sagemaker

package module
v0.29.0 Latest Latest
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 Go to latest Published: Oct 31, 2020 License: Apache-2.0 Imports: 28 Imported by: 45

Documentation

Overview

Package sagemaker provides the API client, operations, and parameter types for Amazon SageMaker Service.

Provides APIs for creating and managing Amazon SageMaker resources. Other Resources:

* Amazon SageMaker Developer Guide (https://docs.aws.amazon.com/sagemaker/latest/dg/whatis.html#first-time-user)

* Amazon Augmented AI Runtime API Reference (https://docs.aws.amazon.com/augmented-ai/2019-11-07/APIReference/Welcome.html)

Index

Constants

View Source 
const ServiceAPIVersion = "2017-07-24"
View Source 
const ServiceID = "SageMaker"

Variables

This section is empty.

Functions

func NewDefaultEndpointResolver 

func NewDefaultEndpointResolver() *internalendpoints.Resolver

NewDefaultEndpointResolver constructs a new service endpoint resolver

Types

type AddTagsInput 

type AddTagsInput struct {

	// The Amazon Resource Name (ARN) of the resource that you want to tag.
	//
	// This member is required.
	ResourceArn *string

	// 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.
	//
	// This member is required.
	Tags []*types.Tag
}

type AddTagsOutput 

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 

type AssociateTrialComponentInput struct {

	// The name of the component to associated with the trial.
	//
	// This member is required.
	TrialComponentName *string

	// The name of the trial to associate with.
	//
	// This member is required.
	TrialName *string
}

type AssociateTrialComponentOutput 

type AssociateTrialComponentOutput struct {

	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

	// The ARN of the trial component.
	TrialComponentArn *string

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

type Client 

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

Client provides the API client to make operations call for Amazon SageMaker Service.

func New 

func New(options Options, optFns ...func(*Options)) *Client

New returns an initialized Client based on the functional options. Provide additional functional options to further configure the behavior of the client, such as changing the client's endpoint or adding custom middleware behavior.

func NewFromConfig 

func NewFromConfig(cfg aws.Config, optFns ...func(*Options)) *Client

NewFromConfig returns a new client from the provided config.

func (*Client) AddTags 

func (c *Client) AddTags(ctx context.Context, params *AddTagsInput, optFns ...func(*Options)) (*AddTagsOutput, error)

Adds or overwrites one or more tags for the specified Amazon SageMaker resource. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. Each tag consists of a key and an optional value. Tag keys must be unique per resource. For more information about tags, see For more information, see AWS Tagging Strategies (https://aws.amazon.com/answers/account-management/aws-tagging-strategies/). Tags that you add to a hyperparameter tuning job by calling this API are also added to any training jobs that the hyperparameter tuning job launches after you call this API, but not to training jobs that the hyperparameter tuning job launched before you called this API. To make sure that the tags associated with a hyperparameter tuning job are also added to all training jobs that the hyperparameter tuning job launches, add the tags when you first create the tuning job by specifying them in the Tags parameter of CreateHyperParameterTuningJob

func (*Client) AssociateTrialComponent 

func (c *Client) AssociateTrialComponent(ctx context.Context, params *AssociateTrialComponentInput, optFns ...func(*Options)) (*AssociateTrialComponentOutput, error)

Associates a trial component with a trial. A trial component can be associated with multiple trials. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.

func (*Client) CreateAlgorithm 

func (c *Client) CreateAlgorithm(ctx context.Context, params *CreateAlgorithmInput, optFns ...func(*Options)) (*CreateAlgorithmOutput, error)

Create a machine learning algorithm that you can use in Amazon SageMaker and list in the AWS Marketplace.

func (*Client) CreateApp 

func (c *Client) CreateApp(ctx context.Context, params *CreateAppInput, optFns ...func(*Options)) (*CreateAppOutput, error)

Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.

func (*Client) CreateAppImageConfig added in v0.29.0 

func (c *Client) CreateAppImageConfig(ctx context.Context, params *CreateAppImageConfigInput, optFns ...func(*Options)) (*CreateAppImageConfigOutput, error)

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

func (*Client) CreateAutoMLJob 

func (c *Client) CreateAutoMLJob(ctx context.Context, params *CreateAutoMLJobInput, optFns ...func(*Options)) (*CreateAutoMLJobOutput, error)

Creates an Autopilot job. Find the best performing model after you run an Autopilot job by calling . Deploy that model by following the steps described in Step 6.1: Deploy the Model to Amazon SageMaker Hosting Services (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html). For information about how to use Autopilot, see Automate Model Development with Amazon SageMaker Autopilot (https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development.html).

func (*Client) CreateCodeRepository 

func (c *Client) CreateCodeRepository(ctx context.Context, params *CreateCodeRepositoryInput, optFns ...func(*Options)) (*CreateCodeRepositoryOutput, error)

Creates a Git repository as a resource in your Amazon SageMaker account. You can associate the repository with notebook instances so that you can use Git source control for the notebooks you create. The Git repository is a resource in your Amazon SageMaker account, so it can be associated with more than one notebook instance, and it persists independently from the lifecycle of any notebook instances it is associated with. The repository can be hosted either in AWS CodeCommit (https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any other Git repository.

func (*Client) CreateCompilationJob 

func (c *Client) CreateCompilationJob(ctx context.Context, params *CreateCompilationJobInput, optFns ...func(*Options)) (*CreateCompilationJobOutput, error)

Starts a model compilation job. After the model has been compiled, Amazon SageMaker saves the resulting model artifacts to an Amazon Simple Storage Service (Amazon S3) bucket that you specify. If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts with AWS IoT Greengrass. In that case, deploy them as an ML resource. In the request body, you provide the following:

* A name for the compilation job

* Information about the input model artifacts

* The output location for the compiled model and the device (target) that the model runs on

* The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker assumes to perform the model compilation job.

You can also provide a Tag to track the model compilation job's resource use and costs. The response body contains the CompilationJobArn for the compiled job. To stop a model compilation job, use StopCompilationJob. To get information about a particular model compilation job, use DescribeCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.

func (*Client) CreateDomain 

func (c *Client) CreateDomain(ctx context.Context, params *CreateDomainInput, optFns ...func(*Options)) (*CreateDomainOutput, error)

Creates a Domain used by Amazon SageMaker Studio. A domain consists of an associated Amazon Elastic File System (EFS) volume, a list of authorized users, and a variety of security, application, policy, and Amazon Virtual Private Cloud (VPC) configurations. An AWS account is limited to one domain per region. Users within a domain can share notebook files and other artifacts with each other. When a domain is created, an EFS volume is created for use by all of the users within the domain. Each user receives a private home directory within the EFS volume for notebooks, Git repositories, and data files. VPC configuration All SageMaker Studio traffic between the domain and the EFS volume is through the specified VPC and subnets. For other Studio traffic, you can specify the AppNetworkAccessType parameter. AppNetworkAccessType corresponds to the network access type that you choose when you onboard to Studio. The following options are available:

* PublicInternetOnly - Non-EFS traffic goes through a VPC managed by Amazon SageMaker, which allows internet access. This is the default value.

* VpcOnly - All Studio traffic is through the specified VPC and subnets. Internet access is disabled by default. To allow internet access, you must specify a NAT gateway. When internet access is disabled, you won't be able to run a Studio notebook or to train or host models unless your VPC has an interface endpoint to the SageMaker API and runtime or a NAT gateway and your security groups allow outbound connections.

For more information, see Connect SageMaker Studio Notebooks to Resources in a VPC (https://docs.aws.amazon.com/sagemaker/latest/dg/studio-notebooks-and-internet-access.html).

func (*Client) CreateEndpoint 

func (c *Client) CreateEndpoint(ctx context.Context, params *CreateEndpointInput, optFns ...func(*Options)) (*CreateEndpointOutput, error)

Creates an endpoint using the endpoint configuration specified in the request. Amazon SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API. Use this API to deploy models using Amazon SageMaker hosting services. For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)). (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto) You must not delete an EndpointConfig that is in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig. The endpoint name must be unique within an AWS Region in your AWS account. When it receives the request, Amazon SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them. When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads (https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html), the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read. When Amazon SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. Amazon SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API. If any of the models hosted at this endpoint get model data from an Amazon S3 location, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS in an AWS Region (https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html) in the AWS Identity and Access Management User Guide.

func (*Client) CreateEndpointConfig 

func (c *Client) CreateEndpointConfig(ctx context.Context, params *CreateEndpointConfigInput, optFns ...func(*Options)) (*CreateEndpointConfigOutput, error)

Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want Amazon SageMaker to provision. Then you call the CreateEndpoint API. Use this API if you want to use Amazon SageMaker hosting services to deploy models into production. In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want Amazon SageMaker to provision. This includes the number and type of ML compute instances to deploy. If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B. For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)). (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto) When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads (https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/HowItWorks.ReadConsistency.html), the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.

func (*Client) CreateExperiment 

func (c *Client) CreateExperiment(ctx context.Context, params *CreateExperimentInput, optFns ...func(*Options)) (*CreateExperimentOutput, error)

Creates an SageMaker experiment. An experiment is a collection of trials that are observed, compared and evaluated as a group. A trial is a set of steps, called trial components, that produce a machine learning model. The goal of an experiment is to determine the components that produce the best model. Multiple trials are performed, each one isolating and measuring the impact of a change to one or more inputs, while keeping the remaining inputs constant. When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK. You can add tags to experiments, trials, trial components and then use the Search API to search for the tags. To add a description to an experiment, specify the optional Description parameter. To add a description later, or to change the description, call the UpdateExperiment API. To get a list of all your experiments, call the ListExperiments API. To view an experiment's properties, call the DescribeExperiment API. To get a list of all the trials associated with an experiment, call the ListTrials API. To create a trial call the CreateTrial API.

func (*Client) CreateFlowDefinition 

func (c *Client) CreateFlowDefinition(ctx context.Context, params *CreateFlowDefinitionInput, optFns ...func(*Options)) (*CreateFlowDefinitionOutput, error)

Creates a flow definition.

func (*Client) CreateHumanTaskUi 

func (c *Client) CreateHumanTaskUi(ctx context.Context, params *CreateHumanTaskUiInput, optFns ...func(*Options)) (*CreateHumanTaskUiOutput, error)

Defines the settings you will use for the human review workflow user interface. Reviewers will see a three-panel interface with an instruction area, the item to review, and an input area.

func (*Client) CreateHyperParameterTuningJob 

func (c *Client) CreateHyperParameterTuningJob(ctx context.Context, params *CreateHyperParameterTuningJobInput, optFns ...func(*Options)) (*CreateHyperParameterTuningJobOutput, error)

Starts a hyperparameter tuning job. A hyperparameter tuning job finds the best version of a model by running many training jobs on your dataset using the algorithm you choose and values for hyperparameters within ranges that you specify. It then chooses the hyperparameter values that result in a model that performs the best, as measured by an objective metric that you choose.

func (*Client) CreateImage added in v0.29.0 

func (c *Client) CreateImage(ctx context.Context, params *CreateImageInput, optFns ...func(*Options)) (*CreateImageOutput, error)

Creates a SageMaker Image. A SageMaker image represents a set of container images. Each of these container images is represented by a SageMaker ImageVersion.

func (*Client) CreateImageVersion added in v0.29.0 

func (c *Client) CreateImageVersion(ctx context.Context, params *CreateImageVersionInput, optFns ...func(*Options)) (*CreateImageVersionOutput, error)

Creates a version of the SageMaker image specified by ImageName. The version represents the Amazon Container Registry (ECR) container image specified by BaseImage.

func (*Client) CreateLabelingJob 

func (c *Client) CreateLabelingJob(ctx context.Context, params *CreateLabelingJobInput, optFns ...func(*Options)) (*CreateLabelingJobOutput, error)

Creates a job that uses workers to label the data objects in your input dataset. You can use the labeled data to train machine learning models. You can select your workforce from one of three providers:

* A private workforce that you create. It can include employees, contractors, and outside experts. Use a private workforce when want the data to stay within your organization or when a specific set of skills is required.

* One or more vendors that you select from the AWS Marketplace. Vendors provide expertise in specific areas.

* The Amazon Mechanical Turk workforce. This is the largest workforce, but it should only be used for public data or data that has been stripped of any personally identifiable information.

You can also use automated data labeling to reduce the number of data objects that need to be labeled by a human. Automated data labeling uses active learning to determine if a data object can be labeled by machine or if it needs to be sent to a human worker. For more information, see Using Automated Data Labeling (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-automated-labeling.html). The data objects to be labeled are contained in an Amazon S3 bucket. You create a manifest file that describes the location of each object. For more information, see Using Input and Output Data (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-data.html). The output can be used as the manifest file for another labeling job or as training data for your machine learning models.

func (*Client) CreateModel 

func (c *Client) CreateModel(ctx context.Context, params *CreateModelInput, optFns ...func(*Options)) (*CreateModelOutput, error)

Creates a model in Amazon SageMaker. In the request, you name the model and describe a primary container. For the primary container, you specify the Docker image that contains inference code, artifacts (from prior training), and a custom environment map that the inference code uses when you deploy the model for predictions. Use this API to create a model if you want to use Amazon SageMaker hosting services or run a batch transform job. To host your model, you create an endpoint configuration with the CreateEndpointConfig API, and then create an endpoint with the CreateEndpoint API. Amazon SageMaker then deploys all of the containers that you defined for the model in the hosting environment. For an example that calls this method when deploying a model to Amazon SageMaker hosting services, see Deploy the Model to Amazon SageMaker Hosting Services (AWS SDK for Python (Boto 3)). (https://docs.aws.amazon.com/sagemaker/latest/dg/ex1-deploy-model.html#ex1-deploy-model-boto) To run a batch transform using your model, you start a job with the CreateTransformJob API. Amazon SageMaker uses your model and your dataset to get inferences which are then saved to a specified S3 location. In the CreateModel request, you must define a container with the PrimaryContainer parameter. In the request, you also provide an IAM role that Amazon SageMaker can assume to access model artifacts and docker image for deployment on ML compute hosting instances or for batch transform jobs. In addition, you also use the IAM role to manage permissions the inference code needs. For example, if the inference code access any other AWS resources, you grant necessary permissions via this role.

func (*Client) CreateModelPackage 

func (c *Client) CreateModelPackage(ctx context.Context, params *CreateModelPackageInput, optFns ...func(*Options)) (*CreateModelPackageOutput, error)

Creates a model package that you can use to create Amazon SageMaker models or list on AWS Marketplace. Buyers can subscribe to model packages listed on AWS Marketplace to create models in Amazon SageMaker. To create a model package by specifying a Docker container that contains your inference code and the Amazon S3 location of your model artifacts, provide values for InferenceSpecification. To create a model from an algorithm resource that you created or subscribed to in AWS Marketplace, provide a value for SourceAlgorithmSpecification.

func (*Client) CreateMonitoringSchedule 

func (c *Client) CreateMonitoringSchedule(ctx context.Context, params *CreateMonitoringScheduleInput, optFns ...func(*Options)) (*CreateMonitoringScheduleOutput, error)

Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endoint.

func (*Client) CreateNotebookInstance 

func (c *Client) CreateNotebookInstance(ctx context.Context, params *CreateNotebookInstanceInput, optFns ...func(*Options)) (*CreateNotebookInstanceOutput, error)

Creates an Amazon SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook. In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. Amazon SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance. Amazon SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use Amazon SageMaker with a specific algorithm or with a machine learning framework. After receiving the request, Amazon SageMaker does the following:

* Creates a network interface in the Amazon SageMaker VPC.

* (Option) If you specified SubnetId, Amazon SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, Amazon SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.

* Launches an EC2 instance of the type specified in the request in the Amazon SageMaker VPC. If you specified SubnetId of your VPC, Amazon SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.

After creating the notebook instance, Amazon SageMaker returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it. After Amazon SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating Amazon SageMaker endpoints, and validate hosted models. For more information, see How It Works (https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html).

func (*Client) CreateNotebookInstanceLifecycleConfig 

func (c *Client) CreateNotebookInstanceLifecycleConfig(ctx context.Context, params *CreateNotebookInstanceLifecycleConfigInput, optFns ...func(*Options)) (*CreateNotebookInstanceLifecycleConfigOutput, error)

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

func (*Client) CreatePresignedDomainUrl 

func (c *Client) CreatePresignedDomainUrl(ctx context.Context, params *CreatePresignedDomainUrlInput, optFns ...func(*Options)) (*CreatePresignedDomainUrlOutput, error)

Creates a URL for a specified UserProfile in a Domain. When accessed in a web browser, the user will be automatically signed in to Amazon SageMaker Studio, and granted access to all of the Apps and files associated with the Domain's Amazon Elastic File System (EFS) volume. This operation can only be called when the authentication mode equals IAM. The URL that you get from a call to CreatePresignedDomainUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.

func (*Client) CreatePresignedNotebookInstanceUrl 

func (c *Client) CreatePresignedNotebookInstanceUrl(ctx context.Context, params *CreatePresignedNotebookInstanceUrlInput, optFns ...func(*Options)) (*CreatePresignedNotebookInstanceUrlOutput, error)

Returns a URL that you can use to connect to the Jupyter server from a notebook instance. In the Amazon SageMaker console, when you choose Open next to a notebook instance, Amazon SageMaker opens a new tab showing the Jupyter server home page from the notebook instance. The console uses this API to get the URL and show the page. The IAM role or user used to call this API defines the permissions to access the notebook instance. Once the presigned URL is created, no additional permission is required to access this URL. IAM authorization policies for this API are also enforced for every HTTP request and WebSocket frame that attempts to connect to the notebook instance. You can restrict access to this API and to the URL that it returns to a list of IP addresses that you specify. Use the NotIpAddress condition operator and the aws:SourceIP condition context key to specify the list of IP addresses that you want to have access to the notebook instance. For more information, see Limit Access to a Notebook Instance by IP Address (https://docs.aws.amazon.com/sagemaker/latest/dg/security_iam_id-based-policy-examples.html#nbi-ip-filter). The URL that you get from a call to CreatePresignedNotebookInstanceUrl is valid only for 5 minutes. If you try to use the URL after the 5-minute limit expires, you are directed to the AWS console sign-in page.

func (*Client) CreateProcessingJob 

func (c *Client) CreateProcessingJob(ctx context.Context, params *CreateProcessingJobInput, optFns ...func(*Options)) (*CreateProcessingJobOutput, error)

Creates a processing job.

func (*Client) CreateTrainingJob 

func (c *Client) CreateTrainingJob(ctx context.Context, params *CreateTrainingJobInput, optFns ...func(*Options)) (*CreateTrainingJobOutput, error)

Starts a model training job. After training completes, Amazon SageMaker saves the resulting model artifacts to an Amazon S3 location that you specify. If you choose to host your model using Amazon SageMaker hosting services, you can use the resulting model artifacts as part of the model. You can also use the artifacts in a machine learning service other than Amazon SageMaker, provided that you know how to use them for inferences. In the request body, you provide the following:

* AlgorithmSpecification - Identifies the training algorithm to use.

* HyperParameters - Specify these algorithm-specific parameters to enable the estimation of model parameters during training. Hyperparameters can be tuned to optimize this 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).

* InputDataConfig - Describes the training dataset and the Amazon S3, EFS, or FSx location where it is stored.

* OutputDataConfig - Identifies the Amazon S3 bucket where you want Amazon SageMaker to save the results of model training.

* ResourceConfig - Identifies the resources, ML compute instances, and ML storage volumes to deploy for model training. In distributed training, you specify more than one instance.

* EnableManagedSpotTraining - Optimize the cost of training machine learning models by up to 80% by using Amazon EC2 Spot instances. For more information, see Managed Spot Training (https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html).

* RoleARN - The Amazon Resource Number (ARN) that Amazon SageMaker assumes to perform tasks on your behalf during model training. You must grant this role the necessary permissions so that Amazon SageMaker can successfully complete model training.

* StoppingCondition - To help cap training costs, use MaxRuntimeInSeconds to set a time limit for training. Use MaxWaitTimeInSeconds to specify how long you are willing to wait for a managed spot training job to complete.

For more information about Amazon SageMaker, see How It Works (https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works.html).

func (*Client) CreateTransformJob 

func (c *Client) CreateTransformJob(ctx context.Context, params *CreateTransformJobInput, optFns ...func(*Options)) (*CreateTransformJobOutput, error)

Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify. To perform batch transformations, you create a transform job and use the data that you have readily available. In the request body, you provide the following:

* TransformJobName - Identifies the transform job. The name must be unique within an AWS Region in an AWS account.

* ModelName - Identifies the model to use. ModelName must be the name of an existing Amazon SageMaker model in the same AWS Region and AWS account. For information on creating a model, see CreateModel.

* TransformInput - Describes the dataset to be transformed and the Amazon S3 location where it is stored.

* TransformOutput - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.

* TransformResources - Identifies the ML compute instances for the transform job.

For more information about how batch transformation works, see Batch Transform (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html).

func (*Client) CreateTrial 

func (c *Client) CreateTrial(ctx context.Context, params *CreateTrialInput, optFns ...func(*Options)) (*CreateTrialOutput, error)

Creates an Amazon SageMaker trial. A trial is a set of steps called trial components that produce a machine learning model. A trial is part of a single Amazon SageMaker experiment. When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK. You can add tags to a trial and then use the Search API to search for the tags. To get a list of all your trials, call the ListTrials API. To view a trial's properties, call the DescribeTrial API. To create a trial component, call the CreateTrialComponent API.

func (*Client) CreateTrialComponent 

func (c *Client) CreateTrialComponent(ctx context.Context, params *CreateTrialComponentInput, optFns ...func(*Options)) (*CreateTrialComponentOutput, error)

Creates a trial component, which is a stage of a machine learning trial. A trial is composed of one or more trial components. A trial component can be used in multiple trials. Trial components include pre-processing jobs, training jobs, and batch transform jobs. When you use Amazon SageMaker Studio or the Amazon SageMaker Python SDK, all experiments, trials, and trial components are automatically tracked, logged, and indexed. When you use the AWS SDK for Python (Boto), you must use the logging APIs provided by the SDK. You can add tags to a trial component and then use the Search API to search for the tags. CreateTrialComponent can only be invoked from within an Amazon SageMaker managed environment. This includes Amazon SageMaker training jobs, processing jobs, transform jobs, and Amazon SageMaker notebooks. A call to CreateTrialComponent from outside one of these environments results in an error.

func (*Client) CreateUserProfile 

func (c *Client) CreateUserProfile(ctx context.Context, params *CreateUserProfileInput, optFns ...func(*Options)) (*CreateUserProfileOutput, error)

Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a "person" for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user's private Amazon Elastic File System (EFS) home directory.

func (*Client) CreateWorkforce 

func (c *Client) CreateWorkforce(ctx context.Context, params *CreateWorkforceInput, optFns ...func(*Options)) (*CreateWorkforceOutput, error)

Use this operation to create a workforce. This operation will return an error if a workforce already exists in the AWS Region that you specify. You can only create one workforce in each AWS Region per AWS account. If you want to create a new workforce in an AWS Region where a workforce already exists, use the API operation to delete the existing workforce and then use CreateWorkforce to create a new workforce. To create a private workforce using Amazon Cognito, you must specify a Cognito user pool in CognitoConfig. You can also create an Amazon Cognito workforce using the Amazon SageMaker console. For more information, see Create a Private Workforce (Amazon Cognito) (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html). To create a private workforce using your own OIDC Identity Provider (IdP), specify your IdP configuration in OidcConfig. Your OIDC IdP must support groups because groups are used by Ground Truth and Amazon A2I to create work teams. For more information, see Create a Private Workforce (OIDC IdP) (https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private-oidc.html).

func (*Client) CreateWorkteam 

func (c *Client) CreateWorkteam(ctx context.Context, params *CreateWorkteamInput, optFns ...func(*Options)) (*CreateWorkteamOutput, error)

Creates a new work team for labeling your data. A work team is defined by one or more Amazon Cognito user pools. You must first create the user pools before you can create a work team. You cannot create more than 25 work teams in an account and region.

func (*Client) DeleteAlgorithm 

func (c *Client) DeleteAlgorithm(ctx context.Context, params *DeleteAlgorithmInput, optFns ...func(*Options)) (*DeleteAlgorithmOutput, error)

Removes the specified algorithm from your account.

func (*Client) DeleteApp 

func (c *Client) DeleteApp(ctx context.Context, params *DeleteAppInput, optFns ...func(*Options)) (*DeleteAppOutput, error)

Used to stop and delete an app.

func (*Client) DeleteAppImageConfig added in v0.29.0 

func (c *Client) DeleteAppImageConfig(ctx context.Context, params *DeleteAppImageConfigInput, optFns ...func(*Options)) (*DeleteAppImageConfigOutput, error)

Deletes an AppImageConfig.

func (*Client) DeleteCodeRepository 

func (c *Client) DeleteCodeRepository(ctx context.Context, params *DeleteCodeRepositoryInput, optFns ...func(*Options)) (*DeleteCodeRepositoryOutput, error)

Deletes the specified Git repository from your account.

func (*Client) DeleteDomain 

func (c *Client) DeleteDomain(ctx context.Context, params *DeleteDomainInput, optFns ...func(*Options)) (*DeleteDomainOutput, error)

Used to delete a domain. If you onboarded with IAM mode, you will need to delete your domain to onboard again using SSO. Use with caution. All of the members of the domain will lose access to their EFS volume, including data, notebooks, and other artifacts.

func (*Client) DeleteEndpoint 

func (c *Client) DeleteEndpoint(ctx context.Context, params *DeleteEndpointInput, optFns ...func(*Options)) (*DeleteEndpointOutput, error)

Deletes an endpoint. Amazon SageMaker frees up all of the resources that were deployed when the endpoint was created. Amazon SageMaker retires any custom KMS key grants associated with the endpoint, meaning you don't need to use the RevokeGrant (http://docs.aws.amazon.com/kms/latest/APIReference/API_RevokeGrant.html) API call.

func (*Client) DeleteEndpointConfig 

func (c *Client) DeleteEndpointConfig(ctx context.Context, params *DeleteEndpointConfigInput, optFns ...func(*Options)) (*DeleteEndpointConfigOutput, error)

Deletes an endpoint configuration. The DeleteEndpointConfig API deletes only the specified configuration. It does not delete endpoints created using the configuration. You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.

func (*Client) DeleteExperiment 

func (c *Client) DeleteExperiment(ctx context.Context, params *DeleteExperimentInput, optFns ...func(*Options)) (*DeleteExperimentOutput, error)

Deletes an Amazon SageMaker experiment. All trials associated with the experiment must be deleted first. Use the ListTrials API to get a list of the trials associated with the experiment.

func (*Client) DeleteFlowDefinition 

func (c *Client) DeleteFlowDefinition(ctx context.Context, params *DeleteFlowDefinitionInput, optFns ...func(*Options)) (*DeleteFlowDefinitionOutput, error)

Deletes the specified flow definition.

func (*Client) DeleteHumanTaskUi 

func (c *Client) DeleteHumanTaskUi(ctx context.Context, params *DeleteHumanTaskUiInput, optFns ...func(*Options)) (*DeleteHumanTaskUiOutput, error)

Use this operation to delete a human task user interface (worker task template). To see a list of human task user interfaces (work task templates) in your account, use . When you delete a worker task template, it no longer appears when you call ListHumanTaskUis.

func (*Client) DeleteImage added in v0.29.0 

func (c *Client) DeleteImage(ctx context.Context, params *DeleteImageInput, optFns ...func(*Options)) (*DeleteImageOutput, error)

Deletes a SageMaker image and all versions of the image. The container images aren't deleted.

func (*Client) DeleteImageVersion added in v0.29.0 

func (c *Client) DeleteImageVersion(ctx context.Context, params *DeleteImageVersionInput, optFns ...func(*Options)) (*DeleteImageVersionOutput, error)

Deletes a version of a SageMaker image. The container image the version represents isn't deleted.

func (*Client) DeleteModel 

func (c *Client) DeleteModel(ctx context.Context, params *DeleteModelInput, optFns ...func(*Options)) (*DeleteModelOutput, error)

Deletes a model. The DeleteModel API deletes only the model entry that was created in Amazon SageMaker when you called the CreateModel API. It does not delete model artifacts, inference code, or the IAM role that you specified when creating the model.

func (*Client) DeleteModelPackage 

func (c *Client) DeleteModelPackage(ctx context.Context, params *DeleteModelPackageInput, optFns ...func(*Options)) (*DeleteModelPackageOutput, error)

Deletes a model package. A model package is used to create Amazon SageMaker models or list on AWS Marketplace. Buyers can subscribe to model packages listed on AWS Marketplace to create models in Amazon SageMaker.

func (*Client) DeleteMonitoringSchedule 

func (c *Client) DeleteMonitoringSchedule(ctx context.Context, params *DeleteMonitoringScheduleInput, optFns ...func(*Options)) (*DeleteMonitoringScheduleOutput, error)

Deletes a monitoring schedule. Also stops the schedule had not already been stopped. This does not delete the job execution history of the monitoring schedule.

func (*Client) DeleteNotebookInstance 

func (c *Client) DeleteNotebookInstance(ctx context.Context, params *DeleteNotebookInstanceInput, optFns ...func(*Options)) (*DeleteNotebookInstanceOutput, error)

Deletes an Amazon SageMaker notebook instance. Before you can delete a notebook instance, you must call the StopNotebookInstance API. When you delete a notebook instance, you lose all of your data. Amazon SageMaker removes the ML compute instance, and deletes the ML storage volume and the network interface associated with the notebook instance.

func (*Client) DeleteNotebookInstanceLifecycleConfig 

func (c *Client) DeleteNotebookInstanceLifecycleConfig(ctx context.Context, params *DeleteNotebookInstanceLifecycleConfigInput, optFns ...func(*Options)) (*DeleteNotebookInstanceLifecycleConfigOutput, error)

Deletes a notebook instance lifecycle configuration.

func (*Client) DeleteTags 

func (c *Client) DeleteTags(ctx context.Context, params *DeleteTagsInput, optFns ...func(*Options)) (*DeleteTagsOutput, error)

Deletes the specified tags from an Amazon SageMaker resource. To list a resource's tags, use the ListTags API. When you call this API to delete tags from a hyperparameter tuning job, the deleted tags are not removed from training jobs that the hyperparameter tuning job launched before you called this API.

func (*Client) DeleteTrial 

func (c *Client) DeleteTrial(ctx context.Context, params *DeleteTrialInput, optFns ...func(*Options)) (*DeleteTrialOutput, error)

Deletes the specified trial. All trial components that make up the trial must be deleted first. Use the DescribeTrialComponent API to get the list of trial components.

func (*Client) DeleteTrialComponent 

func (c *Client) DeleteTrialComponent(ctx context.Context, params *DeleteTrialComponentInput, optFns ...func(*Options)) (*DeleteTrialComponentOutput, error)

Deletes the specified trial component. A trial component must be disassociated from all trials before the trial component can be deleted. To disassociate a trial component from a trial, call the DisassociateTrialComponent API.

func (*Client) DeleteUserProfile 

func (c *Client) DeleteUserProfile(ctx context.Context, params *DeleteUserProfileInput, optFns ...func(*Options)) (*DeleteUserProfileOutput, error)

Deletes a user profile. When a user profile is deleted, the user loses access to their EFS volume, including data, notebooks, and other artifacts.

func (*Client) DeleteWorkforce 

func (c *Client) DeleteWorkforce(ctx context.Context, params *DeleteWorkforceInput, optFns ...func(*Options)) (*DeleteWorkforceOutput, error)

Use this operation to delete a workforce. If you want to create a new workforce in an AWS Region where a workforce already exists, use this operation to delete the existing workforce and then use to create a new workforce. If a private workforce contains one or more work teams, you must use the operation to delete all work teams before you delete the workforce. If you try to delete a workforce that contains one or more work teams, you will recieve a ResourceInUse error.

func (*Client) DeleteWorkteam 

func (c *Client) DeleteWorkteam(ctx context.Context, params *DeleteWorkteamInput, optFns ...func(*Options)) (*DeleteWorkteamOutput, error)

Deletes an existing work team. This operation can't be undone.

func (*Client) DescribeAlgorithm 

func (c *Client) DescribeAlgorithm(ctx context.Context, params *DescribeAlgorithmInput, optFns ...func(*Options)) (*DescribeAlgorithmOutput, error)

Returns a description of the specified algorithm that is in your account.

func (*Client) DescribeApp 

func (c *Client) DescribeApp(ctx context.Context, params *DescribeAppInput, optFns ...func(*Options)) (*DescribeAppOutput, error)

Describes the app.

func (*Client) DescribeAppImageConfig added in v0.29.0 

func (c *Client) DescribeAppImageConfig(ctx context.Context, params *DescribeAppImageConfigInput, optFns ...func(*Options)) (*DescribeAppImageConfigOutput, error)

Describes an AppImageConfig.

func (*Client) DescribeAutoMLJob 

func (c *Client) DescribeAutoMLJob(ctx context.Context, params *DescribeAutoMLJobInput, optFns ...func(*Options)) (*DescribeAutoMLJobOutput, error)

Returns information about an Amazon SageMaker job.

func (*Client) DescribeCodeRepository 

func (c *Client) DescribeCodeRepository(ctx context.Context, params *DescribeCodeRepositoryInput, optFns ...func(*Options)) (*DescribeCodeRepositoryOutput, error)

Gets details about the specified Git repository.

func (*Client) DescribeCompilationJob 

func (c *Client) DescribeCompilationJob(ctx context.Context, params *DescribeCompilationJobInput, optFns ...func(*Options)) (*DescribeCompilationJobOutput, error)

Returns information about a model compilation job. To create a model compilation job, use CreateCompilationJob. To get information about multiple model compilation jobs, use ListCompilationJobs.

func (*Client) DescribeDomain 

func (c *Client) DescribeDomain(ctx context.Context, params *DescribeDomainInput, optFns ...func(*Options)) (*DescribeDomainOutput, error)

The description of the domain.

func (*Client) DescribeEndpoint 

func (c *Client) DescribeEndpoint(ctx context.Context, params *DescribeEndpointInput, optFns ...func(*Options)) (*DescribeEndpointOutput, error)

Returns the description of an endpoint.

func (*Client) DescribeEndpointConfig 

func (c *Client) DescribeEndpointConfig(ctx context.Context, params *DescribeEndpointConfigInput, optFns ...func(*Options)) (*DescribeEndpointConfigOutput, error)

Returns the description of an endpoint configuration created using the CreateEndpointConfig API.

func (*Client) DescribeExperiment 

func (c *Client) DescribeExperiment(ctx context.Context, params *DescribeExperimentInput, optFns ...func(*Options)) (*DescribeExperimentOutput, error)

Provides a list of an experiment's properties.

func (*Client) DescribeFlowDefinition 

func (c *Client) DescribeFlowDefinition(ctx context.Context, params *DescribeFlowDefinitionInput, optFns ...func(*Options)) (*DescribeFlowDefinitionOutput, error)

Returns information about the specified flow definition.

func (*Client) DescribeHumanTaskUi 

func (c *Client) DescribeHumanTaskUi(ctx context.Context, params *DescribeHumanTaskUiInput, optFns ...func(*Options)) (*DescribeHumanTaskUiOutput, error)

Returns information about the requested human task user interface (worker task template).

func (*Client) DescribeHyperParameterTuningJob 

func (c *Client) DescribeHyperParameterTuningJob(ctx context.Context, params *DescribeHyperParameterTuningJobInput, optFns ...func(*Options)) (*DescribeHyperParameterTuningJobOutput, error)

Gets a description of a hyperparameter tuning job.

func (*Client) DescribeImage added in v0.29.0 

func (c *Client) DescribeImage(ctx context.Context, params *DescribeImageInput, optFns ...func(*Options)) (*DescribeImageOutput, error)

Describes a SageMaker image.

func (*Client) DescribeImageVersion added in v0.29.0 

func (c *Client) DescribeImageVersion(ctx context.Context, params *DescribeImageVersionInput, optFns ...func(*Options)) (*DescribeImageVersionOutput, error)

Describes a version of a SageMaker image.

func (*Client) DescribeLabelingJob 

func (c *Client) DescribeLabelingJob(ctx context.Context, params *DescribeLabelingJobInput, optFns ...func(*Options)) (*DescribeLabelingJobOutput, error)

Gets information about a labeling job.

func (*Client) DescribeModel 

func (c *Client) DescribeModel(ctx context.Context, params *DescribeModelInput, optFns ...func(*Options)) (*DescribeModelOutput, error)

Describes a model that you created using the CreateModel API.

func (*Client) DescribeModelPackage 

func (c *Client) DescribeModelPackage(ctx context.Context, params *DescribeModelPackageInput, optFns ...func(*Options)) (*DescribeModelPackageOutput, error)

Returns a description of the specified model package, which is used to create Amazon SageMaker models or list them on AWS Marketplace. To create models in Amazon SageMaker, buyers can subscribe to model packages listed on AWS Marketplace.

func (*Client) DescribeMonitoringSchedule 

func (c *Client) DescribeMonitoringSchedule(ctx context.Context, params *DescribeMonitoringScheduleInput, optFns ...func(*Options)) (*DescribeMonitoringScheduleOutput, error)

Describes the schedule for a monitoring job.

func (*Client) DescribeNotebookInstance 

func (c *Client) DescribeNotebookInstance(ctx context.Context, params *DescribeNotebookInstanceInput, optFns ...func(*Options)) (*DescribeNotebookInstanceOutput, error)

Returns information about a notebook instance.

func (*Client) DescribeNotebookInstanceLifecycleConfig 

func (c *Client) DescribeNotebookInstanceLifecycleConfig(ctx context.Context, params *DescribeNotebookInstanceLifecycleConfigInput, optFns ...func(*Options)) (*DescribeNotebookInstanceLifecycleConfigOutput, error)

Returns a description 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).

func (*Client) DescribeProcessingJob 

func (c *Client) DescribeProcessingJob(ctx context.Context, params *DescribeProcessingJobInput, optFns ...func(*Options)) (*DescribeProcessingJobOutput, error)

Returns a description of a processing job.

func (*Client) DescribeSubscribedWorkteam 

func (c *Client) DescribeSubscribedWorkteam(ctx context.Context, params *DescribeSubscribedWorkteamInput, optFns ...func(*Options)) (*DescribeSubscribedWorkteamOutput, error)

Gets information about a work team provided by a vendor. It returns details about the subscription with a vendor in the AWS Marketplace.

func (*Client) DescribeTrainingJob 

func (c *Client) DescribeTrainingJob(ctx context.Context, params *DescribeTrainingJobInput, optFns ...func(*Options)) (*DescribeTrainingJobOutput, error)

Returns information about a training job.

func (*Client) DescribeTransformJob 

func (c *Client) DescribeTransformJob(ctx context.Context, params *DescribeTransformJobInput, optFns ...func(*Options)) (*DescribeTransformJobOutput, error)

Returns information about a transform job.

func (*Client) DescribeTrial 

func (c *Client) DescribeTrial(ctx context.Context, params *DescribeTrialInput, optFns ...func(*Options)) (*DescribeTrialOutput, error)

Provides a list of a trial's properties.

func (*Client) DescribeTrialComponent 

func (c *Client) DescribeTrialComponent(ctx context.Context, params *DescribeTrialComponentInput, optFns ...func(*Options)) (*DescribeTrialComponentOutput, error)

Provides a list of a trials component's properties.

func (*Client) DescribeUserProfile 

func (c *Client) DescribeUserProfile(ctx context.Context, params *DescribeUserProfileInput, optFns ...func(*Options)) (*DescribeUserProfileOutput, error)

Describes a user profile. For more information, see CreateUserProfile.

func (*Client) DescribeWorkforce 

func (c *Client) DescribeWorkforce(ctx context.Context, params *DescribeWorkforceInput, optFns ...func(*Options)) (*DescribeWorkforceOutput, error)

Lists private workforce information, including workforce name, Amazon Resource Name (ARN), and, if applicable, allowed IP address ranges (CIDRs (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html)). Allowable IP address ranges are the IP addresses that workers can use to access tasks. This operation applies only to private workforces.

func (*Client) DescribeWorkteam 

func (c *Client) DescribeWorkteam(ctx context.Context, params *DescribeWorkteamInput, optFns ...func(*Options)) (*DescribeWorkteamOutput, error)

Gets information about a specific work team. You can see information such as the create date, the last updated date, membership information, and the work team's Amazon Resource Name (ARN).

func (*Client) DisassociateTrialComponent 

func (c *Client) DisassociateTrialComponent(ctx context.Context, params *DisassociateTrialComponentInput, optFns ...func(*Options)) (*DisassociateTrialComponentOutput, error)

Disassociates a trial component from a trial. This doesn't effect other trials the component is associated with. Before you can delete a component, you must disassociate the component from all trials it is associated with. To associate a trial component with a trial, call the AssociateTrialComponent API. To get a list of the trials a component is associated with, use the Search API. Specify ExperimentTrialComponent for the Resource parameter. The list appears in the response under Results.TrialComponent.Parents.

func (*Client) GetSearchSuggestions 

func (c *Client) GetSearchSuggestions(ctx context.Context, params *GetSearchSuggestionsInput, optFns ...func(*Options)) (*GetSearchSuggestionsOutput, error)

An auto-complete API for the search functionality in the Amazon SageMaker console. It returns suggestions of possible matches for the property name to use in Search queries. Provides suggestions for HyperParameters, Tags, and Metrics.

func (*Client) ListAlgorithms 

func (c *Client) ListAlgorithms(ctx context.Context, params *ListAlgorithmsInput, optFns ...func(*Options)) (*ListAlgorithmsOutput, error)

Lists the machine learning algorithms that have been created.

func (*Client) ListAppImageConfigs added in v0.29.0 

func (c *Client) ListAppImageConfigs(ctx context.Context, params *ListAppImageConfigsInput, optFns ...func(*Options)) (*ListAppImageConfigsOutput, error)

Lists the AppImageConfigs in your account and their properties. The list can be filtered by creation time or modified time, and whether the AppImageConfig name contains a specified string.

func (*Client) ListApps 

func (c *Client) ListApps(ctx context.Context, params *ListAppsInput, optFns ...func(*Options)) (*ListAppsOutput, error)

Lists apps.

func (*Client) ListAutoMLJobs 

func (c *Client) ListAutoMLJobs(ctx context.Context, params *ListAutoMLJobsInput, optFns ...func(*Options)) (*ListAutoMLJobsOutput, error)

Request a list of jobs.

func (*Client) ListCandidatesForAutoMLJob 

func (c *Client) ListCandidatesForAutoMLJob(ctx context.Context, params *ListCandidatesForAutoMLJobInput, optFns ...func(*Options)) (*ListCandidatesForAutoMLJobOutput, error)

List the Candidates created for the job.

func (*Client) ListCodeRepositories 

func (c *Client) ListCodeRepositories(ctx context.Context, params *ListCodeRepositoriesInput, optFns ...func(*Options)) (*ListCodeRepositoriesOutput, error)

Gets a list of the Git repositories in your account.

func (*Client) ListCompilationJobs 

func (c *Client) ListCompilationJobs(ctx context.Context, params *ListCompilationJobsInput, optFns ...func(*Options)) (*ListCompilationJobsOutput, error)

Lists model compilation jobs that satisfy various filters. To create a model compilation job, use CreateCompilationJob. To get information about a particular model compilation job you have created, use DescribeCompilationJob.

func (*Client) ListDomains 

func (c *Client) ListDomains(ctx context.Context, params *ListDomainsInput, optFns ...func(*Options)) (*ListDomainsOutput, error)

Lists the domains.

func (*Client) ListEndpointConfigs 

func (c *Client) ListEndpointConfigs(ctx context.Context, params *ListEndpointConfigsInput, optFns ...func(*Options)) (*ListEndpointConfigsOutput, error)

Lists endpoint configurations.

func (*Client) ListEndpoints 

func (c *Client) ListEndpoints(ctx context.Context, params *ListEndpointsInput, optFns ...func(*Options)) (*ListEndpointsOutput, error)

Lists endpoints.

func (*Client) ListExperiments 

func (c *Client) ListExperiments(ctx context.Context, params *ListExperimentsInput, optFns ...func(*Options)) (*ListExperimentsOutput, error)

Lists all the experiments in your account. The list can be filtered to show only experiments that were created in a specific time range. The list can be sorted by experiment name or creation time.

func (*Client) ListFlowDefinitions 

func (c *Client) ListFlowDefinitions(ctx context.Context, params *ListFlowDefinitionsInput, optFns ...func(*Options)) (*ListFlowDefinitionsOutput, error)

Returns information about the flow definitions in your account.

func (*Client) ListHumanTaskUis 

func (c *Client) ListHumanTaskUis(ctx context.Context, params *ListHumanTaskUisInput, optFns ...func(*Options)) (*ListHumanTaskUisOutput, error)

Returns information about the human task user interfaces in your account.

func (*Client) ListHyperParameterTuningJobs 

func (c *Client) ListHyperParameterTuningJobs(ctx context.Context, params *ListHyperParameterTuningJobsInput, optFns ...func(*Options)) (*ListHyperParameterTuningJobsOutput, error)

Gets a list of HyperParameterTuningJobSummary objects that describe the hyperparameter tuning jobs launched in your account.

func (*Client) ListImageVersions added in v0.29.0 

func (c *Client) ListImageVersions(ctx context.Context, params *ListImageVersionsInput, optFns ...func(*Options)) (*ListImageVersionsOutput, error)

Lists the versions of a specified image and their properties. The list can be filtered by creation time or modified time.

func (*Client) ListImages added in v0.29.0 

func (c *Client) ListImages(ctx context.Context, params *ListImagesInput, optFns ...func(*Options)) (*ListImagesOutput, error)

Lists the images in your account and their properties. The list can be filtered by creation time or modified time, and whether the image name contains a specified string.

func (*Client) ListLabelingJobs 

func (c *Client) ListLabelingJobs(ctx context.Context, params *ListLabelingJobsInput, optFns ...func(*Options)) (*ListLabelingJobsOutput, error)

Gets a list of labeling jobs.

func (*Client) ListLabelingJobsForWorkteam 

func (c *Client) ListLabelingJobsForWorkteam(ctx context.Context, params *ListLabelingJobsForWorkteamInput, optFns ...func(*Options)) (*ListLabelingJobsForWorkteamOutput, error)

Gets a list of labeling jobs assigned to a specified work team.

func (*Client) ListModelPackages 

func (c *Client) ListModelPackages(ctx context.Context, params *ListModelPackagesInput, optFns ...func(*Options)) (*ListModelPackagesOutput, error)

Lists the model packages that have been created.

func (*Client) ListModels 

func (c *Client) ListModels(ctx context.Context, params *ListModelsInput, optFns ...func(*Options)) (*ListModelsOutput, error)

Lists models created with the CreateModel API.

func (*Client) ListMonitoringExecutions 

func (c *Client) ListMonitoringExecutions(ctx context.Context, params *ListMonitoringExecutionsInput, optFns ...func(*Options)) (*ListMonitoringExecutionsOutput, error)

Returns list of all monitoring job executions.

func (*Client) ListMonitoringSchedules 

func (c *Client) ListMonitoringSchedules(ctx context.Context, params *ListMonitoringSchedulesInput, optFns ...func(*Options)) (*ListMonitoringSchedulesOutput, error)

Returns list of all monitoring schedules.

func (*Client) ListNotebookInstanceLifecycleConfigs 

func (c *Client) ListNotebookInstanceLifecycleConfigs(ctx context.Context, params *ListNotebookInstanceLifecycleConfigsInput, optFns ...func(*Options)) (*ListNotebookInstanceLifecycleConfigsOutput, error)

Lists notebook instance lifestyle configurations created with the CreateNotebookInstanceLifecycleConfig API.

func (*Client) ListNotebookInstances 

func (c *Client) ListNotebookInstances(ctx context.Context, params *ListNotebookInstancesInput, optFns ...func(*Options)) (*ListNotebookInstancesOutput, error)

Returns a list of the Amazon SageMaker notebook instances in the requester's account in an AWS Region.

func (*Client) ListProcessingJobs 

func (c *Client) ListProcessingJobs(ctx context.Context, params *ListProcessingJobsInput, optFns ...func(*Options)) (*ListProcessingJobsOutput, error)

Lists processing jobs that satisfy various filters.

func (*Client) ListSubscribedWorkteams 

func (c *Client) ListSubscribedWorkteams(ctx context.Context, params *ListSubscribedWorkteamsInput, optFns ...func(*Options)) (*ListSubscribedWorkteamsOutput, error)

Gets a list of the work teams that you are subscribed to in the AWS Marketplace. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.

func (*Client) ListTags 

func (c *Client) ListTags(ctx context.Context, params *ListTagsInput, optFns ...func(*Options)) (*ListTagsOutput, error)

Returns the tags for the specified Amazon SageMaker resource.

func (*Client) ListTrainingJobs 

func (c *Client) ListTrainingJobs(ctx context.Context, params *ListTrainingJobsInput, optFns ...func(*Options)) (*ListTrainingJobsOutput, error)

Lists training jobs.

func (*Client) ListTrainingJobsForHyperParameterTuningJob 

func (c *Client) ListTrainingJobsForHyperParameterTuningJob(ctx context.Context, params *ListTrainingJobsForHyperParameterTuningJobInput, optFns ...func(*Options)) (*ListTrainingJobsForHyperParameterTuningJobOutput, error)

Gets a list of TrainingJobSummary objects that describe the training jobs that a hyperparameter tuning job launched.

func (*Client) ListTransformJobs 

func (c *Client) ListTransformJobs(ctx context.Context, params *ListTransformJobsInput, optFns ...func(*Options)) (*ListTransformJobsOutput, error)

Lists transform jobs.

func (*Client) ListTrialComponents 

func (c *Client) ListTrialComponents(ctx context.Context, params *ListTrialComponentsInput, optFns ...func(*Options)) (*ListTrialComponentsOutput, error)

Lists the trial components in your account. You can sort the list by trial component name or creation time. You can filter the list to show only components that were created in a specific time range. You can also filter on one of the following:

* ExperimentName

* SourceArn

* TrialName

func (*Client) ListTrials 

func (c *Client) ListTrials(ctx context.Context, params *ListTrialsInput, optFns ...func(*Options)) (*ListTrialsOutput, error)

Lists the trials in your account. Specify an experiment name to limit the list to the trials that are part of that experiment. Specify a trial component name to limit the list to the trials that associated with that trial component. The list can be filtered to show only trials that were created in a specific time range. The list can be sorted by trial name or creation time.

func (*Client) ListUserProfiles 

func (c *Client) ListUserProfiles(ctx context.Context, params *ListUserProfilesInput, optFns ...func(*Options)) (*ListUserProfilesOutput, error)

Lists user profiles.

func (*Client) ListWorkforces 

func (c *Client) ListWorkforces(ctx context.Context, params *ListWorkforcesInput, optFns ...func(*Options)) (*ListWorkforcesOutput, error)

Use this operation to list all private and vendor workforces in an AWS Region. Note that you can only have one private workforce per AWS Region.

func (*Client) ListWorkteams 

func (c *Client) ListWorkteams(ctx context.Context, params *ListWorkteamsInput, optFns ...func(*Options)) (*ListWorkteamsOutput, error)

Gets a list of private work teams that you have defined in a region. The list may be empty if no work team satisfies the filter specified in the NameContains parameter.

func (*Client) RenderUiTemplate 

func (c *Client) RenderUiTemplate(ctx context.Context, params *RenderUiTemplateInput, optFns ...func(*Options)) (*RenderUiTemplateOutput, error)

Renders the UI template so that you can preview the worker's experience.

func (*Client) Search 

func (c *Client) Search(ctx context.Context, params *SearchInput, optFns ...func(*Options)) (*SearchOutput, error)

Finds Amazon SageMaker resources that match a search query. Matching resources are returned as a list of SearchRecord objects in the response. You can sort the search results by any resource property in a ascending or descending order. You can query against the following value types: numeric, text, Boolean, and timestamp.

func (*Client) StartMonitoringSchedule 

func (c *Client) StartMonitoringSchedule(ctx context.Context, params *StartMonitoringScheduleInput, optFns ...func(*Options)) (*StartMonitoringScheduleOutput, error)

Starts a previously stopped monitoring schedule. New monitoring schedules are immediately started after creation.

func (*Client) StartNotebookInstance 

func (c *Client) StartNotebookInstance(ctx context.Context, params *StartNotebookInstanceInput, optFns ...func(*Options)) (*StartNotebookInstanceOutput, error)

Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, Amazon SageMaker sets the notebook instance status to InService. A notebook instance's status must be InService before you can connect to your Jupyter notebook.

func (*Client) StopAutoMLJob 

func (c *Client) StopAutoMLJob(ctx context.Context, params *StopAutoMLJobInput, optFns ...func(*Options)) (*StopAutoMLJobOutput, error)

A method for forcing the termination of a running job.

func (*Client) StopCompilationJob 

func (c *Client) StopCompilationJob(ctx context.Context, params *StopCompilationJobInput, optFns ...func(*Options)) (*StopCompilationJobOutput, error)

Stops a model compilation job. To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This gracefully shuts the job down. If the job hasn't stopped, it sends the SIGKILL signal. When it receives a StopCompilationJob request, Amazon SageMaker changes the CompilationJobSummary$CompilationJobStatus of the job to Stopping. After Amazon SageMaker stops the job, it sets the CompilationJobSummary$CompilationJobStatus to Stopped.

func (*Client) StopHyperParameterTuningJob 

func (c *Client) StopHyperParameterTuningJob(ctx context.Context, params *StopHyperParameterTuningJobInput, optFns ...func(*Options)) (*StopHyperParameterTuningJobOutput, error)

Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched. All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped state, it releases all reserved resources for the tuning job.

func (*Client) StopLabelingJob 

func (c *Client) StopLabelingJob(ctx context.Context, params *StopLabelingJobInput, optFns ...func(*Options)) (*StopLabelingJobOutput, error)

Stops a running labeling job. A job that is stopped cannot be restarted. Any results obtained before the job is stopped are placed in the Amazon S3 output bucket.

func (*Client) StopMonitoringSchedule 

func (c *Client) StopMonitoringSchedule(ctx context.Context, params *StopMonitoringScheduleInput, optFns ...func(*Options)) (*StopMonitoringScheduleOutput, error)

Stops a previously started monitoring schedule.

func (*Client) StopNotebookInstance 

func (c *Client) StopNotebookInstance(ctx context.Context, params *StopNotebookInstanceInput, optFns ...func(*Options)) (*StopNotebookInstanceOutput, error)

Terminates the ML compute instance. Before terminating the instance, Amazon SageMaker disconnects the ML storage volume from it. Amazon SageMaker preserves the ML storage volume. Amazon SageMaker stops charging you for the ML compute instance when you call StopNotebookInstance. To access data on the ML storage volume for a notebook instance that has been terminated, call the StartNotebookInstance API. StartNotebookInstance launches another ML compute instance, configures it, and attaches the preserved ML storage volume so you can continue your work.

func (*Client) StopProcessingJob 

func (c *Client) StopProcessingJob(ctx context.Context, params *StopProcessingJobInput, optFns ...func(*Options)) (*StopProcessingJobOutput, error)

Stops a processing job.

func (*Client) StopTrainingJob 

func (c *Client) StopTrainingJob(ctx context.Context, params *StopTrainingJobInput, optFns ...func(*Options)) (*StopTrainingJobOutput, error)

Stops a training job. To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost. When it receives a StopTrainingJob request, Amazon SageMaker changes the status of the job to Stopping. After Amazon SageMaker stops the job, it sets the status to Stopped.

func (*Client) StopTransformJob 

func (c *Client) StopTransformJob(ctx context.Context, params *StopTransformJobInput, optFns ...func(*Options)) (*StopTransformJobOutput, error)

Stops a transform job. When Amazon SageMaker receives a StopTransformJob request, the status of the job changes to Stopping. After Amazon SageMaker stops the job, the status is set to Stopped. When you stop a transform job before it is completed, Amazon SageMaker doesn't store the job's output in Amazon S3.

func (*Client) UpdateAppImageConfig added in v0.29.0 

func (c *Client) UpdateAppImageConfig(ctx context.Context, params *UpdateAppImageConfigInput, optFns ...func(*Options)) (*UpdateAppImageConfigOutput, error)

Updates the properties of an AppImageConfig.

func (*Client) UpdateCodeRepository 

func (c *Client) UpdateCodeRepository(ctx context.Context, params *UpdateCodeRepositoryInput, optFns ...func(*Options)) (*UpdateCodeRepositoryOutput, error)

Updates the specified Git repository with the specified values.

func (*Client) UpdateDomain 

func (c *Client) UpdateDomain(ctx context.Context, params *UpdateDomainInput, optFns ...func(*Options)) (*UpdateDomainOutput, error)

Updates the default settings for new user profiles in the domain.

func (*Client) UpdateEndpoint 

func (c *Client) UpdateEndpoint(ctx context.Context, params *UpdateEndpointInput, optFns ...func(*Options)) (*UpdateEndpointOutput, error)

Deploys the new EndpointConfig specified in the request, switches to using newly created endpoint, and then deletes resources provisioned for the endpoint using the previous EndpointConfig (there is no availability loss). When Amazon SageMaker receives the request, it sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API. You must not delete an EndpointConfig in use by an endpoint that is live or while the UpdateEndpoint or CreateEndpoint operations are being performed on the endpoint. To update an endpoint, you must create a new EndpointConfig. If you delete the EndpointConfig of an endpoint that is active or being created or updated you may lose visibility into the instance type the endpoint is using. The endpoint must be deleted in order to stop incurring charges.

func (*Client) UpdateEndpointWeightsAndCapacities 

func (c *Client) UpdateEndpointWeightsAndCapacities(ctx context.Context, params *UpdateEndpointWeightsAndCapacitiesInput, optFns ...func(*Options)) (*UpdateEndpointWeightsAndCapacitiesOutput, error)

Updates variant weight of one or more variants associated with an existing endpoint, or capacity of one variant associated with an existing endpoint. When it receives the request, Amazon SageMaker sets the endpoint status to Updating. After updating the endpoint, it sets the status to InService. To check the status of an endpoint, use the DescribeEndpoint API.

func (*Client) UpdateExperiment 

func (c *Client) UpdateExperiment(ctx context.Context, params *UpdateExperimentInput, optFns ...func(*Options)) (*UpdateExperimentOutput, error)

Adds, updates, or removes the description of an experiment. Updates the display name of an experiment.

func (*Client) UpdateImage added in v0.29.0 

func (c *Client) UpdateImage(ctx context.Context, params *UpdateImageInput, optFns ...func(*Options)) (*UpdateImageOutput, error)

Updates the properties of a SageMaker image. To change the image's tags, use the AddTags and DeleteTags APIs.

func (*Client) UpdateMonitoringSchedule 

func (c *Client) UpdateMonitoringSchedule(ctx context.Context, params *UpdateMonitoringScheduleInput, optFns ...func(*Options)) (*UpdateMonitoringScheduleOutput, error)

Updates a previously created schedule.

func (*Client) UpdateNotebookInstance 

func (c *Client) UpdateNotebookInstance(ctx context.Context, params *UpdateNotebookInstanceInput, optFns ...func(*Options)) (*UpdateNotebookInstanceOutput, error)

Updates a notebook instance. NotebookInstance updates include upgrading or downgrading the ML compute instance used for your notebook instance to accommodate changes in your workload requirements.

func (*Client) UpdateNotebookInstanceLifecycleConfig 

func (c *Client) UpdateNotebookInstanceLifecycleConfig(ctx context.Context, params *UpdateNotebookInstanceLifecycleConfigInput, optFns ...func(*Options)) (*UpdateNotebookInstanceLifecycleConfigOutput, error)

Updates a notebook instance lifecycle configuration created with the CreateNotebookInstanceLifecycleConfig API.

func (*Client) UpdateTrial 

func (c *Client) UpdateTrial(ctx context.Context, params *UpdateTrialInput, optFns ...func(*Options)) (*UpdateTrialOutput, error)

Updates the display name of a trial.

func (*Client) UpdateTrialComponent 

func (c *Client) UpdateTrialComponent(ctx context.Context, params *UpdateTrialComponentInput, optFns ...func(*Options)) (*UpdateTrialComponentOutput, error)

Updates one or more properties of a trial component.

func (*Client) UpdateUserProfile 

func (c *Client) UpdateUserProfile(ctx context.Context, params *UpdateUserProfileInput, optFns ...func(*Options)) (*UpdateUserProfileOutput, error)

Updates a user profile.

func (*Client) UpdateWorkforce 

func (c *Client) UpdateWorkforce(ctx context.Context, params *UpdateWorkforceInput, optFns ...func(*Options)) (*UpdateWorkforceOutput, error)

Use this operation to update your workforce. You can use this operation to require that workers use specific IP addresses to work on tasks and to update your OpenID Connect (OIDC) Identity Provider (IdP) workforce configuration. Use SourceIpConfig to restrict worker access to tasks to a specific range of IP addresses. You specify allowed IP addresses by creating a list of up to ten CIDRs (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html). By default, a workforce isn't restricted to specific IP addresses. If you specify a range of IP addresses, workers who attempt to access tasks using any IP address outside the specified range are denied and get a Not Found error message on the worker portal. Use OidcConfig to update the configuration of a workforce created using your own OIDC IdP. You can only update your OIDC IdP configuration when there are no work teams associated with your workforce. You can delete work teams using the operation. After restricting access to a range of IP addresses or updating your OIDC IdP configuration with this operation, you can view details about your update workforce using the operation. This operation only applies to private workforces.

func (*Client) UpdateWorkteam 

func (c *Client) UpdateWorkteam(ctx context.Context, params *UpdateWorkteamInput, optFns ...func(*Options)) (*UpdateWorkteamOutput, error)

Updates an existing work team with new member definitions or description.

type CreateAlgorithmInput 

type CreateAlgorithmInput struct {

	// The name of the algorithm.
	//
	// This member is required.
	AlgorithmName *string

	// 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.
	//
	// This member is required.
	TrainingSpecification *types.TrainingSpecification

	// A description of the algorithm.
	AlgorithmDescription *string

	// Whether to certify the algorithm so that it can be listed in AWS Marketplace.
	CertifyForMarketplace *bool

	// 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

	// 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 

type CreateAlgorithmOutput struct {

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

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

type CreateAppImageConfigInput added in v0.29.0 

type CreateAppImageConfigInput struct {

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

	// The KernelGatewayImageConfig.
	KernelGatewayImageConfig *types.KernelGatewayImageConfig

	// A list of tags to apply to the AppImageConfig.
	Tags []*types.Tag
}

type CreateAppImageConfigOutput added in v0.29.0 

type CreateAppImageConfigOutput struct {

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

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

type CreateAppInput 

type CreateAppInput struct {

	// The name of the app.
	//
	// This member is required.
	AppName *string

	// The type of app.
	//
	// This member is required.
	AppType types.AppType

	// The domain ID.
	//
	// This member is required.
	DomainId *string

	// The user profile name.
	//
	// This member is required.
	UserProfileName *string

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

	// Each tag consists of a key and an optional value. Tag keys must be unique per
	// resource.
	Tags []*types.Tag
}

type CreateAppOutput 

type CreateAppOutput struct {

	// The Amazon Resource Name (ARN) of the app.
	AppArn *string

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

type CreateAutoMLJobInput 

type CreateAutoMLJobInput struct {

	// Identifies an Autopilot job. Must be unique to your account and is
	// case-insensitive.
	//
	// This member is required.
	AutoMLJobName *string

	// Similar to InputDataConfig supported by Tuning. Format(s) supported: CSV.
	// Minimum of 500 rows.
	//
	// This member is required.
	InputDataConfig []*types.AutoMLChannel

	// Similar to OutputDataConfig supported by Tuning. Format(s) supported: CSV.
	//
	// This member is required.
	OutputDataConfig *types.AutoMLOutputDataConfig

	// The ARN of the role that is used to access the data.
	//
	// This member is required.
	RoleArn *string

	// Contains CompletionCriteria and SecurityConfig.
	AutoMLJobConfig *types.AutoMLJobConfig

	// Defines the objective of a an AutoML job. You provide a
	// AutoMLJobObjective$MetricName and Autopilot infers whether to minimize or
	// maximize it. If a metric is not specified, the most commonly used
	// ObjectiveMetric for problem type is automaically selected.
	AutoMLJobObjective *types.AutoMLJobObjective

	// Generates possible candidates without training a model. A candidate is a
	// combination of data preprocessors, algorithms, and algorithm parameter settings.
	GenerateCandidateDefinitionsOnly *bool

	// Defines the kind of preprocessing and algorithms intended for the candidates.
	// Options include: BinaryClassification, MulticlassClassification, and Regression.
	ProblemType types.ProblemType

	// Each tag consists of a key and an optional value. Tag keys must be unique per
	// resource.
	Tags []*types.Tag
}

type CreateAutoMLJobOutput 

type CreateAutoMLJobOutput struct {

	// When a job is created, it is assigned a unique ARN.
	//
	// This member is required.
	AutoMLJobArn *string

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

type CreateCodeRepositoryInput 

type CreateCodeRepositoryInput struct {

	// 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).
	//
	// This member is required.
	CodeRepositoryName *string

	// Specifies details about the repository, including the URL where the repository
	// is located, the default branch, and credentials to use to access the repository.
	//
	// This member is required.
	GitConfig *types.GitConfig
}

type CreateCodeRepositoryOutput 

type CreateCodeRepositoryOutput struct {

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

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

type CreateCompilationJobInput 

type CreateCompilationJobInput struct {

	// A name for the model compilation job. The name must be unique within the AWS
	// Region and within your AWS account.
	//
	// This member is required.
	CompilationJobName *string

	// 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.
	//
	// This member is required.
	InputConfig *types.InputConfig

	// Provides information about the output location for the compiled model and the
	// target device the model runs on.
	//
	// This member is required.
	OutputConfig *types.OutputConfig

	// 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)
	//
	// This member is required.
	RoleArn *string

	// 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.
	//
	// This member is required.
	StoppingCondition *types.StoppingCondition

	// An array of key-value pairs that you want to use to organize and track your AWS
	// resource costs. 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
}

type CreateCompilationJobOutput 

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

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

type CreateDomainInput 

type CreateDomainInput struct {

	// The mode of authentication that members use to access the domain.
	//
	// This member is required.
	AuthMode types.AuthMode

	// The default user settings.
	//
	// This member is required.
	DefaultUserSettings *types.UserSettings

	// A name for the domain.
	//
	// This member is required.
	DomainName *string

	// The VPC subnets that Studio uses for communication.
	//
	// This member is required.
	SubnetIds []*string

	// The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for
	// communication.
	//
	// This member is required.
	VpcId *string

	// Specifies the VPC used for non-EFS traffic. The default value is
	// PublicInternetOnly.
	//
	// * PublicInternetOnly - Non-EFS traffic is through a VPC
	// managed by Amazon SageMaker, which allows direct internet access
	//
	// * VpcOnly -
	// All Studio traffic is through the specified VPC and subnets
	AppNetworkAccessType types.AppNetworkAccessType

	// 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
}

type CreateDomainOutput 

type CreateDomainOutput struct {

	// The Amazon Resource Name (ARN) of the created domain.
	DomainArn *string

	// The URL to the created domain.
	Url *string

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

type CreateEndpointConfigInput 

type CreateEndpointConfigInput struct {

	// The name of the endpoint configuration. You specify this name in a
	// CreateEndpoint request.
	//
	// This member is required.
	EndpointConfigName *string

	// An list of ProductionVariant objects, one for each model that you want to host
	// at this endpoint.
	//
	// This member is required.
	ProductionVariants []*types.ProductionVariant

	//
	DataCaptureConfig *types.DataCaptureConfig

	// 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

	// 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
}

type CreateEndpointConfigOutput 

type CreateEndpointConfigOutput struct {

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

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

type CreateEndpointInput 

type CreateEndpointInput struct {

	// The name of an endpoint configuration. For more information, see
	// CreateEndpointConfig.
	//
	// This member is required.
	EndpointConfigName *string

	// The name of the endpoint.The name must be unique within an AWS Region in your
	// AWS account. The name is case-insensitive in CreateEndpoint, but the case is
	// preserved and must be matched in .
	//
	// This member is required.
	EndpointName *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
}

type CreateEndpointOutput 

type CreateEndpointOutput struct {

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

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

type CreateExperimentInput 

type CreateExperimentInput struct {

	// The name of the experiment. The name must be unique in your AWS account and is
	// not case-sensitive.
	//
	// This member is required.
	ExperimentName *string

	// The description of the experiment.
	Description *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 

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 

type CreateFlowDefinitionInput struct {

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

	// An object containing information about the tasks the human reviewers will
	// perform.
	//
	// This member is required.
	HumanLoopConfig *types.HumanLoopConfig

	// An object containing information about where the human review results will be
	// uploaded.
	//
	// This member is required.
	OutputConfig *types.FlowDefinitionOutputConfig

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

	// An object containing information about the events that trigger a human workflow.
	HumanLoopActivationConfig *types.HumanLoopActivationConfig

	// 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

	// 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
}

type CreateFlowDefinitionOutput 

type CreateFlowDefinitionOutput struct {

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

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

type CreateHumanTaskUiInput 

type CreateHumanTaskUiInput struct {

	// The name of the user interface you are creating.
	//
	// This member is required.
	HumanTaskUiName *string

	// The Liquid template for the worker user interface.
	//
	// This member is required.
	UiTemplate *types.UiTemplate

	// 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
}

type CreateHumanTaskUiOutput 

type CreateHumanTaskUiOutput struct {

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

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

type CreateHyperParameterTuningJobInput 

type CreateHyperParameterTuningJobInput struct {

	// 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).
	//
	// This member is required.
	HyperParameterTuningJobConfig *types.HyperParameterTuningJobConfig

	// 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 1 to 32 characters. Valid
	// characters are a-z, A-Z, 0-9, and : + = @ _ % - (hyphen). The name is not case
	// sensitive.
	//
	// This member is required.
	HyperParameterTuningJobName *string

	// 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 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

	// A list of the HyperParameterTrainingJobDefinition objects launched for this
	// tuning job.
	TrainingJobDefinitions []*types.HyperParameterTrainingJobDefinition

	// 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 

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

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

type CreateImageInput added in v0.29.0 

type CreateImageInput struct {

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

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

	// The description of the image.
	Description *string

	// The display name of the image. When the image is added to a domain, DisplayName
	// must be unique to the domain.
	DisplayName *string

	// A list of tags to apply to the image.
	Tags []*types.Tag
}

type CreateImageOutput added in v0.29.0 

type CreateImageOutput struct {

	// The Amazon Resource Name (ARN) of the image.
	ImageArn *string

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

type CreateImageVersionInput added in v0.29.0 

type CreateImageVersionInput struct {

	// The registry path of the container image to use as the starting point for this
	// version. The path is an Amazon Container Registry (ECR) URI in the following
	// format: .dkr.ecr..amazonaws.com/
	//
	// This member is required.
	BaseImage *string

	// A unique ID. If not specified, the AWS CLI and AWS SDKs, such as the SDK for
	// Python (Boto3), add a unique value to the call.
	//
	// This member is required.
	ClientToken *string

	// The ImageName of the Image to create a version of.
	//
	// This member is required.
	ImageName *string
}

type CreateImageVersionOutput added in v0.29.0 

type CreateImageVersionOutput struct {

	// The Amazon Resource Name (ARN) of the image version.
	ImageVersionArn *string

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

type CreateLabelingJobInput 

type CreateLabelingJobInput struct {

	// Configures the labeling task and how it is presented to workers; including, but
	// not limited to price, keywords, and batch size (task count).
	//
	// This member is required.
	HumanTaskConfig *types.HumanTaskConfig

	// 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.
	//
	// This member is required.
	InputConfig *types.LabelingJobInputConfig

	// 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".
	//
	// This member is required.
	LabelAttributeName *string

	// The name of the labeling job. This name is used to identify the job in a list of
	// labeling jobs.
	//
	// This member is required.
	LabelingJobName *string

	// 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.
	//
	// This member is required.
	OutputConfig *types.LabelingJobOutputConfig

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

	// The S3 URI 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

	// Configures the information required to perform automated data labeling.
	LabelingJobAlgorithmsConfig *types.LabelingJobAlgorithmsConfig

	// 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

	// 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
}

type CreateLabelingJobOutput 

type CreateLabelingJobOutput struct {

	// The Amazon Resource Name (ARN) of the labeling job. You use this ARN to identify
	// the labeling job.
	//
	// This member is required.
	LabelingJobArn *string

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

type CreateModelInput 

type CreateModelInput struct {

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

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

	// Specifies the containers in the inference pipeline.
	Containers []*types.ContainerDefinition

	// Isolates the model container. No inbound or outbound network calls can be made
	// to or from the model container.
	EnableNetworkIsolation *bool

	// 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

	// 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

	// 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
}

type CreateModelOutput 

type CreateModelOutput struct {

	// The ARN of the model created in Amazon SageMaker.
	//
	// This member is required.
	ModelArn *string

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

type CreateModelPackageInput 

type CreateModelPackageInput struct {

	// Whether to certify the model package for listing on AWS Marketplace.
	CertifyForMarketplace *bool

	// 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

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

	// 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

	// 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
}

type CreateModelPackageOutput 

type CreateModelPackageOutput struct {

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

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

type CreateMonitoringScheduleInput 

type CreateMonitoringScheduleInput struct {

	// The configuration object that specifies the monitoring schedule and defines the
	// monitoring job.
	//
	// This member is required.
	MonitoringScheduleConfig *types.MonitoringScheduleConfig

	// The name of the monitoring schedule. The name must be unique within an AWS
	// Region within an AWS account.
	//
	// This member is required.
	MonitoringScheduleName *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
}

type CreateMonitoringScheduleOutput 

type CreateMonitoringScheduleOutput struct {

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

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

type CreateNotebookInstanceInput 

type CreateNotebookInstanceInput struct {

	// The type of ML compute instance to launch for the notebook instance.
	//
	// This member is required.
	InstanceType types.InstanceType

	// The name of the new notebook instance.
	//
	// This member is required.
	NotebookInstanceName *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.
	//
	// This member is required.
	RoleArn *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

	// 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

	// 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

	// 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 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

	// 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 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

	// 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 tags to associate with the notebook instance. You can add tags later
	// by using the CreateTags API.
	Tags []*types.Tag

	// The size, in GB, of the ML storage volume to attach to the notebook instance.
	// The default value is 5 GB.
	VolumeSizeInGB *int32
}

type CreateNotebookInstanceLifecycleConfigInput 

type CreateNotebookInstanceLifecycleConfigInput struct {

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

	// 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
}

type CreateNotebookInstanceLifecycleConfigOutput 

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 

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 

type CreatePresignedDomainUrlInput struct {

	// The domain ID.
	//
	// This member is required.
	DomainId *string

	// The name of the UserProfile to sign-in as.
	//
	// This member is required.
	UserProfileName *string

	// The session expiration duration in seconds.
	SessionExpirationDurationInSeconds *int32
}

type CreatePresignedDomainUrlOutput 

type CreatePresignedDomainUrlOutput struct {

	// The presigned URL.
	AuthorizedUrl *string

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

type CreatePresignedNotebookInstanceUrlInput 

type CreatePresignedNotebookInstanceUrlInput struct {

	// The name of the notebook instance.
	//
	// This member is required.
	NotebookInstanceName *string

	// The duration of the session, in seconds. The default is 12 hours.
	SessionExpirationDurationInSeconds *int32
}

type CreatePresignedNotebookInstanceUrlOutput 

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 

type CreateProcessingJobInput struct {

	// Configures the processing job to run a specified Docker container image.
	//
	// This member is required.
	AppSpecification *types.AppSpecification

	// The name of the processing job. The name must be unique within an AWS Region in
	// the AWS account.
	//
	// This member is required.
	ProcessingJobName *string

	// 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.
	//
	// This member is required.
	ProcessingResources *types.ProcessingResources

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

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

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

	// Networking options for a processing job.
	NetworkConfig *types.NetworkConfig

	// 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

	// Output configuration for the processing job.
	ProcessingOutputConfig *types.ProcessingOutputConfig

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

	// (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 CreateProcessingJobOutput 

type CreateProcessingJobOutput struct {

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

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

type CreateTrainingJobInput 

type CreateTrainingJobInput struct {

	// 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).
	//
	// This member is required.
	AlgorithmSpecification *types.AlgorithmSpecification

	// Specifies the path to the S3 location where you want to store model artifacts.
	// Amazon SageMaker creates subfolders for the artifacts.
	//
	// This member is required.
	OutputDataConfig *types.OutputDataConfig

	// 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.
	//
	// This member is required.
	ResourceConfig *types.ResourceConfig

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

	// 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.
	//
	// This member is required.
	StoppingCondition *types.StoppingCondition

	// The name of the training job. The name must be unique within an AWS Region in an
	// AWS account.
	//
	// This member is required.
	TrainingJobName *string

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

	// Configuration information for the debug hook parameters, collection
	// configuration, and storage paths.
	DebugHookConfig *types.DebugHookConfig

	// Configuration information for debugging rules.
	DebugRuleConfigurations []*types.DebugRuleConfiguration

	// 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

	// 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

	// 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

	// 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 Channel objects. Each channel is a named input source.
	// InputDataConfig describes the input data and its location. Algorithms can accept
	// input data from one or more channels. For example, an algorithm might have two
	// channels of input data, training_data and validation_data. 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.
	// 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.
	InputDataConfig []*types.Channel

	// 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

	// Configuration of storage locations for TensorBoard output.
	TensorBoardOutputConfig *types.TensorBoardOutputConfig

	// 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
}

type CreateTrainingJobOutput 

type CreateTrainingJobOutput struct {

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

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

type CreateTransformJobInput 

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

	// Describes the input source and the way the transform job consumes it.
	//
	// This member is required.
	TransformInput *types.TransformInput

	// The name of the transform job. The name must be unique within an AWS Region in
	// an AWS account.
	//
	// This member is required.
	TransformJobName *string

	// Describes the results of the transform job.
	//
	// This member is required.
	TransformOutput *types.TransformOutput

	// Describes the resources, including ML instance types and ML instance count, to
	// use for the transform job.
	//
	// This member is required.
	TransformResources *types.TransformResources

	// 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

	// 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

	// 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 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

	// 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

	// Configures the timeout and maximum number of retries for processing a transform
	// job invocation.
	ModelClientConfig *types.ModelClientConfig

	// (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
}

type CreateTransformJobOutput 

type CreateTransformJobOutput struct {

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

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

type CreateTrialComponentInput 

type CreateTrialComponentInput struct {

	// The name of the component. The name must be unique in your AWS account and is
	// not case-sensitive.
	//
	// This member is required.
	TrialComponentName *string

	// 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 ended.
	EndTime *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

	// The output artifacts for the component. Examples of output artifacts are
	// metrics, snapshots, logs, and images.
	OutputArtifacts map[string]*types.TrialComponentArtifact

	// The hyperparameters for the component.
	Parameters map[string]*types.TrialComponentParameterValue

	// When the component started.
	StartTime *time.Time

	// The status of the component. States include:
	//
	// * InProgress
	//
	// * Completed
	//
	// *
	// Failed
	Status *types.TrialComponentStatus

	// A list of tags to associate with the component. You can use Search API to search
	// on the tags.
	Tags []*types.Tag
}

type CreateTrialComponentOutput 

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 

type CreateTrialInput struct {

	// The name of the experiment to associate the trial with.
	//
	// This member is required.
	ExperimentName *string

	// The name of the trial. The name must be unique in your AWS account and is not
	// case-sensitive.
	//
	// This member is required.
	TrialName *string

	// 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

	// A list of tags to associate with the trial. You can use Search API to search on
	// the tags.
	Tags []*types.Tag
}

type CreateTrialOutput 

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 

type CreateUserProfileInput struct {

	// The ID of the associated Domain.
	//
	// This member is required.
	DomainId *string

	// A name for the UserProfile.
	//
	// This member is required.
	UserProfileName *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

	// 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

	// Each tag consists of a key and an optional value. Tag keys must be unique per
	// resource.
	Tags []*types.Tag

	// A collection of settings.
	UserSettings *types.UserSettings
}

type CreateUserProfileOutput 

type CreateUserProfileOutput struct {

	// The user profile Amazon Resource Name (ARN).
	UserProfileArn *string

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

type CreateWorkforceInput 

type CreateWorkforceInput struct {

	// The name of the private workforce.
	//
	// This member is required.
	WorkforceName *string

	// 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).
	// Do not use OidcConfig if you specify values for CognitoConfig.
	CognitoConfig *types.CognitoConfig

	// 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

	// A list of IP address ranges (CIDRs
	// (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html)). Used to
	// create an allow list of IP addresses for a private workforce. Workers will only
	// be able to login to their worker portal from an IP address within this range. By
	// default, a workforce isn't restricted to specific IP addresses.
	SourceIpConfig *types.SourceIpConfig

	// 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
}

type CreateWorkforceOutput 

type CreateWorkforceOutput struct {

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

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

type CreateWorkteamInput 

type CreateWorkteamInput struct {

	// A description of the work team.
	//
	// This member is required.
	Description *string

	// A list of MemberDefinition objects that contains objects that identify the
	// workers that make up the work team. Workforces can be created using Amazon
	// Cognito or your own OIDC Identity Provider (IdP). For private workforces created
	// using Amazon Cognito use CognitoMemberDefinition. For workforces created using
	// your own OIDC identity provider (IdP) use OidcMemberDefinition. Do not provide
	// input for both of these parameters in a single request. For workforces created
	// using Amazon Cognito, private work teams correspond to Amazon Cognito user
	// groups within the user pool used to create a workforce. All of the
	// CognitoMemberDefinition objects that make up the member definition must have the
	// same ClientId and UserPool values. To add a Amazon Cognito user group to an
	// existing worker pool, see Adding groups to a User Pool. For more information
	// about user pools, see Amazon Cognito User Pools
	// (https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html).
	// For workforces created using your own OIDC IdP, specify the user groups that you
	// want to include in your private work team in OidcMemberDefinition by listing
	// those groups in Groups.
	//
	// This member is required.
	MemberDefinitions []*types.MemberDefinition

	// The name of the work team. Use this name to identify the work team.
	//
	// This member is required.
	WorkteamName *string

	// Configures notification of workers regarding available or expiring work items.
	NotificationConfiguration *types.NotificationConfiguration

	// 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

	// The name of the workforce.
	WorkforceName *string
}

type CreateWorkteamOutput 

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 

type DeleteAlgorithmInput struct {

	// The name of the algorithm to delete.
	//
	// This member is required.
	AlgorithmName *string
}

type DeleteAlgorithmOutput 

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

type DeleteAppImageConfigInput added in v0.29.0 

type DeleteAppImageConfigInput struct {

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

type DeleteAppImageConfigOutput added in v0.29.0 

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

type DeleteAppInput 

type DeleteAppInput struct {

	// The name of the app.
	//
	// This member is required.
	AppName *string

	// The type of app.
	//
	// This member is required.
	AppType types.AppType

	// The domain ID.
	//
	// This member is required.
	DomainId *string

	// The user profile name.
	//
	// This member is required.
	UserProfileName *string
}

type DeleteAppOutput 

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

type DeleteCodeRepositoryInput 

type DeleteCodeRepositoryInput struct {

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

type DeleteCodeRepositoryOutput 

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

type DeleteDomainInput 

type DeleteDomainInput struct {

	// The domain ID.
	//
	// This member is required.
	DomainId *string

	// 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
}

type DeleteDomainOutput 

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

type DeleteEndpointConfigInput 

type DeleteEndpointConfigInput struct {

	// The name of the endpoint configuration that you want to delete.
	//
	// This member is required.
	EndpointConfigName *string
}

type DeleteEndpointConfigOutput 

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

type DeleteEndpointInput 

type DeleteEndpointInput struct {

	// The name of the endpoint that you want to delete.
	//
	// This member is required.
	EndpointName *string
}

type DeleteEndpointOutput 

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

type DeleteExperimentInput 

type DeleteExperimentInput struct {

	// The name of the experiment to delete.
	//
	// This member is required.
	ExperimentName *string
}

type DeleteExperimentOutput 

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 

type DeleteFlowDefinitionInput struct {

	// The name of the flow definition you are deleting.
	//
	// This member is required.
	FlowDefinitionName *string
}

type DeleteFlowDefinitionOutput 

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

type DeleteHumanTaskUiInput 

type DeleteHumanTaskUiInput struct {

	// The name of the human task user interface (work task template) you want to
	// delete.
	//
	// This member is required.
	HumanTaskUiName *string
}

type DeleteHumanTaskUiOutput 

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

type DeleteImageInput added in v0.29.0 

type DeleteImageInput struct {

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

type DeleteImageOutput added in v0.29.0 

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

type DeleteImageVersionInput added in v0.29.0 

type DeleteImageVersionInput struct {

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

	// The version to delete.
	//
	// This member is required.
	Version *int32
}

type DeleteImageVersionOutput added in v0.29.0 

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

type DeleteModelInput 

type DeleteModelInput struct {

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

type DeleteModelOutput 

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

type DeleteModelPackageInput 

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

type DeleteModelPackageOutput 

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

type DeleteMonitoringScheduleInput 

type DeleteMonitoringScheduleInput struct {

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

type DeleteMonitoringScheduleOutput 

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

type DeleteNotebookInstanceInput 

type DeleteNotebookInstanceInput struct {

	// The name of the Amazon SageMaker notebook instance to delete.
	//
	// This member is required.
	NotebookInstanceName *string
}

type DeleteNotebookInstanceLifecycleConfigInput 

type DeleteNotebookInstanceLifecycleConfigInput struct {

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

type DeleteNotebookInstanceLifecycleConfigOutput 

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

type DeleteNotebookInstanceOutput 

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

type DeleteTagsInput 

type DeleteTagsInput struct {

	// The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
	//
	// This member is required.
	ResourceArn *string

	// An array or one or more tag keys to delete.
	//
	// This member is required.
	TagKeys []*string
}

type DeleteTagsOutput 

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

type DeleteTrialComponentInput 

type DeleteTrialComponentInput struct {

	// The name of the component to delete.
	//
	// This member is required.
	TrialComponentName *string
}

type DeleteTrialComponentOutput 

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 

type DeleteTrialInput struct {

	// The name of the trial to delete.
	//
	// This member is required.
	TrialName *string
}

type DeleteTrialOutput 

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 

type DeleteUserProfileInput struct {

	// The domain ID.
	//
	// This member is required.
	DomainId *string

	// The user profile name.
	//
	// This member is required.
	UserProfileName *string
}

type DeleteUserProfileOutput 

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

type DeleteWorkforceInput 

type DeleteWorkforceInput struct {

	// The name of the workforce.
	//
	// This member is required.
	WorkforceName *string
}

type DeleteWorkforceOutput 

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

type DeleteWorkteamInput 

type DeleteWorkteamInput struct {

	// The name of the work team to delete.
	//
	// This member is required.
	WorkteamName *string
}

type DeleteWorkteamOutput 

type DeleteWorkteamOutput struct {

	// Returns true if the work team was successfully deleted; otherwise, returns
	// false.
	//
	// This member is required.
	Success *bool

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

type DescribeAlgorithmInput 

type DescribeAlgorithmInput struct {

	// The name of the algorithm to describe.
	//
	// This member is required.
	AlgorithmName *string
}

type DescribeAlgorithmOutput 

type DescribeAlgorithmOutput struct {

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

	// The name of the algorithm being described.
	//
	// This member is required.
	AlgorithmName *string

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

	// Details about the current status of the algorithm.
	//
	// This member is required.
	AlgorithmStatusDetails *types.AlgorithmStatusDetails

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

	// Details about training jobs run by this algorithm.
	//
	// This member is required.
	TrainingSpecification *types.TrainingSpecification

	// A brief summary about the algorithm.
	AlgorithmDescription *string

	// Whether the algorithm is certified to be listed in AWS Marketplace.
	CertifyForMarketplace *bool

	// Details about inference jobs that the algorithm runs.
	InferenceSpecification *types.InferenceSpecification

	// The product identifier of the algorithm.
	ProductId *string

	// Details about configurations for one or more training jobs that Amazon SageMaker
	// runs to test the algorithm.
	ValidationSpecification *types.AlgorithmValidationSpecification

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

type DescribeAppImageConfigInput added in v0.29.0 

type DescribeAppImageConfigInput struct {

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

type DescribeAppImageConfigOutput added in v0.29.0 

type DescribeAppImageConfigOutput struct {

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

	// The name of the AppImageConfig.
	AppImageConfigName *string

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

	// The KernelGateway app.
	KernelGatewayImageConfig *types.KernelGatewayImageConfig

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

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

type DescribeAppInput 

type DescribeAppInput struct {

	// The name of the app.
	//
	// This member is required.
	AppName *string

	// The type of app.
	//
	// This member is required.
	AppType types.AppType

	// The domain ID.
	//
	// This member is required.
	DomainId *string

	// The user profile name.
	//
	// This member is required.
	UserProfileName *string
}

type DescribeAppOutput 

type DescribeAppOutput struct {

	// The Amazon Resource Name (ARN) of the app.
	AppArn *string

	// The name of the app.
	AppName *string

	// The type of app.
	AppType types.AppType

	// The creation time.
	CreationTime *time.Time

	// The domain ID.
	DomainId *string

	// The failure reason.
	FailureReason *string

	// The timestamp of the last health check.
	LastHealthCheckTimestamp *time.Time

	// The timestamp of the last user's activity.
	LastUserActivityTimestamp *time.Time

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

	// The status.
	Status types.AppStatus

	// The user profile name.
	UserProfileName *string

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

type DescribeAutoMLJobInput 

type DescribeAutoMLJobInput struct {

	// Request information about a job using that job's unique name.
	//
	// This member is required.
	AutoMLJobName *string
}

type DescribeAutoMLJobOutput 

type DescribeAutoMLJobOutput struct {

	// Returns the job's ARN.
	//
	// This member is required.
	AutoMLJobArn *string

	// Returns the name of a job.
	//
	// This member is required.
	AutoMLJobName *string

	// Returns the job's AutoMLJobSecondaryStatus.
	//
	// This member is required.
	AutoMLJobSecondaryStatus types.AutoMLJobSecondaryStatus

	// Returns the job's AutoMLJobStatus.
	//
	// This member is required.
	AutoMLJobStatus types.AutoMLJobStatus

	// Returns the job's creation time.
	//
	// This member is required.
	CreationTime *time.Time

	// Returns the job's input data config.
	//
	// This member is required.
	InputDataConfig []*types.AutoMLChannel

	// Returns the job's last modified time.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// Returns the job's output data config.
	//
	// This member is required.
	OutputDataConfig *types.AutoMLOutputDataConfig

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

	// Returns information on the job's artifacts found in AutoMLJobArtifacts.
	AutoMLJobArtifacts *types.AutoMLJobArtifacts

	// Returns the job's config.
	AutoMLJobConfig *types.AutoMLJobConfig

	// Returns the job's objective.
	AutoMLJobObjective *types.AutoMLJobObjective

	// Returns the job's BestCandidate.
	BestCandidate *types.AutoMLCandidate

	// Returns the job's end time.
	EndTime *time.Time

	// Returns the job's FailureReason.
	FailureReason *string

	// Returns the job's output from GenerateCandidateDefinitionsOnly.
	GenerateCandidateDefinitionsOnly *bool

	// Returns the job's problem type.
	ProblemType types.ProblemType

	// 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

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

type DescribeCodeRepositoryInput 

type DescribeCodeRepositoryInput struct {

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

type DescribeCodeRepositoryOutput 

type DescribeCodeRepositoryOutput struct {

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

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

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

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

	// 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

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

type DescribeCompilationJobInput 

type DescribeCompilationJobInput struct {

	// The name of the model compilation job that you want information about.
	//
	// This member is required.
	CompilationJobName *string
}

type DescribeCompilationJobOutput 

type DescribeCompilationJobOutput struct {

	// The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker assumes to
	// perform the model compilation job.
	//
	// This member is required.
	CompilationJobArn *string

	// The name of the model compilation job.
	//
	// This member is required.
	CompilationJobName *string

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

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

	// If a model compilation job failed, the reason it failed.
	//
	// This member is required.
	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.
	//
	// This member is required.
	InputConfig *types.InputConfig

	// The time that the status of the model compilation job was last modified.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// Information about the location in Amazon S3 that has been configured for storing
	// the model artifacts used in the compilation job.
	//
	// This member is required.
	ModelArtifacts *types.ModelArtifacts

	// Information about the output location for the compiled model and the target
	// device that the model runs on.
	//
	// This member is required.
	OutputConfig *types.OutputConfig

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

	// 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.
	//
	// This member is required.
	StoppingCondition *types.StoppingCondition

	// 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

	// 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

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

type DescribeDomainInput 

type DescribeDomainInput struct {

	// The domain ID.
	//
	// This member is required.
	DomainId *string
}

type DescribeDomainOutput 

type DescribeDomainOutput struct {

	// Specifies the VPC used for non-EFS traffic. The default value is
	// PublicInternetOnly.
	//
	// * PublicInternetOnly - Non-EFS traffic is through a VPC
	// managed by Amazon SageMaker, which allows direct internet access
	//
	// * VpcOnly -
	// All Studio traffic is through the specified VPC and subnets
	AppNetworkAccessType types.AppNetworkAccessType

	// The domain's authentication mode.
	AuthMode types.AuthMode

	// The creation time.
	CreationTime *time.Time

	// Settings which are applied to all UserProfile in this domain, if settings are
	// not explicitly specified in a given UserProfile.
	DefaultUserSettings *types.UserSettings

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

	// The domain ID.
	DomainId *string

	// The domain name.
	DomainName *string

	// The failure reason.
	FailureReason *string

	// The ID of the Amazon Elastic File System (EFS) managed by this Domain.
	HomeEfsFileSystemId *string

	// The AWS Key Management Service encryption key ID.
	HomeEfsFileSystemKmsKeyId *string

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

	// The SSO managed application instance ID.
	SingleSignOnManagedApplicationInstanceId *string

	// The status.
	Status types.DomainStatus

	// The VPC subnets that Studio uses for communication.
	SubnetIds []*string

	// The domain's URL.
	Url *string

	// The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses for
	// communication.
	VpcId *string

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

type DescribeEndpointConfigInput 

type DescribeEndpointConfigInput struct {

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

type DescribeEndpointConfigOutput 

type DescribeEndpointConfigOutput struct {

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

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

	// Name of the Amazon SageMaker endpoint configuration.
	//
	// This member is required.
	EndpointConfigName *string

	// An array of ProductionVariant objects, one for each model that you want to host
	// at this endpoint.
	//
	// This member is required.
	ProductionVariants []*types.ProductionVariant

	//
	DataCaptureConfig *types.DataCaptureConfig

	// AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the ML
	// storage volume attached to the instance.
	KmsKeyId *string

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

type DescribeEndpointInput 

type DescribeEndpointInput struct {

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

type DescribeEndpointOutput 

type DescribeEndpointOutput struct {

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

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

	// The name of the endpoint configuration associated with this endpoint.
	//
	// This member is required.
	EndpointConfigName *string

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

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

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

	//
	DataCaptureConfig *types.DataCaptureConfigSummary

	// If the status of the endpoint is Failed, the reason why it failed.
	FailureReason *string

	// An array of ProductionVariantSummary objects, one for each model hosted behind
	// this endpoint.
	ProductionVariants []*types.ProductionVariantSummary

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

type DescribeExperimentInput 

type DescribeExperimentInput struct {

	// The name of the experiment to describe.
	//
	// This member is required.
	ExperimentName *string
}

type DescribeExperimentOutput 

type DescribeExperimentOutput struct {

	// Who created the experiment.
	CreatedBy *types.UserContext

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

	// The description of the experiment.
	Description *string

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

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

	// The name of the experiment.
	ExperimentName *string

	// Who last modified the experiment.
	LastModifiedBy *types.UserContext

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

	// The ARN of the source and, optionally, the type.
	Source *types.ExperimentSource

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

type DescribeFlowDefinitionInput 

type DescribeFlowDefinitionInput struct {

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

type DescribeFlowDefinitionOutput 

type DescribeFlowDefinitionOutput struct {

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

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

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

	// The status of the flow definition. Valid values are listed below.
	//
	// This member is required.
	FlowDefinitionStatus types.FlowDefinitionStatus

	// An object containing information about who works on the task, the workforce task
	// price, and other task details.
	//
	// This member is required.
	HumanLoopConfig *types.HumanLoopConfig

	// An object containing information about the output file.
	//
	// This member is required.
	OutputConfig *types.FlowDefinitionOutputConfig

	// The Amazon Resource Name (ARN) of the AWS Identity and Access Management (IAM)
	// execution role for the flow definition.
	//
	// This member is required.
	RoleArn *string

	// The reason your flow definition failed.
	FailureReason *string

	// 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

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

type DescribeHumanTaskUiInput 

type DescribeHumanTaskUiInput struct {

	// The name of the human task user interface (worker task template) you want
	// information about.
	//
	// This member is required.
	HumanTaskUiName *string
}

type DescribeHumanTaskUiOutput 

type DescribeHumanTaskUiOutput struct {

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

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

	// The name of the human task user interface (worker task template).
	//
	// This member is required.
	HumanTaskUiName *string

	// Container for user interface template information.
	//
	// This member is required.
	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 

type DescribeHyperParameterTuningJobInput struct {

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

type DescribeHyperParameterTuningJobOutput 

type DescribeHyperParameterTuningJobOutput struct {

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

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

	// The HyperParameterTuningJobConfig object that specifies the configuration of the
	// tuning job.
	//
	// This member is required.
	HyperParameterTuningJobConfig *types.HyperParameterTuningJobConfig

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

	// The status of the tuning job: InProgress, Completed, Failed, Stopping, or
	// Stopped.
	//
	// This member is required.
	HyperParameterTuningJobStatus types.HyperParameterTuningJobStatus

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

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

	// A TrainingJobSummary object that describes the training job that completed with
	// the best current HyperParameterTuningJobObjective.
	BestTrainingJob *types.HyperParameterTrainingJobSummary

	// If the tuning job failed, the reason it failed.
	FailureReason *string

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

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

	// 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 HyperParameterTrainingJobDefinition object that specifies the definition of
	// the training jobs that this tuning job launches.
	TrainingJobDefinition *types.HyperParameterTrainingJobDefinition

	// A list of the HyperParameterTrainingJobDefinition objects launched for this
	// tuning job.
	TrainingJobDefinitions []*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

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

type DescribeImageInput added in v0.29.0 

type DescribeImageInput struct {

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

type DescribeImageOutput added in v0.29.0 

type DescribeImageOutput struct {

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

	// The description of the image.
	Description *string

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

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

	// The Amazon Resource Name (ARN) of the image.
	ImageArn *string

	// The name of the image.
	ImageName *string

	// The status of the image.
	ImageStatus types.ImageStatus

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

	// The Amazon Resource Name (ARN) of the IAM role that enables Amazon SageMaker to
	// perform tasks on your behalf.
	RoleArn *string

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

type DescribeImageVersionInput added in v0.29.0 

type DescribeImageVersionInput struct {

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

	// The version of the image. If not specified, the latest version is described.
	Version *int32
}

type DescribeImageVersionOutput added in v0.29.0 

type DescribeImageVersionOutput struct {

	// The registry path of the container image on which this image version is based.
	BaseImage *string

	// The registry path of the container image that contains this image version.
	ContainerImage *string

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

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

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

	// The ARN of the version.
	ImageVersionArn *string

	// The status of the version.
	ImageVersionStatus types.ImageVersionStatus

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

	// The version number.
	Version *int32

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

type DescribeLabelingJobInput 

type DescribeLabelingJobInput struct {

	// The name of the labeling job to return information for.
	//
	// This member is required.
	LabelingJobName *string
}

type DescribeLabelingJobOutput 

type DescribeLabelingJobOutput struct {

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

	// Configuration information required for human workers to complete a labeling
	// task.
	//
	// This member is required.
	HumanTaskConfig *types.HumanTaskConfig

	// 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.
	//
	// This member is required.
	InputConfig *types.LabelingJobInputConfig

	// A unique identifier for work done as part of a labeling job.
	//
	// This member is required.
	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.
	//
	// This member is required.
	LabelCounters *types.LabelCounters

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

	// The name assigned to the labeling job when it was created.
	//
	// This member is required.
	LabelingJobName *string

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

	// The date and time that the labeling job was last updated.
	//
	// This member is required.
	LastModifiedTime *time.Time

	// 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.
	//
	// This member is required.
	OutputConfig *types.LabelingJobOutputConfig

	// The Amazon Resource Name (ARN) that Amazon SageMaker assumes to perform tasks on
	// your behalf during data labeling.
	//
	// This member is required.
	RoleArn *string

	// If the job failed, the reason that it failed.
	FailureReason *string

	// The attribute used as the label in the output manifest file.
	LabelAttributeName *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

	// Configuration information for automated data labeling.
	LabelingJobAlgorithmsConfig *types.LabelingJobAlgorithmsConfig

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

	// A set of conditions for stopping a labeling job. If any of the conditions are
	// met, the job is automatically stopped.
	StoppingConditions *types.LabelingJobStoppingConditions

	// 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

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

type DescribeModelInput 

type DescribeModelInput struct {

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

type DescribeModelOutput 

type DescribeModelOutput struct {

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

	// The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
	//
	// This member is required.
	ExecutionRoleArn *string

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

	// Name of the Amazon SageMaker model.
	//
	// This member is required.
	ModelName *string

	// The containers in the inference pipeline.
	Containers []*types.ContainerDefinition

	// If True, no inbound or outbound network calls can be made to or from the model
	// container.
	EnableNetworkIsolation *bool

	// 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 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

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

type DescribeModelPackageInput 

type DescribeModelPackageInput struct {

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

type DescribeModelPackageOutput 

type DescribeModelPackageOutput struct {

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

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

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

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

	// Details about the current status of the model package.
	//
	// This member is required.
	ModelPackageStatusDetails *types.ModelPackageStatusDetails

	// Whether the model package is certified for listing on AWS Marketplace.
	CertifyForMarketplace *bool

	// Details about inference jobs that can be run with models based on this model
	// package.
	InferenceSpecification *types.InferenceSpecification

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

	// Details about the algorithm that was used to create the model package.
	SourceAlgorithmSpecification *types.SourceAlgorithmSpecification

	// Configurations for one or more transform jobs that Amazon SageMaker runs to test
	// the model package.
	ValidationSpecification *types.ModelPackageValidationSpecification

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

type DescribeMonitoringScheduleInput 

type DescribeMonitoringScheduleInput struct {

	// Name of a previously created monitoring schedule.
	//
	// This member is required.
	MonitoringScheduleName *string
}

type DescribeMonitoringScheduleOutput 

type DescribeMonitoringScheduleOutput struct {

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

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

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

	// The configuration object that specifies the monitoring schedule and defines the
	// monitoring job.
	//
	// This member is required.
	MonitoringScheduleConfig *types.MonitoringScheduleConfig

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

	// The status of an monitoring job.
	//
	// This member is required.
	MonitoringScheduleStatus types.ScheduleStatus

	// The name of the endpoint for the monitoring job.
	EndpointName *string

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

	// Describes metadata on the last execution to run, if there was one.
	LastMonitoringExecutionSummary *types.MonitoringExecutionSummary

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

type DescribeNotebookInstanceInput 

type DescribeNotebookInstanceInput struct {

	// The name of the notebook instance that you want information about.
	//
	// This member is required.
	NotebookInstanceName *string
}

type DescribeNotebookInstanceLifecycleConfigInput 

type DescribeNotebookInstanceLifecycleConfigInput struct {

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

type DescribeNotebookInstanceLifecycleConfigOutput 

type DescribeNotebookInstanceLifecycleConfigOutput struct {

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

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

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

	// The name of the lifecycle configuration.
	NotebookInstanceLifecycleConfigName *string

	// The shell script that runs only once, when you create a notebook instance.
	OnCreate []*types.NotebookInstanceLifecycleHook

	// The shell script that runs every time you start a notebook instance, including
	// when you create the notebook instance.
	OnStart []*types.NotebookInstanceLifecycleHook

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

type DescribeNotebookInstanceOutput 

type DescribeNotebookInstanceOutput struct {

	// 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

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

	// A timestamp. Use this parameter to return the time when the notebook instance
	// was created
	CreationTime *time.Time

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

	// 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

	// If status is Failed, the reason it failed.
	FailureReason *string

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

	// 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

	// A timestamp. Use this parameter to retrieve the time when the notebook instance
	// was last modified.
	LastModifiedTime *time.Time

	// The network interface IDs that Amazon SageMaker created at the time of creating
	// the instance.
	NetworkInterfaceId *string

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

	// 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

	// The name of the Amazon SageMaker notebook instance.
	NotebookInstanceName *string

	// The status of the notebook instance.
	NotebookInstanceStatus types.NotebookInstanceStatus

	// The Amazon Resource Name (ARN) of the IAM role associated with the instance.
	RoleArn *string

	// 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 IDs of the VPC security groups.
	SecurityGroups []*string

	// The ID of the VPC subnet.
	SubnetId *string

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

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

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

type DescribeProcessingJobInput 

type DescribeProcessingJobInput struct {

	// The name of the processing job. The name must be unique within an AWS Region in
	// the AWS account.
	//
	// This member is required.
	ProcessingJobName *string
}

type DescribeProcessingJobOutput 

type DescribeProcessingJobOutput struct {

	// Configures the processing job to run a specified container image.
	//
	// This member is required.
	AppSpecification *types.AppSpecification

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

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

	// The name of the processing job. The name must be unique within an AWS Region in
	// the AWS account.
	//
	// This member is required.
	ProcessingJobName *string

	// Provides the status of a processing job.
	//
	// This member is required.
	ProcessingJobStatus types.ProcessingJobStatus

	// 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.
	//
	// This member is required.
	ProcessingResources *types.ProcessingResources

	// The ARN of an AutoML job associated with this processing job.
	AutoMLJobArn *string

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

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

	// The configuration information used to create an experiment.
	ExperimentConfig *types.ExperimentConfig

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

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

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

	// Networking options for a processing job.
	NetworkConfig *types.NetworkConfig

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

	// The inputs for a processing job.
	ProcessingInputs []*types.ProcessingInput

	// Output configuration for the processing job.
	ProcessingOutputConfig *types.ProcessingOutputConfig

	// The time at which the processing job started.
	ProcessingStartTime *time.Time

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

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

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

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

type DescribeSubscribedWorkteamInput 

type DescribeSubscribedWorkteamInput struct {

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

type DescribeSubscribedWorkteamOutput 

type DescribeSubscribedWorkteamOutput struct {

	// A Workteam instance that contains information about the work team.
	//
	// This member is required.
	SubscribedWorkteam *types.SubscribedWorkteam

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

type DescribeTrainingJobInput 

type DescribeTrainingJobInput struct {

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

type DescribeTrainingJobOutput 

type DescribeTrainingJobOutput struct {

	// Information about the algorithm used for training, and algorithm metadata.
	//
	// This member is required.
	AlgorithmSpecification *types.AlgorithmSpecification

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

	// Information about the Amazon S3 location that is configured for storing model
	// artifacts.
	//
	// This member is required.
	ModelArtifacts *types.ModelArtifacts

	// Resources, including ML compute instances and ML storage volumes, that are
	// configured for model training.
	//
	// This member is required.
	ResourceConfig *types.ResourceConfig

	// 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.
	//
	// * MaxWaitTimeExceeded - The
	// job stopped because it exceeded the maximum allowed wait time.
	//
	// * Stopped - The
	// training job has stopped.
	//
	// Stopping
	//
	// * Stopping - Stopping the training
	// job.
	//
	// Valid values for SecondaryStatus are subject to change. We no longer
	// support the following secondary statuses:
	//
	// * LaunchingMLInstances
	//
	// *
	// PreparingTrainingStack
	//
	// * DownloadingTrainingImage
	//
	// This member is required.
	SecondaryStatus types.SecondaryStatus

	// 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.
	//
	// This member is required.
	StoppingCondition *types.StoppingCondition

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

	// Name of the model training job.
	//
	// This member is required.
	TrainingJobName *string

	// 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.
	//
	// This member is required.
	TrainingJobStatus types.TrainingJobStatus

	// The Amazon Resource Name (ARN) of an AutoML job.
	AutoMLJobArn *string

	// 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

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

	// Configuration information for the debug hook parameters, collection
	// configuration, and storage paths.
	DebugHookConfig *types.DebugHookConfig

	// Configuration information for debugging rules.
	DebugRuleConfigurations []*types.DebugRuleConfiguration

	// Status about the debug rule evaluation.
	DebugRuleEvaluationStatuses []*types.DebugRuleEvaluationStatus

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

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

	// 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

	// 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

	// If the training job failed, the reason it failed.
	FailureReason *string

	// 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

	// Algorithm-specific parameters.
	HyperParameters map[string]*string

	// An array of Channel objects that describes each data input channel.
	InputDataConfig []*types.Channel

	// The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job
	// that created the transform or training job.
	LabelingJobArn *string

	// A timestamp that indicates when the status of the training job was last
	// modified.
	LastModifiedTime *time.Time

	// 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

	// The AWS Identity and Access Management (IAM) role configured for the training
	// job.
	RoleArn *string

	// A history of all of the secondary statuses that the training job has
	// transitioned through.
	SecondaryStatusTransitions []*types.SecondaryStatusTransition

	// Configuration of storage locations for TensorBoard output.
	TensorBoardOutputConfig *types.TensorBoardOutputConfig

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

	// Indicates the time when the training job starts on training instances. You are
	// billed for the time interval between this time and the value of TrainingEndTime.
	// The start time in CloudWatch Logs might be later than this time. The difference
	// is due to the time it takes to download the training data and to the size of the
	// training container.
	TrainingStartTime *time.Time

	// The training time in seconds.
	TrainingTimeInSeconds *int32

	// The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if
	// the training job was launched by a hyperparameter tuning job.
	TuningJobArn *string

	// A VpcConfig object that specifies the VPC that this training job has access to.
	// For more information, see Protect Training Jobs by Using an Amazon Virtual
	// Private Cloud (https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html).
	VpcConfig *types.VpcConfig

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

type DescribeTransformJobInput 

type DescribeTransformJobInput struct {

	// The name of the transform job that you want to view details of.
	//
	// This member is required.
	TransformJobName *string
}

type DescribeTransformJobOutput 

type DescribeTransformJobOutput struct {

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

	// The name of the model used in the transform job.
	//
	// This member is required.
	ModelName *string

	// Describes the dataset to be transformed and the Amazon S3 location where it is
	// stored.
	//
	// This member is required.
	TransformInput *types.TransformInput

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

	// The name of the transform job.
	//
	// This member is required.
	TransformJobName *string

	// The status of the transform job. If the transform job failed, the reason is
	// returned in the FailureReason field.
	//
	// This member is required.
	TransformJobStatus types.TransformJobStatus

	// Describes the resources, including ML instance types and ML instance count, to
	// use for the transform job.
	//
	// This member is required.
	TransformResources *types.TransformResources

	// The Amazon Resource Name (ARN) of the AutoML transform job.
	AutoMLJobArn *string

	// Specifies the number of records to include in a mini-batch for an HTTP inference
	// request. A record is a single unit of input data that inference can be made on.
	// For example, a single line in a CSV file is a record. To enable the batch
	// strategy, you must set SplitType to Line, RecordIO, or TFRecord.
	BatchStrategy types.BatchStrategy

	// 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

	// 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

	// 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 Amazon SageMaker Ground Truth labeling job
	// that created the transform or training job.
	LabelingJobArn *string

	// 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

	// The maximum payload size, in MB, used in the transform job.
	MaxPayloadInMB *int32

	// The timeout and maximum number of retries for processing a transform job
	// invocation.
	ModelClientConfig *types.ModelClientConfig

	// Indicates when the transform job has been completed, or has stopped or failed.
	// You are billed for the time interval between this time and the value of
	// TransformStartTime.
	TransformEndTime *time.Time

	// Identifies the Amazon S3 location where you want Amazon SageMaker to save the
	// results from the transform job.
	TransformOutput *types.TransformOutput

	// 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

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

type DescribeTrialComponentInput 

type DescribeTrialComponentInput struct {

	// The name of the trial component to describe.
	//
	// This member is required.
	TrialComponentName *string
}

type DescribeTrialComponentOutput 

type DescribeTrialComponentOutput struct {

	// Who created the component.
	CreatedBy *types.UserContext

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

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

	// When the component ended.
	EndTime *time.Time

	// The input artifacts of the component.
	InputArtifacts map[string]*types.TrialComponentArtifact

	// Who last modified the component.
	LastModifiedBy *types.UserContext

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

	// The metrics for the component.
	Metrics []*types.TrialComponentMetricSummary

	// The output artifacts of the component.
	OutputArtifacts map[string]*types.TrialComponentArtifact

	// The hyperparameters of the component.
	Parameters map[string]*types.TrialComponentParameterValue

	// The Amazon Resource Name (ARN) of the source and, optionally, the job type.
	Source *types.TrialComponentSource

	// When the component started.
	StartTime *time.Time

	// The status of the component. States include:
	//
	// * InProgress
	//
	// * Completed
	//
	// *
	// Failed
	Status *types.TrialComponentStatus

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

	// The name of the trial component.
	TrialComponentName *string

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

type DescribeTrialInput 

type DescribeTrialInput struct {

	// The name of the trial to describe.
	//
	// This member is required.
	TrialName *string
}

type DescribeTrialOutput 

type DescribeTrialOutput struct {

	// Who created the trial.
	CreatedBy *types.UserContext

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

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

	// The name of the experiment the trial is part of.
	ExperimentName *string

	// Who last modified the trial.
	LastModifiedBy *types.UserContext

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

	// The Amazon Resource Name (ARN) of the source and, optionally, the job type.
	Source *types.TrialSource

	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

	// The name of the trial.
	TrialName *string

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

type DescribeUserProfileInput 

type DescribeUserProfileInput struct {

	// The domain ID.
	//
	// This member is required.
	DomainId *string

	// The user profile name.
	//
	// This member is required.
	UserProfileName *string
}

type DescribeUserProfileOutput 

type DescribeUserProfileOutput struct {

	// The creation time.
	CreationTime *time.Time

	// The ID of the domain that contains the profile.
	DomainId *string

	// The failure reason.
	FailureReason *string

	// The ID of the user's profile in the Amazon Elastic File System (EFS) volume.
	HomeEfsFileSystemUid *string

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

	// The SSO user identifier.
	SingleSignOnUserIdentifier *string

	// The SSO user value.
	SingleSignOnUserValue *string

	// The status.
	Status types.UserProfileStatus

	// The user profile Amazon Resource Name (ARN).
	UserProfileArn *string

	// The user profile name.
	UserProfileName *string

	// A collection of settings.
	UserSettings *types.UserSettings

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

type DescribeWorkforceInput 

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

type DescribeWorkforceOutput 

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).
	//
	// This member is required.
	Workforce *types.Workforce

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

type DescribeWorkteamInput 

type DescribeWorkteamInput struct {

	// The name of the work team to return a description of.
	//
	// This member is required.
	WorkteamName *string
}

type DescribeWorkteamOutput 

type DescribeWorkteamOutput struct {

	// A Workteam instance that contains information about the work team.
	//
	// This member is required.
	Workteam *types.Workteam

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

type DisassociateTrialComponentInput 

type DisassociateTrialComponentInput struct {

	// The name of the component to disassociate from the trial.
	//
	// This member is required.
	TrialComponentName *string

	// The name of the trial to disassociate from.
	//
	// This member is required.
	TrialName *string
}

type DisassociateTrialComponentOutput 

type DisassociateTrialComponentOutput struct {

	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

	// The ARN of the trial component.
	TrialComponentArn *string

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

type EndpointResolver 

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

EndpointResolver interface for resolving service endpoints.

func WithEndpointResolver 

func WithEndpointResolver(awsResolver aws.EndpointResolver, fallbackResolver EndpointResolver) EndpointResolver

WithEndpointResolver returns an EndpointResolver that first delegates endpoint resolution to the awsResolver. If awsResolver returns aws.EndpointNotFoundError error, the resolver will use the the provided fallbackResolver for resolution. awsResolver and fallbackResolver must not be nil

type EndpointResolverFunc 

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

EndpointResolverFunc is a helper utility that wraps a function so it satisfies the EndpointResolver interface. This is useful when you want to add additional endpoint resolving logic, or stub out specific endpoints with custom values.

func (EndpointResolverFunc) ResolveEndpoint 

func (fn EndpointResolverFunc) ResolveEndpoint(region string, options EndpointResolverOptions) (endpoint aws.Endpoint, err error)

type EndpointResolverOptions added in v0.29.0 

type EndpointResolverOptions = internalendpoints.Options

EndpointResolverOptions is the service endpoint resolver options

type GetSearchSuggestionsInput 

type GetSearchSuggestionsInput struct {

	// The name of the Amazon SageMaker resource to search for.
	//
	// This member is required.
	Resource types.ResourceType

	// Limits the property names that are included in the response.
	SuggestionQuery *types.SuggestionQuery
}

type GetSearchSuggestionsOutput 

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 

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

type HTTPSignerV4 

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

type IdempotencyTokenProvider added in v0.29.0 

type IdempotencyTokenProvider interface {
	GetIdempotencyToken() (string, error)
}

IdempotencyTokenProvider interface for providing idempotency token

type ListAlgorithmsInput 

type ListAlgorithmsInput struct {

	// A filter that returns only algorithms created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time

	// A filter that returns only algorithms created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time

	// The maximum number of algorithms to return in the response.
	MaxResults *int32

	// A string in the algorithm name. This filter returns only algorithms whose name
	// contains the specified string.
	NameContains *string

	// 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

	// The sort order for the results. The default is Ascending.
	SortOrder types.SortOrder
}

type ListAlgorithmsOutput 

type ListAlgorithmsOutput struct {

	// >An array of AlgorithmSummary objects, each of which lists an algorithm.
	//
	// This member is required.
	AlgorithmSummaryList []*types.AlgorithmSummary

	// 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

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

type ListAppImageConfigsInput added in v0.29.0 

type ListAppImageConfigsInput struct {

	// A filter that returns only AppImageConfigs created on or after the specified
	// time.
	CreationTimeAfter *time.Time

	// A filter that returns only AppImageConfigs created on or before the specified
	// time.
	CreationTimeBefore *time.Time

	// The maximum number of AppImageConfigs to return in the response. The default
	// value is 10.
	MaxResults *int32

	// A filter that returns only AppImageConfigs modified on or after the specified
	// time.
	ModifiedTimeAfter *time.Time

	// A filter that returns only AppImageConfigs modified on or before the specified
	// time.
	ModifiedTimeBefore *time.Time

	// A filter that returns only AppImageConfigs whose name contains the specified
	// string.
	NameContains *string

	// If the previous call to ListImages didn't return the full set of
	// AppImageConfigs, the call returns a token for getting the next set of
	// AppImageConfigs.
	NextToken *string

	// The property used to sort results. The default value is CreationTime.
	SortBy types.AppImageConfigSortKey

	// The sort order. The default value is Descending.
	SortOrder types.SortOrder
}

type ListAppImageConfigsOutput added in v0.29.0 

type ListAppImageConfigsOutput struct {

	// A list of AppImageConfigs and their properties.
	AppImageConfigs []*types.AppImageConfigDetails

	// A token for getting the next set of AppImageConfigs, if there are any.
	NextToken *string

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

type ListAppsInput 

type ListAppsInput struct {

	// A parameter to search for the domain ID.
	DomainIdEquals *string

	// 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

	// The parameter by which to sort the results. The default is CreationTime.
	SortBy types.AppSortKey

	// The sort order for the results. The default is Ascending.
	SortOrder types.SortOrder

	// A parameter to search by user profile name.
	UserProfileNameEquals *string
}

type ListAppsOutput 

type ListAppsOutput struct {

	// The list of apps.
	Apps []*types.AppDetails

	// 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 ListAutoMLJobsInput 

type ListAutoMLJobsInput struct {

	// Request a list of jobs, using a filter for time.
	CreationTimeAfter *time.Time

	// Request a list of jobs, using a filter for time.
	CreationTimeBefore *time.Time

	// Request a list of jobs, using a filter for time.
	LastModifiedTimeAfter *time.Time

	// Request a list of jobs, using a filter for time.
	LastModifiedTimeBefore *time.Time

	// Request a list of jobs up to a specified limit.
	MaxResults *int32

	// Request a list of jobs, using a search filter for name.
	NameContains *string

	// If the previous response was truncated, you 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 AutoMLJobName.
	SortBy types.AutoMLSortBy

	// The sort order for the results. The default is Descending.
	SortOrder types.AutoMLSortOrder

	// Request a list of jobs, using a filter for status.
	StatusEquals types.AutoMLJobStatus
}

type ListAutoMLJobsOutput 

type ListAutoMLJobsOutput struct {

	// Returns a summary list of jobs.
	//
	// This member is required.
	AutoMLJobSummaries []*types.AutoMLJobSummary

	// If the previous response was truncated, you 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 

type ListCandidatesForAutoMLJobInput struct {

	// List the Candidates created for the job by providing the job's name.
	//
	// This member is required.
	AutoMLJobName *string

	// List the Candidates for the job and filter by candidate name.
	CandidateNameEquals *string

	// List the job's Candidates up to a specified limit.
	MaxResults *int32

	// If the previous response was truncated, you 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 Descending.
	SortBy types.CandidateSortBy

	// The sort order for the results. The default is Ascending.
	SortOrder types.AutoMLSortOrder

	// List the Candidates for the job and filter by status.
	StatusEquals types.CandidateStatus
}

type ListCandidatesForAutoMLJobOutput 

type ListCandidatesForAutoMLJobOutput struct {

	// Summaries about the Candidates.
	//
	// This member is required.
	Candidates []*types.AutoMLCandidate

	// If the previous response was truncated, you 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 

type ListCodeRepositoriesInput struct {

	// A filter that returns only Git repositories that were created after the
	// specified time.
	CreationTimeAfter *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 last modified after the
	// specified time.
	LastModifiedTimeAfter *time.Time

	// A filter that returns only Git repositories that were last modified before the
	// specified time.
	LastModifiedTimeBefore *time.Time

	// The maximum number of Git repositories to return in the response.
	MaxResults *int32

	// A string in the Git repositories name. This filter returns only repositories
	// whose name contains the specified string.
	NameContains *string

	// 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 field to sort results by. The default is Name.
	SortBy types.CodeRepositorySortBy

	// The sort order for results. The default is Ascending.
	SortOrder types.CodeRepositorySortOrder
}

type ListCodeRepositoriesOutput 

type ListCodeRepositoriesOutput struct {

	// 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.
	//
	// This member is required.
	CodeRepositorySummaryList []*types.CodeRepositorySummary

	// 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

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

type ListCompilationJobsInput 

type ListCompilationJobsInput struct {

	// 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 created before a
	// specified time.
	CreationTimeBefore *time.Time

	// A filter that returns the model compilation jobs that were modified after a
	// specified time.
	LastModifiedTimeAfter *time.Time

	// A filter that returns the model compilation jobs that were modified before a
	// specified time.
	LastModifiedTimeBefore *time.Time

	// The maximum number of model compilation jobs to return in the response.
	MaxResults *int32

	// A filter that returns the model compilation jobs whose name contains a specified
	// string.
	NameContains *string

	// 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

	// The field by which to sort results. The default is CreationTime.
	SortBy types.ListCompilationJobsSortBy

	// 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
}

type ListCompilationJobsOutput 

type ListCompilationJobsOutput struct {

	// An array of CompilationJobSummary objects, each describing a model compilation
	// job.
	//
	// This member is required.
	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 

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 

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 

type ListEndpointConfigsInput struct {

	// A filter that returns only endpoint configurations with a creation time greater
	// than or equal to the specified time (timestamp).
	CreationTimeAfter *time.Time

	// A filter that returns only endpoint configurations created before the specified
	// time (timestamp).
	CreationTimeBefore *time.Time

	// The maximum number of training jobs to return in the response.
	MaxResults *int32

	// A string in the endpoint configuration name. This filter returns only endpoint
	// configurations whose name contains the specified string.
	NameContains *string

	// 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 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 

type ListEndpointConfigsOutput struct {

	// An array of endpoint configurations.
	//
	// This member is required.
	EndpointConfigs []*types.EndpointConfigSummary

	// 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

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

type ListEndpointsInput 

type ListEndpointsInput struct {

	// 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 created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time

	// A filter that returns only endpoints that were modified after the specified
	// timestamp.
	LastModifiedTimeAfter *time.Time

	// A filter that returns only endpoints that were modified before the specified
	// timestamp.
	LastModifiedTimeBefore *time.Time

	// 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

	// 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

	// Sorts the list of results. The default is CreationTime.
	SortBy types.EndpointSortKey

	// The sort order for results. The default is Descending.
	SortOrder types.OrderKey

	// A filter that returns only endpoints with the specified status.
	StatusEquals types.EndpointStatus
}

type ListEndpointsOutput 

type ListEndpointsOutput struct {

	// An array or endpoint objects.
	//
	// This member is required.
	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 

type ListExperimentsInput struct {

	// A filter that returns only experiments created after the specified time.
	CreatedAfter *time.Time

	// A filter that returns only experiments created before the specified time.
	CreatedBefore *time.Time

	// The maximum number of experiments to return in the response. The default value
	// is 10.
	MaxResults *int32

	// 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 property used to sort results. The default value is CreationTime.
	SortBy types.SortExperimentsBy

	// The sort order. The default value is Descending.
	SortOrder types.SortOrder
}

type ListExperimentsOutput 

type ListExperimentsOutput struct {

	// A list of the summaries of your experiments.
	ExperimentSummaries []*types.ExperimentSummary

	// A token for getting the next set of experiments, if there are any.
	NextToken *string

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

type ListFlowDefinitionsInput 

type ListFlowDefinitionsInput struct {

	// A filter that returns only flow definitions with a creation time greater than or
	// equal to the specified timestamp.
	CreationTimeAfter *time.Time

	// A filter that returns only flow definitions that were created before the
	// specified timestamp.
	CreationTimeBefore *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 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
}

type ListFlowDefinitionsOutput 

type ListFlowDefinitionsOutput struct {

	// An array of objects describing the flow definitions.
	//
	// This member is required.
	FlowDefinitionSummaries []*types.FlowDefinitionSummary

	// A token to resume pagination.
	NextToken *string

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

type ListHumanTaskUisInput 

type ListHumanTaskUisInput struct {

	// A filter that returns only human task user interfaces with a creation time
	// greater than or equal to the specified timestamp.
	CreationTimeAfter *time.Time

	// A filter that returns only human task user interfaces that were created before
	// the specified timestamp.
	CreationTimeBefore *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 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
}

type ListHumanTaskUisOutput 

type ListHumanTaskUisOutput struct {

	// An array of objects describing the human task user interfaces.
	//
	// This member is required.
	HumanTaskUiSummaries []*types.HumanTaskUiSummary

	// A token to resume pagination.
	NextToken *string

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

type ListHyperParameterTuningJobsInput 

type ListHyperParameterTuningJobsInput struct {

	// A filter that returns only tuning jobs that were created after the specified
	// time.
	CreationTimeAfter *time.Time

	// 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 after the specified
	// time.
	LastModifiedTimeAfter *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 string in the tuning job name. This filter returns only tuning jobs whose name
	// contains the specified string.
	NameContains *string

	// 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

	// 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

	// A filter that returns only tuning jobs with the specified status.
	StatusEquals types.HyperParameterTuningJobStatus
}

type ListHyperParameterTuningJobsOutput 

type ListHyperParameterTuningJobsOutput struct {

	// A list of HyperParameterTuningJobSummary objects that describe the tuning jobs
	// that the ListHyperParameterTuningJobs request returned.
	//
	// This member is required.
	HyperParameterTuningJobSummaries []*types.HyperParameterTuningJobSummary

	// 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

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

type ListImageVersionsInput added in v0.29.0 

type ListImageVersionsInput struct {

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

	// A filter that returns only versions created on or after the specified time.
	CreationTimeAfter *time.Time

	// A filter that returns only versions created on or before the specified time.
	CreationTimeBefore *time.Time

	// A filter that returns only versions modified on or after the specified time.
	LastModifiedTimeAfter *time.Time

	// A filter that returns only versions modified on or before the specified time.
	LastModifiedTimeBefore *time.Time

	// The maximum number of versions to return in the response. The default value is
	// 10.
	MaxResults *int32

	// If the previous call to ListImageVersions didn't return the full set of
	// versions, the call returns a token for getting the next set of versions.
	NextToken *string

	// The property used to sort results. The default value is CREATION_TIME.
	SortBy types.ImageVersionSortBy

	// The sort order. The default value is DESCENDING.
	SortOrder types.ImageVersionSortOrder
}

type ListImageVersionsOutput added in v0.29.0 

type ListImageVersionsOutput struct {

	// A list of versions and their properties.
	ImageVersions []*types.ImageVersion

	// A token for getting the next set of versions, if there are any.
	NextToken *string

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

type ListImagesInput added in v0.29.0 

type ListImagesInput struct {

	// A filter that returns only images created on or after the specified time.
	CreationTimeAfter *time.Time

	// A filter that returns only images created on or before the specified time.
	CreationTimeBefore *time.Time

	// A filter that returns only images modified on or after the specified time.
	LastModifiedTimeAfter *time.Time

	// A filter that returns only images modified on or before the specified time.
	LastModifiedTimeBefore *time.Time

	// The maximum number of images to return in the response. The default value is 10.
	MaxResults *int32

	// A filter that returns only images whose name contains the specified string.
	NameContains *string

	// If the previous call to ListImages didn't return the full set of images, the
	// call returns a token for getting the next set of images.
	NextToken *string

	// The property used to sort results. The default value is CREATION_TIME.
	SortBy types.ImageSortBy

	// The sort order. The default value is DESCENDING.
	SortOrder types.ImageSortOrder
}

type ListImagesOutput added in v0.29.0 

type ListImagesOutput struct {

	// A list of images and their properties.
	Images []*types.Image

	// A token for getting the next set of images, if there are any.
	NextToken *string

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

type ListLabelingJobsForWorkteamInput 

type ListLabelingJobsForWorkteamInput struct {

	// The Amazon Resource Name (ARN) of the work team for which you want to see
	// labeling jobs for.
	//
	// This member is required.
	WorkteamArn *string

	// A filter that returns only labeling jobs created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time

	// A filter that returns only labeling jobs created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time

	// A filter the limits jobs to only the ones whose job reference code contains the
	// specified string.
	JobReferenceCodeContains *string

	// The maximum number of labeling jobs to return in each page of the response.
	MaxResults *int32

	// 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 field to sort results by. The default is CreationTime.
	SortBy types.ListLabelingJobsForWorkteamSortByOptions

	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
}

type ListLabelingJobsForWorkteamOutput 

type ListLabelingJobsForWorkteamOutput struct {

	// An array of LabelingJobSummary objects, each describing a labeling job.
	//
	// This member is required.
	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 

type ListLabelingJobsInput struct {

	// A filter that returns only labeling jobs created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time

	// A filter that returns only labeling jobs created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time

	// A filter that returns only labeling jobs modified after the specified time
	// (timestamp).
	LastModifiedTimeAfter *time.Time

	// A filter that returns only labeling jobs modified before the specified time
	// (timestamp).
	LastModifiedTimeBefore *time.Time

	// The maximum number of labeling jobs to return in each page of the response.
	MaxResults *int32

	// 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

	// 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
}

type ListLabelingJobsOutput 

type ListLabelingJobsOutput struct {

	// An array of LabelingJobSummary objects, each describing a labeling job.
	LabelingJobSummaryList []*types.LabelingJobSummary

	// 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 ListModelPackagesInput 

type ListModelPackagesInput struct {

	// 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

	// The maximum number of model packages to return in the response.
	MaxResults *int32

	// A string in the model package name. This filter returns only model packages
	// whose name contains the specified string.
	NameContains *string

	// 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

	// The parameter by which to sort the results. The default is CreationTime.
	SortBy types.ModelPackageSortBy

	// The sort order for the results. The default is Ascending.
	SortOrder types.SortOrder
}

type ListModelPackagesOutput 

type ListModelPackagesOutput struct {

	// An array of ModelPackageSummary objects, each of which lists a model package.
	//
	// This member is required.
	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 

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

	// 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

	// A string in the training job name. This filter returns only models in the
	// training job whose name contains the specified string.
	NameContains *string

	// 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

	// 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 

type ListModelsOutput struct {

	// An array of ModelSummary objects, each of which lists a model.
	//
	// This member is required.
	Models []*types.ModelSummary

	// 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

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

type ListMonitoringExecutionsInput 

type ListMonitoringExecutionsInput struct {

	// A filter that returns only jobs created after a specified time.
	CreationTimeAfter *time.Time

	// A filter that returns only jobs created before a specified time.
	CreationTimeBefore *time.Time

	// Name of a specific endpoint to fetch jobs for.
	EndpointName *string

	// A filter that returns only jobs modified before a specified time.
	LastModifiedTimeAfter *time.Time

	// A filter that returns only jobs modified after a specified time.
	LastModifiedTimeBefore *time.Time

	// The maximum number of jobs to return in the response. The default value is 10.
	MaxResults *int32

	// Name of a specific schedule to fetch jobs for.
	MonitoringScheduleName *string

	// The token returned if the response is truncated. To retrieve the next set of job
	// executions, use it in the next request.
	NextToken *string

	// Filter for jobs scheduled after a specified time.
	ScheduledTimeAfter *time.Time

	// 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

	// Whether to sort the results in Ascending or Descending order. The default is
	// Descending.
	SortOrder types.SortOrder

	// A filter that retrieves only jobs with a specific status.
	StatusEquals types.ExecutionStatus
}

type ListMonitoringExecutionsOutput 

type ListMonitoringExecutionsOutput struct {

	// A JSON array in which each element is a summary for a monitoring execution.
	//
	// This member is required.
	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 

type ListMonitoringSchedulesInput struct {

	// A filter that returns only monitoring schedules created after a specified time.
	CreationTimeAfter *time.Time

	// A filter that returns only monitoring schedules created before a specified time.
	CreationTimeBefore *time.Time

	// Name of a specific endpoint to fetch schedules for.
	EndpointName *string

	// A filter that returns only monitoring schedules modified after a specified time.
	LastModifiedTimeAfter *time.Time

	// A filter that returns only monitoring schedules modified before a specified
	// time.
	LastModifiedTimeBefore *time.Time

	// The maximum number of jobs to return in the response. The default value is 10.
	MaxResults *int32

	// Filter for monitoring schedules whose name contains a specified string.
	NameContains *string

	// The token returned if the response is truncated. To retrieve the next set of job
	// executions, use it in the next request.
	NextToken *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

	// A filter that returns only monitoring schedules modified before a specified
	// time.
	StatusEquals types.ScheduleStatus
}

type ListMonitoringSchedulesOutput 

type ListMonitoringSchedulesOutput struct {

	// A JSON array in which each element is a summary for a monitoring schedule.
	//
	// This member is required.
	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 

type ListNotebookInstanceLifecycleConfigsInput struct {

	// A filter that returns only lifecycle configurations that were created after the
	// specified time (timestamp).
	CreationTimeAfter *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 after the
	// specified time (timestamp).
	LastModifiedTimeAfter *time.Time

	// A filter that returns only lifecycle configurations that were modified before
	// the specified time (timestamp).
	LastModifiedTimeBefore *time.Time

	// The maximum number of lifecycle configurations to return in the response.
	MaxResults *int32

	// A string in the lifecycle configuration name. This filter returns only lifecycle
	// configurations whose name contains the specified string.
	NameContains *string

	// 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

	// Sorts the list of results. The default is CreationTime.
	SortBy types.NotebookInstanceLifecycleConfigSortKey

	// The sort order for results.
	SortOrder types.NotebookInstanceLifecycleConfigSortOrder
}

type ListNotebookInstanceLifecycleConfigsOutput 

type ListNotebookInstanceLifecycleConfigsOutput struct {

	// 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

	// An array of NotebookInstanceLifecycleConfiguration objects, each listing a
	// lifecycle configuration.
	NotebookInstanceLifecycleConfigs []*types.NotebookInstanceLifecycleConfigSummary

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

type ListNotebookInstancesInput 

type ListNotebookInstancesInput struct {

	// A filter that returns only notebook instances with associated with the specified
	// git repository.
	AdditionalCodeRepositoryEquals *string

	// A filter that returns only notebook instances that were created after the
	// specified time (timestamp).
	CreationTimeAfter *time.Time

	// 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 that were modified after the
	// specified time (timestamp).
	LastModifiedTimeAfter *time.Time

	// A filter that returns only notebook instances that were modified before the
	// specified time (timestamp).
	LastModifiedTimeBefore *time.Time

	// The maximum number of notebook instances to return.
	MaxResults *int32

	// A string in the notebook instances' name. This filter returns only notebook
	// instances whose name contains the specified string.
	NameContains *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

	// 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

	// 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 with the specified status.
	StatusEquals types.NotebookInstanceStatus
}

type ListNotebookInstancesOutput 

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 

type ListProcessingJobsInput struct {

	// A filter that returns only processing jobs created after the specified time.
	CreationTimeAfter *time.Time

	// A filter that returns only processing jobs created after the specified time.
	CreationTimeBefore *time.Time

	// A filter that returns only processing jobs modified after the specified time.
	LastModifiedTimeAfter *time.Time

	// A filter that returns only processing jobs modified before the specified time.
	LastModifiedTimeBefore *time.Time

	// The maximum number of processing jobs to return in the response.
	MaxResults *int32

	// A string in the processing job name. This filter returns only processing jobs
	// whose name contains the specified string.
	NameContains *string

	// 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 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 processing jobs with a specific status.
	StatusEquals types.ProcessingJobStatus
}

type ListProcessingJobsOutput 

type ListProcessingJobsOutput struct {

	// An array of ProcessingJobSummary objects, each listing a processing job.
	//
	// This member is required.
	ProcessingJobSummaries []*types.ProcessingJobSummary

	// 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

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

type ListSubscribedWorkteamsInput 

type ListSubscribedWorkteamsInput struct {

	// The maximum number of work teams to return in each page of the response.
	MaxResults *int32

	// A string in the work team name. This filter returns only work teams whose name
	// contains the specified string.
	NameContains *string

	// 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
}

type ListSubscribedWorkteamsOutput 

type ListSubscribedWorkteamsOutput struct {

	// An array of Workteam objects, each describing a work team.
	//
	// This member is required.
	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 

type ListTagsInput struct {

	// The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
	//
	// This member is required.
	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 

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 

type ListTrainingJobsForHyperParameterTuningJobInput struct {

	// The name of the tuning job whose training jobs you want to list.
	//
	// This member is required.
	HyperParameterTuningJobName *string

	// 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 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 sort order for results. The default is Ascending.
	SortOrder types.SortOrder

	// A filter that returns only training jobs with the specified status.
	StatusEquals types.TrainingJobStatus
}

type ListTrainingJobsForHyperParameterTuningJobOutput 

type ListTrainingJobsForHyperParameterTuningJobOutput struct {

	// A list of TrainingJobSummary objects that describe the training jobs that the
	// ListTrainingJobsForHyperParameterTuningJob request returned.
	//
	// This member is required.
	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 

type ListTrainingJobsInput struct {

	// A filter that returns only training jobs created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time

	// A filter that returns only training jobs created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time

	// A filter that returns only training jobs modified after the specified time
	// (timestamp).
	LastModifiedTimeAfter *time.Time

	// 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 string in the training job name. This filter returns only training jobs whose
	// name contains the specified string.
	NameContains *string

	// 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 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 training jobs with a specific status.
	StatusEquals types.TrainingJobStatus
}

type ListTrainingJobsOutput 

type ListTrainingJobsOutput struct {

	// An array of TrainingJobSummary objects, each listing a training job.
	//
	// This member is required.
	TrainingJobSummaries []*types.TrainingJobSummary

	// 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 ListTransformJobsInput 

type ListTransformJobsInput struct {

	// A filter that returns only transform jobs created after the specified time.
	CreationTimeAfter *time.Time

	// A filter that returns only transform jobs created before the specified time.
	CreationTimeBefore *time.Time

	// A filter that returns only transform jobs modified after the specified time.
	LastModifiedTimeAfter *time.Time

	// A filter that returns only transform jobs modified before the specified time.
	LastModifiedTimeBefore *time.Time

	// The maximum number of transform jobs to return in the response. The default
	// value is 10.
	MaxResults *int32

	// A string in the transform job name. This filter returns only transform jobs
	// whose name contains the specified string.
	NameContains *string

	// 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 field to sort results by. The default is CreationTime.
	SortBy types.SortBy

	// The sort order for results. The default is Descending.
	SortOrder types.SortOrder

	// A filter that retrieves only transform jobs with a specific status.
	StatusEquals types.TransformJobStatus
}

type ListTransformJobsOutput 

type ListTransformJobsOutput struct {

	// An array of TransformJobSummary objects.
	//
	// This member is required.
	TransformJobSummaries []*types.TransformJobSummary

	// 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

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

type ListTrialComponentsInput 

type ListTrialComponentsInput struct {

	// A filter that returns only components created after the specified time.
	CreatedAfter *time.Time

	// A filter that returns only components created before the specified time.
	CreatedBefore *time.Time

	// 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

	// The maximum number of components to return in the response. The default value is
	// 10.
	MaxResults *int32

	// 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

	// 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

	// 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

	// 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
}

type ListTrialComponentsOutput 

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 

type ListTrialsInput struct {

	// A filter that returns only trials created after the specified time.
	CreatedAfter *time.Time

	// A filter that returns only trials created before the specified time.
	CreatedBefore *time.Time

	// A filter that returns only trials that are part of the specified experiment.
	ExperimentName *string

	// The maximum number of trials to return in the response. The default value is 10.
	MaxResults *int32

	// 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 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 that are associated with the specified trial
	// component.
	TrialComponentName *string
}

type ListTrialsOutput 

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 

type ListUserProfilesInput struct {

	// A parameter by which to filter the results.
	DomainIdEquals *string

	// 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

	// The parameter by which to sort the results. The default is CreationTime.
	SortBy types.UserProfileSortKey

	// The sort order for the results. The default is Ascending.
	SortOrder types.SortOrder

	// A parameter by which to filter the results.
	UserProfileNameContains *string
}

type ListUserProfilesOutput 

type ListUserProfilesOutput 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 user profiles.
	UserProfiles []*types.UserProfileDetails

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

type ListWorkforcesInput 

type ListWorkforcesInput struct {

	// 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

	// 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
}

type ListWorkforcesOutput 

type ListWorkforcesOutput struct {

	// A list containing information about your workforce.
	//
	// This member is required.
	Workforces []*types.Workforce

	// A token to resume pagination.
	NextToken *string

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

type ListWorkteamsInput 

type ListWorkteamsInput struct {

	// The maximum number of work teams to return in each page of the response.
	MaxResults *int32

	// A string in the work team's name. This filter returns only work teams whose name
	// contains the specified string.
	NameContains *string

	// 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 field to sort results by. The default is CreationTime.
	SortBy types.ListWorkteamsSortByOptions

	// The sort order for results. The default is Ascending.
	SortOrder types.SortOrder
}

type ListWorkteamsOutput 

type ListWorkteamsOutput struct {

	// An array of Workteam objects, each describing a work team.
	//
	// This member is required.
	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 

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 EndpointResolverOptions

	// The service endpoint resolver.
	EndpointResolver EndpointResolver

	// Signature Version 4 (SigV4) Signer
	HTTPSignerV4 HTTPSignerV4

	// Provides idempotency tokens values that will be automatically populated into
	// idempotent API operations.
	IdempotencyTokenProvider IdempotencyTokenProvider

	// 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
}

func (Options) Copy 

func (o Options) Copy() Options

Copy creates a clone where the APIOptions list is deep copied.

type RenderUiTemplateInput 

type RenderUiTemplateInput struct {

	// The Amazon Resource Name (ARN) that has access to the S3 objects that are used
	// by the template.
	//
	// This member is required.
	RoleArn *string

	// A RenderableTask object containing a representative task to render.
	//
	// This member is required.
	Task *types.RenderableTask

	// 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 Template object containing the worker UI template to render.
	UiTemplate *types.UiTemplate
}

type RenderUiTemplateOutput 

type RenderUiTemplateOutput struct {

	// 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.
	//
	// This member is required.
	Errors []*types.RenderingError

	// A Liquid template that renders the HTML for the worker UI.
	//
	// This member is required.
	RenderedContent *string

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

type ResolveEndpoint 

type ResolveEndpoint struct {
	Resolver EndpointResolver
	Options  EndpointResolverOptions
}

func (*ResolveEndpoint) HandleSerialize 

func (m *ResolveEndpoint) HandleSerialize(ctx context.Context, in middleware.SerializeInput, next middleware.SerializeHandler) (
	out middleware.SerializeOutput, metadata middleware.Metadata, err error,
)

func (*ResolveEndpoint) ID 

func (*ResolveEndpoint) ID() string

type SearchInput 

type SearchInput struct {

	// The name of the Amazon SageMaker resource to search for.
	//
	// This member is required.
	Resource types.ResourceType

	// The maximum number of results to return.
	MaxResults *int32

	// 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

	// 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

	// How SearchResults are ordered. Valid values are Ascending or Descending. The
	// default is Descending.
	SortOrder types.SearchSortOrder
}

type SearchOutput 

type SearchOutput struct {

	// 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

	// A list of SearchRecord objects.
	Results []*types.SearchRecord

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

type StartMonitoringScheduleInput 

type StartMonitoringScheduleInput struct {

	// The name of the schedule to start.
	//
	// This member is required.
	MonitoringScheduleName *string
}

type StartMonitoringScheduleOutput 

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

type StartNotebookInstanceInput 

type StartNotebookInstanceInput struct {

	// The name of the notebook instance to start.
	//
	// This member is required.
	NotebookInstanceName *string
}

type StartNotebookInstanceOutput 

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

type StopAutoMLJobInput 

type StopAutoMLJobInput struct {

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

type StopAutoMLJobOutput 

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

type StopCompilationJobInput 

type StopCompilationJobInput struct {

	// The name of the model compilation job to stop.
	//
	// This member is required.
	CompilationJobName *string
}

type StopCompilationJobOutput 

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

type StopHyperParameterTuningJobInput 

type StopHyperParameterTuningJobInput struct {

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

type StopHyperParameterTuningJobOutput 

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

type StopLabelingJobInput 

type StopLabelingJobInput struct {

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

type StopLabelingJobOutput 

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

type StopMonitoringScheduleInput 

type StopMonitoringScheduleInput struct {

	// The name of the schedule to stop.
	//
	// This member is required.
	MonitoringScheduleName *string
}

type StopMonitoringScheduleOutput 

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

type StopNotebookInstanceInput 

type StopNotebookInstanceInput struct {

	// The name of the notebook instance to terminate.
	//
	// This member is required.
	NotebookInstanceName *string
}

type StopNotebookInstanceOutput 

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

type StopProcessingJobInput 

type StopProcessingJobInput struct {

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

type StopProcessingJobOutput 

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

type StopTrainingJobInput 

type StopTrainingJobInput struct {

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

type StopTrainingJobOutput 

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

type StopTransformJobInput 

type StopTransformJobInput struct {

	// The name of the transform job to stop.
	//
	// This member is required.
	TransformJobName *string
}

type StopTransformJobOutput 

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

type UpdateAppImageConfigInput added in v0.29.0 

type UpdateAppImageConfigInput struct {

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

	// The new KernelGateway app to run on the image.
	KernelGatewayImageConfig *types.KernelGatewayImageConfig
}

type UpdateAppImageConfigOutput added in v0.29.0 

type UpdateAppImageConfigOutput struct {

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

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

type UpdateCodeRepositoryInput 

type UpdateCodeRepositoryInput struct {

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

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

type UpdateCodeRepositoryOutput 

type UpdateCodeRepositoryOutput struct {

	// The ARN of the Git repository.
	//
	// This member is required.
	CodeRepositoryArn *string

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

type UpdateDomainInput 

type UpdateDomainInput struct {

	// The ID of the domain to be updated.
	//
	// This member is required.
	DomainId *string

	// A collection of settings.
	DefaultUserSettings *types.UserSettings
}

type UpdateDomainOutput 

type UpdateDomainOutput struct {

	// The Amazon Resource Name (ARN) of the domain.
	DomainArn *string

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

type UpdateEndpointInput 

type UpdateEndpointInput struct {

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

	// The name of the endpoint whose configuration you want to update.
	//
	// This member is required.
	EndpointName *string

	// When you are updating endpoint resources with
	// UpdateEndpointInput$RetainAllVariantProperties, whose value is set to true,
	// ExcludeRetainedVariantProperties specifies the list of type VariantProperty to
	// override with the values provided by EndpointConfig. If you don't specify a
	// value for ExcludeAllVariantProperties, no variant properties are overridden.
	ExcludeRetainedVariantProperties []*types.VariantProperty

	// When updating endpoint resources, enables or disables the retention of variant
	// properties, such as the instance count or the variant weight. To retain the
	// variant properties of an endpoint when updating it, set
	// RetainAllVariantProperties to true. To use the variant properties specified in a
	// new EndpointConfig call when updating an endpoint, set
	// RetainAllVariantProperties to false.
	RetainAllVariantProperties *bool
}

type UpdateEndpointOutput 

type UpdateEndpointOutput struct {

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

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

type UpdateEndpointWeightsAndCapacitiesInput 

type UpdateEndpointWeightsAndCapacitiesInput struct {

	// An object that provides new capacity and weight values for a variant.
	//
	// This member is required.
	DesiredWeightsAndCapacities []*types.DesiredWeightAndCapacity

	// The name of an existing Amazon SageMaker endpoint.
	//
	// This member is required.
	EndpointName *string
}

type UpdateEndpointWeightsAndCapacitiesOutput 

type UpdateEndpointWeightsAndCapacitiesOutput struct {

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

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

type UpdateExperimentInput 

type UpdateExperimentInput struct {

	// The name of the experiment to update.
	//
	// This member is required.
	ExperimentName *string

	// The description of the experiment.
	Description *string

	// The name of the experiment as displayed. The name doesn't need to be unique. If
	// DisplayName isn't specified, ExperimentName is displayed.
	DisplayName *string
}

type UpdateExperimentOutput 

type UpdateExperimentOutput struct {

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

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

type UpdateImageInput added in v0.29.0 

type UpdateImageInput struct {

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

	// A list of properties to delete. Only the Description and DisplayName properties
	// can be deleted.
	DeleteProperties []*string

	// The new description for the image.
	Description *string

	// The new display name for the image.
	DisplayName *string

	// The new Amazon Resource Name (ARN) for the IAM role that enables Amazon
	// SageMaker to perform tasks on your behalf.
	RoleArn *string
}

type UpdateImageOutput added in v0.29.0 

type UpdateImageOutput struct {

	// The Amazon Resource Name (ARN) of the image.
	ImageArn *string

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

type UpdateMonitoringScheduleInput 

type UpdateMonitoringScheduleInput struct {

	// The configuration object that specifies the monitoring schedule and defines the
	// monitoring job.
	//
	// This member is required.
	MonitoringScheduleConfig *types.MonitoringScheduleConfig

	// The name of the monitoring schedule. The name must be unique within an AWS
	// Region within an AWS account.
	//
	// This member is required.
	MonitoringScheduleName *string
}

type UpdateMonitoringScheduleOutput 

type UpdateMonitoringScheduleOutput struct {

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

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

type UpdateNotebookInstanceInput 

type UpdateNotebookInstanceInput struct {

	// The name of the notebook instance to update.
	//
	// This member is required.
	NotebookInstanceName *string

	// A list of the Elastic Inference (EI) instance types to associate 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

	// 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

	// The 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

	// A list of the Elastic Inference (EI) instance types to remove from this notebook
	// instance. This operation is idempotent. If you specify an accelerator type that
	// is not associated with the notebook instance when you call this method, it does
	// not throw an error.
	DisassociateAcceleratorTypes *bool

	// A list of names or URLs of the default Git repositories to remove from this
	// notebook instance. This operation is idempotent. If you specify a Git repository
	// that is not associated with the notebook instance when you call this method, it
	// does not throw an error.
	DisassociateAdditionalCodeRepositories *bool

	// The name or URL of the default Git repository to remove from this notebook
	// instance. This operation is idempotent. If you specify a Git repository that is
	// not associated with the notebook instance when you call this method, it does not
	// throw an error.
	DisassociateDefaultCodeRepository *bool

	// Set to true to remove the notebook instance lifecycle configuration currently
	// associated with the notebook instance. This operation is idempotent. If you
	// specify a lifecycle configuration that is not associated with the notebook
	// instance when you call this method, it does not throw an error.
	DisassociateLifecycleConfig *bool

	// The Amazon ML compute instance type.
	InstanceType types.InstanceType

	// 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

	// The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker can assume
	// to access the notebook instance. 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

	// Whether root access is enabled or disabled for users of the notebook instance.
	// The default value is Enabled. If you set this to Disabled, users don't have root
	// access on the notebook instance, but lifecycle configuration scripts still run
	// with root permissions.
	RootAccess types.RootAccess

	// The size, in GB, of the ML storage volume to attach to the notebook instance.
	// The default value is 5 GB. ML storage volumes are encrypted, so Amazon SageMaker
	// can't determine the amount of available free space on the volume. Because of
	// this, you can increase the volume size when you update a notebook instance, but
	// you can't decrease the volume size. If you want to decrease the size of the ML
	// storage volume in use, create a new notebook instance with the desired size.
	VolumeSizeInGB *int32
}

type UpdateNotebookInstanceLifecycleConfigInput 

type UpdateNotebookInstanceLifecycleConfigInput struct {

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

	// The shell script that runs only once, when you create a notebook instance. The
	// shell script must be a base64-encoded string.
	OnCreate []*types.NotebookInstanceLifecycleHook

	// The 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
}

type UpdateNotebookInstanceLifecycleConfigOutput 

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

type UpdateNotebookInstanceOutput 

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

type UpdateTrialComponentInput 

type UpdateTrialComponentInput struct {

	// The name of the component to update.
	//
	// This member is required.
	TrialComponentName *string

	// 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 ended.
	EndTime *time.Time

	// Replaces all of the component's input artifacts with the specified artifacts.
	InputArtifacts map[string]*types.TrialComponentArtifact

	// The input artifacts to remove from the component.
	InputArtifactsToRemove []*string

	// Replaces all of the component's output artifacts with the specified artifacts.
	OutputArtifacts map[string]*types.TrialComponentArtifact

	// The output artifacts to remove from the component.
	OutputArtifactsToRemove []*string

	// Replaces all of the component's hyperparameters with the specified
	// hyperparameters.
	Parameters map[string]*types.TrialComponentParameterValue

	// The hyperparameters to remove from the component.
	ParametersToRemove []*string

	// When the component started.
	StartTime *time.Time

	// The new status of the component.
	Status *types.TrialComponentStatus
}

type UpdateTrialComponentOutput 

type UpdateTrialComponentOutput struct {

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

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

type UpdateTrialInput 

type UpdateTrialInput struct {

	// The name of the trial to update.
	//
	// This member is required.
	TrialName *string

	// 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
}

type UpdateTrialOutput 

type UpdateTrialOutput struct {

	// The Amazon Resource Name (ARN) of the trial.
	TrialArn *string

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

type UpdateUserProfileInput 

type UpdateUserProfileInput struct {

	// The domain ID.
	//
	// This member is required.
	DomainId *string

	// The user profile name.
	//
	// This member is required.
	UserProfileName *string

	// A collection of settings.
	UserSettings *types.UserSettings
}

type UpdateUserProfileOutput 

type UpdateUserProfileOutput struct {

	// The user profile Amazon Resource Name (ARN).
	UserProfileArn *string

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

type UpdateWorkforceInput 

type UpdateWorkforceInput struct {

	// The name of the private workforce that you want to update. You can find your
	// workforce name by using the operation.
	//
	// This member is required.
	WorkforceName *string

	// Use this parameter to update your OIDC Identity Provider (IdP) configuration for
	// a workforce made using your own IdP.
	OidcConfig *types.OidcConfig

	// A list of one to ten worker IP address ranges (CIDRs
	// (https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html)) that can be
	// used to access tasks assigned to this workforce. Maximum: Ten CIDR values
	SourceIpConfig *types.SourceIpConfig
}

type UpdateWorkforceOutput 

type UpdateWorkforceOutput struct {

	// A single private workforce. 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).
	//
	// This member is required.
	Workforce *types.Workforce

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

type UpdateWorkteamInput 

type UpdateWorkteamInput struct {

	// The name of the work team to update.
	//
	// This member is required.
	WorkteamName *string

	// An updated description for the work team.
	Description *string

	// A list of MemberDefinition objects that contains objects that identify the
	// workers that make up the work team. Workforces can be created using Amazon
	// Cognito or your own OIDC Identity Provider (IdP). For private workforces created
	// using Amazon Cognito use CognitoMemberDefinition. For workforces created using
	// your own OIDC identity provider (IdP) use OidcMemberDefinition. You should not
	// provide input for both of these parameters in a single request. For workforces
	// created using Amazon Cognito, private work teams correspond to Amazon Cognito
	// user groups within the user pool used to create a workforce. All of the
	// CognitoMemberDefinition objects that make up the member definition must have the
	// same ClientId and UserPool values. To add a Amazon Cognito user group to an
	// existing worker pool, see Adding groups to a User Pool. For more information
	// about user pools, see Amazon Cognito User Pools
	// (https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html).
	// For workforces created using your own OIDC IdP, specify the user groups that you
	// want to include in your private work team in OidcMemberDefinition by listing
	// those groups in Groups. Be aware that user groups that are already in the work
	// team must also be listed in Groups when you make this request to remain on the
	// work team. If you do not include these user groups, they will no longer be
	// associated with the work team you update.
	MemberDefinitions []*types.MemberDefinition

	// Configures SNS topic notifications for available or expiring work items
	NotificationConfiguration *types.NotificationConfiguration
}

type UpdateWorkteamOutput 

type UpdateWorkteamOutput struct {

	// A Workteam object that describes the updated work team.
	//
	// This member is required.
	Workteam *types.Workteam

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

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