sagemaker-2017-07-24 library

Classes

ActionSource
A structure describing the source of an action.
ActionSummary
Lists the properties of an action. An action represents an action or activity. Some examples are a workflow step and a model deployment. Generally, an action involves at least one input artifact or output artifact.
AddAssociationResponse
AddTagsOutput
AgentVersion
Edge Manager agent version.
Alarm
This API is not supported.
AlgorithmSpecification
Specifies the training algorithm to use in a CreateTrainingJob request.
AlgorithmStatusDetails
Specifies the validation and image scan statuses of the algorithm.
AlgorithmStatusItem
Represents the overall status of an algorithm.
AlgorithmSummary
Provides summary information about an algorithm.
AlgorithmValidationProfile
Defines a training job and a batch transform job that Amazon SageMaker runs to validate your algorithm.
AlgorithmValidationSpecification
Specifies configurations for one or more training jobs that Amazon SageMaker runs to test the algorithm.
AnnotationConsolidationConfig
Configures how labels are consolidated across human workers and processes output data.
AppDetails
Details about an Amazon SageMaker app.
AppImageConfigDetails
The configuration for running a SageMaker image as a KernelGateway app.
AppSpecification
Configuration to run a processing job in a specified container image.
ArtifactSource
A structure describing the source of an artifact.
ArtifactSourceType
The ID and ID type of an artifact source.
ArtifactSummary
Lists a summary of the properties of an artifact. An artifact represents a URI addressable object or data. Some examples are a dataset and a model.
AssociateTrialComponentResponse
AssociationSummary
Lists a summary of the properties of an association. An association is an entity that links other lineage or experiment entities. An example would be an association between a training job and a model.
AthenaDatasetDefinition
Configuration for Athena Dataset Definition input.
AutoMLCandidate
An Autopilot job returns recommendations, or candidates. Each candidate has futher details about the steps involed, and the status.
AutoMLCandidateStep
Information about the steps for a Candidate, and what step it is working on.
AutoMLChannel
Similar to Channel. A channel is a named input source that training algorithms can consume. Refer to Channel for detailed descriptions.
AutoMLContainerDefinition
A list of container definitions that describe the different containers that make up one AutoML candidate. Refer to ContainerDefinition for more details.
AutoMLDataSource
The data source for the Autopilot job.
AutoMLJobArtifacts
Artifacts that are generation during a job.
AutoMLJobCompletionCriteria
How long a job is allowed to run, or how many candidates a job is allowed to generate.
AutoMLJobConfig
A collection of settings used for a job.
AutoMLJobObjective
Specifies a metric to minimize or maximize as the objective of a job.
AutoMLJobSummary
Provides a summary about a job.
AutoMLOutputDataConfig
The output data configuration.
AutoMLS3DataSource
The Amazon S3 data source.
AutoMLSecurityConfig
Security options.
AutoRollbackConfig
Currently, the AutoRollbackConfig API is not supported.
AwsClientCredentials
AWS credentials.
Bias
Contains bias metrics for a model.
BlueGreenUpdatePolicy
Currently, the BlueGreenUpdatePolicy API is not supported.
CacheHitResult
Details on the cache hit of a pipeline execution step.
CapacitySize
Currently, the CapacitySize API is not supported.
CaptureContentTypeHeader
CaptureOption
CategoricalParameterRange
A list of categorical hyperparameters to tune.
CategoricalParameterRangeSpecification
Defines the possible values for a categorical hyperparameter.
Channel
A channel is a named input source that training algorithms can consume.
ChannelSpecification
Defines a named input source, called a channel, to be used by an algorithm.
CheckpointConfig
Contains information about the output location for managed spot training checkpoint data.
CodeRepositorySummary
Specifies summary information about a Git repository.
CognitoConfig
Use this parameter to configure your Amazon Cognito workforce. A single Cognito workforce is created using and corresponds to a single Amazon Cognito user pool.
CognitoMemberDefinition
Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
CollectionConfiguration
Configuration information for the Debugger output tensor collections.
CompilationJobSummary
A summary of a model compilation job.
ConditionStepMetadata
Metadata for a Condition step.
ContainerDefinition
Describes the container, as part of model definition.
ContextSource
A structure describing the source of a context.
ContextSummary
Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
ContinuousParameterRange
A list of continuous hyperparameters to tune.
ContinuousParameterRangeSpecification
Defines the possible values for a continuous hyperparameter.
CreateActionResponse
CreateAlgorithmOutput
CreateAppImageConfigResponse
CreateAppResponse
CreateArtifactResponse
CreateAutoMLJobResponse
CreateCodeRepositoryOutput
CreateCompilationJobResponse
CreateContextResponse
CreateDataQualityJobDefinitionResponse
CreateDomainResponse
CreateEndpointConfigOutput
CreateEndpointOutput
CreateExperimentResponse
CreateFeatureGroupResponse
CreateFlowDefinitionResponse
CreateHumanTaskUiResponse
CreateHyperParameterTuningJobResponse
CreateImageResponse
CreateImageVersionResponse
CreateLabelingJobResponse
CreateModelBiasJobDefinitionResponse
CreateModelExplainabilityJobDefinitionResponse
CreateModelOutput
CreateModelPackageGroupOutput
CreateModelPackageOutput
CreateModelQualityJobDefinitionResponse
CreateMonitoringScheduleResponse
CreateNotebookInstanceLifecycleConfigOutput
CreateNotebookInstanceOutput
CreatePipelineResponse
CreatePresignedDomainUrlResponse
CreatePresignedNotebookInstanceUrlOutput
CreateProcessingJobResponse
CreateProjectOutput
CreateTrainingJobResponse
CreateTransformJobResponse
CreateTrialComponentResponse
CreateTrialResponse
CreateUserProfileResponse
CreateWorkforceResponse
CreateWorkteamResponse
CustomImage
A custom SageMaker image. For more information, see Bring your own SageMaker image.
DataCaptureConfig
DataCaptureConfigSummary
DataCatalogConfig
The meta data of the Glue table which serves as data catalog for the OfflineStore.
DataProcessing
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.
DataQualityAppSpecification
Information about the container that a data quality monitoring job runs.
DataQualityBaselineConfig
Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
DataQualityJobInput
The input for the data quality monitoring job. Currently endpoints are supported for input.
DatasetDefinition
Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either AthenaDatasetDefinition or RedshiftDatasetDefinition types.
DataSource
Describes the location of the channel data.
DebugHookConfig
Configuration information for the Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the DebugHookConfig parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
DebugRuleConfiguration
Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the DebugRuleConfiguration parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.
DebugRuleEvaluationStatus
Information about the status of the rule evaluation.
DeleteActionResponse
DeleteArtifactResponse
DeleteAssociationResponse
DeleteContextResponse
DeleteExperimentResponse
DeleteFlowDefinitionResponse
DeleteHumanTaskUiResponse
DeleteImageResponse
DeleteImageVersionResponse
DeletePipelineResponse
DeleteTagsOutput
DeleteTrialComponentResponse
DeleteTrialResponse
DeleteWorkforceResponse
DeleteWorkteamResponse
DeployedImage
Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
DeploymentConfig
Currently, the DeploymentConfig API is not supported.
DescribeActionResponse
DescribeAlgorithmOutput
DescribeAppImageConfigResponse
DescribeAppResponse
DescribeArtifactResponse
DescribeAutoMLJobResponse
DescribeCodeRepositoryOutput
DescribeCompilationJobResponse
DescribeContextResponse
DescribeDataQualityJobDefinitionResponse
DescribeDeviceFleetResponse
DescribeDeviceResponse
DescribeDomainResponse
DescribeEdgePackagingJobResponse
DescribeEndpointConfigOutput
DescribeEndpointOutput
DescribeExperimentResponse
DescribeFeatureGroupResponse
DescribeFlowDefinitionResponse
DescribeHumanTaskUiResponse
DescribeHyperParameterTuningJobResponse
DescribeImageResponse
DescribeImageVersionResponse
DescribeLabelingJobResponse
DescribeModelBiasJobDefinitionResponse
DescribeModelExplainabilityJobDefinitionResponse
DescribeModelOutput
DescribeModelPackageGroupOutput
DescribeModelPackageOutput
DescribeModelQualityJobDefinitionResponse
DescribeMonitoringScheduleResponse
DescribeNotebookInstanceLifecycleConfigOutput
DescribeNotebookInstanceOutput
DescribePipelineDefinitionForExecutionResponse
DescribePipelineExecutionResponse
DescribePipelineResponse
DescribeProcessingJobResponse
DescribeProjectOutput
DescribeSubscribedWorkteamResponse
DescribeTrainingJobResponse
DescribeTransformJobResponse
DescribeTrialComponentResponse
DescribeTrialResponse
DescribeUserProfileResponse
DescribeWorkforceResponse
DescribeWorkteamResponse
DesiredWeightAndCapacity
Specifies weight and capacity values for a production variant.
Device
Information of a particular device.
DeviceFleetSummary
Summary of the device fleet.
DeviceStats
Status of devices.
DeviceSummary
Summary of the device.
DisableSagemakerServicecatalogPortfolioOutput
DisassociateTrialComponentResponse
DomainDetails
The domain's details.
EdgeModel
The model on the edge device.
EdgeModelStat
Status of edge devices with this model.
EdgeModelSummary
Summary of model on edge device.
EdgeOutputConfig
The output configuration.
EdgePackagingJobSummary
Summary of edge packaging job.
EnableSagemakerServicecatalogPortfolioOutput
Endpoint
A hosted endpoint for real-time inference.
EndpointConfigSummary
Provides summary information for an endpoint configuration.
EndpointInput
Input object for the endpoint
EndpointSummary
Provides summary information for an endpoint.
Experiment
The properties of an experiment as returned by the Search API.
ExperimentConfig
Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
ExperimentSource
The source of the experiment.
ExperimentSummary
A summary of the properties of an experiment. To get the complete set of properties, call the DescribeExperiment API and provide the ExperimentName.
Explainability
Contains explainability metrics for a model.
FeatureDefinition
A list of features. You must include FeatureName and FeatureType. Valid feature FeatureTypes are Integral, Fractional and String.
FeatureGroup
Amazon SageMaker Feature Store stores features in a collection called Feature Group. A Feature Group can be visualized as a table which has rows, with a unique identifier for each row where each column in the table is a feature. In principle, a Feature Group is composed of features and values per features.
FeatureGroupSummary
The name, Arn, CreationTime, FeatureGroup values, LastUpdatedTime and EnableOnlineStorage status of a FeatureGroup.
FileSystemConfig
The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
FileSystemDataSource
Specifies a file system data source for a channel.
Filter
A conditional statement for a search expression that includes a resource property, a Boolean operator, and a value. Resources that match the statement are returned in the results from the Search API.
FinalAutoMLJobObjectiveMetric
The best candidate result from an AutoML training job.
FinalHyperParameterTuningJobObjectiveMetric
Shows the final value for the objective metric for a training job that was launched by a hyperparameter tuning job. You define the objective metric in the HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.
FlowDefinitionOutputConfig
Contains information about where human output will be stored.
FlowDefinitionSummary
Contains summary information about the flow definition.
GetDeviceFleetReportResponse
GetModelPackageGroupPolicyOutput
GetSagemakerServicecatalogPortfolioStatusOutput
GetSearchSuggestionsResponse
GitConfig
Specifies configuration details for a Git repository in your AWS account.
GitConfigForUpdate
Specifies configuration details for a Git repository when the repository is updated.
HumanLoopActivationConditionsConfig
Defines under what conditions SageMaker creates a human loop. Used within . See for the required format of activation conditions.
HumanLoopActivationConfig
Provides information about how and under what conditions SageMaker creates a human loop. If HumanLoopActivationConfig is not given, then all requests go to humans.
HumanLoopConfig
Describes the work to be performed by human workers.
HumanLoopRequestSource
Container for configuring the source of human task requests.
HumanTaskConfig
Information required for human workers to complete a labeling task.
HumanTaskUiSummary
Container for human task user interface information.
HyperParameterAlgorithmSpecification
Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
HyperParameterSpecification
Defines a hyperparameter to be used by an algorithm.
HyperParameterTrainingJobDefinition
Defines the training jobs launched by a hyperparameter tuning job.
HyperParameterTrainingJobSummary
Specifies summary information about a training job.
HyperParameterTuningJobConfig
Configures a hyperparameter tuning job.
HyperParameterTuningJobObjective
Defines the objective metric for a hyperparameter tuning job. Hyperparameter tuning uses the value of this metric to evaluate the training jobs it launches, and returns the training job that results in either the highest or lowest value for this metric, depending on the value you specify for the Type parameter.
HyperParameterTuningJobSummary
Provides summary information about a hyperparameter tuning job.
HyperParameterTuningJobWarmStartConfig
Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
Image
A SageMaker image. A SageMaker image represents a set of container images that are derived from a common base container image. Each of these container images is represented by a SageMaker ImageVersion.
ImageConfig
Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
ImageVersion
A version of a SageMaker Image. A version represents an existing container image.
InferenceSpecification
Defines how to perform inference generation after a training job is run.
InputConfig
Contains information about the location of input model artifacts, the name and shape of the expected data inputs, and the framework in which the model was trained.
IntegerParameterRange
For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
IntegerParameterRangeSpecification
Defines the possible values for an integer hyperparameter.
JupyterServerAppSettings
The JupyterServer app settings.
KernelGatewayAppSettings
The KernelGateway app settings.
KernelGatewayImageConfig
The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.
KernelSpec
The specification of a Jupyter kernel.
LabelCounters
Provides a breakdown of the number of objects labeled.
LabelCountersForWorkteam
Provides counts for human-labeled tasks in the labeling job.
LabelingJobAlgorithmsConfig
Provides configuration information for auto-labeling of your data objects. A LabelingJobAlgorithmsConfig object must be supplied in order to use auto-labeling.
LabelingJobDataAttributes
Attributes of the data specified by the customer. Use these to describe the data to be labeled.
LabelingJobDataSource
Provides information about the location of input data.
LabelingJobForWorkteamSummary
Provides summary information for a work team.
LabelingJobInputConfig
Input configuration information for a labeling job.
LabelingJobOutput
Specifies the location of the output produced by the labeling job.
LabelingJobOutputConfig
Output configuration information for a labeling job.
LabelingJobResourceConfig
Provides configuration information for labeling jobs.
LabelingJobS3DataSource
The Amazon S3 location of the input data objects.
LabelingJobSnsDataSource
An Amazon SNS data source used for streaming labeling jobs.
LabelingJobStoppingConditions
A set of conditions for stopping a labeling job. If any of the conditions are met, the job is automatically stopped. You can use these conditions to control the cost of data labeling.
LabelingJobSummary
Provides summary information about a labeling job.
ListActionsResponse
ListAlgorithmsOutput
ListAppImageConfigsResponse
ListAppsResponse
ListArtifactsResponse
ListAssociationsResponse
ListAutoMLJobsResponse
ListCandidatesForAutoMLJobResponse
ListCodeRepositoriesOutput
ListCompilationJobsResponse
ListContextsResponse
ListDataQualityJobDefinitionsResponse
ListDeviceFleetsResponse
ListDevicesResponse
ListDomainsResponse
ListEdgePackagingJobsResponse
ListEndpointConfigsOutput
ListEndpointsOutput
ListExperimentsResponse
ListFeatureGroupsResponse
ListFlowDefinitionsResponse
ListHumanTaskUisResponse
ListHyperParameterTuningJobsResponse
ListImagesResponse
ListImageVersionsResponse
ListLabelingJobsForWorkteamResponse
ListLabelingJobsResponse
ListModelBiasJobDefinitionsResponse
ListModelExplainabilityJobDefinitionsResponse
ListModelPackageGroupsOutput
ListModelPackagesOutput
ListModelQualityJobDefinitionsResponse
ListModelsOutput
ListMonitoringExecutionsResponse
ListMonitoringSchedulesResponse
ListNotebookInstanceLifecycleConfigsOutput
ListNotebookInstancesOutput
ListPipelineExecutionsResponse
ListPipelineExecutionStepsResponse
ListPipelineParametersForExecutionResponse
ListPipelinesResponse
ListProcessingJobsResponse
ListProjectsOutput
ListSubscribedWorkteamsResponse
ListTagsOutput
ListTrainingJobsForHyperParameterTuningJobResponse
ListTrainingJobsResponse
ListTransformJobsResponse
ListTrialComponentsResponse
ListTrialsResponse
ListUserProfilesResponse
ListWorkforcesResponse
ListWorkteamsResponse
MemberDefinition
Defines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.
MetadataProperties
Metadata properties of the tracking entity, trial, or trial component.
MetricData
The name, value, and date and time of a metric that was emitted to Amazon CloudWatch.
MetricDefinition
Specifies a metric that the training algorithm writes to stderr or stdout . Amazon SageMakerhyperparameter tuning captures all defined metrics. You specify one metric that a hyperparameter tuning job uses as its objective metric to choose the best training job.
MetricsSource
ModelArtifacts
Provides information about the location that is configured for storing model artifacts.
ModelBiasAppSpecification
Docker container image configuration object for the model bias job.
ModelBiasBaselineConfig
The configuration for a baseline model bias job.
ModelBiasJobInput
Inputs for the model bias job.
ModelClientConfig
Configures the timeout and maximum number of retries for processing a transform job invocation.
ModelDataQuality
Data quality constraints and statistics for a model.
ModelDigests
Provides information to verify the integrity of stored model artifacts.
ModelExplainabilityAppSpecification
Docker container image configuration object for the model explainability job.
ModelExplainabilityBaselineConfig
The configuration for a baseline model explainability job.
ModelExplainabilityJobInput
Inputs for the model explainability job.
ModelMetrics
Contains metrics captured from a model.
ModelPackage
A versioned model that can be deployed for SageMaker inference.
ModelPackageContainerDefinition
Describes the Docker container for the model package.
ModelPackageGroup
A group of versioned models in the model registry.
ModelPackageGroupSummary
Summary information about a model group.
ModelPackageStatusDetails
Specifies the validation and image scan statuses of the model package.
ModelPackageStatusItem
Represents the overall status of a model package.
ModelPackageSummary
Provides summary information about a model package.
ModelPackageValidationProfile
Contains data, such as the inputs and targeted instance types that are used in the process of validating the model package.
ModelPackageValidationSpecification
Specifies batch transform jobs that Amazon SageMaker runs to validate your model package.
ModelQuality
Model quality statistics and constraints.
ModelQualityAppSpecification
Container image configuration object for the monitoring job.
ModelQualityBaselineConfig
Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
ModelQualityJobInput
The input for the model quality monitoring job. Currently endponts are supported for input for model quality monitoring jobs.
ModelStepMetadata
Metadata for Model steps.
ModelSummary
Provides summary information about a model.
MonitoringAppSpecification
Container image configuration object for the monitoring job.
MonitoringBaselineConfig
Configuration for monitoring constraints and monitoring statistics. These baseline resources are compared against the results of the current job from the series of jobs scheduled to collect data periodically.
MonitoringClusterConfig
Configuration for the cluster used to run model monitoring jobs.
MonitoringConstraintsResource
The constraints resource for a monitoring job.
MonitoringExecutionSummary
Summary of information about the last monitoring job to run.
MonitoringGroundTruthS3Input
The ground truth labels for the dataset used for the monitoring job.
MonitoringInput
The inputs for a monitoring job.
MonitoringJobDefinition
Defines the monitoring job.
MonitoringJobDefinitionSummary
Summary information about a monitoring job.
MonitoringNetworkConfig
The networking configuration for the monitoring job.
MonitoringOutput
The output object for a monitoring job.
MonitoringOutputConfig
The output configuration for monitoring jobs.
MonitoringResources
Identifies the resources to deploy for a monitoring job.
MonitoringS3Output
Information about where and how you want to store the results of a monitoring job.
MonitoringSchedule
A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
MonitoringScheduleConfig
Configures the monitoring schedule and defines the monitoring job.
MonitoringScheduleSummary
Summarizes the monitoring schedule.
MonitoringStatisticsResource
The statistics resource for a monitoring job.
MonitoringStoppingCondition
A time limit for how long the monitoring job is allowed to run before stopping.
NestedFilters
A list of nested Filter objects. A resource must satisfy the conditions of all filters to be included in the results returned from the Search API.
NetworkConfig
Networking options for a job, such as network traffic encryption between containers, whether to allow inbound and outbound network calls to and from containers, and the VPC subnets and security groups to use for VPC-enabled jobs.
NotebookInstanceLifecycleConfigSummary
Provides a summary of a notebook instance lifecycle configuration.
NotebookInstanceLifecycleHook
Contains the notebook instance lifecycle configuration script.
NotebookInstanceSummary
Provides summary information for an Amazon SageMaker notebook instance.
NotificationConfiguration
Configures SNS notifications of available or expiring work items for work teams.
ObjectiveStatusCounters
Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
OfflineStoreConfig
The configuration of an OfflineStore.
OfflineStoreStatus
The status of OfflineStore.
OidcConfig
Use this parameter to configure your OIDC Identity Provider (IdP).
OidcConfigForResponse
Your OIDC IdP workforce configuration.
OidcMemberDefinition
A list of user groups that exist in your OIDC Identity Provider (IdP). One to ten groups can be used to create a single private work team. When you add a user group to the list of Groups, you can add that user group to one or more private work teams. If you add a user group to a private work team, all workers in that user group are added to the work team.
OnlineStoreConfig
Use this to specify the AWS Key Management Service (KMS) Key ID, or KMSKeyId, for at rest data encryption. You can turn OnlineStore on or off by specifying the EnableOnlineStore flag at General Assembly; the default value is False.
OnlineStoreSecurityConfig
The security configuration for OnlineStore.
OutputConfig
Contains information about the output location for the compiled model and the target device that the model runs on. TargetDevice and TargetPlatform are mutually exclusive, so you need to choose one between the two to specify your target device or platform. If you cannot find your device you want to use from the TargetDevice list, use TargetPlatform to describe the platform of your edge device and CompilerOptions if there are specific settings that are required or recommended to use for particular TargetPlatform.
OutputDataConfig
Provides information about how to store model training results (model artifacts).
Parameter
Assigns a value to a named Pipeline parameter.
ParameterRange
Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
ParameterRanges
Specifies ranges of integer, continuous, and categorical hyperparameters that a hyperparameter tuning job searches. The hyperparameter tuning job launches training jobs with hyperparameter values within these ranges to find the combination of values that result in the training job with the best performance as measured by the objective metric of the hyperparameter tuning job.
Parent
The trial that a trial component is associated with and the experiment the trial is part of. A component might not be associated with a trial. A component can be associated with multiple trials.
ParentHyperParameterTuningJob
A previously completed or stopped hyperparameter tuning job to be used as a starting point for a new hyperparameter tuning job.
Pipeline
A SageMaker Model Building Pipeline instance.
PipelineExecution
An execution of a pipeline.
PipelineExecutionStep
An execution of a step in a pipeline.
PipelineExecutionStepMetadata
Metadata for a step execution.
PipelineExecutionSummary
A pipeline execution summary.
PipelineSummary
A summary of a pipeline.
ProcessingClusterConfig
Configuration for the cluster used to run a processing job.
ProcessingFeatureStoreOutput
Configuration for processing job outputs in Amazon SageMaker Feature Store.
ProcessingInput
The inputs for a processing job. The processing input must specify exactly one of either S3Input or DatasetDefinition types.
ProcessingJob
An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
ProcessingJobStepMetadata
Metadata for a processing job step.
ProcessingJobSummary
Summary of information about a processing job.
ProcessingOutput
Describes the results of a processing job. The processing output must specify exactly one of either S3Output or FeatureStoreOutput types.
ProcessingOutputConfig
The output configuration for the processing job.
ProcessingResources
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.
ProcessingS3Input
Configuration for processing job inputs in Amazon S3.
ProcessingS3Output
Configuration for processing job outputs in Amazon S3.
ProcessingStoppingCondition
Specifies a time limit for how long the processing job is allowed to run.
ProductionVariant
Identifies a model that you want to host and the resources to deploy for hosting it. If you are deploying multiple models, tell Amazon SageMaker how to distribute traffic among the models by specifying variant weights.
ProductionVariantSummary
Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the UpdateEndpointWeightsAndCapacities API and the endpoint status is Updating, you get different desired and current values.
ProfilerConfig
Configuration information for Debugger system monitoring, framework profiling, and storage paths.
ProfilerConfigForUpdate
Configuration information for updating the Debugger profile parameters, system and framework metrics configurations, and storage paths.
ProfilerRuleConfiguration
Configuration information for profiling rules.
ProfilerRuleEvaluationStatus
Information about the status of the rule evaluation.
ProjectSummary
Information about a project.
PropertyNameQuery
Part of the SuggestionQuery type. Specifies a hint for retrieving property names that begin with the specified text.
PropertyNameSuggestion
A property name returned from a GetSearchSuggestions call that specifies a value in the PropertyNameQuery field.
ProvisioningParameter
A key value pair used when you provision a project as a service catalog product. For information, see What is AWS Service Catalog.
PublicWorkforceTaskPrice
Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
PutModelPackageGroupPolicyOutput
RedshiftDatasetDefinition
Configuration for Redshift Dataset Definition input.
RegisterModelStepMetadata
Metadata for a register model job step.
RenderableTask
Contains input values for a task.
RenderingError
A description of an error that occurred while rendering the template.
RenderUiTemplateResponse
ResolvedAttributes
The resolved attributes.
ResourceConfig
Describes the resources, including ML compute instances and ML storage volumes, to use for model training.
ResourceLimits
Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
ResourceSpec
Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
RetentionPolicy
The retention policy for data stored on an Amazon Elastic File System (EFS) volume.
S3DataSource
Describes the S3 data source.
S3StorageConfig
The Amazon Simple Storage (Amazon S3) location and and security configuration for OfflineStore.
SageMaker
Provides APIs for creating and managing Amazon SageMaker resources.
ScheduleConfig
Configuration details about the monitoring schedule.
SearchExpression
A multi-expression that searches for the specified resource or resources in a search. All resource objects that satisfy the expression's condition are included in the search results. You must specify at least one subexpression, filter, or nested filter. A SearchExpression can contain up to twenty elements.
SearchRecord
A single resource returned as part of the Search API response.
SearchResponse
SecondaryStatusTransition
An array element of DescribeTrainingJobResponse$SecondaryStatusTransitions. It provides additional details about a status that the training job has transitioned through. A training job can be in one of several states, for example, starting, downloading, training, or uploading. Within each state, there are a number of intermediate states. For example, within the starting state, Amazon SageMaker could be starting the training job or launching the ML instances. These transitional states are referred to as the job's secondary status.
ServiceCatalogProvisionedProductDetails
Details of a provisioned service catalog product. For information about service catalog, see What is AWS Service Catalog.
ServiceCatalogProvisioningDetails
Details that you specify to provision a service catalog product. For information about service catalog, see .What is AWS Service Catalog.
SharingSettings
Specifies options when sharing an Amazon SageMaker Studio notebook. These settings are specified as part of DefaultUserSettings when the CreateDomain API is called, and as part of UserSettings when the CreateUserProfile API is called.
ShuffleConfig
A configuration for a shuffle option for input data in a channel. If you use S3Prefix for S3DataType, the results of the S3 key prefix matches are shuffled. If you use ManifestFile, the order of the S3 object references in the ManifestFile is shuffled. If you use AugmentedManifestFile, the order of the JSON lines in the AugmentedManifestFile is shuffled. The shuffling order is determined using the Seed value.
SourceAlgorithm
Specifies an algorithm that was used to create the model package. The algorithm must be either an algorithm resource in your Amazon SageMaker account or an algorithm in AWS Marketplace that you are subscribed to.
SourceAlgorithmSpecification
A list of algorithms that were used to create a model package.
SourceIpConfig
A list of IP address ranges (CIDRs). 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.
StartPipelineExecutionResponse
StoppingCondition
Specifies a limit to how long a model training or compilation job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the time limit, Amazon SageMaker ends the training or compilation job. Use this API to cap model training costs.
StopPipelineExecutionResponse
SubscribedWorkteam
Describes a work team of a vendor that does the a labelling job.
SuggestionQuery
Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
Tag
Describes a tag.
TargetPlatform
Contains information about a target platform that you want your model to run on, such as OS, architecture, and accelerators. It is an alternative of TargetDevice.
TensorBoardAppSettings
The TensorBoard app settings.
TensorBoardOutputConfig
Configuration of storage locations for the Debugger TensorBoard output data.
TrafficRoutingConfig
Currently, the TrafficRoutingConfig API is not supported.
TrainingJob
Contains information about a training job.
TrainingJobDefinition
Defines the input needed to run a training job using the algorithm.
TrainingJobStatusCounters
The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
TrainingJobStepMetadata
Metadata for a training job step.
TrainingJobSummary
Provides summary information about a training job.
TrainingSpecification
Defines how the algorithm is used for a training job.
TransformDataSource
Describes the location of the channel data.
TransformInput
Describes the input source of a transform job and the way the transform job consumes it.
TransformJob
A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
TransformJobDefinition
Defines the input needed to run a transform job using the inference specification specified in the algorithm.
TransformJobStepMetadata
Metadata for a transform job step.
TransformJobSummary
Provides a summary of a transform job. Multiple TransformJobSummary objects are returned as a list after in response to a ListTransformJobs call.
TransformOutput
Describes the results of a transform job.
TransformResources
Describes the resources, including ML instance types and ML instance count, to use for transform job.
TransformS3DataSource
Describes the S3 data source.
Trial
The properties of a trial as returned by the Search API.
TrialComponent
The properties of a trial component as returned by the Search API.
TrialComponentArtifact
Represents an input or output artifact of a trial component. You specify TrialComponentArtifact as part of the InputArtifacts and OutputArtifacts parameters in the CreateTrialComponent request.
TrialComponentMetricSummary
A summary of the metrics of a trial component.
TrialComponentParameterValue
The value of a hyperparameter. Only one of NumberValue or StringValue can be specified.
TrialComponentSimpleSummary
A short summary of a trial component.
TrialComponentSource
The Amazon Resource Name (ARN) and job type of the source of a trial component.
TrialComponentSourceDetail
Detailed information about the source of a trial component. Either ProcessingJob or TrainingJob is returned.
TrialComponentStatus
The status of the trial component.
TrialComponentSummary
A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the TrialComponentName.
TrialSource
The source of the trial.
TrialSummary
A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the TrialName.
TuningJobCompletionCriteria
The job completion criteria.
UiConfig
Provided configuration information for the worker UI for a labeling job.
UiTemplate
The Liquid template for the worker user interface.
UiTemplateInfo
Container for user interface template information.
UpdateActionResponse
UpdateAppImageConfigResponse
UpdateArtifactResponse
UpdateCodeRepositoryOutput
UpdateContextResponse
UpdateDomainResponse
UpdateEndpointOutput
UpdateEndpointWeightsAndCapacitiesOutput
UpdateExperimentResponse
UpdateImageResponse
UpdateModelPackageOutput
UpdateMonitoringScheduleResponse
UpdateNotebookInstanceLifecycleConfigOutput
UpdateNotebookInstanceOutput
UpdatePipelineExecutionResponse
UpdatePipelineResponse
UpdateTrainingJobResponse
UpdateTrialComponentResponse
UpdateTrialResponse
UpdateUserProfileResponse
UpdateWorkforceResponse
UpdateWorkteamResponse
USD
Represents an amount of money in United States dollars/
UserContext
Information about the user who created or modified an experiment, trial, or trial component.
UserProfileDetails
The user profile details.
UserSettings
A collection of settings.
VariantProperty
Specifies a production variant property type for an Endpoint.
VpcConfig
Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC. For more information, see Protect Endpoints by Using an Amazon Virtual Private Cloud and Protect Training Jobs by Using an Amazon Virtual Private Cloud.
Workforce
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.
Workteam
Provides details about a labeling work team.

Enums

ActionStatus
AlgorithmSortBy
AlgorithmStatus
AppImageConfigSortKey
AppInstanceType
AppNetworkAccessType
AppSortKey
AppStatus
AppType
ArtifactSourceIdType
AssemblyType
AssociationEdgeType
AthenaResultCompressionType
The compression used for Athena query results.
AthenaResultFormat
The data storage format for Athena query results.
AuthMode
AutoMLJobObjectiveType
AutoMLJobSecondaryStatus
AutoMLJobStatus
AutoMLMetricEnum
AutoMLS3DataType
AutoMLSortBy
AutoMLSortOrder
AwsManagedHumanLoopRequestSource
BatchStrategy
BooleanOperator
CandidateSortBy
CandidateStatus
CandidateStepType
CapacitySizeType
CaptureMode
CaptureStatus
CodeRepositorySortBy
CodeRepositorySortOrder
CompilationJobStatus
CompressionType
ConditionOutcome
ContainerMode
ContentClassifier
DataDistributionType
DetailedAlgorithmStatus
DetailedModelPackageStatus
DirectInternetAccess
DomainStatus
EdgePackagingJobStatus
EndpointConfigSortKey
EndpointSortKey
EndpointStatus
ExecutionStatus
FeatureGroupSortBy
FeatureGroupSortOrder
FeatureGroupStatus
FeatureType
FileSystemAccessMode
FileSystemType
FlowDefinitionStatus
Framework
HumanTaskUiStatus
HyperParameterScalingType
HyperParameterTuningJobObjectiveType
HyperParameterTuningJobSortByOptions
HyperParameterTuningJobStatus
HyperParameterTuningJobStrategyType
The strategy hyperparameter tuning uses to find the best combination of hyperparameters for your model. Currently, the only supported value is Bayesian.
HyperParameterTuningJobWarmStartType
ImageSortBy
ImageSortOrder
ImageStatus
ImageVersionSortBy
ImageVersionSortOrder
ImageVersionStatus
InputMode
InstanceType
JoinSource
LabelingJobStatus
ListCompilationJobsSortBy
ListDeviceFleetsSortBy
ListEdgePackagingJobsSortBy
ListLabelingJobsForWorkteamSortByOptions
ListWorkforcesSortByOptions
ListWorkteamsSortByOptions
ModelApprovalStatus
ModelPackageGroupSortBy
ModelPackageGroupStatus
ModelPackageSortBy
ModelPackageStatus
ModelPackageType
ModelSortKey
MonitoringExecutionSortKey
MonitoringJobDefinitionSortKey
MonitoringProblemType
MonitoringScheduleSortKey
MonitoringType
NotebookInstanceAcceleratorType
NotebookInstanceLifecycleConfigSortKey
NotebookInstanceLifecycleConfigSortOrder
NotebookInstanceSortKey
NotebookInstanceSortOrder
NotebookInstanceStatus
NotebookOutputOption
ObjectiveStatus
OfflineStoreStatusValue
Operator
OrderKey
ParameterType
PipelineExecutionStatus
PipelineStatus
ProblemType
ProcessingInstanceType
ProcessingJobStatus
ProcessingS3CompressionType
ProcessingS3DataDistributionType
ProcessingS3DataType
ProcessingS3InputMode
ProcessingS3UploadMode
ProductionVariantAcceleratorType
ProductionVariantInstanceType
ProfilingStatus
ProjectSortBy
ProjectSortOrder
ProjectStatus
RecordWrapper
RedshiftResultCompressionType
The compression used for Redshift query results.
RedshiftResultFormat
The data storage format for Redshift query results.
RepositoryAccessMode
ResourceType
RetentionType
RootAccess
RuleEvaluationStatus
S3DataDistribution
S3DataType
SagemakerServicecatalogStatus
ScheduleStatus
SearchSortOrder
SecondaryStatus
SortActionsBy
SortArtifactsBy
SortAssociationsBy
SortBy
SortContextsBy
SortExperimentsBy
SortOrder
SortPipelineExecutionsBy
SortPipelinesBy
SortTrialComponentsBy
SortTrialsBy
SplitType
StepStatus
TargetDevice
TargetPlatformAccelerator
TargetPlatformArch
TargetPlatformOs
TrafficRoutingConfigType
TrainingInputMode
TrainingInstanceType
TrainingJobEarlyStoppingType
TrainingJobSortByOptions
TrainingJobStatus
TransformInstanceType
TransformJobStatus
TrialComponentPrimaryStatus
UserProfileSortKey
UserProfileStatus
VariantPropertyType