const ServiceAPIVersion = "2017-07-24"

const ServiceID = "SageMaker"

type AddTagsInput struct {
	// An array of Tag objects. Each tag is a key-value pair. Only the key parameter is
	// required. If you don't specify a value, Amazon SageMaker sets the value to an
	// empty string.
	Tags []*types.Tag
	// The Amazon Resource Name (ARN) of the resource that you want to tag.
	ResourceArn *string
}

type AddTagsOutput struct {
	// A list of tags associated with the Amazon SageMaker resource.
	Tags []*types.Tag

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type AssociateTrialComponentInput struct {
	// The name of the component to associated with the trial.
	TrialComponentName *string
	// The name of the trial to associate with.
	TrialName *string
}

type AssociateTrialComponentOutput struct {
	// The ARN of the trial component.
	TrialComponentArn *string
	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

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

type CreateAlgorithmInput struct {
	// Specifies details about training jobs run by this algorithm, including the
	// following:
	//
	//     * The Amazon ECR path of the container and the version digest of
	// the algorithm.
	//
	//     * The hyperparameters that the algorithm supports.
	//
	//     *
	// The instance types that the algorithm supports for training.
	//
	//     * Whether the
	// algorithm supports distributed training.
	//
	//     * The metrics that the algorithm
	// emits to Amazon CloudWatch.
	//
	//     * Which metrics that the algorithm emits can be
	// used as the objective metric for hyperparameter tuning jobs.
	//
	//     * The input
	// channels that the algorithm supports for training data. For example, an
	// algorithm might support train, validation, and test channels.
	TrainingSpecification *types.TrainingSpecification
	// Specifies details about inference jobs that the algorithm runs, including the
	// following:
	//
	//     * The Amazon ECR paths of containers that contain the inference
	// code and model artifacts.
	//
	//     * The instance types that the algorithm supports
	// for transform jobs and real-time endpoints used for inference.
	//
	//     * The input
	// and output content formats that the algorithm supports for inference.
	InferenceSpecification *types.InferenceSpecification
	// A description of the algorithm.
	AlgorithmDescription *string
	// Whether to certify the algorithm so that it can be listed in AWS Marketplace.
	CertifyForMarketplace *bool
	// The name of the algorithm.
	AlgorithmName *string
	// Specifies configurations for one or more training jobs and that Amazon SageMaker
	// runs to test the algorithm's training code and, optionally, one or more batch
	// transform jobs that Amazon SageMaker runs to test the algorithm's inference
	// code.
	ValidationSpecification *types.AlgorithmValidationSpecification
}

type CreateAlgorithmOutput struct {
	// The Amazon Resource Name (ARN) of the new algorithm.
	AlgorithmArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateAppInput struct {
	// The instance type and the Amazon Resource Name (ARN) of the SageMaker image
	// created on the instance.
	ResourceSpec *types.ResourceSpec
	// The name of the app.
	AppName *string
	// The type of app.
	AppType types.AppType
	// The domain ID.
	DomainId *string
	// The user profile name.
	UserProfileName *string
	// Each tag consists of a key and an optional value. Tag keys must be unique per
	// resource.
	Tags []*types.Tag
}

type CreateAppOutput struct {
	// The App's Amazon Resource Name (ARN).
	AppArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateAutoMLJobInput struct {
	// Identifies an AutoPilot job. Must be unique to your account and is
	// case-insensitive.
	AutoMLJobName *string
	// Defines the job's objective. You provide a MetricName and AutoML will infer
	// minimize or maximize. If this is not provided, the most commonly used
	// ObjectiveMetric for problem type will be selected.
	AutoMLJobObjective *types.AutoMLJobObjective
	// Defines the kind of preprocessing and algorithms intended for the candidates.
	// Options include: BinaryClassification, MulticlassClassification, and Regression.
	ProblemType types.ProblemType
	// Similar to InputDataConfig supported by Tuning. Format(s) supported: CSV.
	// Minimum of 1000 rows.
	InputDataConfig []*types.AutoMLChannel
	// The ARN of the role that will be used to access the data.
	RoleArn *string
	// Contains CompletionCriteria and SecurityConfig.
	AutoMLJobConfig *types.AutoMLJobConfig
	// This will generate possible candidates without training a model. A candidate is
	// a combination of data preprocessors, algorithms, and algorithm parameter
	// settings.
	GenerateCandidateDefinitionsOnly *bool
	// Similar to OutputDataConfig supported by Tuning. Format(s) supported: CSV.
	OutputDataConfig *types.AutoMLOutputDataConfig
	// Each tag consists of a key and an optional value. Tag keys must be unique per
	// resource.
	Tags []*types.Tag
}

type CreateAutoMLJobOutput struct {
	// When a job is created, it is assigned a unique ARN.
	AutoMLJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateCodeRepositoryInput struct {
	// Specifies details about the repository, including the URL where the repository
	// is located, the default branch, and credentials to use to access the repository.
	GitConfig *types.GitConfig
	// The name of the Git repository. The name must have 1 to 63 characters. Valid
	// characters are a-z, A-Z, 0-9, and - (hyphen).
	CodeRepositoryName *string
}

type CreateCodeRepositoryOutput struct {
	// The Amazon Resource Name (ARN) of the new repository.
	CodeRepositoryArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateCompilationJobInput struct {
	// Provides information about the output location for the compiled model and the
	// target device the model runs on.
	OutputConfig *types.OutputConfig
	// Specifies a limit to how long a model compilation job can run. When the job
	// reaches the time limit, Amazon SageMaker ends the compilation job. Use this API
	// to cap model training costs.
	StoppingCondition *types.StoppingCondition
	// Provides 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.
	InputConfig *types.InputConfig
	// The Amazon Resource Name (ARN) of an IAM role that enables Amazon SageMaker to
	// perform tasks on your behalf. During model compilation, Amazon SageMaker needs
	// your permission to:
	//
	//     * Read input data from an S3 bucket
	//
	//     * Write model
	// artifacts to an S3 bucket
	//
	//     * Write logs to Amazon CloudWatch Logs
	//
	//     *
	// Publish metrics to Amazon CloudWatch
	//
	// You grant permissions for all of these
	// tasks to an IAM role. To pass this role to Amazon SageMaker, the caller of this
	// API must have the iam:PassRole permission. For more information, see Amazon
	// SageMaker Roles.
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html)
	RoleArn *string
	// A name for the model compilation job. The name must be unique within the AWS
	// Region and within your AWS account.
	CompilationJobName *string
}

type CreateCompilationJobOutput struct {
	// If the action is successful, the service sends back an HTTP 200 response. Amazon
	// SageMaker returns the following data in JSON format:
	//
	//     * CompilationJobArn:
	// The Amazon Resource Name (ARN) of the compiled job.
	CompilationJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateDomainInput struct {
	// The ID of the Amazon Virtual Private Cloud (VPC) to use for communication with
	// the EFS volume.
	VpcId *string
	// The default user settings.
	DefaultUserSettings *types.UserSettings
	// The mode of authentication that members use to access the domain.
	AuthMode types.AuthMode
	// The VPC subnets to use for communication with the EFS volume.
	SubnetIds []*string
	// The AWS Key Management Service (KMS) encryption key ID. Encryption with a
	// customer master key (CMK) is not supported.
	HomeEfsFileSystemKmsKeyId *string
	// Tags to associated with the Domain. Each tag consists of a key and an optional
	// value. Tag keys must be unique per resource. Tags are searchable using the
	// Search () API.
	Tags []*types.Tag
	// A name for the domain.
	DomainName *string
}

type CreateDomainOutput struct {
	// The URL to the created domain.
	Url *string
	// The Amazon Resource Name (ARN) of the created domain.
	DomainArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateEndpointConfigInput struct {
	// The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon
	// SageMaker uses to encrypt data on the storage volume attached to the ML compute
	// instance that hosts the endpoint. 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
	//
	// The KMS key policy must
	// grant permission to the IAM role that you specify in your CreateEndpoint,
	// UpdateEndpoint requests. For more information, refer to the AWS Key Management
	// Service section Using Key Policies in AWS KMS
	// (https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html)
	// 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 KmsKeyId when using an instance type with local
	// storage. If any of the models that you specify in the ProductionVariants
	// parameter use nitro-based instances with local storage, do not specify a value
	// for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any
	// nitro-based instances with local storage, the call to CreateEndpointConfig
	// fails. 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).
	KmsKeyId *string
	// The name of the endpoint configuration. You specify this name in a
	// CreateEndpoint () request.
	EndpointConfigName *string
	// A list of key-value pairs. For more information, see Using Cost Allocation Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*types.Tag
	// An list of ProductionVariant objects, one for each model that you want to host
	// at this endpoint.
	ProductionVariants []*types.ProductionVariant
	//
	DataCaptureConfig *types.DataCaptureConfig
}

type CreateEndpointConfigOutput struct {
	// The Amazon Resource Name (ARN) of the endpoint configuration.
	EndpointConfigArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateEndpointInput struct {
	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)in
	// the AWS Billing and Cost Management User Guide.  </p>
	Tags []*types.Tag
	// The name of the endpoint. The name must be unique within an AWS Region in your
	// AWS account.
	EndpointName *string
	// The name of an endpoint configuration. For more information, see
	// CreateEndpointConfig ().
	EndpointConfigName *string
}

type CreateEndpointOutput struct {
	// The Amazon Resource Name (ARN) of the endpoint.
	EndpointArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateExperimentInput struct {
	// The description of the experiment.
	Description *string
	// The name of the experiment. The name must be unique in your AWS account and is
	// not case-sensitive.
	ExperimentName *string
	// The name of the experiment as displayed. The name doesn't need to be unique. If
	// you don't specify DisplayName, the value in ExperimentName is displayed.
	DisplayName *string
	// A list of tags to associate with the experiment. You can use Search () API to
	// search on the tags.
	Tags []*types.Tag
}

type CreateExperimentOutput struct {
	// The Amazon Resource Name (ARN) of the experiment.
	ExperimentArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateFlowDefinitionInput struct {
	// An object containing information about the tasks the human reviewers will
	// perform.
	HumanLoopConfig *types.HumanLoopConfig
	// Container for configuring the source of human task requests. Use to specify if
	// Amazon Rekognition or Amazon Textract is used as an integration source.
	HumanLoopRequestSource *types.HumanLoopRequestSource
	// The name of your flow definition.
	FlowDefinitionName *string
	// An object containing information about the events that trigger a human workflow.
	HumanLoopActivationConfig *types.HumanLoopActivationConfig
	// An array of key-value pairs that contain metadata to help you categorize and
	// organize a flow definition. Each tag consists of a key and a value, both of
	// which you define.
	Tags []*types.Tag
	// The Amazon Resource Name (ARN) of the role needed to call other services on your
	// behalf. For example,
	// arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298.
	RoleArn *string
	// An object containing information about where the human review results will be
	// uploaded.
	OutputConfig *types.FlowDefinitionOutputConfig
}

type CreateFlowDefinitionOutput struct {
	// The Amazon Resource Name (ARN) of the flow definition you create.
	FlowDefinitionArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateHumanTaskUiInput struct {
	// The name of the user interface you are creating.
	HumanTaskUiName *string
	// An array of key-value pairs that contain metadata to help you categorize and
	// organize a human review workflow user interface. Each tag consists of a key and
	// a value, both of which you define.
	Tags []*types.Tag
	// The Liquid template for the worker user interface.
	UiTemplate *types.UiTemplate
}

type CreateHumanTaskUiOutput struct {
	// The Amazon Resource Name (ARN) of the human review workflow user interface you
	// create.
	HumanTaskUiArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateHyperParameterTuningJobInput struct {
	// An array of key-value pairs. You can use tags to categorize your AWS resources
	// in different ways, for example, by purpose, owner, or environment. For more
	// information, see AWS Tagging Strategies
	// (https://aws.amazon.com/answers/account-management/aws-tagging-strategies/).
	// Tags that you specify for the tuning job are also added to all training jobs
	// that the tuning job launches.
	Tags []*types.Tag
	// The name of the tuning job. This name is the prefix for the names of all
	// training jobs that this tuning job launches. The name must be unique within the
	// same AWS account and AWS Region. The name must have { } to { } characters. Valid
	// characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case
	// sensitive.
	HyperParameterTuningJobName *string
	// A list of the HyperParameterTrainingJobDefinition () objects launched for this
	// tuning job.
	TrainingJobDefinitions []*types.HyperParameterTrainingJobDefinition
	// The HyperParameterTrainingJobDefinition () object that describes the training
	// jobs that this tuning job launches, including static hyperparameters, input data
	// configuration, output data configuration, resource configuration, and stopping
	// condition.
	TrainingJobDefinition *types.HyperParameterTrainingJobDefinition
	// The HyperParameterTuningJobConfig () object that describes the tuning job,
	// including the search strategy, the objective metric used to evaluate training
	// jobs, ranges of parameters to search, and resource limits for the tuning job.
	// For more information, see How Hyperparameter Tuning Works
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.html).
	HyperParameterTuningJobConfig *types.HyperParameterTuningJobConfig
	// Specifies the configuration for starting the hyperparameter tuning job using one
	// or more previous 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. If you specify
	// IDENTICAL_DATA_AND_ALGORITHM as the WarmStartType value for the warm start
	// configuration, the training job that performs the best in the new tuning job 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.
	WarmStartConfig *types.HyperParameterTuningJobWarmStartConfig
}

type CreateHyperParameterTuningJobOutput struct {
	// The Amazon Resource Name (ARN) of the tuning job. Amazon SageMaker assigns an
	// ARN to a hyperparameter tuning job when you create it.
	HyperParameterTuningJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateLabelingJobInput struct {
	// A set of conditions for stopping the 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.
	StoppingConditions *types.LabelingJobStoppingConditions
	// Input data for the labeling job, such as the Amazon S3 location of the data
	// objects and the location of the manifest file that describes the data objects.
	InputConfig *types.LabelingJobInputConfig
	// Configures the labeling task and how it is presented to workers; including, but
	// not limited to price, keywords, and batch size (task count).
	HumanTaskConfig *types.HumanTaskConfig
	// The name of the labeling job. This name is used to identify the job in a list of
	// labeling jobs.
	LabelingJobName *string
	// An array of key/value pairs. For more information, see Using Cost Allocation
	// Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*types.Tag
	// The S3 URL of the file that defines the categories used to label the data
	// objects. For 3D point cloud task types, see Create a Labeling Category
	// Configuration File for 3D Point Cloud Labeling Jobs
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-label-category-config.html).
	// For all other built-in task types
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html) and custom
	// tasks
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates.html),
	// your label category configuration file must be a JSON file in the following
	// format. Identify the labels you want to use by replacing label_1,
	// label_2,...,label_n with your label categories. {
	//     "document-version":
	// "2018-11-28"
	//
	//     "labels": [
	//
	//     {
	//
	//     "label": "label_1"
	//
	//     },
	//
	//     {
	//
	//
	// "label": "label_2"
	//
	//     },
	//
	//     ...
	//
	//     {
	//
	//     "label": "label_n"
	//
	//     }
	//
	//
	// ]
	//
	//     }
	LabelCategoryConfigS3Uri *string
	// The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks
	// on your behalf during data labeling. You must grant this role the necessary
	// permissions so that Amazon SageMaker can successfully complete data labeling.
	RoleArn *string
	// The attribute name to use for the label in the output manifest file. This is the
	// key for the key/value pair formed with the label that a worker assigns to the
	// object. The name can't end with "-metadata". If you are running a semantic
	// segmentation labeling job, the attribute name must end with "-ref". If you are
	// running any other kind of labeling job, the attribute name must not end with
	// "-ref".
	LabelAttributeName *string
	// Configures the information required to perform automated data labeling.
	LabelingJobAlgorithmsConfig *types.LabelingJobAlgorithmsConfig
	// The location of the output data and the AWS Key Management Service key ID for
	// the key used to encrypt the output data, if any.
	OutputConfig *types.LabelingJobOutputConfig
}

type CreateLabelingJobOutput struct {
	// The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify
	// the labeling job.
	LabelingJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateModelInput struct {
	// A VpcConfig () object that specifies the VPC that you want your model to connect
	// to. Control access to and from your model container by configuring the VPC.
	// VpcConfig is used in hosting services and in batch transform. 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 Data
	// in Batch Transform Jobs by Using an Amazon Virtual Private Cloud
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-vpc.html).
	VpcConfig *types.VpcConfig
	// Isolates the model container. No inbound or outbound network calls can be made
	// to or from the model container.
	EnableNetworkIsolation *bool
	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*types.Tag
	// The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker can assume
	// to access model artifacts and docker image for deployment on ML compute
	// instances or for batch transform jobs. Deploying on ML compute instances is part
	// of model hosting. For more information, see Amazon SageMaker Roles
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html). To be
	// able to pass this role to Amazon SageMaker, the caller of this API must have the
	// iam:PassRole permission.
	ExecutionRoleArn *string
	// The location of the primary docker image containing inference code, associated
	// artifacts, and custom environment map that the inference code uses when the
	// model is deployed for predictions.
	PrimaryContainer *types.ContainerDefinition
	// The name of the new model.
	ModelName *string
	// Specifies the containers in the inference pipeline.
	Containers []*types.ContainerDefinition
}

type CreateModelOutput struct {
	// The ARN of the model created in Amazon SageMaker.
	ModelArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateModelPackageInput struct {
	// Details about the algorithm that was used to create the model package.
	SourceAlgorithmSpecification *types.SourceAlgorithmSpecification
	// Specifies configurations for one or more transform jobs that Amazon SageMaker
	// runs to test the model package.
	ValidationSpecification *types.ModelPackageValidationSpecification
	// A description of the model package.
	ModelPackageDescription *string
	// Specifies details about inference jobs that can be run with models based on this
	// model package, including the following:
	//
	//     * The Amazon ECR paths of
	// containers that contain the inference code and model artifacts.
	//
	//     * The
	// instance types that the model package supports for transform jobs and real-time
	// endpoints used for inference.
	//
	//     * The input and output content formats that
	// the model package supports for inference.
	InferenceSpecification *types.InferenceSpecification
	// The name of the model package. The name must have 1 to 63 characters. Valid
	// characters are a-z, A-Z, 0-9, and - (hyphen).
	ModelPackageName *string
	// Whether to certify the model package for listing on AWS Marketplace.
	CertifyForMarketplace *bool
}

type CreateModelPackageOutput struct {
	// The Amazon Resource Name (ARN) of the new model package.
	ModelPackageArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateMonitoringScheduleInput struct {
	// The name of the monitoring schedule. The name must be unique within an AWS
	// Region within an AWS account.
	MonitoringScheduleName *string
	// The configuration object that specifies the monitoring schedule and defines the
	// monitoring job.
	MonitoringScheduleConfig *types.MonitoringScheduleConfig
	// (Optional) An array of key-value pairs. For more information, see Using Cost
	// Allocation Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*types.Tag
}

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

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateNotebookInstanceInput struct {
	// A Git repository to associate with the notebook instance as its default code
	// repository. This can be either the name of a Git repository stored as a resource
	// in your account, or the URL of a Git repository in AWS CodeCommit
	// (https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any
	// other Git repository. When you open a notebook instance, it opens in the
	// directory that contains this repository. For more information, see Associating
	// Git Repositories with Amazon SageMaker Notebook Instances
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html).
	DefaultCodeRepository *string
	// An array of up to three Git repositories to associate with the notebook
	// instance. These can be either the names of Git repositories stored as resources
	// in your account, or the URL of Git repositories in AWS CodeCommit
	// (https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any
	// other Git repository. These repositories are cloned at the same level as the
	// default repository of your notebook instance. For more information, see
	// Associating Git Repositories with Amazon SageMaker Notebook Instances
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html).
	AdditionalCodeRepositories []*string
	// Sets whether Amazon SageMaker provides internet access to the notebook instance.
	// If you set this to Disabled this notebook instance will be able to access
	// resources only in your VPC, and will not be able to connect to Amazon SageMaker
	// training and endpoint services unless your configure a NAT Gateway in your VPC.
	// For more information, see Notebook Instances Are Internet-Enabled by Default
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access).
	// You can set the value of this parameter to Disabled only if you set a value for
	// the SubnetId parameter.
	DirectInternetAccess types.DirectInternetAccess
	// The ID of the subnet in a VPC to which you would like to have a connectivity
	// from your ML compute instance.
	SubnetId *string
	// A list of Elastic Inference (EI) instance types to associate with this notebook
	// instance. Currently, only one instance type can be associated with a notebook
	// instance. For more information, see Using Elastic Inference in Amazon SageMaker
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html).
	AcceleratorTypes []types.NotebookInstanceAcceleratorType
	// The name of a lifecycle configuration to associate with the notebook instance.
	// For information about lifestyle configurations, see Step 2.1: (Optional)
	// Customize a Notebook Instance
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html).
	LifecycleConfigName *string
	// Whether root access is enabled or disabled for users of the notebook instance.
	// The default value is Enabled. Lifecycle configurations need root access to be
	// able to set up a notebook instance. Because of this, lifecycle configurations
	// associated with a notebook instance always run with root access even if you
	// disable root access for users.
	RootAccess types.RootAccess
	// The type of ML compute instance to launch for the notebook instance.
	InstanceType types.InstanceType
	// The size, in GB, of the ML storage volume to attach to the notebook instance.
	// The default value is 5 GB.
	VolumeSizeInGB *int32
	// A list of tags to associate with the notebook instance. You can add tags later
	// by using the CreateTags API.
	Tags []*types.Tag
	// The name of the new notebook instance.
	NotebookInstanceName *string
	// The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon
	// SageMaker uses to encrypt data on the storage volume attached to your notebook
	// instance. The KMS key you provide must be enabled. For information, see Enabling
	// and Disabling Keys
	// (https://docs.aws.amazon.com/kms/latest/developerguide/enabling-keys.html) in
	// the AWS Key Management Service Developer Guide.
	KmsKeyId *string
	// When you send any requests to AWS resources from the notebook instance, Amazon
	// SageMaker assumes this role to perform tasks on your behalf. You must grant this
	// role necessary permissions so Amazon SageMaker can perform these tasks. The
	// policy must allow the Amazon SageMaker service principal
	// (sagemaker.amazonaws.com) permissions to assume this role. For more information,
	// see Amazon SageMaker Roles
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html). To be
	// able to pass this role to Amazon SageMaker, the caller of this API must have the
	// iam:PassRole permission.
	RoleArn *string
	// The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be
	// for the same VPC as specified in the subnet.
	SecurityGroupIds []*string
}

type CreateNotebookInstanceLifecycleConfigInput struct {
	// A shell script that runs only once, when you create a notebook instance. The
	// shell script must be a base64-encoded string.
	OnCreate []*types.NotebookInstanceLifecycleHook
	// A shell script that runs every time you start a notebook instance, including
	// when you create the notebook instance. The shell script must be a base64-encoded
	// string.
	OnStart []*types.NotebookInstanceLifecycleHook
	// The name of the lifecycle configuration.
	NotebookInstanceLifecycleConfigName *string
}

type CreateNotebookInstanceLifecycleConfigOutput struct {
	// The Amazon Resource Name (ARN) of the lifecycle configuration.
	NotebookInstanceLifecycleConfigArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateNotebookInstanceOutput struct {
	// The Amazon Resource Name (ARN) of the notebook instance.
	NotebookInstanceArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreatePresignedDomainUrlInput struct {
	// The name of the UserProfile to sign-in as.
	UserProfileName *string
	// The domain ID.
	DomainId *string
	// The session expiration duration in seconds.
	SessionExpirationDurationInSeconds *int32
}

type CreatePresignedDomainUrlOutput struct {
	// The presigned URL.
	AuthorizedUrl *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreatePresignedNotebookInstanceUrlInput struct {
	// The name of the notebook instance.
	NotebookInstanceName *string
	// The duration of the session, in seconds. The default is 12 hours.
	SessionExpirationDurationInSeconds *int32
}

type CreatePresignedNotebookInstanceUrlOutput struct {
	// A JSON object that contains the URL string.
	AuthorizedUrl *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateProcessingJobInput struct {
	// The name of the processing job. The name must be unique within an AWS Region in
	// the AWS account.
	ProcessingJobName *string
	// Configures the processing job to run a specified Docker container image.
	AppSpecification *types.AppSpecification
	// Sets the environment variables in the Docker container.
	Environment map[string]*string
	// Output configuration for the processing job.
	ProcessingOutputConfig *types.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 *types.ProcessingResources
	// The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume
	// to perform tasks on your behalf.
	RoleArn *string
	// (Optional) An array of key-value pairs. For more information, see Using Cost
	// Allocation Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*types.Tag
	// For each input, data is downloaded from S3 into the processing container before
	// the processing job begins running if "S3InputMode" is set to File.
	ProcessingInputs []*types.ProcessingInput
	// The time limit for how long the processing job is allowed to run.
	StoppingCondition *types.ProcessingStoppingCondition
	// Networking options for a processing job.
	NetworkConfig *types.NetworkConfig
	// Associates a SageMaker job as a trial component with an experiment and trial.
	// Specified when you call the following APIs:
	//
	//     * CreateProcessingJob ()
	//
	//     *
	// CreateTrainingJob ()
	//
	//     * CreateTransformJob ()
	ExperimentConfig *types.ExperimentConfig
}

type CreateProcessingJobOutput struct {
	// The Amazon Resource Name (ARN) of the processing job.
	ProcessingJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateTrainingJobInput struct {
	// 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. For more information, see Protect
	// Communications Between ML Compute Instances in a Distributed Training Job
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/train-encrypt.html).
	EnableInterContainerTrafficEncryption *bool
	// Algorithm-specific parameters that influence the quality of the model. You set
	// hyperparameters before you start the learning process. For a list of
	// hyperparameters for each training algorithm provided by Amazon SageMaker, see
	// Algorithms (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html). You can
	// specify a maximum of 100 hyperparameters. Each hyperparameter is a key-value
	// pair. Each key and value is limited to 256 characters, as specified by the
	// Length Constraint.
	HyperParameters map[string]*string
	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.  </p>
	Tags []*types.Tag
	// Configuration information for debugging rules.
	DebugRuleConfigurations []*types.DebugRuleConfiguration
	// Configuration of storage locations for TensorBoard output.
	TensorBoardOutputConfig *types.TensorBoardOutputConfig
	// The registry path of the Docker image that contains the training algorithm and
	// algorithm-specific metadata, including the input mode. For more information
	// about algorithms provided by Amazon SageMaker, see Algorithms
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html). For information
	// about providing your own algorithms, see Using Your Own Algorithms with Amazon
	// SageMaker
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html).
	AlgorithmSpecification *types.AlgorithmSpecification
	// Associates a SageMaker job as a trial component with an experiment and trial.
	// Specified when you call the following APIs:
	//
	//     * CreateProcessingJob ()
	//
	//     *
	// CreateTrainingJob ()
	//
	//     * CreateTransformJob ()
	ExperimentConfig *types.ExperimentConfig
	// An array of Channel objects. Each channel is a named input source.
	// InputDataConfig
	//     describes the input data and its location. </p>
	// <p>Algorithms can accept input data from one or more channels. For example, an
	// algorithm might have two channels of input data, <code>training_data</code> and
	// <code>validation_data</code>. The configuration for each channel provides the
	// S3, EFS, or FSx location where the input data is stored. It also provides
	// information about the stored data: the MIME type, compression method, and
	// whether the data is wrapped in RecordIO format. </p> <p>Depending on the input
	// mode that the algorithm supports, Amazon SageMaker either copies input data
	// files from an S3 bucket to a local directory in the Docker container, or makes
	// it available as input streams. For example, if you specify an EFS location,
	// input data files will be made available as input streams. They do not need to be
	// downloaded.</p>
	InputDataConfig []*types.Channel
	// Configuration information for the debug hook parameters, collection
	// configuration, and storage paths.
	DebugHookConfig *types.DebugHookConfig
	// The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume
	// to perform tasks on your behalf. During model training, Amazon SageMaker needs
	// your permission to read input data from an S3 bucket, download a Docker image
	// that contains training code, write model artifacts to an S3 bucket, write logs
	// to Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch. You grant
	// permissions for all of these tasks to an IAM role. For more information, see
	// Amazon SageMaker Roles
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html). To be
	// able to pass this role to Amazon SageMaker, the caller of this API must have the
	// iam:PassRole permission.
	RoleArn *string
	// To train models using managed spot training, choose True. Managed spot training
	// provides a fully managed and scalable infrastructure for training machine
	// learning models. this option is useful when training jobs can be interrupted and
	// when there is flexibility when the training job is run. The complete and
	// intermediate results of jobs are stored in an Amazon S3 bucket, and can be used
	// as a starting point to train models incrementally. Amazon SageMaker provides
	// metrics and logs in CloudWatch. They can be used to see when managed spot
	// training jobs are running, interrupted, resumed, or completed.
	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 you enable network isolation 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 a limit to how long a model training job can run. When the job reaches
	// the time limit, Amazon SageMaker ends the training job. Use this API to cap
	// model training costs. To stop a job, Amazon SageMaker sends the algorithm the
	// SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use
	// this 120-second window to save the model artifacts, so the results of training
	// are not lost.
	StoppingCondition *types.StoppingCondition
	// The resources, including the ML compute instances and ML storage volumes, to use
	// for model training. ML storage volumes store model artifacts and incremental
	// states. Training algorithms might also use ML storage volumes for scratch space.
	// If you want Amazon SageMaker to use the ML 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.
	ResourceConfig *types.ResourceConfig
	// Contains information about the output location for managed spot training
	// checkpoint data.
	CheckpointConfig *types.CheckpointConfig
	// Specifies the path to the S3 location where you want to store model artifacts.
	// Amazon SageMaker creates subfolders for the artifacts.
	OutputDataConfig *types.OutputDataConfig
	// A VpcConfig () object that specifies the VPC that you want your training job 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 *types.VpcConfig
	// The name of the training job. The name must be unique within an AWS Region in an
	// AWS account.
	TrainingJobName *string
}

type CreateTrainingJobOutput struct {
	// The Amazon Resource Name (ARN) of the training job.
	TrainingJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateTransformJobInput struct {
	// The name of the model that you want to use for the transform job. ModelName must
	// be the name of an existing Amazon SageMaker model within an AWS Region in an AWS
	// account.
	ModelName *string
	// Describes the results of the transform job.
	TransformOutput *types.TransformOutput
	// Associates a SageMaker job as a trial component with an experiment and trial.
	// Specified when you call the following APIs:
	//
	//     * CreateProcessingJob ()
	//
	//     *
	// CreateTrainingJob ()
	//
	//     * CreateTransformJob ()
	ExperimentConfig *types.ExperimentConfig
	// The name of the transform job. The name must be unique within an AWS Region in
	// an AWS account.
	TransformJobName *string
	// 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, Amazon
	// SageMaker built-in algorithms do not support HTTP chunked encoding.
	MaxPayloadInMB *int32
	// 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. To enable the batch
	// strategy, you must set the SplitType property to Line, RecordIO, or TFRecord. To
	// use only one record when making an HTTP invocation request to a container, set
	// BatchStrategy to SingleRecord and SplitType to Line. To fit as many records in a
	// mini-batch as can fit within the MaxPayloadInMB limit, set BatchStrategy to
	// MultiRecord and SplitType to Line.
	BatchStrategy types.BatchStrategy
	// (Optional) An array of key-value pairs. For more information, see Using Cost
	// Allocation Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*types.Tag
	// Describes the resources, including ML instance types and ML instance count, to
	// use for the transform job.
	TransformResources *types.TransformResources
	// 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 *types.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
	// Configures the timeout and maximum number of retries for processing a transform
	// job invocation.
	ModelClientConfig *types.ModelClientConfig
	// Describes the input source and the way the transform job consumes it.
	TransformInput *types.TransformInput
	// 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, Amazon
	// SageMaker checks the optional execution-parameters to determine the settings for
	// your chosen algorithm. If the execution-parameters endpoint is not enabled, the
	// default value is 1. For more information on execution-parameters, see How
	// Containers Serve Requests
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requests).
	// For built-in algorithms, you don't need to set a value for
	// MaxConcurrentTransforms.
	MaxConcurrentTransforms *int32
}

type CreateTransformJobOutput struct {
	// The Amazon Resource Name (ARN) of the transform job.
	TransformJobArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateTrialComponentInput struct {
	// The hyperparameters for the component.
	Parameters map[string]*types.TrialComponentParameterValue
	// The status of the component. States include:
	//
	//     * InProgress
	//
	//     *
	// Completed
	//
	//     * Failed
	Status *types.TrialComponentStatus
	// When the component ended.
	EndTime *time.Time
	// The name of the component. The name must be unique in your AWS account and is
	// not case-sensitive.
	TrialComponentName *string
	// A list of tags to associate with the component. You can use Search () API to
	// search on the tags.
	Tags []*types.Tag
	// The output artifacts for the component. Examples of output artifacts are
	// metrics, snapshots, logs, and images.
	OutputArtifacts map[string]*types.TrialComponentArtifact
	// The name of the component as displayed. The name doesn't need to be unique. If
	// DisplayName isn't specified, TrialComponentName is displayed.
	DisplayName *string
	// When the component started.
	StartTime *time.Time
	// The input artifacts for the component. Examples of input artifacts are datasets,
	// algorithms, hyperparameters, source code, and instance types.
	InputArtifacts map[string]*types.TrialComponentArtifact
}

type CreateTrialComponentOutput struct {
	// The Amazon Resource Name (ARN) of the trial component.
	TrialComponentArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateTrialInput struct {
	// The name of the trial as displayed. The name doesn't need to be unique. If
	// DisplayName isn't specified, TrialName is displayed.
	DisplayName *string
	// The name of the experiment to associate the trial with.
	ExperimentName *string
	// The name of the trial. The name must be unique in your AWS account and is not
	// case-sensitive.
	TrialName *string
	// A list of tags to associate with the trial. You can use Search () API to search
	// on the tags.
	Tags []*types.Tag
}

type CreateTrialOutput struct {
	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateUserProfileInput struct {
	// The username of the associated AWS Single Sign-On User for this UserProfile. If
	// the Domain's AuthMode is SSO, this field is required, and must match a valid
	// username of a user in your directory. If the Domain's AuthMode is not SSO, this
	// field cannot be specified.
	SingleSignOnUserValue *string
	// A collection of settings.
	UserSettings *types.UserSettings
	// The ID of the associated Domain.
	DomainId *string
	// A specifier for the type of value specified in SingleSignOnUserValue. Currently,
	// the only supported value is "UserName". If the Domain's AuthMode is SSO, this
	// field is required. If the Domain's AuthMode is not SSO, this field cannot be
	// specified.
	SingleSignOnUserIdentifier *string
	// A name for the UserProfile.
	UserProfileName *string
	// Each tag consists of a key and an optional value. Tag keys must be unique per
	// resource.
	Tags []*types.Tag
}

type CreateUserProfileOutput struct {
	// The user profile Amazon Resource Name (ARN).
	UserProfileArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateWorkforceInput struct {
	// An array of key-value pairs that contain metadata to help you categorize and
	// organize our workforce. Each tag consists of a key and a value, both of which
	// you define.
	Tags []*types.Tag
	// Use this parameter to configure a private workforce using your own OIDC Identity
	// Provider. Do not use CognitoConfig if you specify values for OidcConfig.
	OidcConfig *types.OidcConfig
	// Use this parameter to configure an Amazon Cognito private 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).
	// <p>Do not use <code>OidcConfig</code> if you specify values for
	// <code>CognitoConfig</code>.</p>
	CognitoConfig *types.CognitoConfig
	// 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. For more
	// information, see .
	SourceIpConfig *types.SourceIpConfig
	// The name of the private workforce.
	WorkforceName *string
}

type CreateWorkforceOutput struct {
	// The Amazon Resource Name (ARN) of the workforce.
	WorkforceArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type CreateWorkteamInput struct {
	// Configures notification of workers regarding available or expiring work items.
	NotificationConfiguration *types.NotificationConfiguration
	// The name of the work team. Use this name to identify the work team.
	WorkteamName *string
	// A description of the work team.
	Description *string
	// A list of MemberDefinition objects that contains objects that identify the
	// Amazon Cognito user pool that makes up the work team. For more information, see
	// Amazon Cognito User Pools
	// (https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html).
	// All of the CognitoMemberDefinition objects that make up the member definition
	// must have the same ClientId and UserPool values.
	MemberDefinitions []*types.MemberDefinition
	// The name of the workforce.
	WorkforceName *string
	// An array of key-value pairs. For more information, see Resource Tag
	// (https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-resource-tags.html)
	// and Using Cost Allocation Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*types.Tag
}

type CreateWorkteamOutput struct {
	// The Amazon Resource Name (ARN) of the work team. You can use this ARN to
	// identify the work team.
	WorkteamArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteAlgorithmInput struct {
	// The name of the algorithm to delete.
	AlgorithmName *string
}

type DeleteAlgorithmOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteAppInput struct {
	// The type of app.
	AppType types.AppType
	// The user profile name.
	UserProfileName *string
	// The name of the app.
	AppName *string
	// The domain ID.
	DomainId *string
}

type DeleteAppOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteCodeRepositoryInput struct {
	// The name of the Git repository to delete.
	CodeRepositoryName *string
}

type DeleteCodeRepositoryOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteDomainInput struct {
	// The retention policy for this domain, which specifies whether resources will be
	// retained after the Domain is deleted. By default, all resources are retained
	// (not automatically deleted).
	RetentionPolicy *types.RetentionPolicy
	// The domain ID.
	DomainId *string
}

type DeleteDomainOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteEndpointConfigInput struct {
	// The name of the endpoint configuration that you want to delete.
	EndpointConfigName *string
}

type DeleteEndpointConfigOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteEndpointInput struct {
	// The name of the endpoint that you want to delete.
	EndpointName *string
}

type DeleteEndpointOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteExperimentInput struct {
	// The name of the experiment to delete.
	ExperimentName *string
}

type DeleteExperimentOutput struct {
	// The Amazon Resource Name (ARN) of the experiment that is being deleted.
	ExperimentArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteFlowDefinitionInput struct {
	// The name of the flow definition you are deleting.
	FlowDefinitionName *string
}

type DeleteFlowDefinitionOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteHumanTaskUiInput struct {
	// The name of the human task user interface (work task template) you want to
	// delete.
	HumanTaskUiName *string
}

type DeleteHumanTaskUiOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteModelInput struct {
	// The name of the model to delete.
	ModelName *string
}

type DeleteModelOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteModelPackageInput struct {
	// The name of the model package. The name must have 1 to 63 characters. Valid
	// characters are a-z, A-Z, 0-9, and - (hyphen).
	ModelPackageName *string
}

type DeleteModelPackageOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteMonitoringScheduleInput struct {
	// The name of the monitoring schedule to delete.
	MonitoringScheduleName *string
}

type DeleteMonitoringScheduleOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteNotebookInstanceInput struct {
	// The name of the Amazon SageMaker notebook instance to delete.
	NotebookInstanceName *string
}

type DeleteNotebookInstanceLifecycleConfigInput struct {
	// The name of the lifecycle configuration to delete.
	NotebookInstanceLifecycleConfigName *string
}

type DeleteNotebookInstanceLifecycleConfigOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteNotebookInstanceOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteTagsInput struct {
	// An array or one or more tag keys to delete.
	TagKeys []*string
	// The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
	ResourceArn *string
}

type DeleteTagsOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteTrialComponentInput struct {
	// The name of the component to delete.
	TrialComponentName *string
}

type DeleteTrialComponentOutput struct {
	// The Amazon Resource Name (ARN) of the component is being deleted.
	TrialComponentArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteTrialInput struct {
	// The name of the trial to delete.
	TrialName *string
}

type DeleteTrialOutput struct {
	// The Amazon Resource Name (ARN) of the trial that is being deleted.
	TrialArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteUserProfileInput struct {
	// The user profile name.
	UserProfileName *string
	// The domain ID.
	DomainId *string
}

type DeleteUserProfileOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteWorkforceInput struct {
	// The name of the workforce.
	WorkforceName *string
}

type DeleteWorkforceOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DeleteWorkteamInput struct {
	// The name of the work team to delete.
	WorkteamName *string
}

type DeleteWorkteamOutput struct {
	// Returns true if the work team was successfully deleted; otherwise, returns
	// false.
	Success *bool

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeAlgorithmInput struct {
	// The name of the algorithm to describe.
	AlgorithmName *string
}

type DescribeAlgorithmOutput struct {
	// Whether the algorithm is certified to be listed in AWS Marketplace.
	CertifyForMarketplace *bool
	// Details about training jobs run by this algorithm.
	TrainingSpecification *types.TrainingSpecification
	// The product identifier of the algorithm.
	ProductId *string
	// Details about inference jobs that the algorithm runs.
	InferenceSpecification *types.InferenceSpecification
	// The current status of the algorithm.
	AlgorithmStatus types.AlgorithmStatus
	// Details about configurations for one or more training jobs that Amazon SageMaker
	// runs to test the algorithm.
	ValidationSpecification *types.AlgorithmValidationSpecification
	// Details about the current status of the algorithm.
	AlgorithmStatusDetails *types.AlgorithmStatusDetails
	// A brief summary about the algorithm.
	AlgorithmDescription *string
	// A timestamp specifying when the algorithm was created.
	CreationTime *time.Time
	// The Amazon Resource Name (ARN) of the algorithm.
	AlgorithmArn *string
	// The name of the algorithm being described.
	AlgorithmName *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeAppInput struct {
	// The type of app.
	AppType types.AppType
	// The name of the app.
	AppName *string
	// The user profile name.
	UserProfileName *string
	// The domain ID.
	DomainId *string
}

type DescribeAppOutput struct {
	// The status.
	Status types.AppStatus
	// The user profile name.
	UserProfileName *string
	// The app's Amazon Resource Name (ARN).
	AppArn *string
	// The failure reason.
	FailureReason *string
	// The domain ID.
	DomainId *string
	// The instance type and the Amazon Resource Name (ARN) of the SageMaker image
	// created on the instance.
	ResourceSpec *types.ResourceSpec
	// The name of the app.
	AppName *string
	// The timestamp of the last health check.
	LastHealthCheckTimestamp *time.Time
	// The timestamp of the last user's activity.
	LastUserActivityTimestamp *time.Time
	// The creation time.
	CreationTime *time.Time
	// The type of app.
	AppType types.AppType

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeAutoMLJobInput struct {
	// Request information about a job using that job's unique name.
	AutoMLJobName *string
}

type DescribeAutoMLJobOutput struct {
	// Returns the job's creation time.
	CreationTime *time.Time
	// Returns the job's last modified time.
	LastModifiedTime *time.Time
	// Returns the job's BestCandidate.
	BestCandidate *types.AutoMLCandidate
	// Returns the job's end time.
	EndTime *time.Time
	// Returns the name of a job.
	AutoMLJobName *string
	// Returns the job's ARN.
	AutoMLJobArn *string
	// Returns the job's output from GenerateCandidateDefinitionsOnly.
	GenerateCandidateDefinitionsOnly *bool
	// Returns the job's FailureReason.
	FailureReason *string
	// Returns the job's objective.
	AutoMLJobObjective *types.AutoMLJobObjective
	// Returns information on the job's artifacts found in AutoMLJobArtifacts.
	AutoMLJobArtifacts *types.AutoMLJobArtifacts
	// Returns the job's AutoMLJobSecondaryStatus.
	AutoMLJobSecondaryStatus types.AutoMLJobSecondaryStatus
	// This contains ProblemType, AutoMLJobObjective and CompletionCriteria. They're
	// auto-inferred values, if not provided by you. If you do provide them, then
	// they'll be the same as provided.
	ResolvedAttributes *types.ResolvedAttributes
	// Returns the job's output data config.
	OutputDataConfig *types.AutoMLOutputDataConfig
	// Returns the job's problem type.
	ProblemType types.ProblemType
	// Returns the job's AutoMLJobStatus.
	AutoMLJobStatus types.AutoMLJobStatus
	// Returns the job's config.
	AutoMLJobConfig *types.AutoMLJobConfig
	// The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM)
	// role that has read permission to the input data location and write permission to
	// the output data location in Amazon S3.
	RoleArn *string
	// Returns the job's input data config.
	InputDataConfig []*types.AutoMLChannel

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeCodeRepositoryInput struct {
	// The name of the Git repository to describe.
	CodeRepositoryName *string
}

type DescribeCodeRepositoryOutput struct {
	// The Amazon Resource Name (ARN) of the Git repository.
	CodeRepositoryArn *string
	// The name of the Git repository.
	CodeRepositoryName *string
	// Configuration details about the repository, including the URL where the
	// repository is located, the default branch, and the Amazon Resource Name (ARN) of
	// the AWS Secrets Manager secret that contains the credentials used to access the
	// repository.
	GitConfig *types.GitConfig
	// The date and time that the repository was created.
	CreationTime *time.Time
	// The date and time that the repository was last changed.
	LastModifiedTime *time.Time

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeCompilationJobInput struct {
	// The name of the model compilation job that you want information about.
	CompilationJobName *string
}

type DescribeCompilationJobOutput struct {
	// Information about the location in Amazon S3 that has been configured for storing
	// the model artifacts used in the compilation job.
	ModelArtifacts *types.ModelArtifacts
	// The Amazon Resource Name (ARN) of the model compilation job.
	RoleArn *string
	// The time when the model compilation job started the CompilationJob instances.
	// You are billed for the time between this timestamp and the timestamp in the
	// DescribeCompilationJobResponse$CompilationEndTime () field. In Amazon CloudWatch
	// Logs, the start time might be later than this time. That's because it takes time
	// to download the compilation job, which depends on the size of the compilation
	// job container.
	CompilationStartTime *time.Time
	// The name of the model compilation job.
	CompilationJobName *string
	// The time that the model compilation job was created.
	CreationTime *time.Time
	// The time that the status of the model compilation job was last modified.
	LastModifiedTime *time.Time
	// If a model compilation job failed, the reason it failed.
	FailureReason *string
	// Information about the location in Amazon S3 of the input model artifacts, the
	// name and shape of the expected data inputs, and the framework in which the model
	// was trained.
	InputConfig *types.InputConfig
	// Information about the output location for the compiled model and the target
	// device that the model runs on.
	OutputConfig *types.OutputConfig
	// The status of the model compilation job.
	CompilationJobStatus types.CompilationJobStatus
	// Specifies a limit to how long a model compilation job can run. When the job
	// reaches the time limit, Amazon SageMaker ends the compilation job. Use this API
	// to cap model training costs.
	StoppingCondition *types.StoppingCondition
	// The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to
	// perform the model compilation job.
	CompilationJobArn *string
	// The time when the model compilation job on a compilation job instance ended. For
	// a successful or stopped job, this is when the job's model artifacts have
	// finished uploading. For a failed job, this is when Amazon SageMaker detected
	// that the job failed.
	CompilationEndTime *time.Time

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeDomainInput struct {
	// The domain ID.
	DomainId *string
}

type DescribeDomainOutput struct {
	// Settings which are applied to all UserProfile in this domain, if settings are
	// not explicitly specified in a given UserProfile.
	DefaultUserSettings *types.UserSettings
	// The AWS Key Management Service encryption key ID.
	HomeEfsFileSystemKmsKeyId *string
	// The domain's URL.
	Url *string
	// Security setting to limit to a set of subnets.
	SubnetIds []*string
	// The domain's Amazon Resource Name (ARN).
	DomainArn *string
	// The ID of the Amazon Virtual Private Cloud.
	VpcId *string
	// The domain name.
	DomainName *string
	// The domain's authentication mode.
	AuthMode types.AuthMode
	// The creation time.
	CreationTime *time.Time
	// The last modified time.
	LastModifiedTime *time.Time
	// The SSO managed application instance ID.
	SingleSignOnManagedApplicationInstanceId *string
	// The domain ID.
	DomainId *string
	// The ID of the Amazon Elastic File System (EFS) managed by this Domain.
	HomeEfsFileSystemId *string
	// The status.
	Status types.DomainStatus
	// The failure reason.
	FailureReason *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeEndpointConfigInput struct {
	// The name of the endpoint configuration.
	EndpointConfigName *string
}

type DescribeEndpointConfigOutput struct {
	// An array of ProductionVariant objects, one for each model that you want to host
	// at this endpoint.
	ProductionVariants []*types.ProductionVariant
	//
	DataCaptureConfig *types.DataCaptureConfig
	// A timestamp that shows when the endpoint configuration was created.
	CreationTime *time.Time
	// The Amazon Resource Name (ARN) of the endpoint configuration.
	EndpointConfigArn *string
	// AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML
	// storage volume attached to the instance.
	KmsKeyId *string
	// Name of the Amazon SageMaker endpoint configuration.
	EndpointConfigName *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeEndpointInput struct {
	// The name of the endpoint.
	EndpointName *string
}

type DescribeEndpointOutput struct {
	// 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.
	EndpointStatus types.EndpointStatus
	// An array of ProductionVariantSummary () objects, one for each model hosted
	// behind this endpoint.
	ProductionVariants []*types.ProductionVariantSummary
	// The name of the endpoint configuration associated with this endpoint.
	EndpointConfigName *string
	// Name of the endpoint.
	EndpointName *string
	// If the status of the endpoint is Failed, the reason why it failed.
	FailureReason *string
	// A timestamp that shows when the endpoint was created.
	CreationTime *time.Time
	// A timestamp that shows when the endpoint was last modified.
	LastModifiedTime *time.Time
	// The Amazon Resource Name (ARN) of the endpoint.
	EndpointArn *string
	//
	DataCaptureConfig *types.DataCaptureConfigSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeExperimentInput struct {
	// The name of the experiment to describe.
	ExperimentName *string
}

type DescribeExperimentOutput struct {
	// When the experiment was created.
	CreationTime *time.Time
	// When the experiment was last modified.
	LastModifiedTime *time.Time
	// The name of the experiment as displayed. If DisplayName isn't specified,
	// ExperimentName is displayed.
	DisplayName *string
	// Who last modified the experiment.
	LastModifiedBy *types.UserContext
	// The ARN of the source and, optionally, the type.
	Source *types.ExperimentSource
	// Who created the experiment.
	CreatedBy *types.UserContext
	// The description of the experiment.
	Description *string
	// The name of the experiment.
	ExperimentName *string
	// The Amazon Resource Name (ARN) of the experiment.
	ExperimentArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeFlowDefinitionInput struct {
	// The name of the flow definition.
	FlowDefinitionName *string
}

type DescribeFlowDefinitionOutput struct {
	// The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM)
	// execution role for the flow definition.
	RoleArn *string
	// The status of the flow definition. Valid values are listed below.
	FlowDefinitionStatus types.FlowDefinitionStatus
	// The timestamp when the flow definition was created.
	CreationTime *time.Time
	// An object containing information about the output file.
	OutputConfig *types.FlowDefinitionOutputConfig
	// An object containing information about what triggers a human review workflow.
	HumanLoopActivationConfig *types.HumanLoopActivationConfig
	// Container for configuring the source of human task requests. Used to specify if
	// Amazon Rekognition or Amazon Textract is used as an integration source.
	HumanLoopRequestSource *types.HumanLoopRequestSource
	// An object containing information about who works on the task, the workforce task
	// price, and other task details.
	HumanLoopConfig *types.HumanLoopConfig
	// The reason your flow definition failed.
	FailureReason *string
	// The Amazon Resource Name (ARN) of the flow defintion.
	FlowDefinitionArn *string
	// The Amazon Resource Name (ARN) of the flow definition.
	FlowDefinitionName *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeHumanTaskUiInput struct {
	// The name of the human task user interface (worker task template) you want
	// information about.
	HumanTaskUiName *string
}

type DescribeHumanTaskUiOutput struct {
	// The name of the human task user interface (worker task template).
	HumanTaskUiName *string
	// The Amazon Resource Name (ARN) of the human task user interface (worker task
	// template).
	HumanTaskUiArn *string
	// The timestamp when the human task user interface was created.
	CreationTime *time.Time
	// Container for user interface template information.
	UiTemplate *types.UiTemplateInfo
	// The status of the human task user interface (worker task template). Valid values
	// are listed below.
	HumanTaskUiStatus types.HumanTaskUiStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeHyperParameterTuningJobInput struct {
	// The name of the tuning job.
	HyperParameterTuningJobName *string
}

type DescribeHyperParameterTuningJobOutput struct {
	// The HyperParameterTuningJobConfig () object that specifies the configuration of
	// the tuning job.
	HyperParameterTuningJobConfig *types.HyperParameterTuningJobConfig
	// If the hyperparameter tuning job is an warm start tuning job with a
	// WarmStartType of IDENTICAL_DATA_AND_ALGORITHM, this is the TrainingJobSummary ()
	// for the training job with the best objective metric value of all training jobs
	// launched by this tuning job and all parent jobs specified for the warm start
	// tuning job.
	OverallBestTrainingJob *types.HyperParameterTrainingJobSummary
	// The TrainingJobStatusCounters () object that specifies the number of training
	// jobs, categorized by status, that this tuning job launched.
	TrainingJobStatusCounters *types.TrainingJobStatusCounters
	// The date and time that the tuning job ended.
	HyperParameterTuningEndTime *time.Time
	// The HyperParameterTrainingJobDefinition () object that specifies the definition
	// of the training jobs that this tuning job launches.
	TrainingJobDefinition *types.HyperParameterTrainingJobDefinition
	// The configuration for starting the hyperparameter parameter tuning job using one
	// or more previous 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.
	WarmStartConfig *types.HyperParameterTuningJobWarmStartConfig
	// The ObjectiveStatusCounters () object that specifies the number of training
	// jobs, categorized by the status of their final objective metric, that this
	// tuning job launched.
	ObjectiveStatusCounters *types.ObjectiveStatusCounters
	// The status of the tuning job: InProgress, Completed, Failed, Stopping, or
	// Stopped.
	HyperParameterTuningJobStatus types.HyperParameterTuningJobStatus
	// A list of the HyperParameterTrainingJobDefinition () objects launched for this
	// tuning job.
	TrainingJobDefinitions []*types.HyperParameterTrainingJobDefinition
	// The date and time that the tuning job started.
	CreationTime *time.Time
	// The date and time that the status of the tuning job was modified.
	LastModifiedTime *time.Time
	// The name of the tuning job.
	HyperParameterTuningJobName *string
	// A TrainingJobSummary () object that describes the training job that completed
	// with the best current HyperParameterTuningJobObjective ().
	BestTrainingJob *types.HyperParameterTrainingJobSummary
	// The Amazon Resource Name (ARN) of the tuning job.
	HyperParameterTuningJobArn *string
	// If the tuning job failed, the reason it failed.
	FailureReason *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeLabelingJobInput struct {
	// The name of the labeling job to return information for.
	LabelingJobName *string
}

type DescribeLabelingJobOutput struct {
	// The date and time that the labeling job was last updated.
	LastModifiedTime *time.Time
	// The date and time that the labeling job was created.
	CreationTime *time.Time
	// Input configuration information for the labeling job, such as the Amazon S3
	// location of the data objects and the location of the manifest file that
	// describes the data objects.
	InputConfig *types.LabelingJobInputConfig
	// Configuration information required for human workers to complete a labeling
	// task.
	HumanTaskConfig *types.HumanTaskConfig
	// A set of conditions for stopping a labeling job. If any of the conditions are
	// met, the job is automatically stopped.
	StoppingConditions *types.LabelingJobStoppingConditions
	// Configuration information for automated data labeling.
	LabelingJobAlgorithmsConfig *types.LabelingJobAlgorithmsConfig
	// The processing status of the labeling job.
	LabelingJobStatus types.LabelingJobStatus
	// The Amazon Resource Name (ARN) of the labeling job.
	LabelingJobArn *string
	// If the job failed, the reason that it failed.
	FailureReason *string
	// The name assigned to the labeling job when it was created.
	LabelingJobName *string
	// The S3 location of the JSON file that defines the categories used to label data
	// objects. Please note the following label-category limits:
	//
	//     * Semantic
	// segmentation labeling jobs using automated labeling: 20 labels
	//
	//     * Box
	// bounding labeling jobs (all): 10 labels
	//
	// The file is a JSON structure in the
	// following format: {
	//     "document-version": "2018-11-28"
	//
	//     "labels": [
	//
	//
	// {
	//
	//     "label": "label 1"
	//
	//     },
	//
	//     {
	//
	//     "label": "label 2"
	//
	//     },
	//
	//
	// ...
	//
	//     {
	//
	//     "label": "label n"
	//
	//     }
	//
	//     ]
	//
	//     }
	LabelCategoryConfigS3Uri *string
	// An array of key/value pairs. For more information, see Using Cost Allocation
	// Tags
	// (https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []*types.Tag
	// The location of the output produced by the labeling job.
	LabelingJobOutput *types.LabelingJobOutput
	// The attribute used as the label in the output manifest file.
	LabelAttributeName *string
	// A unique identifier for work done as part of a labeling job.
	JobReferenceCode *string
	// Provides a breakdown of the number of data objects labeled by humans, the number
	// of objects labeled by machine, the number of objects than couldn't be labeled,
	// and the total number of objects labeled.
	LabelCounters *types.LabelCounters
	// The location of the job's output data and the AWS Key Management Service key ID
	// for the key used to encrypt the output data, if any.
	OutputConfig *types.LabelingJobOutputConfig
	// The Amazon Resource Name (ARN) that Amazon SageMaker assumes to perform tasks on
	// your behalf during data labeling.
	RoleArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeModelInput struct {
	// The name of the model.
	ModelName *string
}

type DescribeModelOutput struct {
	// A VpcConfig () object that specifies the VPC that this model has access to. For
	// more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html)
	VpcConfig *types.VpcConfig
	// The Amazon Resource Name (ARN) of the model.
	ModelArn *string
	// The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
	ExecutionRoleArn *string
	// The containers in the inference pipeline.
	Containers []*types.ContainerDefinition
	// Name of the Amazon SageMaker model.
	ModelName *string
	// The location of the primary inference code, associated artifacts, and custom
	// environment map that the inference code uses when it is deployed in production.
	PrimaryContainer *types.ContainerDefinition
	// A timestamp that shows when the model was created.
	CreationTime *time.Time
	// If True, no inbound or outbound network calls can be made to or from the model
	// container.
	EnableNetworkIsolation *bool

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeModelPackageInput struct {
	// The name of the model package to describe.
	ModelPackageName *string
}

type DescribeModelPackageOutput struct {
	// The name of the model package being described.
	ModelPackageName *string
	// A timestamp specifying when the model package was created.
	CreationTime *time.Time
	// The Amazon Resource Name (ARN) of the model package.
	ModelPackageArn *string
	// Details about the algorithm that was used to create the model package.
	SourceAlgorithmSpecification *types.SourceAlgorithmSpecification
	// Details about the current status of the model package.
	ModelPackageStatusDetails *types.ModelPackageStatusDetails
	// Configurations for one or more transform jobs that Amazon SageMaker runs to test
	// the model package.
	ValidationSpecification *types.ModelPackageValidationSpecification
	// A brief summary of the model package.
	ModelPackageDescription *string
	// Whether the model package is certified for listing on AWS Marketplace.
	CertifyForMarketplace *bool
	// The current status of the model package.
	ModelPackageStatus types.ModelPackageStatus
	// Details about inference jobs that can be run with models based on this model
	// package.
	InferenceSpecification *types.InferenceSpecification

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeMonitoringScheduleInput struct {
	// Name of a previously created monitoring schedule.
	MonitoringScheduleName *string
}

type DescribeMonitoringScheduleOutput struct {
	// The status of an monitoring job.
	MonitoringScheduleStatus types.ScheduleStatus
	// The name of the endpoint for the monitoring job.
	EndpointName *string
	// Describes metadata on the last execution to run, if there was one.
	LastMonitoringExecutionSummary *types.MonitoringExecutionSummary
	// The configuration object that specifies the monitoring schedule and defines the
	// monitoring job.
	MonitoringScheduleConfig *types.MonitoringScheduleConfig
	// A string, up to one KB in size, that contains the reason a monitoring job
	// failed, if it failed.
	FailureReason *string
	// The time at which the monitoring job was created.
	CreationTime *time.Time
	// The time at which the monitoring job was last modified.
	LastModifiedTime *time.Time
	// Name of the monitoring schedule.
	MonitoringScheduleName *string
	// The Amazon Resource Name (ARN) of the monitoring schedule.
	MonitoringScheduleArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeNotebookInstanceInput struct {
	// The name of the notebook instance that you want information about.
	NotebookInstanceName *string
}

type DescribeNotebookInstanceLifecycleConfigInput struct {
	// The name of the lifecycle configuration to describe.
	NotebookInstanceLifecycleConfigName *string
}

type DescribeNotebookInstanceLifecycleConfigOutput struct {
	// The shell script that runs every time you start a notebook instance, including
	// when you create the notebook instance.
	OnStart []*types.NotebookInstanceLifecycleHook
	// A timestamp that tells when the lifecycle configuration was last modified.
	LastModifiedTime *time.Time
	// A timestamp that tells when the lifecycle configuration was created.
	CreationTime *time.Time
	// The Amazon Resource Name (ARN) of the lifecycle configuration.
	NotebookInstanceLifecycleConfigArn *string
	// The shell script that runs only once, when you create a notebook instance.
	OnCreate []*types.NotebookInstanceLifecycleHook
	// The name of the lifecycle configuration.
	NotebookInstanceLifecycleConfigName *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeNotebookInstanceOutput struct {
	// Whether root access is enabled or disabled for users of the notebook instance.
	// Lifecycle configurations need root access to be able to set up a notebook
	// instance. Because of this, lifecycle configurations associated with a notebook
	// instance always run with root access even if you disable root access for users.
	RootAccess types.RootAccess
	// The name of the Amazon SageMaker notebook instance.
	NotebookInstanceName *string
	// A timestamp. Use this parameter to return the time when the notebook instance
	// was created
	CreationTime *time.Time
	// A timestamp. Use this parameter to retrieve the time when the notebook instance
	// was last modified.
	LastModifiedTime *time.Time
	// The URL that you use to connect to the Jupyter notebook that is running in your
	// notebook instance.
	Url *string
	// The network interface IDs that Amazon SageMaker created at the time of creating
	// the instance.
	NetworkInterfaceId *string
	// A list of the Elastic Inference (EI) instance types associated with this
	// notebook instance. Currently only one EI instance type can be associated with a
	// notebook instance. For more information, see Using Elastic Inference in Amazon
	// SageMaker (https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html).
	AcceleratorTypes []types.NotebookInstanceAcceleratorType
	// The Amazon Resource Name (ARN) of the IAM role associated with the instance.
	RoleArn *string
	// The size, in GB, of the ML storage volume attached to the notebook instance.
	VolumeSizeInGB *int32
	// Returns the name of a notebook instance lifecycle configuration. 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
	// Describes whether Amazon SageMaker provides internet access to the notebook
	// instance. If this value is set to Disabled, the notebook instance does not have
	// internet access, and cannot connect to Amazon SageMaker training and endpoint
	// services. For more information, see Notebook Instances Are Internet-Enabled by
	// Default
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access).
	DirectInternetAccess types.DirectInternetAccess
	// The Amazon Resource Name (ARN) of the notebook instance.
	NotebookInstanceArn *string
	// The AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the
	// ML storage volume attached to the instance.
	KmsKeyId *string
	// The ID of the VPC subnet.
	SubnetId *string
	// An array of up to three Git repositories associated with the notebook instance.
	// These can be either the names of Git repositories stored as resources in your
	// account, or the URL of Git repositories in AWS CodeCommit
	// (https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any
	// other Git repository. These repositories are cloned at the same level as the
	// default repository of your notebook instance. For more information, see
	// Associating Git Repositories with Amazon SageMaker Notebook Instances
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html).
	AdditionalCodeRepositories []*string
	// The type of ML compute instance running on the notebook instance.
	InstanceType types.InstanceType
	// The IDs of the VPC security groups.
	SecurityGroups []*string
	// The Git repository associated with the notebook instance as its default code
	// repository. This can be either the name of a Git repository stored as a resource
	// in your account, or the URL of a Git repository in AWS CodeCommit
	// (https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any
	// other Git repository. When you open a notebook instance, it opens in the
	// directory that contains this repository. For more information, see Associating
	// Git Repositories with Amazon SageMaker Notebook Instances
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html).
	DefaultCodeRepository *string
	// The status of the notebook instance.
	NotebookInstanceStatus types.NotebookInstanceStatus
	// If status is Failed, the reason it failed.
	FailureReason *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeProcessingJobInput struct {
	// The name of the processing job. The name must be unique within an AWS Region in
	// the AWS account.
	ProcessingJobName *string
}

type DescribeProcessingJobOutput struct {
	// The ARN of a monitoring schedule for an endpoint associated with this processing
	// job.
	MonitoringScheduleArn *string
	// The time at which the processing job started.
	ProcessingStartTime *time.Time
	// The configuration information used to create an experiment.
	ExperimentConfig *types.ExperimentConfig
	// The time limit for how long the processing job is allowed to run.
	StoppingCondition *types.ProcessingStoppingCondition
	// 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 *types.ProcessingResources
	// Networking options for a processing job.
	NetworkConfig *types.NetworkConfig
	// The ARN of an AutoML job associated with this processing job.
	AutoMLJobArn *string
	// A string, up to one KB in size, that contains the reason a processing job
	// failed, if it failed.
	FailureReason *string
	// The ARN of a training job associated with this processing job.
	TrainingJobArn *string
	// The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume
	// to perform tasks on your behalf.
	RoleArn *string
	// The time at which the processing job completed.
	ProcessingEndTime *time.Time
	// The inputs for a processing job.
	ProcessingInputs []*types.ProcessingInput
	// The name of the processing job. The name must be unique within an AWS Region in
	// the AWS account.
	ProcessingJobName *string
	// The Amazon Resource Name (ARN) of the processing job.
	ProcessingJobArn *string
	// An optional string, up to one KB in size, that contains metadata from the
	// processing container when the processing job exits.
	ExitMessage *string
	// Provides the status of a processing job.
	ProcessingJobStatus types.ProcessingJobStatus
	// Configures the processing job to run a specified container image.
	AppSpecification *types.AppSpecification
	// Output configuration for the processing job.
	ProcessingOutputConfig *types.ProcessingOutputConfig
	// The time at which the processing job was created.
	CreationTime *time.Time
	// The environment variables set in the Docker container.
	Environment map[string]*string
	// The time at which the processing job was last modified.
	LastModifiedTime *time.Time

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeSubscribedWorkteamInput struct {
	// The Amazon Resource Name (ARN) of the subscribed work team to describe.
	WorkteamArn *string
}

type DescribeSubscribedWorkteamOutput struct {
	// A Workteam instance that contains information about the work team.
	SubscribedWorkteam *types.SubscribedWorkteam

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeTrainingJobInput struct {
	// The name of the training job.
	TrainingJobName *string
}

type DescribeTrainingJobOutput struct {
	// Configuration of storage locations for TensorBoard output.
	TensorBoardOutputConfig *types.TensorBoardOutputConfig
	// If the training job failed, the reason it failed.
	FailureReason *string
	// The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job
	// that created the transform or training job.
	LabelingJobArn *string
	// If you want to allow inbound or outbound network calls, except for calls between
	// peers within a training cluster for distributed training, choose True. If you
	// enable network isolation 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
	// 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
	// Contains information about the output location for managed spot training
	// checkpoint data.
	CheckpointConfig *types.CheckpointConfig
	// A timestamp that indicates when the training job was created.
	CreationTime *time.Time
	// A timestamp that indicates when the status of the training job was last
	// modified.
	LastModifiedTime *time.Time
	// Resources, including ML compute instances and ML storage volumes, that are
	// configured for model training.
	ResourceConfig *types.ResourceConfig
	// A collection of MetricData objects that specify the names, values, and dates and
	// times that the training algorithm emitted to Amazon CloudWatch.
	FinalMetricDataList []*types.MetricData
	// Name of the model training job.
	TrainingJobName *string
	// Provides detailed information about the state of the training job. For detailed
	// information on 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.
	//
	//     * Interrupted - The job stopped because the managed spot training
	// instances were interrupted.
	//
	//     * 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.
	//
	//     *
	// MaxWaitTmeExceeded - The job stopped because it exceeded the maximum allowed
	// wait time.
	//
	//     * Stopped - The training job has stopped.
	//
	// Stopping
	//
	//     *
	// Stopping - Stopping the training job.
	//
	//     <important> <p>Valid values for
	// <code>SecondaryStatus</code> are subject to change. </p> </important> <p>We no
	// longer support the following secondary statuses:</p> <ul> <li> <p>
	// <code>LaunchingMLInstances</code> </p> </li> <li> <p>
	// <code>PreparingTrainingStack</code> </p> </li> <li> <p>
	// <code>DownloadingTrainingImage</code> </p> </li> </ul>
	SecondaryStatus types.SecondaryStatus
	// An array of Channel objects that describes each data input channel.
	InputDataConfig []*types.Channel
	// The billable time in seconds. You can calculate the savings from using managed
	// spot training using the formula (1 - BillableTimeInSeconds /
	// TrainingTimeInSeconds) * 100. For example, if BillableTimeInSeconds is 100 and
	// TrainingTimeInSeconds is 500, the savings is 80%.
	BillableTimeInSeconds *int32
	// The AWS Identity and Access Management (IAM) role configured for the training
	// job.
	RoleArn *string
	// Information about the Amazon S3 location that is configured for storing model
	// artifacts.
	ModelArtifacts *types.ModelArtifacts
	// Specifies a limit to how long a model training job can run. It also specifies
	// the maximum time to wait for a spot instance. 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 *types.StoppingCondition
	// Associates a SageMaker job as a trial component with an experiment and trial.
	// Specified when you call the following APIs:
	//
	//     * CreateProcessingJob ()
	//
	//     *
	// CreateTrainingJob ()
	//
	//     * CreateTransformJob ()
	ExperimentConfig *types.ExperimentConfig
	// The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
	// the training job was launched by a hyperparameter tuning job.
	TuningJobArn *string
	// Configuration information for debugging rules.
	DebugRuleConfigurations []*types.DebugRuleConfiguration
	// The Amazon Resource Name (ARN) of an AutoML job.
	AutoMLJobArn *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 algorithms in distributed training.
	EnableInterContainerTrafficEncryption *bool
	// 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 *types.VpcConfig
	// The status of the training job. Amazon SageMaker provides the following training
	// job statuses:
	//
	//     * 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 types.TrainingJobStatus
	// A history of all of the secondary statuses that the training job has
	// transitioned through.
	SecondaryStatusTransitions []*types.SecondaryStatusTransition
	// A Boolean indicating whether managed spot training is enabled (True) or not
	// (False).
	EnableManagedSpotTraining *bool
	// Configuration information for the debug hook parameters, collection
	// configuration, and storage paths.
	DebugHookConfig *types.DebugHookConfig
	// The S3 path where model artifacts that you configured when creating the job are
	// stored. Amazon SageMaker creates subfolders for model artifacts.
	OutputDataConfig *types.OutputDataConfig
	// Information about the algorithm used for training, and algorithm metadata.
	AlgorithmSpecification *types.AlgorithmSpecification
	// 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 Amazon Resource Name (ARN) of the training job.
	TrainingJobArn *string
	// The training time in seconds.
	TrainingTimeInSeconds *int32
	// Status about the debug rule evaluation.
	DebugRuleEvaluationStatuses []*types.DebugRuleEvaluationStatus
	// Algorithm-specific parameters.
	HyperParameters map[string]*string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeTransformJobInput struct {
	// The name of the transform job that you want to view details of.
	TransformJobName *string
}

type DescribeTransformJobOutput struct {
	// The name of the model used in the transform job.
	ModelName *string
	// A timestamp that shows when the transform Job was created.
	CreationTime *time.Time
	// 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. To enable the batch
	// strategy, you must set SplitType to Line, RecordIO, or TFRecord.
	BatchStrategy types.BatchStrategy
	// The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job
	// that created the transform or training job.
	LabelingJobArn *string
	// The name of the transform job.
	TransformJobName *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 *types.ExperimentConfig
	// The maximum payload size, in MB, used in the transform job.
	MaxPayloadInMB *int32
	// If the transform job failed, FailureReason describes why it failed. A transform
	// job creates a log file, which includes error messages, and stores it as an
	// Amazon S3 object. For more information, see Log Amazon SageMaker Events with
	// Amazon CloudWatch
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/logging-cloudwatch.html).
	FailureReason *string
	// The Amazon Resource Name (ARN) of the AutoML transform job.
	AutoMLJobArn *string
	// The status of the transform job. If the transform job failed, the reason is
	// returned in the FailureReason field.
	TransformJobStatus types.TransformJobStatus
	// 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
	// <code>TransformStartTime</code>.</p>
	TransformEndTime *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 *types.DataProcessing
	// The maximum number of parallel requests on each instance node that can be
	// launched in a transform job. The default value is 1.
	MaxConcurrentTransforms *int32
	// Describes the resources, including ML instance types and ML instance count, to
	// use for the transform job.
	TransformResources *types.TransformResources
	// Describes the dataset to be transformed and the Amazon S3 location where it is
	// stored.
	TransformInput *types.TransformInput
	// 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
	// The Amazon Resource Name (ARN) of the transform job.
	TransformJobArn *string
	// The timeout and maximum number of retries for processing a transform job
	// invocation.
	ModelClientConfig *types.ModelClientConfig
	// 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
	// Identifies the Amazon S3 location where you want Amazon SageMaker to save the
	// results from the transform job.
	TransformOutput *types.TransformOutput

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeTrialComponentInput struct {
	// The name of the trial component to describe.
	TrialComponentName *string
}

type DescribeTrialComponentOutput struct {
	// When the component started.
	StartTime *time.Time
	// The metrics for the component.
	Metrics []*types.TrialComponentMetricSummary
	// The hyperparameters of the component.
	Parameters map[string]*types.TrialComponentParameterValue
	// Who last modified the component.
	LastModifiedBy *types.UserContext
	// The Amazon Resource Name (ARN) of the source and, optionally, the job type.
	Source *types.TrialComponentSource
	// The name of the trial component.
	TrialComponentName *string
	// When the component ended.
	EndTime *time.Time
	// The input artifacts of the component.
	InputArtifacts map[string]*types.TrialComponentArtifact
	// The output artifacts of the component.
	OutputArtifacts map[string]*types.TrialComponentArtifact
	// Who created the component.
	CreatedBy *types.UserContext
	// The status of the component. States include:
	//
	//     * InProgress
	//
	//     *
	// Completed
	//
	//     * Failed
	Status *types.TrialComponentStatus
	// The name of the component as displayed. If DisplayName isn't specified,
	// TrialComponentName is displayed.
	DisplayName *string
	// When the component was last modified.
	LastModifiedTime *time.Time
	// When the component was created.
	CreationTime *time.Time
	// The Amazon Resource Name (ARN) of the trial component.
	TrialComponentArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeTrialInput struct {
	// The name of the trial to describe.
	TrialName *string
}

type DescribeTrialOutput struct {
	// When the trial was last modified.
	LastModifiedTime *time.Time
	// The name of the trial as displayed. If DisplayName isn't specified, TrialName is
	// displayed.
	DisplayName *string
	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string
	// When the trial was created.
	CreationTime *time.Time
	// The name of the experiment the trial is part of.
	ExperimentName *string
	// The name of the trial.
	TrialName *string
	// Who created the trial.
	CreatedBy *types.UserContext
	// Who last modified the trial.
	LastModifiedBy *types.UserContext
	// The Amazon Resource Name (ARN) of the source and, optionally, the job type.
	Source *types.TrialSource

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeUserProfileInput struct {
	// The user profile name.
	UserProfileName *string
	// The domain ID.
	DomainId *string
}

type DescribeUserProfileOutput struct {
	// The user profile Amazon Resource Name (ARN).
	UserProfileArn *string
	// The SSO user value.
	SingleSignOnUserValue *string
	// The ID of the user's profile in the Amazon Elastic File System (EFS) volume.
	HomeEfsFileSystemUid *string
	// The failure reason.
	FailureReason *string
	// A collection of settings.
	UserSettings *types.UserSettings
	// The SSO user identifier.
	SingleSignOnUserIdentifier *string
	// The ID of the domain that contains the profile.
	DomainId *string
	// The status.
	Status types.UserProfileStatus
	// The user profile name.
	UserProfileName *string
	// The last modified time.
	LastModifiedTime *time.Time
	// The creation time.
	CreationTime *time.Time

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeWorkforceInput struct {
	// The name of the private workforce whose access you want to restrict.
	// WorkforceName is automatically set to default when a workforce is created and
	// cannot be modified.
	WorkforceName *string
}

type DescribeWorkforceOutput struct {
	// A single private workforce, which is automatically created when you create your
	// first private work team. You can create one private work force in each AWS
	// Region. By default, any workforce-related API operation used in a specific
	// region will apply to the workforce created in that region. To learn how to
	// create a private workforce, see Create a Private Workforce
	// (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html).
	Workforce *types.Workforce

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DescribeWorkteamInput struct {
	// The name of the work team to return a description of.
	WorkteamName *string
}

type DescribeWorkteamOutput struct {
	// A Workteam instance that contains information about the work team.
	Workteam *types.Workteam

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type DisassociateTrialComponentInput struct {
	// The name of the trial to disassociate from.
	TrialName *string
	// The name of the component to disassociate from the trial.
	TrialComponentName *string
}

type DisassociateTrialComponentOutput struct {
	// The ARN of the trial component.
	TrialComponentArn *string
	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type EndpointResolver interface {
	ResolveEndpoint(region string, options ResolverOptions) (aws.Endpoint, error)
}

type EndpointResolverFunc func(region string, options ResolverOptions) (aws.Endpoint, error)

type GetSearchSuggestionsInput struct {
	// Limits the property names that are included in the response.
	SuggestionQuery *types.SuggestionQuery
	// The name of the Amazon SageMaker resource to search for.
	Resource types.ResourceType
}

type GetSearchSuggestionsOutput struct {
	// A list of property names for a Resource that match a SuggestionQuery.
	PropertyNameSuggestions []*types.PropertyNameSuggestion

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type HTTPClient interface {
	Do(*http.Request) (*http.Response, error)
}

type HTTPSignerV4 interface {
	SignHTTP(ctx context.Context, credentials aws.Credentials, r *http.Request, payloadHash string, service string, region string, signingTime time.Time) error
}

type ListAlgorithmsInput struct {
	// The sort order for the results. The default is Ascending.
	SortOrder types.SortOrder
	// A string in the algorithm name. This filter returns only algorithms whose name
	// contains the specified string.
	NameContains *string
	// A filter that returns only algorithms created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time
	// A filter that returns only algorithms created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time
	// The maximum number of algorithms to return in the response.
	MaxResults *int32
	// If the response to a previous ListAlgorithms request was truncated, the response
	// includes a NextToken. To retrieve the next set of algorithms, use the token in
	// the next request.
	NextToken *string
	// The parameter by which to sort the results. The default is CreationTime.
	SortBy types.AlgorithmSortBy
}

type ListAlgorithmsOutput struct {
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of algorithms, use it in the subsequent request.
	NextToken *string
	// >An array of AlgorithmSummary objects, each of which lists an algorithm.
	AlgorithmSummaryList []*types.AlgorithmSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListAppsInput struct {
	// The sort order for the results. The default is Ascending.
	SortOrder types.SortOrder
	// A parameter to search by user profile name.
	UserProfileNameEquals *string
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string
	// Returns a list up to a specified limit.
	MaxResults *int32
	// The parameter by which to sort the results. The default is CreationTime.
	SortBy types.AppSortKey
	// A parameter to search for the domain ID.
	DomainIdEquals *string
}

type ListAppsOutput struct {
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string
	// The list of apps.
	Apps []*types.AppDetails

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListAutoMLJobsInput struct {
	// The parameter by which to sort the results. The default is AutoMLJobName.
	SortBy types.AutoMLSortBy
	// Request a list of jobs, using a filter for time.
	CreationTimeBefore *time.Time
	// Request a list of jobs, using a filter for status.
	StatusEquals types.AutoMLJobStatus
	// Request a list of jobs, using a filter for time.
	LastModifiedTimeBefore *time.Time
	// Request a list of jobs, using a filter for time.
	CreationTimeAfter *time.Time
	// Request a list of jobs, using a search filter for name.
	NameContains *string
	// The sort order for the results. The default is Descending.
	SortOrder types.AutoMLSortOrder
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string
	// Request a list of jobs, using a filter for time.
	LastModifiedTimeAfter *time.Time
	// Request a list of jobs up to a specified limit.
	MaxResults *int32
}

type ListAutoMLJobsOutput struct {
	// Returns a summary list of jobs.
	AutoMLJobSummaries []*types.AutoMLJobSummary
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListCandidatesForAutoMLJobInput struct {
	// List the Candidates for the job and filter by status.
	StatusEquals types.CandidateStatus
	// The parameter by which to sort the results. The default is Descending.
	SortBy types.CandidateSortBy
	// The sort order for the results. The default is Ascending.
	SortOrder types.AutoMLSortOrder
	// List the job's Candidates up to a specified limit.
	MaxResults *int32
	// List the Candidates created for the job by providing the job's name.
	AutoMLJobName *string
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string
	// List the Candidates for the job and filter by candidate name.
	CandidateNameEquals *string
}

type ListCandidatesForAutoMLJobOutput struct {
	// Summaries about the Candidates.
	Candidates []*types.AutoMLCandidate
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListCodeRepositoriesInput struct {
	// A filter that returns only Git repositories that were last modified after the
	// specified time.
	LastModifiedTimeAfter *time.Time
	// A string in the Git repositories name. This filter returns only repositories
	// whose name contains the specified string.
	NameContains *string
	// A filter that returns only Git repositories that were last modified before the
	// specified time.
	LastModifiedTimeBefore *time.Time
	// A filter that returns only Git repositories that were created before the
	// specified time.
	CreationTimeBefore *time.Time
	// A filter that returns only Git repositories that were created after the
	// specified time.
	CreationTimeAfter *time.Time
	// The sort order for results. The default is Ascending.
	SortOrder types.CodeRepositorySortOrder
	// If the result of a ListCodeRepositoriesOutput request was truncated, the
	// response includes a NextToken. To get the next set of Git repositories, use the
	// token in the next request.
	NextToken *string
	// The maximum number of Git repositories to return in the response.
	MaxResults *int32
	// The field to sort results by. The default is Name.
	SortBy types.CodeRepositorySortBy
}

type ListCodeRepositoriesOutput struct {
	// If the result of a ListCodeRepositoriesOutput request was truncated, the
	// response includes a NextToken. To get the next set of Git repositories, use the
	// token in the next request.
	NextToken *string
	// Gets a list of summaries of the Git repositories. Each summary specifies the
	// following values for the repository:
	//
	//     * Name
	//
	//     * Amazon Resource Name
	// (ARN)
	//
	//     * Creation time
	//
	//     * Last modified time
	//
	//     * Configuration
	// information, including the URL location of the repository and the ARN of the AWS
	// Secrets Manager secret that contains the credentials used to access the
	// repository.
	CodeRepositorySummaryList []*types.CodeRepositorySummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListCompilationJobsInput struct {
	// If the result of the previous ListCompilationJobs request was truncated, the
	// response includes a NextToken. To retrieve the next set of model compilation
	// jobs, use the token in the next request.
	NextToken *string
	// A filter that returns the model compilation jobs that were created after a
	// specified time.
	CreationTimeAfter *time.Time
	// A filter that returns the model compilation jobs that were modified before a
	// specified time.
	LastModifiedTimeBefore *time.Time
	// The field by which to sort results. The default is CreationTime.
	SortBy types.ListCompilationJobsSortBy
	// A filter that returns the model compilation jobs whose name contains a specified
	// string.
	NameContains *string
	// The maximum number of model compilation jobs to return in the response.
	MaxResults *int32
	// A filter that returns the model compilation jobs that were modified after a
	// specified time.
	LastModifiedTimeAfter *time.Time
	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
	// A filter that retrieves model compilation jobs with a specific
	// DescribeCompilationJobResponse$CompilationJobStatus () status.
	StatusEquals types.CompilationJobStatus
	// A filter that returns the model compilation jobs that were created before a
	// specified time.
	CreationTimeBefore *time.Time
}

type ListCompilationJobsOutput struct {
	// An array of CompilationJobSummary () objects, each describing a model
	// compilation job.
	CompilationJobSummaries []*types.CompilationJobSummary
	// If the response is truncated, Amazon SageMaker returns this NextToken. To
	// retrieve the next set of model compilation jobs, use this token in the next
	// request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListDomainsInput struct {
	// Returns a list up to a specified limit.
	MaxResults *int32
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string
}

type ListDomainsOutput struct {
	// The list of domains.
	Domains []*types.DomainDetails
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListEndpointConfigsInput struct {
	// A filter that returns only endpoint configurations created before the specified
	// time (timestamp).
	CreationTimeBefore *time.Time
	// A string in the endpoint configuration name. This filter returns only endpoint
	// configurations whose name contains the specified string.
	NameContains *string
	// A filter that returns only endpoint configurations with a creation time greater
	// than or equal to the specified time (timestamp).
	CreationTimeAfter *time.Time
	// If the result of the previous ListEndpointConfig request was truncated, the
	// response includes a NextToken. To retrieve the next set of endpoint
	// configurations, use the token in the next request.
	NextToken *string
	// The maximum number of training jobs to return in the response.
	MaxResults *int32
	// The field to sort results by. The default is CreationTime.
	SortBy types.EndpointConfigSortKey
	// The sort order for results. The default is Descending.
	SortOrder types.OrderKey
}

type ListEndpointConfigsOutput struct {
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of endpoint configurations, use it in the subsequent request
	NextToken *string
	// An array of endpoint configurations.
	EndpointConfigs []*types.EndpointConfigSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListEndpointsInput struct {
	// A filter that returns only endpoints with the specified status.
	StatusEquals types.EndpointStatus
	// A filter that returns only endpoints that were modified after the specified
	// timestamp.
	LastModifiedTimeAfter *time.Time
	// Sorts the list of results. The default is CreationTime.
	SortBy types.EndpointSortKey
	// A filter that returns only endpoints that were created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time
	// If the result of a ListEndpoints request was truncated, the response includes a
	// NextToken. To retrieve the next set of endpoints, use the token in the next
	// request.
	NextToken *string
	// The maximum number of endpoints to return in the response.
	MaxResults *int32
	// A string in endpoint names. This filter returns only endpoints whose name
	// contains the specified string.
	NameContains *string
	// The sort order for results. The default is Descending.
	SortOrder types.OrderKey
	// A filter that returns only endpoints with a creation time greater than or equal
	// to the specified time (timestamp).
	CreationTimeAfter *time.Time
	// A filter that returns only endpoints that were modified before the specified
	// timestamp.
	LastModifiedTimeBefore *time.Time
}

type ListEndpointsOutput struct {
	// An array or endpoint objects.
	Endpoints []*types.EndpointSummary
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of training jobs, use it in the subsequent request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListExperimentsInput struct {
	// The sort order. The default value is Descending.
	SortOrder types.SortOrder
	// A filter that returns only experiments created before the specified time.
	CreatedBefore *time.Time
	// A filter that returns only experiments created after the specified time.
	CreatedAfter *time.Time
	// The property used to sort results. The default value is CreationTime.
	SortBy types.SortExperimentsBy
	// If the previous call to ListExperiments didn't return the full set of
	// experiments, the call returns a token for getting the next set of experiments.
	NextToken *string
	// The maximum number of experiments to return in the response. The default value
	// is 10.
	MaxResults *int32
}

type ListExperimentsOutput struct {
	// A token for getting the next set of experiments, if there are any.
	NextToken *string
	// A list of the summaries of your experiments.
	ExperimentSummaries []*types.ExperimentSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListFlowDefinitionsInput struct {
	// A token to resume pagination.
	NextToken *string
	// An optional value that specifies whether you want the results sorted in
	// Ascending or Descending order.
	SortOrder types.SortOrder
	// A filter that returns only flow definitions with a creation time greater than or
	// equal to the specified timestamp.
	CreationTimeAfter *time.Time
	// The total number of items to return. If the total number of available items is
	// more than the value specified in MaxResults, then a NextToken will be provided
	// in the output that you can use to resume pagination.
	MaxResults *int32
	// A filter that returns only flow definitions that were created before the
	// specified timestamp.
	CreationTimeBefore *time.Time
}

type ListFlowDefinitionsOutput struct {
	// A token to resume pagination.
	NextToken *string
	// An array of objects describing the flow definitions.
	FlowDefinitionSummaries []*types.FlowDefinitionSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListHumanTaskUisInput struct {
	// The total number of items to return. If the total number of available items is
	// more than the value specified in MaxResults, then a NextToken will be provided
	// in the output that you can use to resume pagination.
	MaxResults *int32
	// A filter that returns only human task user interfaces that were created before
	// the specified timestamp.
	CreationTimeBefore *time.Time
	// An optional value that specifies whether you want the results sorted in
	// Ascending or Descending order.
	SortOrder types.SortOrder
	// A token to resume pagination.
	NextToken *string
	// A filter that returns only human task user interfaces with a creation time
	// greater than or equal to the specified timestamp.
	CreationTimeAfter *time.Time
}

type ListHumanTaskUisOutput struct {
	// An array of objects describing the human task user interfaces.
	HumanTaskUiSummaries []*types.HumanTaskUiSummary
	// A token to resume pagination.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListHyperParameterTuningJobsInput struct {
	// A filter that returns only tuning jobs that were created after the specified
	// time.
	CreationTimeAfter *time.Time
	// If the result of the previous ListHyperParameterTuningJobs request was
	// truncated, the response includes a NextToken. To retrieve the next set of tuning
	// jobs, use the token in the next request.
	NextToken *string
	// A string in the tuning job name. This filter returns only tuning jobs whose name
	// contains the specified string.
	NameContains *string
	// A filter that returns only tuning jobs that were created before the specified
	// time.
	CreationTimeBefore *time.Time
	// A filter that returns only tuning jobs that were modified before the specified
	// time.
	LastModifiedTimeBefore *time.Time
	// The maximum number of tuning jobs to return. The default value is 10.
	MaxResults *int32
	// A filter that returns only tuning jobs with the specified status.
	StatusEquals types.HyperParameterTuningJobStatus
	// A filter that returns only tuning jobs that were modified after the specified
	// time.
	LastModifiedTimeAfter *time.Time
	// The field to sort results by. The default is Name.
	SortBy types.HyperParameterTuningJobSortByOptions
	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
}

type ListHyperParameterTuningJobsOutput struct {
	// If the result of this ListHyperParameterTuningJobs request was truncated, the
	// response includes a NextToken. To retrieve the next set of tuning jobs, use the
	// token in the next request.
	NextToken *string
	// A list of HyperParameterTuningJobSummary () objects that describe the tuning
	// jobs that the ListHyperParameterTuningJobs request returned.
	HyperParameterTuningJobSummaries []*types.HyperParameterTuningJobSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListLabelingJobsForWorkteamInput struct {
	// The field to sort results by. The default is CreationTime.
	SortBy types.ListLabelingJobsForWorkteamSortByOptions
	// A filter the limits jobs to only the ones whose job reference code contains the
	// specified string.
	JobReferenceCodeContains *string
	// If the result of the previous ListLabelingJobsForWorkteam request was truncated,
	// the response includes a NextToken. To retrieve the next set of labeling jobs,
	// use the token in the next request.
	NextToken *string
	// The maximum number of labeling jobs to return in each page of the response.
	MaxResults *int32
	// A filter that returns only labeling jobs created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time
	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
	// A filter that returns only labeling jobs created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time
	// The Amazon Resource Name (ARN) of the work team for which you want to see
	// labeling jobs for.
	WorkteamArn *string
}

type ListLabelingJobsForWorkteamOutput struct {
	// An array of LabelingJobSummary objects, each describing a labeling job.
	LabelingJobSummaryList []*types.LabelingJobForWorkteamSummary
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of labeling jobs, use it in the subsequent request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListLabelingJobsInput struct {
	// A string in the labeling job name. This filter returns only labeling jobs whose
	// name contains the specified string.
	NameContains *string
	// If the result of the previous ListLabelingJobs request was truncated, the
	// response includes a NextToken. To retrieve the next set of labeling jobs, use
	// the token in the next request.
	NextToken *string
	// A filter that returns only labeling jobs created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time
	// The field to sort results by. The default is CreationTime.
	SortBy types.SortBy
	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
	// A filter that retrieves only labeling jobs with a specific status.
	StatusEquals types.LabelingJobStatus
	// A filter that returns only labeling jobs modified after the specified time
	// (timestamp).
	LastModifiedTimeAfter *time.Time
	// The maximum number of labeling jobs to return in each page of the response.
	MaxResults *int32
	// A filter that returns only labeling jobs created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time
	// A filter that returns only labeling jobs modified before the specified time
	// (timestamp).
	LastModifiedTimeBefore *time.Time
}

type ListLabelingJobsOutput struct {
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of labeling jobs, use it in the subsequent request.
	NextToken *string
	// An array of LabelingJobSummary objects, each describing a labeling job.
	LabelingJobSummaryList []*types.LabelingJobSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListModelPackagesInput struct {
	// The maximum number of model packages to return in the response.
	MaxResults *int32
	// The sort order for the results. The default is Ascending.
	SortOrder types.SortOrder
	// The parameter by which to sort the results. The default is CreationTime.
	SortBy types.ModelPackageSortBy
	// A filter that returns only model packages created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time
	// A filter that returns only model packages created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time
	// If the response to a previous ListModelPackages request was truncated, the
	// response includes a NextToken. To retrieve the next set of model packages, use
	// the token in the next request.
	NextToken *string
	// A string in the model package name. This filter returns only model packages
	// whose name contains the specified string.
	NameContains *string
}

type ListModelPackagesOutput struct {
	// An array of ModelPackageSummary objects, each of which lists a model package.
	ModelPackageSummaryList []*types.ModelPackageSummary
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of model packages, use it in the subsequent request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListModelsInput struct {
	// A filter that returns only models with a creation time greater than or equal to
	// the specified time (timestamp).
	CreationTimeAfter *time.Time
	// If the response to a previous ListModels request was truncated, the response
	// includes a NextToken. To retrieve the next set of models, use the token in the
	// next request.
	NextToken *string
	// A string in the training job name. This filter returns only models in the
	// training job whose name contains the specified string.
	NameContains *string
	// A filter that returns only models created before the specified time (timestamp).
	CreationTimeBefore *time.Time
	// The maximum number of models to return in the response.
	MaxResults *int32
	// Sorts the list of results. The default is CreationTime.
	SortBy types.ModelSortKey
	// The sort order for results. The default is Descending.
	SortOrder types.OrderKey
}

type ListModelsOutput struct {
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of models, use it in the subsequent request.
	NextToken *string
	// An array of ModelSummary objects, each of which lists a model.
	Models []*types.ModelSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListMonitoringExecutionsInput struct {
	// Whether to sort the results in Ascending or Descending order. The default is
	// Descending.
	SortOrder types.SortOrder
	// A filter that returns only jobs modified after a specified time.
	LastModifiedTimeBefore *time.Time
	// A filter that returns only jobs modified before a specified time.
	LastModifiedTimeAfter *time.Time
	// Filter for jobs scheduled after a specified time.
	ScheduledTimeAfter *time.Time
	// The maximum number of jobs to return in the response. The default value is 10.
	MaxResults *int32
	// Filter for jobs scheduled before a specified time.
	ScheduledTimeBefore *time.Time
	// Whether to sort results by Status, CreationTime, ScheduledTime field. The
	// default is CreationTime.
	SortBy types.MonitoringExecutionSortKey
	// The token returned if the response is truncated. To retrieve the next set of job
	// executions, use it in the next request.
	NextToken *string
	// Name of a specific endpoint to fetch jobs for.
	EndpointName *string
	// Name of a specific schedule to fetch jobs for.
	MonitoringScheduleName *string
	// A filter that returns only jobs created before a specified time.
	CreationTimeBefore *time.Time
	// A filter that retrieves only jobs with a specific status.
	StatusEquals types.ExecutionStatus
	// A filter that returns only jobs created after a specified time.
	CreationTimeAfter *time.Time
}

type ListMonitoringExecutionsOutput struct {
	// A JSON array in which each element is a summary for a monitoring execution.
	MonitoringExecutionSummaries []*types.MonitoringExecutionSummary
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of jobs, use it in the subsequent reques
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListMonitoringSchedulesInput struct {
	// The maximum number of jobs to return in the response. The default value is 10.
	MaxResults *int32
	// A filter that returns only monitoring schedules modified after a specified time.
	LastModifiedTimeAfter *time.Time
	// Name of a specific endpoint to fetch schedules for.
	EndpointName *string
	// Whether to sort results by Status, CreationTime, ScheduledTime field. The
	// default is CreationTime.
	SortBy types.MonitoringScheduleSortKey
	// Whether to sort the results in Ascending or Descending order. The default is
	// Descending.
	SortOrder types.SortOrder
	// The token returned if the response is truncated. To retrieve the next set of job
	// executions, use it in the next request.
	NextToken *string
	// A filter that returns only monitoring schedules created after a specified time.
	CreationTimeAfter *time.Time
	// Filter for monitoring schedules whose name contains a specified string.
	NameContains *string
	// A filter that returns only monitoring schedules created before a specified time.
	CreationTimeBefore *time.Time
	// A filter that returns only monitoring schedules modified before a specified
	// time.
	StatusEquals types.ScheduleStatus
	// A filter that returns only monitoring schedules modified before a specified
	// time.
	LastModifiedTimeBefore *time.Time
}

type ListMonitoringSchedulesOutput struct {
	// A JSON array in which each element is a summary for a monitoring schedule.
	MonitoringScheduleSummaries []*types.MonitoringScheduleSummary
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of jobs, use it in the subsequent reques
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListNotebookInstanceLifecycleConfigsInput struct {
	// The maximum number of lifecycle configurations to return in the response.
	MaxResults *int32
	// A filter that returns only lifecycle configurations that were modified after the
	// specified time (timestamp).
	LastModifiedTimeAfter *time.Time
	// A filter that returns only lifecycle configurations that were created before the
	// specified time (timestamp).
	CreationTimeBefore *time.Time
	// A filter that returns only lifecycle configurations that were modified before
	// the specified time (timestamp).
	LastModifiedTimeBefore *time.Time
	// If the result of a ListNotebookInstanceLifecycleConfigs request was truncated,
	// the response includes a NextToken. To get the next set of lifecycle
	// configurations, use the token in the next request.
	NextToken *string
	// A filter that returns only lifecycle configurations that were created after the
	// specified time (timestamp).
	CreationTimeAfter *time.Time
	// A string in the lifecycle configuration name. This filter returns only lifecycle
	// configurations whose name contains the specified string.
	NameContains *string
	// Sorts the list of results. The default is CreationTime.
	SortBy types.NotebookInstanceLifecycleConfigSortKey
	// The sort order for results.
	SortOrder types.NotebookInstanceLifecycleConfigSortOrder
}

type ListNotebookInstanceLifecycleConfigsOutput struct {
	// An array of NotebookInstanceLifecycleConfiguration objects, each listing a
	// lifecycle configuration.
	NotebookInstanceLifecycleConfigs []*types.NotebookInstanceLifecycleConfigSummary
	// If the response is truncated, Amazon SageMaker returns this token. To get the
	// next set of lifecycle configurations, use it in the next request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListNotebookInstancesInput struct {
	// A filter that returns only notebook instances that were modified before the
	// specified time (timestamp).
	LastModifiedTimeBefore *time.Time
	// A string in the name of a notebook instances lifecycle configuration associated
	// with this notebook instance. This filter returns only notebook instances
	// associated with a lifecycle configuration with a name that contains the
	// specified string.
	NotebookInstanceLifecycleConfigNameContains *string
	// If the previous call to the ListNotebookInstances is truncated, the response
	// includes a NextToken. You can use this token in your subsequent
	// ListNotebookInstances request to fetch the next set of notebook instances. You
	// might specify a filter or a sort order in your request. When response is
	// truncated, you must use the same values for the filer and sort order in the next
	// request.
	NextToken *string
	// The field to sort results by. The default is Name.
	SortBy types.NotebookInstanceSortKey
	// The sort order for results.
	SortOrder types.NotebookInstanceSortOrder
	// A filter that returns only notebook instances that were modified after the
	// specified time (timestamp).
	LastModifiedTimeAfter *time.Time
	// The maximum number of notebook instances to return.
	MaxResults *int32
	// A filter that returns only notebook instances that were created before the
	// specified time (timestamp).
	CreationTimeBefore *time.Time
	// A string in the name or URL of a Git repository associated with this notebook
	// instance. This filter returns only notebook instances associated with a git
	// repository with a name that contains the specified string.
	DefaultCodeRepositoryContains *string
	// A filter that returns only notebook instances with the specified status.
	StatusEquals types.NotebookInstanceStatus
	// A filter that returns only notebook instances that were created after the
	// specified time (timestamp).
	CreationTimeAfter *time.Time
	// A string in the notebook instances' name. This filter returns only notebook
	// instances whose name contains the specified string.
	NameContains *string
	// A filter that returns only notebook instances with associated with the specified
	// git repository.
	AdditionalCodeRepositoryEquals *string
}

type ListNotebookInstancesOutput struct {
	// If the response to the previous ListNotebookInstances request was truncated,
	// Amazon SageMaker returns this token. To retrieve the next set of notebook
	// instances, use the token in the next request.
	NextToken *string
	// An array of NotebookInstanceSummary objects, one for each notebook instance.
	NotebookInstances []*types.NotebookInstanceSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListProcessingJobsInput struct {
	// The field to sort results by. The default is CreationTime.
	SortBy types.SortBy
	// A filter that returns only processing jobs created after the specified time.
	CreationTimeBefore *time.Time
	// A filter that returns only processing jobs created after the specified time.
	CreationTimeAfter *time.Time
	// A filter that returns only processing jobs modified before the specified time.
	LastModifiedTimeBefore *time.Time
	// A filter that retrieves only processing jobs with a specific status.
	StatusEquals types.ProcessingJobStatus
	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
	// If the result of the previous ListProcessingJobs request was truncated, the
	// response includes a NextToken. To retrieve the next set of processing jobs, use
	// the token in the next request.
	NextToken *string
	// The maximum number of processing jobs to return in the response.
	MaxResults *int32
	// A filter that returns only processing jobs modified after the specified time.
	LastModifiedTimeAfter *time.Time
	// A string in the processing job name. This filter returns only processing jobs
	// whose name contains the specified string.
	NameContains *string
}

type ListProcessingJobsOutput struct {
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of processing jobs, use it in the subsequent request.
	NextToken *string
	// An array of ProcessingJobSummary objects, each listing a processing job.
	ProcessingJobSummaries []*types.ProcessingJobSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListSubscribedWorkteamsInput struct {
	// If the result of the previous ListSubscribedWorkteams request was truncated, the
	// response includes a NextToken. To retrieve the next set of labeling jobs, use
	// the token in the next request.
	NextToken *string
	// A string in the work team name. This filter returns only work teams whose name
	// contains the specified string.
	NameContains *string
	// The maximum number of work teams to return in each page of the response.
	MaxResults *int32
}

type ListSubscribedWorkteamsOutput struct {
	// An array of Workteam objects, each describing a work team.
	SubscribedWorkteams []*types.SubscribedWorkteam
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of work teams, use it in the subsequent request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListTagsInput struct {
	// The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
	ResourceArn *string
	// Maximum number of tags to return.
	MaxResults *int32
	// If the response to the previous ListTags request is truncated, Amazon SageMaker
	// returns this token. To retrieve the next set of tags, use it in the subsequent
	// request.
	NextToken *string
}

type ListTagsOutput struct {
	// If response is truncated, Amazon SageMaker includes a token in the response. You
	// can use this token in your subsequent request to fetch next set of tokens.
	NextToken *string
	// An array of Tag objects, each with a tag key and a value.
	Tags []*types.Tag

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListTrainingJobsForHyperParameterTuningJobInput struct {
	// The field to sort results by. The default is Name. If the value of this field is
	// FinalObjectiveMetricValue, any training jobs that did not return an objective
	// metric are not listed.
	SortBy types.TrainingJobSortByOptions
	// The maximum number of training jobs to return. The default value is 10.
	MaxResults *int32
	// If the result of the previous ListTrainingJobsForHyperParameterTuningJob request
	// was truncated, the response includes a NextToken. To retrieve the next set of
	// training jobs, use the token in the next request.
	NextToken *string
	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
	// The name of the tuning job whose training jobs you want to list.
	HyperParameterTuningJobName *string
	// A filter that returns only training jobs with the specified status.
	StatusEquals types.TrainingJobStatus
}

type ListTrainingJobsForHyperParameterTuningJobOutput struct {
	// A list of TrainingJobSummary () objects that describe the training jobs that the
	// ListTrainingJobsForHyperParameterTuningJob request returned.
	TrainingJobSummaries []*types.HyperParameterTrainingJobSummary
	// If the result of this ListTrainingJobsForHyperParameterTuningJob request was
	// truncated, the response includes a NextToken. To retrieve the next set of
	// training jobs, use the token in the next request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListTrainingJobsInput struct {
	// A filter that returns only training jobs created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time
	// The field to sort results by. The default is CreationTime.
	SortBy types.SortBy
	// A filter that returns only training jobs modified before the specified time
	// (timestamp).
	LastModifiedTimeBefore *time.Time
	// The maximum number of training jobs to return in the response.
	MaxResults *int32
	// A filter that returns only training jobs modified after the specified time
	// (timestamp).
	LastModifiedTimeAfter *time.Time
	// A filter that retrieves only training jobs with a specific status.
	StatusEquals types.TrainingJobStatus
	// If the result of the previous ListTrainingJobs request was truncated, the
	// response includes a NextToken. To retrieve the next set of training jobs, use
	// the token in the next request.
	NextToken *string
	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
	// A filter that returns only training jobs created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time
	// A string in the training job name. This filter returns only training jobs whose
	// name contains the specified string.
	NameContains *string
}

type ListTrainingJobsOutput struct {
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of training jobs, use it in the subsequent request.
	NextToken *string
	// An array of TrainingJobSummary objects, each listing a training job.
	TrainingJobSummaries []*types.TrainingJobSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListTransformJobsInput struct {
	// A filter that retrieves only transform jobs with a specific status.
	StatusEquals types.TransformJobStatus
	// A filter that returns only transform jobs modified after the specified time.
	LastModifiedTimeAfter *time.Time
	// The sort order for results. The default is Descending.
	SortOrder types.SortOrder
	// If the result of the previous ListTransformJobs request was truncated, the
	// response includes a NextToken. To retrieve the next set of transform jobs, use
	// the token in the next request.
	NextToken *string
	// The maximum number of transform jobs to return in the response. The default
	// value is 10.
	MaxResults *int32
	// The field to sort results by. The default is CreationTime.
	SortBy types.SortBy
	// A filter that returns only transform jobs modified before the specified time.
	LastModifiedTimeBefore *time.Time
	// A filter that returns only transform jobs created before the specified time.
	CreationTimeBefore *time.Time
	// A filter that returns only transform jobs created after the specified time.
	CreationTimeAfter *time.Time
	// A string in the transform job name. This filter returns only transform jobs
	// whose name contains the specified string.
	NameContains *string
}

type ListTransformJobsOutput struct {
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of transform jobs, use it in the next request.
	NextToken *string
	// An array of TransformJobSummary objects.
	TransformJobSummaries []*types.TransformJobSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListTrialComponentsInput struct {
	// If the previous call to ListTrialComponents didn't return the full set of
	// components, the call returns a token for getting the next set of components.
	NextToken *string
	// A filter that returns only components created before the specified time.
	CreatedBefore *time.Time
	// A filter that returns only components that have the specified source Amazon
	// Resource Name (ARN). If you specify SourceArn, you can't filter by
	// ExperimentName or TrialName.
	SourceArn *string
	// The maximum number of components to return in the response. The default value is
	// 10.
	MaxResults *int32
	// A filter that returns only components that are part of the specified experiment.
	// If you specify ExperimentName, you can't filter by SourceArn or TrialName.
	ExperimentName *string
	// A filter that returns only components that are part of the specified trial. If
	// you specify TrialName, you can't filter by ExperimentName or SourceArn.
	TrialName *string
	// A filter that returns only components created after the specified time.
	CreatedAfter *time.Time
	// The property used to sort results. The default value is CreationTime.
	SortBy types.SortTrialComponentsBy
	// The sort order. The default value is Descending.
	SortOrder types.SortOrder
}

type ListTrialComponentsOutput struct {
	// A token for getting the next set of components, if there are any.
	NextToken *string
	// A list of the summaries of your trial components.
	TrialComponentSummaries []*types.TrialComponentSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListTrialsInput struct {
	// A filter that returns only trials that are part of the specified experiment.
	ExperimentName *string
	// If the previous call to ListTrials didn't return the full set of trials, the
	// call returns a token for getting the next set of trials.
	NextToken *string
	// The maximum number of trials to return in the response. The default value is 10.
	MaxResults *int32
	// The property used to sort results. The default value is CreationTime.
	SortBy types.SortTrialsBy
	// The sort order. The default value is Descending.
	SortOrder types.SortOrder
	// A filter that returns only trials created after the specified time.
	CreatedAfter *time.Time
	// A filter that returns only trials that are associated with the specified trial
	// component.
	TrialComponentName *string
	// A filter that returns only trials created before the specified time.
	CreatedBefore *time.Time
}

type ListTrialsOutput struct {
	// A token for getting the next set of trials, if there are any.
	NextToken *string
	// A list of the summaries of your trials.
	TrialSummaries []*types.TrialSummary

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListUserProfilesInput struct {
	// The sort order for the results. The default is Ascending.
	SortOrder types.SortOrder
	// A parameter by which to filter the results.
	UserProfileNameContains *string
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string
	// The parameter by which to sort the results. The default is CreationTime.
	SortBy types.UserProfileSortKey
	// A parameter by which to filter the results.
	DomainIdEquals *string
	// Returns a list up to a specified limit.
	MaxResults *int32
}

type ListUserProfilesOutput struct {
	// The list of user profiles.
	UserProfiles []*types.UserProfileDetails
	// If the previous response was truncated, you will receive this token. Use it in
	// your next request to receive the next set of results.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListWorkforcesInput struct {
	// A token to resume pagination.
	NextToken *string
	// Sort workforces using the workforce name or creation date.
	SortBy types.ListWorkforcesSortByOptions
	// Sort workforces in ascending or descending order.
	SortOrder types.SortOrder
	// The maximum number of workforces returned in the response.
	MaxResults *int32
	// A filter you can use to search for workforces using part of the workforce name.
	NameContains *string
}

type ListWorkforcesOutput struct {
	// A token to resume pagination.
	NextToken *string
	// A list containing information about your workforce.
	Workforces []*types.Workforce

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ListWorkteamsInput struct {
	// If the result of the previous ListWorkteams request was truncated, the response
	// includes a NextToken. To retrieve the next set of labeling jobs, use the token
	// in the next request.
	NextToken *string
	// The maximum number of work teams to return in each page of the response.
	MaxResults *int32
	// The field to sort results by. The default is CreationTime.
	SortBy types.ListWorkteamsSortByOptions
	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
	// A string in the work team's name. This filter returns only work teams whose name
	// contains the specified string.
	NameContains *string
}

type ListWorkteamsOutput struct {
	// An array of Workteam objects, each describing a work team.
	Workteams []*types.Workteam
	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of work teams, use it in the subsequent request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type Options struct {
	// Set of options to modify how an operation is invoked. These apply to all
	// operations invoked for this client. Use functional options on operation call to
	// modify this list for per operation behavior.
	APIOptions []func(*middleware.Stack) error

	// The credentials object to use when signing requests.
	Credentials aws.CredentialsProvider

	// The endpoint options to be used when attempting to resolve an endpoint.
	EndpointOptions ResolverOptions

	// The service endpoint resolver.
	EndpointResolver EndpointResolver

	// Signature Version 4 (SigV4) Signer
	HTTPSignerV4 HTTPSignerV4

	// The region to send requests to. (Required)
	Region string

	// Retryer guides how HTTP requests should be retried in case of recoverable
	// failures. When nil the API client will use a default retryer.
	Retryer retry.Retryer

	// The HTTP client to invoke API calls with. Defaults to client's default HTTP
	// implementation if nil.
	HTTPClient HTTPClient
}

type RenderUiTemplateInput struct {
	// A Template object containing the worker UI template to render.
	UiTemplate *types.UiTemplate
	// The HumanTaskUiArn of the worker UI that you want to render. Do not provide a
	// HumanTaskUiArn if you use the UiTemplate parameter. See a list of available
	// Human Ui Amazon Resource Names (ARNs) in UiConfig ().
	HumanTaskUiArn *string
	// A RenderableTask object containing a representative task to render.
	Task *types.RenderableTask
	// The Amazon Resource Name (ARN) that has access to the S3 objects that are used
	// by the template.
	RoleArn *string
}

type RenderUiTemplateOutput struct {
	// A Liquid template that renders the HTML for the worker UI.
	RenderedContent *string
	// A list of one or more RenderingError objects if any were encountered while
	// rendering the template. If there were no errors, the list is empty.
	Errors []*types.RenderingError

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type ResolveEndpoint struct {
	Resolver EndpointResolver
	Options  ResolverOptions
}

type ResolveEndpointMiddlewareOptions interface {
	GetEndpointResolver() EndpointResolver
	GetEndpointOptions() ResolverOptions
}

type ResolverOptions = internalendpoints.Options

type SearchInput struct {
	// The name of the Amazon SageMaker resource to search for.
	Resource types.ResourceType
	// How SearchResults are ordered. Valid values are Ascending or Descending. The
	// default is Descending.
	SortOrder types.SearchSortOrder
	// A Boolean conditional statement. Resources must satisfy this condition to be
	// included in search results. You must provide at least one subexpression, filter,
	// or nested filter. The maximum number of recursive SubExpressions, NestedFilters,
	// and Filters that can be included in a SearchExpression object is 50.
	SearchExpression *types.SearchExpression
	// The name of the resource property used to sort the SearchResults. The default is
	// LastModifiedTime.
	SortBy *string
	// If more than MaxResults resources match the specified SearchExpression, the
	// response includes a NextToken. The NextToken can be passed to the next
	// SearchRequest to continue retrieving results.
	NextToken *string
	// The maximum number of results to return.
	MaxResults *int32
}

type SearchOutput struct {
	// A list of SearchRecord objects.
	Results []*types.SearchRecord
	// If the result of the previous Search request was truncated, the response
	// includes a NextToken. To retrieve the next set of results, use the token in the
	// next request.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type StartMonitoringScheduleInput struct {
	// The name of the schedule to start.
	MonitoringScheduleName *string
}

type StartMonitoringScheduleOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type StartNotebookInstanceInput struct {
	// The name of the notebook instance to start.
	NotebookInstanceName *string
}

type StartNotebookInstanceOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type StopAutoMLJobInput struct {
	// The name of the object you are requesting.
	AutoMLJobName *string
}

type StopAutoMLJobOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type StopCompilationJobInput struct {
	// The name of the model compilation job to stop.
	CompilationJobName *string
}

type StopCompilationJobOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type StopHyperParameterTuningJobInput struct {
	// The name of the tuning job to stop.
	HyperParameterTuningJobName *string
}

type StopHyperParameterTuningJobOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type StopLabelingJobInput struct {
	// The name of the labeling job to stop.
	LabelingJobName *string
}

type StopLabelingJobOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type StopMonitoringScheduleInput struct {
	// The name of the schedule to stop.
	MonitoringScheduleName *string
}

type StopMonitoringScheduleOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}

type StopNotebookInstanceInput struct {
	// The name of the notebook instance to terminate.
	NotebookInstanceName *string
}

type StopNotebookInstanceOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
}