types

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 Go to latest Published: Oct 31, 2020 License: Apache-2.0 Imports: 3 Imported by: 13

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Types

type AlgorithmSortBy 

type AlgorithmSortBy string
const (
	AlgorithmSortByName         AlgorithmSortBy = "Name"
	AlgorithmSortByCreationTime AlgorithmSortBy = "CreationTime"
)

Enum values for AlgorithmSortBy

func (AlgorithmSortBy) Values added in v0.29.0 

func (AlgorithmSortBy) Values() []AlgorithmSortBy

Values returns all known values for AlgorithmSortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AlgorithmSpecification 

type AlgorithmSpecification struct {

	// The input mode that the algorithm supports. For the input modes that Amazon
	// SageMaker algorithms support, see Algorithms
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html). If an algorithm
	// supports the File input mode, Amazon SageMaker downloads the training data from
	// S3 to the provisioned ML storage Volume, and mounts the directory to docker
	// volume for training container. If an algorithm supports the Pipe input mode,
	// Amazon SageMaker streams data directly from S3 to the container. In File mode,
	// make sure you provision ML storage volume with sufficient capacity to
	// accommodate the data download from S3. In addition to the training data, the ML
	// storage volume also stores the output model. The algorithm container use ML
	// storage volume to also store intermediate information, if any. For distributed
	// algorithms using File mode, training data is distributed uniformly, and your
	// training duration is predictable if the input data objects size is approximately
	// same. Amazon SageMaker does not split the files any further for model training.
	// If the object sizes are skewed, training won't be optimal as the data
	// distribution is also skewed where one host in a training cluster is overloaded,
	// thus becoming bottleneck in training.
	//
	// This member is required.
	TrainingInputMode TrainingInputMode

	// The 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.
	AlgorithmName *string

	// To generate and save time-series metrics during training, set to true. The
	// default is false and time-series metrics aren't generated except in the
	// following cases:
	//
	// * You use one of the Amazon SageMaker built-in algorithms
	//
	// *
	// You use one of the following Prebuilt Amazon SageMaker Docker Images
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html):
	//
	// *
	// Tensorflow (version >= 1.15)
	//
	// * MXNet (version >= 1.6)
	//
	// * PyTorch (version >=
	// 1.3)
	//
	// * You specify at least one MetricDefinition
	EnableSageMakerMetricsTimeSeries *bool

	// A list of metric definition objects. Each object specifies the metric name and
	// regular expressions used to parse algorithm logs. Amazon SageMaker publishes
	// each metric to Amazon CloudWatch.
	MetricDefinitions []*MetricDefinition

	// The registry path of the Docker image that contains the training algorithm. For
	// information about docker registry paths for built-in algorithms, see Algorithms
	// Provided by Amazon SageMaker: Common Parameters
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html).
	// Amazon SageMaker supports both registry/repository[:tag] and
	// registry/repository[@digest] image path formats. For more information, see Using
	// Your Own Algorithms with Amazon SageMaker
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html).
	TrainingImage *string
}

Specifies the training algorithm to use in a CreateTrainingJob request. For more information about algorithms provided by Amazon SageMaker, see Algorithms (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html). For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker (https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html).

type AlgorithmStatus 

type AlgorithmStatus string
const (
	AlgorithmStatusPending    AlgorithmStatus = "Pending"
	AlgorithmStatusInProgress AlgorithmStatus = "InProgress"
	AlgorithmStatusCompleted  AlgorithmStatus = "Completed"
	AlgorithmStatusFailed     AlgorithmStatus = "Failed"
	AlgorithmStatusDeleting   AlgorithmStatus = "Deleting"
)

Enum values for AlgorithmStatus

func (AlgorithmStatus) Values added in v0.29.0 

func (AlgorithmStatus) Values() []AlgorithmStatus

Values returns all known values for AlgorithmStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AlgorithmStatusDetails 

type AlgorithmStatusDetails struct {

	// The status of the scan of the algorithm's Docker image container.
	ImageScanStatuses []*AlgorithmStatusItem

	// The status of algorithm validation.
	ValidationStatuses []*AlgorithmStatusItem
}

Specifies the validation and image scan statuses of the algorithm.

type AlgorithmStatusItem 

type AlgorithmStatusItem struct {

	// The name of the algorithm for which the overall status is being reported.
	//
	// This member is required.
	Name *string

	// The current status.
	//
	// This member is required.
	Status DetailedAlgorithmStatus

	// if the overall status is Failed, the reason for the failure.
	FailureReason *string
}

Represents the overall status of an algorithm.

type AlgorithmSummary 

type AlgorithmSummary struct {

	// The Amazon Resource Name (ARN) of the algorithm.
	//
	// This member is required.
	AlgorithmArn *string

	// The name of the algorithm that is described by the summary.
	//
	// This member is required.
	AlgorithmName *string

	// The overall status of the algorithm.
	//
	// This member is required.
	AlgorithmStatus AlgorithmStatus

	// A timestamp that shows when the algorithm was created.
	//
	// This member is required.
	CreationTime *time.Time

	// A brief description of the algorithm.
	AlgorithmDescription *string
}

Provides summary information about an algorithm.

type AlgorithmValidationProfile 

type AlgorithmValidationProfile struct {

	// The name of the profile for the algorithm. The name must have 1 to 63
	// characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
	//
	// This member is required.
	ProfileName *string

	// The TrainingJobDefinition object that describes the training job that Amazon
	// SageMaker runs to validate your algorithm.
	//
	// This member is required.
	TrainingJobDefinition *TrainingJobDefinition

	// The TransformJobDefinition object that describes the transform job that Amazon
	// SageMaker runs to validate your algorithm.
	TransformJobDefinition *TransformJobDefinition
}

Defines a training job and a batch transform job that Amazon SageMaker runs to validate your algorithm. The data provided in the validation profile is made available to your buyers on AWS Marketplace.

type AlgorithmValidationSpecification 

type AlgorithmValidationSpecification struct {

	// An array of AlgorithmValidationProfile objects, each of which specifies a
	// training job and batch transform job that Amazon SageMaker runs to validate your
	// algorithm.
	//
	// This member is required.
	ValidationProfiles []*AlgorithmValidationProfile

	// The IAM roles that Amazon SageMaker uses to run the training jobs.
	//
	// This member is required.
	ValidationRole *string
}

Specifies configurations for one or more training jobs that Amazon SageMaker runs to test the algorithm.

type AnnotationConsolidationConfig 

type AnnotationConsolidationConfig struct {

	// The Amazon Resource Name (ARN) of a Lambda function implements the logic for
	// annotation consolidation
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.html)
	// and to process output data. This parameter is required for all labeling jobs.
	// For built-in task types
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html), use one
	// of the following Amazon SageMaker Ground Truth Lambda function ARNs for
	// AnnotationConsolidationLambdaArn. For custom labeling workflows, see
	// Post-annotation Lambda
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-postlambda).
	// Bounding box - Finds the most similar boxes from different workers based on the
	// Jaccard index of the boxes.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBoxarn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBoxarn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBoxarn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBoxarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBoxarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBoxarn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBoxarn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBoxarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBoxarn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBoxarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBoxarn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox
	//
	// Image
	// classification - Uses a variant of the Expectation Maximization approach to
	// estimate the true class of an image based on annotations from individual
	// workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassarn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassarn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassarn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassarn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassarn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassarn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassarn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass
	//
	// Multi-label
	// image classification - Uses a variant of the Expectation Maximization approach
	// to estimate the true classes of an image based on annotations from individual
	// workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabelarn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel
	//
	// Semantic
	// segmentation - Treats each pixel in an image as a multi-class classification and
	// treats pixel annotations from workers as "votes" for the correct label.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentationarn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentationarn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentationarn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentationarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentationarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentationarn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentationarn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentationarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentationarn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentationarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentationarn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation
	//
	// Text
	// classification - Uses a variant of the Expectation Maximization approach to
	// estimate the true class of text based on annotations from individual workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassarn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassarn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassarn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassarn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassarn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassarn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassarn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass
	//
	// Multi-label
	// text classification - Uses a variant of the Expectation Maximization approach to
	// estimate the true classes of text based on annotations from individual
	// workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabelarn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel
	//
	// Named
	// entity recognition - Groups similar selections and calculates aggregate
	// boundaries, resolving to most-assigned label.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognitionarn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognitionarn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognitionarn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognitionarn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognitionarn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognitionarn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
	//
	// Named
	// entity recognition - Groups similar selections and calculates aggregate
	// boundaries, resolving to most-assigned label.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognitionarn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognitionarn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognitionarn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognitionarn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognitionarn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognitionarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognitionarn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition
	//
	// Video
	// Classification - Use this task type when you need workers to classify videos
	// using predefined labels that you specify. Workers are shown videos and are asked
	// to choose one label for each video.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClassarn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClassarn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClassarn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClassarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClassarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClassarn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClassarn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClassarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClassarn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClassarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClassarn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass
	//
	// Video
	// Frame Object Detection - Use this task type to have workers identify and locate
	// objects in a sequence of video frames (images extracted from a video) using
	// bounding boxes. For example, you can use this task to ask workers to identify
	// and localize various objects in a series of video frames, such as cars, bikes,
	// and pedestrians.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetectionarn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetectionarn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetectionarn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetectionarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetectionarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetectionarn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetectionarn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetectionarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetectionarn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetectionarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetectionarn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection
	//
	// Video
	// Frame Object Tracking - Use this task type to have workers track the movement of
	// objects in a sequence of video frames (images extracted from a video) using
	// bounding boxes. For example, you can use this task to ask workers to track the
	// movement of objects, such as cars, bikes, and pedestrians.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTrackingarn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTrackingarn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTrackingarn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTrackingarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTrackingarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTrackingarn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTrackingarn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTrackingarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTrackingarn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTrackingarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTrackingarn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking
	//
	// 3D
	// point cloud object detection - Use this task type when you want workers to
	// classify objects in a 3D point cloud by drawing 3D cuboids around objects. For
	// example, you can use this task type to ask workers to identify different types
	// of objects in a point cloud, such as cars, bikes, and pedestrians.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetectionarn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection
	//
	// 3D
	// point cloud object tracking - Use this task type when you want workers to draw
	// 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
	// For example, you can use this task type to ask workers to track the movement of
	// vehicles across multiple point cloud frames.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTrackingarn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking
	//
	// 3D
	// point cloud semantic segmentation - Use this task type when you want workers to
	// create a point-level semantic segmentation masks by painting objects in a 3D
	// point cloud using different colors where each color is assigned to one of the
	// classes you specify.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentationarn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation
	//
	// Use
	// the following ARNs for Label Verification and Adjustment Jobs Use label
	// verification and adjustment jobs to review and adjust labels. To learn more, see
	// Verify and Adjust Labels
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.html).
	// Semantic segmentation adjustment - Treats each pixel in an image as a
	// multi-class classification and treats pixel adjusted annotations from workers as
	// "votes" for the correct label.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentationarn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation
	//
	// Semantic
	// segmentation verification - Uses a variant of the Expectation Maximization
	// approach to estimate the true class of verification judgment for semantic
	// segmentation labels based on annotations from individual workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentationarn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
	//
	// Bounding
	// box verification - Uses a variant of the Expectation Maximization approach to
	// estimate the true class of verification judgement for bounding box labels based
	// on annotations from individual workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBoxarn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBoxarn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBoxarn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBoxarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBoxarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBoxarn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBoxarn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBoxarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBoxarn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBoxarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBoxarn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
	//
	// Bounding
	// box adjustment - Finds the most similar boxes from different workers based on
	// the Jaccard index of the adjusted annotations.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBoxarn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
	//
	// Video
	// Frame Object Detection Adjustment - Use this task type when you want workers to
	// adjust bounding boxes that workers have added to video frames to classify and
	// localize objects in a sequence of video frames.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetectionarn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection
	//
	// Video
	// Frame Object Tracking Adjustment - Use this task type when you want workers to
	// adjust bounding boxes that workers have added to video frames to track object
	// movement across a sequence of video frames.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTrackingarn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking
	//
	// 3D
	// point cloud object detection adjustment - Use this task type when you want
	// workers to adjust 3D cuboids around objects in a 3D point cloud.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetectionarn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// 3D
	// point cloud object tracking adjustment - Use this task type when you want
	// workers to adjust 3D cuboids around objects that appear in a sequence of 3D
	// point cloud frames.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTrackingarn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// 3D
	// point cloud semantic segmentation adjustment - Use this task type when you want
	// workers to adjust a point-level semantic segmentation masks using a paint
	// tool.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentationarn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// This member is required.
	AnnotationConsolidationLambdaArn *string
}

Configures how labels are consolidated across human workers and processes output data.

type AppDetails 

type AppDetails struct {

	// The name of the app.
	AppName *string

	// The type of app.
	AppType AppType

	// The creation time.
	CreationTime *time.Time

	// The domain ID.
	DomainId *string

	// The status.
	Status AppStatus

	// The user profile name.
	UserProfileName *string
}

Details about an Amazon SageMaker app.

type AppImageConfigDetails added in v0.29.0 

type AppImageConfigDetails struct {

	// The Amazon Resource Name (ARN) of the AppImageConfig.
	AppImageConfigArn *string

	// The name of the AppImageConfig.
	AppImageConfigName *string

	// When the AppImageConfig was created.
	CreationTime *time.Time

	// The KernelGateway app.
	KernelGatewayImageConfig *KernelGatewayImageConfig

	// When the AppImageConfig was last modified.
	LastModifiedTime *time.Time
}

The configuration for running an Amazon SageMaker image as a KernelGateway app.

type AppImageConfigSortKey added in v0.29.0 

type AppImageConfigSortKey string
const (
	AppImageConfigSortKeyCreationtime     AppImageConfigSortKey = "CreationTime"
	AppImageConfigSortKeyLastmodifiedtime AppImageConfigSortKey = "LastModifiedTime"
	AppImageConfigSortKeyName             AppImageConfigSortKey = "Name"
)

Enum values for AppImageConfigSortKey

func (AppImageConfigSortKey) Values added in v0.29.0 

func (AppImageConfigSortKey) Values() []AppImageConfigSortKey

Values returns all known values for AppImageConfigSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AppInstanceType 

type AppInstanceType string
const (
	AppInstanceTypeSystem         AppInstanceType = "system"
	AppInstanceTypeMlT3Micro      AppInstanceType = "ml.t3.micro"
	AppInstanceTypeMlT3Small      AppInstanceType = "ml.t3.small"
	AppInstanceTypeMlT3Medium     AppInstanceType = "ml.t3.medium"
	AppInstanceTypeMlT3Large      AppInstanceType = "ml.t3.large"
	AppInstanceTypeMlT3Xlarge     AppInstanceType = "ml.t3.xlarge"
	AppInstanceTypeMlT32xlarge    AppInstanceType = "ml.t3.2xlarge"
	AppInstanceTypeMlM5Large      AppInstanceType = "ml.m5.large"
	AppInstanceTypeMlM5Xlarge     AppInstanceType = "ml.m5.xlarge"
	AppInstanceTypeMlM52xlarge    AppInstanceType = "ml.m5.2xlarge"
	AppInstanceTypeMlM54xlarge    AppInstanceType = "ml.m5.4xlarge"
	AppInstanceTypeMlM58xlarge    AppInstanceType = "ml.m5.8xlarge"
	AppInstanceTypeMlM512xlarge   AppInstanceType = "ml.m5.12xlarge"
	AppInstanceTypeMlM516xlarge   AppInstanceType = "ml.m5.16xlarge"
	AppInstanceTypeMlM524xlarge   AppInstanceType = "ml.m5.24xlarge"
	AppInstanceTypeMlC5Large      AppInstanceType = "ml.c5.large"
	AppInstanceTypeMlC5Xlarge     AppInstanceType = "ml.c5.xlarge"
	AppInstanceTypeMlC52xlarge    AppInstanceType = "ml.c5.2xlarge"
	AppInstanceTypeMlC54xlarge    AppInstanceType = "ml.c5.4xlarge"
	AppInstanceTypeMlC59xlarge    AppInstanceType = "ml.c5.9xlarge"
	AppInstanceTypeMlC512xlarge   AppInstanceType = "ml.c5.12xlarge"
	AppInstanceTypeMlC518xlarge   AppInstanceType = "ml.c5.18xlarge"
	AppInstanceTypeMlC524xlarge   AppInstanceType = "ml.c5.24xlarge"
	AppInstanceTypeMlP32xlarge    AppInstanceType = "ml.p3.2xlarge"
	AppInstanceTypeMlP38xlarge    AppInstanceType = "ml.p3.8xlarge"
	AppInstanceTypeMlP316xlarge   AppInstanceType = "ml.p3.16xlarge"
	AppInstanceTypeMlG4dnXlarge   AppInstanceType = "ml.g4dn.xlarge"
	AppInstanceTypeMlG4dn2xlarge  AppInstanceType = "ml.g4dn.2xlarge"
	AppInstanceTypeMlG4dn4xlarge  AppInstanceType = "ml.g4dn.4xlarge"
	AppInstanceTypeMlG4dn8xlarge  AppInstanceType = "ml.g4dn.8xlarge"
	AppInstanceTypeMlG4dn12xlarge AppInstanceType = "ml.g4dn.12xlarge"
	AppInstanceTypeMlG4dn16xlarge AppInstanceType = "ml.g4dn.16xlarge"
)

Enum values for AppInstanceType

func (AppInstanceType) Values added in v0.29.0 

func (AppInstanceType) Values() []AppInstanceType

Values returns all known values for AppInstanceType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AppNetworkAccessType added in v0.29.0 

type AppNetworkAccessType string
const (
	AppNetworkAccessTypePublicinternetonly AppNetworkAccessType = "PublicInternetOnly"
	AppNetworkAccessTypeVpconly            AppNetworkAccessType = "VpcOnly"
)

Enum values for AppNetworkAccessType

func (AppNetworkAccessType) Values added in v0.29.0 

func (AppNetworkAccessType) Values() []AppNetworkAccessType

Values returns all known values for AppNetworkAccessType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AppSortKey 

type AppSortKey string
const (
	AppSortKeyCreationtime AppSortKey = "CreationTime"
)

Enum values for AppSortKey

func (AppSortKey) Values added in v0.29.0 

func (AppSortKey) Values() []AppSortKey

Values returns all known values for AppSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AppSpecification 

type AppSpecification struct {

	// The container image to be run by the processing job.
	//
	// This member is required.
	ImageUri *string

	// The arguments for a container used to run a processing job.
	ContainerArguments []*string

	// The entrypoint for a container used to run a processing job.
	ContainerEntrypoint []*string
}

Configuration to run a processing job in a specified container image.

type AppStatus 

type AppStatus string
const (
	AppStatusDeleted   AppStatus = "Deleted"
	AppStatusDeleting  AppStatus = "Deleting"
	AppStatusFailed    AppStatus = "Failed"
	AppStatusInservice AppStatus = "InService"
	AppStatusPending   AppStatus = "Pending"
)

Enum values for AppStatus

func (AppStatus) Values added in v0.29.0 

func (AppStatus) Values() []AppStatus

Values returns all known values for AppStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AppType 

type AppType string
const (
	AppTypeJupyterserver AppType = "JupyterServer"
	AppTypeKernelgateway AppType = "KernelGateway"
	AppTypeTensorboard   AppType = "TensorBoard"
)

Enum values for AppType

func (AppType) Values added in v0.29.0 

func (AppType) Values() []AppType

Values returns all known values for AppType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AssemblyType 

type AssemblyType string
const (
	AssemblyTypeNone AssemblyType = "None"
	AssemblyTypeLine AssemblyType = "Line"
)

Enum values for AssemblyType

func (AssemblyType) Values added in v0.29.0 

func (AssemblyType) Values() []AssemblyType

Values returns all known values for AssemblyType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AuthMode 

type AuthMode string
const (
	AuthModeSso AuthMode = "SSO"
	AuthModeIam AuthMode = "IAM"
)

Enum values for AuthMode

func (AuthMode) Values added in v0.29.0 

func (AuthMode) Values() []AuthMode

Values returns all known values for AuthMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AutoMLCandidate 

type AutoMLCandidate struct {

	// The candidate name.
	//
	// This member is required.
	CandidateName *string

	// The candidate's status.
	//
	// This member is required.
	CandidateStatus CandidateStatus

	// The candidate's steps.
	//
	// This member is required.
	CandidateSteps []*AutoMLCandidateStep

	// The creation time.
	//
	// This member is required.
	CreationTime *time.Time

	// The last modified time.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// The objective status.
	//
	// This member is required.
	ObjectiveStatus ObjectiveStatus

	// The end time.
	EndTime *time.Time

	// The failure reason.
	FailureReason *string

	// The best candidate result from an AutoML training job.
	FinalAutoMLJobObjectiveMetric *FinalAutoMLJobObjectiveMetric

	// The inference containers.
	InferenceContainers []*AutoMLContainerDefinition
}

An Autopilot job returns recommendations, or candidates. Each candidate has futher details about the steps involed, and the status.

type AutoMLCandidateStep 

type AutoMLCandidateStep struct {

	// The ARN for the Candidate's step.
	//
	// This member is required.
	CandidateStepArn *string

	// The name for the Candidate's step.
	//
	// This member is required.
	CandidateStepName *string

	// Whether the Candidate is at the transform, training, or processing step.
	//
	// This member is required.
	CandidateStepType CandidateStepType
}

Information about the steps for a Candidate, and what step it is working on.

type AutoMLChannel 

type AutoMLChannel struct {

	// The data source.
	//
	// This member is required.
	DataSource *AutoMLDataSource

	// The name of the target variable in supervised learning, a.k.a. 'y'.
	//
	// This member is required.
	TargetAttributeName *string

	// You can use Gzip or None. The default value is None.
	CompressionType CompressionType
}

Similar to Channel. A channel is a named input source that training algorithms can consume. Refer to Channel for detailed descriptions.

type AutoMLContainerDefinition 

type AutoMLContainerDefinition struct {

	// The ECR path of the container. Refer to ContainerDefinition for more details.
	//
	// This member is required.
	Image *string

	// The location of the model artifacts. Refer to ContainerDefinition for more
	// details.
	//
	// This member is required.
	ModelDataUrl *string

	// Environment variables to set in the container. Refer to ContainerDefinition for
	// more details.
	Environment map[string]*string
}

A list of container definitions that describe the different containers that make up one AutoML candidate. Refer to ContainerDefinition for more details.

type AutoMLDataSource 

type AutoMLDataSource struct {

	// The Amazon S3 location of the input data. The input data must be in CSV format
	// and contain at least 500 rows.
	//
	// This member is required.
	S3DataSource *AutoMLS3DataSource
}

The data source for the Autopilot job.

type AutoMLJobArtifacts 

type AutoMLJobArtifacts struct {

	// The URL to the notebook location.
	CandidateDefinitionNotebookLocation *string

	// The URL to the notebook location.
	DataExplorationNotebookLocation *string
}

Artifacts that are generation during a job.

type AutoMLJobCompletionCriteria 

type AutoMLJobCompletionCriteria struct {

	// The maximum time, in seconds, an AutoML job is allowed to wait for a trial to
	// complete. It must be equal to or greater than MaxRuntimePerTrainingJobInSeconds.
	MaxAutoMLJobRuntimeInSeconds *int32

	// The maximum number of times a training job is allowed to run.
	MaxCandidates *int32

	// The maximum time, in seconds, a job is allowed to run.
	MaxRuntimePerTrainingJobInSeconds *int32
}

How long a job is allowed to run, or how many candidates a job is allowed to generate.

type AutoMLJobConfig 

type AutoMLJobConfig struct {

	// How long a job is allowed to run, or how many candidates a job is allowed to
	// generate.
	CompletionCriteria *AutoMLJobCompletionCriteria

	// Security configuration for traffic encryption or Amazon VPC settings.
	SecurityConfig *AutoMLSecurityConfig
}

A collection of settings used for a job.

type AutoMLJobObjective 

type AutoMLJobObjective struct {

	// The name of the objective metric used to measure the predictive quality of a
	// machine learning system. This metric is optimized during training to provide the
	// best estimate for model parameter values from data. Here are the options:
	//
	// *
	// MSE: The mean squared error (MSE) is the average of the squared differences
	// between the predicted and actual values. It is used for regression. MSE values
	// are always positive, the better a model is at predicting the actual values the
	// smaller the MSE value. When the data contains outliers, they tend to dominate
	// the MSE which might cause subpar prediction performance.
	//
	// * Accuracy: The ratio
	// of the number correctly classified items to the total number (correctly and
	// incorrectly) classified. It is used for binary and multiclass classification.
	// Measures how close the predicted class values are to the actual values. Accuracy
	// values vary between zero and one, one being perfect accuracy and zero perfect
	// inaccuracy.
	//
	// * F1: The F1 score is the harmonic mean of the precision and
	// recall. It is used for binary classification into classes traditionally referred
	// to as positive and negative. Predictions are said to be true when they match
	// their actual (correct) class; false when they do not. Precision is the ratio of
	// the true positive predictions to all positive predictions (including the false
	// positives) in a data set and measures the quality of the prediction when it
	// predicts the positive class. Recall (or sensitivity) is the ratio of the true
	// positive predictions to all actual positive instances and measures how
	// completely a model predicts the actual class members in a data set. The standard
	// F1 score weighs precision and recall equally. But which metric is paramount
	// typically depends on specific aspects of a problem. F1 scores vary between zero
	// and one, one being the best possible performance and zero the worst.
	//
	// * AUC: The
	// area under the curve (AUC) metric is used to compare and evaluate binary
	// classification by algorithms such as logistic regression that return
	// probabilities. A threshold is needed to map the probabilities into
	// classifications. The relevant curve is the receiver operating characteristic
	// curve that plots the true positive rate (TPR) of predictions (or recall) against
	// the false positive rate (FPR) as a function of the threshold value, above which
	// a prediction is considered positive. Increasing the threshold results in fewer
	// false positives but more false negatives. AUC is the area under this receiver
	// operating characteristic curve and so provides an aggregated measure of the
	// model performance across all possible classification thresholds. The AUC score
	// can also be interpreted as the probability that a randomly selected positive
	// data point is more likely to be predicted positive than a randomly selected
	// negative example. AUC scores vary between zero and one, one being perfect
	// accuracy and one half not better than a random classifier. Values less that one
	// half predict worse than a random predictor and such consistently bad predictors
	// can be inverted to obtain better than random predictors.
	//
	// * F1macro: The F1macro
	// score applies F1 scoring to multiclass classification. In this context, you have
	// multiple classes to predict. You just calculate the precision and recall for
	// each class as you did for the positive class in binary classification. Then used
	// these values to calculate the F1 score for each class and average them to obtain
	// the F1macro score. F1macro scores vary between zero and one, one being the best
	// possible performance and zero the worst.
	//
	// If you do not specify a metric
	// explicitly, the default behavior is to automatically use:
	//
	// * MSE: for
	// regression.
	//
	// * F1: for binary classification
	//
	// * Accuracy: for multiclass
	// classification.
	//
	// This member is required.
	MetricName AutoMLMetricEnum
}

Specifies a metric to minimize or maximize as the objective of a job.

type AutoMLJobObjectiveType 

type AutoMLJobObjectiveType string
const (
	AutoMLJobObjectiveTypeMaximize AutoMLJobObjectiveType = "Maximize"
	AutoMLJobObjectiveTypeMinimize AutoMLJobObjectiveType = "Minimize"
)

Enum values for AutoMLJobObjectiveType

func (AutoMLJobObjectiveType) Values added in v0.29.0 

func (AutoMLJobObjectiveType) Values() []AutoMLJobObjectiveType

Values returns all known values for AutoMLJobObjectiveType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AutoMLJobSecondaryStatus 

type AutoMLJobSecondaryStatus string
const (
	AutoMLJobSecondaryStatusStarting                      AutoMLJobSecondaryStatus = "Starting"
	AutoMLJobSecondaryStatusAnalyzingData                 AutoMLJobSecondaryStatus = "AnalyzingData"
	AutoMLJobSecondaryStatusFeatureEngineering            AutoMLJobSecondaryStatus = "FeatureEngineering"
	AutoMLJobSecondaryStatusModelTuning                   AutoMLJobSecondaryStatus = "ModelTuning"
	AutoMLJobSecondaryStatusMaxCandidatesReached          AutoMLJobSecondaryStatus = "MaxCandidatesReached"
	AutoMLJobSecondaryStatusFailed                        AutoMLJobSecondaryStatus = "Failed"
	AutoMLJobSecondaryStatusStopped                       AutoMLJobSecondaryStatus = "Stopped"
	AutoMLJobSecondaryStatusMaxAutoMlJobRuntimeReached    AutoMLJobSecondaryStatus = "MaxAutoMLJobRuntimeReached"
	AutoMLJobSecondaryStatusStopping                      AutoMLJobSecondaryStatus = "Stopping"
	AutoMLJobSecondaryStatusCandidateDefinitionsGenerated AutoMLJobSecondaryStatus = "CandidateDefinitionsGenerated"
)

Enum values for AutoMLJobSecondaryStatus

func (AutoMLJobSecondaryStatus) Values added in v0.29.0 

func (AutoMLJobSecondaryStatus) Values() []AutoMLJobSecondaryStatus

Values returns all known values for AutoMLJobSecondaryStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AutoMLJobStatus 

type AutoMLJobStatus string
const (
	AutoMLJobStatusCompleted  AutoMLJobStatus = "Completed"
	AutoMLJobStatusInProgress AutoMLJobStatus = "InProgress"
	AutoMLJobStatusFailed     AutoMLJobStatus = "Failed"
	AutoMLJobStatusStopped    AutoMLJobStatus = "Stopped"
	AutoMLJobStatusStopping   AutoMLJobStatus = "Stopping"
)

Enum values for AutoMLJobStatus

func (AutoMLJobStatus) Values added in v0.29.0 

func (AutoMLJobStatus) Values() []AutoMLJobStatus

Values returns all known values for AutoMLJobStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AutoMLJobSummary 

type AutoMLJobSummary struct {

	// The ARN of the job.
	//
	// This member is required.
	AutoMLJobArn *string

	// The name of the object you are requesting.
	//
	// This member is required.
	AutoMLJobName *string

	// The job's secondary status.
	//
	// This member is required.
	AutoMLJobSecondaryStatus AutoMLJobSecondaryStatus

	// The job's status.
	//
	// This member is required.
	AutoMLJobStatus AutoMLJobStatus

	// When the job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// When the job was last modified.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// The end time of an AutoML job.
	EndTime *time.Time

	// The failure reason of a job.
	FailureReason *string
}

Provides a summary about a job.

type AutoMLMetricEnum 

type AutoMLMetricEnum string
const (
	AutoMLMetricEnumAccuracy AutoMLMetricEnum = "Accuracy"
	AutoMLMetricEnumMse      AutoMLMetricEnum = "MSE"
	AutoMLMetricEnumF1       AutoMLMetricEnum = "F1"
	AutoMLMetricEnumF1Macro  AutoMLMetricEnum = "F1macro"
	AutoMLMetricEnumAuc      AutoMLMetricEnum = "AUC"
)

Enum values for AutoMLMetricEnum

func (AutoMLMetricEnum) Values added in v0.29.0 

func (AutoMLMetricEnum) Values() []AutoMLMetricEnum

Values returns all known values for AutoMLMetricEnum. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AutoMLOutputDataConfig 

type AutoMLOutputDataConfig struct {

	// The Amazon S3 output path. Must be 128 characters or less.
	//
	// This member is required.
	S3OutputPath *string

	// The AWS KMS encryption key ID.
	KmsKeyId *string
}

The output data configuration.

type AutoMLS3DataSource 

type AutoMLS3DataSource struct {

	// The data type.
	//
	// This member is required.
	S3DataType AutoMLS3DataType

	// The URL to the Amazon S3 data source.
	//
	// This member is required.
	S3Uri *string
}

The Amazon S3 data source.

type AutoMLS3DataType 

type AutoMLS3DataType string
const (
	AutoMLS3DataTypeManifestFile AutoMLS3DataType = "ManifestFile"
	AutoMLS3DataTypeS3Prefix     AutoMLS3DataType = "S3Prefix"
)

Enum values for AutoMLS3DataType

func (AutoMLS3DataType) Values added in v0.29.0 

func (AutoMLS3DataType) Values() []AutoMLS3DataType

Values returns all known values for AutoMLS3DataType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AutoMLSecurityConfig 

type AutoMLSecurityConfig struct {

	// Whether to use traffic encryption between the container layers.
	EnableInterContainerTrafficEncryption *bool

	// The key used to encrypt stored data.
	VolumeKmsKeyId *string

	// VPC configuration.
	VpcConfig *VpcConfig
}

Security options.

type AutoMLSortBy 

type AutoMLSortBy string
const (
	AutoMLSortByName         AutoMLSortBy = "Name"
	AutoMLSortByCreationTime AutoMLSortBy = "CreationTime"
	AutoMLSortByStatus       AutoMLSortBy = "Status"
)

Enum values for AutoMLSortBy

func (AutoMLSortBy) Values added in v0.29.0 

func (AutoMLSortBy) Values() []AutoMLSortBy

Values returns all known values for AutoMLSortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AutoMLSortOrder 

type AutoMLSortOrder string
const (
	AutoMLSortOrderAscending  AutoMLSortOrder = "Ascending"
	AutoMLSortOrderDescending AutoMLSortOrder = "Descending"
)

Enum values for AutoMLSortOrder

func (AutoMLSortOrder) Values added in v0.29.0 

func (AutoMLSortOrder) Values() []AutoMLSortOrder

Values returns all known values for AutoMLSortOrder. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type AwsManagedHumanLoopRequestSource 

type AwsManagedHumanLoopRequestSource string
const (
	AwsManagedHumanLoopRequestSourceRekognitionDetectModerationLabelsImageV3 AwsManagedHumanLoopRequestSource = "AWS/Rekognition/DetectModerationLabels/Image/V3"
	AwsManagedHumanLoopRequestSourceTextractAnalyzeDocumentFormsV1           AwsManagedHumanLoopRequestSource = "AWS/Textract/AnalyzeDocument/Forms/V1"
)

Enum values for AwsManagedHumanLoopRequestSource

func (AwsManagedHumanLoopRequestSource) Values added in v0.29.0 

func (AwsManagedHumanLoopRequestSource) Values() []AwsManagedHumanLoopRequestSource

Values returns all known values for AwsManagedHumanLoopRequestSource. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type BatchStrategy 

type BatchStrategy string
const (
	BatchStrategyMultiRecord  BatchStrategy = "MultiRecord"
	BatchStrategySingleRecord BatchStrategy = "SingleRecord"
)

Enum values for BatchStrategy

func (BatchStrategy) Values added in v0.29.0 

func (BatchStrategy) Values() []BatchStrategy

Values returns all known values for BatchStrategy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type BooleanOperator 

type BooleanOperator string
const (
	BooleanOperatorAnd BooleanOperator = "And"
	BooleanOperatorOr  BooleanOperator = "Or"
)

Enum values for BooleanOperator

func (BooleanOperator) Values added in v0.29.0 

func (BooleanOperator) Values() []BooleanOperator

Values returns all known values for BooleanOperator. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CandidateSortBy 

type CandidateSortBy string
const (
	CandidateSortByCreationtime              CandidateSortBy = "CreationTime"
	CandidateSortByStatus                    CandidateSortBy = "Status"
	CandidateSortByFinalobjectivemetricvalue CandidateSortBy = "FinalObjectiveMetricValue"
)

Enum values for CandidateSortBy

func (CandidateSortBy) Values added in v0.29.0 

func (CandidateSortBy) Values() []CandidateSortBy

Values returns all known values for CandidateSortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CandidateStatus 

type CandidateStatus string
const (
	CandidateStatusCompleted  CandidateStatus = "Completed"
	CandidateStatusInProgress CandidateStatus = "InProgress"
	CandidateStatusFailed     CandidateStatus = "Failed"
	CandidateStatusStopped    CandidateStatus = "Stopped"
	CandidateStatusStopping   CandidateStatus = "Stopping"
)

Enum values for CandidateStatus

func (CandidateStatus) Values added in v0.29.0 

func (CandidateStatus) Values() []CandidateStatus

Values returns all known values for CandidateStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CandidateStepType 

type CandidateStepType string
const (
	CandidateStepTypeTraining   CandidateStepType = "AWS::SageMaker::TrainingJob"
	CandidateStepTypeTransform  CandidateStepType = "AWS::SageMaker::TransformJob"
	CandidateStepTypeProcessing CandidateStepType = "AWS::SageMaker::ProcessingJob"
)

Enum values for CandidateStepType

func (CandidateStepType) Values added in v0.29.0 

func (CandidateStepType) Values() []CandidateStepType

Values returns all known values for CandidateStepType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CaptureContentTypeHeader 

type CaptureContentTypeHeader struct {

	//
	CsvContentTypes []*string

	//
	JsonContentTypes []*string
}

type CaptureMode 

type CaptureMode string
const (
	CaptureModeInput  CaptureMode = "Input"
	CaptureModeOutput CaptureMode = "Output"
)

Enum values for CaptureMode

func (CaptureMode) Values added in v0.29.0 

func (CaptureMode) Values() []CaptureMode

Values returns all known values for CaptureMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CaptureOption 

type CaptureOption struct {

	//
	//
	// This member is required.
	CaptureMode CaptureMode
}

type CaptureStatus 

type CaptureStatus string
const (
	CaptureStatusStarted CaptureStatus = "Started"
	CaptureStatusStopped CaptureStatus = "Stopped"
)

Enum values for CaptureStatus

func (CaptureStatus) Values added in v0.29.0 

func (CaptureStatus) Values() []CaptureStatus

Values returns all known values for CaptureStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CategoricalParameterRange 

type CategoricalParameterRange struct {

	// The name of the categorical hyperparameter to tune.
	//
	// This member is required.
	Name *string

	// A list of the categories for the hyperparameter.
	//
	// This member is required.
	Values []*string
}

A list of categorical hyperparameters to tune.

type CategoricalParameterRangeSpecification 

type CategoricalParameterRangeSpecification struct {

	// The allowed categories for the hyperparameter.
	//
	// This member is required.
	Values []*string
}

Defines the possible values for a categorical hyperparameter.

type Channel 

type Channel struct {

	// The name of the channel.
	//
	// This member is required.
	ChannelName *string

	// The location of the channel data.
	//
	// This member is required.
	DataSource *DataSource

	// If training data is compressed, the compression type. The default value is None.
	// CompressionType is used only in Pipe input mode. In File mode, leave this field
	// unset or set it to None.
	CompressionType CompressionType

	// The MIME type of the data.
	ContentType *string

	// (Optional) The input mode to use for the data channel in a training job. If you
	// don't set a value for InputMode, Amazon SageMaker uses the value set for
	// TrainingInputMode. Use this parameter to override the TrainingInputMode setting
	// in a AlgorithmSpecification request when you have a channel that needs a
	// different input mode from the training job's general setting. To download the
	// data from Amazon Simple Storage Service (Amazon S3) to the provisioned ML
	// storage volume, and mount the directory to a Docker volume, use File input mode.
	// To stream data directly from Amazon S3 to the container, choose Pipe input mode.
	// To use a model for incremental training, choose File input model.
	InputMode TrainingInputMode

	// 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. For more information, see
	// Create a Dataset Using RecordIO
	// (https://mxnet.apache.org/api/architecture/note_data_loading#data-format). In
	// File mode, leave this field unset or set it to None.
	RecordWrapperType RecordWrapper

	// A configuration for a shuffle option for input data in a channel. If you use
	// S3Prefix for S3DataType, this shuffles the results of the S3 key prefix matches.
	// If you use ManifestFile, the order of the S3 object references in the
	// ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the
	// JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is
	// determined using the Seed value. For Pipe input mode, shuffling is done at the
	// start of every epoch. With large datasets this ensures that the order of the
	// training data is different for each epoch, it helps reduce bias and possible
	// overfitting. In a multi-node training job when ShuffleConfig is combined with
	// S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so
	// that the content sent to a particular node on the first epoch might be sent to a
	// different node on the second epoch.
	ShuffleConfig *ShuffleConfig
}

A channel is a named input source that training algorithms can consume.

type ChannelSpecification 

type ChannelSpecification struct {

	// The name of the channel.
	//
	// This member is required.
	Name *string

	// The supported MIME types for the data.
	//
	// This member is required.
	SupportedContentTypes []*string

	// The allowed input mode, either FILE or PIPE. In FILE mode, Amazon SageMaker
	// copies the data from the input source onto the local Amazon Elastic Block Store
	// (Amazon EBS) volumes before starting your training algorithm. This is the most
	// commonly used input mode. In PIPE mode, Amazon SageMaker streams input data from
	// the source directly to your algorithm without using the EBS volume.
	//
	// This member is required.
	SupportedInputModes []TrainingInputMode

	// A brief description of the channel.
	Description *string

	// Indicates whether the channel is required by the algorithm.
	IsRequired *bool

	// The allowed compression types, if data compression is used.
	SupportedCompressionTypes []CompressionType
}

Defines a named input source, called a channel, to be used by an algorithm.

type CheckpointConfig 

type CheckpointConfig struct {

	// Identifies the S3 path where you want Amazon SageMaker to store checkpoints. For
	// example, s3://bucket-name/key-name-prefix.
	//
	// This member is required.
	S3Uri *string

	// (Optional) The local directory where checkpoints are written. The default
	// directory is /opt/ml/checkpoints/.
	LocalPath *string
}

Contains information about the output location for managed spot training checkpoint data.

type CodeRepositorySortBy 

type CodeRepositorySortBy string
const (
	CodeRepositorySortByName             CodeRepositorySortBy = "Name"
	CodeRepositorySortByCreationTime     CodeRepositorySortBy = "CreationTime"
	CodeRepositorySortByLastModifiedTime CodeRepositorySortBy = "LastModifiedTime"
)

Enum values for CodeRepositorySortBy

func (CodeRepositorySortBy) Values added in v0.29.0 

func (CodeRepositorySortBy) Values() []CodeRepositorySortBy

Values returns all known values for CodeRepositorySortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CodeRepositorySortOrder 

type CodeRepositorySortOrder string
const (
	CodeRepositorySortOrderAscending  CodeRepositorySortOrder = "Ascending"
	CodeRepositorySortOrderDescending CodeRepositorySortOrder = "Descending"
)

Enum values for CodeRepositorySortOrder

func (CodeRepositorySortOrder) Values added in v0.29.0 

func (CodeRepositorySortOrder) Values() []CodeRepositorySortOrder

Values returns all known values for CodeRepositorySortOrder. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CodeRepositorySummary 

type CodeRepositorySummary struct {

	// The Amazon Resource Name (ARN) of the Git repository.
	//
	// This member is required.
	CodeRepositoryArn *string

	// The name of the Git repository.
	//
	// This member is required.
	CodeRepositoryName *string

	// The date and time that the Git repository was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The date and time that the Git repository was last modified.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// Configuration details for the Git repository, including the URL where it is
	// located and the ARN of the AWS Secrets Manager secret that contains the
	// credentials used to access the repository.
	GitConfig *GitConfig
}

Specifies summary information about a Git repository.

type CognitoConfig 

type CognitoConfig struct {

	// The client ID for your Amazon Cognito user pool.
	//
	// This member is required.
	ClientId *string

	// A  user pool
	// (https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html)
	// is a user directory in Amazon Cognito. With a user pool, your users can sign in
	// to your web or mobile app through Amazon Cognito. Your users can also sign in
	// through social identity providers like Google, Facebook, Amazon, or Apple, and
	// through SAML identity providers.
	//
	// This member is required.
	UserPool *string
}

Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool (https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html).

type CognitoMemberDefinition 

type CognitoMemberDefinition struct {

	// An identifier for an application client. You must create the app client ID using
	// Amazon Cognito.
	//
	// This member is required.
	ClientId *string

	// An identifier for a user group.
	//
	// This member is required.
	UserGroup *string

	// An identifier for a user pool. The user pool must be in the same region as the
	// service that you are calling.
	//
	// This member is required.
	UserPool *string
}

Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.

type CollectionConfiguration 

type CollectionConfiguration struct {

	// The name of the tensor collection. The name must be unique relative to other
	// rule configuration names.
	CollectionName *string

	// Parameter values for the tensor collection. The allowed parameters are "name",
	// "include_regex", "reduction_config", "save_config", "tensor_names", and
	// "save_histogram".
	CollectionParameters map[string]*string
}

Configuration information for tensor collections.

type CompilationJobStatus 

type CompilationJobStatus string
const (
	CompilationJobStatusInprogress CompilationJobStatus = "INPROGRESS"
	CompilationJobStatusCompleted  CompilationJobStatus = "COMPLETED"
	CompilationJobStatusFailed     CompilationJobStatus = "FAILED"
	CompilationJobStatusStarting   CompilationJobStatus = "STARTING"
	CompilationJobStatusStopping   CompilationJobStatus = "STOPPING"
	CompilationJobStatusStopped    CompilationJobStatus = "STOPPED"
)

Enum values for CompilationJobStatus

func (CompilationJobStatus) Values added in v0.29.0 

func (CompilationJobStatus) Values() []CompilationJobStatus

Values returns all known values for CompilationJobStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type CompilationJobSummary 

type CompilationJobSummary struct {

	// The Amazon Resource Name (ARN) of the model compilation job.
	//
	// This member is required.
	CompilationJobArn *string

	// The name of the model compilation job that you want a summary for.
	//
	// This member is required.
	CompilationJobName *string

	// The status of the model compilation job.
	//
	// This member is required.
	CompilationJobStatus CompilationJobStatus

	// The time when the model compilation job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The time when the model compilation job completed.
	CompilationEndTime *time.Time

	// The time when the model compilation job started.
	CompilationStartTime *time.Time

	// The type of device that the model will run on after the compilation job has
	// completed.
	CompilationTargetDevice TargetDevice

	// The type of accelerator that the model will run on after the compilation job has
	// completed.
	CompilationTargetPlatformAccelerator TargetPlatformAccelerator

	// The type of architecture that the model will run on after the compilation job
	// has completed.
	CompilationTargetPlatformArch TargetPlatformArch

	// The type of OS that the model will run on after the compilation job has
	// completed.
	CompilationTargetPlatformOs TargetPlatformOs

	// The time when the model compilation job was last modified.
	LastModifiedTime *time.Time
}

A summary of a model compilation job.

type CompressionType 

type CompressionType string
const (
	CompressionTypeNone CompressionType = "None"
	CompressionTypeGzip CompressionType = "Gzip"
)

Enum values for CompressionType

func (CompressionType) Values added in v0.29.0 

func (CompressionType) Values() []CompressionType

Values returns all known values for CompressionType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ConflictException 

type ConflictException struct {
	Message *string
}

There was a conflict when you attempted to modify an experiment, trial, or trial component.

func (*ConflictException) Error 

func (e *ConflictException) Error() string

func (*ConflictException) ErrorCode 

func (e *ConflictException) ErrorCode() string

func (*ConflictException) ErrorFault 

func (e *ConflictException) ErrorFault() smithy.ErrorFault

func (*ConflictException) ErrorMessage 

func (e *ConflictException) ErrorMessage() string

type ContainerDefinition 

type ContainerDefinition struct {

	// 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. For information, see Use Logs and Metrics to Monitor an Inference
	// Pipeline
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/inference-pipeline-logs-metrics.html).
	// If you don't specify a value for this parameter for a ContainerDefinition that
	// is part of an inference pipeline, a unique name is automatically assigned based
	// on the position of the ContainerDefinition in the pipeline. If you specify a
	// value for the ContainerHostName for any ContainerDefinition that is part of an
	// inference pipeline, you must specify a value for the ContainerHostName parameter
	// of every ContainerDefinition in that pipeline.
	ContainerHostname *string

	// The environment variables to set in the Docker container. Each key and value in
	// the Environment string to string map can have length of up to 1024. We support
	// up to 16 entries in the map.
	Environment map[string]*string

	// The path where inference code is stored. This can be either in Amazon EC2
	// Container Registry or in a Docker registry that is accessible from the same VPC
	// that you configure for your endpoint. If you are using your own custom algorithm
	// instead of an algorithm provided by Amazon SageMaker, the inference code must
	// meet Amazon SageMaker requirements. Amazon SageMaker supports both
	// registry/repository[:tag] and registry/repository[@digest] image path formats.
	// For more information, see Using Your Own Algorithms with Amazon SageMaker
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html)
	Image *string

	// Specifies whether the model container is in Amazon ECR or a private Docker
	// registry accessible from your Amazon Virtual Private Cloud (VPC). For
	// information about storing containers in a private Docker registry, see Use a
	// Private Docker Registry for Real-Time Inference Containers
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-containers-inference-private.html)
	ImageConfig *ImageConfig

	// Whether the container hosts a single model or multiple models.
	Mode ContainerMode

	// 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. For more information on built-in algorithms,
	// see Common Parameters
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html).
	// The model artifacts must be in an S3 bucket that is in the same region as the
	// model or endpoint you are creating. If you provide a value for this parameter,
	// Amazon SageMaker uses AWS Security Token Service to download model artifacts
	// from the S3 path you provide. AWS STS is activated in your IAM user account by
	// default. If you previously deactivated AWS STS for a region, you need to
	// reactivate AWS STS for that region. For more information, see Activating and
	// Deactivating AWS STS in an AWS Region
	// (https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html)
	// in the AWS Identity and Access Management User Guide. If you use a built-in
	// algorithm to create a model, Amazon SageMaker requires that you provide a S3
	// path to the model artifacts in ModelDataUrl.
	ModelDataUrl *string

	// The name or Amazon Resource Name (ARN) of the model package to use to create the
	// model.
	ModelPackageName *string
}

Describes the container, as part of model definition.

type ContainerMode 

type ContainerMode string
const (
	ContainerModeSingleModel ContainerMode = "SingleModel"
	ContainerModeMultiModel  ContainerMode = "MultiModel"
)

Enum values for ContainerMode

func (ContainerMode) Values added in v0.29.0 

func (ContainerMode) Values() []ContainerMode

Values returns all known values for ContainerMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ContentClassifier 

type ContentClassifier string
const (
	ContentClassifierFreeOfPersonallyIdentifiableInformation ContentClassifier = "FreeOfPersonallyIdentifiableInformation"
	ContentClassifierFreeOfAdultContent                      ContentClassifier = "FreeOfAdultContent"
)

Enum values for ContentClassifier

func (ContentClassifier) Values added in v0.29.0 

func (ContentClassifier) Values() []ContentClassifier

Values returns all known values for ContentClassifier. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ContinuousParameterRange 

type ContinuousParameterRange struct {

	// The maximum value for the hyperparameter. The tuning job uses floating-point
	// values between MinValue value and this value for tuning.
	//
	// This member is required.
	MaxValue *string

	// The minimum value for the hyperparameter. The tuning job uses floating-point
	// values between this value and MaxValuefor tuning.
	//
	// This member is required.
	MinValue *string

	// The name of the continuous hyperparameter to tune.
	//
	// This member is required.
	Name *string

	// The scale that hyperparameter tuning uses to search the hyperparameter range.
	// For information about choosing a hyperparameter scale, see Hyperparameter
	// Scaling
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-type).
	// One of the following values: Auto Amazon SageMaker hyperparameter tuning chooses
	// the best scale for the hyperparameter. Linear Hyperparameter tuning searches the
	// values in the hyperparameter range by using a linear scale. Logarithmic
	// Hyperparameter tuning searches the values in the hyperparameter range by using a
	// logarithmic scale. Logarithmic scaling works only for ranges that have only
	// values greater than 0. ReverseLogarithmic Hyperparameter tuning searches the
	// values in the hyperparameter range by using a reverse logarithmic scale. Reverse
	// logarithmic scaling works only for ranges that are entirely within the range
	// 0<=x<1.0.
	ScalingType HyperParameterScalingType
}

A list of continuous hyperparameters to tune.

type ContinuousParameterRangeSpecification 

type ContinuousParameterRangeSpecification struct {

	// The maximum floating-point value allowed.
	//
	// This member is required.
	MaxValue *string

	// The minimum floating-point value allowed.
	//
	// This member is required.
	MinValue *string
}

Defines the possible values for a continuous hyperparameter.

type CustomImage added in v0.29.0 

type CustomImage struct {

	// The name of the AppImageConfig.
	//
	// This member is required.
	AppImageConfigName *string

	// The name of the CustomImage. Must be unique to your account.
	//
	// This member is required.
	ImageName *string

	// The version number of the CustomImage.
	ImageVersionNumber *int32
}

A custom image.

type DataCaptureConfig 

type DataCaptureConfig struct {

	//
	//
	// This member is required.
	CaptureOptions []*CaptureOption

	//
	//
	// This member is required.
	DestinationS3Uri *string

	//
	//
	// This member is required.
	InitialSamplingPercentage *int32

	//
	CaptureContentTypeHeader *CaptureContentTypeHeader

	//
	EnableCapture *bool

	//
	KmsKeyId *string
}

type DataCaptureConfigSummary 

type DataCaptureConfigSummary struct {

	//
	//
	// This member is required.
	CaptureStatus CaptureStatus

	//
	//
	// This member is required.
	CurrentSamplingPercentage *int32

	//
	//
	// This member is required.
	DestinationS3Uri *string

	//
	//
	// This member is required.
	EnableCapture *bool

	//
	//
	// This member is required.
	KmsKeyId *string
}

type DataProcessing 

type DataProcessing struct {

	// A JSONPath
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators)
	// expression used to select a portion of the input data to pass to the algorithm.
	// Use the InputFilter parameter to exclude fields, such as an ID column, from the
	// input. If you want Amazon SageMaker to pass the entire input dataset to the
	// algorithm, accept the default value $. Examples: "$", "$[1:]", "$.features"
	InputFilter *string

	// Specifies the source of the data to join with the transformed data. The valid
	// values are None and Input. The default value is None, which specifies not to
	// join the input with the transformed data. If you want the batch transform job to
	// join the original input data with the transformed data, set JoinSource to Input.
	// For JSON or JSONLines objects, such as a JSON array, Amazon SageMaker adds the
	// transformed data to the input JSON object in an attribute called
	// SageMakerOutput. The joined result for JSON must be a key-value pair object. If
	// the input is not a key-value pair object, Amazon SageMaker creates a new JSON
	// file. In the new JSON file, and the input data is stored under the
	// SageMakerInput key and the results are stored in SageMakerOutput. For CSV files,
	// Amazon SageMaker combines the transformed data with the input data at the end of
	// the input data and stores it in the output file. The joined data has the joined
	// input data followed by the transformed data and the output is a CSV file.
	JoinSource JoinSource

	// A JSONPath
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators)
	// expression used to select a portion of the joined dataset to save in the output
	// file for a batch transform job. If you want Amazon SageMaker to store the entire
	// input dataset in the output file, leave the default value, $. If you specify
	// indexes that aren't within the dimension size of the joined dataset, you get an
	// error. Examples: "$", "$[0,5:]", "$['id','SageMakerOutput']"
	OutputFilter *string
}

The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see Associate Prediction Results with their Corresponding Input Records (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html).

type DataSource 

type DataSource struct {

	// The file system that is associated with a channel.
	FileSystemDataSource *FileSystemDataSource

	// The S3 location of the data source that is associated with a channel.
	S3DataSource *S3DataSource
}

Describes the location of the channel data.

type DebugHookConfig 

type DebugHookConfig struct {

	// Path to Amazon S3 storage location for tensors.
	//
	// This member is required.
	S3OutputPath *string

	// Configuration information for tensor collections.
	CollectionConfigurations []*CollectionConfiguration

	// Configuration information for the debug hook parameters.
	HookParameters map[string]*string

	// Path to local storage location for tensors. Defaults to /opt/ml/output/tensors/.
	LocalPath *string
}

Configuration information for the debug hook parameters, collection configuration, and storage paths.

type DebugRuleConfiguration 

type DebugRuleConfiguration struct {

	// The name of the rule configuration. It must be unique relative to other rule
	// configuration names.
	//
	// This member is required.
	RuleConfigurationName *string

	// The Amazon Elastic Container (ECR) Image for the managed rule evaluation.
	//
	// This member is required.
	RuleEvaluatorImage *string

	// The instance type to deploy for a training job.
	InstanceType ProcessingInstanceType

	// Path to local storage location for output of rules. Defaults to
	// /opt/ml/processing/output/rule/.
	LocalPath *string

	// Runtime configuration for rule container.
	RuleParameters map[string]*string

	// Path to Amazon S3 storage location for rules.
	S3OutputPath *string

	// The size, in GB, of the ML storage volume attached to the processing instance.
	VolumeSizeInGB *int32
}

Configuration information for debugging rules.

type DebugRuleEvaluationStatus 

type DebugRuleEvaluationStatus struct {

	// Timestamp when the rule evaluation status was last modified.
	LastModifiedTime *time.Time

	// The name of the rule configuration
	RuleConfigurationName *string

	// The Amazon Resource Name (ARN) of the rule evaluation job.
	RuleEvaluationJobArn *string

	// Status of the rule evaluation.
	RuleEvaluationStatus RuleEvaluationStatus

	// Details from the rule evaluation.
	StatusDetails *string
}

Information about the status of the rule evaluation.

type DeployedImage 

type DeployedImage struct {

	// The date and time when the image path for the model resolved to the
	// ResolvedImage
	ResolutionTime *time.Time

	// The specific digest path of the image hosted in this ProductionVariant.
	ResolvedImage *string

	// The image path you specified when you created the model.
	SpecifiedImage *string
}

Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant. If you used the registry/repository[:tag] form to specify the image path of the primary container when you created the model hosted in this ProductionVariant, the path resolves to a path of the form registry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image (https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-pull-ecr-image.html) in the Amazon ECR User Guide.

type DesiredWeightAndCapacity 

type DesiredWeightAndCapacity struct {

	// The name of the variant to update.
	//
	// This member is required.
	VariantName *string

	// The variant's capacity.
	DesiredInstanceCount *int32

	// The variant's weight.
	DesiredWeight *float32
}

Specifies weight and capacity values for a production variant.

type DetailedAlgorithmStatus 

type DetailedAlgorithmStatus string
const (
	DetailedAlgorithmStatusNotStarted DetailedAlgorithmStatus = "NotStarted"
	DetailedAlgorithmStatusInProgress DetailedAlgorithmStatus = "InProgress"
	DetailedAlgorithmStatusCompleted  DetailedAlgorithmStatus = "Completed"
	DetailedAlgorithmStatusFailed     DetailedAlgorithmStatus = "Failed"
)

Enum values for DetailedAlgorithmStatus

func (DetailedAlgorithmStatus) Values added in v0.29.0 

func (DetailedAlgorithmStatus) Values() []DetailedAlgorithmStatus

Values returns all known values for DetailedAlgorithmStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type DetailedModelPackageStatus 

type DetailedModelPackageStatus string
const (
	DetailedModelPackageStatusNotStarted DetailedModelPackageStatus = "NotStarted"
	DetailedModelPackageStatusInProgress DetailedModelPackageStatus = "InProgress"
	DetailedModelPackageStatusCompleted  DetailedModelPackageStatus = "Completed"
	DetailedModelPackageStatusFailed     DetailedModelPackageStatus = "Failed"
)

Enum values for DetailedModelPackageStatus

func (DetailedModelPackageStatus) Values added in v0.29.0 

func (DetailedModelPackageStatus) Values() []DetailedModelPackageStatus

Values returns all known values for DetailedModelPackageStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type DirectInternetAccess 

type DirectInternetAccess string
const (
	DirectInternetAccessEnabled  DirectInternetAccess = "Enabled"
	DirectInternetAccessDisabled DirectInternetAccess = "Disabled"
)

Enum values for DirectInternetAccess

func (DirectInternetAccess) Values added in v0.29.0 

func (DirectInternetAccess) Values() []DirectInternetAccess

Values returns all known values for DirectInternetAccess. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type DomainDetails 

type DomainDetails struct {

	// The creation time.
	CreationTime *time.Time

	// The domain's Amazon Resource Name (ARN).
	DomainArn *string

	// The domain ID.
	DomainId *string

	// The domain name.
	DomainName *string

	// The last modified time.
	LastModifiedTime *time.Time

	// The status.
	Status DomainStatus

	// The domain's URL.
	Url *string
}

The domain's details.

type DomainStatus 

type DomainStatus string
const (
	DomainStatusDeleting     DomainStatus = "Deleting"
	DomainStatusFailed       DomainStatus = "Failed"
	DomainStatusInservice    DomainStatus = "InService"
	DomainStatusPending      DomainStatus = "Pending"
	DomainStatusUpdating     DomainStatus = "Updating"
	DomainStatusUpdateFailed DomainStatus = "Update_Failed"
	DomainStatusDeleteFailed DomainStatus = "Delete_Failed"
)

Enum values for DomainStatus

func (DomainStatus) Values added in v0.29.0 

func (DomainStatus) Values() []DomainStatus

Values returns all known values for DomainStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type EndpointConfigSortKey 

type EndpointConfigSortKey string
const (
	EndpointConfigSortKeyName         EndpointConfigSortKey = "Name"
	EndpointConfigSortKeyCreationtime EndpointConfigSortKey = "CreationTime"
)

Enum values for EndpointConfigSortKey

func (EndpointConfigSortKey) Values added in v0.29.0 

func (EndpointConfigSortKey) Values() []EndpointConfigSortKey

Values returns all known values for EndpointConfigSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type EndpointConfigSummary 

type EndpointConfigSummary struct {

	// A timestamp that shows when the endpoint configuration was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the endpoint configuration.
	//
	// This member is required.
	EndpointConfigArn *string

	// The name of the endpoint configuration.
	//
	// This member is required.
	EndpointConfigName *string
}

Provides summary information for an endpoint configuration.

type EndpointInput 

type EndpointInput struct {

	// An endpoint in customer's account which has enabled DataCaptureConfig enabled.
	//
	// This member is required.
	EndpointName *string

	// Path to the filesystem where the endpoint data is available to the container.
	//
	// This member is required.
	LocalPath *string

	// Whether input data distributed in Amazon S3 is fully replicated or sharded by an
	// S3 key. Defauts to FullyReplicated
	S3DataDistributionType ProcessingS3DataDistributionType

	// Whether the Pipe or File is used as the input mode for transfering data for the
	// monitoring job. Pipe mode is recommended for large datasets. File mode is useful
	// for small files that fit in memory. Defaults to File.
	S3InputMode ProcessingS3InputMode
}

Input object for the endpoint

type EndpointSortKey 

type EndpointSortKey string
const (
	EndpointSortKeyName         EndpointSortKey = "Name"
	EndpointSortKeyCreationtime EndpointSortKey = "CreationTime"
	EndpointSortKeyStatus       EndpointSortKey = "Status"
)

Enum values for EndpointSortKey

func (EndpointSortKey) Values added in v0.29.0 

func (EndpointSortKey) Values() []EndpointSortKey

Values returns all known values for EndpointSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type EndpointStatus 

type EndpointStatus string
const (
	EndpointStatusOutOfService   EndpointStatus = "OutOfService"
	EndpointStatusCreating       EndpointStatus = "Creating"
	EndpointStatusUpdating       EndpointStatus = "Updating"
	EndpointStatusSystemUpdating EndpointStatus = "SystemUpdating"
	EndpointStatusRollingBack    EndpointStatus = "RollingBack"
	EndpointStatusInService      EndpointStatus = "InService"
	EndpointStatusDeleting       EndpointStatus = "Deleting"
	EndpointStatusFailed         EndpointStatus = "Failed"
)

Enum values for EndpointStatus

func (EndpointStatus) Values added in v0.29.0 

func (EndpointStatus) Values() []EndpointStatus

Values returns all known values for EndpointStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type EndpointSummary 

type EndpointSummary struct {

	// A timestamp that shows when the endpoint was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the endpoint.
	//
	// This member is required.
	EndpointArn *string

	// The name of the endpoint.
	//
	// This member is required.
	EndpointName *string

	// The status of the endpoint.
	//
	// * OutOfService: Endpoint is not available to take
	// incoming requests.
	//
	// * Creating: CreateEndpoint is executing.
	//
	// * Updating:
	// UpdateEndpoint or UpdateEndpointWeightsAndCapacities is executing.
	//
	// *
	// SystemUpdating: Endpoint is undergoing maintenance and cannot be updated or
	// deleted or re-scaled until it has completed. This maintenance operation does not
	// change any customer-specified values such as VPC config, KMS encryption, model,
	// instance type, or instance count.
	//
	// * RollingBack: Endpoint fails to scale up or
	// down or change its variant weight and is in the process of rolling back to its
	// previous configuration. Once the rollback completes, endpoint returns to an
	// InService status. This transitional status only applies to an endpoint that has
	// autoscaling enabled and is undergoing variant weight or capacity changes as part
	// of an UpdateEndpointWeightsAndCapacities call or when the
	// UpdateEndpointWeightsAndCapacities operation is called explicitly.
	//
	// * InService:
	// Endpoint is available to process incoming requests.
	//
	// * Deleting: DeleteEndpoint
	// is executing.
	//
	// * Failed: Endpoint could not be created, updated, or re-scaled.
	// Use DescribeEndpointOutput$FailureReason for information about the failure.
	// DeleteEndpoint is the only operation that can be performed on a failed
	// endpoint.
	//
	// To get a list of endpoints with a specified status, use the
	// ListEndpointsInput$StatusEquals filter.
	//
	// This member is required.
	EndpointStatus EndpointStatus

	// A timestamp that shows when the endpoint was last modified.
	//
	// This member is required.
	LastModifiedTime *time.Time
}

Provides summary information for an endpoint.

type ExecutionStatus 

type ExecutionStatus string
const (
	ExecutionStatusPending                 ExecutionStatus = "Pending"
	ExecutionStatusCompleted               ExecutionStatus = "Completed"
	ExecutionStatusCompletedWithViolations ExecutionStatus = "CompletedWithViolations"
	ExecutionStatusInProgress              ExecutionStatus = "InProgress"
	ExecutionStatusFailed                  ExecutionStatus = "Failed"
	ExecutionStatusStopping                ExecutionStatus = "Stopping"
	ExecutionStatusStopped                 ExecutionStatus = "Stopped"
)

Enum values for ExecutionStatus

func (ExecutionStatus) Values added in v0.29.0 

func (ExecutionStatus) Values() []ExecutionStatus

Values returns all known values for ExecutionStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type Experiment 

type Experiment struct {

	// Information about the user who created or modified an experiment, trial, or
	// trial component.
	CreatedBy *UserContext

	// When the experiment was created.
	CreationTime *time.Time

	// The description of the experiment.
	Description *string

	// The name of the experiment as displayed. If DisplayName isn't specified,
	// ExperimentName is displayed.
	DisplayName *string

	// The Amazon Resource Name (ARN) of the experiment.
	ExperimentArn *string

	// The name of the experiment.
	ExperimentName *string

	// Information about the user who created or modified an experiment, trial, or
	// trial component.
	LastModifiedBy *UserContext

	// When the experiment was last modified.
	LastModifiedTime *time.Time

	// The source of the experiment.
	Source *ExperimentSource

	// The list of tags that are associated with the experiment. You can use Search API
	// to search on the tags.
	Tags []*Tag
}

The properties of an experiment as returned by the Search API.

type ExperimentConfig 

type ExperimentConfig struct {

	// The name of an existing experiment to associate the trial component with.
	ExperimentName *string

	// The display name for the trial component. If this key isn't specified, the
	// display name is the trial component name.
	TrialComponentDisplayName *string

	// The name of an existing trial to associate the trial component with. If not
	// specified, a new trial is created.
	TrialName *string
}

Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:

* CreateProcessingJob

* CreateTrainingJob

* CreateTransformJob

type ExperimentSource 

type ExperimentSource struct {

	// The Amazon Resource Name (ARN) of the source.
	//
	// This member is required.
	SourceArn *string

	// The source type.
	SourceType *string
}

The source of the experiment.

type ExperimentSummary 

type ExperimentSummary struct {

	// When the experiment was created.
	CreationTime *time.Time

	// The name of the experiment as displayed. If DisplayName isn't specified,
	// ExperimentName is displayed.
	DisplayName *string

	// The Amazon Resource Name (ARN) of the experiment.
	ExperimentArn *string

	// The name of the experiment.
	ExperimentName *string

	// The source of the experiment.
	ExperimentSource *ExperimentSource

	// When the experiment was last modified.
	LastModifiedTime *time.Time
}

A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName.

type FileSystemAccessMode 

type FileSystemAccessMode string
const (
	FileSystemAccessModeRw FileSystemAccessMode = "rw"
	FileSystemAccessModeRo FileSystemAccessMode = "ro"
)

Enum values for FileSystemAccessMode

func (FileSystemAccessMode) Values added in v0.29.0 

func (FileSystemAccessMode) Values() []FileSystemAccessMode

Values returns all known values for FileSystemAccessMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type FileSystemConfig added in v0.29.0 

type FileSystemConfig struct {

	// The default POSIX group ID. If not specified, defaults to 100.
	DefaultGid *int32

	// The default POSIX user ID. If not specified, defaults to 1000.
	DefaultUid *int32

	// The path within the image to mount the user's EFS home directory. The directory
	// should be empty. If not specified, defaults to /home/sagemaker-user.
	MountPath *string
}

The Amazon Elastic File System (EFS) storage configuration for an image.

type FileSystemDataSource 

type FileSystemDataSource struct {

	// The full path to the directory to associate with the channel.
	//
	// This member is required.
	DirectoryPath *string

	// The access mode of the mount of the directory associated with the channel. A
	// directory can be mounted either in ro (read-only) or rw (read-write) mode.
	//
	// This member is required.
	FileSystemAccessMode FileSystemAccessMode

	// The file system id.
	//
	// This member is required.
	FileSystemId *string

	// The file system type.
	//
	// This member is required.
	FileSystemType FileSystemType
}

Specifies a file system data source for a channel.

type FileSystemType 

type FileSystemType string
const (
	FileSystemTypeEfs       FileSystemType = "EFS"
	FileSystemTypeFsxlustre FileSystemType = "FSxLustre"
)

Enum values for FileSystemType

func (FileSystemType) Values added in v0.29.0 

func (FileSystemType) Values() []FileSystemType

Values returns all known values for FileSystemType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type Filter 

type Filter struct {

	// A resource property name. For example, TrainingJobName. For valid property
	// names, see SearchRecord. You must specify a valid property for the resource.
	//
	// This member is required.
	Name *string

	// A Boolean binary operator that is used to evaluate the filter. The operator
	// field contains one of the following values: Equals The value of Name equals
	// Value. NotEquals The value of Name doesn't equal Value. Exists The Name property
	// exists. NotExists The Name property does not exist. GreaterThan The value of
	// Name is greater than Value. Not supported for text properties.
	// GreaterThanOrEqualTo The value of Name is greater than or equal to Value. Not
	// supported for text properties. LessThan The value of Name is less than Value.
	// Not supported for text properties. LessThanOrEqualTo The value of Name is less
	// than or equal to Value. Not supported for text properties. In The value of Name
	// is one of the comma delimited strings in Value. Only supported for text
	// properties. Contains The value of Name contains the string Value. Only supported
	// for text properties. A SearchExpression can include the Contains operator
	// multiple times when the value of Name is one of the following:
	//
	// *
	// Experiment.DisplayName
	//
	// * Experiment.ExperimentName
	//
	// * Experiment.Tags
	//
	// *
	// Trial.DisplayName
	//
	// * Trial.TrialName
	//
	// * Trial.Tags
	//
	// *
	// TrialComponent.DisplayName
	//
	// * TrialComponent.TrialComponentName
	//
	// *
	// TrialComponent.Tags
	//
	// * TrialComponent.InputArtifacts
	//
	// *
	// TrialComponent.OutputArtifacts
	//
	// A SearchExpression can include only one Contains
	// operator for all other values of Name. In these cases, if you include multiple
	// Contains operators in the SearchExpression, the result is the following error
	// message: "'CONTAINS' operator usage limit of 1 exceeded."
	Operator Operator

	// A value used with Name and Operator to determine which resources satisfy the
	// filter's condition. For numerical properties, Value must be an integer or
	// floating-point decimal. For timestamp properties, Value must be an ISO 8601
	// date-time string of the following format: YYYY-mm-dd'T'HH:MM:SS.
	Value *string
}

A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API. If you specify a Value, but not an Operator, Amazon SageMaker uses the equals operator. In search, there are several property types: Metrics To define a metric filter, enter a value using the form "Metrics.", where is a metric name. For example, the following filter searches for training jobs with an "accuracy" metric greater than "0.9": {

"Name": "Metrics.accuracy", 

"Operator": "GreaterThan",

"Value":

"0.9"

} HyperParameters To define a hyperparameter filter, enter a value with the form "HyperParameters.". Decimal hyperparameter values are treated as a decimal in a comparison if the specified Value is also a decimal value. If the specified Value is an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a 

"learning_rate" hyperparameter that is less than "0.5":  {
    "Name":

"HyperParameters.learning_rate", 

"Operator": "LessThan",

"Value":

"0.5"

} Tags To define a tag filter, enter a value with the form Tags..

type FinalAutoMLJobObjectiveMetric 

type FinalAutoMLJobObjectiveMetric struct {

	// The name of the metric with the best result. For a description of the possible
	// objective metrics, see AutoMLJobObjective$MetricName.
	//
	// This member is required.
	MetricName AutoMLMetricEnum

	// The value of the metric with the best result.
	//
	// This member is required.
	Value *float32

	// The type of metric with the best result.
	Type AutoMLJobObjectiveType
}

The best candidate result from an AutoML training job.

type FinalHyperParameterTuningJobObjectiveMetric 

type FinalHyperParameterTuningJobObjectiveMetric struct {

	// The name of the objective metric.
	//
	// This member is required.
	MetricName *string

	// The value of the objective metric.
	//
	// This member is required.
	Value *float32

	// Whether to minimize or maximize the objective metric. Valid values are Minimize
	// and Maximize.
	Type HyperParameterTuningJobObjectiveType
}

Shows the final value for the objective metric for a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.

type FlowDefinitionOutputConfig 

type FlowDefinitionOutputConfig struct {

	// The Amazon S3 path where the object containing human output will be made
	// available.
	//
	// This member is required.
	S3OutputPath *string

	// The Amazon Key Management Service (KMS) key ID for server-side encryption.
	KmsKeyId *string
}

Contains information about where human output will be stored.

type FlowDefinitionStatus 

type FlowDefinitionStatus string
const (
	FlowDefinitionStatusInitializing FlowDefinitionStatus = "Initializing"
	FlowDefinitionStatusActive       FlowDefinitionStatus = "Active"
	FlowDefinitionStatusFailed       FlowDefinitionStatus = "Failed"
	FlowDefinitionStatusDeleting     FlowDefinitionStatus = "Deleting"
)

Enum values for FlowDefinitionStatus

func (FlowDefinitionStatus) Values added in v0.29.0 

func (FlowDefinitionStatus) Values() []FlowDefinitionStatus

Values returns all known values for FlowDefinitionStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type FlowDefinitionSummary 

type FlowDefinitionSummary struct {

	// The timestamp when SageMaker created the flow definition.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the flow definition.
	//
	// This member is required.
	FlowDefinitionArn *string

	// The name of the flow definition.
	//
	// This member is required.
	FlowDefinitionName *string

	// The status of the flow definition. Valid values:
	//
	// This member is required.
	FlowDefinitionStatus FlowDefinitionStatus

	// The reason why the flow definition creation failed. A failure reason is returned
	// only when the flow definition status is Failed.
	FailureReason *string
}

Contains summary information about the flow definition.

type Framework 

type Framework string
const (
	FrameworkTensorflow Framework = "TENSORFLOW"
	FrameworkKeras      Framework = "KERAS"
	FrameworkMxnet      Framework = "MXNET"
	FrameworkOnnx       Framework = "ONNX"
	FrameworkPytorch    Framework = "PYTORCH"
	FrameworkXgboost    Framework = "XGBOOST"
	FrameworkTflite     Framework = "TFLITE"
	FrameworkDarknet    Framework = "DARKNET"
)

Enum values for Framework

func (Framework) Values added in v0.29.0 

func (Framework) Values() []Framework

Values returns all known values for Framework. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type GitConfig 

type GitConfig struct {

	// The URL where the Git repository is located.
	//
	// This member is required.
	RepositoryUrl *string

	// The default branch for the Git repository.
	Branch *string

	// The Amazon Resource Name (ARN) of the AWS Secrets Manager secret that contains
	// the credentials used to access the git repository. The secret must have a
	// staging label of AWSCURRENT and must be in the following format: {"username":
	// UserName, "password": Password}
	SecretArn *string
}

Specifies configuration details for a Git repository in your AWS account.

type GitConfigForUpdate 

type GitConfigForUpdate struct {

	// The Amazon Resource Name (ARN) of the AWS Secrets Manager secret that contains
	// the credentials used to access the git repository. The secret must have a
	// staging label of AWSCURRENT and must be in the following format: {"username":
	// UserName, "password": Password}
	SecretArn *string
}

Specifies configuration details for a Git repository when the repository is updated.

type HumanLoopActivationConditionsConfig 

type HumanLoopActivationConditionsConfig struct {

	// JSON expressing use-case specific conditions declaratively. If any condition is
	// matched, atomic tasks are created against the configured work team. The set of
	// conditions is different for Rekognition and Textract. For more information about
	// how to structure the JSON, see JSON Schema for Human Loop Activation Conditions
	// in Amazon Augmented AI
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-human-fallback-conditions-json-schema.html)
	// in the Amazon SageMaker Developer Guide.
	// This value conforms to the media type: application/json
	//
	// This member is required.
	HumanLoopActivationConditions *string
}

Defines under what conditions SageMaker creates a human loop. Used within . See for the required format of activation conditions.

type HumanLoopActivationConfig 

type HumanLoopActivationConfig struct {

	// Container structure for defining under what conditions SageMaker creates a human
	// loop.
	//
	// This member is required.
	HumanLoopActivationConditionsConfig *HumanLoopActivationConditionsConfig
}

Provides information about how and under what conditions SageMaker creates a human loop. If HumanLoopActivationConfig is not given, then all requests go to humans.

type HumanLoopConfig 

type HumanLoopConfig struct {

	// The Amazon Resource Name (ARN) of the human task user interface.
	//
	// This member is required.
	HumanTaskUiArn *string

	// The number of distinct workers who will perform the same task on each object.
	// For example, if TaskCount is set to 3 for an image classification labeling job,
	// three workers will classify each input image. Increasing TaskCount can improve
	// label accuracy.
	//
	// This member is required.
	TaskCount *int32

	// A description for the human worker task.
	//
	// This member is required.
	TaskDescription *string

	// A title for the human worker task.
	//
	// This member is required.
	TaskTitle *string

	// Amazon Resource Name (ARN) of a team of workers.
	//
	// This member is required.
	WorkteamArn *string

	// Defines the amount of money paid to an Amazon Mechanical Turk worker for each
	// task performed. Use one of the following prices for bounding box tasks. Prices
	// are in US dollars and should be based on the complexity of the task; the longer
	// it takes in your initial testing, the more you should offer.
	//
	// * 0.036
	//
	// *
	// 0.048
	//
	// * 0.060
	//
	// * 0.072
	//
	// * 0.120
	//
	// * 0.240
	//
	// * 0.360
	//
	// * 0.480
	//
	// * 0.600
	//
	// * 0.720
	//
	// *
	// 0.840
	//
	// * 0.960
	//
	// * 1.080
	//
	// * 1.200
	//
	// Use one of the following prices for image
	// classification, text classification, and custom tasks. Prices are in US
	// dollars.
	//
	// * 0.012
	//
	// * 0.024
	//
	// * 0.036
	//
	// * 0.048
	//
	// * 0.060
	//
	// * 0.072
	//
	// * 0.120
	//
	// *
	// 0.240
	//
	// * 0.360
	//
	// * 0.480
	//
	// * 0.600
	//
	// * 0.720
	//
	// * 0.840
	//
	// * 0.960
	//
	// * 1.080
	//
	// *
	// 1.200
	//
	// Use one of the following prices for semantic segmentation tasks. Prices
	// are in US dollars.
	//
	// * 0.840
	//
	// * 0.960
	//
	// * 1.080
	//
	// * 1.200
	//
	// Use one of the following
	// prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI
	// review tasks. Prices are in US dollars.
	//
	// * 2.400
	//
	// * 2.280
	//
	// * 2.160
	//
	// * 2.040
	//
	// *
	// 1.920
	//
	// * 1.800
	//
	// * 1.680
	//
	// * 1.560
	//
	// * 1.440
	//
	// * 1.320
	//
	// * 1.200
	//
	// * 1.080
	//
	// * 0.960
	//
	// *
	// 0.840
	//
	// * 0.720
	//
	// * 0.600
	//
	// * 0.480
	//
	// * 0.360
	//
	// * 0.240
	//
	// * 0.120
	//
	// * 0.072
	//
	// * 0.060
	//
	// *
	// 0.048
	//
	// * 0.036
	//
	// * 0.024
	//
	// * 0.012
	//
	// Use one of the following prices for
	// Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are
	// in US dollars.
	//
	// * 1.200
	//
	// * 1.080
	//
	// * 0.960
	//
	// * 0.840
	//
	// * 0.720
	//
	// * 0.600
	//
	// * 0.480
	//
	// *
	// 0.360
	//
	// * 0.240
	//
	// * 0.120
	//
	// * 0.072
	//
	// * 0.060
	//
	// * 0.048
	//
	// * 0.036
	//
	// * 0.024
	//
	// *
	// 0.012
	//
	// Use one of the following prices for Amazon Augmented AI custom human
	// review tasks. Prices are in US dollars.
	//
	// * 1.200
	//
	// * 1.080
	//
	// * 0.960
	//
	// * 0.840
	//
	// *
	// 0.720
	//
	// * 0.600
	//
	// * 0.480
	//
	// * 0.360
	//
	// * 0.240
	//
	// * 0.120
	//
	// * 0.072
	//
	// * 0.060
	//
	// * 0.048
	//
	// *
	// 0.036
	//
	// * 0.024
	//
	// * 0.012
	PublicWorkforceTaskPrice *PublicWorkforceTaskPrice

	// The length of time that a task remains available for review by human workers.
	TaskAvailabilityLifetimeInSeconds *int32

	// Keywords used to describe the task so that workers can discover the task.
	TaskKeywords []*string

	// The amount of time that a worker has to complete a task. The default value is
	// 3,600 seconds (1 hour)
	TaskTimeLimitInSeconds *int32
}

Describes the work to be performed by human workers.

type HumanLoopRequestSource 

type HumanLoopRequestSource struct {

	// Specifies whether Amazon Rekognition or Amazon Textract are used as the
	// integration source. The default field settings and JSON parsing rules are
	// different based on the integration source. Valid values:
	//
	// This member is required.
	AwsManagedHumanLoopRequestSource AwsManagedHumanLoopRequestSource
}

Container for configuring the source of human task requests.

type HumanTaskConfig 

type HumanTaskConfig struct {

	// Configures how labels are consolidated across human workers.
	//
	// This member is required.
	AnnotationConsolidationConfig *AnnotationConsolidationConfig

	// The number of human workers that will label an object.
	//
	// This member is required.
	NumberOfHumanWorkersPerDataObject *int32

	// The Amazon Resource Name (ARN) of a Lambda function that is run before a data
	// object is sent to a human worker. Use this function to provide input to a custom
	// labeling job. For built-in task types
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html), use one
	// of the following Amazon SageMaker Ground Truth Lambda function ARNs for
	// PreHumanTaskLambdaArn. For custom labeling workflows, see Pre-annotation Lambda
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-prelambda).
	// Bounding box - Finds the most similar boxes from different workers based on the
	// Jaccard index of the boxes.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox
	//
	// Image
	// classification - Uses a variant of the Expectation Maximization approach to
	// estimate the true class of an image based on annotations from individual
	// workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass
	//
	// Multi-label
	// image classification - Uses a variant of the Expectation Maximization approach
	// to estimate the true classes of an image based on annotations from individual
	// workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel
	//
	// Semantic
	// segmentation - Treats each pixel in an image as a multi-class classification and
	// treats pixel annotations from workers as "votes" for the correct label.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation
	//
	// Text
	// classification - Uses a variant of the Expectation Maximization approach to
	// estimate the true class of text based on annotations from individual workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass
	//
	// Multi-label
	// text classification - Uses a variant of the Expectation Maximization approach to
	// estimate the true classes of text based on annotations from individual
	// workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel
	//
	// Named
	// entity recognition - Groups similar selections and calculates aggregate
	// boundaries, resolving to most-assigned label.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition
	//
	// Video
	// Classification - Use this task type when you need workers to classify videos
	// using predefined labels that you specify. Workers are shown videos and are asked
	// to choose one label for each video.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass
	//
	// Video
	// Frame Object Detection - Use this task type to have workers identify and locate
	// objects in a sequence of video frames (images extracted from a video) using
	// bounding boxes. For example, you can use this task to ask workers to identify
	// and localize various objects in a series of video frames, such as cars, bikes,
	// and pedestrians.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection
	//
	// Video
	// Frame Object Tracking - Use this task type to have workers track the movement of
	// objects in a sequence of video frames (images extracted from a video) using
	// bounding boxes. For example, you can use this task to ask workers to track the
	// movement of objects, such as cars, bikes, and pedestrians.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking
	//
	// 3D
	// Point Cloud Modalities Use the following pre-annotation lambdas for 3D point
	// cloud labeling modality tasks. See 3D Point Cloud Task types
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-task-types.html)
	// to learn more. 3D Point Cloud Object Detection - Use this task type when you
	// want workers to classify objects in a 3D point cloud by drawing 3D cuboids
	// around objects. For example, you can use this task type to ask workers to
	// identify different types of objects in a point cloud, such as cars, bikes, and
	// pedestrians.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection
	//
	// 3D
	// Point Cloud Object Tracking - Use this task type when you want workers to draw
	// 3D cuboids around objects that appear in a sequence of 3D point cloud frames.
	// For example, you can use this task type to ask workers to track the movement of
	// vehicles across multiple point cloud frames.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking
	//
	// 3D
	// Point Cloud Semantic Segmentation - Use this task type when you want workers to
	// create a point-level semantic segmentation masks by painting objects in a 3D
	// point cloud using different colors where each color is assigned to one of the
	// classes you specify.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation
	//
	// Use
	// the following ARNs for Label Verification and Adjustment Jobs Use label
	// verification and adjustment jobs to review and adjust labels. To learn more, see
	// Verify and Adjust Labels
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.html).
	// Bounding box verification - Uses a variant of the Expectation Maximization
	// approach to estimate the true class of verification judgement for bounding box
	// labels based on annotations from individual workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// Bounding
	// box adjustment - Finds the most similar boxes from different workers based on
	// the Jaccard index of the adjusted annotations.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox
	//
	// Semantic
	// segmentation verification - Uses a variant of the Expectation Maximization
	// approach to estimate the true class of verification judgment for semantic
	// segmentation labels based on annotations from individual workers.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation
	//
	// Semantic
	// segmentation adjustment - Treats each pixel in an image as a multi-class
	// classification and treats pixel adjusted annotations from workers as "votes" for
	// the correct label.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation
	//
	// Video
	// Frame Object Detection Adjustment - Use this task type when you want workers to
	// adjust bounding boxes that workers have added to video frames to classify and
	// localize objects in a sequence of video frames.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection
	//
	// Video
	// Frame Object Tracking Adjustment - Use this task type when you want workers to
	// adjust bounding boxes that workers have added to video frames to track object
	// movement across a sequence of video frames.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking
	//
	// 3D
	// point cloud object detection adjustment - Adjust 3D cuboids in a point cloud
	// frame.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection
	//
	// 3D
	// point cloud object tracking adjustment - Adjust 3D cuboids across a sequence of
	// point cloud frames.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking
	//
	// 3D
	// point cloud semantic segmentation adjustment - Adjust semantic segmentation
	// masks in a 3D point cloud.
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation
	//
	// This member is required.
	PreHumanTaskLambdaArn *string

	// A description of the task for your human workers.
	//
	// This member is required.
	TaskDescription *string

	// The amount of time that a worker has to complete a task.
	//
	// This member is required.
	TaskTimeLimitInSeconds *int32

	// A title for the task for your human workers.
	//
	// This member is required.
	TaskTitle *string

	// Information about the user interface that workers use to complete the labeling
	// task.
	//
	// This member is required.
	UiConfig *UiConfig

	// The Amazon Resource Name (ARN) of the work team assigned to complete the tasks.
	//
	// This member is required.
	WorkteamArn *string

	// Defines the maximum number of data objects that can be labeled by human workers
	// at the same time. Also referred to as batch size. Each object may have more than
	// one worker at one time. The default value is 1000 objects.
	MaxConcurrentTaskCount *int32

	// The price that you pay for each task performed by an Amazon Mechanical Turk
	// worker.
	PublicWorkforceTaskPrice *PublicWorkforceTaskPrice

	// The length of time that a task remains available for labeling by human workers.
	// If you choose the Amazon Mechanical Turk workforce, the maximum is 12 hours
	// (43200). The default value is 864000 seconds (10 days). For private and vendor
	// workforces, the maximum is as listed.
	TaskAvailabilityLifetimeInSeconds *int32

	// Keywords used to describe the task so that workers on Amazon Mechanical Turk can
	// discover the task.
	TaskKeywords []*string
}

Information required for human workers to complete a labeling task.

type HumanTaskUiStatus 

type HumanTaskUiStatus string
const (
	HumanTaskUiStatusActive   HumanTaskUiStatus = "Active"
	HumanTaskUiStatusDeleting HumanTaskUiStatus = "Deleting"
)

Enum values for HumanTaskUiStatus

func (HumanTaskUiStatus) Values added in v0.29.0 

func (HumanTaskUiStatus) Values() []HumanTaskUiStatus

Values returns all known values for HumanTaskUiStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type HumanTaskUiSummary 

type HumanTaskUiSummary struct {

	// A timestamp when SageMaker created the human task user interface.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the human task user interface.
	//
	// This member is required.
	HumanTaskUiArn *string

	// The name of the human task user interface.
	//
	// This member is required.
	HumanTaskUiName *string
}

Container for human task user interface information.

type HyperParameterAlgorithmSpecification 

type HyperParameterAlgorithmSpecification struct {

	// The input mode that the algorithm supports: File or Pipe. In File input mode,
	// Amazon SageMaker downloads the training data from Amazon S3 to the storage
	// volume that is attached to the training instance and mounts the directory to the
	// Docker volume for the training container. In Pipe input mode, Amazon SageMaker
	// streams data directly from Amazon S3 to the container. If you specify File mode,
	// make sure that you provision the storage volume that is attached to the training
	// instance with enough capacity to accommodate the training data downloaded from
	// Amazon S3, the model artifacts, and intermediate information. For more
	// information about input modes, see Algorithms
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html).
	//
	// This member is required.
	TrainingInputMode TrainingInputMode

	// The name of the resource algorithm to use for the hyperparameter tuning job. If
	// you specify a value for this parameter, do not specify a value for
	// TrainingImage.
	AlgorithmName *string

	// An array of MetricDefinition objects that specify the metrics that the algorithm
	// emits.
	MetricDefinitions []*MetricDefinition

	// The registry path of the Docker image that contains the training algorithm. For
	// information about Docker registry paths for built-in algorithms, see Algorithms
	// Provided by Amazon SageMaker: Common Parameters
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html).
	// Amazon SageMaker supports both registry/repository[:tag] and
	// registry/repository[@digest] image path formats. For more information, see Using
	// Your Own Algorithms with Amazon SageMaker
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html).
	TrainingImage *string
}

Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.

type HyperParameterScalingType 

type HyperParameterScalingType string
const (
	HyperParameterScalingTypeAuto               HyperParameterScalingType = "Auto"
	HyperParameterScalingTypeLinear             HyperParameterScalingType = "Linear"
	HyperParameterScalingTypeLogarithmic        HyperParameterScalingType = "Logarithmic"
	HyperParameterScalingTypeReverseLogarithmic HyperParameterScalingType = "ReverseLogarithmic"
)

Enum values for HyperParameterScalingType

func (HyperParameterScalingType) Values added in v0.29.0 

func (HyperParameterScalingType) Values() []HyperParameterScalingType

Values returns all known values for HyperParameterScalingType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type HyperParameterSpecification 

type HyperParameterSpecification struct {

	// The name of this hyperparameter. The name must be unique.
	//
	// This member is required.
	Name *string

	// The type of this hyperparameter. The valid types are Integer, Continuous,
	// Categorical, and FreeText.
	//
	// This member is required.
	Type ParameterType

	// The default value for this hyperparameter. If a default value is specified, a
	// hyperparameter cannot be required.
	DefaultValue *string

	// A brief description of the hyperparameter.
	Description *string

	// Indicates whether this hyperparameter is required.
	IsRequired *bool

	// Indicates whether this hyperparameter is tunable in a hyperparameter tuning job.
	IsTunable *bool

	// The allowed range for this hyperparameter.
	Range *ParameterRange
}

Defines a hyperparameter to be used by an algorithm.

type HyperParameterTrainingJobDefinition 

type HyperParameterTrainingJobDefinition struct {

	// The HyperParameterAlgorithmSpecification object that specifies the resource
	// algorithm to use for the training jobs that the tuning job launches.
	//
	// This member is required.
	AlgorithmSpecification *HyperParameterAlgorithmSpecification

	// Specifies the path to the Amazon S3 bucket where you store model artifacts from
	// the training jobs that the tuning job launches.
	//
	// This member is required.
	OutputDataConfig *OutputDataConfig

	// The resources, including the compute instances and storage volumes, to use for
	// the training jobs that the tuning job launches. Storage volumes store model
	// artifacts and incremental states. Training algorithms might also use storage
	// volumes for scratch space. If you want Amazon SageMaker to use the storage
	// volume to store the training data, choose File as the TrainingInputMode in the
	// algorithm specification. For distributed training algorithms, specify an
	// instance count greater than 1.
	//
	// This member is required.
	ResourceConfig *ResourceConfig

	// The Amazon Resource Name (ARN) of the IAM role associated with the training jobs
	// that the tuning job launches.
	//
	// This member is required.
	RoleArn *string

	// Specifies a limit to how long a model hyperparameter training job can run. It
	// also specifies how long you are willing to wait for a managed spot training job
	// to complete. When the job reaches the a limit, Amazon SageMaker ends the
	// training job. Use this API to cap model training costs.
	//
	// This member is required.
	StoppingCondition *StoppingCondition

	// Contains information about the output location for managed spot training
	// checkpoint data.
	CheckpointConfig *CheckpointConfig

	// The job definition name.
	DefinitionName *string

	// To encrypt all communications between ML compute instances in distributed
	// training, choose True. Encryption provides greater security for distributed
	// training, but training might take longer. How long it takes depends on the
	// amount of communication between compute instances, especially if you use a deep
	// learning algorithm in distributed training.
	EnableInterContainerTrafficEncryption *bool

	// A Boolean indicating whether managed spot training is enabled (True) or not
	// (False).
	EnableManagedSpotTraining *bool

	// Isolates the training container. No inbound or outbound network calls can be
	// made, except for calls between peers within a training cluster for distributed
	// training. If network isolation is used for training jobs that are configured to
	// use a VPC, Amazon SageMaker downloads and uploads customer data and model
	// artifacts through the specified VPC, but the training container does not have
	// network access.
	EnableNetworkIsolation *bool

	// Specifies ranges of integer, continuous, and categorical hyperparameters that a
	// hyperparameter tuning job searches. The hyperparameter tuning job launches
	// training jobs with hyperparameter values within these ranges to find the
	// combination of values that result in the training job with the best performance
	// as measured by the objective metric of the hyperparameter tuning job. You can
	// specify a maximum of 20 hyperparameters that a hyperparameter tuning job can
	// search over. Every possible value of a categorical parameter range counts
	// against this limit.
	HyperParameterRanges *ParameterRanges

	// An array of Channel objects that specify the input for the training jobs that
	// the tuning job launches.
	InputDataConfig []*Channel

	// Specifies the values of hyperparameters that do not change for the tuning job.
	StaticHyperParameters map[string]*string

	// Defines the objective metric for a hyperparameter tuning job. Hyperparameter
	// tuning uses the value of this metric to evaluate the training jobs it launches,
	// and returns the training job that results in either the highest or lowest value
	// for this metric, depending on the value you specify for the Type parameter.
	TuningObjective *HyperParameterTuningJobObjective

	// The VpcConfig object that specifies the VPC that you want the training jobs that
	// this hyperparameter tuning job launches to connect to. Control access to and
	// from your training container by configuring the VPC. For more information, see
	// Protect Training Jobs by Using an Amazon Virtual Private Cloud
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html).
	VpcConfig *VpcConfig
}

Defines the training jobs launched by a hyperparameter tuning job.

type HyperParameterTrainingJobSummary 

type HyperParameterTrainingJobSummary struct {

	// The date and time that the training job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the training job.
	//
	// This member is required.
	TrainingJobArn *string

	// The name of the training job.
	//
	// This member is required.
	TrainingJobName *string

	// The status of the training job.
	//
	// This member is required.
	TrainingJobStatus TrainingJobStatus

	// A list of the hyperparameters for which you specified ranges to search.
	//
	// This member is required.
	TunedHyperParameters map[string]*string

	// The reason that the training job failed.
	FailureReason *string

	// The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value
	// of the objective metric of the tuning job that launched this training job.
	FinalHyperParameterTuningJobObjectiveMetric *FinalHyperParameterTuningJobObjectiveMetric

	// The status of the objective metric for the training job:
	//
	// * Succeeded: The final
	// objective metric for the training job was evaluated by the hyperparameter tuning
	// job and used in the hyperparameter tuning process.
	//
	// * Pending: The training job
	// is in progress and evaluation of its final objective metric is pending.
	//
	// *
	// Failed: The final objective metric for the training job was not evaluated, and
	// was not used in the hyperparameter tuning process. This typically occurs when
	// the training job failed or did not emit an objective metric.
	ObjectiveStatus ObjectiveStatus

	// Specifies the time when the training job ends on training instances. You are
	// billed for the time interval between the value of TrainingStartTime and this
	// time. For successful jobs and stopped jobs, this is the time after model
	// artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker
	// detects a job failure.
	TrainingEndTime *time.Time

	// The training job definition name.
	TrainingJobDefinitionName *string

	// The date and time that the training job started.
	TrainingStartTime *time.Time

	// The HyperParameter tuning job that launched the training job.
	TuningJobName *string
}

Specifies summary information about a training job.

type HyperParameterTuningJobConfig 

type HyperParameterTuningJobConfig struct {

	// The ResourceLimits object that specifies the maximum number of training jobs and
	// parallel training jobs for this tuning job.
	//
	// This member is required.
	ResourceLimits *ResourceLimits

	// Specifies how hyperparameter tuning chooses the combinations of hyperparameter
	// values to use for the training job it launches. To use the Bayesian search
	// strategy, set this to Bayesian. To randomly search, set it to Random. For
	// information about search strategies, see How Hyperparameter Tuning Works
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.html).
	//
	// This member is required.
	Strategy HyperParameterTuningJobStrategyType

	// The HyperParameterTuningJobObjective object that specifies the objective metric
	// for this tuning job.
	HyperParameterTuningJobObjective *HyperParameterTuningJobObjective

	// The ParameterRanges object that specifies the ranges of hyperparameters that
	// this tuning job searches.
	ParameterRanges *ParameterRanges

	// Specifies whether to use early stopping for training jobs launched by the
	// hyperparameter tuning job. This can be one of the following values (the default
	// value is OFF): OFF Training jobs launched by the hyperparameter tuning job do
	// not use early stopping. AUTO Amazon SageMaker stops training jobs launched by
	// the hyperparameter tuning job when they are unlikely to perform better than
	// previously completed training jobs. For more information, see Stop Training Jobs
	// Early
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-early-stopping.html).
	TrainingJobEarlyStoppingType TrainingJobEarlyStoppingType

	// The tuning job's completion criteria.
	TuningJobCompletionCriteria *TuningJobCompletionCriteria
}

Configures a hyperparameter tuning job.

type HyperParameterTuningJobObjective 

type HyperParameterTuningJobObjective struct {

	// The name of the metric to use for the objective metric.
	//
	// This member is required.
	MetricName *string

	// Whether to minimize or maximize the objective metric.
	//
	// This member is required.
	Type HyperParameterTuningJobObjectiveType
}

Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type parameter.

type HyperParameterTuningJobObjectiveType 

type HyperParameterTuningJobObjectiveType string
const (
	HyperParameterTuningJobObjectiveTypeMaximize HyperParameterTuningJobObjectiveType = "Maximize"
	HyperParameterTuningJobObjectiveTypeMinimize HyperParameterTuningJobObjectiveType = "Minimize"
)

Enum values for HyperParameterTuningJobObjectiveType

func (HyperParameterTuningJobObjectiveType) Values added in v0.29.0 

func (HyperParameterTuningJobObjectiveType) Values() []HyperParameterTuningJobObjectiveType

Values returns all known values for HyperParameterTuningJobObjectiveType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type HyperParameterTuningJobSortByOptions 

type HyperParameterTuningJobSortByOptions string
const (
	HyperParameterTuningJobSortByOptionsName         HyperParameterTuningJobSortByOptions = "Name"
	HyperParameterTuningJobSortByOptionsStatus       HyperParameterTuningJobSortByOptions = "Status"
	HyperParameterTuningJobSortByOptionsCreationtime HyperParameterTuningJobSortByOptions = "CreationTime"
)

Enum values for HyperParameterTuningJobSortByOptions

func (HyperParameterTuningJobSortByOptions) Values added in v0.29.0 

func (HyperParameterTuningJobSortByOptions) Values() []HyperParameterTuningJobSortByOptions

Values returns all known values for HyperParameterTuningJobSortByOptions. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type HyperParameterTuningJobStatus 

type HyperParameterTuningJobStatus string
const (
	HyperParameterTuningJobStatusCompleted  HyperParameterTuningJobStatus = "Completed"
	HyperParameterTuningJobStatusInProgress HyperParameterTuningJobStatus = "InProgress"
	HyperParameterTuningJobStatusFailed     HyperParameterTuningJobStatus = "Failed"
	HyperParameterTuningJobStatusStopped    HyperParameterTuningJobStatus = "Stopped"
	HyperParameterTuningJobStatusStopping   HyperParameterTuningJobStatus = "Stopping"
)

Enum values for HyperParameterTuningJobStatus

func (HyperParameterTuningJobStatus) Values added in v0.29.0 

func (HyperParameterTuningJobStatus) Values() []HyperParameterTuningJobStatus

Values returns all known values for HyperParameterTuningJobStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type HyperParameterTuningJobStrategyType 

type HyperParameterTuningJobStrategyType string
const (
	HyperParameterTuningJobStrategyTypeBayesian HyperParameterTuningJobStrategyType = "Bayesian"
	HyperParameterTuningJobStrategyTypeRandom   HyperParameterTuningJobStrategyType = "Random"
)

Enum values for HyperParameterTuningJobStrategyType

func (HyperParameterTuningJobStrategyType) Values added in v0.29.0 

func (HyperParameterTuningJobStrategyType) Values() []HyperParameterTuningJobStrategyType

Values returns all known values for HyperParameterTuningJobStrategyType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type HyperParameterTuningJobSummary 

type HyperParameterTuningJobSummary struct {

	// The date and time that the tuning job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the tuning job.
	//
	// This member is required.
	HyperParameterTuningJobArn *string

	// The name of the tuning job.
	//
	// This member is required.
	HyperParameterTuningJobName *string

	// The status of the tuning job.
	//
	// This member is required.
	HyperParameterTuningJobStatus HyperParameterTuningJobStatus

	// The ObjectiveStatusCounters object that specifies the numbers of training jobs,
	// categorized by objective metric status, that this tuning job launched.
	//
	// This member is required.
	ObjectiveStatusCounters *ObjectiveStatusCounters

	// Specifies the search strategy hyperparameter tuning uses to choose which
	// hyperparameters to use for each iteration. Currently, the only valid value is
	// Bayesian.
	//
	// This member is required.
	Strategy HyperParameterTuningJobStrategyType

	// The TrainingJobStatusCounters object that specifies the numbers of training
	// jobs, categorized by status, that this tuning job launched.
	//
	// This member is required.
	TrainingJobStatusCounters *TrainingJobStatusCounters

	// The date and time that the tuning job ended.
	HyperParameterTuningEndTime *time.Time

	// The date and time that the tuning job was modified.
	LastModifiedTime *time.Time

	// The ResourceLimits object that specifies the maximum number of training jobs and
	// parallel training jobs allowed for this tuning job.
	ResourceLimits *ResourceLimits
}

Provides summary information about a hyperparameter tuning job.

type HyperParameterTuningJobWarmStartConfig 

type HyperParameterTuningJobWarmStartConfig struct {

	// An array of hyperparameter tuning jobs that are used as the starting point for
	// the new hyperparameter tuning job. For more information about warm starting a
	// hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a
	// Starting Point
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-warm-start.html).
	// Hyperparameter tuning jobs created before October 1, 2018 cannot be used as
	// parent jobs for warm start tuning jobs.
	//
	// This member is required.
	ParentHyperParameterTuningJobs []*ParentHyperParameterTuningJob

	// Specifies one of the following: IDENTICAL_DATA_AND_ALGORITHM The new
	// hyperparameter tuning job uses the same input data and training image as the
	// parent tuning jobs. You can change the hyperparameter ranges to search and the
	// maximum number of training jobs that the hyperparameter tuning job launches. You
	// cannot use a new version of the training algorithm, unless the changes in the
	// new version do not affect the algorithm itself. For example, changes that
	// improve logging or adding support for a different data format are allowed. You
	// can also change hyperparameters from tunable to static, and from static to
	// tunable, but the total number of static plus tunable hyperparameters must remain
	// the same as it is in all parent jobs. The objective metric for the new tuning
	// job must be the same as for all parent jobs. TRANSFER_LEARNING The new
	// hyperparameter tuning job can include input data, hyperparameter ranges, maximum
	// number of concurrent training jobs, and maximum number of training jobs that are
	// different than those of its parent hyperparameter tuning jobs. The training
	// image can also be a different version from the version used in the parent
	// hyperparameter tuning job. You can also change hyperparameters from tunable to
	// static, and from static to tunable, but the total number of static plus tunable
	// hyperparameters must remain the same as it is in all parent jobs. The objective
	// metric for the new tuning job must be the same as for all parent jobs.
	//
	// This member is required.
	WarmStartType HyperParameterTuningJobWarmStartType
}

Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job. All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job. All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.

type HyperParameterTuningJobWarmStartType 

type HyperParameterTuningJobWarmStartType string
const (
	HyperParameterTuningJobWarmStartTypeIdenticalDataAndAlgorithm HyperParameterTuningJobWarmStartType = "IdenticalDataAndAlgorithm"
	HyperParameterTuningJobWarmStartTypeTransferLearning          HyperParameterTuningJobWarmStartType = "TransferLearning"
)

Enum values for HyperParameterTuningJobWarmStartType

func (HyperParameterTuningJobWarmStartType) Values added in v0.29.0 

func (HyperParameterTuningJobWarmStartType) Values() []HyperParameterTuningJobWarmStartType

Values returns all known values for HyperParameterTuningJobWarmStartType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type Image added in v0.29.0 

type Image struct {

	// When the image was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the image.
	//
	// This member is required.
	ImageArn *string

	// The name of the image.
	//
	// This member is required.
	ImageName *string

	// The status of the image.
	//
	// This member is required.
	ImageStatus ImageStatus

	// When the image was last modified.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// The description of the image.
	Description *string

	// The name of the image as displayed.
	DisplayName *string

	// When a create, update, or delete operation fails, the reason for the failure.
	FailureReason *string
}

A SageMaker image. A SageMaker image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker ImageVersion.

type ImageConfig added in v0.29.0 

type ImageConfig struct {

	// Set this to one of the following values:
	//
	// * Platform - The model image is hosted
	// in Amazon ECR.
	//
	// * Vpc - The model image is hosted in a private Docker registry
	// in your VPC.
	//
	// This member is required.
	RepositoryAccessMode RepositoryAccessMode
}

Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).

type ImageSortBy added in v0.29.0 

type ImageSortBy string
const (
	ImageSortByCreationTime     ImageSortBy = "CREATION_TIME"
	ImageSortByLastModifiedTime ImageSortBy = "LAST_MODIFIED_TIME"
	ImageSortByImageName        ImageSortBy = "IMAGE_NAME"
)

Enum values for ImageSortBy

func (ImageSortBy) Values added in v0.29.0 

func (ImageSortBy) Values() []ImageSortBy

Values returns all known values for ImageSortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ImageSortOrder added in v0.29.0 

type ImageSortOrder string
const (
	ImageSortOrderAscending  ImageSortOrder = "ASCENDING"
	ImageSortOrderDescending ImageSortOrder = "DESCENDING"
)

Enum values for ImageSortOrder

func (ImageSortOrder) Values added in v0.29.0 

func (ImageSortOrder) Values() []ImageSortOrder

Values returns all known values for ImageSortOrder. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ImageStatus added in v0.29.0 

type ImageStatus string
const (
	ImageStatusCreating     ImageStatus = "CREATING"
	ImageStatusCreated      ImageStatus = "CREATED"
	ImageStatusCreateFailed ImageStatus = "CREATE_FAILED"
	ImageStatusUpdating     ImageStatus = "UPDATING"
	ImageStatusUpdateFailed ImageStatus = "UPDATE_FAILED"
	ImageStatusDeleting     ImageStatus = "DELETING"
	ImageStatusDeleteFailed ImageStatus = "DELETE_FAILED"
)

Enum values for ImageStatus

func (ImageStatus) Values added in v0.29.0 

func (ImageStatus) Values() []ImageStatus

Values returns all known values for ImageStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ImageVersion added in v0.29.0 

type ImageVersion struct {

	// When the version was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the image the version is based on.
	//
	// This member is required.
	ImageArn *string

	// The ARN of the version.
	//
	// This member is required.
	ImageVersionArn *string

	// The status of the version.
	//
	// This member is required.
	ImageVersionStatus ImageVersionStatus

	// When the version was last modified.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// The version number.
	//
	// This member is required.
	Version *int32

	// When a create or delete operation fails, the reason for the failure.
	FailureReason *string
}

A version of a SageMaker Image. A version represents an existing container image.

type ImageVersionSortBy added in v0.29.0 

type ImageVersionSortBy string
const (
	ImageVersionSortByCreationTime     ImageVersionSortBy = "CREATION_TIME"
	ImageVersionSortByLastModifiedTime ImageVersionSortBy = "LAST_MODIFIED_TIME"
	ImageVersionSortByVersion          ImageVersionSortBy = "VERSION"
)

Enum values for ImageVersionSortBy

func (ImageVersionSortBy) Values added in v0.29.0 

func (ImageVersionSortBy) Values() []ImageVersionSortBy

Values returns all known values for ImageVersionSortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ImageVersionSortOrder added in v0.29.0 

type ImageVersionSortOrder string
const (
	ImageVersionSortOrderAscending  ImageVersionSortOrder = "ASCENDING"
	ImageVersionSortOrderDescending ImageVersionSortOrder = "DESCENDING"
)

Enum values for ImageVersionSortOrder

func (ImageVersionSortOrder) Values added in v0.29.0 

func (ImageVersionSortOrder) Values() []ImageVersionSortOrder

Values returns all known values for ImageVersionSortOrder. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ImageVersionStatus added in v0.29.0 

type ImageVersionStatus string
const (
	ImageVersionStatusCreating     ImageVersionStatus = "CREATING"
	ImageVersionStatusCreated      ImageVersionStatus = "CREATED"
	ImageVersionStatusCreateFailed ImageVersionStatus = "CREATE_FAILED"
	ImageVersionStatusDeleting     ImageVersionStatus = "DELETING"
	ImageVersionStatusDeleteFailed ImageVersionStatus = "DELETE_FAILED"
)

Enum values for ImageVersionStatus

func (ImageVersionStatus) Values added in v0.29.0 

func (ImageVersionStatus) Values() []ImageVersionStatus

Values returns all known values for ImageVersionStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type InferenceSpecification 

type InferenceSpecification struct {

	// The Amazon ECR registry path of the Docker image that contains the inference
	// code.
	//
	// This member is required.
	Containers []*ModelPackageContainerDefinition

	// The supported MIME types for the input data.
	//
	// This member is required.
	SupportedContentTypes []*string

	// A list of the instance types that are used to generate inferences in real-time.
	//
	// This member is required.
	SupportedRealtimeInferenceInstanceTypes []ProductionVariantInstanceType

	// The supported MIME types for the output data.
	//
	// This member is required.
	SupportedResponseMIMETypes []*string

	// A list of the instance types on which a transformation job can be run or on
	// which an endpoint can be deployed.
	//
	// This member is required.
	SupportedTransformInstanceTypes []TransformInstanceType
}

Defines how to perform inference generation after a training job is run.

type InputConfig 

type InputConfig struct {

	// Specifies the name and shape of the expected data inputs for your trained model
	// with a JSON dictionary form. The data inputs are InputConfig$Framework
	// specific.
	//
	// * TensorFlow: You must specify the name and shape (NHWC format) of
	// the expected data inputs using a dictionary format for your trained model. The
	// dictionary formats required for the console and CLI are different.
	//
	// * Examples
	// for one input:
	//
	// * If using the console, {"input":[1,1024,1024,3]}
	//
	// * If using
	// the CLI, {\"input\":[1,1024,1024,3]}
	//
	// * Examples for two inputs:
	//
	// * If using the
	// console, {"data1": [1,28,28,1], "data2":[1,28,28,1]}
	//
	// * If using the CLI,
	// {\"data1\": [1,28,28,1], \"data2\":[1,28,28,1]}
	//
	// * KERAS: You must specify the
	// name and shape (NCHW format) of expected data inputs using a dictionary format
	// for your trained model. Note that while Keras model artifacts should be uploaded
	// in NHWC (channel-last) format, DataInputConfig should be specified in NCHW
	// (channel-first) format. The dictionary formats required for the console and CLI
	// are different.
	//
	// * Examples for one input:
	//
	// * If using the console,
	// {"input_1":[1,3,224,224]}
	//
	// * If using the CLI, {\"input_1\":[1,3,224,224]}
	//
	// *
	// Examples for two inputs:
	//
	// * If using the console, {"input_1": [1,3,224,224],
	// "input_2":[1,3,224,224]}
	//
	// * If using the CLI, {\"input_1\": [1,3,224,224],
	// \"input_2\":[1,3,224,224]}
	//
	// * MXNET/ONNX: You must specify the name and shape
	// (NCHW format) of the expected data inputs in order using a dictionary format for
	// your trained model. The dictionary formats required for the console and CLI are
	// different.
	//
	// * Examples for one input:
	//
	// * If using the console,
	// {"data":[1,3,1024,1024]}
	//
	// * If using the CLI, {\"data\":[1,3,1024,1024]}
	//
	// *
	// Examples for two inputs:
	//
	// * If using the console, {"var1": [1,1,28,28],
	// "var2":[1,1,28,28]}
	//
	// * If using the CLI, {\"var1\": [1,1,28,28],
	// \"var2\":[1,1,28,28]}
	//
	// * PyTorch: You can either specify the name and shape
	// (NCHW format) of expected data inputs in order using a dictionary format for
	// your trained model or you can specify the shape only using a list format. The
	// dictionary formats required for the console and CLI are different. The list
	// formats for the console and CLI are the same.
	//
	// * Examples for one input in
	// dictionary format:
	//
	// * If using the console, {"input0":[1,3,224,224]}
	//
	// * If using
	// the CLI, {\"input0\":[1,3,224,224]}
	//
	// * Example for one input in list format:
	// [[1,3,224,224]]
	//
	// * Examples for two inputs in dictionary format:
	//
	// * If using the
	// console, {"input0":[1,3,224,224], "input1":[1,3,224,224]}
	//
	// * If using the CLI,
	// {\"input0\":[1,3,224,224], \"input1\":[1,3,224,224]}
	//
	// * Example for two inputs
	// in list format: [[1,3,224,224], [1,3,224,224]]
	//
	// * XGBOOST: input data name and
	// shape are not needed.
	//
	// DataInputConfig supports the following parameters for
	// CoreMLOutputConfig$TargetDevice (ML Model format):
	//
	// * shape: Input shape, for
	// example {"input_1": {"shape": [1,224,224,3]}}. In addition to static input
	// shapes, CoreML converter supports Flexible input shapes:
	//
	// * Range Dimension. You
	// can use the Range Dimension feature if you know the input shape will be within
	// some specific interval in that dimension, for example: {"input_1": {"shape":
	// ["1..10", 224, 224, 3]}}
	//
	// * Enumerated shapes. Sometimes, the models are trained
	// to work only on a select set of inputs. You can enumerate all supported input
	// shapes, for example: {"input_1": {"shape": [[1, 224, 224, 3], [1, 160, 160,
	// 3]]}}
	//
	// * default_shape: Default input shape. You can set a default shape during
	// conversion for both Range Dimension and Enumerated Shapes. For example
	// {"input_1": {"shape": ["1..10", 224, 224, 3], "default_shape": [1, 224, 224,
	// 3]}}
	//
	// * type: Input type. Allowed values: Image and Tensor. By default, the
	// converter generates an ML Model with inputs of type Tensor (MultiArray). User
	// can set input type to be Image. Image input type requires additional input
	// parameters such as bias and scale.
	//
	// * bias: If the input type is an Image, you
	// need to provide the bias vector.
	//
	// * scale: If the input type is an Image, you
	// need to provide a scale factor.
	//
	// CoreML ClassifierConfig parameters can be
	// specified using OutputConfig$CompilerOptions. CoreML converter supports
	// Tensorflow and PyTorch models. CoreML conversion examples:
	//
	// * Tensor type
	// input:
	//
	// * "DataInputConfig": {"input_1": {"shape": [[1,224,224,3],
	// [1,160,160,3]], "default_shape": [1,224,224,3]}}
	//
	// * Tensor type input without
	// input name (PyTorch):
	//
	// * "DataInputConfig": [{"shape": [[1,3,224,224],
	// [1,3,160,160]], "default_shape": [1,3,224,224]}]
	//
	// * Image type input:
	//
	// *
	// "DataInputConfig": {"input_1": {"shape": [[1,224,224,3], [1,160,160,3]],
	// "default_shape": [1,224,224,3], "type": "Image", "bias": [-1,-1,-1], "scale":
	// 0.007843137255}}
	//
	// * "CompilerOptions": {"class_labels":
	// "imagenet_labels_1000.txt"}
	//
	// * Image type input without input name (PyTorch):
	//
	// *
	// "DataInputConfig": [{"shape": [[1,3,224,224], [1,3,160,160]], "default_shape":
	// [1,3,224,224], "type": "Image", "bias": [-1,-1,-1], "scale": 0.007843137255}]
	//
	// *
	// "CompilerOptions": {"class_labels": "imagenet_labels_1000.txt"}
	//
	// This member is required.
	DataInputConfig *string

	// Identifies the framework in which the model was trained. For example:
	// TENSORFLOW.
	//
	// This member is required.
	Framework Framework

	// 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).
	//
	// This member is required.
	S3Uri *string
}

Contains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.

type InstanceType 

type InstanceType string
const (
	InstanceTypeMlT2Medium    InstanceType = "ml.t2.medium"
	InstanceTypeMlT2Large     InstanceType = "ml.t2.large"
	InstanceTypeMlT2Xlarge    InstanceType = "ml.t2.xlarge"
	InstanceTypeMlT22xlarge   InstanceType = "ml.t2.2xlarge"
	InstanceTypeMlT3Medium    InstanceType = "ml.t3.medium"
	InstanceTypeMlT3Large     InstanceType = "ml.t3.large"
	InstanceTypeMlT3Xlarge    InstanceType = "ml.t3.xlarge"
	InstanceTypeMlT32xlarge   InstanceType = "ml.t3.2xlarge"
	InstanceTypeMlM4Xlarge    InstanceType = "ml.m4.xlarge"
	InstanceTypeMlM42xlarge   InstanceType = "ml.m4.2xlarge"
	InstanceTypeMlM44xlarge   InstanceType = "ml.m4.4xlarge"
	InstanceTypeMlM410xlarge  InstanceType = "ml.m4.10xlarge"
	InstanceTypeMlM416xlarge  InstanceType = "ml.m4.16xlarge"
	InstanceTypeMlM5Xlarge    InstanceType = "ml.m5.xlarge"
	InstanceTypeMlM52xlarge   InstanceType = "ml.m5.2xlarge"
	InstanceTypeMlM54xlarge   InstanceType = "ml.m5.4xlarge"
	InstanceTypeMlM512xlarge  InstanceType = "ml.m5.12xlarge"
	InstanceTypeMlM524xlarge  InstanceType = "ml.m5.24xlarge"
	InstanceTypeMlC4Xlarge    InstanceType = "ml.c4.xlarge"
	InstanceTypeMlC42xlarge   InstanceType = "ml.c4.2xlarge"
	InstanceTypeMlC44xlarge   InstanceType = "ml.c4.4xlarge"
	InstanceTypeMlC48xlarge   InstanceType = "ml.c4.8xlarge"
	InstanceTypeMlC5Xlarge    InstanceType = "ml.c5.xlarge"
	InstanceTypeMlC52xlarge   InstanceType = "ml.c5.2xlarge"
	InstanceTypeMlC54xlarge   InstanceType = "ml.c5.4xlarge"
	InstanceTypeMlC59xlarge   InstanceType = "ml.c5.9xlarge"
	InstanceTypeMlC518xlarge  InstanceType = "ml.c5.18xlarge"
	InstanceTypeMlC5dXlarge   InstanceType = "ml.c5d.xlarge"
	InstanceTypeMlC5d2xlarge  InstanceType = "ml.c5d.2xlarge"
	InstanceTypeMlC5d4xlarge  InstanceType = "ml.c5d.4xlarge"
	InstanceTypeMlC5d9xlarge  InstanceType = "ml.c5d.9xlarge"
	InstanceTypeMlC5d18xlarge InstanceType = "ml.c5d.18xlarge"
	InstanceTypeMlP2Xlarge    InstanceType = "ml.p2.xlarge"
	InstanceTypeMlP28xlarge   InstanceType = "ml.p2.8xlarge"
	InstanceTypeMlP216xlarge  InstanceType = "ml.p2.16xlarge"
	InstanceTypeMlP32xlarge   InstanceType = "ml.p3.2xlarge"
	InstanceTypeMlP38xlarge   InstanceType = "ml.p3.8xlarge"
	InstanceTypeMlP316xlarge  InstanceType = "ml.p3.16xlarge"
)

Enum values for InstanceType

func (InstanceType) Values added in v0.29.0 

func (InstanceType) Values() []InstanceType

Values returns all known values for InstanceType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type IntegerParameterRange 

type IntegerParameterRange struct {

	// The maximum value of the hyperparameter to search.
	//
	// This member is required.
	MaxValue *string

	// The minimum value of the hyperparameter to search.
	//
	// This member is required.
	MinValue *string

	// The name of the hyperparameter to search.
	//
	// This member is required.
	Name *string

	// The scale that hyperparameter tuning uses to search the hyperparameter range.
	// For information about choosing a hyperparameter scale, see Hyperparameter
	// Scaling
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-type).
	// One of the following values: Auto Amazon SageMaker hyperparameter tuning chooses
	// the best scale for the hyperparameter. Linear Hyperparameter tuning searches the
	// values in the hyperparameter range by using a linear scale. Logarithmic
	// Hyperparameter tuning searches the values in the hyperparameter range by using a
	// logarithmic scale. Logarithmic scaling works only for ranges that have only
	// values greater than 0.
	ScalingType HyperParameterScalingType
}

For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.

type IntegerParameterRangeSpecification 

type IntegerParameterRangeSpecification struct {

	// The maximum integer value allowed.
	//
	// This member is required.
	MaxValue *string

	// The minimum integer value allowed.
	//
	// This member is required.
	MinValue *string
}

Defines the possible values for an integer hyperparameter.

type JoinSource 

type JoinSource string
const (
	JoinSourceInput JoinSource = "Input"
	JoinSourceNone  JoinSource = "None"
)

Enum values for JoinSource

func (JoinSource) Values added in v0.29.0 

func (JoinSource) Values() []JoinSource

Values returns all known values for JoinSource. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type JupyterServerAppSettings 

type JupyterServerAppSettings struct {

	// The default instance type and the Amazon Resource Name (ARN) of the SageMaker
	// image created on the instance.
	DefaultResourceSpec *ResourceSpec
}

Jupyter server's app settings.

type KernelGatewayAppSettings 

type KernelGatewayAppSettings struct {

	// A list of custom images that are configured to run as a KernelGateway app.
	CustomImages []*CustomImage

	// The default instance type and the Amazon Resource Name (ARN) of the default
	// SageMaker image used by the KernelGateway app.
	DefaultResourceSpec *ResourceSpec
}

The KernelGateway app settings.

type KernelGatewayImageConfig added in v0.29.0 

type KernelGatewayImageConfig struct {

	// Defines how a kernel is started and the arguments, environment variables, and
	// metadata that are available to the kernel.
	//
	// This member is required.
	KernelSpecs []*KernelSpec

	// The file system configuration.
	FileSystemConfig *FileSystemConfig
}

The configuration for an Amazon SageMaker KernelGateway app.

type KernelSpec added in v0.29.0 

type KernelSpec struct {

	// The name of the kernel. Must be unique to your account.
	//
	// This member is required.
	Name *string

	// The display name of the kernel.
	DisplayName *string
}

Defines how a kernel is started and the arguments, environment variables, and metadata that are available to the kernel.

type LabelCounters 

type LabelCounters struct {

	// The total number of objects that could not be labeled due to an error.
	FailedNonRetryableError *int32

	// The total number of objects labeled by a human worker.
	HumanLabeled *int32

	// The total number of objects labeled by automated data labeling.
	MachineLabeled *int32

	// The total number of objects labeled.
	TotalLabeled *int32

	// The total number of objects not yet labeled.
	Unlabeled *int32
}

Provides a breakdown of the number of objects labeled.

type LabelCountersForWorkteam 

type LabelCountersForWorkteam struct {

	// The total number of data objects labeled by a human worker.
	HumanLabeled *int32

	// The total number of data objects that need to be labeled by a human worker.
	PendingHuman *int32

	// The total number of tasks in the labeling job.
	Total *int32
}

Provides counts for human-labeled tasks in the labeling job.

type LabelingJobAlgorithmsConfig 

type LabelingJobAlgorithmsConfig struct {

	// Specifies the Amazon Resource Name (ARN) of the algorithm used for
	// auto-labeling. You must select one of the following ARNs:
	//
	// * Image
	// classification
	// arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification
	//
	// *
	// Text classification
	// arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification
	//
	// *
	// Object detection
	// arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection
	//
	// *
	// Semantic Segmentation
	// arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation
	//
	// This member is required.
	LabelingJobAlgorithmSpecificationArn *string

	// At the end of an auto-label job Ground Truth sends the Amazon Resource Name
	// (ARN) of the final model used for auto-labeling. You can use this model as the
	// starting point for subsequent similar jobs by providing the ARN of the model
	// here.
	InitialActiveLearningModelArn *string

	// Provides configuration information for a labeling job.
	LabelingJobResourceConfig *LabelingJobResourceConfig
}

Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig object must be supplied in order to use auto-labeling.

type LabelingJobDataAttributes 

type LabelingJobDataAttributes struct {

	// Declares that your content is free of personally identifiable information or
	// adult content. Amazon SageMaker may restrict the Amazon Mechanical Turk workers
	// that can view your task based on this information.
	ContentClassifiers []ContentClassifier
}

Attributes of the data specified by the customer. Use these to describe the data to be labeled.

type LabelingJobDataSource 

type LabelingJobDataSource struct {

	// The Amazon S3 location of the input data objects.
	S3DataSource *LabelingJobS3DataSource

	// An Amazon SNS data source used for streaming labeling jobs.
	SnsDataSource *LabelingJobSnsDataSource
}

Provides information about the location of input data. You must specify at least one of the following: S3DataSource or SnsDataSource. Use SnsDataSource to specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job. Use S3DataSource to specify an input manifest file for both streaming and one-time labeling jobs. Adding an S3DataSource is optional if you use SnsDataSource to create a streaming labeling job.

type LabelingJobForWorkteamSummary 

type LabelingJobForWorkteamSummary struct {

	// The date and time that the labeling job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// A unique identifier for a labeling job. You can use this to refer to a specific
	// labeling job.
	//
	// This member is required.
	JobReferenceCode *string

	//
	//
	// This member is required.
	WorkRequesterAccountId *string

	// Provides information about the progress of a labeling job.
	LabelCounters *LabelCountersForWorkteam

	// The name of the labeling job that the work team is assigned to.
	LabelingJobName *string

	// The configured number of workers per data object.
	NumberOfHumanWorkersPerDataObject *int32
}

Provides summary information for a work team.

type LabelingJobInputConfig 

type LabelingJobInputConfig struct {

	// The location of the input data.
	//
	// This member is required.
	DataSource *LabelingJobDataSource

	// Attributes of the data specified by the customer.
	DataAttributes *LabelingJobDataAttributes
}

Input configuration information for a labeling job.

type LabelingJobOutput 

type LabelingJobOutput struct {

	// The Amazon S3 bucket location of the manifest file for labeled data.
	//
	// This member is required.
	OutputDatasetS3Uri *string

	// The Amazon Resource Name (ARN) for the most recent Amazon SageMaker model
	// trained as part of automated data labeling.
	FinalActiveLearningModelArn *string
}

Specifies the location of the output produced by the labeling job.

type LabelingJobOutputConfig 

type LabelingJobOutputConfig struct {

	// The Amazon S3 location to write output data.
	//
	// This member is required.
	S3OutputPath *string

	// The AWS Key Management Service ID of the key used to encrypt the output data, if
	// any. If you use a KMS key ID or an alias of your master key, the Amazon
	// SageMaker execution role must include permissions to call kms:Encrypt. If you
	// don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon
	// S3 for your role's account. Amazon SageMaker uses server-side encryption with
	// KMS-managed keys for LabelingJobOutputConfig. If you use a bucket policy with an
	// s3:PutObject permission that only allows objects with server-side encryption,
	// set the condition key of s3:x-amz-server-side-encryption to "aws:kms". For more
	// information, see KMS-Managed Encryption Keys
	// (https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html) in the
	// Amazon Simple Storage Service Developer Guide. The KMS key policy must grant
	// permission to the IAM role that you specify in your CreateLabelingJob request.
	// For more information, see Using Key Policies in AWS KMS
	// (http://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html) in the
	// AWS Key Management Service Developer Guide.
	KmsKeyId *string

	// An Amazon Simple Notification Service (Amazon SNS) output topic ARN. When
	// workers complete labeling tasks, Ground Truth will send labeling task output
	// data to the SNS output topic you specify here. You must provide a value for this
	// parameter if you provide an Amazon SNS input topic in SnsDataSource in
	// InputConfig.
	SnsTopicArn *string
}

Output configuration information for a labeling job.

type LabelingJobResourceConfig 

type LabelingJobResourceConfig struct {

	// The AWS Key Management Service (AWS 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. The VolumeKmsKeyId can be any of the following formats:
	//
	// *
	// // KMS Key ID "1234abcd-12ab-34cd-56ef-1234567890ab"
	//
	// * // Amazon Resource Name
	// (ARN) of a KMS Key
	// "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
	VolumeKmsKeyId *string
}

Provides configuration information for labeling jobs.

type LabelingJobS3DataSource 

type LabelingJobS3DataSource struct {

	// The Amazon S3 location of the manifest file that describes the input data
	// objects.
	//
	// This member is required.
	ManifestS3Uri *string
}

The Amazon S3 location of the input data objects.

type LabelingJobSnsDataSource added in v0.29.0 

type LabelingJobSnsDataSource struct {

	// The Amazon SNS input topic Amazon Resource Name (ARN). Specify the ARN of the
	// input topic you will use to send new data objects to a streaming labeling job.
	// If you specify an input topic for SnsTopicArn in InputConfig, you must specify a
	// value for SnsTopicArn in OutputConfig.
	//
	// This member is required.
	SnsTopicArn *string
}

An Amazon SNS data source used for streaming labeling jobs.

type LabelingJobStatus 

type LabelingJobStatus string
const (
	LabelingJobStatusInitializing LabelingJobStatus = "Initializing"
	LabelingJobStatusInProgress   LabelingJobStatus = "InProgress"
	LabelingJobStatusCompleted    LabelingJobStatus = "Completed"
	LabelingJobStatusFailed       LabelingJobStatus = "Failed"
	LabelingJobStatusStopping     LabelingJobStatus = "Stopping"
	LabelingJobStatusStopped      LabelingJobStatus = "Stopped"
)

Enum values for LabelingJobStatus

func (LabelingJobStatus) Values added in v0.29.0 

func (LabelingJobStatus) Values() []LabelingJobStatus

Values returns all known values for LabelingJobStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type LabelingJobStoppingConditions 

type LabelingJobStoppingConditions struct {

	// The maximum number of objects that can be labeled by human workers.
	MaxHumanLabeledObjectCount *int32

	// The maximum number of input data objects that should be labeled.
	MaxPercentageOfInputDatasetLabeled *int32
}

A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling. Labeling jobs fail after 30 days with an appropriate client error message.

type LabelingJobSummary 

type LabelingJobSummary struct {

	// The date and time that the job was created (timestamp).
	//
	// This member is required.
	CreationTime *time.Time

	// Counts showing the progress of the labeling job.
	//
	// This member is required.
	LabelCounters *LabelCounters

	// The Amazon Resource Name (ARN) assigned to the labeling job when it was created.
	//
	// This member is required.
	LabelingJobArn *string

	// The name of the labeling job.
	//
	// This member is required.
	LabelingJobName *string

	// The current status of the labeling job.
	//
	// This member is required.
	LabelingJobStatus LabelingJobStatus

	// The date and time that the job was last modified (timestamp).
	//
	// This member is required.
	LastModifiedTime *time.Time

	// The Amazon Resource Name (ARN) of a Lambda function. The function is run before
	// each data object is sent to a worker.
	//
	// This member is required.
	PreHumanTaskLambdaArn *string

	// The Amazon Resource Name (ARN) of the work team assigned to the job.
	//
	// This member is required.
	WorkteamArn *string

	// The Amazon Resource Name (ARN) of the Lambda function used to consolidate the
	// annotations from individual workers into a label for a data object. For more
	// information, see Annotation Consolidation
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.html).
	AnnotationConsolidationLambdaArn *string

	// If the LabelingJobStatus field is Failed, this field contains a description of
	// the error.
	FailureReason *string

	// Input configuration for the labeling job.
	InputConfig *LabelingJobInputConfig

	// The location of the output produced by the labeling job.
	LabelingJobOutput *LabelingJobOutput
}

Provides summary information about a labeling job.

type ListCompilationJobsSortBy 

type ListCompilationJobsSortBy string
const (
	ListCompilationJobsSortByName         ListCompilationJobsSortBy = "Name"
	ListCompilationJobsSortByCreationTime ListCompilationJobsSortBy = "CreationTime"
	ListCompilationJobsSortByStatus       ListCompilationJobsSortBy = "Status"
)

Enum values for ListCompilationJobsSortBy

func (ListCompilationJobsSortBy) Values added in v0.29.0 

func (ListCompilationJobsSortBy) Values() []ListCompilationJobsSortBy

Values returns all known values for ListCompilationJobsSortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ListLabelingJobsForWorkteamSortByOptions 

type ListLabelingJobsForWorkteamSortByOptions string
const (
	ListLabelingJobsForWorkteamSortByOptionsCreationTime ListLabelingJobsForWorkteamSortByOptions = "CreationTime"
)

Enum values for ListLabelingJobsForWorkteamSortByOptions

func (ListLabelingJobsForWorkteamSortByOptions) Values added in v0.29.0 

func (ListLabelingJobsForWorkteamSortByOptions) Values() []ListLabelingJobsForWorkteamSortByOptions

Values returns all known values for ListLabelingJobsForWorkteamSortByOptions. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ListWorkforcesSortByOptions 

type ListWorkforcesSortByOptions string
const (
	ListWorkforcesSortByOptionsName       ListWorkforcesSortByOptions = "Name"
	ListWorkforcesSortByOptionsCreatedate ListWorkforcesSortByOptions = "CreateDate"
)

Enum values for ListWorkforcesSortByOptions

func (ListWorkforcesSortByOptions) Values added in v0.29.0 

func (ListWorkforcesSortByOptions) Values() []ListWorkforcesSortByOptions

Values returns all known values for ListWorkforcesSortByOptions. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ListWorkteamsSortByOptions 

type ListWorkteamsSortByOptions string
const (
	ListWorkteamsSortByOptionsName       ListWorkteamsSortByOptions = "Name"
	ListWorkteamsSortByOptionsCreatedate ListWorkteamsSortByOptions = "CreateDate"
)

Enum values for ListWorkteamsSortByOptions

func (ListWorkteamsSortByOptions) Values added in v0.29.0 

func (ListWorkteamsSortByOptions) Values() []ListWorkteamsSortByOptions

Values returns all known values for ListWorkteamsSortByOptions. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type MemberDefinition 

type MemberDefinition struct {

	// The Amazon Cognito user group that is part of the work team.
	CognitoMemberDefinition *CognitoMemberDefinition

	// A list user groups that exist in your OIDC Identity Provider (IdP). One to ten
	// groups can be used to create a single private work team. When you add a user
	// group to the list of Groups, you can add that user group to one or more private
	// work teams. If you add a user group to a private work team, all workers in that
	// user group are added to the work team.
	OidcMemberDefinition *OidcMemberDefinition
}

Defines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.

type MetricData 

type MetricData struct {

	// The name of the metric.
	MetricName *string

	// The date and time that the algorithm emitted the metric.
	Timestamp *time.Time

	// The value of the metric.
	Value *float32
}

The name, value, and date and time of a metric that was emitted to Amazon CloudWatch.

type MetricDefinition 

type MetricDefinition struct {

	// The name of the metric.
	//
	// This member is required.
	Name *string

	// A regular expression that searches the output of a training job and gets the
	// value of the metric. For more information about using regular expressions to
	// define metrics, see Defining Objective Metrics
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics.html).
	//
	// This member is required.
	Regex *string
}

Specifies a metric that the training algorithm writes to stderr or stdout . Amazon SageMakerhyperparameter tuning captures all defined metrics. You specify one metric that a hyperparameter tuning job uses as its objective metric to choose the best training job.

type ModelArtifacts 

type ModelArtifacts struct {

	// The path of the S3 object that contains the model artifacts. For example,
	// s3://bucket-name/keynameprefix/model.tar.gz.
	//
	// This member is required.
	S3ModelArtifacts *string
}

Provides information about the location that is configured for storing model artifacts. Model artifacts are the output that results from training a model, and typically consist of trained parameters, a model defintion that desribes how to compute inferences, and other metadata.

type ModelClientConfig 

type ModelClientConfig struct {

	// The maximum number of retries when invocation requests are failing.
	InvocationsMaxRetries *int32

	// The timeout value in seconds for an invocation request.
	InvocationsTimeoutInSeconds *int32
}

Configures the timeout and maximum number of retries for processing a transform job invocation.

type ModelPackageContainerDefinition 

type ModelPackageContainerDefinition struct {

	// The Amazon EC2 Container Registry (Amazon ECR) path where inference code is
	// stored. If you are using your own custom algorithm instead of an algorithm
	// provided by Amazon SageMaker, the inference code must meet Amazon SageMaker
	// requirements. Amazon SageMaker supports both registry/repository[:tag] and
	// registry/repository[@digest] image path formats. For more information, see Using
	// Your Own Algorithms with Amazon SageMaker
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html).
	//
	// This member is required.
	Image *string

	// The DNS host name for the Docker container.
	ContainerHostname *string

	// An MD5 hash of the training algorithm that identifies the Docker image used for
	// training.
	ImageDigest *string

	// The Amazon 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 model artifacts must be in an S3 bucket that is in the
	// same region as the model package.
	ModelDataUrl *string

	// The AWS Marketplace product ID of the model package.
	ProductId *string
}

Describes the Docker container for the model package.

type ModelPackageSortBy 

type ModelPackageSortBy string
const (
	ModelPackageSortByName         ModelPackageSortBy = "Name"
	ModelPackageSortByCreationTime ModelPackageSortBy = "CreationTime"
)

Enum values for ModelPackageSortBy

func (ModelPackageSortBy) Values added in v0.29.0 

func (ModelPackageSortBy) Values() []ModelPackageSortBy

Values returns all known values for ModelPackageSortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ModelPackageStatus 

type ModelPackageStatus string
const (
	ModelPackageStatusPending    ModelPackageStatus = "Pending"
	ModelPackageStatusInProgress ModelPackageStatus = "InProgress"
	ModelPackageStatusCompleted  ModelPackageStatus = "Completed"
	ModelPackageStatusFailed     ModelPackageStatus = "Failed"
	ModelPackageStatusDeleting   ModelPackageStatus = "Deleting"
)

Enum values for ModelPackageStatus

func (ModelPackageStatus) Values added in v0.29.0 

func (ModelPackageStatus) Values() []ModelPackageStatus

Values returns all known values for ModelPackageStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ModelPackageStatusDetails 

type ModelPackageStatusDetails struct {

	// The validation status of the model package.
	//
	// This member is required.
	ValidationStatuses []*ModelPackageStatusItem

	// The status of the scan of the Docker image container for the model package.
	ImageScanStatuses []*ModelPackageStatusItem
}

Specifies the validation and image scan statuses of the model package.

type ModelPackageStatusItem 

type ModelPackageStatusItem struct {

	// The name of the model package for which the overall status is being reported.
	//
	// This member is required.
	Name *string

	// The current status.
	//
	// This member is required.
	Status DetailedModelPackageStatus

	// if the overall status is Failed, the reason for the failure.
	FailureReason *string
}

Represents the overall status of a model package.

type ModelPackageSummary 

type ModelPackageSummary struct {

	// A timestamp that shows when the model package was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the model package.
	//
	// This member is required.
	ModelPackageArn *string

	// The name of the model package.
	//
	// This member is required.
	ModelPackageName *string

	// The overall status of the model package.
	//
	// This member is required.
	ModelPackageStatus ModelPackageStatus

	// A brief description of the model package.
	ModelPackageDescription *string
}

Provides summary information about a model package.

type ModelPackageValidationProfile 

type ModelPackageValidationProfile struct {

	// The name of the profile for the model package.
	//
	// This member is required.
	ProfileName *string

	// The TransformJobDefinition object that describes the transform job used for the
	// validation of the model package.
	//
	// This member is required.
	TransformJobDefinition *TransformJobDefinition
}

Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package. The data provided in the validation profile is made available to your buyers on AWS Marketplace.

type ModelPackageValidationSpecification 

type ModelPackageValidationSpecification struct {

	// An array of ModelPackageValidationProfile objects, each of which specifies a
	// batch transform job that Amazon SageMaker runs to validate your model package.
	//
	// This member is required.
	ValidationProfiles []*ModelPackageValidationProfile

	// The IAM roles to be used for the validation of the model package.
	//
	// This member is required.
	ValidationRole *string
}

Specifies batch transform jobs that Amazon SageMaker runs to validate your model package.

type ModelSortKey 

type ModelSortKey string
const (
	ModelSortKeyName         ModelSortKey = "Name"
	ModelSortKeyCreationtime ModelSortKey = "CreationTime"
)

Enum values for ModelSortKey

func (ModelSortKey) Values added in v0.29.0 

func (ModelSortKey) Values() []ModelSortKey

Values returns all known values for ModelSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ModelSummary 

type ModelSummary struct {

	// A timestamp that indicates when the model was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the model.
	//
	// This member is required.
	ModelArn *string

	// The name of the model that you want a summary for.
	//
	// This member is required.
	ModelName *string
}

Provides summary information about a model.

type MonitoringAppSpecification 

type MonitoringAppSpecification struct {

	// The container image to be run by the monitoring job.
	//
	// This member is required.
	ImageUri *string

	// An array of arguments for the container used to run the monitoring job.
	ContainerArguments []*string

	// Specifies the entrypoint for a container used to run the monitoring job.
	ContainerEntrypoint []*string

	// An Amazon S3 URI to a script that is called after analysis has been performed.
	// Applicable only for the built-in (first party) containers.
	PostAnalyticsProcessorSourceUri *string

	// An Amazon S3 URI to a script that is called per row prior to running analysis.
	// It can base64 decode the payload and convert it into a flatted json so that the
	// built-in container can use the converted data. Applicable only for the built-in
	// (first party) containers.
	RecordPreprocessorSourceUri *string
}

Container image configuration object for the monitoring job.

type MonitoringBaselineConfig 

type MonitoringBaselineConfig struct {

	// The baseline constraint file in Amazon S3 that the current monitoring job should
	// validated against.
	ConstraintsResource *MonitoringConstraintsResource

	// The baseline statistics file in Amazon S3 that the current monitoring job should
	// be validated against.
	StatisticsResource *MonitoringStatisticsResource
}

Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.

type MonitoringClusterConfig 

type MonitoringClusterConfig struct {

	// The number of ML compute instances to use in the model monitoring job. For
	// distributed processing jobs, specify a value greater than 1. The default value
	// is 1.
	//
	// This member is required.
	InstanceCount *int32

	// The ML compute instance type for the processing job.
	//
	// This member is required.
	InstanceType ProcessingInstanceType

	// The size of the ML storage volume, in gigabytes, that you want to provision. You
	// must specify sufficient ML storage for your scenario.
	//
	// This member is required.
	VolumeSizeInGB *int32

	// The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to
	// encrypt data on the storage volume attached to the ML compute instance(s) that
	// run the model monitoring job.
	VolumeKmsKeyId *string
}

Configuration for the cluster used to run model monitoring jobs.

type MonitoringConstraintsResource 

type MonitoringConstraintsResource struct {

	// The Amazon S3 URI for the constraints resource.
	S3Uri *string
}

The constraints resource for a monitoring job.

type MonitoringExecutionSortKey 

type MonitoringExecutionSortKey string
const (
	MonitoringExecutionSortKeyCreationTime  MonitoringExecutionSortKey = "CreationTime"
	MonitoringExecutionSortKeyScheduledTime MonitoringExecutionSortKey = "ScheduledTime"
	MonitoringExecutionSortKeyStatus        MonitoringExecutionSortKey = "Status"
)

Enum values for MonitoringExecutionSortKey

func (MonitoringExecutionSortKey) Values added in v0.29.0 

func (MonitoringExecutionSortKey) Values() []MonitoringExecutionSortKey

Values returns all known values for MonitoringExecutionSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type MonitoringExecutionSummary 

type MonitoringExecutionSummary struct {

	// The time at which the monitoring job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// A timestamp that indicates the last time the monitoring job was modified.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// The status of the monitoring job.
	//
	// This member is required.
	MonitoringExecutionStatus ExecutionStatus

	// The name of the monitoring schedule.
	//
	// This member is required.
	MonitoringScheduleName *string

	// The time the monitoring job was scheduled.
	//
	// This member is required.
	ScheduledTime *time.Time

	// The name of teh endpoint used to run the monitoring job.
	EndpointName *string

	// Contains the reason a monitoring job failed, if it failed.
	FailureReason *string

	// The Amazon Resource Name (ARN) of the monitoring job.
	ProcessingJobArn *string
}

Summary of information about the last monitoring job to run.

type MonitoringInput 

type MonitoringInput struct {

	// The endpoint for a monitoring job.
	//
	// This member is required.
	EndpointInput *EndpointInput
}

The inputs for a monitoring job.

type MonitoringJobDefinition 

type MonitoringJobDefinition struct {

	// Configures the monitoring job to run a specified Docker container image.
	//
	// This member is required.
	MonitoringAppSpecification *MonitoringAppSpecification

	// The array of inputs for the monitoring job. Currently we support monitoring an
	// Amazon SageMaker Endpoint.
	//
	// This member is required.
	MonitoringInputs []*MonitoringInput

	// The array of outputs from the monitoring job to be uploaded to Amazon Simple
	// Storage Service (Amazon S3).
	//
	// This member is required.
	MonitoringOutputConfig *MonitoringOutputConfig

	// Identifies the resources, ML compute instances, and ML storage volumes to deploy
	// for a monitoring job. In distributed processing, you specify more than one
	// instance.
	//
	// This member is required.
	MonitoringResources *MonitoringResources

	// The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume
	// to perform tasks on your behalf.
	//
	// This member is required.
	RoleArn *string

	// Baseline configuration used to validate that the data conforms to the specified
	// constraints and statistics
	BaselineConfig *MonitoringBaselineConfig

	// Sets the environment variables in the Docker container.
	Environment map[string]*string

	// Specifies networking options for an monitoring job.
	NetworkConfig *NetworkConfig

	// Specifies a time limit for how long the monitoring job is allowed to run.
	StoppingCondition *MonitoringStoppingCondition
}

Defines the monitoring job.

type MonitoringOutput 

type MonitoringOutput struct {

	// The Amazon S3 storage location where the results of a monitoring job are saved.
	//
	// This member is required.
	S3Output *MonitoringS3Output
}

The output object for a monitoring job.

type MonitoringOutputConfig 

type MonitoringOutputConfig struct {

	// Monitoring outputs for monitoring jobs. This is where the output of the periodic
	// monitoring jobs is uploaded.
	//
	// This member is required.
	MonitoringOutputs []*MonitoringOutput

	// The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to
	// encrypt the model artifacts at rest using Amazon S3 server-side encryption.
	KmsKeyId *string
}

The output configuration for monitoring jobs.

type MonitoringResources 

type MonitoringResources struct {

	// The configuration for the cluster resources used to run the processing job.
	//
	// This member is required.
	ClusterConfig *MonitoringClusterConfig
}

Identifies the resources to deploy for a monitoring job.

type MonitoringS3Output 

type MonitoringS3Output struct {

	// The local path to the Amazon S3 storage location where Amazon SageMaker saves
	// the results of a monitoring job. LocalPath is an absolute path for the output
	// data.
	//
	// This member is required.
	LocalPath *string

	// A URI that identifies the Amazon S3 storage location where Amazon SageMaker
	// saves the results of a monitoring job.
	//
	// This member is required.
	S3Uri *string

	// Whether to upload the results of the monitoring job continuously or after the
	// job completes.
	S3UploadMode ProcessingS3UploadMode
}

Information about where and how you want to store the results of a monitoring job.

type MonitoringScheduleConfig 

type MonitoringScheduleConfig struct {

	// Defines the monitoring job.
	//
	// This member is required.
	MonitoringJobDefinition *MonitoringJobDefinition

	// Configures the monitoring schedule.
	ScheduleConfig *ScheduleConfig
}

Configures the monitoring schedule and defines the monitoring job.

type MonitoringScheduleSortKey 

type MonitoringScheduleSortKey string
const (
	MonitoringScheduleSortKeyName         MonitoringScheduleSortKey = "Name"
	MonitoringScheduleSortKeyCreationTime MonitoringScheduleSortKey = "CreationTime"
	MonitoringScheduleSortKeyStatus       MonitoringScheduleSortKey = "Status"
)

Enum values for MonitoringScheduleSortKey

func (MonitoringScheduleSortKey) Values added in v0.29.0 

func (MonitoringScheduleSortKey) Values() []MonitoringScheduleSortKey

Values returns all known values for MonitoringScheduleSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type MonitoringScheduleSummary 

type MonitoringScheduleSummary struct {

	// The creation time of the monitoring schedule.
	//
	// This member is required.
	CreationTime *time.Time

	// The last time the monitoring schedule was modified.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// The Amazon Resource Name (ARN) of the monitoring schedule.
	//
	// This member is required.
	MonitoringScheduleArn *string

	// The name of the monitoring schedule.
	//
	// This member is required.
	MonitoringScheduleName *string

	// The status of the monitoring schedule.
	//
	// This member is required.
	MonitoringScheduleStatus ScheduleStatus

	// The name of the endpoint using the monitoring schedule.
	EndpointName *string
}

Summarizes the monitoring schedule.

type MonitoringStatisticsResource 

type MonitoringStatisticsResource struct {

	// The Amazon S3 URI for the statistics resource.
	S3Uri *string
}

The statistics resource for a monitoring job.

type MonitoringStoppingCondition 

type MonitoringStoppingCondition struct {

	// The maximum runtime allowed in seconds.
	//
	// This member is required.
	MaxRuntimeInSeconds *int32
}

A time limit for how long the monitoring job is allowed to run before stopping.

type NestedFilters 

type NestedFilters struct {

	// A list of filters. Each filter acts on a property. Filters must contain at least
	// one Filters value. For example, a NestedFilters call might include a filter on
	// the PropertyName parameter of the InputDataConfig property:
	// InputDataConfig.DataSource.S3DataSource.S3Uri.
	//
	// This member is required.
	Filters []*Filter

	// The name of the property to use in the nested filters. The value must match a
	// listed property name, such as InputDataConfig.
	//
	// This member is required.
	NestedPropertyName *string
}

A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API. For example, to filter on a training job's InputDataConfig property with a specific channel name and S3Uri prefix, define the following filters:

* '{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}',

* '{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}'

type NetworkConfig 

type NetworkConfig struct {

	// Whether to encrypt all communications between distributed processing jobs.
	// Choose True to encrypt communications. Encryption provides greater security for
	// distributed processing jobs, but the processing might take longer.
	EnableInterContainerTrafficEncryption *bool

	// Whether to allow inbound and outbound network calls to and from the containers
	// used for the processing job.
	EnableNetworkIsolation *bool

	// Specifies a VPC that your training jobs and hosted models have access to.
	// Control access to and from your training and model containers by configuring the
	// VPC. For more information, see Protect Endpoints by Using an Amazon Virtual
	// Private Cloud (https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html)
	// and Protect Training Jobs by Using an Amazon Virtual Private Cloud
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html).
	VpcConfig *VpcConfig
}

Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.

type NotebookInstanceAcceleratorType 

type NotebookInstanceAcceleratorType string
const (
	NotebookInstanceAcceleratorTypeMlEia1Medium NotebookInstanceAcceleratorType = "ml.eia1.medium"
	NotebookInstanceAcceleratorTypeMlEia1Large  NotebookInstanceAcceleratorType = "ml.eia1.large"
	NotebookInstanceAcceleratorTypeMlEia1Xlarge NotebookInstanceAcceleratorType = "ml.eia1.xlarge"
	NotebookInstanceAcceleratorTypeMlEia2Medium NotebookInstanceAcceleratorType = "ml.eia2.medium"
	NotebookInstanceAcceleratorTypeMlEia2Large  NotebookInstanceAcceleratorType = "ml.eia2.large"
	NotebookInstanceAcceleratorTypeMlEia2Xlarge NotebookInstanceAcceleratorType = "ml.eia2.xlarge"
)

Enum values for NotebookInstanceAcceleratorType

func (NotebookInstanceAcceleratorType) Values added in v0.29.0 

func (NotebookInstanceAcceleratorType) Values() []NotebookInstanceAcceleratorType

Values returns all known values for NotebookInstanceAcceleratorType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type NotebookInstanceLifecycleConfigSortKey 

type NotebookInstanceLifecycleConfigSortKey string
const (
	NotebookInstanceLifecycleConfigSortKeyName             NotebookInstanceLifecycleConfigSortKey = "Name"
	NotebookInstanceLifecycleConfigSortKeyCreationTime     NotebookInstanceLifecycleConfigSortKey = "CreationTime"
	NotebookInstanceLifecycleConfigSortKeyLastModifiedTime NotebookInstanceLifecycleConfigSortKey = "LastModifiedTime"
)

Enum values for NotebookInstanceLifecycleConfigSortKey

func (NotebookInstanceLifecycleConfigSortKey) Values added in v0.29.0 

func (NotebookInstanceLifecycleConfigSortKey) Values() []NotebookInstanceLifecycleConfigSortKey

Values returns all known values for NotebookInstanceLifecycleConfigSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type NotebookInstanceLifecycleConfigSortOrder 

type NotebookInstanceLifecycleConfigSortOrder string
const (
	NotebookInstanceLifecycleConfigSortOrderAscending  NotebookInstanceLifecycleConfigSortOrder = "Ascending"
	NotebookInstanceLifecycleConfigSortOrderDescending NotebookInstanceLifecycleConfigSortOrder = "Descending"
)

Enum values for NotebookInstanceLifecycleConfigSortOrder

func (NotebookInstanceLifecycleConfigSortOrder) Values added in v0.29.0 

func (NotebookInstanceLifecycleConfigSortOrder) Values() []NotebookInstanceLifecycleConfigSortOrder

Values returns all known values for NotebookInstanceLifecycleConfigSortOrder. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type NotebookInstanceLifecycleConfigSummary 

type NotebookInstanceLifecycleConfigSummary struct {

	// The Amazon Resource Name (ARN) of the lifecycle configuration.
	//
	// This member is required.
	NotebookInstanceLifecycleConfigArn *string

	// The name of the lifecycle configuration.
	//
	// This member is required.
	NotebookInstanceLifecycleConfigName *string

	// A timestamp that tells when the lifecycle configuration was created.
	CreationTime *time.Time

	// A timestamp that tells when the lifecycle configuration was last modified.
	LastModifiedTime *time.Time
}

Provides a summary of a notebook instance lifecycle configuration.

type NotebookInstanceLifecycleHook 

type NotebookInstanceLifecycleHook struct {

	// A base64-encoded string that contains a shell script for a notebook instance
	// lifecycle configuration.
	Content *string
}

Contains the notebook instance lifecycle configuration script. Each lifecycle configuration script has a limit of 16384 characters. The value of the $PATH environment variable that is available to both scripts is /sbin:bin:/usr/sbin:/usr/bin. View CloudWatch Logs for notebook instance lifecycle configurations in log group /aws/sagemaker/NotebookInstances in log stream [notebook-instance-name]/[LifecycleConfigHook]. Lifecycle configuration scripts cannot run for longer than 5 minutes. If a script runs for longer than 5 minutes, it fails and the notebook instance is not created or started. For information about notebook instance lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance (https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html).

type NotebookInstanceSortKey 

type NotebookInstanceSortKey string
const (
	NotebookInstanceSortKeyName         NotebookInstanceSortKey = "Name"
	NotebookInstanceSortKeyCreationTime NotebookInstanceSortKey = "CreationTime"
	NotebookInstanceSortKeyStatus       NotebookInstanceSortKey = "Status"
)

Enum values for NotebookInstanceSortKey

func (NotebookInstanceSortKey) Values added in v0.29.0 

func (NotebookInstanceSortKey) Values() []NotebookInstanceSortKey

Values returns all known values for NotebookInstanceSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type NotebookInstanceSortOrder 

type NotebookInstanceSortOrder string
const (
	NotebookInstanceSortOrderAscending  NotebookInstanceSortOrder = "Ascending"
	NotebookInstanceSortOrderDescending NotebookInstanceSortOrder = "Descending"
)

Enum values for NotebookInstanceSortOrder

func (NotebookInstanceSortOrder) Values added in v0.29.0 

func (NotebookInstanceSortOrder) Values() []NotebookInstanceSortOrder

Values returns all known values for NotebookInstanceSortOrder. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type NotebookInstanceStatus 

type NotebookInstanceStatus string
const (
	NotebookInstanceStatusPending   NotebookInstanceStatus = "Pending"
	NotebookInstanceStatusInservice NotebookInstanceStatus = "InService"
	NotebookInstanceStatusStopping  NotebookInstanceStatus = "Stopping"
	NotebookInstanceStatusStopped   NotebookInstanceStatus = "Stopped"
	NotebookInstanceStatusFailed    NotebookInstanceStatus = "Failed"
	NotebookInstanceStatusDeleting  NotebookInstanceStatus = "Deleting"
	NotebookInstanceStatusUpdating  NotebookInstanceStatus = "Updating"
)

Enum values for NotebookInstanceStatus

func (NotebookInstanceStatus) Values added in v0.29.0 

func (NotebookInstanceStatus) Values() []NotebookInstanceStatus

Values returns all known values for NotebookInstanceStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type NotebookInstanceSummary 

type NotebookInstanceSummary struct {

	// The Amazon Resource Name (ARN) of the notebook instance.
	//
	// This member is required.
	NotebookInstanceArn *string

	// The name of the notebook instance that you want a summary for.
	//
	// This member is required.
	NotebookInstanceName *string

	// An array of up to three Git repositories associated with the notebook instance.
	// These can be either the names of Git repositories stored as resources in your
	// account, or the URL of Git repositories in AWS CodeCommit
	// (https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any
	// other Git repository. These repositories are cloned at the same level as the
	// default repository of your notebook instance. For more information, see
	// Associating Git Repositories with Amazon SageMaker Notebook Instances
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html).
	AdditionalCodeRepositories []*string

	// A timestamp that shows when the notebook instance was created.
	CreationTime *time.Time

	// The Git repository associated with the notebook instance as its default code
	// repository. This can be either the name of a Git repository stored as a resource
	// in your account, or the URL of a Git repository in AWS CodeCommit
	// (https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any
	// other Git repository. When you open a notebook instance, it opens in the
	// directory that contains this repository. For more information, see Associating
	// Git Repositories with Amazon SageMaker Notebook Instances
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html).
	DefaultCodeRepository *string

	// The type of ML compute instance that the notebook instance is running on.
	InstanceType InstanceType

	// A timestamp that shows when the notebook instance was last modified.
	LastModifiedTime *time.Time

	// The name of a notebook instance lifecycle configuration associated with this
	// notebook instance. For information about notebook instance lifestyle
	// configurations, see Step 2.1: (Optional) Customize a Notebook Instance
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html).
	NotebookInstanceLifecycleConfigName *string

	// The status of the notebook instance.
	NotebookInstanceStatus NotebookInstanceStatus

	// The URL that you use to connect to the Jupyter instance running in your notebook
	// instance.
	Url *string
}

Provides summary information for an Amazon SageMaker notebook instance.

type NotebookOutputOption 

type NotebookOutputOption string
const (
	NotebookOutputOptionAllowed  NotebookOutputOption = "Allowed"
	NotebookOutputOptionDisabled NotebookOutputOption = "Disabled"
)

Enum values for NotebookOutputOption

func (NotebookOutputOption) Values added in v0.29.0 

func (NotebookOutputOption) Values() []NotebookOutputOption

Values returns all known values for NotebookOutputOption. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type NotificationConfiguration 

type NotificationConfiguration struct {

	// The ARN for the SNS topic to which notifications should be published.
	NotificationTopicArn *string
}

Configures SNS notifications of available or expiring work items for work teams.

type ObjectiveStatus 

type ObjectiveStatus string
const (
	ObjectiveStatusSucceeded ObjectiveStatus = "Succeeded"
	ObjectiveStatusPending   ObjectiveStatus = "Pending"
	ObjectiveStatusFailed    ObjectiveStatus = "Failed"
)

Enum values for ObjectiveStatus

func (ObjectiveStatus) Values added in v0.29.0 

func (ObjectiveStatus) Values() []ObjectiveStatus

Values returns all known values for ObjectiveStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ObjectiveStatusCounters 

type ObjectiveStatusCounters struct {

	// The number of training jobs whose final objective metric was not evaluated and
	// used in the hyperparameter tuning process. This typically occurs when the
	// training job failed or did not emit an objective metric.
	Failed *int32

	// The number of training jobs that are in progress and pending evaluation of their
	// final objective metric.
	Pending *int32

	// The number of training jobs whose final objective metric was evaluated by the
	// hyperparameter tuning job and used in the hyperparameter tuning process.
	Succeeded *int32
}

Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.

type OidcConfig 

type OidcConfig struct {

	// The OIDC IdP authorization endpoint used to configure your private workforce.
	//
	// This member is required.
	AuthorizationEndpoint *string

	// The OIDC IdP client ID used to configure your private workforce.
	//
	// This member is required.
	ClientId *string

	// The OIDC IdP client secret used to configure your private workforce.
	//
	// This member is required.
	ClientSecret *string

	// The OIDC IdP issuer used to configure your private workforce.
	//
	// This member is required.
	Issuer *string

	// The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private
	// workforce.
	//
	// This member is required.
	JwksUri *string

	// The OIDC IdP logout endpoint used to configure your private workforce.
	//
	// This member is required.
	LogoutEndpoint *string

	// The OIDC IdP token endpoint used to configure your private workforce.
	//
	// This member is required.
	TokenEndpoint *string

	// The OIDC IdP user information endpoint used to configure your private workforce.
	//
	// This member is required.
	UserInfoEndpoint *string
}

Use this parameter to configure your OIDC Identity Provider (IdP).

type OidcConfigForResponse 

type OidcConfigForResponse struct {

	// The OIDC IdP authorization endpoint used to configure your private workforce.
	AuthorizationEndpoint *string

	// The OIDC IdP client ID used to configure your private workforce.
	ClientId *string

	// The OIDC IdP issuer used to configure your private workforce.
	Issuer *string

	// The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your private
	// workforce.
	JwksUri *string

	// The OIDC IdP logout endpoint used to configure your private workforce.
	LogoutEndpoint *string

	// The OIDC IdP token endpoint used to configure your private workforce.
	TokenEndpoint *string

	// The OIDC IdP user information endpoint used to configure your private workforce.
	UserInfoEndpoint *string
}

Your OIDC IdP workforce configuration.

type OidcMemberDefinition 

type OidcMemberDefinition struct {

	// A list of comma seperated strings that identifies user groups in your OIDC IdP.
	// Each user group is made up of a group of private workers.
	//
	// This member is required.
	Groups []*string
}

A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.

type Operator 

type Operator string
const (
	OperatorEquals               Operator = "Equals"
	OperatorNotEquals            Operator = "NotEquals"
	OperatorGreaterThan          Operator = "GreaterThan"
	OperatorGreaterThanOrEqualTo Operator = "GreaterThanOrEqualTo"
	OperatorLessThan             Operator = "LessThan"
	OperatorLessThanOrEqualTo    Operator = "LessThanOrEqualTo"
	OperatorContains             Operator = "Contains"
	OperatorExists               Operator = "Exists"
	OperatorNotExists            Operator = "NotExists"
	OperatorIn                   Operator = "In"
)

Enum values for Operator

func (Operator) Values added in v0.29.0 

func (Operator) Values() []Operator

Values returns all known values for Operator. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type OrderKey 

type OrderKey string
const (
	OrderKeyAscending  OrderKey = "Ascending"
	OrderKeyDescending OrderKey = "Descending"
)

Enum values for OrderKey

func (OrderKey) Values added in v0.29.0 

func (OrderKey) Values() []OrderKey

Values returns all known values for OrderKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type OutputConfig 

type OutputConfig struct {

	// Identifies the S3 bucket where you want Amazon SageMaker to store the model
	// artifacts. For example, s3://bucket-name/key-name-prefix.
	//
	// This member is required.
	S3OutputLocation *string

	// Specifies additional parameters for compiler options in JSON format. The
	// compiler options are TargetPlatform specific. It is required for NVIDIA
	// accelerators and highly recommended for CPU compilations. For any other cases,
	// it is optional to specify CompilerOptions.
	//
	// * CPU: Compilation for CPU supports
	// the following compiler options.
	//
	// * mcpu: CPU micro-architecture. For example,
	// {'mcpu': 'skylake-avx512'}
	//
	// * mattr: CPU flags. For example, {'mattr': ['+neon',
	// '+vfpv4']}
	//
	// * ARM: Details of ARM CPU compilations.
	//
	// * NEON: NEON is an
	// implementation of the Advanced SIMD extension used in ARMv7 processors. For
	// example, add {'mattr': ['+neon']} to the compiler options if compiling for ARM
	// 32-bit platform with the NEON support.
	//
	// * NVIDIA: Compilation for NVIDIA GPU
	// supports the following compiler options.
	//
	// * gpu_code: Specifies the targeted
	// architecture.
	//
	// * trt-ver: Specifies the TensorRT versions in x.y.z. format.
	//
	// *
	// cuda-ver: Specifies the CUDA version in x.y format.
	//
	// For example, {'gpu-code':
	// 'sm_72', 'trt-ver': '6.0.1', 'cuda-ver': '10.1'}
	//
	// * ANDROID: Compilation for the
	// Android OS supports the following compiler options:
	//
	// * ANDROID_PLATFORM:
	// Specifies the Android API levels. Available levels range from 21 to 29. For
	// example, {'ANDROID_PLATFORM': 28}.
	//
	// * mattr: Add {'mattr': ['+neon']} to
	// compiler options if compiling for ARM 32-bit platform with NEON support.
	//
	// *
	// INFERENTIA: Compilation for target ml_inf1 uses compiler options passed in as a
	// JSON string. For example, "CompilerOptions": "\"--verbose 1 --num-neuroncores 2
	// -O2\"". For information about supported compiler options, see  Neuron Compiler
	// CLI
	// (https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-cc/command-line-reference.md).
	//
	// *
	// CoreML: Compilation for the CoreML OutputConfig$TargetDevice supports the
	// following compiler options:
	//
	// * class_labels: Specifies the classification labels
	// file name inside input tar.gz file. For example, {"class_labels":
	// "imagenet_labels_1000.txt"}. Labels inside the txt file should be separated by
	// newlines.
	CompilerOptions *string

	// Identifies the target device or the machine learning instance that you want to
	// run your model on after the compilation has completed. Alternatively, you can
	// specify OS, architecture, and accelerator using TargetPlatform fields. It can be
	// used instead of TargetPlatform.
	TargetDevice TargetDevice

	// Contains information about a target platform that you want your model to run on,
	// such as OS, architecture, and accelerators. It is an alternative of
	// TargetDevice. The following examples show how to configure the TargetPlatform
	// and CompilerOptions JSON strings for popular target platforms:
	//
	// * Raspberry Pi 3
	// Model B+ "TargetPlatform": {"Os": "LINUX", "Arch": "ARM_EABIHF"},
	// "CompilerOptions": {'mattr': ['+neon']}
	//
	// * Jetson TX2 "TargetPlatform": {"Os":
	// "LINUX", "Arch": "ARM64", "Accelerator": "NVIDIA"}, "CompilerOptions":
	// {'gpu-code': 'sm_62', 'trt-ver': '6.0.1', 'cuda-ver': '10.0'}
	//
	// * EC2 m5.2xlarge
	// instance OS "TargetPlatform": {"Os": "LINUX", "Arch": "X86_64", "Accelerator":
	// "NVIDIA"}, "CompilerOptions": {'mcpu': 'skylake-avx512'}
	//
	// * RK3399
	// "TargetPlatform": {"Os": "LINUX", "Arch": "ARM64", "Accelerator": "MALI"}
	//
	// *
	// ARMv7 phone (CPU) "TargetPlatform": {"Os": "ANDROID", "Arch": "ARM_EABI"},
	// "CompilerOptions": {'ANDROID_PLATFORM': 25, 'mattr': ['+neon']}
	//
	// * ARMv8 phone
	// (CPU) "TargetPlatform": {"Os": "ANDROID", "Arch": "ARM64"}, "CompilerOptions":
	// {'ANDROID_PLATFORM': 29}
	TargetPlatform *TargetPlatform
}

Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.

type OutputDataConfig 

type OutputDataConfig struct {

	// Identifies the S3 path where you want Amazon SageMaker to store the model
	// artifacts. For example, s3://bucket-name/key-name-prefix.
	//
	// This member is required.
	S3OutputPath *string

	// The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to
	// encrypt the model artifacts at rest using Amazon S3 server-side encryption. The
	// KmsKeyId can be any of the following formats:
	//
	// * // KMS Key ID
	// "1234abcd-12ab-34cd-56ef-1234567890ab"
	//
	// * // Amazon Resource Name (ARN) of a KMS
	// Key
	// "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
	//
	// *
	// // KMS Key Alias "alias/ExampleAlias"
	//
	// * // Amazon Resource Name (ARN) of a KMS
	// Key Alias "arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
	//
	// If you use a
	// KMS key ID or an alias of your master key, the Amazon SageMaker execution role
	// must include permissions to call kms:Encrypt. If you don't provide a KMS key ID,
	// Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account.
	// Amazon SageMaker uses server-side encryption with KMS-managed keys for
	// OutputDataConfig. If you use a bucket policy with an s3:PutObject permission
	// that only allows objects with server-side encryption, set the condition key of
	// s3:x-amz-server-side-encryption to "aws:kms". For more information, see
	// KMS-Managed Encryption Keys
	// (https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html) in the
	// Amazon Simple Storage Service Developer Guide. The KMS key policy must grant
	// permission to the IAM role that you specify in your CreateTrainingJob,
	// CreateTransformJob, or CreateHyperParameterTuningJob requests. For more
	// information, see Using Key Policies in AWS KMS
	// (http://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html) in the
	// AWS Key Management Service Developer Guide.
	KmsKeyId *string
}

Provides information about how to store model training results (model artifacts).

type ParameterRange 

type ParameterRange struct {

	// A CategoricalParameterRangeSpecification object that defines the possible values
	// for a categorical hyperparameter.
	CategoricalParameterRangeSpecification *CategoricalParameterRangeSpecification

	// A ContinuousParameterRangeSpecification object that defines the possible values
	// for a continuous hyperparameter.
	ContinuousParameterRangeSpecification *ContinuousParameterRangeSpecification

	// A IntegerParameterRangeSpecification object that defines the possible values for
	// an integer hyperparameter.
	IntegerParameterRangeSpecification *IntegerParameterRangeSpecification
}

Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.

type ParameterRanges 

type ParameterRanges struct {

	// The array of CategoricalParameterRange objects that specify ranges of
	// categorical hyperparameters that a hyperparameter tuning job searches.
	CategoricalParameterRanges []*CategoricalParameterRange

	// The array of ContinuousParameterRange objects that specify ranges of continuous
	// hyperparameters that a hyperparameter tuning job searches.
	ContinuousParameterRanges []*ContinuousParameterRange

	// The array of IntegerParameterRange objects that specify ranges of integer
	// hyperparameters that a hyperparameter tuning job searches.
	IntegerParameterRanges []*IntegerParameterRange
}

Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job. You can specify a maximum of 20 hyperparameters that a hyperparameter tuning job can search over. Every possible value of a categorical parameter range counts against this limit.

type ParameterType 

type ParameterType string
const (
	ParameterTypeInteger     ParameterType = "Integer"
	ParameterTypeContinuous  ParameterType = "Continuous"
	ParameterTypeCategorical ParameterType = "Categorical"
	ParameterTypeFreeText    ParameterType = "FreeText"
)

Enum values for ParameterType

func (ParameterType) Values added in v0.29.0 

func (ParameterType) Values() []ParameterType

Values returns all known values for ParameterType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type Parent 

type Parent struct {

	// The name of the experiment.
	ExperimentName *string

	// The name of the trial.
	TrialName *string
}

The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.

type ParentHyperParameterTuningJob 

type ParentHyperParameterTuningJob struct {

	// The name of the hyperparameter tuning job to be used as a starting point for a
	// new hyperparameter tuning job.
	HyperParameterTuningJobName *string
}

A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.

type ProblemType 

type ProblemType string
const (
	ProblemTypeBinaryClassification     ProblemType = "BinaryClassification"
	ProblemTypeMulticlassClassification ProblemType = "MulticlassClassification"
	ProblemTypeRegression               ProblemType = "Regression"
)

Enum values for ProblemType

func (ProblemType) Values added in v0.29.0 

func (ProblemType) Values() []ProblemType

Values returns all known values for ProblemType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProcessingClusterConfig 

type ProcessingClusterConfig struct {

	// The number of ML compute instances to use in the processing job. For distributed
	// processing jobs, specify a value greater than 1. The default value is 1.
	//
	// This member is required.
	InstanceCount *int32

	// The ML compute instance type for the processing job.
	//
	// This member is required.
	InstanceType ProcessingInstanceType

	// The size of the ML storage volume in gigabytes that you want to provision. You
	// must specify sufficient ML storage for your scenario.
	//
	// This member is required.
	VolumeSizeInGB *int32

	// The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to
	// encrypt data on the storage volume attached to the ML compute instance(s) that
	// run the processing job.
	VolumeKmsKeyId *string
}

Configuration for the cluster used to run a processing job.

type ProcessingInput 

type ProcessingInput struct {

	// The name of the inputs for the processing job.
	//
	// This member is required.
	InputName *string

	// The S3 inputs for the processing job.
	//
	// This member is required.
	S3Input *ProcessingS3Input
}

The inputs for a processing job.

type ProcessingInstanceType 

type ProcessingInstanceType string
const (
	ProcessingInstanceTypeMlT3Medium   ProcessingInstanceType = "ml.t3.medium"
	ProcessingInstanceTypeMlT3Large    ProcessingInstanceType = "ml.t3.large"
	ProcessingInstanceTypeMlT3Xlarge   ProcessingInstanceType = "ml.t3.xlarge"
	ProcessingInstanceTypeMlT32xlarge  ProcessingInstanceType = "ml.t3.2xlarge"
	ProcessingInstanceTypeMlM4Xlarge   ProcessingInstanceType = "ml.m4.xlarge"
	ProcessingInstanceTypeMlM42xlarge  ProcessingInstanceType = "ml.m4.2xlarge"
	ProcessingInstanceTypeMlM44xlarge  ProcessingInstanceType = "ml.m4.4xlarge"
	ProcessingInstanceTypeMlM410xlarge ProcessingInstanceType = "ml.m4.10xlarge"
	ProcessingInstanceTypeMlM416xlarge ProcessingInstanceType = "ml.m4.16xlarge"
	ProcessingInstanceTypeMlC4Xlarge   ProcessingInstanceType = "ml.c4.xlarge"
	ProcessingInstanceTypeMlC42xlarge  ProcessingInstanceType = "ml.c4.2xlarge"
	ProcessingInstanceTypeMlC44xlarge  ProcessingInstanceType = "ml.c4.4xlarge"
	ProcessingInstanceTypeMlC48xlarge  ProcessingInstanceType = "ml.c4.8xlarge"
	ProcessingInstanceTypeMlP2Xlarge   ProcessingInstanceType = "ml.p2.xlarge"
	ProcessingInstanceTypeMlP28xlarge  ProcessingInstanceType = "ml.p2.8xlarge"
	ProcessingInstanceTypeMlP216xlarge ProcessingInstanceType = "ml.p2.16xlarge"
	ProcessingInstanceTypeMlP32xlarge  ProcessingInstanceType = "ml.p3.2xlarge"
	ProcessingInstanceTypeMlP38xlarge  ProcessingInstanceType = "ml.p3.8xlarge"
	ProcessingInstanceTypeMlP316xlarge ProcessingInstanceType = "ml.p3.16xlarge"
	ProcessingInstanceTypeMlC5Xlarge   ProcessingInstanceType = "ml.c5.xlarge"
	ProcessingInstanceTypeMlC52xlarge  ProcessingInstanceType = "ml.c5.2xlarge"
	ProcessingInstanceTypeMlC54xlarge  ProcessingInstanceType = "ml.c5.4xlarge"
	ProcessingInstanceTypeMlC59xlarge  ProcessingInstanceType = "ml.c5.9xlarge"
	ProcessingInstanceTypeMlC518xlarge ProcessingInstanceType = "ml.c5.18xlarge"
	ProcessingInstanceTypeMlM5Large    ProcessingInstanceType = "ml.m5.large"
	ProcessingInstanceTypeMlM5Xlarge   ProcessingInstanceType = "ml.m5.xlarge"
	ProcessingInstanceTypeMlM52xlarge  ProcessingInstanceType = "ml.m5.2xlarge"
	ProcessingInstanceTypeMlM54xlarge  ProcessingInstanceType = "ml.m5.4xlarge"
	ProcessingInstanceTypeMlM512xlarge ProcessingInstanceType = "ml.m5.12xlarge"
	ProcessingInstanceTypeMlM524xlarge ProcessingInstanceType = "ml.m5.24xlarge"
	ProcessingInstanceTypeMlR5Large    ProcessingInstanceType = "ml.r5.large"
	ProcessingInstanceTypeMlR5Xlarge   ProcessingInstanceType = "ml.r5.xlarge"
	ProcessingInstanceTypeMlR52xlarge  ProcessingInstanceType = "ml.r5.2xlarge"
	ProcessingInstanceTypeMlR54xlarge  ProcessingInstanceType = "ml.r5.4xlarge"
	ProcessingInstanceTypeMlR58xlarge  ProcessingInstanceType = "ml.r5.8xlarge"
	ProcessingInstanceTypeMlR512xlarge ProcessingInstanceType = "ml.r5.12xlarge"
	ProcessingInstanceTypeMlR516xlarge ProcessingInstanceType = "ml.r5.16xlarge"
	ProcessingInstanceTypeMlR524xlarge ProcessingInstanceType = "ml.r5.24xlarge"
)

Enum values for ProcessingInstanceType

func (ProcessingInstanceType) Values added in v0.29.0 

func (ProcessingInstanceType) Values() []ProcessingInstanceType

Values returns all known values for ProcessingInstanceType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProcessingJob 

type ProcessingJob struct {

	// Configuration to run a processing job in a specified container image.
	AppSpecification *AppSpecification

	// The Amazon Resource Name (ARN) of the AutoML job associated with this processing
	// job.
	AutoMLJobArn *string

	// The time the processing job was created.
	CreationTime *time.Time

	// Sets the environment variables in the Docker container.
	Environment map[string]*string

	// A string, up to one KB in size, that contains metadata from the processing
	// container when the processing job exits.
	ExitMessage *string

	// Associates a SageMaker job as a trial component with an experiment and trial.
	// Specified when you call the following APIs:
	//
	// * CreateProcessingJob
	//
	// *
	// CreateTrainingJob
	//
	// * CreateTransformJob
	ExperimentConfig *ExperimentConfig

	// A string, up to one KB in size, that contains the reason a processing job
	// failed, if it failed.
	FailureReason *string

	// The time the processing job was last modified.
	LastModifiedTime *time.Time

	// The ARN of a monitoring schedule for an endpoint associated with this processing
	// job.
	MonitoringScheduleArn *string

	// Networking options for a job, such as network traffic encryption between
	// containers, whether to allow inbound and outbound network calls to and from
	// containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
	NetworkConfig *NetworkConfig

	// The time that the processing job ended.
	ProcessingEndTime *time.Time

	// For each input, data is downloaded from S3 into the processing container before
	// the processing job begins running if "S3InputMode" is set to File.
	ProcessingInputs []*ProcessingInput

	// The ARN of the processing job.
	ProcessingJobArn *string

	// The name of the processing job.
	ProcessingJobName *string

	// The status of the processing job.
	ProcessingJobStatus ProcessingJobStatus

	// The output configuration for the processing job.
	ProcessingOutputConfig *ProcessingOutputConfig

	// Identifies the resources, ML compute instances, and ML storage volumes to deploy
	// for a processing job. In distributed training, you specify more than one
	// instance.
	ProcessingResources *ProcessingResources

	// The time that the processing job started.
	ProcessingStartTime *time.Time

	// The ARN of the role used to create the processing job.
	RoleArn *string

	// Specifies a time limit for how long the processing job is allowed to run.
	StoppingCondition *ProcessingStoppingCondition

	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*Tag

	// The ARN of the training job associated with this processing job.
	TrainingJobArn *string
}

An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models (https://docs.aws.amazon.com/sagemaker/latest/dg/processing-job.html).

type ProcessingJobStatus 

type ProcessingJobStatus string
const (
	ProcessingJobStatusInProgress ProcessingJobStatus = "InProgress"
	ProcessingJobStatusCompleted  ProcessingJobStatus = "Completed"
	ProcessingJobStatusFailed     ProcessingJobStatus = "Failed"
	ProcessingJobStatusStopping   ProcessingJobStatus = "Stopping"
	ProcessingJobStatusStopped    ProcessingJobStatus = "Stopped"
)

Enum values for ProcessingJobStatus

func (ProcessingJobStatus) Values added in v0.29.0 

func (ProcessingJobStatus) Values() []ProcessingJobStatus

Values returns all known values for ProcessingJobStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProcessingJobSummary 

type ProcessingJobSummary struct {

	// The time at which the processing job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the processing job..
	//
	// This member is required.
	ProcessingJobArn *string

	// The name of the processing job.
	//
	// This member is required.
	ProcessingJobName *string

	// The status of the processing job.
	//
	// This member is required.
	ProcessingJobStatus ProcessingJobStatus

	// An optional string, up to one KB in size, that contains metadata from the
	// processing container when the processing job exits.
	ExitMessage *string

	// A string, up to one KB in size, that contains the reason a processing job
	// failed, if it failed.
	FailureReason *string

	// A timestamp that indicates the last time the processing job was modified.
	LastModifiedTime *time.Time

	// The time at which the processing job completed.
	ProcessingEndTime *time.Time
}

Summary of information about a processing job.

type ProcessingOutput 

type ProcessingOutput struct {

	// The name for the processing job output.
	//
	// This member is required.
	OutputName *string

	// Configuration for processing job outputs in Amazon S3.
	//
	// This member is required.
	S3Output *ProcessingS3Output
}

Describes the results of a processing job.

type ProcessingOutputConfig 

type ProcessingOutputConfig struct {

	// Output configuration information for a processing job.
	//
	// This member is required.
	Outputs []*ProcessingOutput

	// The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to
	// encrypt the processing job output. KmsKeyId can be an ID of a KMS key, ARN of a
	// KMS key, alias of a KMS key, or alias of a KMS key. The KmsKeyId is applied to
	// all outputs.
	KmsKeyId *string
}

The output configuration for the processing job.

type ProcessingResources 

type ProcessingResources struct {

	// The configuration for the resources in a cluster used to run the processing job.
	//
	// This member is required.
	ClusterConfig *ProcessingClusterConfig
}

Identifies the resources, ML compute instances, and ML storage volumes to deploy for a processing job. In distributed training, you specify more than one instance.

type ProcessingS3CompressionType 

type ProcessingS3CompressionType string
const (
	ProcessingS3CompressionTypeNone ProcessingS3CompressionType = "None"
	ProcessingS3CompressionTypeGzip ProcessingS3CompressionType = "Gzip"
)

Enum values for ProcessingS3CompressionType

func (ProcessingS3CompressionType) Values added in v0.29.0 

func (ProcessingS3CompressionType) Values() []ProcessingS3CompressionType

Values returns all known values for ProcessingS3CompressionType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProcessingS3DataDistributionType 

type ProcessingS3DataDistributionType string
const (
	ProcessingS3DataDistributionTypeFullyreplicated ProcessingS3DataDistributionType = "FullyReplicated"
	ProcessingS3DataDistributionTypeShardedbys3key  ProcessingS3DataDistributionType = "ShardedByS3Key"
)

Enum values for ProcessingS3DataDistributionType

func (ProcessingS3DataDistributionType) Values added in v0.29.0 

func (ProcessingS3DataDistributionType) Values() []ProcessingS3DataDistributionType

Values returns all known values for ProcessingS3DataDistributionType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProcessingS3DataType 

type ProcessingS3DataType string
const (
	ProcessingS3DataTypeManifestFile ProcessingS3DataType = "ManifestFile"
	ProcessingS3DataTypeS3Prefix     ProcessingS3DataType = "S3Prefix"
)

Enum values for ProcessingS3DataType

func (ProcessingS3DataType) Values added in v0.29.0 

func (ProcessingS3DataType) Values() []ProcessingS3DataType

Values returns all known values for ProcessingS3DataType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProcessingS3Input 

type ProcessingS3Input struct {

	// The local path to the Amazon S3 bucket where you want Amazon SageMaker to
	// download the inputs to run a processing job. LocalPath is an absolute path to
	// the input data.
	//
	// This member is required.
	LocalPath *string

	// Whether you use an S3Prefix or a ManifestFile for the data type. If you choose
	// S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker uses all objects
	// with the specified key name prefix for the processing job. If you choose
	// ManifestFile, S3Uri identifies an object that is a manifest file containing a
	// list of object keys that you want Amazon SageMaker to use for the processing
	// job.
	//
	// This member is required.
	S3DataType ProcessingS3DataType

	// Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies
	// the data from the input source onto the local Amazon Elastic Block Store (Amazon
	// EBS) volumes before starting your training algorithm. This is the most commonly
	// used input mode. In Pipe mode, Amazon SageMaker streams input data from the
	// source directly to your algorithm without using the EBS volume.
	//
	// This member is required.
	S3InputMode ProcessingS3InputMode

	// The URI for the Amazon S3 storage where you want Amazon SageMaker to download
	// the artifacts needed to run a processing job.
	//
	// This member is required.
	S3Uri *string

	// Whether to use Gzip compression for Amazon S3 storage.
	S3CompressionType ProcessingS3CompressionType

	// Whether the data stored in Amazon S3 is FullyReplicated or ShardedByS3Key.
	S3DataDistributionType ProcessingS3DataDistributionType
}

Information about where and how you want to obtain the inputs for an processing job.

type ProcessingS3InputMode 

type ProcessingS3InputMode string
const (
	ProcessingS3InputModePipe ProcessingS3InputMode = "Pipe"
	ProcessingS3InputModeFile ProcessingS3InputMode = "File"
)

Enum values for ProcessingS3InputMode

func (ProcessingS3InputMode) Values added in v0.29.0 

func (ProcessingS3InputMode) Values() []ProcessingS3InputMode

Values returns all known values for ProcessingS3InputMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProcessingS3Output 

type ProcessingS3Output struct {

	// The local path to the Amazon S3 bucket where you want Amazon SageMaker to save
	// the results of an processing job. LocalPath is an absolute path to the input
	// data.
	//
	// This member is required.
	LocalPath *string

	// Whether to upload the results of the processing job continuously or after the
	// job completes.
	//
	// This member is required.
	S3UploadMode ProcessingS3UploadMode

	// A URI that identifies the Amazon S3 bucket where you want Amazon SageMaker to
	// save the results of a processing job.
	//
	// This member is required.
	S3Uri *string
}

Information about where and how you want to store the results of an processing job.

type ProcessingS3UploadMode 

type ProcessingS3UploadMode string
const (
	ProcessingS3UploadModeContinuous ProcessingS3UploadMode = "Continuous"
	ProcessingS3UploadModeEndOfJob   ProcessingS3UploadMode = "EndOfJob"
)

Enum values for ProcessingS3UploadMode

func (ProcessingS3UploadMode) Values added in v0.29.0 

func (ProcessingS3UploadMode) Values() []ProcessingS3UploadMode

Values returns all known values for ProcessingS3UploadMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProcessingStoppingCondition 

type ProcessingStoppingCondition struct {

	// Specifies the maximum runtime in seconds.
	//
	// This member is required.
	MaxRuntimeInSeconds *int32
}

Specifies a time limit for how long the processing job is allowed to run.

type ProductionVariant 

type ProductionVariant struct {

	// Number of instances to launch initially.
	//
	// This member is required.
	InitialInstanceCount *int32

	// The ML compute instance type.
	//
	// This member is required.
	InstanceType ProductionVariantInstanceType

	// The name of the model that you want to host. This is the name that you specified
	// when creating the model.
	//
	// This member is required.
	ModelName *string

	// The name of the production variant.
	//
	// This member is required.
	VariantName *string

	// The size of the Elastic Inference (EI) instance to use for the production
	// variant. EI instances provide on-demand GPU computing for inference. For more
	// information, see Using Elastic Inference in Amazon SageMaker
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html).
	AcceleratorType ProductionVariantAcceleratorType

	// Determines initial traffic distribution among all of the models that you specify
	// in the endpoint configuration. The traffic to a production variant is determined
	// by the ratio of the VariantWeight to the sum of all VariantWeight values across
	// all ProductionVariants. If unspecified, it defaults to 1.0.
	InitialVariantWeight *float32
}

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.

type ProductionVariantAcceleratorType 

type ProductionVariantAcceleratorType string
const (
	ProductionVariantAcceleratorTypeMlEia1Medium ProductionVariantAcceleratorType = "ml.eia1.medium"
	ProductionVariantAcceleratorTypeMlEia1Large  ProductionVariantAcceleratorType = "ml.eia1.large"
	ProductionVariantAcceleratorTypeMlEia1Xlarge ProductionVariantAcceleratorType = "ml.eia1.xlarge"
	ProductionVariantAcceleratorTypeMlEia2Medium ProductionVariantAcceleratorType = "ml.eia2.medium"
	ProductionVariantAcceleratorTypeMlEia2Large  ProductionVariantAcceleratorType = "ml.eia2.large"
	ProductionVariantAcceleratorTypeMlEia2Xlarge ProductionVariantAcceleratorType = "ml.eia2.xlarge"
)

Enum values for ProductionVariantAcceleratorType

func (ProductionVariantAcceleratorType) Values added in v0.29.0 

func (ProductionVariantAcceleratorType) Values() []ProductionVariantAcceleratorType

Values returns all known values for ProductionVariantAcceleratorType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProductionVariantInstanceType 

type ProductionVariantInstanceType string
const (
	ProductionVariantInstanceTypeMlT2Medium     ProductionVariantInstanceType = "ml.t2.medium"
	ProductionVariantInstanceTypeMlT2Large      ProductionVariantInstanceType = "ml.t2.large"
	ProductionVariantInstanceTypeMlT2Xlarge     ProductionVariantInstanceType = "ml.t2.xlarge"
	ProductionVariantInstanceTypeMlT22xlarge    ProductionVariantInstanceType = "ml.t2.2xlarge"
	ProductionVariantInstanceTypeMlM4Xlarge     ProductionVariantInstanceType = "ml.m4.xlarge"
	ProductionVariantInstanceTypeMlM42xlarge    ProductionVariantInstanceType = "ml.m4.2xlarge"
	ProductionVariantInstanceTypeMlM44xlarge    ProductionVariantInstanceType = "ml.m4.4xlarge"
	ProductionVariantInstanceTypeMlM410xlarge   ProductionVariantInstanceType = "ml.m4.10xlarge"
	ProductionVariantInstanceTypeMlM416xlarge   ProductionVariantInstanceType = "ml.m4.16xlarge"
	ProductionVariantInstanceTypeMlM5Large      ProductionVariantInstanceType = "ml.m5.large"
	ProductionVariantInstanceTypeMlM5Xlarge     ProductionVariantInstanceType = "ml.m5.xlarge"
	ProductionVariantInstanceTypeMlM52xlarge    ProductionVariantInstanceType = "ml.m5.2xlarge"
	ProductionVariantInstanceTypeMlM54xlarge    ProductionVariantInstanceType = "ml.m5.4xlarge"
	ProductionVariantInstanceTypeMlM512xlarge   ProductionVariantInstanceType = "ml.m5.12xlarge"
	ProductionVariantInstanceTypeMlM524xlarge   ProductionVariantInstanceType = "ml.m5.24xlarge"
	ProductionVariantInstanceTypeMlM5dLarge     ProductionVariantInstanceType = "ml.m5d.large"
	ProductionVariantInstanceTypeMlM5dXlarge    ProductionVariantInstanceType = "ml.m5d.xlarge"
	ProductionVariantInstanceTypeMlM5d2xlarge   ProductionVariantInstanceType = "ml.m5d.2xlarge"
	ProductionVariantInstanceTypeMlM5d4xlarge   ProductionVariantInstanceType = "ml.m5d.4xlarge"
	ProductionVariantInstanceTypeMlM5d12xlarge  ProductionVariantInstanceType = "ml.m5d.12xlarge"
	ProductionVariantInstanceTypeMlM5d24xlarge  ProductionVariantInstanceType = "ml.m5d.24xlarge"
	ProductionVariantInstanceTypeMlC4Large      ProductionVariantInstanceType = "ml.c4.large"
	ProductionVariantInstanceTypeMlC4Xlarge     ProductionVariantInstanceType = "ml.c4.xlarge"
	ProductionVariantInstanceTypeMlC42xlarge    ProductionVariantInstanceType = "ml.c4.2xlarge"
	ProductionVariantInstanceTypeMlC44xlarge    ProductionVariantInstanceType = "ml.c4.4xlarge"
	ProductionVariantInstanceTypeMlC48xlarge    ProductionVariantInstanceType = "ml.c4.8xlarge"
	ProductionVariantInstanceTypeMlP2Xlarge     ProductionVariantInstanceType = "ml.p2.xlarge"
	ProductionVariantInstanceTypeMlP28xlarge    ProductionVariantInstanceType = "ml.p2.8xlarge"
	ProductionVariantInstanceTypeMlP216xlarge   ProductionVariantInstanceType = "ml.p2.16xlarge"
	ProductionVariantInstanceTypeMlP32xlarge    ProductionVariantInstanceType = "ml.p3.2xlarge"
	ProductionVariantInstanceTypeMlP38xlarge    ProductionVariantInstanceType = "ml.p3.8xlarge"
	ProductionVariantInstanceTypeMlP316xlarge   ProductionVariantInstanceType = "ml.p3.16xlarge"
	ProductionVariantInstanceTypeMlC5Large      ProductionVariantInstanceType = "ml.c5.large"
	ProductionVariantInstanceTypeMlC5Xlarge     ProductionVariantInstanceType = "ml.c5.xlarge"
	ProductionVariantInstanceTypeMlC52xlarge    ProductionVariantInstanceType = "ml.c5.2xlarge"
	ProductionVariantInstanceTypeMlC54xlarge    ProductionVariantInstanceType = "ml.c5.4xlarge"
	ProductionVariantInstanceTypeMlC59xlarge    ProductionVariantInstanceType = "ml.c5.9xlarge"
	ProductionVariantInstanceTypeMlC518xlarge   ProductionVariantInstanceType = "ml.c5.18xlarge"
	ProductionVariantInstanceTypeMlC5dLarge     ProductionVariantInstanceType = "ml.c5d.large"
	ProductionVariantInstanceTypeMlC5dXlarge    ProductionVariantInstanceType = "ml.c5d.xlarge"
	ProductionVariantInstanceTypeMlC5d2xlarge   ProductionVariantInstanceType = "ml.c5d.2xlarge"
	ProductionVariantInstanceTypeMlC5d4xlarge   ProductionVariantInstanceType = "ml.c5d.4xlarge"
	ProductionVariantInstanceTypeMlC5d9xlarge   ProductionVariantInstanceType = "ml.c5d.9xlarge"
	ProductionVariantInstanceTypeMlC5d18xlarge  ProductionVariantInstanceType = "ml.c5d.18xlarge"
	ProductionVariantInstanceTypeMlG4dnXlarge   ProductionVariantInstanceType = "ml.g4dn.xlarge"
	ProductionVariantInstanceTypeMlG4dn2xlarge  ProductionVariantInstanceType = "ml.g4dn.2xlarge"
	ProductionVariantInstanceTypeMlG4dn4xlarge  ProductionVariantInstanceType = "ml.g4dn.4xlarge"
	ProductionVariantInstanceTypeMlG4dn8xlarge  ProductionVariantInstanceType = "ml.g4dn.8xlarge"
	ProductionVariantInstanceTypeMlG4dn12xlarge ProductionVariantInstanceType = "ml.g4dn.12xlarge"
	ProductionVariantInstanceTypeMlG4dn16xlarge ProductionVariantInstanceType = "ml.g4dn.16xlarge"
	ProductionVariantInstanceTypeMlR5Large      ProductionVariantInstanceType = "ml.r5.large"
	ProductionVariantInstanceTypeMlR5Xlarge     ProductionVariantInstanceType = "ml.r5.xlarge"
	ProductionVariantInstanceTypeMlR52xlarge    ProductionVariantInstanceType = "ml.r5.2xlarge"
	ProductionVariantInstanceTypeMlR54xlarge    ProductionVariantInstanceType = "ml.r5.4xlarge"
	ProductionVariantInstanceTypeMlR512xlarge   ProductionVariantInstanceType = "ml.r5.12xlarge"
	ProductionVariantInstanceTypeMlR524xlarge   ProductionVariantInstanceType = "ml.r5.24xlarge"
	ProductionVariantInstanceTypeMlR5dLarge     ProductionVariantInstanceType = "ml.r5d.large"
	ProductionVariantInstanceTypeMlR5dXlarge    ProductionVariantInstanceType = "ml.r5d.xlarge"
	ProductionVariantInstanceTypeMlR5d2xlarge   ProductionVariantInstanceType = "ml.r5d.2xlarge"
	ProductionVariantInstanceTypeMlR5d4xlarge   ProductionVariantInstanceType = "ml.r5d.4xlarge"
	ProductionVariantInstanceTypeMlR5d12xlarge  ProductionVariantInstanceType = "ml.r5d.12xlarge"
	ProductionVariantInstanceTypeMlR5d24xlarge  ProductionVariantInstanceType = "ml.r5d.24xlarge"
	ProductionVariantInstanceTypeMlInf1Xlarge   ProductionVariantInstanceType = "ml.inf1.xlarge"
	ProductionVariantInstanceTypeMlInf12xlarge  ProductionVariantInstanceType = "ml.inf1.2xlarge"
	ProductionVariantInstanceTypeMlInf16xlarge  ProductionVariantInstanceType = "ml.inf1.6xlarge"
	ProductionVariantInstanceTypeMlInf124xlarge ProductionVariantInstanceType = "ml.inf1.24xlarge"
)

Enum values for ProductionVariantInstanceType

func (ProductionVariantInstanceType) Values added in v0.29.0 

func (ProductionVariantInstanceType) Values() []ProductionVariantInstanceType

Values returns all known values for ProductionVariantInstanceType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ProductionVariantSummary 

type ProductionVariantSummary struct {

	// The name of the variant.
	//
	// This member is required.
	VariantName *string

	// The number of instances associated with the variant.
	CurrentInstanceCount *int32

	// The weight associated with the variant.
	CurrentWeight *float32

	// An array of DeployedImage objects that specify the Amazon EC2 Container Registry
	// paths of the inference images deployed on instances of this ProductionVariant.
	DeployedImages []*DeployedImage

	// The number of instances requested in the UpdateEndpointWeightsAndCapacities
	// request.
	DesiredInstanceCount *int32

	// The requested weight, as specified in the UpdateEndpointWeightsAndCapacities
	// request.
	DesiredWeight *float32
}

Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities API and the endpoint status is Updating, you get different desired and current values.

type PropertyNameQuery 

type PropertyNameQuery struct {

	// Text that begins a property's name.
	//
	// This member is required.
	PropertyNameHint *string
}

Part of the SuggestionQuery type. Specifies a hint for retrieving property names that begin with the specified text.

type PropertyNameSuggestion 

type PropertyNameSuggestion struct {

	// A suggested property name based on what you entered in the search textbox in the
	// Amazon SageMaker console.
	PropertyName *string
}

A property name returned from a GetSearchSuggestions call that specifies a value in the PropertyNameQuery field.

type PublicWorkforceTaskPrice 

type PublicWorkforceTaskPrice struct {

	// Defines the amount of money paid to an Amazon Mechanical Turk worker in United
	// States dollars.
	AmountInUsd *USD
}

Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed. Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.

* 0.036

* 0.048

* 0.060

* 0.072

* 0.120

* 0.240

* 0.360

* 0.480

* 0.600

* 0.720

* 0.840

* 0.960

* 1.080

* 1.200

Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.

* 0.012

* 0.024

* 0.036

* 0.048

* 0.060

* 0.072

* 0.120

* 0.240

* 0.360

* 0.480

* 0.600

* 0.720

* 0.840

* 0.960

* 1.080

* 1.200

Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.

* 0.840

* 0.960

* 1.080

* 1.200

Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.

* 2.400

* 2.280

* 2.160

* 2.040

* 1.920

* 1.800

* 1.680

* 1.560

* 1.440

* 1.320

* 1.200

* 1.080

* 0.960

* 0.840

* 0.720

* 0.600

* 0.480

* 0.360

* 0.240

* 0.120

* 0.072

* 0.060

* 0.048

* 0.036

* 0.024

* 0.012

Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.

* 1.200

* 1.080

* 0.960

* 0.840

* 0.720

* 0.600

* 0.480

* 0.360

* 0.240

* 0.120

* 0.072

* 0.060

* 0.048

* 0.036

* 0.024

* 0.012

Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.

* 1.200

* 1.080

* 0.960

* 0.840

* 0.720

* 0.600

* 0.480

* 0.360

* 0.240

* 0.120

* 0.072

* 0.060

* 0.048

* 0.036

* 0.024

* 0.012

type RecordWrapper 

type RecordWrapper string
const (
	RecordWrapperNone     RecordWrapper = "None"
	RecordWrapperRecordio RecordWrapper = "RecordIO"
)

Enum values for RecordWrapper

func (RecordWrapper) Values added in v0.29.0 

func (RecordWrapper) Values() []RecordWrapper

Values returns all known values for RecordWrapper. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type RenderableTask 

type RenderableTask struct {

	// A JSON object that contains values for the variables defined in the template. It
	// is made available to the template under the substitution variable task.input.
	// For example, if you define a variable task.input.text in your template, you can
	// supply the variable in the JSON object as "text": "sample text".
	//
	// This member is required.
	Input *string
}

Contains input values for a task.

type RenderingError 

type RenderingError struct {

	// A unique identifier for a specific class of errors.
	//
	// This member is required.
	Code *string

	// A human-readable message describing the error.
	//
	// This member is required.
	Message *string
}

A description of an error that occurred while rendering the template.

type RepositoryAccessMode added in v0.29.0 

type RepositoryAccessMode string
const (
	RepositoryAccessModePlatform RepositoryAccessMode = "Platform"
	RepositoryAccessModeVpc      RepositoryAccessMode = "Vpc"
)

Enum values for RepositoryAccessMode

func (RepositoryAccessMode) Values added in v0.29.0 

func (RepositoryAccessMode) Values() []RepositoryAccessMode

Values returns all known values for RepositoryAccessMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ResolvedAttributes 

type ResolvedAttributes struct {

	// Specifies a metric to minimize or maximize as the objective of a job.
	AutoMLJobObjective *AutoMLJobObjective

	// How long a job is allowed to run, or how many candidates a job is allowed to
	// generate.
	CompletionCriteria *AutoMLJobCompletionCriteria

	// The problem type.
	ProblemType ProblemType
}

The resolved attributes.

type ResourceConfig 

type ResourceConfig struct {

	// The number of ML compute instances to use. For distributed training, provide a
	// value greater than 1.
	//
	// This member is required.
	InstanceCount *int32

	// The ML compute instance type.
	//
	// This member is required.
	InstanceType TrainingInstanceType

	// The size of the ML storage volume that you want to provision. ML storage volumes
	// store model artifacts and incremental states. Training algorithms might also use
	// the ML storage volume for scratch space. If you want to store the training data
	// in the ML storage volume, choose File as the TrainingInputMode in the algorithm
	// specification. You must specify sufficient ML storage for your scenario. Amazon
	// SageMaker supports only the General Purpose SSD (gp2) ML storage volume type.
	// Certain Nitro-based instances include local storage with a fixed total size,
	// dependent on the instance type. When using these instances for training, Amazon
	// SageMaker mounts the local instance storage instead of Amazon EBS gp2 storage.
	// You can't request a VolumeSizeInGB greater than the total size of the local
	// instance storage. For a list of instance types that support local instance
	// storage, including the total size per instance type, see Instance Store Volumes
	// (https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes).
	//
	// This member is required.
	VolumeSizeInGB *int32

	// The AWS 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. Certain
	// Nitro-based instances include local storage, dependent on the instance type.
	// Local storage volumes are encrypted using a hardware module on the instance. You
	// can't request a VolumeKmsKeyId when using an instance type with local storage.
	// For a list of instance types that support local instance storage, see Instance
	// Store Volumes
	// (https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes).
	// For more information about local instance storage encryption, see SSD Instance
	// Store Volumes
	// (https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.html).
	// The VolumeKmsKeyId can be in any of the following formats:
	//
	// * // KMS Key ID
	// "1234abcd-12ab-34cd-56ef-1234567890ab"
	//
	// * // Amazon Resource Name (ARN) of a KMS
	// Key
	// "arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"
	VolumeKmsKeyId *string
}

Describes the resources, including ML compute instances and ML storage volumes, to use for model training.

type ResourceInUse 

type ResourceInUse struct {
	Message *string
}

Resource being accessed is in use.

func (*ResourceInUse) Error 

func (e *ResourceInUse) Error() string

func (*ResourceInUse) ErrorCode 

func (e *ResourceInUse) ErrorCode() string

func (*ResourceInUse) ErrorFault 

func (e *ResourceInUse) ErrorFault() smithy.ErrorFault

func (*ResourceInUse) ErrorMessage 

func (e *ResourceInUse) ErrorMessage() string

type ResourceLimitExceeded 

type ResourceLimitExceeded struct {
	Message *string
}

You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.

func (*ResourceLimitExceeded) Error 

func (e *ResourceLimitExceeded) Error() string

func (*ResourceLimitExceeded) ErrorCode 

func (e *ResourceLimitExceeded) ErrorCode() string

func (*ResourceLimitExceeded) ErrorFault 

func (e *ResourceLimitExceeded) ErrorFault() smithy.ErrorFault

func (*ResourceLimitExceeded) ErrorMessage 

func (e *ResourceLimitExceeded) ErrorMessage() string

type ResourceLimits 

type ResourceLimits struct {

	// The maximum number of training jobs that a hyperparameter tuning job can launch.
	//
	// This member is required.
	MaxNumberOfTrainingJobs *int32

	// The maximum number of concurrent training jobs that a hyperparameter tuning job
	// can launch.
	//
	// This member is required.
	MaxParallelTrainingJobs *int32
}

Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.

type ResourceNotFound 

type ResourceNotFound struct {
	Message *string
}

Resource being access is not found.

func (*ResourceNotFound) Error 

func (e *ResourceNotFound) Error() string

func (*ResourceNotFound) ErrorCode 

func (e *ResourceNotFound) ErrorCode() string

func (*ResourceNotFound) ErrorFault 

func (e *ResourceNotFound) ErrorFault() smithy.ErrorFault

func (*ResourceNotFound) ErrorMessage 

func (e *ResourceNotFound) ErrorMessage() string

type ResourceSpec 

type ResourceSpec struct {

	// The instance type that the image version runs on.
	InstanceType AppInstanceType

	// The ARN of the SageMaker image that the image version belongs to.
	SageMakerImageArn *string

	// The ARN of the image version created on the instance.
	SageMakerImageVersionArn *string
}

Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.

type ResourceType 

type ResourceType string
const (
	ResourceTypeTrainingJob              ResourceType = "TrainingJob"
	ResourceTypeExperiment               ResourceType = "Experiment"
	ResourceTypeExperimentTrial          ResourceType = "ExperimentTrial"
	ResourceTypeExperimentTrialComponent ResourceType = "ExperimentTrialComponent"
)

Enum values for ResourceType

func (ResourceType) Values added in v0.29.0 

func (ResourceType) Values() []ResourceType

Values returns all known values for ResourceType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type RetentionPolicy 

type RetentionPolicy struct {

	// The default is Retain, which specifies to keep the data stored on the EFS
	// volume. Specify Delete to delete the data stored on the EFS volume.
	HomeEfsFileSystem RetentionType
}

The retention policy for data stored on an Amazon Elastic File System (EFS) volume.

type RetentionType 

type RetentionType string
const (
	RetentionTypeRetain RetentionType = "Retain"
	RetentionTypeDelete RetentionType = "Delete"
)

Enum values for RetentionType

func (RetentionType) Values added in v0.29.0 

func (RetentionType) Values() []RetentionType

Values returns all known values for RetentionType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type RootAccess 

type RootAccess string
const (
	RootAccessEnabled  RootAccess = "Enabled"
	RootAccessDisabled RootAccess = "Disabled"
)

Enum values for RootAccess

func (RootAccess) Values added in v0.29.0 

func (RootAccess) Values() []RootAccess

Values returns all known values for RootAccess. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type RuleEvaluationStatus 

type RuleEvaluationStatus string
const (
	RuleEvaluationStatusInProgress    RuleEvaluationStatus = "InProgress"
	RuleEvaluationStatusNoIssuesFound RuleEvaluationStatus = "NoIssuesFound"
	RuleEvaluationStatusIssuesFound   RuleEvaluationStatus = "IssuesFound"
	RuleEvaluationStatusError         RuleEvaluationStatus = "Error"
	RuleEvaluationStatusStopping      RuleEvaluationStatus = "Stopping"
	RuleEvaluationStatusStopped       RuleEvaluationStatus = "Stopped"
)

Enum values for RuleEvaluationStatus

func (RuleEvaluationStatus) Values added in v0.29.0 

func (RuleEvaluationStatus) Values() []RuleEvaluationStatus

Values returns all known values for RuleEvaluationStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type S3DataDistribution 

type S3DataDistribution string
const (
	S3DataDistributionFullyReplicated S3DataDistribution = "FullyReplicated"
	S3DataDistributionShardedByS3Key  S3DataDistribution = "ShardedByS3Key"
)

Enum values for S3DataDistribution

func (S3DataDistribution) Values added in v0.29.0 

func (S3DataDistribution) Values() []S3DataDistribution

Values returns all known values for S3DataDistribution. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type S3DataSource 

type S3DataSource struct {

	// If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker
	// uses all objects that match the specified key name prefix for model training. If
	// you choose ManifestFile, S3Uri identifies an object that is a manifest file
	// containing a list of object keys that you want Amazon SageMaker to use for model
	// training. If you choose AugmentedManifestFile, S3Uri identifies an object that
	// is an augmented manifest file in JSON lines format. This file contains the data
	// you want to use for model training. AugmentedManifestFile can only be used if
	// the Channel's input mode is Pipe.
	//
	// This member is required.
	S3DataType S3DataType

	// Depending on the value specified for the S3DataType, identifies either a key
	// name prefix or a manifest. For example:
	//
	// * A key name prefix might look like
	// this: s3://bucketname/exampleprefix
	//
	// * A manifest might look like this:
	// s3://bucketname/example.manifest A manifest is an S3 object which is a JSON file
	// consisting of an array of elements. The first element is a prefix which is
	// followed by one or more suffixes. SageMaker appends the suffix elements to the
	// prefix to get a full set of S3Uri. Note that the prefix must be a valid
	// non-empty S3Uri that precludes users from specifying a manifest whose individual
	// S3Uri is sourced from different S3 buckets. The following code example shows a
	// valid manifest format: [ {"prefix": "s3://customer_bucket/some/prefix/"},
	// "relative/path/to/custdata-1", "relative/path/custdata-2", ...
	// "relative/path/custdata-N"] This JSON is equivalent to the following S3Uri list:
	// s3://customer_bucket/some/prefix/relative/path/to/custdata-1s3://customer_bucket/some/prefix/relative/path/custdata-2...s3://customer_bucket/some/prefix/relative/path/custdata-N
	// The complete set of S3Uri in this manifest is the input data for the channel for
	// this data source. The object that each S3Uri points to must be readable by the
	// IAM role that Amazon SageMaker uses to perform tasks on your behalf.
	//
	// This member is required.
	S3Uri *string

	// A list of one or more attribute names to use that are found in a specified
	// augmented manifest file.
	AttributeNames []*string

	// If you want Amazon SageMaker to replicate the entire dataset on each ML compute
	// instance that is launched for model training, specify FullyReplicated. If you
	// want Amazon SageMaker to replicate a subset of data on each ML compute instance
	// that is launched for model training, specify ShardedByS3Key. If there are n ML
	// compute instances launched for a training job, each instance gets approximately
	// 1/n of the number of S3 objects. In this case, model training on each machine
	// uses only the subset of training data. Don't choose more ML compute instances
	// for training than available S3 objects. If you do, some nodes won't get any data
	// and you will pay for nodes that aren't getting any training data. This applies
	// in both File and Pipe modes. Keep this in mind when developing algorithms. In
	// distributed training, where you use multiple ML compute EC2 instances, you might
	// choose ShardedByS3Key. If the algorithm requires copying training data to the ML
	// storage volume (when TrainingInputMode is set to File), this copies 1/n of the
	// number of objects.
	S3DataDistributionType S3DataDistribution
}

Describes the S3 data source.

type S3DataType 

type S3DataType string
const (
	S3DataTypeManifestFile          S3DataType = "ManifestFile"
	S3DataTypeS3Prefix              S3DataType = "S3Prefix"
	S3DataTypeAugmentedManifestFile S3DataType = "AugmentedManifestFile"
)

Enum values for S3DataType

func (S3DataType) Values added in v0.29.0 

func (S3DataType) Values() []S3DataType

Values returns all known values for S3DataType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type ScheduleConfig 

type ScheduleConfig struct {

	// A cron expression that describes details about the monitoring schedule.
	// Currently the only supported cron expressions are:
	//
	// * If you want to set the job
	// to start every hour, please use the following: Hourly: cron(0 * ? * * *)
	//
	// * If
	// you want to start the job daily: cron(0 [00-23] ? * * *)
	//
	// For example, the
	// following are valid cron expressions:
	//
	// * Daily at noon UTC: cron(0 12 ? * *
	// *)
	//
	// * Daily at midnight UTC: cron(0 0 ? * * *)
	//
	// To support running every 6, 12
	// hours, the following are also supported: cron(0 [00-23]/[01-24] ? * * *) For
	// example, the following are valid cron expressions:
	//
	// * Every 12 hours, starting
	// at 5pm UTC: cron(0 17/12 ? * * *)
	//
	// * Every two hours starting at midnight:
	// cron(0 0/2 ? * * *)
	//
	// * Even though the cron expression is set to start at 5PM
	// UTC, note that there could be a delay of 0-20 minutes from the actual requested
	// time to run the execution.
	//
	// * We recommend that if you would like a daily
	// schedule, you do not provide this parameter. Amazon SageMaker will pick a time
	// for running every day.
	//
	// This member is required.
	ScheduleExpression *string
}

Configuration details about the monitoring schedule.

type ScheduleStatus 

type ScheduleStatus string
const (
	ScheduleStatusPending   ScheduleStatus = "Pending"
	ScheduleStatusFailed    ScheduleStatus = "Failed"
	ScheduleStatusScheduled ScheduleStatus = "Scheduled"
	ScheduleStatusStopped   ScheduleStatus = "Stopped"
)

Enum values for ScheduleStatus

func (ScheduleStatus) Values added in v0.29.0 

func (ScheduleStatus) Values() []ScheduleStatus

Values returns all known values for ScheduleStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type SearchExpression 

type SearchExpression struct {

	// A list of filter objects.
	Filters []*Filter

	// A list of nested filter objects.
	NestedFilters []*NestedFilters

	// A Boolean operator used to evaluate the search expression. If you want every
	// conditional statement in all lists to be satisfied for the entire search
	// expression to be true, specify And. If only a single conditional statement needs
	// to be true for the entire search expression to be true, specify Or. The default
	// value is And.
	Operator BooleanOperator

	// A list of search expression objects.
	SubExpressions []*SearchExpression
}

A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression can contain up to twenty elements. A SearchExpression contains the following components:

* A list of Filter objects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value.

* A list of NestedFilter objects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions.

* A list of SearchExpression objects. A search expression object can be nested in a list of search expression objects.

* A Boolean operator: And or Or.

type SearchRecord 

type SearchRecord struct {

	// The properties of an experiment.
	Experiment *Experiment

	// The properties of a training job.
	TrainingJob *TrainingJob

	// The properties of a trial.
	Trial *Trial

	// The properties of a trial component.
	TrialComponent *TrialComponent
}

A single resource returned as part of the Search API response.

type SearchSortOrder 

type SearchSortOrder string
const (
	SearchSortOrderAscending  SearchSortOrder = "Ascending"
	SearchSortOrderDescending SearchSortOrder = "Descending"
)

Enum values for SearchSortOrder

func (SearchSortOrder) Values added in v0.29.0 

func (SearchSortOrder) Values() []SearchSortOrder

Values returns all known values for SearchSortOrder. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type SecondaryStatus 

type SecondaryStatus string
const (
	SecondaryStatusStarting                 SecondaryStatus = "Starting"
	SecondaryStatusLaunchingMlInstances     SecondaryStatus = "LaunchingMLInstances"
	SecondaryStatusPreparingTrainingStack   SecondaryStatus = "PreparingTrainingStack"
	SecondaryStatusDownloading              SecondaryStatus = "Downloading"
	SecondaryStatusDownloadingTrainingImage SecondaryStatus = "DownloadingTrainingImage"
	SecondaryStatusTraining                 SecondaryStatus = "Training"
	SecondaryStatusUploading                SecondaryStatus = "Uploading"
	SecondaryStatusStopping                 SecondaryStatus = "Stopping"
	SecondaryStatusStopped                  SecondaryStatus = "Stopped"
	SecondaryStatusMaxRuntimeExceeded       SecondaryStatus = "MaxRuntimeExceeded"
	SecondaryStatusCompleted                SecondaryStatus = "Completed"
	SecondaryStatusFailed                   SecondaryStatus = "Failed"
	SecondaryStatusInterrupted              SecondaryStatus = "Interrupted"
	SecondaryStatusMaxWaitTimeExceeded      SecondaryStatus = "MaxWaitTimeExceeded"
)

Enum values for SecondaryStatus

func (SecondaryStatus) Values added in v0.29.0 

func (SecondaryStatus) Values() []SecondaryStatus

Values returns all known values for SecondaryStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type SecondaryStatusTransition 

type SecondaryStatusTransition struct {

	// A timestamp that shows when the training job transitioned to the current
	// secondary status state.
	//
	// This member is required.
	StartTime *time.Time

	// Contains a secondary status information from a training job. Status might be one
	// of the following secondary statuses: InProgress
	//
	// * Starting - Starting the
	// training job.
	//
	// * Downloading - An optional stage for algorithms that support
	// File training input mode. It indicates that data is being downloaded to the ML
	// storage volumes.
	//
	// * Training - Training is in progress.
	//
	// * Uploading - Training
	// is complete and the model artifacts are being uploaded to the S3
	// location.
	//
	// Completed
	//
	// * Completed - The training job has completed.
	//
	// Failed
	//
	// *
	// Failed - The training job has failed. The reason for the failure is returned in
	// the FailureReason field of DescribeTrainingJobResponse.
	//
	// Stopped
	//
	// *
	// MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed
	// runtime.
	//
	// * Stopped - The training job has stopped.
	//
	// Stopping
	//
	// * Stopping -
	// Stopping the training job.
	//
	// We no longer support the following secondary
	// statuses:
	//
	// * LaunchingMLInstances
	//
	// * PreparingTrainingStack
	//
	// *
	// DownloadingTrainingImage
	//
	// This member is required.
	Status SecondaryStatus

	// A timestamp that shows when the training job transitioned out of this secondary
	// status state into another secondary status state or when the training job has
	// ended.
	EndTime *time.Time

	// A detailed description of the progress within a secondary status. Amazon
	// SageMaker provides secondary statuses and status messages that apply to each of
	// them: Starting
	//
	// * Starting the training job.
	//
	// * Launching requested ML
	// instances.
	//
	// * Insufficient capacity error from EC2 while launching instances,
	// retrying!
	//
	// * Launched instance was unhealthy, replacing it!
	//
	// * Preparing the
	// instances for training.
	//
	// Training
	//
	// * Downloading the training image.
	//
	// * Training
	// image download completed. Training in progress.
	//
	// Status messages are subject to
	// change. Therefore, we recommend not including them in code that programmatically
	// initiates actions. For examples, don't use status messages in if statements. To
	// have an overview of your training job's progress, view TrainingJobStatus and
	// SecondaryStatus in DescribeTrainingJob, and StatusMessage together. For example,
	// at the start of a training job, you might see the following:
	//
	// *
	// TrainingJobStatus - InProgress
	//
	// * SecondaryStatus - Training
	//
	// * StatusMessage -
	// Downloading the training image
	StatusMessage *string
}

An array element of DescribeTrainingJobResponse$SecondaryStatusTransitions. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, Amazon SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job's secondary status.

type SharingSettings 

type SharingSettings struct {

	// Whether to include the notebook cell output when sharing the notebook. The
	// default is Disabled.
	NotebookOutputOption NotebookOutputOption

	// When NotebookOutputOption is Allowed, the AWS Key Management Service (KMS)
	// encryption key ID used to encrypt the notebook cell output in the Amazon S3
	// bucket.
	S3KmsKeyId *string

	// When NotebookOutputOption is Allowed, the Amazon S3 bucket used to save the
	// notebook cell output.
	S3OutputPath *string
}

Specifies options when sharing an Amazon SageMaker Studio notebook. These settings are specified as part of DefaultUserSettings when the CreateDomain API is called, and as part of UserSettings when the CreateUserProfile API is called.

type ShuffleConfig 

type ShuffleConfig struct {

	// Determines the shuffling order in ShuffleConfig value.
	//
	// This member is required.
	Seed *int64
}

A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, the results of the S3 key prefix matches are shuffled. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value. For Pipe input mode, when ShuffleConfig is specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job when ShuffleConfig is combined with S3DataDistributionType of ShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.

type SortBy 

type SortBy string
const (
	SortByName         SortBy = "Name"
	SortByCreationTime SortBy = "CreationTime"
	SortByStatus       SortBy = "Status"
)

Enum values for SortBy

func (SortBy) Values added in v0.29.0 

func (SortBy) Values() []SortBy

Values returns all known values for SortBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type SortExperimentsBy 

type SortExperimentsBy string
const (
	SortExperimentsByName         SortExperimentsBy = "Name"
	SortExperimentsByCreationTime SortExperimentsBy = "CreationTime"
)

Enum values for SortExperimentsBy

func (SortExperimentsBy) Values added in v0.29.0 

func (SortExperimentsBy) Values() []SortExperimentsBy

Values returns all known values for SortExperimentsBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type SortOrder 

type SortOrder string
const (
	SortOrderAscending  SortOrder = "Ascending"
	SortOrderDescending SortOrder = "Descending"
)

Enum values for SortOrder

func (SortOrder) Values added in v0.29.0 

func (SortOrder) Values() []SortOrder

Values returns all known values for SortOrder. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type SortTrialComponentsBy 

type SortTrialComponentsBy string
const (
	SortTrialComponentsByName         SortTrialComponentsBy = "Name"
	SortTrialComponentsByCreationTime SortTrialComponentsBy = "CreationTime"
)

Enum values for SortTrialComponentsBy

func (SortTrialComponentsBy) Values added in v0.29.0 

func (SortTrialComponentsBy) Values() []SortTrialComponentsBy

Values returns all known values for SortTrialComponentsBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type SortTrialsBy 

type SortTrialsBy string
const (
	SortTrialsByName         SortTrialsBy = "Name"
	SortTrialsByCreationTime SortTrialsBy = "CreationTime"
)

Enum values for SortTrialsBy

func (SortTrialsBy) Values added in v0.29.0 

func (SortTrialsBy) Values() []SortTrialsBy

Values returns all known values for SortTrialsBy. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type SourceAlgorithm 

type SourceAlgorithm struct {

	// The name of an algorithm that was used to create the model package. The
	// algorithm must be either an algorithm resource in your Amazon SageMaker account
	// or an algorithm in AWS Marketplace that you are subscribed to.
	//
	// This member is required.
	AlgorithmName *string

	// The Amazon 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 model artifacts must be in an S3 bucket that is in the
	// same region as the algorithm.
	ModelDataUrl *string
}

Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your Amazon SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.

type SourceAlgorithmSpecification 

type SourceAlgorithmSpecification struct {

	// A list of the algorithms that were used to create a model package.
	//
	// This member is required.
	SourceAlgorithms []*SourceAlgorithm
}

A list of algorithms that were used to create a model package.

type SourceIpConfig 

type SourceIpConfig struct {

	// A list of one to ten Classless Inter-Domain Routing
	// (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html) (CIDR)
	// values. Maximum: Ten CIDR values The following Length Constraints apply to
	// individual CIDR values in the CIDR value list.
	//
	// This member is required.
	Cidrs []*string
}

A list of IP address ranges (CIDRs (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html)). Used to create an allow list of IP addresses for a private workforce. Workers will only be able to login to their worker portal from an IP address within this range. By default, a workforce isn't restricted to specific IP addresses.

type SplitType 

type SplitType string
const (
	SplitTypeNone     SplitType = "None"
	SplitTypeLine     SplitType = "Line"
	SplitTypeRecordio SplitType = "RecordIO"
	SplitTypeTfrecord SplitType = "TFRecord"
)

Enum values for SplitType

func (SplitType) Values added in v0.29.0 

func (SplitType) Values() []SplitType

Values returns all known values for SplitType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type StoppingCondition 

type StoppingCondition struct {

	// The maximum length of time, in seconds, that the training or compilation job can
	// run. If job does not complete during this time, Amazon SageMaker ends the job.
	// If value is not specified, default value is 1 day. The maximum value is 28 days.
	MaxRuntimeInSeconds *int32

	// The maximum length of time, in seconds, how long you are willing to wait for a
	// managed spot training job to complete. It is the amount of time spent waiting
	// for Spot capacity plus the amount of time the training job runs. It must be
	// equal to or greater than MaxRuntimeInSeconds.
	MaxWaitTimeInSeconds *int32
}

Specifies a limit to how long a model training or compilation job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the time limit, Amazon SageMaker ends the training or compilation job. Use this API to cap model training costs. To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost. The training algorithms provided by Amazon SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with CreateModel. The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.

type SubscribedWorkteam 

type SubscribedWorkteam struct {

	// The Amazon Resource Name (ARN) of the vendor that you have subscribed.
	//
	// This member is required.
	WorkteamArn *string

	// Marketplace product listing ID.
	ListingId *string

	// The description of the vendor from the Amazon Marketplace.
	MarketplaceDescription *string

	// The title of the service provided by the vendor in the Amazon Marketplace.
	MarketplaceTitle *string

	// The name of the vendor in the Amazon Marketplace.
	SellerName *string
}

Describes a work team of a vendor that does the a labelling job.

type SuggestionQuery 

type SuggestionQuery struct {

	// Defines a property name hint. Only property names that begin with the specified
	// hint are included in the response.
	PropertyNameQuery *PropertyNameQuery
}

Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.

type Tag 

type Tag struct {

	// The tag key.
	//
	// This member is required.
	Key *string

	// The tag value.
	//
	// This member is required.
	Value *string
}

Describes a tag.

type TargetDevice 

type TargetDevice string
const (
	TargetDeviceLambda       TargetDevice = "lambda"
	TargetDeviceMlM4         TargetDevice = "ml_m4"
	TargetDeviceMlM5         TargetDevice = "ml_m5"
	TargetDeviceMlC4         TargetDevice = "ml_c4"
	TargetDeviceMlC5         TargetDevice = "ml_c5"
	TargetDeviceMlP2         TargetDevice = "ml_p2"
	TargetDeviceMlP3         TargetDevice = "ml_p3"
	TargetDeviceMlG4dn       TargetDevice = "ml_g4dn"
	TargetDeviceMlInf1       TargetDevice = "ml_inf1"
	TargetDeviceJetsonTx1    TargetDevice = "jetson_tx1"
	TargetDeviceJetsonTx2    TargetDevice = "jetson_tx2"
	TargetDeviceJetsonNano   TargetDevice = "jetson_nano"
	TargetDeviceJetsonXavier TargetDevice = "jetson_xavier"
	TargetDeviceRasp3b       TargetDevice = "rasp3b"
	TargetDeviceImx8qm       TargetDevice = "imx8qm"
	TargetDeviceDeeplens     TargetDevice = "deeplens"
	TargetDeviceRk3399       TargetDevice = "rk3399"
	TargetDeviceRk3288       TargetDevice = "rk3288"
	TargetDeviceAisage       TargetDevice = "aisage"
	TargetDeviceSbeC         TargetDevice = "sbe_c"
	TargetDeviceQcs605       TargetDevice = "qcs605"
	TargetDeviceQcs603       TargetDevice = "qcs603"
	TargetDeviceSitaraAm57x  TargetDevice = "sitara_am57x"
	TargetDeviceAmbaCv22     TargetDevice = "amba_cv22"
	TargetDeviceX86Win32     TargetDevice = "x86_win32"
	TargetDeviceX86Win64     TargetDevice = "x86_win64"
	TargetDeviceCoreml       TargetDevice = "coreml"
)

Enum values for TargetDevice

func (TargetDevice) Values added in v0.29.0 

func (TargetDevice) Values() []TargetDevice

Values returns all known values for TargetDevice. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TargetPlatform 

type TargetPlatform struct {

	// Specifies a target platform architecture.
	//
	// * X86_64: 64-bit version of the x86
	// instruction set.
	//
	// * X86: 32-bit version of the x86 instruction set.
	//
	// * ARM64:
	// ARMv8 64-bit CPU.
	//
	// * ARM_EABIHF: ARMv7 32-bit, Hard Float.
	//
	// * ARM_EABI: ARMv7
	// 32-bit, Soft Float. Used by Android 32-bit ARM platform.
	//
	// This member is required.
	Arch TargetPlatformArch

	// Specifies a target platform OS.
	//
	// * LINUX: Linux-based operating systems.
	//
	// *
	// ANDROID: Android operating systems. Android API level can be specified using the
	// ANDROID_PLATFORM compiler option. For example, "CompilerOptions":
	// {'ANDROID_PLATFORM': 28}
	//
	// This member is required.
	Os TargetPlatformOs

	// Specifies a target platform accelerator (optional).
	//
	// * NVIDIA: Nvidia graphics
	// processing unit. It also requires gpu-code, trt-ver, cuda-ver compiler
	// options
	//
	// * MALI: ARM Mali graphics processor
	//
	// * INTEL_GRAPHICS: Integrated Intel
	// graphics
	Accelerator TargetPlatformAccelerator
}

Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.

type TargetPlatformAccelerator 

type TargetPlatformAccelerator string
const (
	TargetPlatformAcceleratorIntelGraphics TargetPlatformAccelerator = "INTEL_GRAPHICS"
	TargetPlatformAcceleratorMali          TargetPlatformAccelerator = "MALI"
	TargetPlatformAcceleratorNvidia        TargetPlatformAccelerator = "NVIDIA"
)

Enum values for TargetPlatformAccelerator

func (TargetPlatformAccelerator) Values added in v0.29.0 

func (TargetPlatformAccelerator) Values() []TargetPlatformAccelerator

Values returns all known values for TargetPlatformAccelerator. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TargetPlatformArch 

type TargetPlatformArch string
const (
	TargetPlatformArchX8664     TargetPlatformArch = "X86_64"
	TargetPlatformArchX86       TargetPlatformArch = "X86"
	TargetPlatformArchArm64     TargetPlatformArch = "ARM64"
	TargetPlatformArchArmEabi   TargetPlatformArch = "ARM_EABI"
	TargetPlatformArchArmEabihf TargetPlatformArch = "ARM_EABIHF"
)

Enum values for TargetPlatformArch

func (TargetPlatformArch) Values added in v0.29.0 

func (TargetPlatformArch) Values() []TargetPlatformArch

Values returns all known values for TargetPlatformArch. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TargetPlatformOs 

type TargetPlatformOs string
const (
	TargetPlatformOsAndroid TargetPlatformOs = "ANDROID"
	TargetPlatformOsLinux   TargetPlatformOs = "LINUX"
)

Enum values for TargetPlatformOs

func (TargetPlatformOs) Values added in v0.29.0 

func (TargetPlatformOs) Values() []TargetPlatformOs

Values returns all known values for TargetPlatformOs. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TensorBoardAppSettings 

type TensorBoardAppSettings struct {

	// The default instance type and the Amazon Resource Name (ARN) of the SageMaker
	// image created on the instance.
	DefaultResourceSpec *ResourceSpec
}

The TensorBoard app settings.

type TensorBoardOutputConfig 

type TensorBoardOutputConfig struct {

	// Path to Amazon S3 storage location for TensorBoard output.
	//
	// This member is required.
	S3OutputPath *string

	// Path to local storage location for tensorBoard output. Defaults to
	// /opt/ml/output/tensorboard.
	LocalPath *string
}

Configuration of storage locations for TensorBoard output.

type TrainingInputMode 

type TrainingInputMode string
const (
	TrainingInputModePipe TrainingInputMode = "Pipe"
	TrainingInputModeFile TrainingInputMode = "File"
)

Enum values for TrainingInputMode

func (TrainingInputMode) Values added in v0.29.0 

func (TrainingInputMode) Values() []TrainingInputMode

Values returns all known values for TrainingInputMode. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TrainingInstanceType 

type TrainingInstanceType string
const (
	TrainingInstanceTypeMlM4Xlarge     TrainingInstanceType = "ml.m4.xlarge"
	TrainingInstanceTypeMlM42xlarge    TrainingInstanceType = "ml.m4.2xlarge"
	TrainingInstanceTypeMlM44xlarge    TrainingInstanceType = "ml.m4.4xlarge"
	TrainingInstanceTypeMlM410xlarge   TrainingInstanceType = "ml.m4.10xlarge"
	TrainingInstanceTypeMlM416xlarge   TrainingInstanceType = "ml.m4.16xlarge"
	TrainingInstanceTypeMlG4dnXlarge   TrainingInstanceType = "ml.g4dn.xlarge"
	TrainingInstanceTypeMlG4dn2xlarge  TrainingInstanceType = "ml.g4dn.2xlarge"
	TrainingInstanceTypeMlG4dn4xlarge  TrainingInstanceType = "ml.g4dn.4xlarge"
	TrainingInstanceTypeMlG4dn8xlarge  TrainingInstanceType = "ml.g4dn.8xlarge"
	TrainingInstanceTypeMlG4dn12xlarge TrainingInstanceType = "ml.g4dn.12xlarge"
	TrainingInstanceTypeMlG4dn16xlarge TrainingInstanceType = "ml.g4dn.16xlarge"
	TrainingInstanceTypeMlM5Large      TrainingInstanceType = "ml.m5.large"
	TrainingInstanceTypeMlM5Xlarge     TrainingInstanceType = "ml.m5.xlarge"
	TrainingInstanceTypeMlM52xlarge    TrainingInstanceType = "ml.m5.2xlarge"
	TrainingInstanceTypeMlM54xlarge    TrainingInstanceType = "ml.m5.4xlarge"
	TrainingInstanceTypeMlM512xlarge   TrainingInstanceType = "ml.m5.12xlarge"
	TrainingInstanceTypeMlM524xlarge   TrainingInstanceType = "ml.m5.24xlarge"
	TrainingInstanceTypeMlC4Xlarge     TrainingInstanceType = "ml.c4.xlarge"
	TrainingInstanceTypeMlC42xlarge    TrainingInstanceType = "ml.c4.2xlarge"
	TrainingInstanceTypeMlC44xlarge    TrainingInstanceType = "ml.c4.4xlarge"
	TrainingInstanceTypeMlC48xlarge    TrainingInstanceType = "ml.c4.8xlarge"
	TrainingInstanceTypeMlP2Xlarge     TrainingInstanceType = "ml.p2.xlarge"
	TrainingInstanceTypeMlP28xlarge    TrainingInstanceType = "ml.p2.8xlarge"
	TrainingInstanceTypeMlP216xlarge   TrainingInstanceType = "ml.p2.16xlarge"
	TrainingInstanceTypeMlP32xlarge    TrainingInstanceType = "ml.p3.2xlarge"
	TrainingInstanceTypeMlP38xlarge    TrainingInstanceType = "ml.p3.8xlarge"
	TrainingInstanceTypeMlP316xlarge   TrainingInstanceType = "ml.p3.16xlarge"
	TrainingInstanceTypeMlP3dn24xlarge TrainingInstanceType = "ml.p3dn.24xlarge"
	TrainingInstanceTypeMlP4d24xlarge  TrainingInstanceType = "ml.p4d.24xlarge"
	TrainingInstanceTypeMlC5Xlarge     TrainingInstanceType = "ml.c5.xlarge"
	TrainingInstanceTypeMlC52xlarge    TrainingInstanceType = "ml.c5.2xlarge"
	TrainingInstanceTypeMlC54xlarge    TrainingInstanceType = "ml.c5.4xlarge"
	TrainingInstanceTypeMlC59xlarge    TrainingInstanceType = "ml.c5.9xlarge"
	TrainingInstanceTypeMlC518xlarge   TrainingInstanceType = "ml.c5.18xlarge"
	TrainingInstanceTypeMlC5nXlarge    TrainingInstanceType = "ml.c5n.xlarge"
	TrainingInstanceTypeMlC5n2xlarge   TrainingInstanceType = "ml.c5n.2xlarge"
	TrainingInstanceTypeMlC5n4xlarge   TrainingInstanceType = "ml.c5n.4xlarge"
	TrainingInstanceTypeMlC5n9xlarge   TrainingInstanceType = "ml.c5n.9xlarge"
	TrainingInstanceTypeMlC5n18xlarge  TrainingInstanceType = "ml.c5n.18xlarge"
)

Enum values for TrainingInstanceType

func (TrainingInstanceType) Values added in v0.29.0 

func (TrainingInstanceType) Values() []TrainingInstanceType

Values returns all known values for TrainingInstanceType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TrainingJob 

type TrainingJob struct {

	// Information about the algorithm used for training, and algorithm metadata.
	AlgorithmSpecification *AlgorithmSpecification

	// The Amazon Resource Name (ARN) of the job.
	AutoMLJobArn *string

	// The billable time in seconds.
	BillableTimeInSeconds *int32

	// Contains information about the output location for managed spot training
	// checkpoint data.
	CheckpointConfig *CheckpointConfig

	// A timestamp that indicates when the training job was created.
	CreationTime *time.Time

	// Configuration information for the debug hook parameters, collection
	// configuration, and storage paths.
	DebugHookConfig *DebugHookConfig

	// Information about the debug rule configuration.
	DebugRuleConfigurations []*DebugRuleConfiguration

	// Information about the evaluation status of the rules for the training job.
	DebugRuleEvaluationStatuses []*DebugRuleEvaluationStatus

	// To encrypt all communications between ML compute instances in distributed
	// training, choose True. Encryption provides greater security for distributed
	// training, but training might take longer. How long it takes depends on the
	// amount of communication between compute instances, especially if you use a deep
	// learning algorithm in distributed training.
	EnableInterContainerTrafficEncryption *bool

	// When true, enables managed spot training using Amazon EC2 Spot instances to run
	// training jobs instead of on-demand instances. For more information, see Managed
	// Spot Training
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html).
	EnableManagedSpotTraining *bool

	// If the TrainingJob was created with network isolation, the value is set to true.
	// If network isolation is enabled, nodes can't communicate beyond the VPC they run
	// in.
	EnableNetworkIsolation *bool

	// Associates a SageMaker job as a trial component with an experiment and trial.
	// Specified when you call the following APIs:
	//
	// * CreateProcessingJob
	//
	// *
	// CreateTrainingJob
	//
	// * CreateTransformJob
	ExperimentConfig *ExperimentConfig

	// If the training job failed, the reason it failed.
	FailureReason *string

	// A list of final metric values that are set when the training job completes. Used
	// only if the training job was configured to use metrics.
	FinalMetricDataList []*MetricData

	// Algorithm-specific parameters.
	HyperParameters map[string]*string

	// An array of Channel objects that describes each data input channel.
	InputDataConfig []*Channel

	// The Amazon Resource Name (ARN) of the labeling job.
	LabelingJobArn *string

	// A timestamp that indicates when the status of the training job was last
	// modified.
	LastModifiedTime *time.Time

	// Information about the Amazon S3 location that is configured for storing model
	// artifacts.
	ModelArtifacts *ModelArtifacts

	// The S3 path where model artifacts that you configured when creating the job are
	// stored. Amazon SageMaker creates subfolders for model artifacts.
	OutputDataConfig *OutputDataConfig

	// Resources, including ML compute instances and ML storage volumes, that are
	// configured for model training.
	ResourceConfig *ResourceConfig

	// The AWS Identity and Access Management (IAM) role configured for the training
	// job.
	RoleArn *string

	// Provides detailed information about the state of the training job. For detailed
	// information about the secondary status of the training job, see StatusMessage
	// under SecondaryStatusTransition. Amazon SageMaker provides primary statuses and
	// secondary statuses that apply to each of them: InProgress
	//
	// * Starting - Starting
	// the training job.
	//
	// * Downloading - An optional stage for algorithms that support
	// File training input mode. It indicates that data is being downloaded to the ML
	// storage volumes.
	//
	// * Training - Training is in progress.
	//
	// * Uploading - Training
	// is complete and the model artifacts are being uploaded to the S3
	// location.
	//
	// Completed
	//
	// * Completed - The training job has completed.
	//
	// Failed
	//
	// *
	// Failed - The training job has failed. The reason for the failure is returned in
	// the FailureReason field of DescribeTrainingJobResponse.
	//
	// Stopped
	//
	// *
	// MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed
	// runtime.
	//
	// * Stopped - The training job has stopped.
	//
	// Stopping
	//
	// * Stopping -
	// Stopping the training job.
	//
	// Valid values for SecondaryStatus are subject to
	// change. We no longer support the following secondary statuses:
	//
	// *
	// LaunchingMLInstances
	//
	// * PreparingTrainingStack
	//
	// * DownloadingTrainingImage
	SecondaryStatus SecondaryStatus

	// A history of all of the secondary statuses that the training job has
	// transitioned through.
	SecondaryStatusTransitions []*SecondaryStatusTransition

	// 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. Use this API to cap
	// model training costs. To stop a job, Amazon SageMaker sends the algorithm the
	// SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use
	// this 120-second window to save the model artifacts, so the results of training
	// are not lost.
	StoppingCondition *StoppingCondition

	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*Tag

	// Configuration of storage locations for TensorBoard output.
	TensorBoardOutputConfig *TensorBoardOutputConfig

	// Indicates the time when the training job ends on training instances. You are
	// billed for the time interval between the value of TrainingStartTime and this
	// time. For successful jobs and stopped jobs, this is the time after model
	// artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker
	// detects a job failure.
	TrainingEndTime *time.Time

	// The Amazon Resource Name (ARN) of the training job.
	TrainingJobArn *string

	// The name of the training job.
	TrainingJobName *string

	// The status of the training job. Training job statuses are:
	//
	// * InProgress - The
	// training is in progress.
	//
	// * Completed - The training job has completed.
	//
	// *
	// Failed - The training job has failed. To see the reason for the failure, see the
	// FailureReason field in the response to a DescribeTrainingJobResponse call.
	//
	// *
	// Stopping - The training job is stopping.
	//
	// * Stopped - The training job has
	// stopped.
	//
	// For more detailed information, see SecondaryStatus.
	TrainingJobStatus TrainingJobStatus

	// Indicates the time when the training job starts on training instances. You are
	// billed for the time interval between this time and the value of TrainingEndTime.
	// The start time in CloudWatch Logs might be later than this time. The difference
	// is due to the time it takes to download the training data and to the size of the
	// training container.
	TrainingStartTime *time.Time

	// The training time in seconds.
	TrainingTimeInSeconds *int32

	// The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
	// the training job was launched by a hyperparameter tuning job.
	TuningJobArn *string

	// A VpcConfig object that specifies the VPC that this training job has access to.
	// For more information, see Protect Training Jobs by Using an Amazon Virtual
	// Private Cloud (https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html).
	VpcConfig *VpcConfig
}

Contains information about a training job.

type TrainingJobDefinition 

type TrainingJobDefinition struct {

	// An array of Channel objects, each of which specifies an input source.
	//
	// This member is required.
	InputDataConfig []*Channel

	// the path to the S3 bucket where you want to store model artifacts. Amazon
	// SageMaker creates subfolders for the artifacts.
	//
	// This member is required.
	OutputDataConfig *OutputDataConfig

	// The resources, including the ML compute instances and ML storage volumes, to use
	// for model training.
	//
	// This member is required.
	ResourceConfig *ResourceConfig

	// 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. Use this API to cap
	// model training costs. To stop a job, Amazon SageMaker sends the algorithm the
	// SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use
	// this 120-second window to save the model artifacts.
	//
	// This member is required.
	StoppingCondition *StoppingCondition

	// The input mode used by the algorithm for the training job. For the input modes
	// that Amazon SageMaker algorithms support, see Algorithms
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html). If an algorithm
	// supports the File input mode, Amazon SageMaker downloads the training data from
	// S3 to the provisioned ML storage Volume, and mounts the directory to docker
	// volume for training container. If an algorithm supports the Pipe input mode,
	// Amazon SageMaker streams data directly from S3 to the container.
	//
	// This member is required.
	TrainingInputMode TrainingInputMode

	// The hyperparameters used for the training job.
	HyperParameters map[string]*string
}

Defines the input needed to run a training job using the algorithm.

type TrainingJobEarlyStoppingType 

type TrainingJobEarlyStoppingType string
const (
	TrainingJobEarlyStoppingTypeOff  TrainingJobEarlyStoppingType = "Off"
	TrainingJobEarlyStoppingTypeAuto TrainingJobEarlyStoppingType = "Auto"
)

Enum values for TrainingJobEarlyStoppingType

func (TrainingJobEarlyStoppingType) Values added in v0.29.0 

func (TrainingJobEarlyStoppingType) Values() []TrainingJobEarlyStoppingType

Values returns all known values for TrainingJobEarlyStoppingType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TrainingJobSortByOptions 

type TrainingJobSortByOptions string
const (
	TrainingJobSortByOptionsName                      TrainingJobSortByOptions = "Name"
	TrainingJobSortByOptionsCreationtime              TrainingJobSortByOptions = "CreationTime"
	TrainingJobSortByOptionsStatus                    TrainingJobSortByOptions = "Status"
	TrainingJobSortByOptionsFinalobjectivemetricvalue TrainingJobSortByOptions = "FinalObjectiveMetricValue"
)

Enum values for TrainingJobSortByOptions

func (TrainingJobSortByOptions) Values added in v0.29.0 

func (TrainingJobSortByOptions) Values() []TrainingJobSortByOptions

Values returns all known values for TrainingJobSortByOptions. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TrainingJobStatus 

type TrainingJobStatus string
const (
	TrainingJobStatusInProgress TrainingJobStatus = "InProgress"
	TrainingJobStatusCompleted  TrainingJobStatus = "Completed"
	TrainingJobStatusFailed     TrainingJobStatus = "Failed"
	TrainingJobStatusStopping   TrainingJobStatus = "Stopping"
	TrainingJobStatusStopped    TrainingJobStatus = "Stopped"
)

Enum values for TrainingJobStatus

func (TrainingJobStatus) Values added in v0.29.0 

func (TrainingJobStatus) Values() []TrainingJobStatus

Values returns all known values for TrainingJobStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TrainingJobStatusCounters 

type TrainingJobStatusCounters struct {

	// The number of completed training jobs launched by the hyperparameter tuning job.
	Completed *int32

	// The number of in-progress training jobs launched by a hyperparameter tuning job.
	InProgress *int32

	// The number of training jobs that failed and can't be retried. A failed training
	// job can't be retried if it failed because a client error occurred.
	NonRetryableError *int32

	// The number of training jobs that failed, but can be retried. A failed training
	// job can be retried only if it failed because an internal service error occurred.
	RetryableError *int32

	// The number of training jobs launched by a hyperparameter tuning job that were
	// manually stopped.
	Stopped *int32
}

The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.

type TrainingJobSummary 

type TrainingJobSummary struct {

	// A timestamp that shows when the training job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the training job.
	//
	// This member is required.
	TrainingJobArn *string

	// The name of the training job that you want a summary for.
	//
	// This member is required.
	TrainingJobName *string

	// The status of the training job.
	//
	// This member is required.
	TrainingJobStatus TrainingJobStatus

	// Timestamp when the training job was last modified.
	LastModifiedTime *time.Time

	// A timestamp that shows when the training job ended. This field is set only if
	// the training job has one of the terminal statuses (Completed, Failed, or
	// Stopped).
	TrainingEndTime *time.Time
}

Provides summary information about a training job.

type TrainingSpecification 

type TrainingSpecification struct {

	// A list of the instance types that this algorithm can use for training.
	//
	// This member is required.
	SupportedTrainingInstanceTypes []TrainingInstanceType

	// A list of ChannelSpecification objects, which specify the input sources to be
	// used by the algorithm.
	//
	// This member is required.
	TrainingChannels []*ChannelSpecification

	// The Amazon ECR registry path of the Docker image that contains the training
	// algorithm.
	//
	// This member is required.
	TrainingImage *string

	// A list of MetricDefinition objects, which are used for parsing metrics generated
	// by the algorithm.
	MetricDefinitions []*MetricDefinition

	// A list of the HyperParameterSpecification objects, that define the supported
	// hyperparameters. This is required if the algorithm supports automatic model
	// tuning.>
	SupportedHyperParameters []*HyperParameterSpecification

	// A list of the metrics that the algorithm emits that can be used as the objective
	// metric in a hyperparameter tuning job.
	SupportedTuningJobObjectiveMetrics []*HyperParameterTuningJobObjective

	// Indicates whether the algorithm supports distributed training. If set to false,
	// buyers can't request more than one instance during training.
	SupportsDistributedTraining *bool

	// An MD5 hash of the training algorithm that identifies the Docker image used for
	// training.
	TrainingImageDigest *string
}

Defines how the algorithm is used for a training job.

type TransformDataSource 

type TransformDataSource struct {

	// The S3 location of the data source that is associated with a channel.
	//
	// This member is required.
	S3DataSource *TransformS3DataSource
}

Describes the location of the channel data.

type TransformInput 

type TransformInput struct {

	// Describes the location of the channel data, which is, the S3 location of the
	// input data that the model can consume.
	//
	// This member is required.
	DataSource *TransformDataSource

	// If your transform data is compressed, specify the compression type. Amazon
	// SageMaker automatically decompresses the data for the transform job accordingly.
	// The default value is None.
	CompressionType CompressionType

	// The multipurpose internet mail extension (MIME) type of the data. Amazon
	// SageMaker uses the MIME type with each http call to transfer data to the
	// transform job.
	ContentType *string

	// The method to use to split the transform job's data files into smaller batches.
	// Splitting is necessary when the total size of each object is too large to fit in
	// a single request. You can also use data splitting to improve performance by
	// processing multiple concurrent mini-batches. The default value for SplitType is
	// None, which indicates that input data files are not split, and request payloads
	// contain the entire contents of an input object. Set the value of this parameter
	// to Line to split records on a newline character boundary. SplitType also
	// supports a number of record-oriented binary data formats. Currently, the
	// supported record formats are:
	//
	// * RecordIO
	//
	// * TFRecord
	//
	// When splitting is
	// enabled, the size of a mini-batch depends on the values of the BatchStrategy and
	// MaxPayloadInMB parameters. When the value of BatchStrategy is MultiRecord,
	// Amazon SageMaker sends the maximum number of records in each request, up to the
	// MaxPayloadInMB limit. If the value of BatchStrategy is SingleRecord, Amazon
	// SageMaker sends individual records in each request. Some data formats represent
	// a record as a binary payload wrapped with extra padding bytes. When splitting is
	// applied to a binary data format, padding is removed if the value of
	// BatchStrategy is set to SingleRecord. Padding is not removed if the value of
	// BatchStrategy is set to MultiRecord. For more information about RecordIO, see
	// Create a Dataset Using RecordIO (https://mxnet.apache.org/api/faq/recordio) in
	// the MXNet documentation. For more information about TFRecord, see Consuming
	// TFRecord data
	// (https://www.tensorflow.org/guide/datasets#consuming_tfrecord_data) in the
	// TensorFlow documentation.
	SplitType SplitType
}

Describes the input source of a transform job and the way the transform job consumes it.

type TransformInstanceType 

type TransformInstanceType string
const (
	TransformInstanceTypeMlM4Xlarge   TransformInstanceType = "ml.m4.xlarge"
	TransformInstanceTypeMlM42xlarge  TransformInstanceType = "ml.m4.2xlarge"
	TransformInstanceTypeMlM44xlarge  TransformInstanceType = "ml.m4.4xlarge"
	TransformInstanceTypeMlM410xlarge TransformInstanceType = "ml.m4.10xlarge"
	TransformInstanceTypeMlM416xlarge TransformInstanceType = "ml.m4.16xlarge"
	TransformInstanceTypeMlC4Xlarge   TransformInstanceType = "ml.c4.xlarge"
	TransformInstanceTypeMlC42xlarge  TransformInstanceType = "ml.c4.2xlarge"
	TransformInstanceTypeMlC44xlarge  TransformInstanceType = "ml.c4.4xlarge"
	TransformInstanceTypeMlC48xlarge  TransformInstanceType = "ml.c4.8xlarge"
	TransformInstanceTypeMlP2Xlarge   TransformInstanceType = "ml.p2.xlarge"
	TransformInstanceTypeMlP28xlarge  TransformInstanceType = "ml.p2.8xlarge"
	TransformInstanceTypeMlP216xlarge TransformInstanceType = "ml.p2.16xlarge"
	TransformInstanceTypeMlP32xlarge  TransformInstanceType = "ml.p3.2xlarge"
	TransformInstanceTypeMlP38xlarge  TransformInstanceType = "ml.p3.8xlarge"
	TransformInstanceTypeMlP316xlarge TransformInstanceType = "ml.p3.16xlarge"
	TransformInstanceTypeMlC5Xlarge   TransformInstanceType = "ml.c5.xlarge"
	TransformInstanceTypeMlC52xlarge  TransformInstanceType = "ml.c5.2xlarge"
	TransformInstanceTypeMlC54xlarge  TransformInstanceType = "ml.c5.4xlarge"
	TransformInstanceTypeMlC59xlarge  TransformInstanceType = "ml.c5.9xlarge"
	TransformInstanceTypeMlC518xlarge TransformInstanceType = "ml.c5.18xlarge"
	TransformInstanceTypeMlM5Large    TransformInstanceType = "ml.m5.large"
	TransformInstanceTypeMlM5Xlarge   TransformInstanceType = "ml.m5.xlarge"
	TransformInstanceTypeMlM52xlarge  TransformInstanceType = "ml.m5.2xlarge"
	TransformInstanceTypeMlM54xlarge  TransformInstanceType = "ml.m5.4xlarge"
	TransformInstanceTypeMlM512xlarge TransformInstanceType = "ml.m5.12xlarge"
	TransformInstanceTypeMlM524xlarge TransformInstanceType = "ml.m5.24xlarge"
)

Enum values for TransformInstanceType

func (TransformInstanceType) Values added in v0.29.0 

func (TransformInstanceType) Values() []TransformInstanceType

Values returns all known values for TransformInstanceType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TransformJob 

type TransformJob struct {

	// The Amazon Resource Name (ARN) of the AutoML job that created the transform job.
	AutoMLJobArn *string

	// Specifies the number of records to include in a mini-batch for an HTTP inference
	// request. A record is a single unit of input data that inference can be made on.
	// For example, a single line in a CSV file is a record.
	BatchStrategy BatchStrategy

	// A timestamp that shows when the transform Job was created.
	CreationTime *time.Time

	// The data structure used to specify the data to be used for inference in a batch
	// transform job and to associate the data that is relevant to the prediction
	// results in the output. The input filter provided allows you to exclude input
	// data that is not needed for inference in a batch transform job. The output
	// filter provided allows you to include input data relevant to interpreting the
	// predictions in the output from the job. For more information, see Associate
	// Prediction Results with their Corresponding Input Records
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html).
	DataProcessing *DataProcessing

	// The environment variables to set in the Docker container. We support up to 16
	// key and values entries in the map.
	Environment map[string]*string

	// Associates a SageMaker job as a trial component with an experiment and trial.
	// Specified when you call the following APIs:
	//
	// * CreateProcessingJob
	//
	// *
	// CreateTrainingJob
	//
	// * CreateTransformJob
	ExperimentConfig *ExperimentConfig

	// If the transform job failed, the reason it failed.
	FailureReason *string

	// The Amazon Resource Name (ARN) of the labeling job that created the transform
	// job.
	LabelingJobArn *string

	// The maximum number of parallel requests that can be sent to each instance in a
	// transform job. If MaxConcurrentTransforms is set to 0 or left unset, 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. For built-in algorithms, you don't need to set a value for
	// MaxConcurrentTransforms.
	MaxConcurrentTransforms *int32

	// The maximum allowed size of the payload, in MB. A payload is the data portion of
	// a record (without metadata). The value in MaxPayloadInMB must be greater than,
	// or equal to, the size of a single record. To estimate the size of a record in
	// MB, divide the size of your dataset by the number of records. To ensure that the
	// records fit within the maximum payload size, we recommend using a slightly
	// larger value. The default value is 6 MB. For cases where the payload might be
	// arbitrarily large and is transmitted using HTTP chunked encoding, set the value
	// to 0. This feature works only in supported algorithms. Currently, SageMaker
	// built-in algorithms do not support HTTP chunked encoding.
	MaxPayloadInMB *int32

	// Configures the timeout and maximum number of retries for processing a transform
	// job invocation.
	ModelClientConfig *ModelClientConfig

	// The name of the model associated with the transform job.
	ModelName *string

	// A list of tags associated with the transform job.
	Tags []*Tag

	// Indicates when the transform job has been completed, or has stopped or failed.
	// You are billed for the time interval between this time and the value of
	// TransformStartTime.
	TransformEndTime *time.Time

	// Describes the input source of a transform job and the way the transform job
	// consumes it.
	TransformInput *TransformInput

	// The Amazon Resource Name (ARN) of the transform job.
	TransformJobArn *string

	// The name of the transform job.
	TransformJobName *string

	// The status of the transform job. Transform job statuses are:
	//
	// * InProgress - The
	// job is in progress.
	//
	// * Completed - The job has completed.
	//
	// * Failed - The
	// transform job has failed. To see the reason for the failure, see the
	// FailureReason field in the response to a DescribeTransformJob call.
	//
	// * Stopping
	// - The transform job is stopping.
	//
	// * Stopped - The transform job has stopped.
	TransformJobStatus TransformJobStatus

	// Describes the results of a transform job.
	TransformOutput *TransformOutput

	// Describes the resources, including ML instance types and ML instance count, to
	// use for transform job.
	TransformResources *TransformResources

	// Indicates when the transform job starts on ML instances. You are billed for the
	// time interval between this time and the value of TransformEndTime.
	TransformStartTime *time.Time
}

A batch transform job. For information about SageMaker batch transform, see Use Batch Transform (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html).

type TransformJobDefinition 

type TransformJobDefinition struct {

	// A description of the input source and the way the transform job consumes it.
	//
	// This member is required.
	TransformInput *TransformInput

	// Identifies the Amazon S3 location where you want Amazon SageMaker to save the
	// results from the transform job.
	//
	// This member is required.
	TransformOutput *TransformOutput

	// Identifies the ML compute instances for the transform job.
	//
	// This member is required.
	TransformResources *TransformResources

	// A string that determines the number of records included in a single mini-batch.
	// SingleRecord means only one record is used per mini-batch. MultiRecord means a
	// mini-batch is set to contain as many records that can fit within the
	// MaxPayloadInMB limit.
	BatchStrategy BatchStrategy

	// The environment variables to set in the Docker container. We support up to 16
	// key and values entries in the map.
	Environment map[string]*string

	// The maximum number of parallel requests that can be sent to each instance in a
	// transform job. The default value is 1.
	MaxConcurrentTransforms *int32

	// The maximum payload size allowed, in MB. A payload is the data portion of a
	// record (without metadata).
	MaxPayloadInMB *int32
}

Defines the input needed to run a transform job using the inference specification specified in the algorithm.

type TransformJobStatus 

type TransformJobStatus string
const (
	TransformJobStatusInProgress TransformJobStatus = "InProgress"
	TransformJobStatusCompleted  TransformJobStatus = "Completed"
	TransformJobStatusFailed     TransformJobStatus = "Failed"
	TransformJobStatusStopping   TransformJobStatus = "Stopping"
	TransformJobStatusStopped    TransformJobStatus = "Stopped"
)

Enum values for TransformJobStatus

func (TransformJobStatus) Values added in v0.29.0 

func (TransformJobStatus) Values() []TransformJobStatus

Values returns all known values for TransformJobStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TransformJobSummary 

type TransformJobSummary struct {

	// A timestamp that shows when the transform Job was created.
	//
	// This member is required.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the transform job.
	//
	// This member is required.
	TransformJobArn *string

	// The name of the transform job.
	//
	// This member is required.
	TransformJobName *string

	// The status of the transform job.
	//
	// This member is required.
	TransformJobStatus TransformJobStatus

	// If the transform job failed, the reason it failed.
	FailureReason *string

	// Indicates when the transform job was last modified.
	LastModifiedTime *time.Time

	// Indicates when the transform job ends on compute instances. For successful jobs
	// and stopped jobs, this is the exact time recorded after the results are
	// uploaded. For failed jobs, this is when Amazon SageMaker detected that the job
	// failed.
	TransformEndTime *time.Time
}

Provides a summary of a transform job. Multiple TransformJobSummary objects are returned as a list after in response to a ListTransformJobs call.

type TransformOutput 

type TransformOutput struct {

	// The Amazon S3 path where you want Amazon SageMaker to store the results of the
	// transform job. For example, s3://bucket-name/key-name-prefix. For every S3
	// object used as input for the transform job, batch transform stores the
	// transformed data with an .out suffix in a corresponding subfolder in the
	// location in the output prefix. For example, for the input data stored at
	// s3://bucket-name/input-name-prefix/dataset01/data.csv, batch transform stores
	// the transformed data at
	// s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out. Batch
	// transform doesn't upload partially processed objects. For an input S3 object
	// that contains multiple records, it creates an .out file only if the transform
	// job succeeds on the entire file. When the input contains multiple S3 objects,
	// the batch transform job processes the listed S3 objects and uploads only the
	// output for successfully processed objects. If any object fails in the transform
	// job batch transform marks the job as failed to prompt investigation.
	//
	// This member is required.
	S3OutputPath *string

	// The MIME type used to specify the output data. Amazon SageMaker uses the MIME
	// type with each http call to transfer data from the transform job.
	Accept *string

	// Defines how to assemble the results of the transform job as a single S3 object.
	// Choose a format that is most convenient to you. To concatenate the results in
	// binary format, specify None. To add a newline character at the end of every
	// transformed record, specify Line.
	AssembleWith AssemblyType

	// The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to
	// encrypt the model artifacts at rest using Amazon S3 server-side encryption. The
	// KmsKeyId can be any of the following formats:
	//
	// * Key ID:
	// 1234abcd-12ab-34cd-56ef-1234567890ab
	//
	// * Key ARN:
	// arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
	//
	// *
	// Alias name: alias/ExampleAlias
	//
	// * Alias name ARN:
	// arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
	//
	// If you don't provide a
	// KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your
	// role's account. For more information, see KMS-Managed Encryption Keys
	// (https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html) in the
	// Amazon Simple Storage Service Developer Guide. The KMS key policy must grant
	// permission to the IAM role that you specify in your CreateModel request. For
	// more information, see Using Key Policies in AWS KMS
	// (http://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html) in the
	// AWS Key Management Service Developer Guide.
	KmsKeyId *string
}

Describes the results of a transform job.

type TransformResources 

type TransformResources struct {

	// The number of ML compute instances to use in the transform job. For distributed
	// transform jobs, specify a value greater than 1. The default value is 1.
	//
	// This member is required.
	InstanceCount *int32

	// The ML compute instance type for the transform job. If you are using built-in
	// algorithms to transform moderately sized datasets, we recommend using
	// ml.m4.xlarge or ml.m5.large instance types.
	//
	// This member is required.
	InstanceType TransformInstanceType

	// The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to
	// encrypt model data on the storage volume attached to the ML compute instance(s)
	// that run the batch transform job. The VolumeKmsKeyId can be any of the following
	// formats:
	//
	// * Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab
	//
	// * Key ARN:
	// arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab
	//
	// *
	// Alias name: alias/ExampleAlias
	//
	// * Alias name ARN:
	// arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias
	VolumeKmsKeyId *string
}

Describes the resources, including ML instance types and ML instance count, to use for transform job.

type TransformS3DataSource 

type TransformS3DataSource struct {

	// If you choose S3Prefix, S3Uri identifies a key name prefix. Amazon SageMaker
	// uses all objects with the specified key name prefix for batch transform. If you
	// choose ManifestFile, S3Uri identifies an object that is a manifest file
	// containing a list of object keys that you want Amazon SageMaker to use for batch
	// transform. The following values are compatible: ManifestFile, S3Prefix The
	// following value is not compatible: AugmentedManifestFile
	//
	// This member is required.
	S3DataType S3DataType

	// Depending on the value specified for the S3DataType, identifies either a key
	// name prefix or a manifest. For example:
	//
	// * A key name prefix might look like
	// this: s3://bucketname/exampleprefix.
	//
	// * A manifest might look like this:
	// s3://bucketname/example.manifest The manifest is an S3 object which is a JSON
	// file with the following format: [ {"prefix":
	// "s3://customer_bucket/some/prefix/"},"relative/path/to/custdata-1","relative/path/custdata-2",..."relative/path/custdata-N"]
	// The preceding JSON matches the following S3Uris:
	// s3://customer_bucket/some/prefix/relative/path/to/custdata-1s3://customer_bucket/some/prefix/relative/path/custdata-2...s3://customer_bucket/some/prefix/relative/path/custdata-N
	// The complete set of S3Uris in this manifest constitutes the input data for the
	// channel for this datasource. The object that each S3Uris points to must be
	// readable by the IAM role that Amazon SageMaker uses to perform tasks on your
	// behalf.
	//
	// This member is required.
	S3Uri *string
}

Describes the S3 data source.

type Trial 

type Trial struct {

	// Information about the user who created or modified an experiment, trial, or
	// trial component.
	CreatedBy *UserContext

	// When the trial was created.
	CreationTime *time.Time

	// The name of the trial as displayed. If DisplayName isn't specified, TrialName is
	// displayed.
	DisplayName *string

	// The name of the experiment the trial is part of.
	ExperimentName *string

	// Information about the user who created or modified an experiment, trial, or
	// trial component.
	LastModifiedBy *UserContext

	// Who last modified the trial.
	LastModifiedTime *time.Time

	// The source of the trial.
	Source *TrialSource

	// The list of tags that are associated with the trial. You can use Search API to
	// search on the tags.
	Tags []*Tag

	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

	// A list of the components associated with the trial. For each component, a
	// summary of the component's properties is included.
	TrialComponentSummaries []*TrialComponentSimpleSummary

	// The name of the trial.
	TrialName *string
}

The properties of a trial as returned by the Search API.

type TrialComponent 

type TrialComponent struct {

	// Information about the user who created or modified an experiment, trial, or
	// trial component.
	CreatedBy *UserContext

	// When the component was created.
	CreationTime *time.Time

	// The name of the component as displayed. If DisplayName isn't specified,
	// TrialComponentName is displayed.
	DisplayName *string

	// When the component ended.
	EndTime *time.Time

	// The input artifacts of the component.
	InputArtifacts map[string]*TrialComponentArtifact

	// Information about the user who created or modified an experiment, trial, or
	// trial component.
	LastModifiedBy *UserContext

	// When the component was last modified.
	LastModifiedTime *time.Time

	// The metrics for the component.
	Metrics []*TrialComponentMetricSummary

	// The output artifacts of the component.
	OutputArtifacts map[string]*TrialComponentArtifact

	// The hyperparameters of the component.
	Parameters map[string]*TrialComponentParameterValue

	// An array of the parents of the component. A parent is a trial the component is
	// associated with and the experiment the trial is part of. A component might not
	// have any parents.
	Parents []*Parent

	// The Amazon Resource Name (ARN) and job type of the source of the component.
	Source *TrialComponentSource

	// Details of the source of the component.
	SourceDetail *TrialComponentSourceDetail

	// When the component started.
	StartTime *time.Time

	// The status of the trial component.
	Status *TrialComponentStatus

	// The list of tags that are associated with the component. You can use Search API
	// to search on the tags.
	Tags []*Tag

	// The Amazon Resource Name (ARN) of the trial component.
	TrialComponentArn *string

	// The name of the trial component.
	TrialComponentName *string
}

The properties of a trial component as returned by the Search API.

type TrialComponentArtifact 

type TrialComponentArtifact struct {

	// The location of the artifact.
	//
	// This member is required.
	Value *string

	// The media type of the artifact, which indicates the type of data in the artifact
	// file. The media type consists of a type and a subtype concatenated with a slash
	// (/) character, for example, text/csv, image/jpeg, and s3/uri. The type specifies
	// the category of the media. The subtype specifies the kind of data.
	MediaType *string
}

Represents an input or output artifact of a trial component. You specify TrialComponentArtifact as part of the InputArtifacts and OutputArtifacts parameters in the CreateTrialComponent request. Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.

type TrialComponentMetricSummary 

type TrialComponentMetricSummary struct {

	// The average value of the metric.
	Avg *float64

	// The number of samples used to generate the metric.
	Count *int32

	// The most recent value of the metric.
	Last *float64

	// The maximum value of the metric.
	Max *float64

	// The name of the metric.
	MetricName *string

	// The minimum value of the metric.
	Min *float64

	// The Amazon Resource Name (ARN) of the source.
	SourceArn *string

	// The standard deviation of the metric.
	StdDev *float64

	// When the metric was last updated.
	TimeStamp *time.Time
}

A summary of the metrics of a trial component.

type TrialComponentParameterValue 

type TrialComponentParameterValue struct {

	// The numeric value of a numeric hyperparameter. If you specify a value for this
	// parameter, you can't specify the StringValue parameter.
	NumberValue *float64

	// The string value of a categorical hyperparameter. If you specify a value for
	// this parameter, you can't specify the NumberValue parameter.
	StringValue *string
}

The value of a hyperparameter. Only one of NumberValue or StringValue can be specified. This object is specified in the CreateTrialComponent request.

type TrialComponentPrimaryStatus 

type TrialComponentPrimaryStatus string
const (
	TrialComponentPrimaryStatusInProgress TrialComponentPrimaryStatus = "InProgress"
	TrialComponentPrimaryStatusCompleted  TrialComponentPrimaryStatus = "Completed"
	TrialComponentPrimaryStatusFailed     TrialComponentPrimaryStatus = "Failed"
	TrialComponentPrimaryStatusStopping   TrialComponentPrimaryStatus = "Stopping"
	TrialComponentPrimaryStatusStopped    TrialComponentPrimaryStatus = "Stopped"
)

Enum values for TrialComponentPrimaryStatus

func (TrialComponentPrimaryStatus) Values added in v0.29.0 

func (TrialComponentPrimaryStatus) Values() []TrialComponentPrimaryStatus

Values returns all known values for TrialComponentPrimaryStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type TrialComponentSimpleSummary 

type TrialComponentSimpleSummary struct {

	// Information about the user who created or modified an experiment, trial, or
	// trial component.
	CreatedBy *UserContext

	// When the component was created.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the trial component.
	TrialComponentArn *string

	// The name of the trial component.
	TrialComponentName *string

	// The Amazon Resource Name (ARN) and job type of the source of a trial component.
	TrialComponentSource *TrialComponentSource
}

A short summary of a trial component.

type TrialComponentSource 

type TrialComponentSource struct {

	// The source ARN.
	//
	// This member is required.
	SourceArn *string

	// The source job type.
	SourceType *string
}

The Amazon Resource Name (ARN) and job type of the source of a trial component.

type TrialComponentSourceDetail 

type TrialComponentSourceDetail struct {

	// Information about a processing job that's the source of a trial component.
	ProcessingJob *ProcessingJob

	// The Amazon Resource Name (ARN) of the source.
	SourceArn *string

	// Information about a training job that's the source of a trial component.
	TrainingJob *TrainingJob

	// Information about a transform job that's the source of a trial component.
	TransformJob *TransformJob
}

Detailed information about the source of a trial component. Either ProcessingJob or TrainingJob is returned.

type TrialComponentStatus 

type TrialComponentStatus struct {

	// If the component failed, a message describing why.
	Message *string

	// The status of the trial component.
	PrimaryStatus TrialComponentPrimaryStatus
}

The status of the trial component.

type TrialComponentSummary 

type TrialComponentSummary struct {

	// Who created the component.
	CreatedBy *UserContext

	// When the component was created.
	CreationTime *time.Time

	// The name of the component as displayed. If DisplayName isn't specified,
	// TrialComponentName is displayed.
	DisplayName *string

	// When the component ended.
	EndTime *time.Time

	// Who last modified the component.
	LastModifiedBy *UserContext

	// When the component was last modified.
	LastModifiedTime *time.Time

	// When the component started.
	StartTime *time.Time

	// The status of the component. States include:
	//
	// * InProgress
	//
	// * Completed
	//
	// *
	// Failed
	Status *TrialComponentStatus

	// The ARN of the trial component.
	TrialComponentArn *string

	// The name of the trial component.
	TrialComponentName *string

	// The Amazon Resource Name (ARN) and job type of the source of a trial component.
	TrialComponentSource *TrialComponentSource
}

A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName.

type TrialSource 

type TrialSource struct {

	// The Amazon Resource Name (ARN) of the source.
	//
	// This member is required.
	SourceArn *string

	// The source job type.
	SourceType *string
}

The source of the trial.

type TrialSummary 

type TrialSummary struct {

	// When the trial was created.
	CreationTime *time.Time

	// The name of the trial as displayed. If DisplayName isn't specified, TrialName is
	// displayed.
	DisplayName *string

	// When the trial was last modified.
	LastModifiedTime *time.Time

	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

	// The name of the trial.
	TrialName *string

	// The source of the trial.
	TrialSource *TrialSource
}

A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName.

type TuningJobCompletionCriteria 

type TuningJobCompletionCriteria struct {

	// The value of the objective metric.
	//
	// This member is required.
	TargetObjectiveMetricValue *float32
}

The job completion criteria.

type USD 

type USD struct {

	// The fractional portion, in cents, of the amount.
	Cents *int32

	// The whole number of dollars in the amount.
	Dollars *int32

	// Fractions of a cent, in tenths.
	TenthFractionsOfACent *int32
}

Represents an amount of money in United States dollars/

type UiConfig 

type UiConfig struct {

	// The ARN of the worker task template used to render the worker UI and tools for
	// labeling job tasks. Use this parameter when you are creating a labeling job for
	// 3D point cloud and video fram labeling jobs. Use your labeling job task type to
	// select one of the following ARN's and use it with this parameter when you create
	// a labeling job. Replace aws-region with the AWS region you are creating your
	// labeling job in. 3D Point Cloud HumanTaskUiArns Use this HumanTaskUiArn for 3D
	// point cloud object detection and 3D point cloud object detection adjustment
	// labeling jobs.
	//
	// *
	// arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection
	//
	// Use
	// this HumanTaskUiArn for 3D point cloud object tracking and 3D point cloud object
	// tracking adjustment labeling jobs.
	//
	// *
	// arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking
	//
	// Use
	// this HumanTaskUiArn for 3D point cloud semantic segmentation and 3D point cloud
	// semantic segmentation adjustment labeling jobs.
	//
	// *
	// arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation
	//
	// Video
	// Frame HumanTaskUiArns Use this HumanTaskUiArn for video frame object detection
	// and video frame object detection adjustment labeling jobs.
	//
	// *
	// arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection
	//
	// Use
	// this HumanTaskUiArn for video frame object tracking and video frame object
	// tracking adjustment labeling jobs.
	//
	// *
	// arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking
	HumanTaskUiArn *string

	// The Amazon S3 bucket location of the UI template, or worker task template. This
	// is the template used to render the worker UI and tools for labeling job tasks.
	// For more information about the contents of a UI template, see  Creating Your
	// Custom Labeling Task Template
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step2.html).
	UiTemplateS3Uri *string
}

Provided configuration information for the worker UI for a labeling job.

type UiTemplate 

type UiTemplate struct {

	// The content of the Liquid template for the worker user interface.
	//
	// This member is required.
	Content *string
}

The Liquid template for the worker user interface.

type UiTemplateInfo 

type UiTemplateInfo struct {

	// The SHA-256 digest of the contents of the template.
	ContentSha256 *string

	// The URL for the user interface template.
	Url *string
}

Container for user interface template information.

type UserContext 

type UserContext struct {

	// The domain associated with the user.
	DomainId *string

	// The Amazon Resource Name (ARN) of the user's profile.
	UserProfileArn *string

	// The name of the user's profile.
	UserProfileName *string
}

Information about the user who created or modified an experiment, trial, or trial component.

type UserProfileDetails 

type UserProfileDetails struct {

	// The creation time.
	CreationTime *time.Time

	// The domain ID.
	DomainId *string

	// The last modified time.
	LastModifiedTime *time.Time

	// The status.
	Status UserProfileStatus

	// The user profile name.
	UserProfileName *string
}

The user profile details.

type UserProfileSortKey 

type UserProfileSortKey string
const (
	UserProfileSortKeyCreationtime     UserProfileSortKey = "CreationTime"
	UserProfileSortKeyLastmodifiedtime UserProfileSortKey = "LastModifiedTime"
)

Enum values for UserProfileSortKey

func (UserProfileSortKey) Values added in v0.29.0 

func (UserProfileSortKey) Values() []UserProfileSortKey

Values returns all known values for UserProfileSortKey. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type UserProfileStatus 

type UserProfileStatus string
const (
	UserProfileStatusDeleting     UserProfileStatus = "Deleting"
	UserProfileStatusFailed       UserProfileStatus = "Failed"
	UserProfileStatusInservice    UserProfileStatus = "InService"
	UserProfileStatusPending      UserProfileStatus = "Pending"
	UserProfileStatusUpdating     UserProfileStatus = "Updating"
	UserProfileStatusUpdateFailed UserProfileStatus = "Update_Failed"
	UserProfileStatusDeleteFailed UserProfileStatus = "Delete_Failed"
)

Enum values for UserProfileStatus

func (UserProfileStatus) Values added in v0.29.0 

func (UserProfileStatus) Values() []UserProfileStatus

Values returns all known values for UserProfileStatus. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type UserSettings 

type UserSettings struct {

	// The execution role for the user.
	ExecutionRole *string

	// The Jupyter server's app settings.
	JupyterServerAppSettings *JupyterServerAppSettings

	// The kernel gateway app settings.
	KernelGatewayAppSettings *KernelGatewayAppSettings

	// The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses
	// for communication. Optional when the CreateDomain.AppNetworkAccessType parameter
	// is set to PublicInternetOnly. Required when the
	// CreateDomain.AppNetworkAccessType parameter is set to VpcOnly.
	SecurityGroups []*string

	// The sharing settings.
	SharingSettings *SharingSettings

	// The TensorBoard app settings.
	TensorBoardAppSettings *TensorBoardAppSettings
}

A collection of settings.

type VariantProperty 

type VariantProperty struct {

	// The type of variant property. The supported values are:
	//
	// * DesiredInstanceCount:
	// Overrides the existing variant instance counts using the
	// ProductionVariant$InitialInstanceCount values in the
	// CreateEndpointConfigInput$ProductionVariants.
	//
	// * DesiredWeight: Overrides the
	// existing variant weights using the ProductionVariant$InitialVariantWeight values
	// in the CreateEndpointConfigInput$ProductionVariants.
	//
	// * DataCaptureConfig: (Not
	// currently supported.)
	//
	// This member is required.
	VariantPropertyType VariantPropertyType
}

Specifies a production variant property type for an Endpoint. If you are updating an endpoint with the UpdateEndpointInput$RetainAllVariantProperties option set to true, the VariantProperty objects listed in UpdateEndpointInput$ExcludeRetainedVariantProperties override the existing variant properties of the endpoint.

type VariantPropertyType 

type VariantPropertyType string
const (
	VariantPropertyTypeDesiredinstancecount VariantPropertyType = "DesiredInstanceCount"
	VariantPropertyTypeDesiredweight        VariantPropertyType = "DesiredWeight"
	VariantPropertyTypeDatacaptureconfig    VariantPropertyType = "DataCaptureConfig"
)

Enum values for VariantPropertyType

func (VariantPropertyType) Values added in v0.29.0 

func (VariantPropertyType) Values() []VariantPropertyType

Values returns all known values for VariantPropertyType. Note that this can be expanded in the future, and so it is only as up to date as the client. The ordering of this slice is not guaranteed to be stable across updates.

type VpcConfig 

type VpcConfig struct {

	// The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups
	// for the VPC that is specified in the Subnets field.
	//
	// This member is required.
	SecurityGroupIds []*string

	// The ID of the subnets in the VPC to which you want to connect your training job
	// or model. For information about the availability of specific instance types, see
	// Supported Instance Types and Availability Zones
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/instance-types-az.html).
	//
	// This member is required.
	Subnets []*string
}

Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud (https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html) and Protect Training Jobs by Using an Amazon Virtual Private Cloud (https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html).

type Workforce 

type Workforce struct {

	// The Amazon Resource Name (ARN) of the private workforce.
	//
	// This member is required.
	WorkforceArn *string

	// The name of the private workforce.
	//
	// This member is required.
	WorkforceName *string

	// The configuration of an Amazon Cognito workforce. A single Cognito workforce is
	// created using and corresponds to a single  Amazon Cognito user pool
	// (https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html).
	CognitoConfig *CognitoConfig

	// The date that the workforce is created.
	CreateDate *time.Time

	// The most recent date that was used to successfully add one or more IP address
	// ranges (CIDRs
	// (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html)) to a
	// private workforce's allow list.
	LastUpdatedDate *time.Time

	// The configuration of an OIDC Identity Provider (IdP) private workforce.
	OidcConfig *OidcConfigForResponse

	// A list of one to ten IP address ranges (CIDRs
	// (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html)) to be added
	// to the workforce allow list. By default, a workforce isn't restricted to
	// specific IP addresses.
	SourceIpConfig *SourceIpConfig

	// The subdomain for your OIDC Identity Provider.
	SubDomain *string
}

A single private workforce, which is automatically created when you create your first private work team. You can create one private work force in each AWS Region. By default, any workforce-related API operation used in a specific region will apply to the workforce created in that region. To learn how to create a private workforce, see Create a Private Workforce (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html).

type Workteam 

type Workteam struct {

	// A description of the work team.
	//
	// This member is required.
	Description *string

	// A list of MemberDefinition objects that contains objects that identify the
	// workers that make up the work team. Workforces can be created using Amazon
	// Cognito or your own OIDC Identity Provider (IdP). For private workforces created
	// using Amazon Cognito use CognitoMemberDefinition. For workforces created using
	// your own OIDC identity provider (IdP) use OidcMemberDefinition.
	//
	// This member is required.
	MemberDefinitions []*MemberDefinition

	// The Amazon Resource Name (ARN) that identifies the work team.
	//
	// This member is required.
	WorkteamArn *string

	// The name of the work team.
	//
	// This member is required.
	WorkteamName *string

	// The date and time that the work team was created (timestamp).
	CreateDate *time.Time

	// The date and time that the work team was last updated (timestamp).
	LastUpdatedDate *time.Time

	// Configures SNS notifications of available or expiring work items for work teams.
	NotificationConfiguration *NotificationConfiguration

	// The Amazon Marketplace identifier for a vendor's work team.
	ProductListingIds []*string

	// The URI of the labeling job's user interface. Workers open this URI to start
	// labeling your data objects.
	SubDomain *string

	// The Amazon Resource Name (ARN) of the workforce.
	WorkforceArn *string
}

Provides details about a labeling work team.

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