**
+     * AWS KMS key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s).
+     *
+     * @default - None
+     */
+    readonly volumeEncryptionKey?: kms.IKeyRef;
+}
+/**
+ * Properties to define a ContainerDefinition
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
+ */
+export interface ContainerDefinitionOptions {
+    /**
+     * The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
+     *
+     * @default - None
+     */
+    readonly image?: DockerImage;
+    /**
+     * The environment variables to set in the Docker container
+     *
+     * @default - No variables
+     */
+    readonly environmentVariables?: sfn.TaskInput;
+    /**
+     * The name or Amazon Resource Name (ARN) of the model package to use to create the model.
+     *
+     * @default - None
+     */
+    readonly modelPackageName?: string;
+    /**
+     * Defines how many models the container hosts
+     *
+     * @default - Mode.SINGLE_MODEL
+     */
+    readonly mode?: Mode;
+    /**
+     * This parameter is ignored for models that contain only a PrimaryContainer.
+     * When a ContainerDefinition is part of an inference pipeline,
+     * the value of the parameter uniquely identifies the container for the purposes of logging and metrics.
+     *
+     * @default - None
+     */
+    readonly containerHostName?: string;
+    /**
+     * The S3 path where the model artifacts, which result from model training, are stored.
+     * This path must point to a single gzip compressed tar archive (.tar.gz suffix).
+     * The S3 path is required for Amazon SageMaker built-in algorithms, but not if you use your own algorithms.
+     *
+     * @default - None
+     */
+    readonly modelS3Location?: S3Location;
+}
+/**
+ * Describes the container, as part of model definition.
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
+ */
+export declare class ContainerDefinition implements IContainerDefinition {
+    private readonly options;
+    constructor(options: ContainerDefinitionOptions);
+    /**
+     * Called when the ContainerDefinition type configured on Sagemaker Task
+     */
+    bind(task: ISageMakerTask): ContainerDefinitionConfig;
+}
+/**
+ * Configuration of the container used to host the model
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
+ */
+export interface IContainerDefinition {
+    /**
+     * Called when the ContainerDefinition is used by a SageMaker task.
+     */
+    bind(task: ISageMakerTask): ContainerDefinitionConfig;
+}
+/**
+ * Configuration options for the ContainerDefinition
+ */
+export interface ContainerDefinitionConfig {
+    /**
+     * Additional parameters to pass to the base task
+     *
+     * @default - No additional parameters passed
+     */
+    readonly parameters?: {
+        [key: string]: any;
+    };
+}
+/**
+ * Specifies how many models the container hosts
+ *
+ */
+export declare enum Mode {
+    /**
+     * Container hosts a single model
+     */
+    SINGLE_MODEL = "SingleModel",
+    /**
+     * Container hosts multiple models
+     *
+     * @see https://docs.aws.amazon.com/sagemaker/latest/dg/multi-model-endpoints.html
+     */
+    MULTI_MODEL = "MultiModel"
+}
+/**
+ * Identifies a model that you want to host and the resources to deploy for hosting it.
+ *
+ * @see  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ProductionVariant.html
+ */
+export interface ProductionVariant {
+    /**
+     * The size of the Elastic Inference (EI) instance to use for the production variant.
+     *
+     * @default - None
+     */
+    readonly acceleratorType?: AcceleratorType;
+    /**
+     * Number of instances to launch initially.
+     *
+     * @default - 1
+     */
+    readonly initialInstanceCount?: number;
+    /**
+     * Determines initial traffic distribution among all of the models that you specify in the endpoint configuration.
+     *
+     * @default - 1.0
+     */
+    readonly initialVariantWeight?: number;
+    /**
+     * The ML compute instance type
+     */
+    readonly instanceType: ec2.InstanceType;
+    /**
+     * The name of the production variant.
+     */
+    readonly variantName: string;
+    /**
+     * The name of the model that you want to host. This is the name that you specified when creating the model.
+     */
+    readonly modelName: string;
+}
+/**
+ * The generation of Elastic Inference (EI) instance
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
+ */
+export declare class AcceleratorClass {
+    readonly version: string;
+    /**
+     * Elastic Inference accelerator 1st generation
+     */
+    static readonly EIA1: AcceleratorClass;
+    /**
+     * Elastic Inference accelerator 2nd generation
+     */
+    static readonly EIA2: AcceleratorClass;
+    /**
+     * Custom AcceleratorType
+     * @param version - Elastic Inference accelerator generation
+     */
+    static of(version: string): AcceleratorClass;
+    /**
+     * @param version - Elastic Inference accelerator generation
+     */
+    private constructor();
+}
+/**
+ * The size of the Elastic Inference (EI) instance to use for the production variant.
+ * EI instances provide on-demand GPU computing for inference
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
+ */
+export declare class AcceleratorType {
+    private readonly instanceTypeIdentifier;
+    /**
+     * AcceleratorType
+     *
+     * This class takes a combination of a class and size.
+     */
+    static of(acceleratorClass: AcceleratorClass, instanceSize: ec2.InstanceSize): AcceleratorType;
+    constructor(instanceTypeIdentifier: string);
+    /**
+     * Return the accelerator type as a dotted string
+     */
+    toString(): string;
+}
+/**
+ * Specifies the number of records to include in a mini-batch for an HTTP inference request.
+ *
+ */
+export declare enum BatchStrategy {
+    /**
+     * Fits multiple records in a mini-batch.
+     */
+    MULTI_RECORD = "MultiRecord",
+    /**
+     * Use a single record when making an invocation request.
+     */
+    SINGLE_RECORD = "SingleRecord"
+}
+/**
+ * Method to use to split the transform job's data files into smaller batches.
+ *
+ */
+export declare enum SplitType {
+    /**
+     * Input data files are not split,
+     */
+    NONE = "None",
+    /**
+     * Split records on a newline character boundary.
+     */
+    LINE = "Line",
+    /**
+     * Split using MXNet RecordIO format.
+     */
+    RECORD_IO = "RecordIO",
+    /**
+     * Split using TensorFlow TFRecord format.
+     */
+    TF_RECORD = "TFRecord"
+}
+/**
+ * How to assemble the results of the transform job as a single S3 object.
+ *
+ */
+export declare enum AssembleWith {
+    /**
+     * Concatenate the results in binary format.
+     */
+    NONE = "None",
+    /**
+     * Add a newline character at the end of every transformed record.
+     */
+    LINE = "Line"
+}

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/create-endpoint-config.d.ts

@@ -0,0 +1,88 @@
+import type { Construct } from 'constructs';
+import type { ProductionVariant } from './base-types';
+import * as iam from '../../../aws-iam';
+import type * as kms from '../../../aws-kms';
+import * as sfn from '../../../aws-stepfunctions';
+interface SageMakerCreateEndpointConfigOptions {
+    /**
+     * The name of the endpoint configuration.
+     */
+    readonly endpointConfigName: string;
+    /**
+     * AWS Key Management Service key that Amazon SageMaker
+     * uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.
+     *
+     * @default - None
+     */
+    readonly kmsKey?: kms.IKeyRef;
+    /**
+     * An list of ProductionVariant objects, one for each model that you want to host at this endpoint.
+     * Identifies a model that you want to host and the resources to deploy for hosting it.
+     * If you are deploying multiple models, tell Amazon SageMaker how to distribute traffic among the models by specifying variant weights.
+     */
+    readonly productionVariants: ProductionVariant[];
+    /**
+     * Tags to be applied to the endpoint configuration.
+     *
+     * @default - No tags
+     */
+    readonly tags?: sfn.TaskInput;
+}
+/**
+ * Properties for creating an Amazon SageMaker endpoint configuration using JSONPath
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateEndpointConfigJsonPathProps extends sfn.TaskStateJsonPathBaseProps, SageMakerCreateEndpointConfigOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker endpoint configuration using JSONata
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateEndpointConfigJsonataProps extends sfn.TaskStateJsonataBaseProps, SageMakerCreateEndpointConfigOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker endpoint configuration
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateEndpointConfigProps extends sfn.TaskStateBaseProps, SageMakerCreateEndpointConfigOptions {
+}
+/**
+ * A Step Functions Task to create a SageMaker endpoint configuration
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export declare class SageMakerCreateEndpointConfig extends sfn.TaskStateBase {
+    private readonly props;
+    /**
+     * Uniquely identifies this class.
+     */
+    static readonly PROPERTY_INJECTION_ID: string;
+    /**
+     * A Step Functions Task using JSONPath to create a SageMaker endpoint configuration
+     *
+     * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+     */
+    static jsonPath(scope: Construct, id: string, props: SageMakerCreateEndpointConfigJsonPathProps): SageMakerCreateEndpointConfig;
+    /**
+     * A Step Functions Task using JSONata to create a SageMaker endpoint configuration
+     *
+     * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+     */
+    static jsonata(scope: Construct, id: string, props: SageMakerCreateEndpointConfigJsonataProps): SageMakerCreateEndpointConfig;
+    private static readonly SUPPORTED_INTEGRATION_PATTERNS;
+    protected readonly taskMetrics?: sfn.TaskMetricsConfig;
+    protected readonly taskPolicies?: iam.PolicyStatement[];
+    private readonly integrationPattern;
+    constructor(scope: Construct, id: string, props: SageMakerCreateEndpointConfigProps);
+    /**
+     * @internal
+     */
+    protected _renderTask(topLevelQueryLanguage?: sfn.QueryLanguage): any;
+    private renderParameters;
+    private makePolicyStatements;
+    private validateProductionVariants;
+}
+export {};

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/create-endpoint.d.ts

@@ -0,0 +1,72 @@
+import type { Construct } from 'constructs';
+import * as iam from '../../../aws-iam';
+import * as sfn from '../../../aws-stepfunctions';
+interface SageMakerCreateEndpointOptions {
+    /**
+     * The name of an endpoint configuration.
+     */
+    readonly endpointConfigName: string;
+    /**
+     * The name of the endpoint. The name must be unique within an AWS Region in your AWS account.
+     */
+    readonly endpointName: string;
+    /**
+     * Tags to be applied to the endpoint.
+     *
+     * @default - No tags
+     */
+    readonly tags?: sfn.TaskInput;
+}
+/**
+ * Properties for creating an Amazon SageMaker endpoint using JSONPath
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateEndpointJsonPathProps extends sfn.TaskStateJsonPathBaseProps, SageMakerCreateEndpointOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker endpoint using JSONata
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateEndpointJsonataProps extends sfn.TaskStateJsonataBaseProps, SageMakerCreateEndpointOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker endpoint
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateEndpointProps extends sfn.TaskStateBaseProps, SageMakerCreateEndpointOptions {
+}
+/**
+ * A Step Functions Task to create a SageMaker endpoint
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export declare class SageMakerCreateEndpoint extends sfn.TaskStateBase {
+    private readonly props;
+    /**
+     * A Step Functions Task using JSONPath to create a SageMaker endpoint
+     *
+     * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+     */
+    static jsonPath(scope: Construct, id: string, props: SageMakerCreateEndpointJsonPathProps): SageMakerCreateEndpoint;
+    /**
+     * A Step Functions Task using JSONata to create a SageMaker endpoint
+     *
+     * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+     */
+    static jsonata(scope: Construct, id: string, props: SageMakerCreateEndpointJsonataProps): SageMakerCreateEndpoint;
+    private static readonly SUPPORTED_INTEGRATION_PATTERNS;
+    protected readonly taskMetrics?: sfn.TaskMetricsConfig;
+    protected readonly taskPolicies?: iam.PolicyStatement[];
+    private readonly integrationPattern;
+    constructor(scope: Construct, id: string, props: SageMakerCreateEndpointProps);
+    /**
+     * @internal
+     */
+    protected _renderTask(topLevelQueryLanguage?: sfn.QueryLanguage): any;
+    private renderParameters;
+    private makePolicyStatements;
+}
+export {};

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/create-endpoint.js

@@ -0,0 +1 @@
+"use strict";Object.defineProperty(exports,"__esModule",{value:!0}),exports.SageMakerCreateEndpoint=void 0;var jsiiDeprecationWarnings=()=>{var tmp=require("../../../.warnings.jsii.js");return jsiiDeprecationWarnings=()=>tmp,tmp};const JSII_RTTI_SYMBOL_1=Symbol.for("jsii.rtti");var iam=()=>{var tmp=require("../../../aws-iam");return iam=()=>tmp,tmp},sfn=()=>{var tmp=require("../../../aws-stepfunctions");return sfn=()=>tmp,tmp},cdk=()=>{var tmp=require("../../../core");return cdk=()=>tmp,tmp},task_utils_1=()=>{var tmp=require("../private/task-utils");return task_utils_1=()=>tmp,tmp};class SageMakerCreateEndpoint extends sfn().TaskStateBase{props;static[JSII_RTTI_SYMBOL_1]={fqn:"aws-cdk-lib.aws_stepfunctions_tasks.SageMakerCreateEndpoint",version:"2.252.0"};static jsonPath(scope,id,props){try{jsiiDeprecationWarnings().aws_cdk_lib_aws_stepfunctions_tasks_SageMakerCreateEndpointJsonPathProps(props)}catch(error){throw process.env.JSII_DEBUG!=="1"&&error.name==="DeprecationError"&&Error.captureStackTrace(error,this.jsonPath),error}return new SageMakerCreateEndpoint(scope,id,props)}static jsonata(scope,id,props){try{jsiiDeprecationWarnings().aws_cdk_lib_aws_stepfunctions_tasks_SageMakerCreateEndpointJsonataProps(props)}catch(error){throw process.env.JSII_DEBUG!=="1"&&error.name==="DeprecationError"&&Error.captureStackTrace(error,this.jsonata),error}return new SageMakerCreateEndpoint(scope,id,{...props,queryLanguage:sfn().QueryLanguage.JSONATA})}static SUPPORTED_INTEGRATION_PATTERNS=[sfn().IntegrationPattern.REQUEST_RESPONSE];taskMetrics;taskPolicies;integrationPattern;constructor(scope,id,props){super(scope,id,props),this.props=props;try{jsiiDeprecationWarnings().aws_cdk_lib_aws_stepfunctions_tasks_SageMakerCreateEndpointProps(props)}catch(error){throw process.env.JSII_DEBUG!=="1"&&error.name==="DeprecationError"&&Error.captureStackTrace(error,SageMakerCreateEndpoint),error}this.integrationPattern=props.integrationPattern||sfn().IntegrationPattern.REQUEST_RESPONSE,(0,task_utils_1().validatePatternSupported)(this.integrationPattern,SageMakerCreateEndpoint.SUPPORTED_INTEGRATION_PATTERNS),this.taskPolicies=this.makePolicyStatements()}_renderTask(topLevelQueryLanguage){const queryLanguage=sfn()._getActualQueryLanguage(topLevelQueryLanguage,this.props.queryLanguage);return{Resource:(0,task_utils_1().integrationResourceArn)("sagemaker","createEndpoint",this.integrationPattern),...this._renderParametersOrArguments(this.renderParameters(),queryLanguage)}}renderParameters(){return{EndpointConfigName:this.props.endpointConfigName,EndpointName:this.props.endpointName,Tags:this.props.tags?.value}}makePolicyStatements(){const stack=cdk().Stack.of(this);return[new(iam()).PolicyStatement({actions:["sagemaker:createEndpoint"],resources:[stack.formatArn({service:"sagemaker",resource:"endpoint",resourceName:(0,task_utils_1().isJsonPathOrJsonataExpression)(this.props.endpointName)?"*":`${this.props.endpointName.toLowerCase()}`}),stack.formatArn({service:"sagemaker",resource:"endpoint-config",resourceName:(0,task_utils_1().isJsonPathOrJsonataExpression)(this.props.endpointConfigName)?"*":`${this.props.endpointConfigName.toLowerCase()}`})]}),new(iam()).PolicyStatement({actions:["sagemaker:ListTags"],resources:["*"]})]}}exports.SageMakerCreateEndpoint=SageMakerCreateEndpoint;

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/create-model.d.ts

@@ -0,0 +1,132 @@
+import type { Construct } from 'constructs';
+import type { IContainerDefinition } from './base-types';
+import * as ec2 from '../../../aws-ec2';
+import * as iam from '../../../aws-iam';
+import * as sfn from '../../../aws-stepfunctions';
+interface SageMakerCreateModelOptions {
+    /**
+     * An execution role that you can pass in a CreateModel API request
+     *
+     * @default - a role will be created.
+     */
+    readonly role?: iam.IRole;
+    /**
+     * The name of the new model.
+     */
+    readonly modelName: string;
+    /**
+     * The definition of the primary docker image containing inference code, associated artifacts,
+     * and custom environment map that the inference code uses when the model is deployed for predictions.
+     */
+    readonly primaryContainer: IContainerDefinition;
+    /**
+     * Specifies the containers in the inference pipeline.
+     *
+     * @default - None
+     */
+    readonly containers?: IContainerDefinition[];
+    /**
+     * Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
+     *
+     * @default false
+     */
+    readonly enableNetworkIsolation?: boolean;
+    /**
+     * The VPC that is accessible by the hosted model
+     *
+     * @default - None
+     */
+    readonly vpc?: ec2.IVpc;
+    /**
+     * The subnets of the VPC to which the hosted model is connected
+     * (Note this parameter is only used when VPC is provided)
+     *
+     * @default - Private Subnets are selected
+     */
+    readonly subnetSelection?: ec2.SubnetSelection;
+    /**
+     * Tags to be applied to the model.
+     *
+     * @default - No tags
+     */
+    readonly tags?: sfn.TaskInput;
+}
+/**
+ * Properties for creating an Amazon SageMaker model using JSONPath
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateModelJsonPathProps extends sfn.TaskStateJsonPathBaseProps, SageMakerCreateModelOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker model using JSONata
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateModelJsonataProps extends sfn.TaskStateJsonataBaseProps, SageMakerCreateModelOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker model
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerCreateModelProps extends sfn.TaskStateBaseProps, SageMakerCreateModelOptions {
+}
+/**
+ * A Step Functions Task to create a SageMaker model
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export declare class SageMakerCreateModel extends sfn.TaskStateBase implements iam.IGrantable, ec2.IConnectable {
+    private readonly props;
+    /**
+     * Uniquely identifies this class.
+     */
+    static readonly PROPERTY_INJECTION_ID: string;
+    /**
+     * A Step Functions Task using JSONPath to create a SageMaker model
+     *
+     * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+     */
+    static jsonPath(scope: Construct, id: string, props: SageMakerCreateModelJsonPathProps): SageMakerCreateModel;
+    /**
+     * A Step Functions Task using JSONata to create a SageMaker model
+     *
+     * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+     */
+    static jsonata(scope: Construct, id: string, props: SageMakerCreateModelJsonataProps): SageMakerCreateModel;
+    private static readonly SUPPORTED_INTEGRATION_PATTERNS;
+    /**
+     * Allows specify security group connections for instances of this fleet.
+     */
+    readonly connections: ec2.Connections;
+    /**
+     * The execution role for the Sagemaker Create Model API.
+     */
+    readonly role: iam.IRole;
+    readonly grantPrincipal: iam.IPrincipal;
+    protected readonly taskMetrics?: sfn.TaskMetricsConfig;
+    protected readonly taskPolicies?: iam.PolicyStatement[];
+    private readonly vpc?;
+    private securityGroup?;
+    private readonly _securityGroups;
+    private readonly subnets?;
+    private readonly integrationPattern;
+    constructor(scope: Construct, id: string, props: SageMakerCreateModelProps);
+    /**
+     * Add the security group to all instances via the launch configuration
+     * security groups array.
+     *
+     * @param securityGroup: The security group to add
+     */
+    addSecurityGroup(securityGroup: ec2.ISecurityGroup): void;
+    /**
+     * @internal
+     */
+    protected _renderTask(topLevelQueryLanguage?: sfn.QueryLanguage): any;
+    private renderParameters;
+    private makePolicyStatements;
+    private createSagemakerRole;
+    private renderVpcConfig;
+}
+export {};

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/create-training-job.d.ts

@@ -0,0 +1,177 @@
+import type { Construct } from 'constructs';
+import type { AlgorithmSpecification, Channel, OutputDataConfig, ResourceConfig, StoppingCondition, VpcConfig } from './base-types';
+import * as ec2 from '../../../aws-ec2';
+import * as iam from '../../../aws-iam';
+import * as sfn from '../../../aws-stepfunctions';
+interface SageMakerCreateTrainingJobOptions {
+    /**
+     * Training Job Name.
+     */
+    readonly trainingJobName: string;
+    /**
+     * Role for the Training Job. The role must be granted all necessary permissions for the SageMaker training job to
+     * be able to operate.
+     *
+     * See https://docs.aws.amazon.com/fr_fr/sagemaker/latest/dg/sagemaker-roles.html#sagemaker-roles-createtrainingjob-perms
+     *
+     * @default - a role will be created.
+     */
+    readonly role?: iam.IRole;
+    /**
+     * Identifies the training algorithm to use.
+     */
+    readonly algorithmSpecification: AlgorithmSpecification;
+    /**
+     * Isolates the training container. No inbound or outbound network calls can be made to or from the training container.
+     *
+     * @default false
+     */
+    readonly enableNetworkIsolation?: boolean;
+    /**
+     * Algorithm-specific parameters that influence the quality of the model. Set hyperparameters before you start the learning process.
+     * For a list of hyperparameters provided by Amazon SageMaker
+     * @see https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
+     *
+     * @default - No hyperparameters
+     */
+    readonly hyperparameters?: {
+        [key: string]: any;
+    };
+    /**
+     *  Describes the various datasets (e.g. train, validation, test) and the Amazon S3 location where stored.
+     *
+     * @default - No inputDataConfig
+     */
+    readonly inputDataConfig?: Channel[];
+    /**
+     * Tags to be applied to the train job.
+     *
+     * @default - No tags
+     */
+    readonly tags?: {
+        [key: string]: string;
+    };
+    /**
+     * Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training.
+     */
+    readonly outputDataConfig: OutputDataConfig;
+    /**
+     * Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training.
+     *
+     * @default - 1 instance of EC2 `M4.XLarge` with `10GB` volume
+     */
+    readonly resourceConfig?: ResourceConfig;
+    /**
+     * Sets a time limit for training.
+     *
+     * @default - max runtime of 1 hour
+     */
+    readonly stoppingCondition?: StoppingCondition;
+    /**
+     * Specifies the VPC that you want your training job to connect to.
+     *
+     * @default - No VPC
+     */
+    readonly vpcConfig?: VpcConfig;
+    /**
+     * Environment variables to set in the Docker container.
+     *
+     * @default - No environment variables
+     */
+    readonly environment?: {
+        [key: string]: string;
+    };
+}
+/**
+ * Properties for creating an Amazon SageMaker training job using JSONPath
+ */
+export interface SageMakerCreateTrainingJobJsonPathProps extends sfn.TaskStateJsonPathBaseProps, SageMakerCreateTrainingJobOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker training job using JSONata
+ */
+export interface SageMakerCreateTrainingJobJsonataProps extends sfn.TaskStateJsonataBaseProps, SageMakerCreateTrainingJobOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker training job
+ */
+export interface SageMakerCreateTrainingJobProps extends sfn.TaskStateBaseProps, SageMakerCreateTrainingJobOptions {
+}
+/**
+ * Class representing the SageMaker Create Training Job task.
+ */
+export declare class SageMakerCreateTrainingJob extends sfn.TaskStateBase implements iam.IGrantable, ec2.IConnectable {
+    private readonly props;
+    /**
+     * Uniquely identifies this class.
+     */
+    static readonly PROPERTY_INJECTION_ID: string;
+    /**
+     * A Step Functions Task using JSONPath to create a SageMaker training job.
+     */
+    static jsonPath(scope: Construct, id: string, props: SageMakerCreateTrainingJobJsonPathProps): SageMakerCreateTrainingJob;
+    /**
+     * A Step Functions Task using JSONata to create a SageMaker training job.
+     */
+    static jsonata(scope: Construct, id: string, props: SageMakerCreateTrainingJobJsonataProps): SageMakerCreateTrainingJob;
+    private static readonly SUPPORTED_INTEGRATION_PATTERNS;
+    /**
+     * Allows specify security group connections for instances of this fleet.
+     */
+    readonly connections: ec2.Connections;
+    protected readonly taskPolicies?: iam.PolicyStatement[];
+    protected readonly taskMetrics?: sfn.TaskMetricsConfig;
+    /**
+     * The Algorithm Specification
+     */
+    private readonly algorithmSpecification;
+    /**
+     * The Input Data Config.
+     */
+    private readonly inputDataConfig?;
+    /**
+     * The resource config for the task.
+     */
+    private readonly resourceConfig;
+    /**
+     * The resource config for the task.
+     */
+    private readonly stoppingCondition;
+    private readonly vpc?;
+    private securityGroup?;
+    private readonly _securityGroups;
+    private readonly subnets?;
+    private readonly integrationPattern;
+    private _role?;
+    private _grantPrincipal?;
+    constructor(scope: Construct, id: string, props: SageMakerCreateTrainingJobProps);
+    /**
+     * The execution role for the Sagemaker training job.
+     *
+     * Only available after task has been added to a state machine.
+     */
+    get role(): iam.IRole;
+    get grantPrincipal(): iam.IPrincipal;
+    /**
+     * Add the security group to all instances via the launch configuration
+     * security groups array.
+     *
+     * @param securityGroup: The security group to add
+     */
+    addSecurityGroup(securityGroup: ec2.ISecurityGroup): void;
+    /**
+     * @internal
+     */
+    protected _renderTask(topLevelQueryLanguage?: sfn.QueryLanguage): any;
+    private renderParameters;
+    private renderAlgorithmSpecification;
+    private renderInputDataConfig;
+    private renderOutputDataConfig;
+    private renderResourceConfig;
+    private renderStoppingCondition;
+    private renderHyperparameters;
+    private renderVpcConfig;
+    private validateAlgorithmName;
+    private makePolicyStatements;
+}
+export {};

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/create-transform-job.d.ts

@@ -0,0 +1,136 @@
+import type { Construct } from 'constructs';
+import type { BatchStrategy, ModelClientOptions, TransformInput, TransformOutput, TransformResources } from './base-types';
+import * as iam from '../../../aws-iam';
+import * as sfn from '../../../aws-stepfunctions';
+import type { Size } from '../../../core';
+interface SageMakerCreateTransformJobOptions {
+    /**
+     * Transform Job Name.
+     */
+    readonly transformJobName: string;
+    /**
+     * Role for the Transform Job.
+     *
+     * @default - A role is created with `AmazonSageMakerFullAccess` managed policy
+     */
+    readonly role?: iam.IRole;
+    /**
+     * Number of records to include in a mini-batch for an HTTP inference request.
+     *
+     * @default - No batch strategy
+     */
+    readonly batchStrategy?: BatchStrategy;
+    /**
+     * Environment variables to set in the Docker container.
+     *
+     * @default - No environment variables
+     */
+    readonly environment?: {
+        [key: string]: string;
+    };
+    /**
+     * Maximum number of parallel requests that can be sent to each instance in a transform job.
+     *
+     * @default - Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm.
+     * If the execution-parameters endpoint is not enabled, the default value is 1.
+     */
+    readonly maxConcurrentTransforms?: number;
+    /**
+     * Maximum allowed size of the payload, in MB.
+     *
+     * @default 6
+     */
+    readonly maxPayload?: Size;
+    /**
+     * Name of the model that you want to use for the transform job.
+     */
+    readonly modelName: string;
+    /**
+     * Configures the timeout and maximum number of retries for processing a transform job invocation.
+     *
+     * @default - 0 retries and 60 seconds of timeout
+     */
+    readonly modelClientOptions?: ModelClientOptions;
+    /**
+     * Tags to be applied to the train job.
+     *
+     * @default - No tags
+     */
+    readonly tags?: {
+        [key: string]: string;
+    };
+    /**
+     * Dataset to be transformed and the Amazon S3 location where it is stored.
+     */
+    readonly transformInput: TransformInput;
+    /**
+     * S3 location where you want Amazon SageMaker to save the results from the transform job.
+     */
+    readonly transformOutput: TransformOutput;
+    /**
+     * ML compute instances for the transform job.
+     *
+     * @default - 1 instance of type M4.XLarge
+     */
+    readonly transformResources?: TransformResources;
+}
+/**
+ * Properties for creating an Amazon SageMaker transform job task using JSONPath
+ */
+export interface SageMakerCreateTransformJobJsonPathProps extends sfn.TaskStateJsonPathBaseProps, SageMakerCreateTransformJobOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker transform job task using JSONata
+ */
+export interface SageMakerCreateTransformJobJsonataProps extends sfn.TaskStateJsonataBaseProps, SageMakerCreateTransformJobOptions {
+}
+/**
+ * Properties for creating an Amazon SageMaker transform job task
+ */
+export interface SageMakerCreateTransformJobProps extends sfn.TaskStateBaseProps, SageMakerCreateTransformJobOptions {
+}
+/**
+ * Class representing the SageMaker Create Transform Job task.
+ */
+export declare class SageMakerCreateTransformJob extends sfn.TaskStateBase {
+    private readonly props;
+    /**
+     * Class representing the SageMaker Create Transform Job task using JSONPath.
+     */
+    static jsonPath(scope: Construct, id: string, props: SageMakerCreateTransformJobJsonPathProps): SageMakerCreateTransformJob;
+    /**
+     * Class representing the SageMaker Create Transform Job task using JSONata.
+     */
+    static jsonata(scope: Construct, id: string, props: SageMakerCreateTransformJobJsonataProps): SageMakerCreateTransformJob;
+    private static readonly SUPPORTED_INTEGRATION_PATTERNS;
+    protected readonly taskPolicies?: iam.PolicyStatement[];
+    protected readonly taskMetrics?: sfn.TaskMetricsConfig;
+    /**
+     * Dataset to be transformed and the Amazon S3 location where it is stored.
+     */
+    private readonly transformInput;
+    /**
+     * ML compute instances for the transform job.
+     */
+    private readonly transformResources;
+    private readonly integrationPattern;
+    private _role?;
+    constructor(scope: Construct, id: string, props: SageMakerCreateTransformJobProps);
+    /**
+     * @internal
+     */
+    protected _renderTask(topLevelQueryLanguage?: sfn.QueryLanguage): any;
+    /**
+     * The execution role for the Sagemaker transform job.
+     *
+     * Only available after task has been added to a state machine.
+     */
+    get role(): iam.IRole;
+    private renderParameters;
+    private renderModelClientOptions;
+    private renderTransformInput;
+    private renderTransformOutput;
+    private renderTransformResources;
+    private makePolicyStatements;
+}
+export {};

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/private/utils.d.ts

@@ -0,0 +1,10 @@
+export declare function renderTags(tags: {
+    [key: string]: any;
+} | undefined): {
+    [key: string]: any;
+};
+export declare function renderEnvironment(environment: {
+    [key: string]: any;
+} | undefined): {
+    [key: string]: any;
+};

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/private/utils.js

@@ -0,0 +1 @@
+"use strict";Object.defineProperty(exports,"__esModule",{value:!0}),exports.renderTags=renderTags,exports.renderEnvironment=renderEnvironment;function renderTags(tags){return tags?{Tags:Object.keys(tags).map(key=>({Key:key,Value:tags[key]}))}:{}}function renderEnvironment(environment){return environment?{Environment:environment}:{}}

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/update-endpoint.d.ts

@@ -0,0 +1,66 @@
+import type { Construct } from 'constructs';
+import * as iam from '../../../aws-iam';
+import * as sfn from '../../../aws-stepfunctions';
+interface SageMakerUpdateEndpointOptions {
+    /**
+     * The name of the new endpoint configuration
+     */
+    readonly endpointConfigName: string;
+    /**
+     * The name of the endpoint whose configuration you want to update.
+     */
+    readonly endpointName: string;
+}
+/**
+ * Properties for updating Amazon SageMaker endpoint using JSONPath
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerUpdateEndpointJsonPathProps extends sfn.TaskStateJsonPathBaseProps, SageMakerUpdateEndpointOptions {
+}
+/**
+ * Properties for updating Amazon SageMaker endpoint using JSONata
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerUpdateEndpointJsonataProps extends sfn.TaskStateJsonataBaseProps, SageMakerUpdateEndpointOptions {
+}
+/**
+ * Properties for updating Amazon SageMaker endpoint
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export interface SageMakerUpdateEndpointProps extends sfn.TaskStateBaseProps, SageMakerUpdateEndpointOptions {
+}
+/**
+ * A Step Functions Task to update a SageMaker endpoint
+ *
+ * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+ */
+export declare class SageMakerUpdateEndpoint extends sfn.TaskStateBase {
+    private readonly props;
+    /**
+     * A Step Functions Task using JSONPath to update a SageMaker endpoint
+     *
+     * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+     */
+    static jsonPath(scope: Construct, id: string, props: SageMakerUpdateEndpointJsonPathProps): SageMakerUpdateEndpoint;
+    /**
+     * A Step Functions Task using JSONata to update a SageMaker endpoint
+     *
+     * @see https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html
+     */
+    static jsonata(scope: Construct, id: string, props: SageMakerUpdateEndpointJsonataProps): SageMakerUpdateEndpoint;
+    private static readonly SUPPORTED_INTEGRATION_PATTERNS;
+    protected readonly taskMetrics?: sfn.TaskMetricsConfig;
+    protected readonly taskPolicies?: iam.PolicyStatement[];
+    private readonly integrationPattern;
+    constructor(scope: Construct, id: string, props: SageMakerUpdateEndpointProps);
+    /**
+     * @internal
+     */
+    protected _renderTask(topLevelQueryLanguage?: sfn.QueryLanguage): any;
+    private renderParameters;
+    private makePolicyStatements;
+}
+export {};

cdk/node_modules/aws-cdk-lib/aws-stepfunctions-tasks/lib/sagemaker/update-endpoint.js

@@ -0,0 +1 @@
+"use strict";Object.defineProperty(exports,"__esModule",{value:!0}),exports.SageMakerUpdateEndpoint=void 0;var jsiiDeprecationWarnings=()=>{var tmp=require("../../../.warnings.jsii.js");return jsiiDeprecationWarnings=()=>tmp,tmp};const JSII_RTTI_SYMBOL_1=Symbol.for("jsii.rtti");var iam=()=>{var tmp=require("../../../aws-iam");return iam=()=>tmp,tmp},sfn=()=>{var tmp=require("../../../aws-stepfunctions");return sfn=()=>tmp,tmp},cdk=()=>{var tmp=require("../../../core");return cdk=()=>tmp,tmp},task_utils_1=()=>{var tmp=require("../private/task-utils");return task_utils_1=()=>tmp,tmp};class SageMakerUpdateEndpoint extends sfn().TaskStateBase{props;static[JSII_RTTI_SYMBOL_1]={fqn:"aws-cdk-lib.aws_stepfunctions_tasks.SageMakerUpdateEndpoint",version:"2.252.0"};static jsonPath(scope,id,props){try{jsiiDeprecationWarnings().aws_cdk_lib_aws_stepfunctions_tasks_SageMakerUpdateEndpointJsonPathProps(props)}catch(error){throw process.env.JSII_DEBUG!=="1"&&error.name==="DeprecationError"&&Error.captureStackTrace(error,this.jsonPath),error}return new SageMakerUpdateEndpoint(scope,id,props)}static jsonata(scope,id,props){try{jsiiDeprecationWarnings().aws_cdk_lib_aws_stepfunctions_tasks_SageMakerUpdateEndpointJsonataProps(props)}catch(error){throw process.env.JSII_DEBUG!=="1"&&error.name==="DeprecationError"&&Error.captureStackTrace(error,this.jsonata),error}return new SageMakerUpdateEndpoint(scope,id,{...props,queryLanguage:sfn().QueryLanguage.JSONATA})}static SUPPORTED_INTEGRATION_PATTERNS=[sfn().IntegrationPattern.REQUEST_RESPONSE];taskMetrics;taskPolicies;integrationPattern;constructor(scope,id,props){super(scope,id,props),this.props=props;try{jsiiDeprecationWarnings().aws_cdk_lib_aws_stepfunctions_tasks_SageMakerUpdateEndpointProps(props)}catch(error){throw process.env.JSII_DEBUG!=="1"&&error.name==="DeprecationError"&&Error.captureStackTrace(error,SageMakerUpdateEndpoint),error}this.integrationPattern=props.integrationPattern||sfn().IntegrationPattern.REQUEST_RESPONSE,(0,task_utils_1().validatePatternSupported)(this.integrationPattern,SageMakerUpdateEndpoint.SUPPORTED_INTEGRATION_PATTERNS),this.taskPolicies=this.makePolicyStatements()}_renderTask(topLevelQueryLanguage){const queryLanguage=sfn()._getActualQueryLanguage(topLevelQueryLanguage,this.props.queryLanguage);return{Resource:(0,task_utils_1().integrationResourceArn)("sagemaker","updateEndpoint",this.integrationPattern),...this._renderParametersOrArguments(this.renderParameters(),queryLanguage)}}renderParameters(){return{EndpointConfigName:this.props.endpointConfigName,EndpointName:this.props.endpointName}}makePolicyStatements(){const stack=cdk().Stack.of(this);return[new(iam()).PolicyStatement({actions:["sagemaker:updateEndpoint"],resources:[stack.formatArn({service:"sagemaker",resource:"endpoint",resourceName:(0,task_utils_1().isJsonPathOrJsonataExpression)(this.props.endpointName)?"*":`${this.props.endpointName.toLowerCase()}`}),stack.formatArn({service:"sagemaker",resource:"endpoint-config",resourceName:(0,task_utils_1().isJsonPathOrJsonataExpression)(this.props.endpointConfigName)?"*":`${this.props.endpointConfigName.toLowerCase()}`})]})]}}exports.SageMakerUpdateEndpoint=SageMakerUpdateEndpoint;