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§
- AddTags
Input - AddTags
Output - 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
The app's details.
- AppSpecification
Configuration to run a processing job in a specified container image.
- Associate
Trial Component Request - Associate
Trial Component Response - AutoML
Candidate An AutoPilot job will return recommendations, or candidates. Each candidate has futher details about the steps involed, and the status.
- AutoML
Candidate Step Information about the steps for a Candidate, and what step it is working on.
- AutoML
Channel Similar to Channel. A channel is a named input source that training algorithms can consume. Refer to Channel for detailed descriptions.
- AutoML
Container Definition A list of container definitions that describe the different containers that make up one AutoML candidate. Refer to ContainerDefinition for more details.
- AutoML
Data Source The data source for the AutoPilot job.
- AutoML
JobArtifacts Artifacts that are generation during a 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 a job.
- AutoML
JobObjective Applies a metric to minimize or maximize for the job's objective.
- AutoML
JobSummary Provides a summary about a job.
- AutoML
Output Data Config The output data configuration.
- AutoML
S3Data Source The Amazon S3 data source.
- AutoML
Security Config Security options.
- 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
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 tensor collections.
- Compilation
JobSummary A summary of a model compilation job.
- Container
Definition Describes the container, as part of model definition.
- Continuous
Parameter Range A list of continuous hyperparameters to tune.
- Continuous
Parameter Range Specification Defines the possible values for a continuous hyperparameter.
- Create
Algorithm Input - Create
Algorithm Output - Create
AppRequest - Create
AppResponse - Create
AutoML JobRequest - Create
AutoML JobResponse - Create
Code Repository Input - Create
Code Repository Output - Create
Compilation JobRequest - Create
Compilation JobResponse - Create
Domain Request - Create
Domain Response - Create
Endpoint Config Input - Create
Endpoint Config Output - Create
Endpoint Input - Create
Endpoint Output - Create
Experiment Request - Create
Experiment 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
Labeling JobRequest - Create
Labeling JobResponse - Create
Model Input - Create
Model Output - Create
Model Package Input - Create
Model Package Output - 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
Presigned Domain UrlRequest - Create
Presigned Domain UrlResponse - Create
Presigned Notebook Instance UrlInput - Create
Presigned Notebook Instance UrlOutput - Create
Processing JobRequest - Create
Processing JobResponse - 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
Workteam Request - Create
Workteam Response - Data
Capture Config - Data
Capture Config Summary - 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
Source Describes the location of the channel data.
- Debug
Hook Config Configuration information for the debug hook parameters, collection configuration, and storage paths.
- Debug
Rule Configuration Configuration information for debugging rules.
- Debug
Rule Evaluation Status Information about the status of the rule evaluation.
- Delete
Algorithm Input - Delete
AppRequest - Delete
Code Repository Input - Delete
Domain Request - Delete
Endpoint Config Input - Delete
Endpoint Input - Delete
Experiment Request - Delete
Experiment Response - Delete
Flow Definition Request - Delete
Flow Definition Response - Delete
Human Task UiRequest - Delete
Human Task UiResponse - Delete
Model Input - Delete
Model Package Input - Delete
Monitoring Schedule Request - Delete
Notebook Instance Input - Delete
Notebook Instance Lifecycle Config 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
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.- Describe
Algorithm Input - Describe
Algorithm Output - Describe
AppRequest - Describe
AppResponse - Describe
AutoML JobRequest - Describe
AutoML JobResponse - Describe
Code Repository Input - Describe
Code Repository Output - Describe
Compilation JobRequest - Describe
Compilation JobResponse - Describe
Domain Request - Describe
Domain Response - Describe
Endpoint Config Input - Describe
Endpoint Config Output - Describe
Endpoint Input - Describe
Endpoint Output - Describe
Experiment Request - Describe
Experiment 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
Labeling JobRequest - Describe
Labeling JobResponse - Describe
Model Input - Describe
Model Output - Describe
Model Package Input - Describe
Model Package Output - 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
Processing JobRequest - Describe
Processing JobResponse - 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.
- Disassociate
Trial Component Request - Disassociate
Trial Component Response - Domain
Details The domain's details.
- 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 Configuration for the experiment.
- 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.- 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 candidate result from a 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.
- 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.
- 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 Jupyter server's app settings.
- Kernel
Gateway AppSettings The kernel gateway app settings.
- 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.
- 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 Provides configuration information for labeling jobs.
- Labeling
JobS3 Data Source The Amazon S3 location of the input data objects.
- 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
Algorithms Input - List
Algorithms Output - List
Apps Request - List
Apps 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
Domains Request - List
Domains Response - List
Endpoint Configs Input - List
Endpoint Configs Output - List
Endpoints Input - List
Endpoints Output - List
Experiments Request - List
Experiments 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
Labeling Jobs ForWorkteam Request - List
Labeling Jobs ForWorkteam Response - List
Labeling Jobs Request - List
Labeling Jobs Response - List
Model Packages Input - List
Model Packages Output - 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
Processing Jobs Request - List
Processing Jobs Response - 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
Workteams Request - List
Workteams Response - Member
Definition Defines the Amazon Cognito user group that is part of a work team.
- 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.- 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 desribes how to compute inferences, and other metadata.
- Model
Client Config Configures the timeout and maximum number of retries for processing a transform job invocation.
- Model
Package Container Definition Describes the Docker container for the model package.
- 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
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
Input The inputs for a monitoring job.
- Monitoring
JobDefinition Defines 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 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.
- 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.
- Output
Config Contains information about the output location for the compiled model and the device (target) that the model runs on.
- Output
Data Config Provides information about how to store model training results (model artifacts).
- 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.
- Processing
Cluster Config Configuration for the cluster used to run a processing job.
- Processing
Input The inputs for a processing job.
- 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
JobSummary Summary of information about a processing job.
- Processing
Output Describes the results of a processing job.
- Processing
Output Config The output configuration for the processing job.
- 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 Information about where and how you want to obtain the inputs for an processing job.
- Processing
S3Output Information about where and how you want to store the results of an processing job.
- Processing
Stopping Condition Specifies a time limit for how long the processing job is allowed to run.
- Production
Variant 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.
- 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.- 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.- 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
-
- 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.
- 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 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.
- Retention
Policy The retention policy for data stored on an Amazon Elastic File System (EFS) volume.
- S3Data
Source Describes the S3 data source.
- 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.
- Sharing
Settings Specifies options when sharing an Amazon SageMaker Studio notebook. These settings are specified as part of
DefaultUserSettingswhen the CreateDomain API is called, and as part ofUserSettingswhen the CreateUserProfile API is called.- 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. For more information, see .
- Start
Monitoring Schedule Request - Start
Notebook Instance Input - Stop
AutoML JobRequest - Stop
Compilation JobRequest - Stop
Hyper Parameter Tuning JobRequest - Stop
Labeling JobRequest - Stop
Monitoring Schedule Request - Stop
Notebook Instance Input - Stop
Processing JobRequest - Stop
Training JobRequest - Stop
Transform JobRequest - Stopping
Condition 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
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
Describes a tag.
- Tensor
Board AppSettings The TensorBoard app settings.
- Tensor
Board Output Config Configuration of storage locations for TensorBoard output.
- 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
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
JobDefinition Defines the input needed to run a transform job using the inference specification specified in the algorithm.
- 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
Code Repository Input - Update
Code Repository Output - 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
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
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.
- 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§
- AddTags
Error - Errors returned by AddTags
- Associate
Trial Component Error - Errors returned by AssociateTrialComponent
- Create
Algorithm Error - Errors returned by CreateAlgorithm
- Create
AppError - Errors returned by CreateApp
- Create
AutoML JobError - Errors returned by CreateAutoMLJob
- Create
Code Repository Error - Errors returned by CreateCodeRepository
- Create
Compilation JobError - Errors returned by CreateCompilationJob
- Create
Domain Error - Errors returned by CreateDomain
- Create
Endpoint Config Error - Errors returned by CreateEndpointConfig
- Create
Endpoint Error - Errors returned by CreateEndpoint
- Create
Experiment Error - Errors returned by CreateExperiment
- 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
Labeling JobError - Errors returned by CreateLabelingJob
- Create
Model Error - Errors returned by CreateModel
- Create
Model Package Error - Errors returned by CreateModelPackage
- 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
Presigned Domain UrlError - Errors returned by CreatePresignedDomainUrl
- Create
Presigned Notebook Instance UrlError - Errors returned by CreatePresignedNotebookInstanceUrl
- Create
Processing JobError - Errors returned by CreateProcessingJob
- 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
Workteam Error - Errors returned by CreateWorkteam
- Delete
Algorithm Error - Errors returned by DeleteAlgorithm
- Delete
AppError - Errors returned by DeleteApp
- Delete
Code Repository Error - Errors returned by DeleteCodeRepository
- 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
Flow Definition Error - Errors returned by DeleteFlowDefinition
- Delete
Human Task UiError - Errors returned by DeleteHumanTaskUi
- Delete
Model Error - Errors returned by DeleteModel
- Delete
Model Package Error - Errors returned by DeleteModelPackage
- 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
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
Workteam Error - Errors returned by DeleteWorkteam
- Describe
Algorithm Error - Errors returned by DescribeAlgorithm
- Describe
AppError - Errors returned by DescribeApp
- Describe
AutoML JobError - Errors returned by DescribeAutoMLJob
- Describe
Code Repository Error - Errors returned by DescribeCodeRepository
- Describe
Compilation JobError - Errors returned by DescribeCompilationJob
- Describe
Domain Error - Errors returned by DescribeDomain
- Describe
Endpoint Config Error - Errors returned by DescribeEndpointConfig
- Describe
Endpoint Error - Errors returned by DescribeEndpoint
- Describe
Experiment Error - Errors returned by DescribeExperiment
- 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
Labeling JobError - Errors returned by DescribeLabelingJob
- Describe
Model Error - Errors returned by DescribeModel
- Describe
Model Package Error - Errors returned by DescribeModelPackage
- 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
Processing JobError - Errors returned by DescribeProcessingJob
- 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
- Disassociate
Trial Component Error - Errors returned by DisassociateTrialComponent
- GetSearch
Suggestions Error - Errors returned by GetSearchSuggestions
- List
Algorithms Error - Errors returned by ListAlgorithms
- List
Apps Error - Errors returned by ListApps
- 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
Domains Error - Errors returned by ListDomains
- List
Endpoint Configs Error - Errors returned by ListEndpointConfigs
- List
Endpoints Error - Errors returned by ListEndpoints
- List
Experiments Error - Errors returned by ListExperiments
- 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
Labeling Jobs Error - Errors returned by ListLabelingJobs
- List
Labeling Jobs ForWorkteam Error - Errors returned by ListLabelingJobsForWorkteam
- List
Model Packages Error - Errors returned by ListModelPackages
- 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
Processing Jobs Error - Errors returned by ListProcessingJobs
- 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
Workteams Error - Errors returned by ListWorkteams
- Render
UiTemplate Error - Errors returned by RenderUiTemplate
- Search
Error - Errors returned by Search
- Start
Monitoring Schedule Error - Errors returned by StartMonitoringSchedule
- Start
Notebook Instance Error - Errors returned by StartNotebookInstance
- Stop
AutoML JobError - Errors returned by StopAutoMLJob
- Stop
Compilation JobError - Errors returned by StopCompilationJob
- 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
Processing JobError - Errors returned by StopProcessingJob
- Stop
Training JobError - Errors returned by StopTrainingJob
- Stop
Transform JobError - Errors returned by StopTransformJob
- Update
Code Repository Error - Errors returned by UpdateCodeRepository
- 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
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
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.