Expand description
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§
- Action
Source A structure describing the source of an action.
- Action
Summary 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.
- AddAssociation
Request - AddAssociation
Response - AddTags
Input - AddTags
Output - Agent
Version Edge Manager agent version.
- Alarm
This API is not supported.
- Algorithm
Specification 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.
- Algorithm
Status Details Specifies the validation and image scan statuses of the algorithm.
- Algorithm
Status Item Represents the overall status of an algorithm.
- Algorithm
Summary Provides summary information about an algorithm.
- Algorithm
Validation Profile 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.
- Algorithm
Validation Specification Specifies configurations for one or more training jobs that Amazon SageMaker runs to test the algorithm.
- Annotation
Consolidation Config Configures how labels are consolidated across human workers and processes output data.
- AppDetails
Details about an Amazon SageMaker app.
- AppImage
Config Details The configuration for running a SageMaker image as a KernelGateway app.
- AppSpecification
Configuration to run a processing job in a specified container image.
- Artifact
Source A structure describing the source of an artifact.
- Artifact
Source Type The ID and ID type of an artifact source.
- Artifact
Summary 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.
- Associate
Trial Component Request - Associate
Trial Component Response - Association
Summary 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.
- Athena
Dataset Definition Configuration for Athena Dataset Definition input.
- AutoML
Candidate An Autopilot job returns recommendations, or candidates. Each candidate has futher details about the steps involved and the status.
- AutoML
Candidate Step Information about the steps for a candidate and what step it is working on.
- AutoML
Channel A channel is a named input source that training algorithms can consume. For more information, see .
- AutoML
Container Definition A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see .
- AutoML
Data Source The data source for the Autopilot job.
- AutoML
JobArtifacts The artifacts that are generated during an AutoML job.
- AutoML
JobCompletion Criteria How long a job is allowed to run, or how many candidates a job is allowed to generate.
- AutoML
JobConfig A collection of settings used for an AutoML job.
- AutoML
JobObjective Specifies a metric to minimize or maximize as the objective of a job.
- AutoML
JobSummary Provides a summary about an AutoML job.
- AutoML
Output Data Config The output data configuration.
- AutoML
Partial Failure Reason The reason for a partial failure of an AutoML job.
- AutoML
S3Data Source The Amazon S3 data source.
- AutoML
Security Config Security options.
- Auto
Rollback Config Currently, the
AutoRollbackConfigAPI is not supported.- Bias
Contains bias metrics for a model.
- Blue
Green Update Policy Currently, the
BlueGreenUpdatePolicyAPI is not supported.- Cache
HitResult Details on the cache hit of a pipeline execution step.
- Callback
Step Metadata Metadata about a callback step.
- Candidate
Artifact Locations The location of artifacts for an AutoML candidate job.
- Candidate
Properties The properties of an AutoML candidate job.
- Capacity
Size Currently, the
CapacitySizeAPI is not supported.- Capture
Content Type Header - Capture
Option - Categorical
Parameter Range A list of categorical hyperparameters to tune.
- Categorical
Parameter Range Specification Defines the possible values for a categorical hyperparameter.
- Channel
A channel is a named input source that training algorithms can consume.
- Channel
Specification Defines a named input source, called a channel, to be used by an algorithm.
- Checkpoint
Config Contains information about the output location for managed spot training checkpoint data.
- Code
Repository Summary Specifies summary information about a Git repository.
- Cognito
Config 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.
- Cognito
Member Definition Identifies a Amazon Cognito user group. A user group can be used in on or more work teams.
- Collection
Configuration Configuration information for the Debugger output tensor collections.
- Compilation
JobSummary A summary of a model compilation job.
- Condition
Step Metadata Metadata for a Condition step.
- Container
Definition Describes the container, as part of model definition.
- Context
Source A structure describing the source of a context.
- Context
Summary Lists a summary of the properties of a context. A context provides a logical grouping of other entities.
- Continuous
Parameter Range A list of continuous hyperparameters to tune.
- Continuous
Parameter Range Specification Defines the possible values for a continuous hyperparameter.
- Create
Action Request - Create
Action Response - Create
Algorithm Input - Create
Algorithm Output - Create
AppImage Config Request - Create
AppImage Config Response - Create
AppRequest - Create
AppResponse - Create
Artifact Request - Create
Artifact Response - Create
AutoML JobRequest - Create
AutoML JobResponse - Create
Code Repository Input - Create
Code Repository Output - Create
Compilation JobRequest - Create
Compilation JobResponse - Create
Context Request - Create
Context Response - Create
Data Quality JobDefinition Request - Create
Data Quality JobDefinition Response - Create
Device Fleet Request - Create
Domain Request - Create
Domain Response - Create
Edge Packaging JobRequest - Create
Endpoint Config Input - Create
Endpoint Config Output - Create
Endpoint Input - Create
Endpoint Output - Create
Experiment Request - Create
Experiment Response - Create
Feature Group Request - Create
Feature Group Response - Create
Flow Definition Request - Create
Flow Definition Response - Create
Human Task UiRequest - Create
Human Task UiResponse - Create
Hyper Parameter Tuning JobRequest - Create
Hyper Parameter Tuning JobResponse - Create
Image Request - Create
Image Response - Create
Image Version Request - Create
Image Version Response - Create
Labeling JobRequest - Create
Labeling JobResponse - Create
Model Bias JobDefinition Request - Create
Model Bias JobDefinition Response - Create
Model Explainability JobDefinition Request - Create
Model Explainability JobDefinition Response - Create
Model Input - Create
Model Output - Create
Model Package Group Input - Create
Model Package Group Output - Create
Model Package Input - Create
Model Package Output - Create
Model Quality JobDefinition Request - Create
Model Quality JobDefinition Response - Create
Monitoring Schedule Request - Create
Monitoring Schedule Response - Create
Notebook Instance Input - Create
Notebook Instance Lifecycle Config Input - Create
Notebook Instance Lifecycle Config Output - Create
Notebook Instance Output - Create
Pipeline Request - Create
Pipeline Response - Create
Presigned Domain UrlRequest - Create
Presigned Domain UrlResponse - Create
Presigned Notebook Instance UrlInput - Create
Presigned Notebook Instance UrlOutput - Create
Processing JobRequest - Create
Processing JobResponse - Create
Project Input - Create
Project Output - Create
Training JobRequest - Create
Training JobResponse - Create
Transform JobRequest - Create
Transform JobResponse - Create
Trial Component Request - Create
Trial Component Response - Create
Trial Request - Create
Trial Response - Create
User Profile Request - Create
User Profile Response - Create
Workforce Request - Create
Workforce Response - Create
Workteam Request - Create
Workteam Response - Custom
Image A custom SageMaker image. For more information, see Bring your own SageMaker image.
- Data
Capture Config - Data
Capture Config Summary - Data
Catalog Config The meta data of the Glue table which serves as data catalog for the
OfflineStore.- Data
Processing 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.
- Data
Quality AppSpecification Information about the container that a data quality monitoring job runs.
- Data
Quality Baseline Config 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.
- Data
Quality JobInput The input for the data quality monitoring job. Currently endpoints are supported for input.
- Data
Source Describes the location of the channel data.
- Dataset
Definition Configuration for Dataset Definition inputs. The Dataset Definition input must specify exactly one of either
AthenaDatasetDefinitionorRedshiftDatasetDefinitiontypes.- Debug
Hook Config Configuration information for the Debugger hook parameters, metric and tensor collections, and storage paths. To learn more about how to configure the
DebugHookConfigparameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.- Debug
Rule Configuration Configuration information for SageMaker Debugger rules for debugging. To learn more about how to configure the
DebugRuleConfigurationparameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job.- Debug
Rule Evaluation Status Information about the status of the rule evaluation.
- Delete
Action Request - Delete
Action Response - Delete
Algorithm Input - Delete
AppImage Config Request - Delete
AppRequest - Delete
Artifact Request - Delete
Artifact Response - Delete
Association Request - Delete
Association Response - Delete
Code Repository Input - Delete
Context Request - Delete
Context Response - Delete
Data Quality JobDefinition Request - Delete
Device Fleet Request - Delete
Domain Request - Delete
Endpoint Config Input - Delete
Endpoint Input - Delete
Experiment Request - Delete
Experiment Response - Delete
Feature Group Request - Delete
Flow Definition Request - Delete
Flow Definition Response - Delete
Human Task UiRequest - Delete
Human Task UiResponse - Delete
Image Request - Delete
Image Response - Delete
Image Version Request - Delete
Image Version Response - Delete
Model Bias JobDefinition Request - Delete
Model Explainability JobDefinition Request - Delete
Model Input - Delete
Model Package Group Input - Delete
Model Package Group Policy Input - Delete
Model Package Input - Delete
Model Quality JobDefinition Request - Delete
Monitoring Schedule Request - Delete
Notebook Instance Input - Delete
Notebook Instance Lifecycle Config Input - Delete
Pipeline Request - Delete
Pipeline Response - Delete
Project Input - Delete
Tags Input - Delete
Tags Output - Delete
Trial Component Request - Delete
Trial Component Response - Delete
Trial Request - Delete
Trial Response - Delete
User Profile Request - Delete
Workforce Request - Delete
Workforce Response - Delete
Workteam Request - Delete
Workteam Response - Deployed
Image Gets the Amazon EC2 Container Registry path of the docker image of the model that is hosted in this ProductionVariant.
If you used the
registry/repository[:tag]form to specify the image path of the primary container when you created the model hosted in thisProductionVariant, the path resolves to a path of the formregistry/repository[@digest]. A digest is a hash value that identifies a specific version of an image. For information about Amazon ECR paths, see Pulling an Image in the Amazon ECR User Guide.- Deployment
Config Currently, the
DeploymentConfigAPI is not supported.- Deregister
Devices Request - Describe
Action Request - Describe
Action Response - Describe
Algorithm Input - Describe
Algorithm Output - Describe
AppImage Config Request - Describe
AppImage Config Response - Describe
AppRequest - Describe
AppResponse - Describe
Artifact Request - Describe
Artifact Response - Describe
AutoML JobRequest - Describe
AutoML JobResponse - Describe
Code Repository Input - Describe
Code Repository Output - Describe
Compilation JobRequest - Describe
Compilation JobResponse - Describe
Context Request - Describe
Context Response - Describe
Data Quality JobDefinition Request - Describe
Data Quality JobDefinition Response - Describe
Device Fleet Request - Describe
Device Fleet Response - Describe
Device Request - Describe
Device Response - Describe
Domain Request - Describe
Domain Response - Describe
Edge Packaging JobRequest - Describe
Edge Packaging JobResponse - Describe
Endpoint Config Input - Describe
Endpoint Config Output - Describe
Endpoint Input - Describe
Endpoint Output - Describe
Experiment Request - Describe
Experiment Response - Describe
Feature Group Request - Describe
Feature Group Response - Describe
Flow Definition Request - Describe
Flow Definition Response - Describe
Human Task UiRequest - Describe
Human Task UiResponse - Describe
Hyper Parameter Tuning JobRequest - Describe
Hyper Parameter Tuning JobResponse - Describe
Image Request - Describe
Image Response - Describe
Image Version Request - Describe
Image Version Response - Describe
Labeling JobRequest - Describe
Labeling JobResponse - Describe
Model Bias JobDefinition Request - Describe
Model Bias JobDefinition Response - Describe
Model Explainability JobDefinition Request - Describe
Model Explainability JobDefinition Response - Describe
Model Input - Describe
Model Output - Describe
Model Package Group Input - Describe
Model Package Group Output - Describe
Model Package Input - Describe
Model Package Output - Describe
Model Quality JobDefinition Request - Describe
Model Quality JobDefinition Response - Describe
Monitoring Schedule Request - Describe
Monitoring Schedule Response - Describe
Notebook Instance Input - Describe
Notebook Instance Lifecycle Config Input - Describe
Notebook Instance Lifecycle Config Output - Describe
Notebook Instance Output - Describe
Pipeline Definition ForExecution Request - Describe
Pipeline Definition ForExecution Response - Describe
Pipeline Execution Request - Describe
Pipeline Execution Response - Describe
Pipeline Request - Describe
Pipeline Response - Describe
Processing JobRequest - Describe
Processing JobResponse - Describe
Project Input - Describe
Project Output - Describe
Subscribed Workteam Request - Describe
Subscribed Workteam Response - Describe
Training JobRequest - Describe
Training JobResponse - Describe
Transform JobRequest - Describe
Transform JobResponse - Describe
Trial Component Request - Describe
Trial Component Response - Describe
Trial Request - Describe
Trial Response - Describe
User Profile Request - Describe
User Profile Response - Describe
Workforce Request - Describe
Workforce Response - Describe
Workteam Request - Describe
Workteam Response - Desired
Weight AndCapacity Specifies weight and capacity values for a production variant.
- Device
Information of a particular device.
- Device
Fleet Summary Summary of the device fleet.
- Device
Stats Status of devices.
- Device
Summary Summary of the device.
- Disable
Sagemaker Servicecatalog Portfolio Input - Disable
Sagemaker Servicecatalog Portfolio Output - Disassociate
Trial Component Request - Disassociate
Trial Component Response - Domain
Details The domain's details.
- Edge
Model The model on the edge device.
- Edge
Model Stat Status of edge devices with this model.
- Edge
Model Summary Summary of model on edge device.
- Edge
Output Config The output configuration.
- Edge
Packaging JobSummary Summary of edge packaging job.
- Edge
Preset Deployment Output The output of a SageMaker Edge Manager deployable resource.
- Enable
Sagemaker Servicecatalog Portfolio Input - Enable
Sagemaker Servicecatalog Portfolio Output - Endpoint
A hosted endpoint for real-time inference.
- Endpoint
Config Summary Provides summary information for an endpoint configuration.
- Endpoint
Input Input object for the endpoint
- Endpoint
Summary Provides summary information for an endpoint.
- Experiment
The properties of an experiment as returned by the Search API.
- Experiment
Config Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:
- Experiment
Source The source of the experiment.
- Experiment
Summary 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.
- Feature
Definition A list of features. You must include
FeatureNameandFeatureType. Valid featureFeatureTypes areIntegral,FractionalandString.- Feature
Group 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.
- Feature
Group Summary The name, Arn,
CreationTime,FeatureGroupvalues,LastUpdatedTimeandEnableOnlineStoragestatus of aFeatureGroup.- File
System Config The Amazon Elastic File System (EFS) storage configuration for a SageMaker image.
- File
System Data Source 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
Value, but not anOperator, Amazon SageMaker uses the equals operator.In search, there are several property types:
- Metrics
-
To define a metric filter, enter a value using the form
"Metrics.<name>", where<name>is a metric name. For example, the following filter searches for training jobs with an"accuracy"metric greater than"0.9":{"Name": "Metrics.accuracy","Operator": "GreaterThan","Value": "0.9"} - HyperParameters
-
To define a hyperparameter filter, enter a value with the form
"HyperParameters.<name>". Decimal hyperparameter values are treated as a decimal in a comparison if the specifiedValueis also a decimal value. If the specifiedValueis an integer, the decimal hyperparameter values are treated as integers. For example, the following filter is satisfied by training jobs with a"learningrate"hyperparameter that is less than"0.5":{"Name": "HyperParameters.learningrate","Operator": "LessThan","Value": "0.5"} - Tags
-
To define a tag filter, enter a value with the form
Tags.<key>.
- Final
AutoML JobObjective Metric The best candidate result from an AutoML training job.
- Final
Hyper Parameter Tuning JobObjective Metric 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
HyperParameterTuningJobObjectiveparameter of HyperParameterTuningJobConfig.- Flow
Definition Output Config Contains information about where human output will be stored.
- Flow
Definition Summary Contains summary information about the flow definition.
- GetDevice
Fleet Report Request - GetDevice
Fleet Report Response - GetModel
Package Group Policy Input - GetModel
Package Group Policy Output - GetSagemaker
Servicecatalog Portfolio Status Input - GetSagemaker
Servicecatalog Portfolio Status Output - GetSearch
Suggestions Request - GetSearch
Suggestions Response - GitConfig
Specifies configuration details for a Git repository in your AWS account.
- GitConfig
ForUpdate Specifies configuration details for a Git repository when the repository is updated.
- Human
Loop Activation Conditions Config Defines under what conditions SageMaker creates a human loop. Used within . See for the required format of activation conditions.
- Human
Loop Activation Config Provides information about how and under what conditions SageMaker creates a human loop. If
HumanLoopActivationConfigis not given, then all requests go to humans.- Human
Loop Config Describes the work to be performed by human workers.
- Human
Loop Request Source Container for configuring the source of human task requests.
- Human
Task Config Information required for human workers to complete a labeling task.
- Human
Task UiSummary Container for human task user interface information.
- Hyper
Parameter Algorithm Specification Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.
- Hyper
Parameter Specification Defines a hyperparameter to be used by an algorithm.
- Hyper
Parameter Training JobDefinition Defines the training jobs launched by a hyperparameter tuning job.
- Hyper
Parameter Training JobSummary Specifies summary information about a training job.
- Hyper
Parameter Tuning JobConfig Configures a hyperparameter tuning job.
- Hyper
Parameter Tuning JobObjective 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
Typeparameter.- Hyper
Parameter Tuning JobSummary Provides summary information about a hyperparameter tuning job.
- Hyper
Parameter Tuning JobWarm Start Config 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.
- 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.- Image
Config Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
- Image
Version A version of a SageMaker
Image. A version represents an existing container image.- Inference
Execution Config Specifies details about how containers in a multi-container endpoint are run.
- Inference
Specification Defines how to perform inference generation after a training job is run.
- Input
Config 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.
- Integer
Parameter Range For a hyperparameter of the integer type, specifies the range that a hyperparameter tuning job searches.
- Integer
Parameter Range Specification Defines the possible values for an integer hyperparameter.
- Jupyter
Server AppSettings The JupyterServer app settings.
- Kernel
Gateway AppSettings The KernelGateway app settings.
- Kernel
Gateway Image Config The configuration for the file system and kernels in a SageMaker image running as a KernelGateway app.
- Kernel
Spec The specification of a Jupyter kernel.
- Label
Counters Provides a breakdown of the number of objects labeled.
- Label
Counters ForWorkteam Provides counts for human-labeled tasks in the labeling job.
- Labeling
JobAlgorithms Config Provides configuration information for auto-labeling of your data objects. A
LabelingJobAlgorithmsConfigobject must be supplied in order to use auto-labeling.- Labeling
JobData Attributes Attributes of the data specified by the customer. Use these to describe the data to be labeled.
- Labeling
JobData Source Provides information about the location of input data.
You must specify at least one of the following:
S3DataSourceorSnsDataSource.Use
SnsDataSourceto specify an SNS input topic for a streaming labeling job. If you do not specify and SNS input topic ARN, Ground Truth will create a one-time labeling job.Use
S3DataSourceto specify an input manifest file for both streaming and one-time labeling jobs. Adding anS3DataSourceis optional if you useSnsDataSourceto create a streaming labeling job.- Labeling
JobFor Workteam Summary Provides summary information for a work team.
- Labeling
JobInput Config Input configuration information for a labeling job.
- Labeling
JobOutput Specifies the location of the output produced by the labeling job.
- Labeling
JobOutput Config Output configuration information for a labeling job.
- Labeling
JobResource Config Configure encryption on the storage volume attached to the ML compute instance used to run automated data labeling model training and inference.
- Labeling
JobS3 Data Source The Amazon S3 location of the input data objects.
- Labeling
JobSns Data Source An Amazon SNS data source used for streaming labeling jobs.
- Labeling
JobStopping Conditions 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.
- Labeling
JobSummary Provides summary information about a labeling job.
- List
Actions Request - List
Actions Response - List
Algorithms Input - List
Algorithms Output - List
AppImage Configs Request - List
AppImage Configs Response - List
Apps Request - List
Apps Response - List
Artifacts Request - List
Artifacts Response - List
Associations Request - List
Associations Response - List
AutoML Jobs Request - List
AutoML Jobs Response - List
Candidates ForAutoML JobRequest - List
Candidates ForAutoML JobResponse - List
Code Repositories Input - List
Code Repositories Output - List
Compilation Jobs Request - List
Compilation Jobs Response - List
Contexts Request - List
Contexts Response - List
Data Quality JobDefinitions Request - List
Data Quality JobDefinitions Response - List
Device Fleets Request - List
Device Fleets Response - List
Devices Request - List
Devices Response - List
Domains Request - List
Domains Response - List
Edge Packaging Jobs Request - List
Edge Packaging Jobs Response - List
Endpoint Configs Input - List
Endpoint Configs Output - List
Endpoints Input - List
Endpoints Output - List
Experiments Request - List
Experiments Response - List
Feature Groups Request - List
Feature Groups Response - List
Flow Definitions Request - List
Flow Definitions Response - List
Human Task UisRequest - List
Human Task UisResponse - List
Hyper Parameter Tuning Jobs Request - List
Hyper Parameter Tuning Jobs Response - List
Image Versions Request - List
Image Versions Response - List
Images Request - List
Images Response - List
Labeling Jobs ForWorkteam Request - List
Labeling Jobs ForWorkteam Response - List
Labeling Jobs Request - List
Labeling Jobs Response - List
Model Bias JobDefinitions Request - List
Model Bias JobDefinitions Response - List
Model Explainability JobDefinitions Request - List
Model Explainability JobDefinitions Response - List
Model Package Groups Input - List
Model Package Groups Output - List
Model Packages Input - List
Model Packages Output - List
Model Quality JobDefinitions Request - List
Model Quality JobDefinitions Response - List
Models Input - List
Models Output - List
Monitoring Executions Request - List
Monitoring Executions Response - List
Monitoring Schedules Request - List
Monitoring Schedules Response - List
Notebook Instance Lifecycle Configs Input - List
Notebook Instance Lifecycle Configs Output - List
Notebook Instances Input - List
Notebook Instances Output - List
Pipeline Execution Steps Request - List
Pipeline Execution Steps Response - List
Pipeline Executions Request - List
Pipeline Executions Response - List
Pipeline Parameters ForExecution Request - List
Pipeline Parameters ForExecution Response - List
Pipelines Request - List
Pipelines Response - List
Processing Jobs Request - List
Processing Jobs Response - List
Projects Input - List
Projects Output - List
Subscribed Workteams Request - List
Subscribed Workteams Response - List
Tags Input - List
Tags Output - List
Training Jobs ForHyper Parameter Tuning JobRequest - List
Training Jobs ForHyper Parameter Tuning JobResponse - List
Training Jobs Request - List
Training Jobs Response - List
Transform Jobs Request - List
Transform Jobs Response - List
Trial Components Request - List
Trial Components Response - List
Trials Request - List
Trials Response - List
User Profiles Request - List
User Profiles Response - List
Workforces Request - List
Workforces Response - List
Workteams Request - List
Workteams Response - Member
Definition Defines an Amazon Cognito or your own OIDC IdP user group that is part of a work team.
- Metadata
Properties Metadata properties of the tracking entity, trial, or trial component.
- Metric
Data The name, value, and date and time of a metric that was emitted to Amazon CloudWatch.
- Metric
Definition Specifies a metric that the training algorithm writes to
stderrorstdout. 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.- Metrics
Source - Model
Artifacts 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 describes how to compute inferences, and other metadata.
- Model
Bias AppSpecification Docker container image configuration object for the model bias job.
- Model
Bias Baseline Config The configuration for a baseline model bias job.
- Model
Bias JobInput Inputs for the model bias job.
- Model
Client Config Configures the timeout and maximum number of retries for processing a transform job invocation.
- Model
Data Quality Data quality constraints and statistics for a model.
- Model
Deploy Config Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
- Model
Deploy Result Provides information about the endpoint of the model deployment.
- Model
Digests Provides information to verify the integrity of stored model artifacts.
- Model
Explainability AppSpecification Docker container image configuration object for the model explainability job.
- Model
Explainability Baseline Config The configuration for a baseline model explainability job.
- Model
Explainability JobInput Inputs for the model explainability job.
- Model
Metrics Contains metrics captured from a model.
- Model
Package A versioned model that can be deployed for SageMaker inference.
- Model
Package Container Definition Describes the Docker container for the model package.
- Model
Package Group A group of versioned models in the model registry.
- Model
Package Group Summary Summary information about a model group.
- Model
Package Status Details Specifies the validation and image scan statuses of the model package.
- Model
Package Status Item Represents the overall status of a model package.
- Model
Package Summary Provides summary information about a model package.
- Model
Package Validation Profile 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.
- Model
Package Validation Specification Specifies batch transform jobs that Amazon SageMaker runs to validate your model package.
- Model
Quality Model quality statistics and constraints.
- Model
Quality AppSpecification Container image configuration object for the monitoring job.
- Model
Quality Baseline Config 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.
- Model
Quality JobInput The input for the model quality monitoring job. Currently endponts are supported for input for model quality monitoring jobs.
- Model
Step Metadata Metadata for Model steps.
- Model
Summary Provides summary information about a model.
- Monitoring
AppSpecification Container image configuration object for the monitoring job.
- Monitoring
Baseline Config 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.
- Monitoring
Cluster Config Configuration for the cluster used to run model monitoring jobs.
- Monitoring
Constraints Resource The constraints resource for a monitoring job.
- Monitoring
Execution Summary Summary of information about the last monitoring job to run.
- Monitoring
Ground Truth S3Input The ground truth labels for the dataset used for the monitoring job.
- Monitoring
Input The inputs for a monitoring job.
- Monitoring
JobDefinition Defines the monitoring job.
- Monitoring
JobDefinition Summary Summary information about a monitoring job.
- Monitoring
Network Config The networking configuration for the monitoring job.
- Monitoring
Output The output object for a monitoring job.
- Monitoring
Output Config The output configuration for monitoring jobs.
- Monitoring
Resources Identifies the resources to deploy for a monitoring job.
- Monitoring
S3Output Information about where and how you want to store the results of a monitoring job.
- Monitoring
Schedule A schedule for a model monitoring job. For information about model monitor, see Amazon SageMaker Model Monitor.
- Monitoring
Schedule Config Configures the monitoring schedule and defines the monitoring job.
- Monitoring
Schedule Summary Summarizes the monitoring schedule.
- Monitoring
Statistics Resource The statistics resource for a monitoring job.
- Monitoring
Stopping Condition A time limit for how long the monitoring job is allowed to run before stopping.
- Multi
Model Config Specifies additional configuration for hosting multi-model endpoints.
- NeoVpc
Config - Nested
Filters 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
InputDataConfigproperty with a specific channel name andS3Uriprefix, define the following filters:-
'{Name:"InputDataConfig.ChannelName", "Operator":"Equals", "Value":"train"}', -
'{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri", "Operator":"Contains", "Value":"mybucket/catdata"}'
-
- Network
Config 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.
- Notebook
Instance Lifecycle Config Summary Provides a summary of a notebook instance lifecycle configuration.
- Notebook
Instance Lifecycle Hook Contains the notebook instance lifecycle configuration script.
Each lifecycle configuration script has a limit of 16384 characters.
The value of the
$PATHenvironment 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/NotebookInstancesin 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.
- Notebook
Instance Summary Provides summary information for an Amazon SageMaker notebook instance.
- Notification
Configuration Configures SNS notifications of available or expiring work items for work teams.
- Objective
Status Counters 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.
- Offline
Store Config The configuration of an
OfflineStore.Provide an
OfflineStoreConfigin a request toCreateFeatureGroupto create anOfflineStore.To encrypt an
OfflineStoreusing at rest data encryption, specify AWS Key Management Service (KMS) key ID, orKMSKeyId, inS3StorageConfig.- Offline
Store Status The status of
OfflineStore.- Oidc
Config Use this parameter to configure your OIDC Identity Provider (IdP).
- Oidc
Config ForResponse Your OIDC IdP workforce configuration.
- Oidc
Member Definition 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.- Online
Store Config Use this to specify the AWS Key Management Service (KMS) Key ID, or
KMSKeyId, for at rest data encryption. You can turnOnlineStoreon or off by specifying theEnableOnlineStoreflag at General Assembly; the default value isFalse.- Online
Store Security Config The security configuration for
OnlineStore.- Output
Config Contains information about the output location for the compiled model and the target device that the model runs on.
TargetDeviceandTargetPlatformare 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 theTargetDevicelist, useTargetPlatformto describe the platform of your edge device andCompilerOptionsif there are specific settings that are required or recommended to use for particular TargetPlatform.- Output
Data Config Provides information about how to store model training results (model artifacts).
- Output
Parameter An output parameter of a pipeline step.
- Parameter
Assigns a value to a named Pipeline parameter.
- Parameter
Range Defines the possible values for categorical, continuous, and integer hyperparameters to be used by an algorithm.
- Parameter
Ranges 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.
- Parent
Hyper Parameter Tuning Job 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.
- Pipeline
Execution An execution of a pipeline.
- Pipeline
Execution Step An execution of a step in a pipeline.
- Pipeline
Execution Step Metadata Metadata for a step execution.
- Pipeline
Execution Summary A pipeline execution summary.
- Pipeline
Experiment Config Specifies the names of the experiment and trial created by a pipeline.
- Pipeline
Summary A summary of a pipeline.
- Processing
Cluster Config Configuration for the cluster used to run a processing job.
- Processing
Feature Store Output Configuration for processing job outputs in Amazon SageMaker Feature Store.
- Processing
Input The inputs for a processing job. The processing input must specify exactly one of either
S3InputorDatasetDefinitiontypes.- Processing
Job An Amazon SageMaker processing job that is used to analyze data and evaluate models. For more information, see Process Data and Evaluate Models.
- Processing
JobStep Metadata Metadata for a processing job step.
- Processing
JobSummary Summary of information about a processing job.
- Processing
Output Describes the results of a processing job. The processing output must specify exactly one of either
S3OutputorFeatureStoreOutputtypes.- Processing
Output Config Configuration for uploading output from the processing container.
- Processing
Resources 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.
- Processing
S3Input Configuration for downloading input data from Amazon S3 into the processing container.
- Processing
S3Output Configuration for uploading output data to Amazon S3 from the processing container.
- Processing
Stopping Condition Configures conditions under which the processing job should be stopped, such as how long the processing job has been running. After the condition is met, the processing job is stopped.
- Production
Variant Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell Amazon SageMaker how to distribute traffic among the models by specifying variant weights.
- Production
Variant Core Dump Config Specifies configuration for a core dump from the model container when the process crashes.
- Production
Variant Summary Describes weight and capacities for a production variant associated with an endpoint. If you sent a request to the
UpdateEndpointWeightsAndCapacitiesAPI and the endpoint status isUpdating, you get different desired and current values.- Profiler
Config Configuration information for Debugger system monitoring, framework profiling, and storage paths.
- Profiler
Config ForUpdate Configuration information for updating the Debugger profile parameters, system and framework metrics configurations, and storage paths.
- Profiler
Rule Configuration Configuration information for profiling rules.
- Profiler
Rule Evaluation Status Information about the status of the rule evaluation.
- Project
Summary Information about a project.
- Property
Name Query Part of the
SuggestionQuerytype. Specifies a hint for retrieving property names that begin with the specified text.- Property
Name Suggestion A property name returned from a
GetSearchSuggestionscall that specifies a value in thePropertyNameQueryfield.- Provisioning
Parameter A key value pair used when you provision a project as a service catalog product. For information, see What is AWS Service Catalog.
- Public
Workforce Task Price Defines the amount of money paid to an Amazon Mechanical Turk worker for each task performed.
Use one of the following prices for bounding box tasks. Prices are in US dollars and should be based on the complexity of the task; the longer it takes in your initial testing, the more you should offer.
-
0.036
-
0.048
-
0.060
-
0.072
-
0.120
-
0.240
-
0.360
-
0.480
-
0.600
-
0.720
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for image classification, text classification, and custom tasks. Prices are in US dollars.
-
0.012
-
0.024
-
0.036
-
0.048
-
0.060
-
0.072
-
0.120
-
0.240
-
0.360
-
0.480
-
0.600
-
0.720
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for semantic segmentation tasks. Prices are in US dollars.
-
0.840
-
0.960
-
1.080
-
1.200
Use one of the following prices for Textract AnalyzeDocument Important Form Key Amazon Augmented AI review tasks. Prices are in US dollars.
-
2.400
-
2.280
-
2.160
-
2.040
-
1.920
-
1.800
-
1.680
-
1.560
-
1.440
-
1.320
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
Use one of the following prices for Rekognition DetectModerationLabels Amazon Augmented AI review tasks. Prices are in US dollars.
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
Use one of the following prices for Amazon Augmented AI custom human review tasks. Prices are in US dollars.
-
1.200
-
1.080
-
0.960
-
0.840
-
0.720
-
0.600
-
0.480
-
0.360
-
0.240
-
0.120
-
0.072
-
0.060
-
0.048
-
0.036
-
0.024
-
0.012
-
- PutModel
Package Group Policy Input - PutModel
Package Group Policy Output - Redshift
Dataset Definition Configuration for Redshift Dataset Definition input.
- Register
Devices Request - Register
Model Step Metadata Metadata for a register model job step.
- Render
UiTemplate Request - Render
UiTemplate Response - Renderable
Task Contains input values for a task.
- Rendering
Error A description of an error that occurred while rendering the template.
- Repository
Auth Config Specifies an authentication configuration for the private docker registry where your model image is hosted. Specify a value for this property only if you specified
Vpcas the value for theRepositoryAccessModefield of theImageConfigobject that you passed to a call to CreateModel and the private Docker registry where the model image is hosted requires authentication.- Resolved
Attributes The resolved attributes.
- Resource
Config Describes the resources, including ML compute instances and ML storage volumes, to use for model training.
- Resource
Limits Specifies the maximum number of training jobs and parallel training jobs that a hyperparameter tuning job can launch.
- Resource
Spec Specifies the ARN's of a SageMaker image and SageMaker image version, and the instance type that the version runs on.
- Retention
Policy The retention policy for data stored on an Amazon Elastic File System (EFS) volume.
- Retry
Strategy The retry strategy to use when a training job fails due to an
InternalServerError.RetryStrategyis specified as part of theCreateTrainingJobandCreateHyperParameterTuningJobrequests. You can add theStoppingConditionparameter to the request to limit the training time for the complete job.- S3Data
Source Describes the S3 data source.
- S3Storage
Config The Amazon Simple Storage (Amazon S3) location and and security configuration for
OfflineStore.- Sage
Maker Client - A client for the SageMaker API.
- Schedule
Config Configuration details about the monitoring schedule.
- Search
Expression 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
SearchExpressioncan contain up to twenty elements.A
SearchExpressioncontains the following components:-
A list of
Filterobjects. Each filter defines a simple Boolean expression comprised of a resource property name, Boolean operator, and value. -
A list of
NestedFilterobjects. Each nested filter defines a list of Boolean expressions using a list of resource properties. A nested filter is satisfied if a single object in the list satisfies all Boolean expressions. -
A list of
SearchExpressionobjects. A search expression object can be nested in a list of search expression objects. -
A Boolean operator:
AndorOr.
-
- Search
Record A single resource returned as part of the Search API response.
- Search
Request - Search
Response - Secondary
Status Transition 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.
- Send
Pipeline Execution Step Failure Request - Send
Pipeline Execution Step Failure Response - Send
Pipeline Execution Step Success Request - Send
Pipeline Execution Step Success Response - Service
Catalog Provisioned Product Details Details of a provisioned service catalog product. For information about service catalog, see What is AWS Service Catalog.
- Service
Catalog Provisioning Details Details that you specify to provision a service catalog product. For information about service catalog, see .What is AWS Service Catalog.
- Sharing
Settings Specifies options for sharing SageMaker Studio notebooks. These settings are specified as part of
DefaultUserSettingswhen theCreateDomainAPI is called, and as part ofUserSettingswhen theCreateUserProfileAPI is called. WhenSharingSettingsis not specified, notebook sharing isn't allowed.- Shuffle
Config A configuration for a shuffle option for input data in a channel. If you use
S3PrefixforS3DataType, the results of the S3 key prefix matches are shuffled. If you useManifestFile, the order of the S3 object references in theManifestFileis shuffled. If you useAugmentedManifestFile, the order of the JSON lines in theAugmentedManifestFileis shuffled. The shuffling order is determined using theSeedvalue.For Pipe input mode, when
ShuffleConfigis specified shuffling is done at the start of every epoch. With large datasets, this ensures that the order of the training data is different for each epoch, and it helps reduce bias and possible overfitting. In a multi-node training job whenShuffleConfigis combined withS3DataDistributionTypeofShardedByS3Key, the data is shuffled across nodes so that the content sent to a particular node on the first epoch might be sent to a different node on the second epoch.- Source
Algorithm 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.
- Source
Algorithm Specification A list of algorithms that were used to create a model package.
- Source
IpConfig 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.
- Start
Monitoring Schedule Request - Start
Notebook Instance Input - Start
Pipeline Execution Request - Start
Pipeline Execution Response - Stop
AutoML JobRequest - Stop
Compilation JobRequest - Stop
Edge Packaging JobRequest - Stop
Hyper Parameter Tuning JobRequest - Stop
Labeling JobRequest - Stop
Monitoring Schedule Request - Stop
Notebook Instance Input - Stop
Pipeline Execution Request - Stop
Pipeline Execution Response - Stop
Processing JobRequest - Stop
Training JobRequest - Stop
Transform JobRequest - Stopping
Condition Specifies a limit to how long a model training job, model compilation job, or hyperparameter tuning job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker ends the training or compilation job. Use this API to cap model training costs.
To stop a job, Amazon SageMaker sends the algorithm the
SIGTERMsignal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.The training algorithms provided by Amazon SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with
CreateModel.The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
- Subscribed
Workteam Describes a work team of a vendor that does the a labelling job.
- Suggestion
Query Specified in the GetSearchSuggestions request. Limits the property names that are included in the response.
- Tag
A tag object that consists of a key and an optional value, used to manage metadata for Amazon SageMaker AWS resources.
You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to Amazon SageMaker resources, see AddTags.
For more information on adding metadata to your AWS resources with tagging, see Tagging AWS resources. For advice on best practices for managing AWS resources with tagging, see Tagging Best Practices: Implement an Effective AWS Resource Tagging Strategy.
- Target
Platform 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.- Tensor
Board AppSettings The TensorBoard app settings.
- Tensor
Board Output Config Configuration of storage locations for the Debugger TensorBoard output data.
- Traffic
Routing Config Currently, the
TrafficRoutingConfigAPI is not supported.- Training
Job Contains information about a training job.
- Training
JobDefinition Defines the input needed to run a training job using the algorithm.
- Training
JobStatus Counters The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
- Training
JobStep Metadata Metadata for a training job step.
- Training
JobSummary Provides summary information about a training job.
- Training
Specification Defines how the algorithm is used for a training job.
- Transform
Data Source Describes the location of the channel data.
- Transform
Input Describes the input source of a transform job and the way the transform job consumes it.
- Transform
Job A batch transform job. For information about SageMaker batch transform, see Use Batch Transform.
- Transform
JobDefinition Defines the input needed to run a transform job using the inference specification specified in the algorithm.
- Transform
JobStep Metadata Metadata for a transform job step.
- Transform
JobSummary Provides a summary of a transform job. Multiple
TransformJobSummaryobjects are returned as a list after in response to a ListTransformJobs call.- Transform
Output Describes the results of a transform job.
- Transform
Resources Describes the resources, including ML instance types and ML instance count, to use for transform job.
- Transform
S3Data Source Describes the S3 data source.
- Trial
The properties of a trial as returned by the Search API.
- Trial
Component The properties of a trial component as returned by the Search API.
- Trial
Component Artifact Represents an input or output artifact of a trial component. You specify
TrialComponentArtifactas part of theInputArtifactsandOutputArtifactsparameters in the CreateTrialComponent request.Examples of input artifacts are datasets, algorithms, hyperparameters, source code, and instance types. Examples of output artifacts are metrics, snapshots, logs, and images.
- Trial
Component Metric Summary A summary of the metrics of a trial component.
- Trial
Component Parameter Value The value of a hyperparameter. Only one of
NumberValueorStringValuecan be specified.This object is specified in the CreateTrialComponent request.
- Trial
Component Simple Summary A short summary of a trial component.
- Trial
Component Source The Amazon Resource Name (ARN) and job type of the source of a trial component.
- Trial
Component Source Detail Detailed information about the source of a trial component. Either
ProcessingJoborTrainingJobis returned.- Trial
Component Status The status of the trial component.
- Trial
Component Summary A summary of the properties of a trial component. To get all the properties, call the DescribeTrialComponent API and provide the
TrialComponentName.- Trial
Source The source of the trial.
- Trial
Summary A summary of the properties of a trial. To get the complete set of properties, call the DescribeTrial API and provide the
TrialName.- Tuning
JobCompletion Criteria 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.
- UiTemplate
Info Container for user interface template information.
- Update
Action Request - Update
Action Response - Update
AppImage Config Request - Update
AppImage Config Response - Update
Artifact Request - Update
Artifact Response - Update
Code Repository Input - Update
Code Repository Output - Update
Context Request - Update
Context Response - Update
Device Fleet Request - Update
Devices Request - Update
Domain Request - Update
Domain Response - Update
Endpoint Input - Update
Endpoint Output - Update
Endpoint Weights AndCapacities Input - Update
Endpoint Weights AndCapacities Output - Update
Experiment Request - Update
Experiment Response - Update
Image Request - Update
Image Response - Update
Model Package Input - Update
Model Package Output - Update
Monitoring Schedule Request - Update
Monitoring Schedule Response - Update
Notebook Instance Input - Update
Notebook Instance Lifecycle Config Input - Update
Notebook Instance Lifecycle Config Output - Update
Notebook Instance Output - Update
Pipeline Execution Request - Update
Pipeline Execution Response - Update
Pipeline Request - Update
Pipeline Response - Update
Training JobRequest - Update
Training JobResponse - Update
Trial Component Request - Update
Trial Component Response - Update
Trial Request - Update
Trial Response - Update
User Profile Request - Update
User Profile Response - Update
Workforce Request - Update
Workforce Response - Update
Workteam Request - Update
Workteam Response - User
Context Information about the user who created or modified an experiment, trial, or trial component.
- User
Profile Details The user profile details.
- User
Settings A collection of settings that apply to users of Amazon SageMaker Studio. These settings are specified when the
CreateUserProfileAPI is called, and asDefaultUserSettingswhen theCreateDomainAPI is called.SecurityGroupsis aggregated when specified in both calls. For all other settings inUserSettings, the values specified inCreateUserProfiletake precedence over those specified inCreateDomain.- Variant
Property Specifies a production variant property type for an Endpoint.
If you are updating an endpoint with the UpdateEndpointInput$RetainAllVariantProperties option set to
true, theVariantPropertyobjects listed in UpdateEndpointInput$ExcludeRetainedVariantProperties override the existing variant properties of the 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§
- AddAssociation
Error - Errors returned by AddAssociation
- AddTags
Error - Errors returned by AddTags
- Associate
Trial Component Error - Errors returned by AssociateTrialComponent
- Create
Action Error - Errors returned by CreateAction
- Create
Algorithm Error - Errors returned by CreateAlgorithm
- Create
AppError - Errors returned by CreateApp
- Create
AppImage Config Error - Errors returned by CreateAppImageConfig
- Create
Artifact Error - Errors returned by CreateArtifact
- Create
AutoML JobError - Errors returned by CreateAutoMLJob
- Create
Code Repository Error - Errors returned by CreateCodeRepository
- Create
Compilation JobError - Errors returned by CreateCompilationJob
- Create
Context Error - Errors returned by CreateContext
- Create
Data Quality JobDefinition Error - Errors returned by CreateDataQualityJobDefinition
- Create
Device Fleet Error - Errors returned by CreateDeviceFleet
- Create
Domain Error - Errors returned by CreateDomain
- Create
Edge Packaging JobError - Errors returned by CreateEdgePackagingJob
- Create
Endpoint Config Error - Errors returned by CreateEndpointConfig
- Create
Endpoint Error - Errors returned by CreateEndpoint
- Create
Experiment Error - Errors returned by CreateExperiment
- Create
Feature Group Error - Errors returned by CreateFeatureGroup
- Create
Flow Definition Error - Errors returned by CreateFlowDefinition
- Create
Human Task UiError - Errors returned by CreateHumanTaskUi
- Create
Hyper Parameter Tuning JobError - Errors returned by CreateHyperParameterTuningJob
- Create
Image Error - Errors returned by CreateImage
- Create
Image Version Error - Errors returned by CreateImageVersion
- Create
Labeling JobError - Errors returned by CreateLabelingJob
- Create
Model Bias JobDefinition Error - Errors returned by CreateModelBiasJobDefinition
- Create
Model Error - Errors returned by CreateModel
- Create
Model Explainability JobDefinition Error - Errors returned by CreateModelExplainabilityJobDefinition
- Create
Model Package Error - Errors returned by CreateModelPackage
- Create
Model Package Group Error - Errors returned by CreateModelPackageGroup
- Create
Model Quality JobDefinition Error - Errors returned by CreateModelQualityJobDefinition
- Create
Monitoring Schedule Error - Errors returned by CreateMonitoringSchedule
- Create
Notebook Instance Error - Errors returned by CreateNotebookInstance
- Create
Notebook Instance Lifecycle Config Error - Errors returned by CreateNotebookInstanceLifecycleConfig
- Create
Pipeline Error - Errors returned by CreatePipeline
- Create
Presigned Domain UrlError - Errors returned by CreatePresignedDomainUrl
- Create
Presigned Notebook Instance UrlError - Errors returned by CreatePresignedNotebookInstanceUrl
- Create
Processing JobError - Errors returned by CreateProcessingJob
- Create
Project Error - Errors returned by CreateProject
- Create
Training JobError - Errors returned by CreateTrainingJob
- Create
Transform JobError - Errors returned by CreateTransformJob
- Create
Trial Component Error - Errors returned by CreateTrialComponent
- Create
Trial Error - Errors returned by CreateTrial
- Create
User Profile Error - Errors returned by CreateUserProfile
- Create
Workforce Error - Errors returned by CreateWorkforce
- Create
Workteam Error - Errors returned by CreateWorkteam
- Delete
Action Error - Errors returned by DeleteAction
- Delete
Algorithm Error - Errors returned by DeleteAlgorithm
- Delete
AppError - Errors returned by DeleteApp
- Delete
AppImage Config Error - Errors returned by DeleteAppImageConfig
- Delete
Artifact Error - Errors returned by DeleteArtifact
- Delete
Association Error - Errors returned by DeleteAssociation
- Delete
Code Repository Error - Errors returned by DeleteCodeRepository
- Delete
Context Error - Errors returned by DeleteContext
- Delete
Data Quality JobDefinition Error - Errors returned by DeleteDataQualityJobDefinition
- Delete
Device Fleet Error - Errors returned by DeleteDeviceFleet
- Delete
Domain Error - Errors returned by DeleteDomain
- Delete
Endpoint Config Error - Errors returned by DeleteEndpointConfig
- Delete
Endpoint Error - Errors returned by DeleteEndpoint
- Delete
Experiment Error - Errors returned by DeleteExperiment
- Delete
Feature Group Error - Errors returned by DeleteFeatureGroup
- Delete
Flow Definition Error - Errors returned by DeleteFlowDefinition
- Delete
Human Task UiError - Errors returned by DeleteHumanTaskUi
- Delete
Image Error - Errors returned by DeleteImage
- Delete
Image Version Error - Errors returned by DeleteImageVersion
- Delete
Model Bias JobDefinition Error - Errors returned by DeleteModelBiasJobDefinition
- Delete
Model Error - Errors returned by DeleteModel
- Delete
Model Explainability JobDefinition Error - Errors returned by DeleteModelExplainabilityJobDefinition
- Delete
Model Package Error - Errors returned by DeleteModelPackage
- Delete
Model Package Group Error - Errors returned by DeleteModelPackageGroup
- Delete
Model Package Group Policy Error - Errors returned by DeleteModelPackageGroupPolicy
- Delete
Model Quality JobDefinition Error - Errors returned by DeleteModelQualityJobDefinition
- Delete
Monitoring Schedule Error - Errors returned by DeleteMonitoringSchedule
- Delete
Notebook Instance Error - Errors returned by DeleteNotebookInstance
- Delete
Notebook Instance Lifecycle Config Error - Errors returned by DeleteNotebookInstanceLifecycleConfig
- Delete
Pipeline Error - Errors returned by DeletePipeline
- Delete
Project Error - Errors returned by DeleteProject
- Delete
Tags Error - Errors returned by DeleteTags
- Delete
Trial Component Error - Errors returned by DeleteTrialComponent
- Delete
Trial Error - Errors returned by DeleteTrial
- Delete
User Profile Error - Errors returned by DeleteUserProfile
- Delete
Workforce Error - Errors returned by DeleteWorkforce
- Delete
Workteam Error - Errors returned by DeleteWorkteam
- Deregister
Devices Error - Errors returned by DeregisterDevices
- Describe
Action Error - Errors returned by DescribeAction
- Describe
Algorithm Error - Errors returned by DescribeAlgorithm
- Describe
AppError - Errors returned by DescribeApp
- Describe
AppImage Config Error - Errors returned by DescribeAppImageConfig
- Describe
Artifact Error - Errors returned by DescribeArtifact
- Describe
AutoML JobError - Errors returned by DescribeAutoMLJob
- Describe
Code Repository Error - Errors returned by DescribeCodeRepository
- Describe
Compilation JobError - Errors returned by DescribeCompilationJob
- Describe
Context Error - Errors returned by DescribeContext
- Describe
Data Quality JobDefinition Error - Errors returned by DescribeDataQualityJobDefinition
- Describe
Device Error - Errors returned by DescribeDevice
- Describe
Device Fleet Error - Errors returned by DescribeDeviceFleet
- Describe
Domain Error - Errors returned by DescribeDomain
- Describe
Edge Packaging JobError - Errors returned by DescribeEdgePackagingJob
- Describe
Endpoint Config Error - Errors returned by DescribeEndpointConfig
- Describe
Endpoint Error - Errors returned by DescribeEndpoint
- Describe
Experiment Error - Errors returned by DescribeExperiment
- Describe
Feature Group Error - Errors returned by DescribeFeatureGroup
- Describe
Flow Definition Error - Errors returned by DescribeFlowDefinition
- Describe
Human Task UiError - Errors returned by DescribeHumanTaskUi
- Describe
Hyper Parameter Tuning JobError - Errors returned by DescribeHyperParameterTuningJob
- Describe
Image Error - Errors returned by DescribeImage
- Describe
Image Version Error - Errors returned by DescribeImageVersion
- Describe
Labeling JobError - Errors returned by DescribeLabelingJob
- Describe
Model Bias JobDefinition Error - Errors returned by DescribeModelBiasJobDefinition
- Describe
Model Error - Errors returned by DescribeModel
- Describe
Model Explainability JobDefinition Error - Errors returned by DescribeModelExplainabilityJobDefinition
- Describe
Model Package Error - Errors returned by DescribeModelPackage
- Describe
Model Package Group Error - Errors returned by DescribeModelPackageGroup
- Describe
Model Quality JobDefinition Error - Errors returned by DescribeModelQualityJobDefinition
- Describe
Monitoring Schedule Error - Errors returned by DescribeMonitoringSchedule
- Describe
Notebook Instance Error - Errors returned by DescribeNotebookInstance
- Describe
Notebook Instance Lifecycle Config Error - Errors returned by DescribeNotebookInstanceLifecycleConfig
- Describe
Pipeline Definition ForExecution Error - Errors returned by DescribePipelineDefinitionForExecution
- Describe
Pipeline Error - Errors returned by DescribePipeline
- Describe
Pipeline Execution Error - Errors returned by DescribePipelineExecution
- Describe
Processing JobError - Errors returned by DescribeProcessingJob
- Describe
Project Error - Errors returned by DescribeProject
- Describe
Subscribed Workteam Error - Errors returned by DescribeSubscribedWorkteam
- Describe
Training JobError - Errors returned by DescribeTrainingJob
- Describe
Transform JobError - Errors returned by DescribeTransformJob
- Describe
Trial Component Error - Errors returned by DescribeTrialComponent
- Describe
Trial Error - Errors returned by DescribeTrial
- Describe
User Profile Error - Errors returned by DescribeUserProfile
- Describe
Workforce Error - Errors returned by DescribeWorkforce
- Describe
Workteam Error - Errors returned by DescribeWorkteam
- Disable
Sagemaker Servicecatalog Portfolio Error - Errors returned by DisableSagemakerServicecatalogPortfolio
- Disassociate
Trial Component Error - Errors returned by DisassociateTrialComponent
- Enable
Sagemaker Servicecatalog Portfolio Error - Errors returned by EnableSagemakerServicecatalogPortfolio
- GetDevice
Fleet Report Error - Errors returned by GetDeviceFleetReport
- GetModel
Package Group Policy Error - Errors returned by GetModelPackageGroupPolicy
- GetSagemaker
Servicecatalog Portfolio Status Error - Errors returned by GetSagemakerServicecatalogPortfolioStatus
- GetSearch
Suggestions Error - Errors returned by GetSearchSuggestions
- List
Actions Error - Errors returned by ListActions
- List
Algorithms Error - Errors returned by ListAlgorithms
- List
AppImage Configs Error - Errors returned by ListAppImageConfigs
- List
Apps Error - Errors returned by ListApps
- List
Artifacts Error - Errors returned by ListArtifacts
- List
Associations Error - Errors returned by ListAssociations
- List
AutoML Jobs Error - Errors returned by ListAutoMLJobs
- List
Candidates ForAutoML JobError - Errors returned by ListCandidatesForAutoMLJob
- List
Code Repositories Error - Errors returned by ListCodeRepositories
- List
Compilation Jobs Error - Errors returned by ListCompilationJobs
- List
Contexts Error - Errors returned by ListContexts
- List
Data Quality JobDefinitions Error - Errors returned by ListDataQualityJobDefinitions
- List
Device Fleets Error - Errors returned by ListDeviceFleets
- List
Devices Error - Errors returned by ListDevices
- List
Domains Error - Errors returned by ListDomains
- List
Edge Packaging Jobs Error - Errors returned by ListEdgePackagingJobs
- List
Endpoint Configs Error - Errors returned by ListEndpointConfigs
- List
Endpoints Error - Errors returned by ListEndpoints
- List
Experiments Error - Errors returned by ListExperiments
- List
Feature Groups Error - Errors returned by ListFeatureGroups
- List
Flow Definitions Error - Errors returned by ListFlowDefinitions
- List
Human Task UisError - Errors returned by ListHumanTaskUis
- List
Hyper Parameter Tuning Jobs Error - Errors returned by ListHyperParameterTuningJobs
- List
Image Versions Error - Errors returned by ListImageVersions
- List
Images Error - Errors returned by ListImages
- List
Labeling Jobs Error - Errors returned by ListLabelingJobs
- List
Labeling Jobs ForWorkteam Error - Errors returned by ListLabelingJobsForWorkteam
- List
Model Bias JobDefinitions Error - Errors returned by ListModelBiasJobDefinitions
- List
Model Explainability JobDefinitions Error - Errors returned by ListModelExplainabilityJobDefinitions
- List
Model Package Groups Error - Errors returned by ListModelPackageGroups
- List
Model Packages Error - Errors returned by ListModelPackages
- List
Model Quality JobDefinitions Error - Errors returned by ListModelQualityJobDefinitions
- List
Models Error - Errors returned by ListModels
- List
Monitoring Executions Error - Errors returned by ListMonitoringExecutions
- List
Monitoring Schedules Error - Errors returned by ListMonitoringSchedules
- List
Notebook Instance Lifecycle Configs Error - Errors returned by ListNotebookInstanceLifecycleConfigs
- List
Notebook Instances Error - Errors returned by ListNotebookInstances
- List
Pipeline Execution Steps Error - Errors returned by ListPipelineExecutionSteps
- List
Pipeline Executions Error - Errors returned by ListPipelineExecutions
- List
Pipeline Parameters ForExecution Error - Errors returned by ListPipelineParametersForExecution
- List
Pipelines Error - Errors returned by ListPipelines
- List
Processing Jobs Error - Errors returned by ListProcessingJobs
- List
Projects Error - Errors returned by ListProjects
- List
Subscribed Workteams Error - Errors returned by ListSubscribedWorkteams
- List
Tags Error - Errors returned by ListTags
- List
Training Jobs Error - Errors returned by ListTrainingJobs
- List
Training Jobs ForHyper Parameter Tuning JobError - Errors returned by ListTrainingJobsForHyperParameterTuningJob
- List
Transform Jobs Error - Errors returned by ListTransformJobs
- List
Trial Components Error - Errors returned by ListTrialComponents
- List
Trials Error - Errors returned by ListTrials
- List
User Profiles Error - Errors returned by ListUserProfiles
- List
Workforces Error - Errors returned by ListWorkforces
- List
Workteams Error - Errors returned by ListWorkteams
- PutModel
Package Group Policy Error - Errors returned by PutModelPackageGroupPolicy
- Register
Devices Error - Errors returned by RegisterDevices
- Render
UiTemplate Error - Errors returned by RenderUiTemplate
- Search
Error - Errors returned by Search
- Send
Pipeline Execution Step Failure Error - Errors returned by SendPipelineExecutionStepFailure
- Send
Pipeline Execution Step Success Error - Errors returned by SendPipelineExecutionStepSuccess
- Start
Monitoring Schedule Error - Errors returned by StartMonitoringSchedule
- Start
Notebook Instance Error - Errors returned by StartNotebookInstance
- Start
Pipeline Execution Error - Errors returned by StartPipelineExecution
- Stop
AutoML JobError - Errors returned by StopAutoMLJob
- Stop
Compilation JobError - Errors returned by StopCompilationJob
- Stop
Edge Packaging JobError - Errors returned by StopEdgePackagingJob
- Stop
Hyper Parameter Tuning JobError - Errors returned by StopHyperParameterTuningJob
- Stop
Labeling JobError - Errors returned by StopLabelingJob
- Stop
Monitoring Schedule Error - Errors returned by StopMonitoringSchedule
- Stop
Notebook Instance Error - Errors returned by StopNotebookInstance
- Stop
Pipeline Execution Error - Errors returned by StopPipelineExecution
- Stop
Processing JobError - Errors returned by StopProcessingJob
- Stop
Training JobError - Errors returned by StopTrainingJob
- Stop
Transform JobError - Errors returned by StopTransformJob
- Update
Action Error - Errors returned by UpdateAction
- Update
AppImage Config Error - Errors returned by UpdateAppImageConfig
- Update
Artifact Error - Errors returned by UpdateArtifact
- Update
Code Repository Error - Errors returned by UpdateCodeRepository
- Update
Context Error - Errors returned by UpdateContext
- Update
Device Fleet Error - Errors returned by UpdateDeviceFleet
- Update
Devices Error - Errors returned by UpdateDevices
- Update
Domain Error - Errors returned by UpdateDomain
- Update
Endpoint Error - Errors returned by UpdateEndpoint
- Update
Endpoint Weights AndCapacities Error - Errors returned by UpdateEndpointWeightsAndCapacities
- Update
Experiment Error - Errors returned by UpdateExperiment
- Update
Image Error - Errors returned by UpdateImage
- Update
Model Package Error - Errors returned by UpdateModelPackage
- Update
Monitoring Schedule Error - Errors returned by UpdateMonitoringSchedule
- Update
Notebook Instance Error - Errors returned by UpdateNotebookInstance
- Update
Notebook Instance Lifecycle Config Error - Errors returned by UpdateNotebookInstanceLifecycleConfig
- Update
Pipeline Error - Errors returned by UpdatePipeline
- Update
Pipeline Execution Error - Errors returned by UpdatePipelineExecution
- Update
Training JobError - Errors returned by UpdateTrainingJob
- Update
Trial Component Error - Errors returned by UpdateTrialComponent
- Update
Trial Error - Errors returned by UpdateTrial
- Update
User Profile Error - Errors returned by UpdateUserProfile
- Update
Workforce Error - Errors returned by UpdateWorkforce
- Update
Workteam Error - Errors returned by UpdateWorkteam
Traits§
- Sage
Maker - Trait representing the capabilities of the SageMaker API. SageMaker clients implement this trait.