types

package
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 Go to latest Published: Nov 12, 2021 License: Apache-2.0 Imports: 4 Imported by: 8

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Types

type ActionSource added in v0.31.0 

type ActionSource struct {

	// The URI of the source.
	//
	// This member is required.
	SourceUri *string

	// The ID of the source.
	SourceId *string

	// The type of the source.
	SourceType *string
	// contains filtered or unexported fields
}

A structure describing the source of an action.

type ActionStatus added in v0.31.0 

type ActionStatus string
const (
	ActionStatusUnknown    ActionStatus = "Unknown"
	ActionStatusInProgress ActionStatus = "InProgress"
	ActionStatusCompleted  ActionStatus = "Completed"
	ActionStatusFailed     ActionStatus = "Failed"
	ActionStatusStopping   ActionStatus = "Stopping"
	ActionStatusStopped    ActionStatus = "Stopped"
)

Enum values for ActionStatus

func (ActionStatus) Values added in v0.31.0 

func (ActionStatus) Values() []ActionStatus

Values returns all known values for ActionStatus. 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 ActionSummary added in v0.31.0 

type ActionSummary struct {

	// The Amazon Resource Name (ARN) of the action.
	ActionArn *string

	// The name of the action.
	ActionName *string

	// The type of the action.
	ActionType *string

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

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

	// The source of the action.
	Source *ActionSource

	// The status of the action.
	Status ActionStatus
	// contains filtered or unexported fields
}

Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.

type AgentVersion added in v0.31.0 

type AgentVersion struct {

	// The number of Edge Manager agents.
	//
	// This member is required.
	AgentCount int64

	// Version of the agent.
	//
	// This member is required.
	Version *string
	// contains filtered or unexported fields
}

Edge Manager agent version.

type Alarm added in v0.31.0 

type Alarm struct {

	// The name of a CloudWatch alarm in your account.
	AlarmName *string
	// contains filtered or unexported fields
}

An Amazon CloudWatch alarm configured to monitor metrics on an endpoint.

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 training input mode that the algorithm supports. For more information about
	// input modes, see Algorithms
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html). Pipe mode If an
	// algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon
	// S3 to the container. File mode If an algorithm supports File mode, SageMaker
	// downloads the training data from S3 to the provisioned ML storage volume, and
	// mounts the directory to the Docker volume for the training container. You must
	// provision the ML storage volume with sufficient capacity to accommodate the data
	// downloaded from S3. In addition to the training data, the ML storage volume also
	// stores the output model. The algorithm container uses the ML storage volume to
	// also store intermediate information, if any. For distributed algorithms,
	// training data is distributed uniformly. Your training duration is predictable if
	// the input data objects sizes are approximately the same. 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 when one host
	// in a training cluster is overloaded, thus becoming a bottleneck in training.
	// FastFile mode If an algorithm supports FastFile mode, SageMaker streams data
	// directly from S3 to the container with no code changes, and provides file system
	// access to the data. Users can author their training script to interact with
	// these files as if they were stored on disk. FastFile mode works best when the
	// data is read sequentially. Augmented manifest files aren't supported. The
	// startup time is lower when there are fewer files in the S3 bucket provided.
	//
	// 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 Amazon Web Services
	// 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 Amazon Web Services 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
	// contains filtered or unexported fields
}

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-BoundingBox
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox
	//
	// *
	// arn: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-ImageMultiClass
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass
	//
	// *
	// arn: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-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel
	//
	// *
	// arn: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-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation
	//
	// *
	// arn: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-TextMultiClass
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass
	//
	// *
	// arn: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-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel
	//
	// *
	// arn: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-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition
	//
	// *
	// arn: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-VideoMultiClass
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass
	//
	// *
	// arn: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-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection
	//
	// *
	// arn: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-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking
	//
	// *
	// arn: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-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection
	//
	// *
	// arn: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-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking
	//
	// *
	// arn: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-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation
	//
	// *
	// arn: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-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation
	//
	// *
	// arn: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-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation
	//
	// 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-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox
	//
	// 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-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox
	//
	// 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-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection
	//
	// *
	// arn: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-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking
	//
	// *
	// arn: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-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection
	//
	// *
	// arn: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-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking
	//
	// *
	// arn: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-3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation
	//
	// This member is required.
	AnnotationConsolidationLambdaArn *string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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. Must be unique to your account.
	AppImageConfigName *string

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

	// The configuration for the file system and kernels in the SageMaker image.
	KernelGatewayImageConfig *KernelGatewayImageConfig

	// When the AppImageConfig was last modified.
	LastModifiedTime *time.Time
	// contains filtered or unexported fields
}

The configuration for running a 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"
	AppInstanceTypeMlM5dLarge     AppInstanceType = "ml.m5d.large"
	AppInstanceTypeMlM5dXlarge    AppInstanceType = "ml.m5d.xlarge"
	AppInstanceTypeMlM5d2xlarge   AppInstanceType = "ml.m5d.2xlarge"
	AppInstanceTypeMlM5d4xlarge   AppInstanceType = "ml.m5d.4xlarge"
	AppInstanceTypeMlM5d8xlarge   AppInstanceType = "ml.m5d.8xlarge"
	AppInstanceTypeMlM5d12xlarge  AppInstanceType = "ml.m5d.12xlarge"
	AppInstanceTypeMlM5d16xlarge  AppInstanceType = "ml.m5d.16xlarge"
	AppInstanceTypeMlM5d24xlarge  AppInstanceType = "ml.m5d.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"
	AppInstanceTypeMlP3dn24xlarge AppInstanceType = "ml.p3dn.24xlarge"
	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"
	AppInstanceTypeMlR5Large      AppInstanceType = "ml.r5.large"
	AppInstanceTypeMlR5Xlarge     AppInstanceType = "ml.r5.xlarge"
	AppInstanceTypeMlR52xlarge    AppInstanceType = "ml.r5.2xlarge"
	AppInstanceTypeMlR54xlarge    AppInstanceType = "ml.r5.4xlarge"
	AppInstanceTypeMlR58xlarge    AppInstanceType = "ml.r5.8xlarge"
	AppInstanceTypeMlR512xlarge   AppInstanceType = "ml.r5.12xlarge"
	AppInstanceTypeMlR516xlarge   AppInstanceType = "ml.r5.16xlarge"
	AppInstanceTypeMlR524xlarge   AppInstanceType = "ml.r5.24xlarge"
)

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 AppSecurityGroupManagement added in v1.18.0 

type AppSecurityGroupManagement string
const (
	AppSecurityGroupManagementService  AppSecurityGroupManagement = "Service"
	AppSecurityGroupManagementCustomer AppSecurityGroupManagement = "Customer"
)

Enum values for AppSecurityGroupManagement

func (AppSecurityGroupManagement) Values added in v1.18.0 

func (AppSecurityGroupManagement) Values() []AppSecurityGroupManagement

Values returns all known values for AppSecurityGroupManagement. 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
	// contains filtered or unexported fields
}

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"
	AppTypeRStudioServerPro AppType = "RStudioServerPro"
	AppTypeRSessionGateway  AppType = "RSessionGateway"
)

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 ArtifactSource added in v0.31.0 

type ArtifactSource struct {

	// The URI of the source.
	//
	// This member is required.
	SourceUri *string

	// A list of source types.
	SourceTypes []ArtifactSourceType
	// contains filtered or unexported fields
}

A structure describing the source of an artifact.

type ArtifactSourceIdType added in v0.31.0 

type ArtifactSourceIdType string
const (
	ArtifactSourceIdTypeMd5Hash   ArtifactSourceIdType = "MD5Hash"
	ArtifactSourceIdTypeS3Etag    ArtifactSourceIdType = "S3ETag"
	ArtifactSourceIdTypeS3Version ArtifactSourceIdType = "S3Version"
	ArtifactSourceIdTypeCustom    ArtifactSourceIdType = "Custom"
)

Enum values for ArtifactSourceIdType

func (ArtifactSourceIdType) Values added in v0.31.0 

func (ArtifactSourceIdType) Values() []ArtifactSourceIdType

Values returns all known values for ArtifactSourceIdType. 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 ArtifactSourceType added in v0.31.0 

type ArtifactSourceType struct {

	// The type of ID.
	//
	// This member is required.
	SourceIdType ArtifactSourceIdType

	// The ID.
	//
	// This member is required.
	Value *string
	// contains filtered or unexported fields
}

The ID and ID type of an artifact source.

type ArtifactSummary added in v0.31.0 

type ArtifactSummary struct {

	// The Amazon Resource Name (ARN) of the artifact.
	ArtifactArn *string

	// The name of the artifact.
	ArtifactName *string

	// The type of the artifact.
	ArtifactType *string

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

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

	// The source of the artifact.
	Source *ArtifactSource
	// contains filtered or unexported fields
}

Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.

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 AssociationEdgeType added in v0.31.0 

type AssociationEdgeType string
const (
	AssociationEdgeTypeContributedTo  AssociationEdgeType = "ContributedTo"
	AssociationEdgeTypeAssociatedWith AssociationEdgeType = "AssociatedWith"
	AssociationEdgeTypeDerivedFrom    AssociationEdgeType = "DerivedFrom"
	AssociationEdgeTypeProduced       AssociationEdgeType = "Produced"
)

Enum values for AssociationEdgeType

func (AssociationEdgeType) Values added in v0.31.0 

func (AssociationEdgeType) Values() []AssociationEdgeType

Values returns all known values for AssociationEdgeType. 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 AssociationSummary added in v0.31.0 

type AssociationSummary struct {

	// The type of the association.
	AssociationType AssociationEdgeType

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

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

	// The Amazon Resource Name (ARN) of the destination.
	DestinationArn *string

	// The name of the destination.
	DestinationName *string

	// The destination type.
	DestinationType *string

	// The ARN of the source.
	SourceArn *string

	// The name of the source.
	SourceName *string

	// The source type.
	SourceType *string
	// contains filtered or unexported fields
}

Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.

type AsyncInferenceClientConfig added in v1.12.0 

type AsyncInferenceClientConfig struct {

	// The maximum number of concurrent requests sent by the SageMaker client to the
	// model container. If no value is provided, Amazon SageMaker will choose an
	// optimal value for you.
	MaxConcurrentInvocationsPerInstance *int32
	// contains filtered or unexported fields
}

Configures the behavior of the client used by Amazon SageMaker to interact with the model container during asynchronous inference.

type AsyncInferenceConfig added in v1.12.0 

type AsyncInferenceConfig struct {

	// Specifies the configuration for asynchronous inference invocation outputs.
	//
	// This member is required.
	OutputConfig *AsyncInferenceOutputConfig

	// Configures the behavior of the client used by Amazon SageMaker to interact with
	// the model container during asynchronous inference.
	ClientConfig *AsyncInferenceClientConfig
	// contains filtered or unexported fields
}

Specifies configuration for how an endpoint performs asynchronous inference.

type AsyncInferenceNotificationConfig added in v1.12.0 

type AsyncInferenceNotificationConfig struct {

	// Amazon SNS topic to post a notification to when inference fails. If no topic is
	// provided, no notification is sent on failure.
	ErrorTopic *string

	// Amazon SNS topic to post a notification to when inference completes
	// successfully. If no topic is provided, no notification is sent on success.
	SuccessTopic *string
	// contains filtered or unexported fields
}

Specifies the configuration for notifications of inference results for asynchronous inference.

type AsyncInferenceOutputConfig added in v1.12.0 

type AsyncInferenceOutputConfig struct {

	// The Amazon S3 location to upload inference responses to.
	//
	// This member is required.
	S3OutputPath *string

	// The Amazon Web Services Key Management Service (Amazon Web Services KMS) key
	// that Amazon SageMaker uses to encrypt the asynchronous inference output in
	// Amazon S3.
	KmsKeyId *string

	// Specifies the configuration for notifications of inference results for
	// asynchronous inference.
	NotificationConfig *AsyncInferenceNotificationConfig
	// contains filtered or unexported fields
}

Specifies the configuration for asynchronous inference invocation outputs.

type AthenaDatasetDefinition added in v0.31.0 

type AthenaDatasetDefinition struct {

	// The name of the data catalog used in Athena query execution.
	//
	// This member is required.
	Catalog *string

	// The name of the database used in the Athena query execution.
	//
	// This member is required.
	Database *string

	// The data storage format for Athena query results.
	//
	// This member is required.
	OutputFormat AthenaResultFormat

	// The location in Amazon S3 where Athena query results are stored.
	//
	// This member is required.
	OutputS3Uri *string

	// The SQL query statements, to be executed.
	//
	// This member is required.
	QueryString *string

	// The Amazon Web Services Key Management Service (Amazon Web Services KMS) key
	// that Amazon SageMaker uses to encrypt data generated from an Athena query
	// execution.
	KmsKeyId *string

	// The compression used for Athena query results.
	OutputCompression AthenaResultCompressionType

	// The name of the workgroup in which the Athena query is being started.
	WorkGroup *string
	// contains filtered or unexported fields
}

Configuration for Athena Dataset Definition input.

type AthenaResultCompressionType added in v0.31.0 

type AthenaResultCompressionType string
const (
	AthenaResultCompressionTypeGzip   AthenaResultCompressionType = "GZIP"
	AthenaResultCompressionTypeSnappy AthenaResultCompressionType = "SNAPPY"
	AthenaResultCompressionTypeZlib   AthenaResultCompressionType = "ZLIB"
)

Enum values for AthenaResultCompressionType

func (AthenaResultCompressionType) Values added in v0.31.0 

func (AthenaResultCompressionType) Values() []AthenaResultCompressionType

Values returns all known values for AthenaResultCompressionType. 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 AthenaResultFormat added in v0.31.0 

type AthenaResultFormat string
const (
	AthenaResultFormatParquet  AthenaResultFormat = "PARQUET"
	AthenaResultFormatOrc      AthenaResultFormat = "ORC"
	AthenaResultFormatAvro     AthenaResultFormat = "AVRO"
	AthenaResultFormatJson     AthenaResultFormat = "JSON"
	AthenaResultFormatTextfile AthenaResultFormat = "TEXTFILE"
)

Enum values for AthenaResultFormat

func (AthenaResultFormat) Values added in v0.31.0 

func (AthenaResultFormat) Values() []AthenaResultFormat

Values returns all known values for AthenaResultFormat. 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 name of the candidate.
	//
	// This member is required.
	CandidateName *string

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

	// Information about 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's status.
	//
	// This member is required.
	ObjectiveStatus ObjectiveStatus

	// The properties of an AutoML candidate job.
	CandidateProperties *CandidateProperties

	// The end time.
	EndTime *time.Time

	// The failure reason.
	FailureReason *string

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

	// Information about the inference container definitions.
	InferenceContainers []AutoMLContainerDefinition
	// contains filtered or unexported fields
}

Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.

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
	// contains filtered or unexported fields
}

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

type AutoMLChannel 

type AutoMLChannel struct {

	// The data source for an AutoML channel.
	//
	// This member is required.
	DataSource *AutoMLDataSource

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

	// You can use Gzip or None. The default value is None.
	CompressionType CompressionType
	// contains filtered or unexported fields
}

A channel is a named input source that training algorithms can consume. For more information, see .

type AutoMLContainerDefinition 

type AutoMLContainerDefinition struct {

	// The Amazon Elastic Container Registry (Amazon ECR) path of the container. For
	// more information, see .
	//
	// This member is required.
	Image *string

	// The location of the model artifacts. For more information, see .
	//
	// This member is required.
	ModelDataUrl *string

	// The environment variables to set in the container. For more information, see .
	Environment map[string]string
	// contains filtered or unexported fields
}

A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see .

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
	// contains filtered or unexported fields
}

The data source for the Autopilot job.

type AutoMLJobArtifacts 

type AutoMLJobArtifacts struct {

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

	// The URL of the notebook location.
	DataExplorationNotebookLocation *string
	// contains filtered or unexported fields
}

The artifacts that are generated during an AutoML job.

type AutoMLJobCompletionCriteria 

type AutoMLJobCompletionCriteria struct {

	// The maximum runtime, in seconds, an AutoML job has to complete. If an AutoML job
	// exceeds the maximum runtime, the job is stopped automatically and its processing
	// is ended gracefully. The AutoML job identifies the best model whose training was
	// completed and marks it as the best-performing model. Any unfinished steps of the
	// job, such as automatic one-click Autopilot model deployment, will not be
	// completed.
	MaxAutoMLJobRuntimeInSeconds *int32

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

	// The maximum time, in seconds, that each training job is allowed to run as part
	// of a hyperparameter tuning job. For more information, see the used by the
	// action.
	MaxRuntimePerTrainingJobInSeconds *int32
	// contains filtered or unexported fields
}

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

	// The security configuration for traffic encryption or Amazon VPC settings.
	SecurityConfig *AutoMLSecurityConfig
	// contains filtered or unexported fields
}

A collection of settings used for an AutoML 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 is. When the data contains outliers, they tend to dominate
	// the MSE, which might cause subpar prediction performance.
	//
	// * Accuracy: The ratio
	// of the number of correctly classified items to the total number of (correctly
	// and incorrectly) classified items. It is used for binary and multiclass
	// classification. It measures how close the predicted class values are to the
	// actual values. Accuracy values vary between zero and one: one indicates perfect
	// accuracy and zero indicates 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 and 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 indicates 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: a
	// score of one indicates perfect accuracy and a score of one half indicates that
	// the prediction is not better than a random classifier. Values under one half
	// predict less accurately than a random predictor. But such consistently bad
	// predictors can simply 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, use 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 indicates 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
	// contains filtered or unexported fields
}

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"
	AutoMLJobSecondaryStatusGeneratingExplainabilityReport AutoMLJobSecondaryStatus = "GeneratingExplainabilityReport"
	AutoMLJobSecondaryStatusCompleted                      AutoMLJobSecondaryStatus = "Completed"
	AutoMLJobSecondaryStatusExplainabilityError            AutoMLJobSecondaryStatus = "ExplainabilityError"
	AutoMLJobSecondaryStatusDeployingModel                 AutoMLJobSecondaryStatus = "DeployingModel"
	AutoMLJobSecondaryStatusModelDeploymentError           AutoMLJobSecondaryStatus = "ModelDeploymentError"
)

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 AutoML job.
	//
	// This member is required.
	AutoMLJobArn *string

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

	// The secondary status of the AutoML job.
	//
	// This member is required.
	AutoMLJobSecondaryStatus AutoMLJobSecondaryStatus

	// The status of the AutoML job.
	//
	// This member is required.
	AutoMLJobStatus AutoMLJobStatus

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

	// When the AutoML 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 an AutoML job.
	FailureReason *string

	// The list of reasons for partial failures within an AutoML job.
	PartialFailureReasons []AutoMLPartialFailureReason
	// contains filtered or unexported fields
}

Provides a summary about an AutoML 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 Amazon Web Services KMS encryption key ID.
	KmsKeyId *string
	// contains filtered or unexported fields
}

The output data configuration.

type AutoMLPartialFailureReason added in v1.3.0 

type AutoMLPartialFailureReason struct {

	// The message containing the reason for a partial failure of an AutoML job.
	PartialFailureMessage *string
	// contains filtered or unexported fields
}

The reason for a partial failure of an AutoML job.

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
	// contains filtered or unexported fields
}

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

	// The VPC configuration.
	VpcConfig *VpcConfig
	// contains filtered or unexported fields
}

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 AutoRollbackConfig added in v0.31.0 

type AutoRollbackConfig struct {

	// List of CloudWatch alarms in your account that are configured to monitor metrics
	// on an endpoint. If any alarms are tripped during a deployment, SageMaker rolls
	// back the deployment.
	Alarms []Alarm
	// contains filtered or unexported fields
}

Automatic rollback configuration for handling endpoint deployment failures and recovery.

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 BatchDescribeModelPackageError added in v1.18.0 

type BatchDescribeModelPackageError struct {

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

	//
	//
	// This member is required.
	ErrorResponse *string
	// contains filtered or unexported fields
}

The error code and error description associated with the resource.

type BatchDescribeModelPackageSummary added in v1.18.0 

type BatchDescribeModelPackageSummary struct {

	// The creation time of the mortgage package summary.
	//
	// This member is required.
	CreationTime *time.Time

	// Defines how to perform inference generation after a training job is run.
	//
	// This member is required.
	InferenceSpecification *InferenceSpecification

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

	// The group name for the model package
	//
	// This member is required.
	ModelPackageGroupName *string

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

	// The approval status of the model.
	ModelApprovalStatus ModelApprovalStatus

	// The description of the model package.
	ModelPackageDescription *string

	// The version number of a versioned model.
	ModelPackageVersion *int32
	// contains filtered or unexported fields
}

Provides summary information about the model package.

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 Bias added in v0.31.0 

type Bias struct {

	// The bias report for a model
	Report *MetricsSource
	// contains filtered or unexported fields
}

Contains bias metrics for a model.

type BlueGreenUpdatePolicy added in v0.31.0 

type BlueGreenUpdatePolicy struct {

	// Defines the traffic routing strategy to shift traffic from the old fleet to the
	// new fleet during an endpoint deployment.
	//
	// This member is required.
	TrafficRoutingConfiguration *TrafficRoutingConfig

	// Maximum execution timeout for the deployment. Note that the timeout value should
	// be larger than the total waiting time specified in TerminationWaitInSeconds and
	// WaitIntervalInSeconds.
	MaximumExecutionTimeoutInSeconds *int32

	// Additional waiting time in seconds after the completion of an endpoint
	// deployment before terminating the old endpoint fleet. Default is 0.
	TerminationWaitInSeconds *int32
	// contains filtered or unexported fields
}

Update policy for a blue/green deployment. If this update policy is specified, SageMaker creates a new fleet during the deployment while maintaining the old fleet. SageMaker flips traffic to the new fleet according to the specified traffic routing configuration. Only one update policy should be used in the deployment configuration. If no update policy is specified, SageMaker uses a blue/green deployment strategy with all at once traffic shifting by default.

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 CacheHitResult added in v0.31.0 

type CacheHitResult struct {

	// The Amazon Resource Name (ARN) of the pipeline execution.
	SourcePipelineExecutionArn *string
	// contains filtered or unexported fields
}

Details on the cache hit of a pipeline execution step.

type CallbackStepMetadata added in v1.7.0 

type CallbackStepMetadata struct {

	// The pipeline generated token from the Amazon SQS queue.
	CallbackToken *string

	// A list of the output parameters of the callback step.
	OutputParameters []OutputParameter

	// The URL of the Amazon Simple Queue Service (Amazon SQS) queue used by the
	// callback step.
	SqsQueueUrl *string
	// contains filtered or unexported fields
}

Metadata about a callback step.

type CandidateArtifactLocations added in v1.3.0 

type CandidateArtifactLocations struct {

	// The Amazon S3 prefix to the explainability artifacts generated for the AutoML
	// candidate.
	//
	// This member is required.
	Explainability *string
	// contains filtered or unexported fields
}

The location of artifacts for an AutoML candidate job.

type CandidateProperties added in v1.3.0 

type CandidateProperties struct {

	// The Amazon S3 prefix to the artifacts generated for an AutoML candidate.
	CandidateArtifactLocations *CandidateArtifactLocations

	// Information about the candidate metrics for an AutoML job.
	CandidateMetrics []MetricDatum
	// contains filtered or unexported fields
}

The properties of an AutoML candidate job.

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 CapacitySize added in v0.31.0 

type CapacitySize struct {

	// Specifies the endpoint capacity type.
	//
	// * INSTANCE_COUNT: The endpoint activates
	// based on the number of instances.
	//
	// * CAPACITY_PERCENT: The endpoint activates
	// based on the specified percentage of capacity.
	//
	// This member is required.
	Type CapacitySizeType

	// Defines the capacity size, either as a number of instances or a capacity
	// percentage.
	//
	// This member is required.
	Value *int32
	// contains filtered or unexported fields
}

Specifies the endpoint capacity to activate for production.

type CapacitySizeType added in v0.31.0 

type CapacitySizeType string
const (
	CapacitySizeTypeInstanceCount   CapacitySizeType = "INSTANCE_COUNT"
	CapacitySizeTypeCapacityPercent CapacitySizeType = "CAPACITY_PERCENT"
)

Enum values for CapacitySizeType

func (CapacitySizeType) Values added in v0.31.0 

func (CapacitySizeType) Values() []CapacitySizeType

Values returns all known values for CapacitySizeType. 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

A list of categorical hyperparameters to tune.

type CategoricalParameterRangeSpecification 

type CategoricalParameterRangeSpecification struct {

	// The allowed categories for the hyperparameter.
	//
	// This member is required.
	Values []string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 filtered or unexported fields
}

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 Amazon Web Services Secrets Manager secret that
	// contains the credentials used to access the repository.
	GitConfig *GitConfig
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Configuration information for the Debugger output 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
	// contains filtered or unexported fields
}

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 ConditionOutcome added in v0.31.0 

type ConditionOutcome string
const (
	ConditionOutcomeTrue  ConditionOutcome = "True"
	ConditionOutcomeFalse ConditionOutcome = "False"
)

Enum values for ConditionOutcome

func (ConditionOutcome) Values added in v0.31.0 

func (ConditionOutcome) Values() []ConditionOutcome

Values returns all known values for ConditionOutcome. 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 ConditionStepMetadata added in v0.31.0 

type ConditionStepMetadata struct {

	// The outcome of the Condition step evaluation.
	Outcome ConditionOutcome
	// contains filtered or unexported fields
}

Metadata for a Condition step.

type ConflictException 

type ConflictException struct {
	Message *string
	// contains filtered or unexported fields
}

There was a conflict when you attempted to modify a SageMaker entity such as an Experiment or Artifact.

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 Amazon Web Services Security Token Service to download
	// model artifacts from the S3 path you provide. Amazon Web Services STS is
	// activated in your IAM user account by default. If you previously deactivated
	// Amazon Web Services STS for a region, you need to reactivate Amazon Web Services
	// STS for that region. For more information, see Activating and Deactivating
	// Amazon Web Services STS in an Amazon Web Services Region
	// (https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html)
	// in the Amazon Web Services 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

	// Specifies additional configuration for multi-model endpoints.
	MultiModelConfig *MultiModelConfig
	// contains filtered or unexported fields
}

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 ContextSource added in v0.31.0 

type ContextSource struct {

	// The URI of the source.
	//
	// This member is required.
	SourceUri *string

	// The ID of the source.
	SourceId *string

	// The type of the source.
	SourceType *string
	// contains filtered or unexported fields
}

A structure describing the source of a context.

type ContextSummary added in v0.31.0 

type ContextSummary struct {

	// The Amazon Resource Name (ARN) of the context.
	ContextArn *string

	// The name of the context.
	ContextName *string

	// The type of the context.
	ContextType *string

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

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

	// The source of the context.
	Source *ContextSource
	// contains filtered or unexported fields
}

Lists a summary of the properties of a context. A context provides a logical grouping of other entities.

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

A custom SageMaker image. For more information, see Bring your own SageMaker image (https://docs.aws.amazon.com/sagemaker/latest/dg/studio-byoi.html).

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

type DataCatalogConfig added in v0.31.0 

type DataCatalogConfig struct {

	// The name of the Glue table catalog.
	//
	// This member is required.
	Catalog *string

	// The name of the Glue table database.
	//
	// This member is required.
	Database *string

	// The name of the Glue table.
	//
	// This member is required.
	TableName *string
	// contains filtered or unexported fields
}

The meta data of the Glue table which serves as data catalog for the OfflineStore.

type DataDistributionType added in v0.31.0 

type DataDistributionType string
const (
	DataDistributionTypeFullyreplicated DataDistributionType = "FullyReplicated"
	DataDistributionTypeShardedbys3key  DataDistributionType = "ShardedByS3Key"
)

Enum values for DataDistributionType

func (DataDistributionType) Values added in v0.31.0 

func (DataDistributionType) Values() []DataDistributionType

Values returns all known values for DataDistributionType. 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 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.
	// You can specify OutputFilter as an additional filter to select a portion of the
	// joined dataset and store it in the output file. For JSON or JSONLines objects,
	// such as a JSON array, 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,
	// 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 data, SageMaker takes each row as a JSON array and
	// joins the transformed data with the input by appending each transformed row to
	// the end of the input. The joined data has the original input data followed by
	// the transformed data and the output is a CSV file. For information on how
	// joining in applied, see Workflow for Associating Inferences with Input Records
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow).
	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
	// contains filtered or unexported fields
}

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 DataQualityAppSpecification added in v0.31.0 

type DataQualityAppSpecification struct {

	// The container image that the data quality monitoring job runs.
	//
	// This member is required.
	ImageUri *string

	// The arguments to send to the container that the monitoring job runs.
	ContainerArguments []string

	// The entrypoint for a container used to run a monitoring job.
	ContainerEntrypoint []string

	// Sets the environment variables in the container that the monitoring job runs.
	Environment map[string]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
	// contains filtered or unexported fields
}

Information about the container that a data quality monitoring job runs.

type DataQualityBaselineConfig added in v0.31.0 

type DataQualityBaselineConfig struct {

	// The name of the job that performs baselining for the data quality monitoring
	// job.
	BaseliningJobName *string

	// The constraints resource for a monitoring job.
	ConstraintsResource *MonitoringConstraintsResource

	// The statistics resource for a monitoring job.
	StatisticsResource *MonitoringStatisticsResource
	// contains filtered or unexported fields
}

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 DataQualityJobInput added in v0.31.0 

type DataQualityJobInput struct {

	// Input object for the endpoint
	//
	// This member is required.
	EndpointInput *EndpointInput
	// contains filtered or unexported fields
}

The input for the data quality monitoring job. Currently endpoints are supported for input.

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
	// contains filtered or unexported fields
}

Describes the location of the channel data.

type DatasetDefinition added in v0.31.0 

type DatasetDefinition struct {

	// Configuration for Athena Dataset Definition input.
	AthenaDatasetDefinition *AthenaDatasetDefinition

	// Whether the generated dataset is FullyReplicated or ShardedByS3Key (default).
	DataDistributionType DataDistributionType

	// Whether to use File or Pipe input mode. In File (default) 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.
	InputMode InputMode

	// The local path where you want Amazon SageMaker to download the Dataset
	// Definition inputs to run a processing job. LocalPath is an absolute path to the
	// input data. This is a required parameter when AppManaged is False (default).
	LocalPath *string

	// Configuration for Redshift Dataset Definition input.
	RedshiftDatasetDefinition *RedshiftDatasetDefinition
	// contains filtered or unexported fields
}

Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.

type DebugHookConfig 

type DebugHookConfig struct {

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

	// Configuration information for Debugger tensor collections. To learn more about
	// how to configure the CollectionConfiguration parameter, see Use the SageMaker
	// and Debugger Configuration API Operations to Create, Update, and Debug Your
	// Training Job
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html).
	CollectionConfigurations []CollectionConfiguration

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

	// Path to local storage location for metrics and tensors. Defaults to
	// /opt/ml/output/tensors/.
	LocalPath *string
	// contains filtered or unexported fields
}

Configuration information for the Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job (https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html).

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 a Debugger custom rule for debugging 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
	// contains filtered or unexported fields
}

Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job (https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html).

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 DeploymentConfig added in v0.31.0 

type DeploymentConfig struct {

	// Update policy for a blue/green deployment. If this update policy is specified,
	// SageMaker creates a new fleet during the deployment while maintaining the old
	// fleet. SageMaker flips traffic to the new fleet according to the specified
	// traffic routing configuration. Only one update policy should be used in the
	// deployment configuration. If no update policy is specified, SageMaker uses a
	// blue/green deployment strategy with all at once traffic shifting by default.
	//
	// This member is required.
	BlueGreenUpdatePolicy *BlueGreenUpdatePolicy

	// Automatic rollback configuration for handling endpoint deployment failures and
	// recovery.
	AutoRollbackConfiguration *AutoRollbackConfig
	// contains filtered or unexported fields
}

The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.

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
	// contains filtered or unexported fields
}

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 Device added in v0.31.0 

type Device struct {

	// The name of the device.
	//
	// This member is required.
	DeviceName *string

	// Description of the device.
	Description *string

	// Amazon Web Services Internet of Things (IoT) object name.
	IotThingName *string
	// contains filtered or unexported fields
}

Information of a particular device.

type DeviceFleetSummary added in v0.31.0 

type DeviceFleetSummary struct {

	// Amazon Resource Name (ARN) of the device fleet.
	//
	// This member is required.
	DeviceFleetArn *string

	// Name of the device fleet.
	//
	// This member is required.
	DeviceFleetName *string

	// Timestamp of when the device fleet was created.
	CreationTime *time.Time

	// Timestamp of when the device fleet was last updated.
	LastModifiedTime *time.Time
	// contains filtered or unexported fields
}

Summary of the device fleet.

type DeviceStats added in v0.31.0 

type DeviceStats struct {

	// The number of devices connected with a heartbeat.
	//
	// This member is required.
	ConnectedDeviceCount int64

	// The number of registered devices.
	//
	// This member is required.
	RegisteredDeviceCount int64
	// contains filtered or unexported fields
}

Status of devices.

type DeviceSummary added in v0.31.0 

type DeviceSummary struct {

	// Amazon Resource Name (ARN) of the device.
	//
	// This member is required.
	DeviceArn *string

	// The unique identifier of the device.
	//
	// This member is required.
	DeviceName *string

	// Edge Manager agent version.
	AgentVersion *string

	// A description of the device.
	Description *string

	// The name of the fleet the device belongs to.
	DeviceFleetName *string

	// The Amazon Web Services Internet of Things (IoT) object thing name associated
	// with the device..
	IotThingName *string

	// The last heartbeat received from the device.
	LatestHeartbeat *time.Time

	// Models on the device.
	Models []EdgeModelSummary

	// The timestamp of the last registration or de-reregistration.
	RegistrationTime *time.Time
	// contains filtered or unexported fields
}

Summary of the device.

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
	// contains filtered or unexported fields
}

The domain's details.

type DomainSettings added in v1.18.0 

type DomainSettings struct {

	// A collection of settings that configure the RStudioServerPro Domain-level app.
	RStudioServerProDomainSettings *RStudioServerProDomainSettings

	// The security groups for the Amazon Virtual Private Cloud that the Domain uses
	// for communication between Domain-level apps and user apps.
	SecurityGroupIds []string
	// contains filtered or unexported fields
}

A collection of settings that apply to the SageMaker Domain. These settings are specified through the CreateDomain API call.

type DomainSettingsForUpdate added in v1.18.0 

type DomainSettingsForUpdate struct {

	// A collection of RStudioServerPro Domain-level app settings to update.
	RStudioServerProDomainSettingsForUpdate *RStudioServerProDomainSettingsForUpdate
	// contains filtered or unexported fields
}

A collection of Domain configuration settings to update.

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 EdgeModel added in v0.31.0 

type EdgeModel struct {

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

	// The model version.
	//
	// This member is required.
	ModelVersion *string

	// The timestamp of the last inference that was made.
	LatestInference *time.Time

	// The timestamp of the last data sample taken.
	LatestSampleTime *time.Time
	// contains filtered or unexported fields
}

The model on the edge device.

type EdgeModelStat added in v0.31.0 

type EdgeModelStat struct {

	// The number of devices that have this model version, a heart beat, and are
	// currently running.
	//
	// This member is required.
	ActiveDeviceCount int64

	// The number of devices that have this model version and have a heart beat.
	//
	// This member is required.
	ConnectedDeviceCount int64

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

	// The model version.
	//
	// This member is required.
	ModelVersion *string

	// The number of devices that have this model version and do not have a heart beat.
	//
	// This member is required.
	OfflineDeviceCount int64

	// The number of devices with this model version and are producing sample data.
	//
	// This member is required.
	SamplingDeviceCount int64
	// contains filtered or unexported fields
}

Status of edge devices with this model.

type EdgeModelSummary added in v0.31.0 

type EdgeModelSummary struct {

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

	// The version model.
	//
	// This member is required.
	ModelVersion *string
	// contains filtered or unexported fields
}

Summary of model on edge device.

type EdgeOutputConfig added in v0.31.0 

type EdgeOutputConfig struct {

	// The Amazon Simple Storage (S3) bucker URI.
	//
	// This member is required.
	S3OutputLocation *string

	// The Amazon Web Services Key Management Service (Amazon Web Services KMS) key
	// that Amazon SageMaker uses to encrypt data on the storage volume after
	// compilation job. If you don't provide a KMS key ID, Amazon SageMaker uses the
	// default KMS key for Amazon S3 for your role's account.
	KmsKeyId *string

	// The configuration used to create deployment artifacts. Specify configuration
	// options with a JSON string. The available configuration options for each type
	// are:
	//
	// * ComponentName (optional) - Name of the GreenGrass V2 component. If not
	// specified, the default name generated consists of "SagemakerEdgeManager" and the
	// name of your SageMaker Edge Manager packaging job.
	//
	// * ComponentDescription
	// (optional) - Description of the component.
	//
	// * ComponentVersion (optional) - The
	// version of the component. Amazon Web Services IoT Greengrass uses semantic
	// versions for components. Semantic versions follow a major.minor.patch number
	// system. For example, version 1.0.0 represents the first major release for a
	// component. For more information, see the semantic version specification
	// (https://semver.org/).
	//
	// * PlatformOS (optional) - The name of the operating
	// system for the platform. Supported platforms include Windows and Linux.
	//
	// *
	// PlatformArchitecture (optional) - The processor architecture for the platform.
	// Supported architectures Windows include: Windows32_x86, Windows64_x64. Supported
	// architectures for Linux include: Linux x86_64, Linux ARMV8.
	PresetDeploymentConfig *string

	// The deployment type SageMaker Edge Manager will create. Currently only supports
	// Amazon Web Services IoT Greengrass Version 2 components.
	PresetDeploymentType EdgePresetDeploymentType
	// contains filtered or unexported fields
}

The output configuration.

type EdgePackagingJobStatus added in v0.31.0 

type EdgePackagingJobStatus string
const (
	EdgePackagingJobStatusStarting   EdgePackagingJobStatus = "STARTING"
	EdgePackagingJobStatusInProgress EdgePackagingJobStatus = "INPROGRESS"
	EdgePackagingJobStatusCompleted  EdgePackagingJobStatus = "COMPLETED"
	EdgePackagingJobStatusFailed     EdgePackagingJobStatus = "FAILED"
	EdgePackagingJobStatusStopping   EdgePackagingJobStatus = "STOPPING"
	EdgePackagingJobStatusStopped    EdgePackagingJobStatus = "STOPPED"
)

Enum values for EdgePackagingJobStatus

func (EdgePackagingJobStatus) Values added in v0.31.0 

func (EdgePackagingJobStatus) Values() []EdgePackagingJobStatus

Values returns all known values for EdgePackagingJobStatus. 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 EdgePackagingJobSummary added in v0.31.0 

type EdgePackagingJobSummary struct {

	// The Amazon Resource Name (ARN) of the edge packaging job.
	//
	// This member is required.
	EdgePackagingJobArn *string

	// The name of the edge packaging job.
	//
	// This member is required.
	EdgePackagingJobName *string

	// The status of the edge packaging job.
	//
	// This member is required.
	EdgePackagingJobStatus EdgePackagingJobStatus

	// The name of the SageMaker Neo compilation job.
	CompilationJobName *string

	// The timestamp of when the job was created.
	CreationTime *time.Time

	// The timestamp of when the edge packaging job was last updated.
	LastModifiedTime *time.Time

	// The name of the model.
	ModelName *string

	// The version of the model.
	ModelVersion *string
	// contains filtered or unexported fields
}

Summary of edge packaging job.

type EdgePresetDeploymentOutput added in v1.8.0 

type EdgePresetDeploymentOutput struct {

	// The deployment type created by SageMaker Edge Manager. Currently only supports
	// Amazon Web Services IoT Greengrass Version 2 components.
	//
	// This member is required.
	Type EdgePresetDeploymentType

	// The Amazon Resource Name (ARN) of the generated deployable resource.
	Artifact *string

	// The status of the deployable resource.
	Status EdgePresetDeploymentStatus

	// Returns a message describing the status of the deployed resource.
	StatusMessage *string
	// contains filtered or unexported fields
}

The output of a SageMaker Edge Manager deployable resource.

type EdgePresetDeploymentStatus added in v1.8.0 

type EdgePresetDeploymentStatus string
const (
	EdgePresetDeploymentStatusCompleted EdgePresetDeploymentStatus = "COMPLETED"
	EdgePresetDeploymentStatusFailed    EdgePresetDeploymentStatus = "FAILED"
)

Enum values for EdgePresetDeploymentStatus

func (EdgePresetDeploymentStatus) Values added in v1.8.0 

func (EdgePresetDeploymentStatus) Values() []EdgePresetDeploymentStatus

Values returns all known values for EdgePresetDeploymentStatus. 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 EdgePresetDeploymentType added in v1.8.0 

type EdgePresetDeploymentType string
const (
	EdgePresetDeploymentTypeGreengrassV2Component EdgePresetDeploymentType = "GreengrassV2Component"
)

Enum values for EdgePresetDeploymentType

func (EdgePresetDeploymentType) Values added in v1.8.0 

func (EdgePresetDeploymentType) Values() []EdgePresetDeploymentType

Values returns all known values for EdgePresetDeploymentType. 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 Endpoint added in v0.31.0 

type Endpoint struct {

	// The time that 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 endpoint configuration associated with the endpoint.
	//
	// This member is required.
	EndpointConfigName *string

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

	// The status of the endpoint.
	//
	// This member is required.
	EndpointStatus EndpointStatus

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

	//
	DataCaptureConfig *DataCaptureConfigSummary

	// If the endpoint failed, the reason it failed.
	FailureReason *string

	// A list of monitoring schedules for the endpoint. For information about model
	// monitoring, see Amazon SageMaker Model Monitor
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.html).
	MonitoringSchedules []MonitoringSchedule

	// A list of the production variants hosted on the endpoint. Each production
	// variant is a model.
	ProductionVariants []ProductionVariantSummary

	// A list of the tags associated with the endpoint. For more information, see
	// Tagging Amazon Web Services resources
	// (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html) in the Amazon
	// Web Services General Reference Guide.
	Tags []Tag
	// contains filtered or unexported fields
}

A hosted endpoint for real-time inference.

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
	// contains filtered or unexported fields
}

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

	// If specified, monitoring jobs substract this time from the end time. For
	// information about using offsets for scheduling monitoring jobs, see Schedule
	// Model Quality Monitoring Jobs
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html).
	EndTimeOffset *string

	// The attributes of the input data that are the input features.
	FeaturesAttribute *string

	// The attribute of the input data that represents the ground truth label.
	InferenceAttribute *string

	// In a classification problem, the attribute that represents the class
	// probability.
	ProbabilityAttribute *string

	// The threshold for the class probability to be evaluated as a positive result.
	ProbabilityThresholdAttribute *float64

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

	// Whether the Pipe or File is used as the input mode for transferring 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

	// If specified, monitoring jobs substract this time from the start time. For
	// information about using offsets for scheduling monitoring jobs, see Schedule
	// Model Quality Monitoring Jobs
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html).
	StartTimeOffset *string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 {

	// Who created the experiment.
	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, trial
	// component, or project.
	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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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

type Explainability added in v0.31.0 

type Explainability struct {

	// The explainability report for a model.
	Report *MetricsSource
	// contains filtered or unexported fields
}

Contains explainability metrics for a model.

type FeatureDefinition added in v0.31.0 

type FeatureDefinition struct {

	// The name of a feature. The type must be a string. FeatureName cannot be any of
	// the following: is_deleted, write_time, api_invocation_time.
	FeatureName *string

	// The value type of a feature. Valid values are Integral, Fractional, or String.
	FeatureType FeatureType
	// contains filtered or unexported fields
}

A list of features. You must include FeatureName and FeatureType. Valid feature FeatureTypes are Integral, Fractional and String.

type FeatureGroup added in v0.31.0 

type FeatureGroup struct {

	// The time a FeatureGroup was created.
	CreationTime *time.Time

	// A free form description of a FeatureGroup.
	Description *string

	// The name of the feature that stores the EventTime of a Record in a FeatureGroup.
	// A EventTime is point in time when a new event occurs that corresponds to the
	// creation or update of a Record in FeatureGroup. All Records in the FeatureGroup
	// must have a corresponding EventTime.
	EventTimeFeatureName *string

	// The reason that the FeatureGroup failed to be replicated in the OfflineStore.
	// This is failure may be due to a failure to create a FeatureGroup in or delete a
	// FeatureGroup from the OfflineStore.
	FailureReason *string

	// A list of Features. Each Feature must include a FeatureName and a FeatureType.
	// Valid FeatureTypes are Integral, Fractional and String. FeatureNames cannot be
	// any of the following: is_deleted, write_time, api_invocation_time. You can
	// create up to 2,500 FeatureDefinitions per FeatureGroup.
	FeatureDefinitions []FeatureDefinition

	// The Amazon Resource Name (ARN) of a FeatureGroup.
	FeatureGroupArn *string

	// The name of the FeatureGroup.
	FeatureGroupName *string

	// A FeatureGroup status.
	FeatureGroupStatus FeatureGroupStatus

	// The configuration of an OfflineStore. Provide an OfflineStoreConfig in a request
	// to CreateFeatureGroup to create an OfflineStore. To encrypt an OfflineStore
	// using at rest data encryption, specify Amazon Web Services Key Management
	// Service (KMS) key ID, or KMSKeyId, in S3StorageConfig.
	OfflineStoreConfig *OfflineStoreConfig

	// The status of OfflineStore.
	OfflineStoreStatus *OfflineStoreStatus

	// Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID,
	// or KMSKeyId, for at rest data encryption. You can turn OnlineStore on or off by
	// specifying the EnableOnlineStore flag at General Assembly; the default value is
	// False.
	OnlineStoreConfig *OnlineStoreConfig

	// The name of the Feature whose value uniquely identifies a Record defined in the
	// FeatureGroupFeatureDefinitions.
	RecordIdentifierFeatureName *string

	// The Amazon Resource Name (ARN) of the IAM execution role used to create the
	// feature group.
	RoleArn *string

	// Tags used to define a FeatureGroup.
	Tags []Tag
	// contains filtered or unexported fields
}

Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.

type FeatureGroupSortBy added in v0.31.0 

type FeatureGroupSortBy string
const (
	FeatureGroupSortByName               FeatureGroupSortBy = "Name"
	FeatureGroupSortByFeatureGroupStatus FeatureGroupSortBy = "FeatureGroupStatus"
	FeatureGroupSortByOfflineStoreStatus FeatureGroupSortBy = "OfflineStoreStatus"
	FeatureGroupSortByCreationTime       FeatureGroupSortBy = "CreationTime"
)

Enum values for FeatureGroupSortBy

func (FeatureGroupSortBy) Values added in v0.31.0 

func (FeatureGroupSortBy) Values() []FeatureGroupSortBy

Values returns all known values for FeatureGroupSortBy. 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 FeatureGroupSortOrder added in v0.31.0 

type FeatureGroupSortOrder string
const (
	FeatureGroupSortOrderAscending  FeatureGroupSortOrder = "Ascending"
	FeatureGroupSortOrderDescending FeatureGroupSortOrder = "Descending"
)

Enum values for FeatureGroupSortOrder

func (FeatureGroupSortOrder) Values added in v0.31.0 

func (FeatureGroupSortOrder) Values() []FeatureGroupSortOrder

Values returns all known values for FeatureGroupSortOrder. 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 FeatureGroupStatus added in v0.31.0 

type FeatureGroupStatus string
const (
	FeatureGroupStatusCreating     FeatureGroupStatus = "Creating"
	FeatureGroupStatusCreated      FeatureGroupStatus = "Created"
	FeatureGroupStatusCreateFailed FeatureGroupStatus = "CreateFailed"
	FeatureGroupStatusDeleting     FeatureGroupStatus = "Deleting"
	FeatureGroupStatusDeleteFailed FeatureGroupStatus = "DeleteFailed"
)

Enum values for FeatureGroupStatus

func (FeatureGroupStatus) Values added in v0.31.0 

func (FeatureGroupStatus) Values() []FeatureGroupStatus

Values returns all known values for FeatureGroupStatus. 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 FeatureGroupSummary added in v0.31.0 

type FeatureGroupSummary struct {

	// A timestamp indicating the time of creation time of the FeatureGroup.
	//
	// This member is required.
	CreationTime *time.Time

	// Unique identifier for the FeatureGroup.
	//
	// This member is required.
	FeatureGroupArn *string

	// The name of FeatureGroup.
	//
	// This member is required.
	FeatureGroupName *string

	// The status of a FeatureGroup. The status can be any of the following: Creating,
	// Created, CreateFail, Deleting or DetailFail.
	FeatureGroupStatus FeatureGroupStatus

	// Notifies you if replicating data into the OfflineStore has failed. Returns
	// either: Active or Blocked.
	OfflineStoreStatus *OfflineStoreStatus
	// contains filtered or unexported fields
}

The name, Arn, CreationTime, FeatureGroup values, LastUpdatedTime and EnableOnlineStorage status of a FeatureGroup.

type FeatureType added in v0.31.0 

type FeatureType string
const (
	FeatureTypeIntegral   FeatureType = "Integral"
	FeatureTypeFractional FeatureType = "Fractional"
	FeatureTypeString     FeatureType = "String"
)

Enum values for FeatureType

func (FeatureType) Values added in v0.31.0 

func (FeatureType) Values() []FeatureType

Values returns all known values for FeatureType. 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 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 (GID). If not specified, defaults to 100.
	DefaultGid int32

	// The default POSIX user ID (UID). 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
	// contains filtered or unexported fields
}

The Amazon Elastic File System (EFS) storage configuration for a SageMaker 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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. To learn more about the format of Amazon A2I output data, see Amazon
	// A2I Output Data
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-output-data.html).
	//
	// This member is required.
	S3OutputPath *string

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

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 filtered or unexported fields
}

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"
	FrameworkSklearn    Framework = "SKLEARN"
)

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 Amazon Web Services 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
	// contains filtered or unexported fields
}

Specifies configuration details for a Git repository in your Amazon Web Services account.

type GitConfigForUpdate 

type GitConfigForUpdate struct {

	// The Amazon Resource Name (ARN) of the Amazon Web Services 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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. You can use
	// standard HTML and Crowd HTML Elements to create a custom worker task template.
	// You use this template to create a human task UI. To learn how to create a custom
	// HTML template, see Create Custom Worker Task Template
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-custom-templates.html). To
	// learn how to create a human task UI, which is a worker task template that can be
	// used in a flow definition, see Create and Delete a Worker Task Templates
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-worker-template-console.html).
	//
	// 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. To learn more about the types
	// of workforces and work teams you can create and use with Amazon A2I, see Create
	// and Manage Workforces
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-management.html).
	//
	// 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox
	//
	// *
	// arn:aws:lambda:ca-central-1:918755190332:function:PRE-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: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. If you create a custom
	// labeling job, the maximum value for this parameter is 8 hours (28,800 seconds).
	// If you create a labeling job using a built-in task type
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html) the
	// maximum for this parameter depends on the task type you use:
	//
	// * For image
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-images.html) and text
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-text.html) labeling
	// jobs, the maximum is 8 hours (28,800 seconds).
	//
	// * For 3D point cloud
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud.html) and video
	// frame (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-video.html) labeling
	// jobs, the maximum is 30 days (2952,000 seconds) for non-AL mode. For most users,
	// the maximum is also 30 days. If you want to change these limits, contact Amazon
	// Web Services Support.
	//
	// 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.
	// The default and maximum values for this parameter depend on the type of
	// workforce you use.
	//
	// * If you choose the Amazon Mechanical Turk workforce, the
	// maximum is 12 hours (43,200 seconds). The default is 6 hours (21,600
	// seconds).
	//
	// * If you choose a private or vendor workforce, the default value is
	// 30 days (2592,000 seconds) for non-AL mode. For most users, the maximum is also
	// 30 days. If you want to change this limit, contact Amazon Web Services Support.
	TaskAvailabilityLifetimeInSeconds *int32

	// Keywords used to describe the task so that workers on Amazon Mechanical Turk can
	// discover the task.
	TaskKeywords []string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Container for human task user interface information.

type HyperParameterAlgorithmSpecification 

type HyperParameterAlgorithmSpecification struct {

	// The training input mode that the algorithm supports. For more information about
	// input modes, see Algorithms
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html). Pipe mode If an
	// algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon
	// S3 to the container. File mode If an algorithm supports File mode, SageMaker
	// downloads the training data from S3 to the provisioned ML storage volume, and
	// mounts the directory to the Docker volume for the training container. You must
	// provision the ML storage volume with sufficient capacity to accommodate the data
	// downloaded from S3. In addition to the training data, the ML storage volume also
	// stores the output model. The algorithm container uses the ML storage volume to
	// also store intermediate information, if any. For distributed algorithms,
	// training data is distributed uniformly. Your training duration is predictable if
	// the input data objects sizes are approximately the same. 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 when one host
	// in a training cluster is overloaded, thus becoming a bottleneck in training.
	// FastFile mode If an algorithm supports FastFile mode, SageMaker streams data
	// directly from S3 to the container with no code changes, and provides file system
	// access to the data. Users can author their training script to interact with
	// these files as if they were stored on disk. FastFile mode works best when the
	// data is read sequentially. Augmented manifest files aren't supported. The
	// startup time is lower when there are fewer files in the S3 bucket provided.
	//
	// 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 a managed spot training job has to complete. When the
	// job reaches the time 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

	// The number of times to retry the job when the job fails due to an
	// InternalServerError.
	RetryStrategy *RetryStrategy

	// 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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

	// (Optional) Specifies an authentication configuration for the private docker
	// registry where your model image is hosted. Specify a value for this property
	// only if you specified Vpc as the value for the RepositoryAccessMode field, and
	// the private Docker registry where the model image is hosted requires
	// authentication.
	RepositoryAuthConfig *RepositoryAuthConfig
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 InferenceExecutionConfig added in v1.2.0 

type InferenceExecutionConfig struct {

	// How containers in a multi-container are run. The following values are valid.
	//
	// *
	// SERIAL - Containers run as a serial pipeline.
	//
	// * DIRECT - Only the individual
	// container that you specify is run.
	//
	// This member is required.
	Mode InferenceExecutionMode
	// contains filtered or unexported fields
}

Specifies details about how containers in a multi-container endpoint are run.

type InferenceExecutionMode added in v1.2.0 

type InferenceExecutionMode string
const (
	InferenceExecutionModeSerial InferenceExecutionMode = "Serial"
	InferenceExecutionModeDirect InferenceExecutionMode = "Direct"
)

Enum values for InferenceExecutionMode

func (InferenceExecutionMode) Values added in v1.2.0 

func (InferenceExecutionMode) Values() []InferenceExecutionMode

Values returns all known values for InferenceExecutionMode. 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

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

	// A list of the instance types that are used to generate inferences in real-time.
	// This parameter is required for unversioned models, and optional for versioned
	// models.
	SupportedRealtimeInferenceInstanceTypes []ProductionVariantInstanceType

	// A list of the instance types on which a transformation job can be run or on
	// which an endpoint can be deployed. This parameter is required for unversioned
	// models, and optional for versioned models.
	SupportedTransformInstanceTypes []TransformInstanceType
	// contains filtered or unexported fields
}

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/DARKNET: 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"}
	//
	// Depending on
	// the model format, DataInputConfig requires the following parameters for
	// ml_eia2OutputConfig:TargetDevice
	// (https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-TargetDevice).
	//
	// *
	// For TensorFlow models saved in the SavedModel format, specify the input names
	// from signature_def_key and the input model shapes for DataInputConfig. Specify
	// the signature_def_key in OutputConfig:CompilerOptions
	// (https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptions)
	// if the model does not use TensorFlow's default signature def key. For
	// example:
	//
	// * "DataInputConfig": {"inputs": [1, 224, 224, 3]}
	//
	// *
	// "CompilerOptions": {"signature_def_key": "serving_custom"}
	//
	// * For TensorFlow
	// models saved as a frozen graph, specify the input tensor names and shapes in
	// DataInputConfig and the output tensor names for output_names in
	// OutputConfig:CompilerOptions
	// (https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptions).
	// For example:
	//
	// * "DataInputConfig": {"input_tensor:0": [1, 224, 224, 3]}
	//
	// *
	// "CompilerOptions": {"output_names": ["output_tensor:0"]}
	//
	// 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

	// Specifies the framework version to use. This API field is only supported for
	// PyTorch framework versions 1.4, 1.5, and 1.6 for cloud instance target devices:
	// ml_c4, ml_c5, ml_m4, ml_m5, ml_p2, ml_p3, and ml_g4dn.
	FrameworkVersion *string
	// contains filtered or unexported fields
}

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 InputMode added in v0.31.0 

type InputMode string
const (
	InputModePipe InputMode = "Pipe"
	InputModeFile InputMode = "File"
)

Enum values for InputMode

func (InputMode) Values added in v0.31.0 

func (InputMode) Values() []InputMode

Values returns all known values for InputMode. 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 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"
	InstanceTypeMlM5dLarge     InstanceType = "ml.m5d.large"
	InstanceTypeMlM5dXlarge    InstanceType = "ml.m5d.xlarge"
	InstanceTypeMlM5d2xlarge   InstanceType = "ml.m5d.2xlarge"
	InstanceTypeMlM5d4xlarge   InstanceType = "ml.m5d.4xlarge"
	InstanceTypeMlM5d8xlarge   InstanceType = "ml.m5d.8xlarge"
	InstanceTypeMlM5d12xlarge  InstanceType = "ml.m5d.12xlarge"
	InstanceTypeMlM5d16xlarge  InstanceType = "ml.m5d.16xlarge"
	InstanceTypeMlM5d24xlarge  InstanceType = "ml.m5d.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"
	InstanceTypeMlP3dn24xlarge InstanceType = "ml.p3dn.24xlarge"
	InstanceTypeMlG4dnXlarge   InstanceType = "ml.g4dn.xlarge"
	InstanceTypeMlG4dn2xlarge  InstanceType = "ml.g4dn.2xlarge"
	InstanceTypeMlG4dn4xlarge  InstanceType = "ml.g4dn.4xlarge"
	InstanceTypeMlG4dn8xlarge  InstanceType = "ml.g4dn.8xlarge"
	InstanceTypeMlG4dn12xlarge InstanceType = "ml.g4dn.12xlarge"
	InstanceTypeMlG4dn16xlarge InstanceType = "ml.g4dn.16xlarge"
	InstanceTypeMlR5Large      InstanceType = "ml.r5.large"
	InstanceTypeMlR5Xlarge     InstanceType = "ml.r5.xlarge"
	InstanceTypeMlR52xlarge    InstanceType = "ml.r5.2xlarge"
	InstanceTypeMlR54xlarge    InstanceType = "ml.r5.4xlarge"
	InstanceTypeMlR58xlarge    InstanceType = "ml.r5.8xlarge"
	InstanceTypeMlR512xlarge   InstanceType = "ml.r5.12xlarge"
	InstanceTypeMlR516xlarge   InstanceType = "ml.r5.16xlarge"
	InstanceTypeMlR524xlarge   InstanceType = "ml.r5.24xlarge"
)

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 default
	// SageMaker image used by the JupyterServer app.
	DefaultResourceSpec *ResourceSpec

	// The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the
	// JupyterServerApp.
	LifecycleConfigArns []string
	// contains filtered or unexported fields
}

The JupyterServer app settings.

type KernelGatewayAppSettings 

type KernelGatewayAppSettings struct {

	// A list of custom SageMaker 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 Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the
	// the user profile or domain.
	LifecycleConfigArns []string
	// contains filtered or unexported fields
}

The KernelGateway app settings.

type KernelGatewayImageConfig added in v0.29.0 

type KernelGatewayImageConfig struct {

	// The specification of the Jupyter kernels in the image.
	//
	// This member is required.
	KernelSpecs []KernelSpec

	// The Amazon Elastic File System (EFS) storage configuration for a SageMaker
	// image.
	FileSystemConfig *FileSystemConfig
	// contains filtered or unexported fields
}

The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.

type KernelSpec added in v0.29.0 

type KernelSpec struct {

	// The name of the Jupyter kernel in the image. This value is case sensitive.
	//
	// This member is required.
	Name *string

	// The display name of the kernel.
	DisplayName *string
	// contains filtered or unexported fields
}

The specification of a Jupyter 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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. To learn more, see
	// Send Data to a Streaming Labeling Job
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-send-data).
	SnsDataSource *LabelingJobSnsDataSource
	// contains filtered or unexported fields
}

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

	// The Amazon Web Services account ID of the account used to start the labeling
	// job.
	//
	// 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 Amazon Web Services Key Management Service ID of the key used to encrypt the
	// output data, if any. If you provide your own KMS key ID, you must add the
	// required permissions to your KMS key described in Encrypt Output Data and
	// Storage Volume with Amazon Web Services KMS
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security-permission.html#sms-security-kms-permissions).
	// If you don't provide a KMS key ID, Amazon SageMaker uses the default Amazon Web
	// Services KMS key for Amazon S3 for your role's account to encrypt your output
	// data. 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.
	KmsKeyId *string

	// An Amazon Simple Notification Service (Amazon SNS) output topic ARN. Provide a
	// SnsTopicArn if you want to do real time chaining to another streaming job and
	// receive an Amazon SNS notifications each time a data object is submitted by a
	// worker. If you provide an SnsTopicArn in OutputConfig, when workers complete
	// labeling tasks, Ground Truth will send labeling task output data to the SNS
	// output topic you specify here. To learn more, see Receive Output Data from a
	// Streaming Labeling Job
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-output-data).
	SnsTopicArn *string
	// contains filtered or unexported fields
}

Output configuration information for a labeling job.

type LabelingJobResourceConfig 

type LabelingJobResourceConfig struct {

	// The Amazon Web Services Key Management Service (Amazon Web Services KMS) key
	// that Amazon SageMaker uses to encrypt data on the storage volume attached to the
	// ML compute instance(s) that run the training and inference jobs used for
	// automated data labeling. You can only specify a VolumeKmsKeyId when you create a
	// labeling job with automated data labeling enabled using the API operation
	// CreateLabelingJob. You cannot specify an Amazon Web Services KMS key to encrypt
	// the storage volume used for automated data labeling model training and inference
	// when you create a labeling job using the console. To learn more, see Output Data
	// and Storage Volume Encryption
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security.html). 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
	// contains filtered or unexported fields
}

Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.

type LabelingJobS3DataSource 

type LabelingJobS3DataSource struct {

	// The Amazon S3 location of the manifest file that describes the input data
	// objects. The input manifest file referenced in ManifestS3Uri must contain one of
	// the following keys: source-ref or source. The value of the keys are interpreted
	// as follows:
	//
	// * source-ref: The source of the object is the Amazon S3 object
	// specified in the value. Use this value when the object is a binary object, such
	// as an image.
	//
	// * source: The source of the object is the value. Use this value
	// when the object is a text value.
	//
	// If you are a new user of Ground Truth, it is
	// recommended you review Use an Input Manifest File
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-input-data-input-manifest.html)
	// in the Amazon SageMaker Developer Guide to learn how to create an input manifest
	// file.
	//
	// This member is required.
	ManifestS3Uri *string
	// contains filtered or unexported fields
}

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.
	//
	// This member is required.
	SnsTopicArn *string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Provides summary information about a labeling job.

type LambdaStepMetadata added in v1.11.0 

type LambdaStepMetadata struct {

	// The Amazon Resource Name (ARN) of the Lambda function that was run by this step
	// execution.
	Arn *string

	// A list of the output parameters of the Lambda step.
	OutputParameters []OutputParameter
	// contains filtered or unexported fields
}

Metadata for a Lambda step.

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 ListDeviceFleetsSortBy added in v0.31.0 

type ListDeviceFleetsSortBy string
const (
	ListDeviceFleetsSortByName             ListDeviceFleetsSortBy = "NAME"
	ListDeviceFleetsSortByCreationTime     ListDeviceFleetsSortBy = "CREATION_TIME"
	ListDeviceFleetsSortByLastModifiedTime ListDeviceFleetsSortBy = "LAST_MODIFIED_TIME"
)

Enum values for ListDeviceFleetsSortBy

func (ListDeviceFleetsSortBy) Values added in v0.31.0 

func (ListDeviceFleetsSortBy) Values() []ListDeviceFleetsSortBy

Values returns all known values for ListDeviceFleetsSortBy. 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 ListEdgePackagingJobsSortBy added in v0.31.0 

type ListEdgePackagingJobsSortBy string
const (
	ListEdgePackagingJobsSortByName                   ListEdgePackagingJobsSortBy = "NAME"
	ListEdgePackagingJobsSortByModelName              ListEdgePackagingJobsSortBy = "MODEL_NAME"
	ListEdgePackagingJobsSortByCreationTime           ListEdgePackagingJobsSortBy = "CREATION_TIME"
	ListEdgePackagingJobsSortByLastModifiedTime       ListEdgePackagingJobsSortBy = "LAST_MODIFIED_TIME"
	ListEdgePackagingJobsSortByEdgePackagingJobStatus ListEdgePackagingJobsSortBy = "STATUS"
)

Enum values for ListEdgePackagingJobsSortBy

func (ListEdgePackagingJobsSortBy) Values added in v0.31.0 

func (ListEdgePackagingJobsSortBy) Values() []ListEdgePackagingJobsSortBy

Values returns all known values for ListEdgePackagingJobsSortBy. 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
	// contains filtered or unexported fields
}

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

type MetadataProperties added in v0.31.0 

type MetadataProperties struct {

	// The commit ID.
	CommitId *string

	// The entity this entity was generated by.
	GeneratedBy *string

	// The project ID.
	ProjectId *string

	// The repository.
	Repository *string
	// contains filtered or unexported fields
}

Metadata properties of the tracking entity, trial, or trial component.

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
	// contains filtered or unexported fields
}

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

type MetricDatum added in v1.12.0 

type MetricDatum struct {

	// The name of the metric.
	MetricName AutoMLMetricEnum

	// The dataset split from which the AutoML job produced the metric.
	Set MetricSetSource

	// The value of the metric.
	Value float32
	// contains filtered or unexported fields
}

Information about the metric for a candidate produced by an AutoML job.

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
	// contains filtered or unexported fields
}

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 MetricSetSource added in v1.12.0 

type MetricSetSource string
const (
	MetricSetSourceTrain      MetricSetSource = "Train"
	MetricSetSourceValidation MetricSetSource = "Validation"
	MetricSetSourceTest       MetricSetSource = "Test"
)

Enum values for MetricSetSource

func (MetricSetSource) Values added in v1.12.0 

func (MetricSetSource) Values() []MetricSetSource

Values returns all known values for MetricSetSource. 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 MetricsSource added in v0.31.0 

type MetricsSource struct {

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

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

	//
	ContentDigest *string
	// contains filtered or unexported fields
}

type ModelApprovalStatus added in v0.31.0 

type ModelApprovalStatus string
const (
	ModelApprovalStatusApproved              ModelApprovalStatus = "Approved"
	ModelApprovalStatusRejected              ModelApprovalStatus = "Rejected"
	ModelApprovalStatusPendingManualApproval ModelApprovalStatus = "PendingManualApproval"
)

Enum values for ModelApprovalStatus

func (ModelApprovalStatus) Values added in v0.31.0 

func (ModelApprovalStatus) Values() []ModelApprovalStatus

Values returns all known values for ModelApprovalStatus. 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 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
	// contains filtered or unexported fields
}

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 definition that describes how to compute inferences, and other metadata.

type ModelBiasAppSpecification added in v0.31.0 

type ModelBiasAppSpecification struct {

	// JSON formatted S3 file that defines bias parameters. For more information on
	// this JSON configuration file, see Configure bias parameters
	// (https://docs.aws.amazon.com/sagemaker/latest/json-bias-parameter-config.html).
	//
	// This member is required.
	ConfigUri *string

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

	// Sets the environment variables in the Docker container.
	Environment map[string]string
	// contains filtered or unexported fields
}

Docker container image configuration object for the model bias job.

type ModelBiasBaselineConfig added in v0.31.0 

type ModelBiasBaselineConfig struct {

	// The name of the baseline model bias job.
	BaseliningJobName *string

	// The constraints resource for a monitoring job.
	ConstraintsResource *MonitoringConstraintsResource
	// contains filtered or unexported fields
}

The configuration for a baseline model bias job.

type ModelBiasJobInput added in v0.31.0 

type ModelBiasJobInput struct {

	// Input object for the endpoint
	//
	// This member is required.
	EndpointInput *EndpointInput

	// Location of ground truth labels to use in model bias job.
	//
	// This member is required.
	GroundTruthS3Input *MonitoringGroundTruthS3Input
	// contains filtered or unexported fields
}

Inputs for the model bias job.

type ModelCacheSetting added in v1.2.0 

type ModelCacheSetting string
const (
	ModelCacheSettingEnabled  ModelCacheSetting = "Enabled"
	ModelCacheSettingDisabled ModelCacheSetting = "Disabled"
)

Enum values for ModelCacheSetting

func (ModelCacheSetting) Values added in v1.2.0 

func (ModelCacheSetting) Values() []ModelCacheSetting

Values returns all known values for ModelCacheSetting. 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 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
	// contains filtered or unexported fields
}

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

type ModelDataQuality added in v0.31.0 

type ModelDataQuality struct {

	// Data quality constraints for a model.
	Constraints *MetricsSource

	// Data quality statistics for a model.
	Statistics *MetricsSource
	// contains filtered or unexported fields
}

Data quality constraints and statistics for a model.

type ModelDeployConfig added in v1.4.0 

type ModelDeployConfig struct {

	// Set to True to automatically generate an endpoint name for a one-click Autopilot
	// model deployment; set to False otherwise. The default value is False. If you set
	// AutoGenerateEndpointName to True, do not specify the EndpointName; otherwise a
	// 400 error is thrown.
	AutoGenerateEndpointName bool

	// Specifies the endpoint name to use for a one-click Autopilot model deployment if
	// the endpoint name is not generated automatically. Specify the EndpointName if
	// and only if you set AutoGenerateEndpointName to False; otherwise a 400 error is
	// thrown.
	EndpointName *string
	// contains filtered or unexported fields
}

Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

type ModelDeployResult added in v1.4.0 

type ModelDeployResult struct {

	// The name of the endpoint to which the model has been deployed. If model
	// deployment fails, this field is omitted from the response.
	EndpointName *string
	// contains filtered or unexported fields
}

Provides information about the endpoint of the model deployment.

type ModelDigests added in v0.31.0 

type ModelDigests struct {

	// Provides a hash value that uniquely identifies the stored model artifacts.
	ArtifactDigest *string
	// contains filtered or unexported fields
}

Provides information to verify the integrity of stored model artifacts.

type ModelExplainabilityAppSpecification added in v0.31.0 

type ModelExplainabilityAppSpecification struct {

	// JSON formatted S3 file that defines explainability parameters. For more
	// information on this JSON configuration file, see Configure model explainability
	// parameters
	// (https://docs.aws.amazon.com/sagemaker/latest/json-model-explainability-parameter-config.html).
	//
	// This member is required.
	ConfigUri *string

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

	// Sets the environment variables in the Docker container.
	Environment map[string]string
	// contains filtered or unexported fields
}

Docker container image configuration object for the model explainability job.

type ModelExplainabilityBaselineConfig added in v0.31.0 

type ModelExplainabilityBaselineConfig struct {

	// The name of the baseline model explainability job.
	BaseliningJobName *string

	// The constraints resource for a monitoring job.
	ConstraintsResource *MonitoringConstraintsResource
	// contains filtered or unexported fields
}

The configuration for a baseline model explainability job.

type ModelExplainabilityJobInput added in v0.31.0 

type ModelExplainabilityJobInput struct {

	// Input object for the endpoint
	//
	// This member is required.
	EndpointInput *EndpointInput
	// contains filtered or unexported fields
}

Inputs for the model explainability job.

type ModelMetrics added in v0.31.0 

type ModelMetrics struct {

	// Metrics that measure bais in a model.
	Bias *Bias

	// Metrics that help explain a model.
	Explainability *Explainability

	// Metrics that measure the quality of the input data for a model.
	ModelDataQuality *ModelDataQuality

	// Metrics that measure the quality of a model.
	ModelQuality *ModelQuality
	// contains filtered or unexported fields
}

Contains metrics captured from a model.

type ModelPackage added in v0.31.0 

type ModelPackage struct {

	// A description provided when the model approval is set.
	ApprovalDescription *string

	// Whether the model package is to be certified to be listed on Amazon Web Services
	// Marketplace. For information about listing model packages on Amazon Web Services
	// Marketplace, see List Your Algorithm or Model Package on Amazon Web Services
	// Marketplace
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-mkt-list.html).
	CertifyForMarketplace bool

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

	// The time that the model package was created.
	CreationTime *time.Time

	// The metadata properties for the model package.
	CustomerMetadataProperties map[string]string

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

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

	// The last time the model package was modified.
	LastModifiedTime *time.Time

	// Metadata properties of the tracking entity, trial, or trial component.
	MetadataProperties *MetadataProperties

	// The approval status of the model. This can be one of the following values.
	//
	// *
	// APPROVED - The model is approved
	//
	// * REJECTED - The model is rejected.
	//
	// *
	// PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
	ModelApprovalStatus ModelApprovalStatus

	// Metrics for the model.
	ModelMetrics *ModelMetrics

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

	// The description of the model package.
	ModelPackageDescription *string

	// The model group to which the model belongs.
	ModelPackageGroupName *string

	// The name of the model.
	ModelPackageName *string

	// The status of the model package. This can be one of the following values.
	//
	// *
	// PENDING - The model package is pending being created.
	//
	// * IN_PROGRESS - The model
	// package is in the process of being created.
	//
	// * COMPLETED - The model package was
	// successfully created.
	//
	// * FAILED - The model package failed.
	//
	// * DELETING - The
	// model package is in the process of being deleted.
	ModelPackageStatus ModelPackageStatus

	// Specifies the validation and image scan statuses of the model package.
	ModelPackageStatusDetails *ModelPackageStatusDetails

	// The version number of a versioned model.
	ModelPackageVersion *int32

	// A list of algorithms that were used to create a model package.
	SourceAlgorithmSpecification *SourceAlgorithmSpecification

	// A list of the tags associated with the model package. For more information, see
	// Tagging Amazon Web Services resources
	// (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html) in the Amazon
	// Web Services General Reference Guide.
	Tags []Tag

	// Specifies batch transform jobs that Amazon SageMaker runs to validate your model
	// package.
	ValidationSpecification *ModelPackageValidationSpecification
	// contains filtered or unexported fields
}

A versioned model that can be deployed for SageMaker inference.

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

	// 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

	// 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 Amazon Web Services Marketplace product ID of the model package.
	ProductId *string
	// contains filtered or unexported fields
}

Describes the Docker container for the model package.

type ModelPackageGroup added in v0.31.0 

type ModelPackageGroup struct {

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

	// The time that the model group was created.
	CreationTime *time.Time

	// The Amazon Resource Name (ARN) of the model group.
	ModelPackageGroupArn *string

	// The description for the model group.
	ModelPackageGroupDescription *string

	// The name of the model group.
	ModelPackageGroupName *string

	// The status of the model group. This can be one of the following values.
	//
	// *
	// PENDING - The model group is pending being created.
	//
	// * IN_PROGRESS - The model
	// group is in the process of being created.
	//
	// * COMPLETED - The model group was
	// successfully created.
	//
	// * FAILED - The model group failed.
	//
	// * DELETING - The
	// model group is in the process of being deleted.
	//
	// * DELETE_FAILED - SageMaker
	// failed to delete the model group.
	ModelPackageGroupStatus ModelPackageGroupStatus

	// A list of the tags associated with the model group. For more information, see
	// Tagging Amazon Web Services resources
	// (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html) in the Amazon
	// Web Services General Reference Guide.
	Tags []Tag
	// contains filtered or unexported fields
}

A group of versioned models in the model registry.

type ModelPackageGroupSortBy added in v0.31.0 

type ModelPackageGroupSortBy string
const (
	ModelPackageGroupSortByName         ModelPackageGroupSortBy = "Name"
	ModelPackageGroupSortByCreationTime ModelPackageGroupSortBy = "CreationTime"
)

Enum values for ModelPackageGroupSortBy

func (ModelPackageGroupSortBy) Values added in v0.31.0 

func (ModelPackageGroupSortBy) Values() []ModelPackageGroupSortBy

Values returns all known values for ModelPackageGroupSortBy. 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 ModelPackageGroupStatus added in v0.31.0 

type ModelPackageGroupStatus string
const (
	ModelPackageGroupStatusPending      ModelPackageGroupStatus = "Pending"
	ModelPackageGroupStatusInProgress   ModelPackageGroupStatus = "InProgress"
	ModelPackageGroupStatusCompleted    ModelPackageGroupStatus = "Completed"
	ModelPackageGroupStatusFailed       ModelPackageGroupStatus = "Failed"
	ModelPackageGroupStatusDeleting     ModelPackageGroupStatus = "Deleting"
	ModelPackageGroupStatusDeleteFailed ModelPackageGroupStatus = "DeleteFailed"
)

Enum values for ModelPackageGroupStatus

func (ModelPackageGroupStatus) Values added in v0.31.0 

func (ModelPackageGroupStatus) Values() []ModelPackageGroupStatus

Values returns all known values for ModelPackageGroupStatus. 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 ModelPackageGroupSummary added in v0.31.0 

type ModelPackageGroupSummary struct {

	// The time that the model group was created.
	//
	// This member is required.
	CreationTime *time.Time

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

	// The name of the model group.
	//
	// This member is required.
	ModelPackageGroupName *string

	// The status of the model group.
	//
	// This member is required.
	ModelPackageGroupStatus ModelPackageGroupStatus

	// A description of the model group.
	ModelPackageGroupDescription *string
	// contains filtered or unexported fields
}

Summary information about a model group.

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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

	// The approval status of the model. This can be one of the following values.
	//
	// *
	// APPROVED - The model is approved
	//
	// * REJECTED - The model is rejected.
	//
	// *
	// PENDING_MANUAL_APPROVAL - The model is waiting for manual approval.
	ModelApprovalStatus ModelApprovalStatus

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

	// If the model package is a versioned model, the model group that the versioned
	// model belongs to.
	ModelPackageGroupName *string

	// If the model package is a versioned model, the version of the model.
	ModelPackageVersion *int32
	// contains filtered or unexported fields
}

Provides summary information about a model package.

type ModelPackageType added in v0.31.0 

type ModelPackageType string
const (
	ModelPackageTypeVersioned   ModelPackageType = "Versioned"
	ModelPackageTypeUnversioned ModelPackageType = "Unversioned"
	ModelPackageTypeBoth        ModelPackageType = "Both"
)

Enum values for ModelPackageType

func (ModelPackageType) Values added in v0.31.0 

func (ModelPackageType) Values() []ModelPackageType

Values returns all known values for ModelPackageType. 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 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 filtered or unexported fields
}

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 Amazon Web Services 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
	// contains filtered or unexported fields
}

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

type ModelQuality added in v0.31.0 

type ModelQuality struct {

	// Model quality constraints.
	Constraints *MetricsSource

	// Model quality statistics.
	Statistics *MetricsSource
	// contains filtered or unexported fields
}

Model quality statistics and constraints.

type ModelQualityAppSpecification added in v0.31.0 

type ModelQualityAppSpecification struct {

	// The address of the container image that the monitoring job runs.
	//
	// 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 that the monitoring job runs.
	ContainerEntrypoint []string

	// Sets the environment variables in the container that the monitoring job runs.
	Environment map[string]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

	// The machine learning problem type of the model that the monitoring job monitors.
	ProblemType MonitoringProblemType

	// 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
	// contains filtered or unexported fields
}

Container image configuration object for the monitoring job.

type ModelQualityBaselineConfig added in v0.31.0 

type ModelQualityBaselineConfig struct {

	// The name of the job that performs baselining for the monitoring job.
	BaseliningJobName *string

	// The constraints resource for a monitoring job.
	ConstraintsResource *MonitoringConstraintsResource
	// contains filtered or unexported fields
}

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 ModelQualityJobInput added in v0.31.0 

type ModelQualityJobInput struct {

	// Input object for the endpoint
	//
	// This member is required.
	EndpointInput *EndpointInput

	// The ground truth label provided for the model.
	//
	// This member is required.
	GroundTruthS3Input *MonitoringGroundTruthS3Input
	// contains filtered or unexported fields
}

The input for the model quality monitoring job. Currently endponts are supported for input for model quality monitoring jobs.

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 ModelStepMetadata added in v0.31.0 

type ModelStepMetadata struct {

	// The Amazon Resource Name (ARN) of the created model.
	Arn *string
	// contains filtered or unexported fields
}

Metadata for Model steps.

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Container image configuration object for the monitoring job.

type MonitoringBaselineConfig 

type MonitoringBaselineConfig struct {

	// The name of the job that performs baselining for the monitoring job.
	BaseliningJobName *string

	// 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
	// contains filtered or unexported fields
}

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 Amazon Web Services Key Management Service (Amazon Web Services 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 the endpoint used to run the monitoring job.
	EndpointName *string

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

	// The name of the monitoring job.
	MonitoringJobDefinitionName *string

	// The type of the monitoring job.
	MonitoringType MonitoringType

	// The Amazon Resource Name (ARN) of the monitoring job.
	ProcessingJobArn *string
	// contains filtered or unexported fields
}

Summary of information about the last monitoring job to run.

type MonitoringGroundTruthS3Input added in v0.31.0 

type MonitoringGroundTruthS3Input struct {

	// The address of the Amazon S3 location of the ground truth labels.
	S3Uri *string
	// contains filtered or unexported fields
}

The ground truth labels for the dataset used for the monitoring job.

type MonitoringInput 

type MonitoringInput struct {

	// The endpoint for a monitoring job.
	//
	// This member is required.
	EndpointInput *EndpointInput
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Defines the monitoring job.

type MonitoringJobDefinitionSortKey added in v0.31.0 

type MonitoringJobDefinitionSortKey string
const (
	MonitoringJobDefinitionSortKeyName         MonitoringJobDefinitionSortKey = "Name"
	MonitoringJobDefinitionSortKeyCreationTime MonitoringJobDefinitionSortKey = "CreationTime"
)

Enum values for MonitoringJobDefinitionSortKey

func (MonitoringJobDefinitionSortKey) Values added in v0.31.0 

func (MonitoringJobDefinitionSortKey) Values() []MonitoringJobDefinitionSortKey

Values returns all known values for MonitoringJobDefinitionSortKey. 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 MonitoringJobDefinitionSummary added in v0.31.0 

type MonitoringJobDefinitionSummary struct {

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

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

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

	// The name of the monitoring job.
	//
	// This member is required.
	MonitoringJobDefinitionName *string
	// contains filtered or unexported fields
}

Summary information about a monitoring job.

type MonitoringNetworkConfig added in v0.31.0 

type MonitoringNetworkConfig struct {

	// Whether to encrypt all communications between the instances used for the
	// monitoring jobs. Choose True to encrypt communications. Encryption provides
	// greater security for distributed 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 monitoring 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
	// contains filtered or unexported fields
}

The networking configuration for 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
	// contains filtered or unexported fields
}

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 Amazon Web Services Key Management Service (Amazon Web Services KMS) key
	// that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon
	// S3 server-side encryption.
	KmsKeyId *string
	// contains filtered or unexported fields
}

The output configuration for monitoring jobs.

type MonitoringProblemType added in v0.31.0 

type MonitoringProblemType string
const (
	MonitoringProblemTypeBinaryClassification     MonitoringProblemType = "BinaryClassification"
	MonitoringProblemTypeMulticlassClassification MonitoringProblemType = "MulticlassClassification"
	MonitoringProblemTypeRegression               MonitoringProblemType = "Regression"
)

Enum values for MonitoringProblemType

func (MonitoringProblemType) Values added in v0.31.0 

func (MonitoringProblemType) Values() []MonitoringProblemType

Values returns all known values for MonitoringProblemType. 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 MonitoringResources 

type MonitoringResources struct {

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

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
	// contains filtered or unexported fields
}

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

type MonitoringSchedule added in v0.31.0 

type MonitoringSchedule struct {

	// The time that the monitoring schedule was created.
	CreationTime *time.Time

	// The endpoint that hosts the model being monitored.
	EndpointName *string

	// If the monitoring schedule failed, the reason it failed.
	FailureReason *string

	// The last time the monitoring schedule was changed.
	LastModifiedTime *time.Time

	// Summary of information about the last monitoring job to run.
	LastMonitoringExecutionSummary *MonitoringExecutionSummary

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

	// Configures the monitoring schedule and defines the monitoring job.
	MonitoringScheduleConfig *MonitoringScheduleConfig

	// The name of the monitoring schedule.
	MonitoringScheduleName *string

	// The status of the monitoring schedule. This can be one of the following
	// values.
	//
	// * PENDING - The schedule is pending being created.
	//
	// * FAILED - The
	// schedule failed.
	//
	// * SCHEDULED - The schedule was successfully created.
	//
	// *
	// STOPPED - The schedule was stopped.
	MonitoringScheduleStatus ScheduleStatus

	// The type of the monitoring job definition to schedule.
	MonitoringType MonitoringType

	// A list of the tags associated with the monitoring schedlue. For more
	// information, see Tagging Amazon Web Services resources
	// (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html) in the Amazon
	// Web Services General Reference Guide.
	Tags []Tag
	// contains filtered or unexported fields
}

A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor (https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.html).

type MonitoringScheduleConfig 

type MonitoringScheduleConfig struct {

	// Defines the monitoring job.
	MonitoringJobDefinition *MonitoringJobDefinition

	// The name of the monitoring job definition to schedule.
	MonitoringJobDefinitionName *string

	// The type of the monitoring job definition to schedule.
	MonitoringType MonitoringType

	// Configures the monitoring schedule.
	ScheduleConfig *ScheduleConfig
	// contains filtered or unexported fields
}

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

	// The name of the monitoring job definition that the schedule is for.
	MonitoringJobDefinitionName *string

	// The type of the monitoring job definition that the schedule is for.
	MonitoringType MonitoringType
	// contains filtered or unexported fields
}

Summarizes the monitoring schedule.

type MonitoringStatisticsResource 

type MonitoringStatisticsResource struct {

	// The Amazon S3 URI for the statistics resource.
	S3Uri *string
	// contains filtered or unexported fields
}

The statistics resource for a monitoring job.

type MonitoringStoppingCondition 

type MonitoringStoppingCondition struct {

	// The maximum runtime allowed in seconds. The MaxRuntimeInSeconds cannot exceed
	// the frequency of the job. For data quality and model explainability, this can be
	// up to 3600 seconds for an hourly schedule. For model bias and model quality
	// hourly schedules, this can be up to 1800 seconds.
	//
	// This member is required.
	MaxRuntimeInSeconds int32
	// contains filtered or unexported fields
}

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

type MonitoringType added in v0.31.0 

type MonitoringType string
const (
	MonitoringTypeDataQuality         MonitoringType = "DataQuality"
	MonitoringTypeModelQuality        MonitoringType = "ModelQuality"
	MonitoringTypeModelBias           MonitoringType = "ModelBias"
	MonitoringTypeModelExplainability MonitoringType = "ModelExplainability"
)

Enum values for MonitoringType

func (MonitoringType) Values added in v0.31.0 

func (MonitoringType) Values() []MonitoringType

Values returns all known values for MonitoringType. 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 MultiModelConfig added in v1.2.0 

type MultiModelConfig struct {

	// Whether to cache models for a multi-model endpoint. By default, multi-model
	// endpoints cache models so that a model does not have to be loaded into memory
	// each time it is invoked. Some use cases do not benefit from model caching. For
	// example, if an endpoint hosts a large number of models that are each invoked
	// infrequently, the endpoint might perform better if you disable model caching. To
	// disable model caching, set the value of this parameter to Disabled.
	ModelCacheSetting ModelCacheSetting
	// contains filtered or unexported fields
}

Specifies additional configuration for hosting multi-model endpoints.

type NeoVpcConfig added in v1.9.0 

type NeoVpcConfig struct {

	// The VPC security group IDs. IDs have the form of 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 that you want to connect the compilation job to
	// for accessing the model in Amazon S3.
	//
	// This member is required.
	Subnets []string
	// contains filtered or unexported fields
}

The VpcConfig configuration object that specifies the VPC that you want the compilation jobs to connect to. For more information on controlling access to your Amazon S3 buckets used for compilation job, see Give Amazon SageMaker Compilation Jobs Access to Resources in Your Amazon VPC (https://docs.aws.amazon.com/sagemaker/latest/dg/neo-vpc.html).

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 filtered or unexported fields
}

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 Amazon Web Services 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 Amazon Web Services
	// 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
	// contains filtered or unexported fields
}

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 Amazon SNS topic to which notifications should be published.
	NotificationTopicArn *string
	// contains filtered or unexported fields
}

Configures Amazon 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
	// contains filtered or unexported fields
}

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 OfflineStoreConfig added in v0.31.0 

type OfflineStoreConfig struct {

	// The Amazon Simple Storage (Amazon S3) location of OfflineStore.
	//
	// This member is required.
	S3StorageConfig *S3StorageConfig

	// The meta data of the Glue table that is autogenerated when an OfflineStore is
	// created.
	DataCatalogConfig *DataCatalogConfig

	// Set to True to disable the automatic creation of an Amazon Web Services Glue
	// table when configuring an OfflineStore.
	DisableGlueTableCreation bool
	// contains filtered or unexported fields
}

The configuration of an OfflineStore. Provide an OfflineStoreConfig in a request to CreateFeatureGroup to create an OfflineStore. To encrypt an OfflineStore using at rest data encryption, specify Amazon Web Services Key Management Service (KMS) key ID, or KMSKeyId, in S3StorageConfig.

type OfflineStoreStatus added in v0.31.0 

type OfflineStoreStatus struct {

	// An OfflineStore status.
	//
	// This member is required.
	Status OfflineStoreStatusValue

	// The justification for why the OfflineStoreStatus is Blocked (if applicable).
	BlockedReason *string
	// contains filtered or unexported fields
}

The status of OfflineStore.

type OfflineStoreStatusValue added in v0.31.0 

type OfflineStoreStatusValue string
const (
	OfflineStoreStatusValueActive   OfflineStoreStatusValue = "Active"
	OfflineStoreStatusValueBlocked  OfflineStoreStatusValue = "Blocked"
	OfflineStoreStatusValueDisabled OfflineStoreStatusValue = "Disabled"
)

Enum values for OfflineStoreStatusValue

func (OfflineStoreStatusValue) Values added in v0.31.0 

func (OfflineStoreStatusValue) Values() []OfflineStoreStatusValue

Values returns all known values for OfflineStoreStatusValue. 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 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 OnlineStoreConfig added in v0.31.0 

type OnlineStoreConfig struct {

	// Turn OnlineStore off by specifying False for the EnableOnlineStore flag. Turn
	// OnlineStore on by specifying True for the EnableOnlineStore flag. The default
	// value is False.
	EnableOnlineStore bool

	// Use to specify KMS Key ID (KMSKeyId) for at-rest encryption of your OnlineStore.
	SecurityConfig *OnlineStoreSecurityConfig
	// contains filtered or unexported fields
}

Use this to specify the Amazon Web Services Key Management Service (KMS) Key ID, or KMSKeyId, for at rest data encryption. You can turn OnlineStore on or off by specifying the EnableOnlineStore flag at General Assembly; the default value is False.

type OnlineStoreSecurityConfig added in v0.31.0 

type OnlineStoreSecurityConfig struct {

	// The ID of the Amazon Web Services Key Management Service (Amazon Web Services
	// KMS) key that SageMaker Feature Store uses to encrypt the Amazon S3 objects at
	// rest using Amazon S3 server-side encryption. The caller (either IAM user or IAM
	// role) of CreateFeatureGroup must have below permissions to the
	// OnlineStoreKmsKeyId:
	//
	// * "kms:Encrypt"
	//
	// * "kms:Decrypt"
	//
	// * "kms:DescribeKey"
	//
	// *
	// "kms:CreateGrant"
	//
	// * "kms:RetireGrant"
	//
	// * "kms:ReEncryptFrom"
	//
	// *
	// "kms:ReEncryptTo"
	//
	// * "kms:GenerateDataKey"
	//
	// * "kms:ListAliases"
	//
	// *
	// "kms:ListGrants"
	//
	// * "kms:RevokeGrant"
	//
	// The caller (either IAM user or IAM role)
	// to all DataPlane operations (PutRecord, GetRecord, DeleteRecord) must have the
	// following permissions to the KmsKeyId:
	//
	// * "kms:Decrypt"
	KmsKeyId *string
	// contains filtered or unexported fields
}

The security configuration for OnlineStore.

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.
	//
	// * DTYPE: Specifies the data type for
	// the input. When compiling for ml_* (except for ml_inf) instances using PyTorch
	// framework, provide the data type (dtype) of the model's input. "float32" is used
	// if "DTYPE" is not specified. Options for data type are:
	//
	// * float32: Use either
	// "float" or "float32".
	//
	// * int64: Use either "int64" or "long".
	//
	// For example,
	// {"dtype" : "float32"}.
	//
	// * 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.
	//
	// * EIA: Compilation for the Elastic Inference Accelerator supports the
	// following compiler options:
	//
	// * precision_mode: Specifies the precision of
	// compiled artifacts. Supported values are "FP16" and "FP32". Default is
	// "FP32".
	//
	// * signature_def_key: Specifies the signature to use for models in
	// SavedModel format. Defaults is TensorFlow's default signature def key.
	//
	// *
	// output_names: Specifies a list of output tensor names for models in FrozenGraph
	// format. Set at most one API field, either: signature_def_key or
	// output_names.
	//
	// For example: {"precision_mode": "FP32", "output_names":
	// ["output:0"]}
	CompilerOptions *string

	// The Amazon Web Services Key Management Service key (Amazon Web Services KMS)
	// that Amazon SageMaker uses to encrypt your output models with Amazon S3
	// server-side encryption after compilation job. 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/userguide/UsingKMSEncryption.html)
	// in the Amazon Simple Storage Service Developer Guide. 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
	KmsKeyId *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 filtered or unexported fields
}

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 Amazon Web Services Key Management Service (Amazon Web Services 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 KMS 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/userguide/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 Amazon Web Services KMS
	// (https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html) in the
	// Amazon Web Services Key Management Service Developer Guide.
	KmsKeyId *string
	// contains filtered or unexported fields
}

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

type OutputParameter added in v1.7.0 

type OutputParameter struct {

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

	// The value of the output parameter.
	//
	// This member is required.
	Value *string
	// contains filtered or unexported fields
}

An output parameter of a pipeline step.

type Parameter added in v0.31.0 

type Parameter struct {

	// The name of the parameter to assign a value to. This parameter name must match a
	// named parameter in the pipeline definition.
	//
	// This member is required.
	Name *string

	// The literal value for the parameter.
	//
	// This member is required.
	Value *string
	// contains filtered or unexported fields
}

Assigns a value to a named Pipeline parameter.

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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

type PendingDeploymentSummary added in v1.19.0 

type PendingDeploymentSummary struct {

	// The name of the endpoint configuration used in the deployment.
	//
	// This member is required.
	EndpointConfigName *string

	// List of PendingProductionVariantSummary objects.
	ProductionVariants []PendingProductionVariantSummary

	// The start time of the deployment.
	StartTime *time.Time
	// contains filtered or unexported fields
}

The summary of an in-progress deployment when an endpoint is creating or updating with a new endpoint configuration.

type PendingProductionVariantSummary added in v1.19.0 

type PendingProductionVariantSummary struct {

	// The name of the 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

	// 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 this deployment, as specified in the
	// endpoint configuration for the endpoint. The value is taken from the request to
	// the CreateEndpointConfig operation.
	DesiredInstanceCount *int32

	// The requested weight for the variant in this deployment, as specified in the
	// endpoint configuration for the endpoint. The value is taken from the request to
	// the CreateEndpointConfig operation.
	DesiredWeight *float32

	// The type of instances associated with the variant.
	InstanceType ProductionVariantInstanceType

	// The endpoint variant status which describes the current deployment stage status
	// or operational status.
	VariantStatus []ProductionVariantStatus
	// contains filtered or unexported fields
}

The production variant summary for a deployment when an endpoint is creating or updating with the CreateEndpoint or UpdateEndpoint operations. Describes the VariantStatus , weight and capacity for a production variant associated with an endpoint.

type Pipeline added in v0.31.0 

type Pipeline struct {

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

	// The creation time of the pipeline.
	CreationTime *time.Time

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

	// The time that the pipeline was last modified.
	LastModifiedTime *time.Time

	// The time when the pipeline was last run.
	LastRunTime *time.Time

	// The Amazon Resource Name (ARN) of the pipeline.
	PipelineArn *string

	// The description of the pipeline.
	PipelineDescription *string

	// The display name of the pipeline.
	PipelineDisplayName *string

	// The name of the pipeline.
	PipelineName *string

	// The status of the pipeline.
	PipelineStatus PipelineStatus

	// The Amazon Resource Name (ARN) of the role that created the pipeline.
	RoleArn *string

	// A list of tags that apply to the pipeline.
	Tags []Tag
	// contains filtered or unexported fields
}

A SageMaker Model Building Pipeline instance.

type PipelineExecution added in v0.31.0 

type PipelineExecution struct {

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

	// The creation time of the pipeline execution.
	CreationTime *time.Time

	// If the execution failed, a message describing why.
	FailureReason *string

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

	// The time that the pipeline execution was last modified.
	LastModifiedTime *time.Time

	// The Amazon Resource Name (ARN) of the pipeline that was executed.
	PipelineArn *string

	// The Amazon Resource Name (ARN) of the pipeline execution.
	PipelineExecutionArn *string

	// The description of the pipeline execution.
	PipelineExecutionDescription *string

	// The display name of the pipeline execution.
	PipelineExecutionDisplayName *string

	// The status of the pipeline status.
	PipelineExecutionStatus PipelineExecutionStatus

	// Specifies the names of the experiment and trial created by a pipeline.
	PipelineExperimentConfig *PipelineExperimentConfig

	// Contains a list of pipeline parameters. This list can be empty.
	PipelineParameters []Parameter
	// contains filtered or unexported fields
}

An execution of a pipeline.

type PipelineExecutionStatus added in v0.31.0 

type PipelineExecutionStatus string
const (
	PipelineExecutionStatusExecuting PipelineExecutionStatus = "Executing"
	PipelineExecutionStatusStopping  PipelineExecutionStatus = "Stopping"
	PipelineExecutionStatusStopped   PipelineExecutionStatus = "Stopped"
	PipelineExecutionStatusFailed    PipelineExecutionStatus = "Failed"
	PipelineExecutionStatusSucceeded PipelineExecutionStatus = "Succeeded"
)

Enum values for PipelineExecutionStatus

func (PipelineExecutionStatus) Values added in v0.31.0 

func (PipelineExecutionStatus) Values() []PipelineExecutionStatus

Values returns all known values for PipelineExecutionStatus. 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 PipelineExecutionStep added in v0.31.0 

type PipelineExecutionStep struct {

	// If this pipeline execution step was cached, details on the cache hit.
	CacheHitResult *CacheHitResult

	// The time that the step stopped executing.
	EndTime *time.Time

	// The reason why the step failed execution. This is only returned if the step
	// failed its execution.
	FailureReason *string

	// Metadata for the step execution.
	Metadata *PipelineExecutionStepMetadata

	// The time that the step started executing.
	StartTime *time.Time

	// The name of the step that is executed.
	StepName *string

	// The status of the step execution.
	StepStatus StepStatus
	// contains filtered or unexported fields
}

An execution of a step in a pipeline.

type PipelineExecutionStepMetadata added in v0.31.0 

type PipelineExecutionStepMetadata struct {

	// The URL of the Amazon SQS queue used by this step execution, the pipeline
	// generated token, and a list of output parameters.
	Callback *CallbackStepMetadata

	// The outcome of the condition evaluation that was run by this step execution.
	Condition *ConditionStepMetadata

	// The Amazon Resource Name (ARN) of the Lambda function that was run by this step
	// execution and a list of output parameters.
	Lambda *LambdaStepMetadata

	// The Amazon Resource Name (ARN) of the model that was created by this step
	// execution.
	Model *ModelStepMetadata

	// The Amazon Resource Name (ARN) of the processing job that was run by this step
	// execution.
	ProcessingJob *ProcessingJobStepMetadata

	// The Amazon Resource Name (ARN) of the model package the model was registered to
	// by this step execution.
	RegisterModel *RegisterModelStepMetadata

	// The Amazon Resource Name (ARN) of the training job that was run by this step
	// execution.
	TrainingJob *TrainingJobStepMetadata

	// The Amazon Resource Name (ARN) of the transform job that was run by this step
	// execution.
	TransformJob *TransformJobStepMetadata

	// The Amazon Resource Name (ARN) of the tuning job that was run by this step
	// execution.
	TuningJob *TuningJobStepMetaData
	// contains filtered or unexported fields
}

Metadata for a step execution.

type PipelineExecutionSummary added in v0.31.0 

type PipelineExecutionSummary struct {

	// The Amazon Resource Name (ARN) of the pipeline execution.
	PipelineExecutionArn *string

	// The description of the pipeline execution.
	PipelineExecutionDescription *string

	// The display name of the pipeline execution.
	PipelineExecutionDisplayName *string

	// The status of the pipeline execution.
	PipelineExecutionStatus PipelineExecutionStatus

	// The start time of the pipeline execution.
	StartTime *time.Time
	// contains filtered or unexported fields
}

A pipeline execution summary.

type PipelineExperimentConfig added in v1.7.0 

type PipelineExperimentConfig struct {

	// The name of the experiment.
	ExperimentName *string

	// The name of the trial.
	TrialName *string
	// contains filtered or unexported fields
}

Specifies the names of the experiment and trial created by a pipeline.

type PipelineStatus added in v0.31.0 

type PipelineStatus string
const (
	PipelineStatusActive PipelineStatus = "Active"
)

Enum values for PipelineStatus

func (PipelineStatus) Values added in v0.31.0 

func (PipelineStatus) Values() []PipelineStatus

Values returns all known values for PipelineStatus. 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 PipelineSummary added in v0.31.0 

type PipelineSummary struct {

	// The creation time of the pipeline.
	CreationTime *time.Time

	// The last time that a pipeline execution began.
	LastExecutionTime *time.Time

	// The time that the pipeline was last modified.
	LastModifiedTime *time.Time

	// The Amazon Resource Name (ARN) of the pipeline.
	PipelineArn *string

	// The description of the pipeline.
	PipelineDescription *string

	// The display name of the pipeline.
	PipelineDisplayName *string

	// The name of the pipeline.
	PipelineName *string

	// The Amazon Resource Name (ARN) that the pipeline used to execute.
	RoleArn *string
	// contains filtered or unexported fields
}

A summary of a pipeline.

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. Certain Nitro-based
	// instances include local storage with a fixed total size, dependent on the
	// instance type. When using these instances for processing, 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 Amazon Web Services Key Management Service (Amazon Web Services 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. 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).
	VolumeKmsKeyId *string
	// contains filtered or unexported fields
}

Configuration for the cluster used to run a processing job.

type ProcessingFeatureStoreOutput added in v0.31.0 

type ProcessingFeatureStoreOutput struct {

	// The name of the Amazon SageMaker FeatureGroup to use as the destination for
	// processing job output. Note that your processing script is responsible for
	// putting records into your Feature Store.
	//
	// This member is required.
	FeatureGroupName *string
	// contains filtered or unexported fields
}

Configuration for processing job outputs in Amazon SageMaker Feature Store.

type ProcessingInput 

type ProcessingInput struct {

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

	// When True, input operations such as data download are managed natively by the
	// processing job application. When False (default), input operations are managed
	// by Amazon SageMaker.
	AppManaged bool

	// Configuration for a Dataset Definition input.
	DatasetDefinition *DatasetDefinition

	// Configuration for downloading input data from Amazon S3 into the processing
	// container.
	S3Input *ProcessingS3Input
	// contains filtered or unexported fields
}

The inputs for a processing job. The processing input must specify exactly one of either S3Input or DatasetDefinition types.

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"
	ProcessingInstanceTypeMlG4dnXlarge   ProcessingInstanceType = "ml.g4dn.xlarge"
	ProcessingInstanceTypeMlG4dn2xlarge  ProcessingInstanceType = "ml.g4dn.2xlarge"
	ProcessingInstanceTypeMlG4dn4xlarge  ProcessingInstanceType = "ml.g4dn.4xlarge"
	ProcessingInstanceTypeMlG4dn8xlarge  ProcessingInstanceType = "ml.g4dn.8xlarge"
	ProcessingInstanceTypeMlG4dn12xlarge ProcessingInstanceType = "ml.g4dn.12xlarge"
	ProcessingInstanceTypeMlG4dn16xlarge ProcessingInstanceType = "ml.g4dn.16xlarge"
)

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

	// List of input configurations for the processing job.
	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

	// Configuration for uploading output from the processing container.
	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

	// Configures conditions under which the processing job should be stopped, such as
	// how long the processing job has been running. After the condition is met, the
	// processing job is stopped.
	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 Amazon Web Services Billing and Cost Management User Guide.
	Tags []Tag

	// The ARN of the training job associated with this processing job.
	TrainingJobArn *string
	// contains filtered or unexported fields
}

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 ProcessingJobStepMetadata added in v0.31.0 

type ProcessingJobStepMetadata struct {

	// The Amazon Resource Name (ARN) of the processing job.
	Arn *string
	// contains filtered or unexported fields
}

Metadata for a processing job step.

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
	// contains filtered or unexported fields
}

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

	// When True, output operations such as data upload are managed natively by the
	// processing job application. When False (default), output operations are managed
	// by Amazon SageMaker.
	AppManaged bool

	// Configuration for processing job outputs in Amazon SageMaker Feature Store. This
	// processing output type is only supported when AppManaged is specified.
	FeatureStoreOutput *ProcessingFeatureStoreOutput

	// Configuration for processing job outputs in Amazon S3.
	S3Output *ProcessingS3Output
	// contains filtered or unexported fields
}

Describes the results of a processing job. The processing output must specify exactly one of either S3Output or FeatureStoreOutput types.

type ProcessingOutputConfig 

type ProcessingOutputConfig struct {

	// An array of outputs configuring the data to upload from the processing
	// container.
	//
	// This member is required.
	Outputs []ProcessingOutput

	// The Amazon Web Services Key Management Service (Amazon Web Services 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
	// contains filtered or unexported fields
}

Configuration for uploading output from the processing container.

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
	// contains filtered or unexported fields
}

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 {

	// 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

	// The URI of the Amazon S3 prefix Amazon SageMaker downloads data required to run
	// a processing job.
	//
	// This member is required.
	S3Uri *string

	// The local path in your container where you want Amazon SageMaker to write input
	// data to. LocalPath is an absolute path to the input data and must begin with
	// /opt/ml/processing/. LocalPath is a required parameter when AppManaged is False
	// (default).
	LocalPath *string

	// Whether to GZIP-decompress the data in Amazon S3 as it is streamed into the
	// processing container. Gzip can only be used when Pipe mode is specified as the
	// S3InputMode. In Pipe mode, Amazon SageMaker streams input data from the source
	// directly to your container without using the EBS volume.
	S3CompressionType ProcessingS3CompressionType

	// Whether to distribute the data from Amazon S3 to all processing instances with
	// FullyReplicated, or whether the data from Amazon S3 is shared by Amazon S3 key,
	// downloading one shard of data to each processing instance.
	S3DataDistributionType ProcessingS3DataDistributionType

	// Whether to use File or Pipe input mode. In File mode, Amazon SageMaker copies
	// the data from the input source onto the local ML storage volume before starting
	// your processing container. This is the most commonly used input mode. In Pipe
	// mode, Amazon SageMaker streams input data from the source directly to your
	// processing container into named pipes without using the ML storage volume.
	S3InputMode ProcessingS3InputMode
	// contains filtered or unexported fields
}

Configuration for downloading input data from Amazon S3 into the processing container.

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 of a directory where you want Amazon SageMaker to upload its
	// contents to Amazon S3. LocalPath is an absolute path to a directory containing
	// output files. This directory will be created by the platform and exist when your
	// container's entrypoint is invoked.
	//
	// 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
	// contains filtered or unexported fields
}

Configuration for uploading output data to Amazon S3 from the processing container.

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
	// contains filtered or unexported fields
}

Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.

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

	// Specifies configuration for a core dump from the model container when the
	// process crashes.
	CoreDumpConfig *ProductionVariantCoreDumpConfig

	// 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
	// contains filtered or unexported fields
}

Identifies a model that you want to host and the resources chosen 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 ProductionVariantCoreDumpConfig added in v1.2.0 

type ProductionVariantCoreDumpConfig struct {

	// The Amazon S3 bucket to send the core dump to.
	//
	// This member is required.
	DestinationS3Uri *string

	// The Amazon Web Services Key Management Service (Amazon Web Services KMS) key
	// that Amazon SageMaker uses to encrypt the core dump data 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 KMS 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 CreateEndpoint and
	// UpdateEndpoint requests. For more information, see Using Key Policies in Amazon
	// Web Services KMS
	// (https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html) in the
	// Amazon Web Services Key Management Service Developer Guide.
	KmsKeyId *string
	// contains filtered or unexported fields
}

Specifies configuration for a core dump from the model container when the process crashes.

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 ProductionVariantStatus added in v1.19.0 

type ProductionVariantStatus struct {

	// The endpoint variant status which describes the current deployment stage status
	// or operational status.
	//
	// * Creating: Creating inference resources for the
	// production variant.
	//
	// * Deleting: Terminating inference resources for the
	// production variant.
	//
	// * Updating: Updating capacity for the production
	// variant.
	//
	// * ActivatingTraffic: Turning on traffic for the production variant.
	//
	// *
	// Baking: Waiting period to monitor the CloudWatch alarms in the automatic
	// rollback configuration.
	//
	// This member is required.
	Status VariantStatus

	// The start time of the current status change.
	StartTime *time.Time

	// A message that describes the status of the production variant.
	StatusMessage *string
	// contains filtered or unexported fields
}

Describes the status of the production variant.

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

	// The endpoint variant status which describes the current deployment stage status
	// or operational status.
	VariantStatus []ProductionVariantStatus
	// contains filtered or unexported fields
}

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 ProfilerConfig added in v0.31.0 

type ProfilerConfig struct {

	// Path to Amazon S3 storage location for system and framework metrics.
	//
	// This member is required.
	S3OutputPath *string

	// A time interval for capturing system metrics in milliseconds. Available values
	// are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute)
	// milliseconds. The default value is 500 milliseconds.
	ProfilingIntervalInMilliseconds *int64

	// Configuration information for capturing framework metrics. Available key strings
	// for different profiling options are DetailedProfilingConfig,
	// PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are
	// configuration structures for the ProfilingParameters parameter. To learn more
	// about how to configure the ProfilingParameters parameter, see Use the SageMaker
	// and Debugger Configuration API Operations to Create, Update, and Debug Your
	// Training Job
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html).
	ProfilingParameters map[string]string
	// contains filtered or unexported fields
}

Configuration information for Debugger system monitoring, framework profiling, and storage paths.

type ProfilerConfigForUpdate added in v0.31.0 

type ProfilerConfigForUpdate struct {

	// To disable Debugger monitoring and profiling, set to True.
	DisableProfiler bool

	// A time interval for capturing system metrics in milliseconds. Available values
	// are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute)
	// milliseconds. The default value is 500 milliseconds.
	ProfilingIntervalInMilliseconds *int64

	// Configuration information for capturing framework metrics. Available key strings
	// for different profiling options are DetailedProfilingConfig,
	// PythonProfilingConfig, and DataLoaderProfilingConfig. The following codes are
	// configuration structures for the ProfilingParameters parameter. To learn more
	// about how to configure the ProfilingParameters parameter, see Use the SageMaker
	// and Debugger Configuration API Operations to Create, Update, and Debug Your
	// Training Job
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html).
	ProfilingParameters map[string]string

	// Path to Amazon S3 storage location for system and framework metrics.
	S3OutputPath *string
	// contains filtered or unexported fields
}

Configuration information for updating the Debugger profile parameters, system and framework metrics configurations, and storage paths.

type ProfilerRuleConfiguration added in v0.31.0 

type ProfilerRuleConfiguration 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 a Debugger custom rule for profiling 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
	// contains filtered or unexported fields
}

Configuration information for profiling rules.

type ProfilerRuleEvaluationStatus added in v0.31.0 

type ProfilerRuleEvaluationStatus 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
	// contains filtered or unexported fields
}

Information about the status of the rule evaluation.

type ProfilingStatus added in v0.31.0 

type ProfilingStatus string
const (
	ProfilingStatusEnabled  ProfilingStatus = "Enabled"
	ProfilingStatusDisabled ProfilingStatus = "Disabled"
)

Enum values for ProfilingStatus

func (ProfilingStatus) Values added in v0.31.0 

func (ProfilingStatus) Values() []ProfilingStatus

Values returns all known values for ProfilingStatus. 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 Project added in v1.15.0 

type Project struct {

	// Who created the project.
	CreatedBy *UserContext

	// A timestamp specifying when the project was created.
	CreationTime *time.Time

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

	// A timestamp container for when the project was last modified.
	LastModifiedTime *time.Time

	// The Amazon Resource Name (ARN) of the project.
	ProjectArn *string

	// The description of the project.
	ProjectDescription *string

	// The ID of the project.
	ProjectId *string

	// The name of the project.
	ProjectName *string

	// The status of the project.
	ProjectStatus ProjectStatus

	// Details of a provisioned service catalog product. For information about service
	// catalog, see What is Amazon Web Services Service Catalog
	// (https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html).
	ServiceCatalogProvisionedProductDetails *ServiceCatalogProvisionedProductDetails

	// Details that you specify to provision a service catalog product. For information
	// about service catalog, see What is Amazon Web Services Service Catalog
	// (https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html).
	ServiceCatalogProvisioningDetails *ServiceCatalogProvisioningDetails

	// An array of key-value pairs. You can use tags to categorize your Amazon Web
	// Services resources in different ways, for example, by purpose, owner, or
	// environment. For more information, see Tagging Amazon Web Services Resources
	// (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html).
	Tags []Tag
	// contains filtered or unexported fields
}

The properties of a project as returned by the Search API.

type ProjectSortBy added in v0.31.0 

type ProjectSortBy string
const (
	ProjectSortByName         ProjectSortBy = "Name"
	ProjectSortByCreationTime ProjectSortBy = "CreationTime"
)

Enum values for ProjectSortBy

func (ProjectSortBy) Values added in v0.31.0 

func (ProjectSortBy) Values() []ProjectSortBy

Values returns all known values for ProjectSortBy. 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 ProjectSortOrder added in v0.31.0 

type ProjectSortOrder string
const (
	ProjectSortOrderAscending  ProjectSortOrder = "Ascending"
	ProjectSortOrderDescending ProjectSortOrder = "Descending"
)

Enum values for ProjectSortOrder

func (ProjectSortOrder) Values added in v0.31.0 

func (ProjectSortOrder) Values() []ProjectSortOrder

Values returns all known values for ProjectSortOrder. 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 ProjectStatus added in v0.31.0 

type ProjectStatus string
const (
	ProjectStatusPending          ProjectStatus = "Pending"
	ProjectStatusCreateInProgress ProjectStatus = "CreateInProgress"
	ProjectStatusCreateCompleted  ProjectStatus = "CreateCompleted"
	ProjectStatusCreateFailed     ProjectStatus = "CreateFailed"
	ProjectStatusDeleteInProgress ProjectStatus = "DeleteInProgress"
	ProjectStatusDeleteFailed     ProjectStatus = "DeleteFailed"
	ProjectStatusDeleteCompleted  ProjectStatus = "DeleteCompleted"
	ProjectStatusUpdateInProgress ProjectStatus = "UpdateInProgress"
	ProjectStatusUpdateCompleted  ProjectStatus = "UpdateCompleted"
	ProjectStatusUpdateFailed     ProjectStatus = "UpdateFailed"
)

Enum values for ProjectStatus

func (ProjectStatus) Values added in v0.31.0 

func (ProjectStatus) Values() []ProjectStatus

Values returns all known values for ProjectStatus. 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 ProjectSummary added in v0.31.0 

type ProjectSummary struct {

	// The time that the project was created.
	//
	// This member is required.
	CreationTime *time.Time

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

	// The ID of the project.
	//
	// This member is required.
	ProjectId *string

	// The name of the project.
	//
	// This member is required.
	ProjectName *string

	// The status of the project.
	//
	// This member is required.
	ProjectStatus ProjectStatus

	// The description of the project.
	ProjectDescription *string
	// contains filtered or unexported fields
}

Information about a project.

type PropertyNameQuery 

type PropertyNameQuery struct {

	// Text that begins a property's name.
	//
	// This member is required.
	PropertyNameHint *string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

A property name returned from a GetSearchSuggestions call that specifies a value in the PropertyNameQuery field.

type ProvisioningParameter added in v0.31.0 

type ProvisioningParameter struct {

	// The key that identifies a provisioning parameter.
	Key *string

	// The value of the provisioning parameter.
	Value *string
	// contains filtered or unexported fields
}

A key value pair used when you provision a project as a service catalog product. For information, see What is Amazon Web Services Service Catalog (https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html).

type PublicWorkforceTaskPrice 

type PublicWorkforceTaskPrice struct {

	// Defines the amount of money paid to an Amazon Mechanical Turk worker in United
	// States dollars.
	AmountInUsd *USD
	// contains filtered or unexported fields
}

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 RSessionAppSettings added in v1.18.0 

type RSessionAppSettings struct {
	// contains filtered or unexported fields
}

A collection of settings that apply to an RSessionGateway app.

type RStudioServerProAccessStatus added in v1.18.0 

type RStudioServerProAccessStatus string
const (
	RStudioServerProAccessStatusEnabled  RStudioServerProAccessStatus = "ENABLED"
	RStudioServerProAccessStatusDisabled RStudioServerProAccessStatus = "DISABLED"
)

Enum values for RStudioServerProAccessStatus

func (RStudioServerProAccessStatus) Values added in v1.18.0 

func (RStudioServerProAccessStatus) Values() []RStudioServerProAccessStatus

Values returns all known values for RStudioServerProAccessStatus. 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 RStudioServerProAppSettings added in v1.18.0 

type RStudioServerProAppSettings struct {

	// Indicates whether the current user has access to the RStudioServerPro app.
	AccessStatus RStudioServerProAccessStatus

	// The level of permissions that the user has within the RStudioServerPro app. This
	// value defaults to `User`. The `Admin` value allows the user access to the
	// RStudio Administrative Dashboard.
	UserGroup RStudioServerProUserGroup
	// contains filtered or unexported fields
}

A collection of settings that configure user interaction with the RStudioServerPro app. RStudioServerProAppSettings cannot be updated. The RStudioServerPro app must be deleted and a new one created to make any changes.

type RStudioServerProDomainSettings added in v1.18.0 

type RStudioServerProDomainSettings struct {

	// The ARN of the execution role for the RStudioServerPro Domain-level app.
	//
	// This member is required.
	DomainExecutionRoleArn *string

	// Specifies the ARN's of a SageMaker image and SageMaker image version, and the
	// instance type that the version runs on.
	DefaultResourceSpec *ResourceSpec

	// A URL pointing to an RStudio Connect server.
	RStudioConnectUrl *string

	// A URL pointing to an RStudio Package Manager server.
	RStudioPackageManagerUrl *string
	// contains filtered or unexported fields
}

A collection of settings that configure the RStudioServerPro Domain-level app.

type RStudioServerProDomainSettingsForUpdate added in v1.18.0 

type RStudioServerProDomainSettingsForUpdate struct {

	// The execution role for the RStudioServerPro Domain-level app.
	//
	// This member is required.
	DomainExecutionRoleArn *string

	// Specifies the ARN's of a SageMaker image and SageMaker image version, and the
	// instance type that the version runs on.
	DefaultResourceSpec *ResourceSpec
	// contains filtered or unexported fields
}

A collection of settings that update the current configuration for the RStudioServerPro Domain-level app.

type RStudioServerProUserGroup added in v1.18.0 

type RStudioServerProUserGroup string
const (
	RStudioServerProUserGroupAdmin RStudioServerProUserGroup = "R_STUDIO_ADMIN"
	RStudioServerProUserGroupUser  RStudioServerProUserGroup = "R_STUDIO_USER"
)

Enum values for RStudioServerProUserGroup

func (RStudioServerProUserGroup) Values added in v1.18.0 

func (RStudioServerProUserGroup) Values() []RStudioServerProUserGroup

Values returns all known values for RStudioServerProUserGroup. 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 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 RedshiftDatasetDefinition added in v0.31.0 

type RedshiftDatasetDefinition struct {

	// The Redshift cluster Identifier.
	//
	// This member is required.
	ClusterId *string

	// The IAM role attached to your Redshift cluster that Amazon SageMaker uses to
	// generate datasets.
	//
	// This member is required.
	ClusterRoleArn *string

	// The name of the Redshift database used in Redshift query execution.
	//
	// This member is required.
	Database *string

	// The database user name used in Redshift query execution.
	//
	// This member is required.
	DbUser *string

	// The data storage format for Redshift query results.
	//
	// This member is required.
	OutputFormat RedshiftResultFormat

	// The location in Amazon S3 where the Redshift query results are stored.
	//
	// This member is required.
	OutputS3Uri *string

	// The SQL query statements to be executed.
	//
	// This member is required.
	QueryString *string

	// The Amazon Web Services Key Management Service (Amazon Web Services KMS) key
	// that Amazon SageMaker uses to encrypt data from a Redshift execution.
	KmsKeyId *string

	// The compression used for Redshift query results.
	OutputCompression RedshiftResultCompressionType
	// contains filtered or unexported fields
}

Configuration for Redshift Dataset Definition input.

type RedshiftResultCompressionType added in v0.31.0 

type RedshiftResultCompressionType string
const (
	RedshiftResultCompressionTypeNone   RedshiftResultCompressionType = "None"
	RedshiftResultCompressionTypeGzip   RedshiftResultCompressionType = "GZIP"
	RedshiftResultCompressionTypeBzip2  RedshiftResultCompressionType = "BZIP2"
	RedshiftResultCompressionTypeZstd   RedshiftResultCompressionType = "ZSTD"
	RedshiftResultCompressionTypeSnappy RedshiftResultCompressionType = "SNAPPY"
)

Enum values for RedshiftResultCompressionType

func (RedshiftResultCompressionType) Values added in v0.31.0 

func (RedshiftResultCompressionType) Values() []RedshiftResultCompressionType

Values returns all known values for RedshiftResultCompressionType. 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 RedshiftResultFormat added in v0.31.0 

type RedshiftResultFormat string
const (
	RedshiftResultFormatParquet RedshiftResultFormat = "PARQUET"
	RedshiftResultFormatCsv     RedshiftResultFormat = "CSV"
)

Enum values for RedshiftResultFormat

func (RedshiftResultFormat) Values added in v0.31.0 

func (RedshiftResultFormat) Values() []RedshiftResultFormat

Values returns all known values for RedshiftResultFormat. 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 RegisterModelStepMetadata added in v0.31.0 

type RegisterModelStepMetadata struct {

	// The Amazon Resource Name (ARN) of the model package.
	Arn *string
	// contains filtered or unexported fields
}

Metadata for a register model job step.

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 filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 RepositoryAuthConfig added in v1.3.0 

type RepositoryAuthConfig struct {

	// The Amazon Resource Name (ARN) of an Amazon Web Services Lambda function that
	// provides credentials to authenticate to the private Docker registry where your
	// model image is hosted. For information about how to create an Amazon Web
	// Services Lambda function, see Create a Lambda function with the console
	// (https://docs.aws.amazon.com/lambda/latest/dg/getting-started-create-function.html)
	// in the Amazon Web Services Lambda Developer Guide.
	//
	// This member is required.
	RepositoryCredentialsProviderArn *string
	// contains filtered or unexported fields
}

Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified Vpc as the value for the RepositoryAccessMode field of the ImageConfig object that you passed to a call to CreateModel and the private Docker registry where the model image is hosted requires authentication.

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
	// contains filtered or unexported fields
}

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 Amazon Web Services 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
	// contains filtered or unexported fields
}

Describes the resources, including ML compute instances and ML storage volumes, to use for model training.

type ResourceInUse 

type ResourceInUse struct {
	Message *string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the
	// Resource.
	LifecycleConfigArn *string

	// 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
	// contains filtered or unexported fields
}

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"
	ResourceTypeEndpoint                 ResourceType = "Endpoint"
	ResourceTypeModelPackage             ResourceType = "ModelPackage"
	ResourceTypeModelPackageGroup        ResourceType = "ModelPackageGroup"
	ResourceTypePipeline                 ResourceType = "Pipeline"
	ResourceTypePipelineExecution        ResourceType = "PipelineExecution"
	ResourceTypeFeatureGroup             ResourceType = "FeatureGroup"
	ResourceTypeProject                  ResourceType = "Project"
)

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
	// contains filtered or unexported fields
}

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 RetryStrategy added in v1.4.0 

type RetryStrategy struct {

	// The number of times to retry the job. When the job is retried, it's
	// SecondaryStatus is changed to STARTING.
	//
	// This member is required.
	MaximumRetryAttempts int32
	// contains filtered or unexported fields
}

The retry strategy to use when a training job fails due to an InternalServerError. RetryStrategy is specified as part of the CreateTrainingJob and CreateHyperParameterTuningJob requests. You can add the StoppingCondition parameter to the request to limit the training time for the complete job.

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
	// contains filtered or unexported fields
}

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 S3StorageConfig added in v0.31.0 

type S3StorageConfig struct {

	// The S3 URI, or location in Amazon S3, of OfflineStore. S3 URIs have a format
	// similar to the following: s3://example-bucket/prefix/.
	//
	// This member is required.
	S3Uri *string

	// The Amazon Web Services Key Management Service (KMS) key ID of the key used to
	// encrypt any objects written into the OfflineStore S3 location. The IAM roleARN
	// that is passed as a parameter to CreateFeatureGroup must have below permissions
	// to the KmsKeyId:
	//
	// * "kms:GenerateDataKey"
	KmsKeyId *string

	// The S3 path where offline records are written.
	ResolvedOutputS3Uri *string
	// contains filtered or unexported fields
}

The Amazon Simple Storage (Amazon S3) location and and security configuration for OfflineStore.

type SagemakerServicecatalogStatus added in v0.31.0 

type SagemakerServicecatalogStatus string
const (
	SagemakerServicecatalogStatusEnabled  SagemakerServicecatalogStatus = "Enabled"
	SagemakerServicecatalogStatusDisabled SagemakerServicecatalogStatus = "Disabled"
)

Enum values for SagemakerServicecatalogStatus

func (SagemakerServicecatalogStatus) Values added in v0.31.0 

func (SagemakerServicecatalogStatus) Values() []SagemakerServicecatalogStatus

Values returns all known values for SagemakerServicecatalogStatus. 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 {

	// A hosted endpoint for real-time inference.
	Endpoint *Endpoint

	// The properties of an experiment.
	Experiment *Experiment

	// Amazon SageMaker Feature Store stores features in a collection called Feature
	// Group. A Feature Group can be visualized as a table which has rows, with a
	// unique identifier for each row where each column in the table is a feature. In
	// principle, a Feature Group is composed of features and values per features.
	FeatureGroup *FeatureGroup

	// A versioned model that can be deployed for SageMaker inference.
	ModelPackage *ModelPackage

	// A group of versioned models in the model registry.
	ModelPackageGroup *ModelPackageGroup

	// A SageMaker Model Building Pipeline instance.
	Pipeline *Pipeline

	// An execution of a pipeline.
	PipelineExecution *PipelineExecution

	// The properties of a project.
	Project *Project

	// The properties of a training job.
	TrainingJob *TrainingJob

	// The properties of a trial.
	Trial *Trial

	// The properties of a trial component.
	TrialComponent *TrialComponent
	// contains filtered or unexported fields
}

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"
	SecondaryStatusUpdating                 SecondaryStatus = "Updating"
	SecondaryStatusRestarting               SecondaryStatus = "Restarting"
)

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
	// contains filtered or unexported fields
}

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 ServiceCatalogProvisionedProductDetails added in v0.31.0 

type ServiceCatalogProvisionedProductDetails struct {

	// The ID of the provisioned product.
	ProvisionedProductId *string

	// The current status of the product.
	//
	// * AVAILABLE - Stable state, ready to perform
	// any operation. The most recent operation succeeded and completed.
	//
	// *
	// UNDER_CHANGE - Transitive state. Operations performed might not have valid
	// results. Wait for an AVAILABLE status before performing operations.
	//
	// * TAINTED -
	// Stable state, ready to perform any operation. The stack has completed the
	// requested operation but is not exactly what was requested. For example, a
	// request to update to a new version failed and the stack rolled back to the
	// current version.
	//
	// * ERROR - An unexpected error occurred. The provisioned
	// product exists but the stack is not running. For example, CloudFormation
	// received a parameter value that was not valid and could not launch the stack.
	//
	// *
	// PLAN_IN_PROGRESS - Transitive state. The plan operations were performed to
	// provision a new product, but resources have not yet been created. After
	// reviewing the list of resources to be created, execute the plan. Wait for an
	// AVAILABLE status before performing operations.
	ProvisionedProductStatusMessage *string
	// contains filtered or unexported fields
}

Details of a provisioned service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog (https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html).

type ServiceCatalogProvisioningDetails added in v0.31.0 

type ServiceCatalogProvisioningDetails struct {

	// The ID of the product to provision.
	//
	// This member is required.
	ProductId *string

	// The path identifier of the product. This value is optional if the product has a
	// default path, and required if the product has more than one path.
	PathId *string

	// The ID of the provisioning artifact.
	ProvisioningArtifactId *string

	// A list of key value pairs that you specify when you provision a product.
	ProvisioningParameters []ProvisioningParameter
	// contains filtered or unexported fields
}

Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog (https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html).

type ServiceCatalogProvisioningUpdateDetails added in v1.18.0 

type ServiceCatalogProvisioningUpdateDetails struct {

	// The ID of the provisioning artifact.
	ProvisioningArtifactId *string

	// A list of key value pairs that you specify when you provision a product.
	ProvisioningParameters []ProvisioningParameter
	// contains filtered or unexported fields
}

Details that you specify to provision a service catalog product. For information about service catalog, see What is Amazon Web Services Service Catalog (https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html).

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 Amazon Web Services 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 store the
	// shared notebook snapshots.
	S3OutputPath *string
	// contains filtered or unexported fields
}

Specifies options for sharing SageMaker Studio notebooks. 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. When SharingSettings is not specified, notebook sharing isn't allowed.

type ShuffleConfig 

type ShuffleConfig struct {

	// Determines the shuffling order in ShuffleConfig value.
	//
	// This member is required.
	Seed int64
	// contains filtered or unexported fields
}

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 SortActionsBy added in v0.31.0 

type SortActionsBy string
const (
	SortActionsByName         SortActionsBy = "Name"
	SortActionsByCreationTime SortActionsBy = "CreationTime"
)

Enum values for SortActionsBy

func (SortActionsBy) Values added in v0.31.0 

func (SortActionsBy) Values() []SortActionsBy

Values returns all known values for SortActionsBy. 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 SortArtifactsBy added in v0.31.0 

type SortArtifactsBy string
const (
	SortArtifactsByCreationTime SortArtifactsBy = "CreationTime"
)

Enum values for SortArtifactsBy

func (SortArtifactsBy) Values added in v0.31.0 

func (SortArtifactsBy) Values() []SortArtifactsBy

Values returns all known values for SortArtifactsBy. 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 SortAssociationsBy added in v0.31.0 

type SortAssociationsBy string
const (
	SortAssociationsBySourceArn       SortAssociationsBy = "SourceArn"
	SortAssociationsByDestinationArn  SortAssociationsBy = "DestinationArn"
	SortAssociationsBySourceType      SortAssociationsBy = "SourceType"
	SortAssociationsByDestinationType SortAssociationsBy = "DestinationType"
	SortAssociationsByCreationTime    SortAssociationsBy = "CreationTime"
)

Enum values for SortAssociationsBy

func (SortAssociationsBy) Values added in v0.31.0 

func (SortAssociationsBy) Values() []SortAssociationsBy

Values returns all known values for SortAssociationsBy. 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 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 SortContextsBy added in v0.31.0 

type SortContextsBy string
const (
	SortContextsByName         SortContextsBy = "Name"
	SortContextsByCreationTime SortContextsBy = "CreationTime"
)

Enum values for SortContextsBy

func (SortContextsBy) Values added in v0.31.0 

func (SortContextsBy) Values() []SortContextsBy

Values returns all known values for SortContextsBy. 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 SortPipelineExecutionsBy added in v0.31.0 

type SortPipelineExecutionsBy string
const (
	SortPipelineExecutionsByCreationTime         SortPipelineExecutionsBy = "CreationTime"
	SortPipelineExecutionsByPipelineExecutionArn SortPipelineExecutionsBy = "PipelineExecutionArn"
)

Enum values for SortPipelineExecutionsBy

func (SortPipelineExecutionsBy) Values added in v0.31.0 

func (SortPipelineExecutionsBy) Values() []SortPipelineExecutionsBy

Values returns all known values for SortPipelineExecutionsBy. 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 SortPipelinesBy added in v0.31.0 

type SortPipelinesBy string
const (
	SortPipelinesByName         SortPipelinesBy = "Name"
	SortPipelinesByCreationTime SortPipelinesBy = "CreationTime"
)

Enum values for SortPipelinesBy

func (SortPipelinesBy) Values added in v0.31.0 

func (SortPipelinesBy) Values() []SortPipelinesBy

Values returns all known values for SortPipelinesBy. 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 Amazon Web Services 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
	// contains filtered or unexported fields
}

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 Amazon Web Services 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 StepStatus added in v0.31.0 

type StepStatus string
const (
	StepStatusStarting  StepStatus = "Starting"
	StepStatusExecuting StepStatus = "Executing"
	StepStatusStopping  StepStatus = "Stopping"
	StepStatusStopped   StepStatus = "Stopped"
	StepStatusFailed    StepStatus = "Failed"
	StepStatusSucceeded StepStatus = "Succeeded"
)

Enum values for StepStatus

func (StepStatus) Values added in v0.31.0 

func (StepStatus) Values() []StepStatus

Values returns all known values for StepStatus. 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 a training or compilation job can
	// run. For compilation jobs, if the job does not complete during this time, you
	// will receive a TimeOut error. We recommend starting with 900 seconds and
	// increase as necessary based on your model. For all other jobs, if the job does
	// not complete during this time, Amazon SageMaker ends the job. When RetryStrategy
	// is specified in the job request, MaxRuntimeInSeconds specifies the maximum time
	// for all of the attempts in total, not each individual attempt. The default value
	// is 1 day. The maximum value is 28 days.
	MaxRuntimeInSeconds int32

	// The maximum length of time, in seconds, that a managed Spot training job has to
	// complete. It is the amount of time spent waiting for Spot capacity plus the
	// amount of time the job can run. It must be equal to or greater than
	// MaxRuntimeInSeconds. If the job does not complete during this time, Amazon
	// SageMaker ends the job. When RetryStrategy is specified in the job request,
	// MaxWaitTimeInSeconds specifies the maximum time for all of the attempts in
	// total, not each individual attempt.
	MaxWaitTimeInSeconds *int32
	// contains filtered or unexported fields
}

Specifies a limit to how long a model training job or model compilation job can run. It also specifies how long a managed spot training job has 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 training 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 StudioLifecycleConfigAppType added in v1.15.0 

type StudioLifecycleConfigAppType string
const (
	StudioLifecycleConfigAppTypeJupyterServer StudioLifecycleConfigAppType = "JupyterServer"
	StudioLifecycleConfigAppTypeKernelGateway StudioLifecycleConfigAppType = "KernelGateway"
)

Enum values for StudioLifecycleConfigAppType

func (StudioLifecycleConfigAppType) Values added in v1.15.0 

func (StudioLifecycleConfigAppType) Values() []StudioLifecycleConfigAppType

Values returns all known values for StudioLifecycleConfigAppType. 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 StudioLifecycleConfigDetails added in v1.15.0 

type StudioLifecycleConfigDetails struct {

	// The creation time of the Studio Lifecycle Configuration.
	CreationTime *time.Time

	// This value is equivalent to CreationTime because Studio Lifecycle Configurations
	// are immutable.
	LastModifiedTime *time.Time

	// The App type to which the Lifecycle Configuration is attached.
	StudioLifecycleConfigAppType StudioLifecycleConfigAppType

	// The Amazon Resource Name (ARN) of the Lifecycle Configuration.
	StudioLifecycleConfigArn *string

	// The name of the Studio Lifecycle Configuration.
	StudioLifecycleConfigName *string
	// contains filtered or unexported fields
}

Details of the Studio Lifecycle Configuration.

type StudioLifecycleConfigSortKey added in v1.15.0 

type StudioLifecycleConfigSortKey string
const (
	StudioLifecycleConfigSortKeyCreationTime     StudioLifecycleConfigSortKey = "CreationTime"
	StudioLifecycleConfigSortKeyLastModifiedTime StudioLifecycleConfigSortKey = "LastModifiedTime"
	StudioLifecycleConfigSortKeyName             StudioLifecycleConfigSortKey = "Name"
)

Enum values for StudioLifecycleConfigSortKey

func (StudioLifecycleConfigSortKey) Values added in v1.15.0 

func (StudioLifecycleConfigSortKey) Values() []StudioLifecycleConfigSortKey

Values returns all known values for StudioLifecycleConfigSortKey. 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 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.

type Tag 

type Tag struct {

	// The tag key. Tag keys must be unique per resource.
	//
	// This member is required.
	Key *string

	// The tag value.
	//
	// This member is required.
	Value *string
	// contains filtered or unexported fields
}

A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags. For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html). For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy (https://d1.awsstatic.com/whitepapers/aws-tagging-best-practices.pdf).

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"
	TargetDeviceMlEia2        TargetDevice = "ml_eia2"
	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"
	TargetDeviceAmbaCv25      TargetDevice = "amba_cv25"
	TargetDeviceX86Win32      TargetDevice = "x86_win32"
	TargetDeviceX86Win64      TargetDevice = "x86_win64"
	TargetDeviceCoreml        TargetDevice = "coreml"
	TargetDeviceJacintoTda4vm TargetDevice = "jacinto_tda4vm"
	TargetDeviceImx8mplus     TargetDevice = "imx8mplus"
)

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 filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Configuration of storage locations for the Debugger TensorBoard output data.

type TrafficRoutingConfig added in v0.31.0 

type TrafficRoutingConfig struct {

	// Traffic routing strategy type.
	//
	// * ALL_AT_ONCE: Endpoint traffic shifts to the
	// new fleet in a single step.
	//
	// * CANARY: Endpoint traffic shifts to the new fleet
	// in two steps. The first step is the canary, which is a small portion of the
	// traffic. The second step is the remainder of the traffic.
	//
	// * LINEAR: Endpoint
	// traffic shifts to the new fleet in n steps of a configurable size.
	//
	// This member is required.
	Type TrafficRoutingConfigType

	// The waiting time (in seconds) between incremental steps to turn on traffic on
	// the new endpoint fleet.
	//
	// This member is required.
	WaitIntervalInSeconds *int32

	// Batch size for the first step to turn on traffic on the new endpoint fleet.
	// Value must be less than or equal to 50% of the variant's total instance count.
	CanarySize *CapacitySize

	// Batch size for each step to turn on traffic on the new endpoint fleet. Value
	// must be 10-50% of the variant's total instance count.
	LinearStepSize *CapacitySize
	// contains filtered or unexported fields
}

Defines the traffic routing strategy during an endpoint deployment to shift traffic from the old fleet to the new fleet.

type TrafficRoutingConfigType added in v0.31.0 

type TrafficRoutingConfigType string
const (
	TrafficRoutingConfigTypeAllAtOnce TrafficRoutingConfigType = "ALL_AT_ONCE"
	TrafficRoutingConfigTypeCanary    TrafficRoutingConfigType = "CANARY"
	TrafficRoutingConfigTypeLinear    TrafficRoutingConfigType = "LINEAR"
)

Enum values for TrafficRoutingConfigType

func (TrafficRoutingConfigType) Values added in v0.31.0 

func (TrafficRoutingConfigType) Values() []TrafficRoutingConfigType

Values returns all known values for TrafficRoutingConfigType. 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 TrainingInputMode 

type TrainingInputMode string
const (
	TrainingInputModePipe     TrainingInputMode = "Pipe"
	TrainingInputModeFile     TrainingInputMode = "File"
	TrainingInputModeFastfile TrainingInputMode = "FastFile"
)

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 Debugger hook parameters, metric and tensor
	// collections, and storage paths. To learn more about how to configure the
	// DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API
	// Operations to Create, Update, and Debug Your Training Job
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html).
	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

	// The environment variables to set in the Docker container.
	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 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 number of times to retry the job when the job fails due to an
	// InternalServerError.
	RetryStrategy *RetryStrategy

	// The Amazon Web Services 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. It also specifies
	// how long a managed Spot training job has to complete. 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. You can use tags to categorize your Amazon Web
	// Services resources in different ways, for example, by purpose, owner, or
	// environment. For more information, see Tagging Amazon Web Services Resources
	// (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html).
	Tags []Tag

	// Configuration of storage locations for the Debugger TensorBoard output data.
	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 filtered or unexported fields
}

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. It also specifies
	// how long a managed Spot training job has to complete. 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 training input mode that the algorithm supports. For more information about
	// input modes, see Algorithms
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html). Pipe mode If an
	// algorithm supports Pipe mode, Amazon SageMaker streams data directly from Amazon
	// S3 to the container. File mode If an algorithm supports File mode, SageMaker
	// downloads the training data from S3 to the provisioned ML storage volume, and
	// mounts the directory to the Docker volume for the training container. You must
	// provision the ML storage volume with sufficient capacity to accommodate the data
	// downloaded from S3. In addition to the training data, the ML storage volume also
	// stores the output model. The algorithm container uses the ML storage volume to
	// also store intermediate information, if any. For distributed algorithms,
	// training data is distributed uniformly. Your training duration is predictable if
	// the input data objects sizes are approximately the same. 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 when one host
	// in a training cluster is overloaded, thus becoming a bottleneck in training.
	// FastFile mode If an algorithm supports FastFile mode, SageMaker streams data
	// directly from S3 to the container with no code changes, and provides file system
	// access to the data. Users can author their training script to interact with
	// these files as if they were stored on disk. FastFile mode works best when the
	// data is read sequentially. Augmented manifest files aren't supported. The
	// startup time is lower when there are fewer files in the S3 bucket provided.
	//
	// This member is required.
	TrainingInputMode TrainingInputMode

	// The hyperparameters used for the training job.
	HyperParameters map[string]string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.

type TrainingJobStepMetadata added in v0.31.0 

type TrainingJobStepMetadata struct {

	// The Amazon Resource Name (ARN) of the training job that was run by this step
	// execution.
	Arn *string
	// contains filtered or unexported fields
}

Metadata for a training job step.

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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/data#consuming_tfrecord_data) in
	// the TensorFlow documentation.
	SplitType SplitType
	// contains filtered or unexported fields
}

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"
	TransformInstanceTypeMlG4dnXlarge   TransformInstanceType = "ml.g4dn.xlarge"
	TransformInstanceTypeMlG4dn2xlarge  TransformInstanceType = "ml.g4dn.2xlarge"
	TransformInstanceTypeMlG4dn4xlarge  TransformInstanceType = "ml.g4dn.4xlarge"
	TransformInstanceTypeMlG4dn8xlarge  TransformInstanceType = "ml.g4dn.8xlarge"
	TransformInstanceTypeMlG4dn12xlarge TransformInstanceType = "ml.g4dn.12xlarge"
	TransformInstanceTypeMlG4dn16xlarge TransformInstanceType = "ml.g4dn.16xlarge"
)

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 TransformJobStepMetadata added in v0.31.0 

type TransformJobStepMetadata struct {

	// The Amazon Resource Name (ARN) of the transform job that was run by this step
	// execution.
	Arn *string
	// contains filtered or unexported fields
}

Metadata for a transform job step.

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
	// contains filtered or unexported fields
}

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 Amazon Web Services Key Management Service (Amazon Web Services 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 Amazon Web Services KMS
	// (http://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html) in the
	// Amazon Web Services Key Management Service Developer Guide.
	KmsKeyId *string
	// contains filtered or unexported fields
}

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.largeinstance types.
	//
	// This member is required.
	InstanceType TransformInstanceType

	// The Amazon Web Services Key Management Service (Amazon Web Services 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. 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 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Describes the S3 data source.

type Trial 

type Trial struct {

	// Who created the trial.
	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, trial
	// component, or project.
	LastModifiedBy *UserContext

	// Who last modified the trial.
	LastModifiedTime *time.Time

	// Metadata properties of the tracking entity, trial, or trial component.
	MetadataProperties *MetadataProperties

	// 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
	// contains filtered or unexported fields
}

The properties of a trial as returned by the Search API.

type TrialComponent 

type TrialComponent struct {

	// Who created the 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, trial
	// component, or project.
	LastModifiedBy *UserContext

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

	// Metadata properties of the tracking entity, trial, or trial component.
	MetadataProperties *MetadataProperties

	// 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

A summary of the metrics of a trial component.

type TrialComponentParameterValue 

type TrialComponentParameterValue interface {
	// contains filtered or unexported methods
}

The value of a hyperparameter. Only one of NumberValue or StringValue can be specified. This object is specified in the CreateTrialComponent request.

The following types satisfy this interface: 

TrialComponentParameterValueMemberNumberValue
TrialComponentParameterValueMemberStringValue
Example (OutputUsage) 
// Code generated by smithy-go-codegen DO NOT EDIT.

package main

import (
	"fmt"
	"github.com/aws/aws-sdk-go-v2/service/sagemaker/types"
)

func main() {
	var union types.TrialComponentParameterValue
	// type switches can be used to check the union value
	switch v := union.(type) {
	case *types.TrialComponentParameterValueMemberNumberValue:
		_ = v.Value // Value is float64

	case *types.TrialComponentParameterValueMemberStringValue:
		_ = v.Value // Value is string

	case *types.UnknownUnionMember:
		fmt.Println("unknown tag:", v.Tag)

	default:
		fmt.Println("union is nil or unknown type")

	}
}

var _ *string
var _ *float64

Output:

type TrialComponentParameterValueMemberNumberValue added in v0.31.0 

type TrialComponentParameterValueMemberNumberValue struct {
	Value float64
	// contains filtered or unexported fields
}

The numeric value of a numeric hyperparameter. If you specify a value for this parameter, you can't specify the StringValue parameter.

type TrialComponentParameterValueMemberStringValue added in v0.31.0 

type TrialComponentParameterValueMemberStringValue struct {
	Value string
	// contains filtered or unexported fields
}

The string value of a categorical hyperparameter. If you specify a value for this parameter, you can't specify the NumberValue parameter.

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, trial
	// component, or project.
	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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

The status of the trial component.

type TrialComponentSummary 

type TrialComponentSummary struct {

	// Who created the 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

	// 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

The job completion criteria.

type TuningJobStepMetaData added in v1.10.0 

type TuningJobStepMetaData struct {

	// The Amazon Resource Name (ARN) of the tuning job that was run by this step
	// execution.
	Arn *string
	// contains filtered or unexported fields
}

Metadata for a tuning step.

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
	// contains filtered or unexported fields
}

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
	// named entity recognition, 3D point cloud and video frame labeling jobs. Use your
	// labeling job task type to select one of the following ARNs and use it with this
	// parameter when you create a labeling job. Replace aws-region with the Amazon Web
	// Services Region you are creating your labeling job in. For example, replace
	// aws-region with us-west-1 if you create a labeling job in US West (N.
	// California). Named Entity Recognition Use the following HumanTaskUiArn for named
	// entity recognition labeling jobs:
	// arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition
	// 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
	// contains filtered or unexported fields
}

Provided configuration information for the worker UI for a labeling job. Provide either HumanTaskUiArn or UiTemplateS3Uri. For named entity recognition, 3D point cloud and video frame labeling jobs, use HumanTaskUiArn. For all other Ground Truth built-in task types and custom task types, use UiTemplateS3Uri to specify the location of a worker task template in Amazon S3.

type UiTemplate 

type UiTemplate struct {

	// The content of the Liquid template for the worker user interface.
	//
	// This member is required.
	Content *string
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

Container for user interface template information.

type UnknownUnionMember added in v0.31.0 

type UnknownUnionMember struct {
	Tag   string
	Value []byte
	// contains filtered or unexported fields
}

UnknownUnionMember is returned when a union member is returned over the wire, but has an unknown tag.

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
	// contains filtered or unexported fields
}

Information about the user who created or modified an experiment, trial, trial component, or project.

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
	// contains filtered or unexported fields
}

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

	// A collection of settings that configure the RSessionGateway app.
	RSessionAppSettings *RSessionAppSettings

	// A collection of settings that configure user interaction with the
	// RStudioServerPro app.
	RStudioServerProAppSettings *RStudioServerProAppSettings

	// 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. Amazon SageMaker
	// adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the
	// number of security groups that you can specify is one less than the maximum
	// number shown.
	SecurityGroups []string

	// Specifies options for sharing SageMaker Studio notebooks.
	SharingSettings *SharingSettings

	// The TensorBoard app settings.
	TensorBoardAppSettings *TensorBoardAppSettings
	// contains filtered or unexported fields
}

A collection of settings that apply to users of Amazon SageMaker Studio. These settings are specified when the CreateUserProfile API is called, and as DefaultUserSettings when the CreateDomain API is called. SecurityGroups is aggregated when specified in both calls. For all other settings in UserSettings, the values specified in CreateUserProfile take precedence over those specified in CreateDomain.

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
	// contains filtered or unexported fields
}

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 VariantStatus added in v1.19.0 

type VariantStatus string
const (
	VariantStatusCreating          VariantStatus = "Creating"
	VariantStatusUpdating          VariantStatus = "Updating"
	VariantStatusDeleting          VariantStatus = "Deleting"
	VariantStatusActivatingTraffic VariantStatus = "ActivatingTraffic"
	VariantStatusBaking            VariantStatus = "Baking"
)

Enum values for VariantStatus

func (VariantStatus) Values added in v1.19.0 

func (VariantStatus) Values() []VariantStatus

Values returns all known values for VariantStatus. 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
	// contains filtered or unexported fields
}

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
	// contains filtered or unexported fields
}

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 Amazon Web Services 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
	// contains filtered or unexported fields
}

Provides details about a labeling work team.

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