[−][src]Crate rusoto_sagemaker
Provides APIs for creating and managing Amazon SageMaker resources.
Other Resources:
If you're using the service, you're probably looking for SageMakerClient and SageMaker.
Structs
AddTagsInput | |
AddTagsOutput | |
AlgorithmSpecification | Specifies the training algorithm to use in a CreateTrainingJob request. For more information about algorithms provided by Amazon SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker. |
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. The data provided in the validation profile is made available to your buyers on AWS Marketplace. |
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 | The app's details. |
AppSpecification | Configuration to run a processing job in a specified container image. |
AssociateTrialComponentRequest | |
AssociateTrialComponentResponse | |
AutoMLCandidate | An AutoPilot job will return 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 | Applies a metric to minimize or maximize for the job's objective. |
AutoMLJobSummary | Provides a summary about a job. |
AutoMLOutputDataConfig | The output data configuration. |
AutoMLS3DataSource | The Amazon S3 data source. |
AutoMLSecurityConfig | Security options. |
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. |
CognitoMemberDefinition | Identifies a Amazon Cognito user group. A user group can be used in on or more work teams. |
CollectionConfiguration | Configuration information for tensor collections. |
CompilationJobSummary | A summary of a model compilation job. |
ContainerDefinition | Describes the container, as part of model definition. |
ContinuousParameterRange | A list of continuous hyperparameters to tune. |
ContinuousParameterRangeSpecification | Defines the possible values for a continuous hyperparameter. |
CreateAlgorithmInput | |
CreateAlgorithmOutput | |
CreateAppRequest | |
CreateAppResponse | |
CreateAutoMLJobRequest | |
CreateAutoMLJobResponse | |
CreateCodeRepositoryInput | |
CreateCodeRepositoryOutput | |
CreateCompilationJobRequest | |
CreateCompilationJobResponse | |
CreateDomainRequest | |
CreateDomainResponse | |
CreateEndpointConfigInput | |
CreateEndpointConfigOutput | |
CreateEndpointInput | |
CreateEndpointOutput | |
CreateExperimentRequest | |
CreateExperimentResponse | |
CreateFlowDefinitionRequest | |
CreateFlowDefinitionResponse | |
CreateHumanTaskUiRequest | |
CreateHumanTaskUiResponse | |
CreateHyperParameterTuningJobRequest | |
CreateHyperParameterTuningJobResponse | |
CreateLabelingJobRequest | |
CreateLabelingJobResponse | |
CreateModelInput | |
CreateModelOutput | |
CreateModelPackageInput | |
CreateModelPackageOutput | |
CreateMonitoringScheduleRequest | |
CreateMonitoringScheduleResponse | |
CreateNotebookInstanceInput | |
CreateNotebookInstanceLifecycleConfigInput | |
CreateNotebookInstanceLifecycleConfigOutput | |
CreateNotebookInstanceOutput | |
CreatePresignedDomainUrlRequest | |
CreatePresignedDomainUrlResponse | |
CreatePresignedNotebookInstanceUrlInput | |
CreatePresignedNotebookInstanceUrlOutput | |
CreateProcessingJobRequest | |
CreateProcessingJobResponse | |
CreateTrainingJobRequest | |
CreateTrainingJobResponse | |
CreateTransformJobRequest | |
CreateTransformJobResponse | |
CreateTrialComponentRequest | |
CreateTrialComponentResponse | |
CreateTrialRequest | |
CreateTrialResponse | |
CreateUserProfileRequest | |
CreateUserProfileResponse | |
CreateWorkteamRequest | |
CreateWorkteamResponse | |
DataCaptureConfig | |
DataCaptureConfigSummary | |
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. |
DataSource | Describes the location of the channel data. |
DebugHookConfig | Configuration information for the debug hook parameters, collection configuration, and storage paths. |
DebugRuleConfiguration | Configuration information for debugging rules. |
DebugRuleEvaluationStatus | Information about the status of the rule evaluation. |
DeleteAlgorithmInput | |
DeleteAppRequest | |
DeleteCodeRepositoryInput | |
DeleteDomainRequest | |
DeleteEndpointConfigInput | |
DeleteEndpointInput | |
DeleteExperimentRequest | |
DeleteExperimentResponse | |
DeleteFlowDefinitionRequest | |
DeleteFlowDefinitionResponse | |
DeleteHumanTaskUiRequest | |
DeleteHumanTaskUiResponse | |
DeleteModelInput | |
DeleteModelPackageInput | |
DeleteMonitoringScheduleRequest | |
DeleteNotebookInstanceInput | |
DeleteNotebookInstanceLifecycleConfigInput | |
DeleteTagsInput | |
DeleteTagsOutput | |
DeleteTrialComponentRequest | |
DeleteTrialComponentResponse | |
DeleteTrialRequest | |
DeleteTrialResponse | |
DeleteUserProfileRequest | |
DeleteWorkteamRequest | |
DeleteWorkteamResponse | |
DeployedImage | Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant. If you used the |
DescribeAlgorithmInput | |
DescribeAlgorithmOutput | |
DescribeAppRequest | |
DescribeAppResponse | |
DescribeAutoMLJobRequest | |
DescribeAutoMLJobResponse | |
DescribeCodeRepositoryInput | |
DescribeCodeRepositoryOutput | |
DescribeCompilationJobRequest | |
DescribeCompilationJobResponse | |
DescribeDomainRequest | |
DescribeDomainResponse | |
DescribeEndpointConfigInput | |
DescribeEndpointConfigOutput | |
DescribeEndpointInput | |
DescribeEndpointOutput | |
DescribeExperimentRequest | |
DescribeExperimentResponse | |
DescribeFlowDefinitionRequest | |
DescribeFlowDefinitionResponse | |
DescribeHumanTaskUiRequest | |
DescribeHumanTaskUiResponse | |
DescribeHyperParameterTuningJobRequest | |
DescribeHyperParameterTuningJobResponse | |
DescribeLabelingJobRequest | |
DescribeLabelingJobResponse | |
DescribeModelInput | |
DescribeModelOutput | |
DescribeModelPackageInput | |
DescribeModelPackageOutput | |
DescribeMonitoringScheduleRequest | |
DescribeMonitoringScheduleResponse | |
DescribeNotebookInstanceInput | |
DescribeNotebookInstanceLifecycleConfigInput | |
DescribeNotebookInstanceLifecycleConfigOutput | |
DescribeNotebookInstanceOutput | |
DescribeProcessingJobRequest | |
DescribeProcessingJobResponse | |
DescribeSubscribedWorkteamRequest | |
DescribeSubscribedWorkteamResponse | |
DescribeTrainingJobRequest | |
DescribeTrainingJobResponse | |
DescribeTransformJobRequest | |
DescribeTransformJobResponse | |
DescribeTrialComponentRequest | |
DescribeTrialComponentResponse | |
DescribeTrialRequest | |
DescribeTrialResponse | |
DescribeUserProfileRequest | |
DescribeUserProfileResponse | |
DescribeWorkforceRequest | |
DescribeWorkforceResponse | |
DescribeWorkteamRequest | |
DescribeWorkteamResponse | |
DesiredWeightAndCapacity | Specifies weight and capacity values for a production variant. |
DisassociateTrialComponentRequest | |
DisassociateTrialComponentResponse | |
DomainDetails | The domain's details. |
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 | Configuration for the experiment. |
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 |
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. If you specify a In search, there are several property types:
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FinalAutoMLJobObjectiveMetric | The candidate result from a 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 |
FlowDefinitionOutputConfig | Contains information about where human output will be stored. |
FlowDefinitionSummary | Contains summary information about the flow definition. |
GetSearchSuggestionsRequest | |
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 |
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 |
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. All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job. All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job. |
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 | Jupyter server's app settings. |
KernelGatewayAppSettings | The kernel gateway app settings. |
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 |
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. |
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. Labeling jobs fail after 30 days with an appropriate client error message. |
LabelingJobSummary | Provides summary information about a labeling job. |
ListAlgorithmsInput | |
ListAlgorithmsOutput | |
ListAppsRequest | |
ListAppsResponse | |
ListAutoMLJobsRequest | |
ListAutoMLJobsResponse | |
ListCandidatesForAutoMLJobRequest | |
ListCandidatesForAutoMLJobResponse | |
ListCodeRepositoriesInput | |
ListCodeRepositoriesOutput | |
ListCompilationJobsRequest | |
ListCompilationJobsResponse | |
ListDomainsRequest | |
ListDomainsResponse | |
ListEndpointConfigsInput | |
ListEndpointConfigsOutput | |
ListEndpointsInput | |
ListEndpointsOutput | |
ListExperimentsRequest | |
ListExperimentsResponse | |
ListFlowDefinitionsRequest | |
ListFlowDefinitionsResponse | |
ListHumanTaskUisRequest | |
ListHumanTaskUisResponse | |
ListHyperParameterTuningJobsRequest | |
ListHyperParameterTuningJobsResponse | |
ListLabelingJobsForWorkteamRequest | |
ListLabelingJobsForWorkteamResponse | |
ListLabelingJobsRequest | |
ListLabelingJobsResponse | |
ListModelPackagesInput | |
ListModelPackagesOutput | |
ListModelsInput | |
ListModelsOutput | |
ListMonitoringExecutionsRequest | |
ListMonitoringExecutionsResponse | |
ListMonitoringSchedulesRequest | |
ListMonitoringSchedulesResponse | |
ListNotebookInstanceLifecycleConfigsInput | |
ListNotebookInstanceLifecycleConfigsOutput | |
ListNotebookInstancesInput | |
ListNotebookInstancesOutput | |
ListProcessingJobsRequest | |
ListProcessingJobsResponse | |
ListSubscribedWorkteamsRequest | |
ListSubscribedWorkteamsResponse | |
ListTagsInput | |
ListTagsOutput | |
ListTrainingJobsForHyperParameterTuningJobRequest | |
ListTrainingJobsForHyperParameterTuningJobResponse | |
ListTrainingJobsRequest | |
ListTrainingJobsResponse | |
ListTransformJobsRequest | |
ListTransformJobsResponse | |
ListTrialComponentsRequest | |
ListTrialComponentsResponse | |
ListTrialsRequest | |
ListTrialsResponse | |
ListUserProfilesRequest | |
ListUserProfilesResponse | |
ListWorkteamsRequest | |
ListWorkteamsResponse | |
MemberDefinition | Defines the Amazon Cognito user group that is part of a work team. |
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 |
ModelArtifacts | Provides information about the location that is configured for storing model artifacts. Model artifacts are the output that results from training a model, and typically consist of trained parameters, a model defintion that desribes how to compute inferences, and other metadata. |
ModelClientConfig | Configures the timeout and maximum number of retries for processing a transform job invocation. |
ModelPackageContainerDefinition | Describes the Docker container for the model package. |
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. The data provided in the validation profile is made available to your buyers on AWS Marketplace. |
ModelPackageValidationSpecification | Specifies batch transform jobs that Amazon SageMaker runs to validate your model package. |
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. |
MonitoringInput | The inputs for a monitoring job. |
MonitoringJobDefinition | Defines 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. |
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. For example, to filter on a training job's
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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. Each lifecycle configuration script has a limit of 16384 characters. The value of the View CloudWatch Logs for notebook instance lifecycle configurations in log group 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. |
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. |
OutputConfig | Contains information about the output location for the compiled model and the device (target) that the model runs on. |
OutputDataConfig | Provides information about how to store model training results (model artifacts). |
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. You can specify a maximum of 20 hyperparameters that a hyperparameter tuning job can search over. Every possible value of a categorical parameter range counts against this limit. |
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. |
ProcessingClusterConfig | Configuration for the cluster used to run a processing job. |
ProcessingInput | The inputs for a processing job. |
ProcessingJob | An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models. |
ProcessingJobSummary | Summary of information about a processing job. |
ProcessingOutput | Describes the results of a processing job. |
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 | Information about where and how you want to obtain the inputs for an processing job. |
ProcessingS3Output | Information about where and how you want to store the results of an processing job. |
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 |
PropertyNameQuery | Part of the |
PropertyNameSuggestion | A property name returned from a |
PublicWorkforceTaskPrice | Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed. Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
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RenderUiTemplateRequest | |
RenderUiTemplateResponse | |
RenderableTask | Contains input values for a task. |
RenderingError | A description of an error that occurred while rendering the template. |
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 | The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance. The ARN is stored as metadata in SageMaker Studio notebooks. |
RetentionPolicy | The retention policy for data stored on an Amazon Elastic File System (EFS) volume. |
S3DataSource | Describes the S3 data source. |
SageMakerClient | A client for the SageMaker API. |
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 A
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SearchRecord | A single resource returned as part of the Search API response. |
SearchRequest | |
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. |
SharingSettings | Specifies options when sharing an Amazon SageMaker Studio notebook. These settings are specified as part of |
ShuffleConfig | A configuration for a shuffle option for input data in a channel. If you use For Pipe input mode, when |
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. For more information, see . |
StartMonitoringScheduleRequest | |
StartNotebookInstanceInput | |
StopAutoMLJobRequest | |
StopCompilationJobRequest | |
StopHyperParameterTuningJobRequest | |
StopLabelingJobRequest | |
StopMonitoringScheduleRequest | |
StopNotebookInstanceInput | |
StopProcessingJobRequest | |
StopTrainingJobRequest | |
StopTransformJobRequest | |
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. To stop a job, Amazon SageMaker sends the algorithm the The training algorithms provided by Amazon SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete. |
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. |
TensorBoardAppSettings | The TensorBoard app settings. |
TensorBoardOutputConfig | Configuration of storage locations for TensorBoard output. |
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. |
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. |
TransformJobDefinition | Defines the input needed to run a transform job using the inference specification specified in the algorithm. |
TransformJobSummary | Provides a summary of a transform job. Multiple |
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 Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images. |
TrialComponentMetricSummary | A summary of the metrics of a trial component. |
TrialComponentParameterValue | The value of a hyperparameter. Only one of This object is specified in the CreateTrialComponent request. |
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 |
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 |
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 |
TuningJobCompletionCriteria | The job completion criteria. |
USD | Represents an amount of money in United States dollars/ |
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. |
UpdateCodeRepositoryInput | |
UpdateCodeRepositoryOutput | |
UpdateDomainRequest | |
UpdateDomainResponse | |
UpdateEndpointInput | |
UpdateEndpointOutput | |
UpdateEndpointWeightsAndCapacitiesInput | |
UpdateEndpointWeightsAndCapacitiesOutput | |
UpdateExperimentRequest | |
UpdateExperimentResponse | |
UpdateMonitoringScheduleRequest | |
UpdateMonitoringScheduleResponse | |
UpdateNotebookInstanceInput | |
UpdateNotebookInstanceLifecycleConfigInput | |
UpdateNotebookInstanceLifecycleConfigOutput | |
UpdateNotebookInstanceOutput | |
UpdateTrialComponentRequest | |
UpdateTrialComponentResponse | |
UpdateTrialRequest | |
UpdateTrialResponse | |
UpdateUserProfileRequest | |
UpdateUserProfileResponse | |
UpdateWorkforceRequest | |
UpdateWorkforceResponse | |
UpdateWorkteamRequest | |
UpdateWorkteamResponse | |
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. If you are updating an endpoint with the UpdateEndpointInput$RetainAllVariantProperties option set to |
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
AddTagsError | Errors returned by AddTags |
AssociateTrialComponentError | Errors returned by AssociateTrialComponent |
CreateAlgorithmError | Errors returned by CreateAlgorithm |
CreateAppError | Errors returned by CreateApp |
CreateAutoMLJobError | Errors returned by CreateAutoMLJob |
CreateCodeRepositoryError | Errors returned by CreateCodeRepository |
CreateCompilationJobError | Errors returned by CreateCompilationJob |
CreateDomainError | Errors returned by CreateDomain |
CreateEndpointConfigError | Errors returned by CreateEndpointConfig |
CreateEndpointError | Errors returned by CreateEndpoint |
CreateExperimentError | Errors returned by CreateExperiment |
CreateFlowDefinitionError | Errors returned by CreateFlowDefinition |
CreateHumanTaskUiError | Errors returned by CreateHumanTaskUi |
CreateHyperParameterTuningJobError | Errors returned by CreateHyperParameterTuningJob |
CreateLabelingJobError | Errors returned by CreateLabelingJob |
CreateModelError | Errors returned by CreateModel |
CreateModelPackageError | Errors returned by CreateModelPackage |
CreateMonitoringScheduleError | Errors returned by CreateMonitoringSchedule |
CreateNotebookInstanceError | Errors returned by CreateNotebookInstance |
CreateNotebookInstanceLifecycleConfigError | Errors returned by CreateNotebookInstanceLifecycleConfig |
CreatePresignedDomainUrlError | Errors returned by CreatePresignedDomainUrl |
CreatePresignedNotebookInstanceUrlError | Errors returned by CreatePresignedNotebookInstanceUrl |
CreateProcessingJobError | Errors returned by CreateProcessingJob |
CreateTrainingJobError | Errors returned by CreateTrainingJob |
CreateTransformJobError | Errors returned by CreateTransformJob |
CreateTrialComponentError | Errors returned by CreateTrialComponent |
CreateTrialError | Errors returned by CreateTrial |
CreateUserProfileError | Errors returned by CreateUserProfile |
CreateWorkteamError | Errors returned by CreateWorkteam |
DeleteAlgorithmError | Errors returned by DeleteAlgorithm |
DeleteAppError | Errors returned by DeleteApp |
DeleteCodeRepositoryError | Errors returned by DeleteCodeRepository |
DeleteDomainError | Errors returned by DeleteDomain |
DeleteEndpointConfigError | Errors returned by DeleteEndpointConfig |
DeleteEndpointError | Errors returned by DeleteEndpoint |
DeleteExperimentError | Errors returned by DeleteExperiment |
DeleteFlowDefinitionError | Errors returned by DeleteFlowDefinition |
DeleteHumanTaskUiError | Errors returned by DeleteHumanTaskUi |
DeleteModelError | Errors returned by DeleteModel |
DeleteModelPackageError | Errors returned by DeleteModelPackage |
DeleteMonitoringScheduleError | Errors returned by DeleteMonitoringSchedule |
DeleteNotebookInstanceError | Errors returned by DeleteNotebookInstance |
DeleteNotebookInstanceLifecycleConfigError | Errors returned by DeleteNotebookInstanceLifecycleConfig |
DeleteTagsError | Errors returned by DeleteTags |
DeleteTrialComponentError | Errors returned by DeleteTrialComponent |
DeleteTrialError | Errors returned by DeleteTrial |
DeleteUserProfileError | Errors returned by DeleteUserProfile |
DeleteWorkteamError | Errors returned by DeleteWorkteam |
DescribeAlgorithmError | Errors returned by DescribeAlgorithm |
DescribeAppError | Errors returned by DescribeApp |
DescribeAutoMLJobError | Errors returned by DescribeAutoMLJob |
DescribeCodeRepositoryError | Errors returned by DescribeCodeRepository |
DescribeCompilationJobError | Errors returned by DescribeCompilationJob |
DescribeDomainError | Errors returned by DescribeDomain |
DescribeEndpointConfigError | Errors returned by DescribeEndpointConfig |
DescribeEndpointError | Errors returned by DescribeEndpoint |
DescribeExperimentError | Errors returned by DescribeExperiment |
DescribeFlowDefinitionError | Errors returned by DescribeFlowDefinition |
DescribeHumanTaskUiError | Errors returned by DescribeHumanTaskUi |
DescribeHyperParameterTuningJobError | Errors returned by DescribeHyperParameterTuningJob |
DescribeLabelingJobError | Errors returned by DescribeLabelingJob |
DescribeModelError | Errors returned by DescribeModel |
DescribeModelPackageError | Errors returned by DescribeModelPackage |
DescribeMonitoringScheduleError | Errors returned by DescribeMonitoringSchedule |
DescribeNotebookInstanceError | Errors returned by DescribeNotebookInstance |
DescribeNotebookInstanceLifecycleConfigError | Errors returned by DescribeNotebookInstanceLifecycleConfig |
DescribeProcessingJobError | Errors returned by DescribeProcessingJob |
DescribeSubscribedWorkteamError | Errors returned by DescribeSubscribedWorkteam |
DescribeTrainingJobError | Errors returned by DescribeTrainingJob |
DescribeTransformJobError | Errors returned by DescribeTransformJob |
DescribeTrialComponentError | Errors returned by DescribeTrialComponent |
DescribeTrialError | Errors returned by DescribeTrial |
DescribeUserProfileError | Errors returned by DescribeUserProfile |
DescribeWorkforceError | Errors returned by DescribeWorkforce |
DescribeWorkteamError | Errors returned by DescribeWorkteam |
DisassociateTrialComponentError | Errors returned by DisassociateTrialComponent |
GetSearchSuggestionsError | Errors returned by GetSearchSuggestions |
ListAlgorithmsError | Errors returned by ListAlgorithms |
ListAppsError | Errors returned by ListApps |
ListAutoMLJobsError | Errors returned by ListAutoMLJobs |
ListCandidatesForAutoMLJobError | Errors returned by ListCandidatesForAutoMLJob |
ListCodeRepositoriesError | Errors returned by ListCodeRepositories |
ListCompilationJobsError | Errors returned by ListCompilationJobs |
ListDomainsError | Errors returned by ListDomains |
ListEndpointConfigsError | Errors returned by ListEndpointConfigs |
ListEndpointsError | Errors returned by ListEndpoints |
ListExperimentsError | Errors returned by ListExperiments |
ListFlowDefinitionsError | Errors returned by ListFlowDefinitions |
ListHumanTaskUisError | Errors returned by ListHumanTaskUis |
ListHyperParameterTuningJobsError | Errors returned by ListHyperParameterTuningJobs |
ListLabelingJobsError | Errors returned by ListLabelingJobs |
ListLabelingJobsForWorkteamError | Errors returned by ListLabelingJobsForWorkteam |
ListModelPackagesError | Errors returned by ListModelPackages |
ListModelsError | Errors returned by ListModels |
ListMonitoringExecutionsError | Errors returned by ListMonitoringExecutions |
ListMonitoringSchedulesError | Errors returned by ListMonitoringSchedules |
ListNotebookInstanceLifecycleConfigsError | Errors returned by ListNotebookInstanceLifecycleConfigs |
ListNotebookInstancesError | Errors returned by ListNotebookInstances |
ListProcessingJobsError | Errors returned by ListProcessingJobs |
ListSubscribedWorkteamsError | Errors returned by ListSubscribedWorkteams |
ListTagsError | Errors returned by ListTags |
ListTrainingJobsError | Errors returned by ListTrainingJobs |
ListTrainingJobsForHyperParameterTuningJobError | Errors returned by ListTrainingJobsForHyperParameterTuningJob |
ListTransformJobsError | Errors returned by ListTransformJobs |
ListTrialComponentsError | Errors returned by ListTrialComponents |
ListTrialsError | Errors returned by ListTrials |
ListUserProfilesError | Errors returned by ListUserProfiles |
ListWorkteamsError | Errors returned by ListWorkteams |
RenderUiTemplateError | Errors returned by RenderUiTemplate |
SearchError | Errors returned by Search |
StartMonitoringScheduleError | Errors returned by StartMonitoringSchedule |
StartNotebookInstanceError | Errors returned by StartNotebookInstance |
StopAutoMLJobError | Errors returned by StopAutoMLJob |
StopCompilationJobError | Errors returned by StopCompilationJob |
StopHyperParameterTuningJobError | Errors returned by StopHyperParameterTuningJob |
StopLabelingJobError | Errors returned by StopLabelingJob |
StopMonitoringScheduleError | Errors returned by StopMonitoringSchedule |
StopNotebookInstanceError | Errors returned by StopNotebookInstance |
StopProcessingJobError | Errors returned by StopProcessingJob |
StopTrainingJobError | Errors returned by StopTrainingJob |
StopTransformJobError | Errors returned by StopTransformJob |
UpdateCodeRepositoryError | Errors returned by UpdateCodeRepository |
UpdateDomainError | Errors returned by UpdateDomain |
UpdateEndpointError | Errors returned by UpdateEndpoint |
UpdateEndpointWeightsAndCapacitiesError | Errors returned by UpdateEndpointWeightsAndCapacities |
UpdateExperimentError | Errors returned by UpdateExperiment |
UpdateMonitoringScheduleError | Errors returned by UpdateMonitoringSchedule |
UpdateNotebookInstanceError | Errors returned by UpdateNotebookInstance |
UpdateNotebookInstanceLifecycleConfigError | Errors returned by UpdateNotebookInstanceLifecycleConfig |
UpdateTrialComponentError | Errors returned by UpdateTrialComponent |
UpdateTrialError | Errors returned by UpdateTrial |
UpdateUserProfileError | Errors returned by UpdateUserProfile |
UpdateWorkforceError | Errors returned by UpdateWorkforce |
UpdateWorkteamError | Errors returned by UpdateWorkteam |
Traits
SageMaker | Trait representing the capabilities of the SageMaker API. SageMaker clients implement this trait. |