# frozen_string_literal: true
# WARNING ABOUT GENERATED CODE
#
# This file is generated. See the contributing guide for more information:
# https://github.com/aws/aws-sdk-ruby/blob/version-3/CONTRIBUTING.md
#
# WARNING ABOUT GENERATED CODE
module Aws::SageMaker
module Types
# A structure describing the source of an action.
#
# @!attribute [rw] source_uri
# The URI of the source.
# @return [String]
#
# @!attribute [rw] source_type
# The type of the source.
# @return [String]
#
# @!attribute [rw] source_id
# The ID of the source.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ActionSource AWS API Documentation
#
class ActionSource < Struct.new(
:source_uri,
:source_type,
:source_id)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] action_arn
# The Amazon Resource Name (ARN) of the action.
# @return [String]
#
# @!attribute [rw] action_name
# The name of the action.
# @return [String]
#
# @!attribute [rw] source
# The source of the action.
# @return [Types::ActionSource]
#
# @!attribute [rw] action_type
# The type of the action.
# @return [String]
#
# @!attribute [rw] status
# The status of the action.
# @return [String]
#
# @!attribute [rw] creation_time
# When the action was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# When the action was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ActionSummary AWS API Documentation
#
class ActionSummary < Struct.new(
:action_arn,
:action_name,
:source,
:action_type,
:status,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_arn
# The ARN of the source.
# @return [String]
#
# @!attribute [rw] destination_arn
# The Amazon Resource Name (ARN) of the destination.
# @return [String]
#
# @!attribute [rw] association_type
# The type of association. The following are suggested uses for each
# type. Amazon SageMaker places no restrictions on their use.
#
# * ContributedTo - The source contributed to the destination or had a
# part in enabling the destination. For example, the training data
# contributed to the training job.
#
# * AssociatedWith - The source is connected to the destination. For
# example, an approval workflow is associated with a model
# deployment.
#
# * DerivedFrom - The destination is a modification of the source. For
# example, a digest output of a channel input for a processing job
# is derived from the original inputs.
#
# * Produced - The source generated the destination. For example, a
# training job produced a model artifact.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AddAssociationRequest AWS API Documentation
#
class AddAssociationRequest < Struct.new(
:source_arn,
:destination_arn,
:association_type)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_arn
# The ARN of the source.
# @return [String]
#
# @!attribute [rw] destination_arn
# The Amazon Resource Name (ARN) of the destination.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AddAssociationResponse AWS API Documentation
#
class AddAssociationResponse < Struct.new(
:source_arn,
:destination_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] resource_arn
# The Amazon Resource Name (ARN) of the resource that you want to tag.
# @return [String]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AddTagsInput AWS API Documentation
#
class AddTagsInput < Struct.new(
:resource_arn,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] tags
# A list of tags associated with the SageMaker resource.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AddTagsOutput AWS API Documentation
#
class AddTagsOutput < Struct.new(
:tags)
SENSITIVE = []
include Aws::Structure
end
# A structure of additional Inference Specification. Additional
# Inference Specification specifies details about inference jobs that
# can be run with models based on this model package
#
# @!attribute [rw] name
# A unique name to identify the additional inference specification.
# The name must be unique within the list of your additional inference
# specifications for a particular model package.
# @return [String]
#
# @!attribute [rw] description
# A description of the additional Inference specification
# @return [String]
#
# @!attribute [rw] containers
# The Amazon ECR registry path of the Docker image that contains the
# inference code.
# @return [Array<Types::ModelPackageContainerDefinition>]
#
# @!attribute [rw] supported_transform_instance_types
# A list of the instance types on which a transformation job can be
# run or on which an endpoint can be deployed.
# @return [Array<String>]
#
# @!attribute [rw] supported_realtime_inference_instance_types
# A list of the instance types that are used to generate inferences in
# real-time.
# @return [Array<String>]
#
# @!attribute [rw] supported_content_types
# The supported MIME types for the input data.
# @return [Array<String>]
#
# @!attribute [rw] supported_response_mime_types
# The supported MIME types for the output data.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AdditionalInferenceSpecificationDefinition AWS API Documentation
#
class AdditionalInferenceSpecificationDefinition < Struct.new(
:name,
:description,
:containers,
:supported_transform_instance_types,
:supported_realtime_inference_instance_types,
:supported_content_types,
:supported_response_mime_types)
SENSITIVE = []
include Aws::Structure
end
# Edge Manager agent version.
#
# @!attribute [rw] version
# Version of the agent.
# @return [String]
#
# @!attribute [rw] agent_count
# The number of Edge Manager agents.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AgentVersion AWS API Documentation
#
class AgentVersion < Struct.new(
:version,
:agent_count)
SENSITIVE = []
include Aws::Structure
end
# An Amazon CloudWatch alarm configured to monitor metrics on an
# endpoint.
#
# @!attribute [rw] alarm_name
# The name of a CloudWatch alarm in your account.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Alarm AWS API Documentation
#
class Alarm < Struct.new(
:alarm_name)
SENSITIVE = []
include Aws::Structure
end
# Specifies the training algorithm to use in a [CreateTrainingJob][1]
# request.
#
# For more information about algorithms provided by SageMaker, see
# [Algorithms][2]. For information about using your own algorithms, see
# [Using Your Own Algorithms with Amazon SageMaker][3].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html
#
# @!attribute [rw] training_image
# The registry path of the Docker image that contains the training
# algorithm. For information about docker registry paths for SageMaker
# built-in algorithms, see [Docker Registry Paths and Example Code][1]
# in the *Amazon SageMaker developer guide*. SageMaker supports both
# `registry/repository[:tag]` and `registry/repository[@digest]` image
# path formats. For more information about using your custom training
# container, see [Using Your Own Algorithms with Amazon SageMaker][2].
#
# <note markdown="1"> You must specify either the algorithm name to the `AlgorithmName`
# parameter or the image URI of the algorithm container to the
# `TrainingImage` parameter.
#
# For more information, see the note in the `AlgorithmName` parameter
# description.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html
# @return [String]
#
# @!attribute [rw] algorithm_name
# The name of the algorithm resource to use for the training job. This
# must be an algorithm resource that you created or subscribe to on
# Amazon Web Services Marketplace.
#
# <note markdown="1"> You must specify either the algorithm name to the `AlgorithmName`
# parameter or the image URI of the algorithm container to the
# `TrainingImage` parameter.
#
# Note that the `AlgorithmName` parameter is mutually exclusive with
# the `TrainingImage` parameter. If you specify a value for the
# `AlgorithmName` parameter, you can't specify a value for
# `TrainingImage`, and vice versa.
#
# If you specify values for both parameters, the training job might
# break; if you don't specify any value for both parameters, the
# training job might raise a `null` error.
#
# </note>
# @return [String]
#
# @!attribute [rw] training_input_mode
# The training input mode that the algorithm supports. For more
# information about input modes, see [Algorithms][1].
#
# **Pipe mode**
#
# If an algorithm supports `Pipe` mode, Amazon SageMaker streams data
# directly from Amazon S3 to the container.
#
# **File mode**
#
# If an algorithm supports `File` mode, SageMaker downloads the
# training data from S3 to the provisioned ML storage volume, and
# mounts the directory to the Docker volume for the training
# container.
#
# You must provision the ML storage volume with sufficient capacity to
# accommodate the data downloaded from S3. In addition to the training
# data, the ML storage volume also stores the output model. The
# algorithm container uses the ML storage volume to also store
# intermediate information, if any.
#
# For distributed algorithms, training data is distributed uniformly.
# Your training duration is predictable if the input data objects
# sizes are approximately the same. SageMaker does not split the files
# any further for model training. If the object sizes are skewed,
# training won't be optimal as the data distribution is also skewed
# when one host in a training cluster is overloaded, thus becoming a
# bottleneck in training.
#
# **FastFile mode**
#
# If an algorithm supports `FastFile` mode, SageMaker streams data
# directly from S3 to the container with no code changes, and provides
# file system access to the data. Users can author their training
# script to interact with these files as if they were stored on disk.
#
# `FastFile` mode works best when the data is read sequentially.
# Augmented manifest files aren't supported. The startup time is
# lower when there are fewer files in the S3 bucket provided.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
# @return [String]
#
# @!attribute [rw] metric_definitions
# A list of metric definition objects. Each object specifies the
# metric name and regular expressions used to parse algorithm logs.
# SageMaker publishes each metric to Amazon CloudWatch.
# @return [Array<Types::MetricDefinition>]
#
# @!attribute [rw] enable_sage_maker_metrics_time_series
# To generate and save time-series metrics during training, set to
# `true`. The default is `false` and time-series metrics aren't
# generated except in the following cases:
#
# * You use one of the SageMaker built-in algorithms
#
# * You use one of the following [Prebuilt SageMaker Docker
# Images][1]:
#
# * Tensorflow (version >= 1.15)
#
# * MXNet (version >= 1.6)
#
# * PyTorch (version >= 1.3)
#
# * You specify at least one [MetricDefinition][2]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_MetricDefinition.html
# @return [Boolean]
#
# @!attribute [rw] container_entrypoint
# The [entrypoint script for a Docker container][1] used to run a
# training job. This script takes precedence over the default train
# processing instructions. See [How Amazon SageMaker Runs Your
# Training Image][2] for more information.
#
#
#
# [1]: https://docs.docker.com/engine/reference/builder/
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html
# @return [Array<String>]
#
# @!attribute [rw] container_arguments
# The arguments for a container used to run a training job. See [How
# Amazon SageMaker Runs Your Training Image][1] for additional
# information.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-training-algo-dockerfile.html
# @return [Array<String>]
#
# @!attribute [rw] training_image_config
# The configuration to use an image from a private Docker registry for
# a training job.
# @return [Types::TrainingImageConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AlgorithmSpecification AWS API Documentation
#
class AlgorithmSpecification < Struct.new(
:training_image,
:algorithm_name,
:training_input_mode,
:metric_definitions,
:enable_sage_maker_metrics_time_series,
:container_entrypoint,
:container_arguments,
:training_image_config)
SENSITIVE = []
include Aws::Structure
end
# Specifies the validation and image scan statuses of the algorithm.
#
# @!attribute [rw] validation_statuses
# The status of algorithm validation.
# @return [Array<Types::AlgorithmStatusItem>]
#
# @!attribute [rw] image_scan_statuses
# The status of the scan of the algorithm's Docker image container.
# @return [Array<Types::AlgorithmStatusItem>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AlgorithmStatusDetails AWS API Documentation
#
class AlgorithmStatusDetails < Struct.new(
:validation_statuses,
:image_scan_statuses)
SENSITIVE = []
include Aws::Structure
end
# Represents the overall status of an algorithm.
#
# @!attribute [rw] name
# The name of the algorithm for which the overall status is being
# reported.
# @return [String]
#
# @!attribute [rw] status
# The current status.
# @return [String]
#
# @!attribute [rw] failure_reason
# if the overall status is `Failed`, the reason for the failure.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AlgorithmStatusItem AWS API Documentation
#
class AlgorithmStatusItem < Struct.new(
:name,
:status,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information about an algorithm.
#
# @!attribute [rw] algorithm_name
# The name of the algorithm that is described by the summary.
# @return [String]
#
# @!attribute [rw] algorithm_arn
# The Amazon Resource Name (ARN) of the algorithm.
# @return [String]
#
# @!attribute [rw] algorithm_description
# A brief description of the algorithm.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the algorithm was created.
# @return [Time]
#
# @!attribute [rw] algorithm_status
# The overall status of the algorithm.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AlgorithmSummary AWS API Documentation
#
class AlgorithmSummary < Struct.new(
:algorithm_name,
:algorithm_arn,
:algorithm_description,
:creation_time,
:algorithm_status)
SENSITIVE = []
include Aws::Structure
end
# Defines a training job and a batch transform job that SageMaker runs
# to validate your algorithm.
#
# The data provided in the validation profile is made available to your
# buyers on Amazon Web Services Marketplace.
#
# @!attribute [rw] profile_name
# The name of the profile for the algorithm. The name must have 1 to
# 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
# @return [String]
#
# @!attribute [rw] training_job_definition
# The `TrainingJobDefinition` object that describes the training job
# that SageMaker runs to validate your algorithm.
# @return [Types::TrainingJobDefinition]
#
# @!attribute [rw] transform_job_definition
# The `TransformJobDefinition` object that describes the transform job
# that SageMaker runs to validate your algorithm.
# @return [Types::TransformJobDefinition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AlgorithmValidationProfile AWS API Documentation
#
class AlgorithmValidationProfile < Struct.new(
:profile_name,
:training_job_definition,
:transform_job_definition)
SENSITIVE = []
include Aws::Structure
end
# Specifies configurations for one or more training jobs that SageMaker
# runs to test the algorithm.
#
# @!attribute [rw] validation_role
# The IAM roles that SageMaker uses to run the training jobs.
# @return [String]
#
# @!attribute [rw] validation_profiles
# An array of `AlgorithmValidationProfile` objects, each of which
# specifies a training job and batch transform job that SageMaker runs
# to validate your algorithm.
# @return [Array<Types::AlgorithmValidationProfile>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AlgorithmValidationSpecification AWS API Documentation
#
class AlgorithmValidationSpecification < Struct.new(
:validation_role,
:validation_profiles)
SENSITIVE = []
include Aws::Structure
end
# Configures how labels are consolidated across human workers and
# processes output data.
#
# @!attribute [rw] annotation_consolidation_lambda_arn
# The Amazon Resource Name (ARN) of a Lambda function implements the
# logic for [annotation consolidation][1] and to process output data.
#
# This parameter is required for all labeling jobs. For [built-in task
# types][2], use one of the following Amazon SageMaker Ground Truth
# Lambda function ARNs for `AnnotationConsolidationLambdaArn`. For
# custom labeling workflows, see [Post-annotation Lambda][3].
#
# **Bounding box** - Finds the most similar boxes from different
# workers based on the Jaccard index of the boxes.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-BoundingBox`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-BoundingBox`
#
# **Image classification** - Uses a variant of the Expectation
# Maximization approach to estimate the true class of an image based
# on annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClass`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClass`
#
# **Multi-label image classification** - Uses a variant of the
# Expectation Maximization approach to estimate the true classes of an
# image based on annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-ImageMultiClassMultiLabel`
#
# **Semantic segmentation** - Treats each pixel in an image as a
# multi-class classification and treats pixel annotations from workers
# as "votes" for the correct label.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-SemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-SemanticSegmentation`
#
# **Text classification** - Uses a variant of the Expectation
# Maximization approach to estimate the true class of text based on
# annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass`
#
# **Multi-label text classification** - Uses a variant of the
# Expectation Maximization approach to estimate the true classes of
# text based on annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel`
#
# **Named entity recognition** - Groups similar selections and
# calculates aggregate boundaries, resolving to most-assigned label.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition`
#
# **Video Classification** - Use this task type when you need workers
# to classify videos using predefined labels that you specify. Workers
# are shown videos and are asked to choose one label for each video.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass`
#
# **Video Frame Object Detection** - Use this task type to have
# workers identify and locate objects in a sequence of video frames
# (images extracted from a video) using bounding boxes. For example,
# you can use this task to ask workers to identify and localize
# various objects in a series of video frames, such as cars, bikes,
# and pedestrians.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection`
#
# **Video Frame Object Tracking** - Use this task type to have workers
# track the movement of objects in a sequence of video frames (images
# extracted from a video) using bounding boxes. For example, you can
# use this task to ask workers to track the movement of objects, such
# as cars, bikes, and pedestrians.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking`
#
# **3D Point Cloud Object Detection** - Use this task type when you
# want workers to classify objects in a 3D point cloud by drawing 3D
# cuboids around objects. For example, you can use this task type to
# ask workers to identify different types of objects in a point cloud,
# such as cars, bikes, and pedestrians.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection`
#
# **3D Point Cloud Object Tracking** - Use this task type when you
# want workers to draw 3D cuboids around objects that appear in a
# sequence of 3D point cloud frames. For example, you can use this
# task type to ask workers to track the movement of vehicles across
# multiple point cloud frames.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking`
#
# **3D Point Cloud Semantic Segmentation** - Use this task type when
# you want workers to create a point-level semantic segmentation masks
# by painting objects in a 3D point cloud using different colors where
# each color is assigned to one of the classes you specify.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation`
#
# **Use the following ARNs for Label Verification and Adjustment
# Jobs**
#
# Use label verification and adjustment jobs to review and adjust
# labels. To learn more, see [Verify and Adjust Labels ][4].
#
# **Semantic Segmentation Adjustment** - Treats each pixel in an image
# as a multi-class classification and treats pixel adjusted
# annotations from workers as "votes" for the correct label.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation`
#
# **Semantic Segmentation Verification** - Uses a variant of the
# Expectation Maximization approach to estimate the true class of
# verification judgment for semantic segmentation labels based on
# annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation`
#
# **Bounding Box Adjustment** - Finds the most similar boxes from
# different workers based on the Jaccard index of the adjusted
# annotations.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox`
#
# **Bounding Box Verification** - Uses a variant of the Expectation
# Maximization approach to estimate the true class of verification
# judgement for bounding box labels based on annotations from
# individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox`
#
# **Video Frame Object Detection Adjustment** - Use this task type
# when you want workers to adjust bounding boxes that workers have
# added to video frames to classify and localize objects in a sequence
# of video frames.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection`
#
# **Video Frame Object Tracking Adjustment** - Use this task type when
# you want workers to adjust bounding boxes that workers have added to
# video frames to track object movement across a sequence of video
# frames.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking`
#
# **3D Point Cloud Object Detection Adjustment** - Use this task type
# when you want workers to adjust 3D cuboids around objects in a 3D
# point cloud.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection`
#
# **3D Point Cloud Object Tracking Adjustment** - Use this task type
# when you want workers to adjust 3D cuboids around objects that
# appear in a sequence of 3D point cloud frames.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking`
#
# **3D Point Cloud Semantic Segmentation Adjustment** - Use this task
# type when you want workers to adjust a point-level semantic
# segmentation masks using a paint tool.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-postlambda
# [4]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AnnotationConsolidationConfig AWS API Documentation
#
class AnnotationConsolidationConfig < Struct.new(
:annotation_consolidation_lambda_arn)
SENSITIVE = []
include Aws::Structure
end
# Details about an Amazon SageMaker app.
#
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name.
# @return [String]
#
# @!attribute [rw] app_type
# The type of app.
# @return [String]
#
# @!attribute [rw] app_name
# The name of the app.
# @return [String]
#
# @!attribute [rw] status
# The status.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AppDetails AWS API Documentation
#
class AppDetails < Struct.new(
:domain_id,
:user_profile_name,
:app_type,
:app_name,
:status,
:creation_time,
:space_name)
SENSITIVE = []
include Aws::Structure
end
# The configuration for running a SageMaker image as a KernelGateway
# app.
#
# @!attribute [rw] app_image_config_arn
# The Amazon Resource Name (ARN) of the AppImageConfig.
# @return [String]
#
# @!attribute [rw] app_image_config_name
# The name of the AppImageConfig. Must be unique to your account.
# @return [String]
#
# @!attribute [rw] creation_time
# When the AppImageConfig was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# When the AppImageConfig was last modified.
# @return [Time]
#
# @!attribute [rw] kernel_gateway_image_config
# The configuration for the file system and kernels in the SageMaker
# image.
# @return [Types::KernelGatewayImageConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AppImageConfigDetails AWS API Documentation
#
class AppImageConfigDetails < Struct.new(
:app_image_config_arn,
:app_image_config_name,
:creation_time,
:last_modified_time,
:kernel_gateway_image_config)
SENSITIVE = []
include Aws::Structure
end
# Configuration to run a processing job in a specified container image.
#
# @!attribute [rw] image_uri
# The container image to be run by the processing job.
# @return [String]
#
# @!attribute [rw] container_entrypoint
# The entrypoint for a container used to run a processing job.
# @return [Array<String>]
#
# @!attribute [rw] container_arguments
# The arguments for a container used to run a processing job.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AppSpecification AWS API Documentation
#
class AppSpecification < Struct.new(
:image_uri,
:container_entrypoint,
:container_arguments)
SENSITIVE = []
include Aws::Structure
end
# A structure describing the source of an artifact.
#
# @!attribute [rw] source_uri
# The URI of the source.
# @return [String]
#
# @!attribute [rw] source_types
# A list of source types.
# @return [Array<Types::ArtifactSourceType>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ArtifactSource AWS API Documentation
#
class ArtifactSource < Struct.new(
:source_uri,
:source_types)
SENSITIVE = []
include Aws::Structure
end
# The ID and ID type of an artifact source.
#
# @!attribute [rw] source_id_type
# The type of ID.
# @return [String]
#
# @!attribute [rw] value
# The ID.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ArtifactSourceType AWS API Documentation
#
class ArtifactSourceType < Struct.new(
:source_id_type,
:value)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] artifact_arn
# The Amazon Resource Name (ARN) of the artifact.
# @return [String]
#
# @!attribute [rw] artifact_name
# The name of the artifact.
# @return [String]
#
# @!attribute [rw] source
# The source of the artifact.
# @return [Types::ArtifactSource]
#
# @!attribute [rw] artifact_type
# The type of the artifact.
# @return [String]
#
# @!attribute [rw] creation_time
# When the artifact was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# When the artifact was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ArtifactSummary AWS API Documentation
#
class ArtifactSummary < Struct.new(
:artifact_arn,
:artifact_name,
:source,
:artifact_type,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_name
# The name of the component to associated with the trial.
# @return [String]
#
# @!attribute [rw] trial_name
# The name of the trial to associate with.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AssociateTrialComponentRequest AWS API Documentation
#
class AssociateTrialComponentRequest < Struct.new(
:trial_component_name,
:trial_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the trial component.
# @return [String]
#
# @!attribute [rw] trial_arn
# The Amazon Resource Name (ARN) of the trial.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AssociateTrialComponentResponse AWS API Documentation
#
class AssociateTrialComponentResponse < Struct.new(
:trial_component_arn,
:trial_arn)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] source_arn
# The ARN of the source.
# @return [String]
#
# @!attribute [rw] destination_arn
# The Amazon Resource Name (ARN) of the destination.
# @return [String]
#
# @!attribute [rw] source_type
# The source type.
# @return [String]
#
# @!attribute [rw] destination_type
# The destination type.
# @return [String]
#
# @!attribute [rw] association_type
# The type of the association.
# @return [String]
#
# @!attribute [rw] source_name
# The name of the source.
# @return [String]
#
# @!attribute [rw] destination_name
# The name of the destination.
# @return [String]
#
# @!attribute [rw] creation_time
# When the association was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AssociationSummary AWS API Documentation
#
class AssociationSummary < Struct.new(
:source_arn,
:destination_arn,
:source_type,
:destination_type,
:association_type,
:source_name,
:destination_name,
:creation_time,
:created_by)
SENSITIVE = []
include Aws::Structure
end
# Configures the behavior of the client used by SageMaker to interact
# with the model container during asynchronous inference.
#
# @!attribute [rw] max_concurrent_invocations_per_instance
# The maximum number of concurrent requests sent by the SageMaker
# client to the model container. If no value is provided, SageMaker
# chooses an optimal value.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AsyncInferenceClientConfig AWS API Documentation
#
class AsyncInferenceClientConfig < Struct.new(
:max_concurrent_invocations_per_instance)
SENSITIVE = []
include Aws::Structure
end
# Specifies configuration for how an endpoint performs asynchronous
# inference.
#
# @!attribute [rw] client_config
# Configures the behavior of the client used by SageMaker to interact
# with the model container during asynchronous inference.
# @return [Types::AsyncInferenceClientConfig]
#
# @!attribute [rw] output_config
# Specifies the configuration for asynchronous inference invocation
# outputs.
# @return [Types::AsyncInferenceOutputConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AsyncInferenceConfig AWS API Documentation
#
class AsyncInferenceConfig < Struct.new(
:client_config,
:output_config)
SENSITIVE = []
include Aws::Structure
end
# Specifies the configuration for notifications of inference results for
# asynchronous inference.
#
# @!attribute [rw] success_topic
# Amazon SNS topic to post a notification to when inference completes
# successfully. If no topic is provided, no notification is sent on
# success.
# @return [String]
#
# @!attribute [rw] error_topic
# Amazon SNS topic to post a notification to when inference fails. If
# no topic is provided, no notification is sent on failure.
# @return [String]
#
# @!attribute [rw] include_inference_response_in
# The Amazon SNS topics where you want the inference response to be
# included.
#
# <note markdown="1"> The inference response is included only if the response size is less
# than or equal to 128 KB.
#
# </note>
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AsyncInferenceNotificationConfig AWS API Documentation
#
class AsyncInferenceNotificationConfig < Struct.new(
:success_topic,
:error_topic,
:include_inference_response_in)
SENSITIVE = []
include Aws::Structure
end
# Specifies the configuration for asynchronous inference invocation
# outputs.
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that SageMaker uses to encrypt the asynchronous inference
# output in Amazon S3.
# @return [String]
#
# @!attribute [rw] s3_output_path
# The Amazon S3 location to upload inference responses to.
# @return [String]
#
# @!attribute [rw] notification_config
# Specifies the configuration for notifications of inference results
# for asynchronous inference.
# @return [Types::AsyncInferenceNotificationConfig]
#
# @!attribute [rw] s3_failure_path
# The Amazon S3 location to upload failure inference responses to.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AsyncInferenceOutputConfig AWS API Documentation
#
class AsyncInferenceOutputConfig < Struct.new(
:kms_key_id,
:s3_output_path,
:notification_config,
:s3_failure_path)
SENSITIVE = []
include Aws::Structure
end
# Configuration for Athena Dataset Definition input.
#
# @!attribute [rw] catalog
# The name of the data catalog used in Athena query execution.
# @return [String]
#
# @!attribute [rw] database
# The name of the database used in the Athena query execution.
# @return [String]
#
# @!attribute [rw] query_string
# The SQL query statements, to be executed.
# @return [String]
#
# @!attribute [rw] work_group
# The name of the workgroup in which the Athena query is being
# started.
# @return [String]
#
# @!attribute [rw] output_s3_uri
# The location in Amazon S3 where Athena query results are stored.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt data generated from
# an Athena query execution.
# @return [String]
#
# @!attribute [rw] output_format
# The data storage format for Athena query results.
# @return [String]
#
# @!attribute [rw] output_compression
# The compression used for Athena query results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AthenaDatasetDefinition AWS API Documentation
#
class AthenaDatasetDefinition < Struct.new(
:catalog,
:database,
:query_string,
:work_group,
:output_s3_uri,
:kms_key_id,
:output_format,
:output_compression)
SENSITIVE = []
include Aws::Structure
end
# The collection of algorithms run on a dataset for training the model
# candidates of an Autopilot job.
#
# @!attribute [rw] auto_ml_algorithms
# The selection of algorithms run on a dataset to train the model
# candidates of an Autopilot job.
#
# <note markdown="1"> Selected algorithms must belong to the list corresponding to the
# training mode set in [AutoMLJobConfig.Mode][1] (`ENSEMBLING` or
# `HYPERPARAMETER_TUNING`). Choose a minimum of 1 algorithm.
#
# </note>
#
# * In `ENSEMBLING` mode:
#
# * "catboost"
#
# * "extra-trees"
#
# * "fastai"
#
# * "lightgbm"
#
# * "linear-learner"
#
# * "nn-torch"
#
# * "randomforest"
#
# * "xgboost"
#
# * In `HYPERPARAMETER_TUNING` mode:
#
# * "linear-learner"
#
# * "mlp"
#
# * "xgboost"
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobConfig.html#sagemaker-Type-AutoMLJobConfig-Mode
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLAlgorithmConfig AWS API Documentation
#
class AutoMLAlgorithmConfig < Struct.new(
:auto_ml_algorithms)
SENSITIVE = []
include Aws::Structure
end
# Information about a candidate produced by an AutoML training job,
# including its status, steps, and other properties.
#
# @!attribute [rw] candidate_name
# The name of the candidate.
# @return [String]
#
# @!attribute [rw] final_auto_ml_job_objective_metric
# The best candidate result from an AutoML training job.
# @return [Types::FinalAutoMLJobObjectiveMetric]
#
# @!attribute [rw] objective_status
# The objective's status.
# @return [String]
#
# @!attribute [rw] candidate_steps
# Information about the candidate's steps.
# @return [Array<Types::AutoMLCandidateStep>]
#
# @!attribute [rw] candidate_status
# The candidate's status.
# @return [String]
#
# @!attribute [rw] inference_containers
# Information about the recommended inference container definitions.
# @return [Array<Types::AutoMLContainerDefinition>]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] end_time
# The end time.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last modified time.
# @return [Time]
#
# @!attribute [rw] failure_reason
# The failure reason.
# @return [String]
#
# @!attribute [rw] candidate_properties
# The properties of an AutoML candidate job.
# @return [Types::CandidateProperties]
#
# @!attribute [rw] inference_container_definitions
# The mapping of all supported processing unit (CPU, GPU, etc...) to
# inference container definitions for the candidate. This field is
# populated for the V2 API only (for example, for jobs created by
# calling `CreateAutoMLJobV2`).
# @return [Hash<String,Array<Types::AutoMLContainerDefinition>>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLCandidate AWS API Documentation
#
class AutoMLCandidate < Struct.new(
:candidate_name,
:final_auto_ml_job_objective_metric,
:objective_status,
:candidate_steps,
:candidate_status,
:inference_containers,
:creation_time,
:end_time,
:last_modified_time,
:failure_reason,
:candidate_properties,
:inference_container_definitions)
SENSITIVE = []
include Aws::Structure
end
# Stores the configuration information for how a candidate is generated
# (optional).
#
# @!attribute [rw] feature_specification_s3_uri
# A URL to the Amazon S3 data source containing selected features from
# the input data source to run an Autopilot job. You can input
# `FeatureAttributeNames` (optional) in JSON format as shown below:
#
# `\{ "FeatureAttributeNames":["col1", "col2", ...] \}`.
#
# You can also specify the data type of the feature (optional) in the
# format shown below:
#
# `\{ "FeatureDataTypes":\{"col1":"numeric", "col2":"categorical" ...
# \} \}`
#
# <note markdown="1"> These column keys may not include the target column.
#
# </note>
#
# In ensembling mode, Autopilot only supports the following data
# types: `numeric`, `categorical`, `text`, and `datetime`. In HPO
# mode, Autopilot can support `numeric`, `categorical`, `text`,
# `datetime`, and `sequence`.
#
# If only `FeatureDataTypes` is provided, the column keys (`col1`,
# `col2`,..) should be a subset of the column names in the input data.
#
# If both `FeatureDataTypes` and `FeatureAttributeNames` are provided,
# then the column keys should be a subset of the column names provided
# in `FeatureAttributeNames`.
#
# The key name `FeatureAttributeNames` is fixed. The values listed in
# `["col1", "col2", ...]` are case sensitive and should be a list of
# strings containing unique values that are a subset of the column
# names in the input data. The list of columns provided must not
# include the target column.
# @return [String]
#
# @!attribute [rw] algorithms_config
# Stores the configuration information for the selection of algorithms
# used to train the model candidates.
#
# The list of available algorithms to choose from depends on the
# training mode set in [ `AutoMLJobConfig.Mode` ][1].
#
# * `AlgorithmsConfig` should not be set in `AUTO` training mode.
#
# * When `AlgorithmsConfig` is provided, one `AutoMLAlgorithms`
# attribute must be set and one only.
#
# If the list of algorithms provided as values for
# `AutoMLAlgorithms` is empty, `AutoMLCandidateGenerationConfig`
# uses the full set of algorithms for the given training mode.
#
# * When `AlgorithmsConfig` is not provided,
# `AutoMLCandidateGenerationConfig` uses the full set of algorithms
# for the given training mode.
#
# For the list of all algorithms per training mode, see [
# AutoMLAlgorithmConfig][2].
#
# For more information on each algorithm, see the [Algorithm
# support][3] section in Autopilot developer guide.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-support
# @return [Array<Types::AutoMLAlgorithmConfig>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLCandidateGenerationConfig AWS API Documentation
#
class AutoMLCandidateGenerationConfig < Struct.new(
:feature_specification_s3_uri,
:algorithms_config)
SENSITIVE = []
include Aws::Structure
end
# Information about the steps for a candidate and what step it is
# working on.
#
# @!attribute [rw] candidate_step_type
# Whether the candidate is at the transform, training, or processing
# step.
# @return [String]
#
# @!attribute [rw] candidate_step_arn
# The ARN for the candidate's step.
# @return [String]
#
# @!attribute [rw] candidate_step_name
# The name for the candidate's step.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLCandidateStep AWS API Documentation
#
class AutoMLCandidateStep < Struct.new(
:candidate_step_type,
:candidate_step_arn,
:candidate_step_name)
SENSITIVE = []
include Aws::Structure
end
# A channel is a named input source that training algorithms can
# consume. The validation dataset size is limited to less than 2 GB. The
# training dataset size must be less than 100 GB. For more information,
# see [ Channel][1].
#
# <note markdown="1"> A validation dataset must contain the same headers as the training
# dataset.
#
# </note>
#
#
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Channel.html
#
# @!attribute [rw] data_source
# The data source for an AutoML channel.
# @return [Types::AutoMLDataSource]
#
# @!attribute [rw] compression_type
# You can use `Gzip` or `None`. The default value is `None`.
# @return [String]
#
# @!attribute [rw] target_attribute_name
# The name of the target variable in supervised learning, usually
# represented by 'y'.
# @return [String]
#
# @!attribute [rw] content_type
# The content type of the data from the input source. You can use
# `text/csv;header=present` or `x-application/vnd.amazon+parquet`. The
# default value is `text/csv;header=present`.
# @return [String]
#
# @!attribute [rw] channel_type
# The channel type (optional) is an `enum` string. The default value
# is `training`. Channels for training and validation must share the
# same `ContentType` and `TargetAttributeName`. For information on
# specifying training and validation channel types, see [How to
# specify training and validation datasets][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-data-sources-training-or-validation
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLChannel AWS API Documentation
#
class AutoMLChannel < Struct.new(
:data_source,
:compression_type,
:target_attribute_name,
:content_type,
:channel_type)
SENSITIVE = []
include Aws::Structure
end
# A list of container definitions that describe the different containers
# that make up an AutoML candidate. For more information, see [
# ContainerDefinition][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
#
# @!attribute [rw] image
# The Amazon Elastic Container Registry (Amazon ECR) path of the
# container. For more information, see [ ContainerDefinition][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
# @return [String]
#
# @!attribute [rw] model_data_url
# The location of the model artifacts. For more information, see [
# ContainerDefinition][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
# @return [String]
#
# @!attribute [rw] environment
# The environment variables to set in the container. For more
# information, see [ ContainerDefinition][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLContainerDefinition AWS API Documentation
#
class AutoMLContainerDefinition < Struct.new(
:image,
:model_data_url,
:environment)
SENSITIVE = []
include Aws::Structure
end
# The data source for the Autopilot job.
#
# @!attribute [rw] s3_data_source
# The Amazon S3 location of the input data.
# @return [Types::AutoMLS3DataSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLDataSource AWS API Documentation
#
class AutoMLDataSource < Struct.new(
:s3_data_source)
SENSITIVE = []
include Aws::Structure
end
# This structure specifies how to split the data into train and
# validation datasets.
#
# If you are using the V1 API (for example `CreateAutoMLJob`) or the V2
# API for Natural Language Processing problems (for example
# `CreateAutoMLJobV2` with a `TextClassificationJobConfig` problem
# type), the validation and training datasets must contain the same
# headers. Also, for V1 API jobs, the validation dataset must be less
# than 2 GB in size.
#
# @!attribute [rw] validation_fraction
# The validation fraction (optional) is a float that specifies the
# portion of the training dataset to be used for validation. The
# default value is 0.2, and values must be greater than 0 and less
# than 1. We recommend setting this value to be less than 0.5.
# @return [Float]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLDataSplitConfig AWS API Documentation
#
class AutoMLDataSplitConfig < Struct.new(
:validation_fraction)
SENSITIVE = []
include Aws::Structure
end
# The artifacts that are generated during an AutoML job.
#
# @!attribute [rw] candidate_definition_notebook_location
# The URL of the notebook location.
# @return [String]
#
# @!attribute [rw] data_exploration_notebook_location
# The URL of the notebook location.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobArtifacts AWS API Documentation
#
class AutoMLJobArtifacts < Struct.new(
:candidate_definition_notebook_location,
:data_exploration_notebook_location)
SENSITIVE = []
include Aws::Structure
end
# A channel is a named input source that training algorithms can
# consume. This channel is used for the non tabular training data of an
# AutoML job using the V2 API. For tabular training data, see [
# AutoMLChannel][1]. For more information, see [ Channel][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLChannel.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Channel.html
#
# @!attribute [rw] channel_type
# The type of channel. Defines whether the data are used for training
# or validation. The default value is `training`. Channels for
# `training` and `validation` must share the same `ContentType`
# @return [String]
#
# @!attribute [rw] content_type
# The content type of the data from the input source. The following
# are the allowed content types for different problems:
#
# * ImageClassification: `image/png`, `image/jpeg`, `image/*`
#
# * TextClassification: `text/csv;header=present`
# @return [String]
#
# @!attribute [rw] compression_type
# The allowed compression types depend on the input format. We allow
# the compression type `Gzip` for `S3Prefix` inputs only. For all
# other inputs, the compression type should be `None`. If no
# compression type is provided, we default to `None`.
# @return [String]
#
# @!attribute [rw] data_source
# The data source for an AutoML channel.
# @return [Types::AutoMLDataSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobChannel AWS API Documentation
#
class AutoMLJobChannel < Struct.new(
:channel_type,
:content_type,
:compression_type,
:data_source)
SENSITIVE = []
include Aws::Structure
end
# How long a job is allowed to run, or how many candidates a job is
# allowed to generate.
#
# @!attribute [rw] max_candidates
# The maximum number of times a training job is allowed to run.
#
# For V2 jobs (jobs created by calling `CreateAutoMLJobV2`), the
# supported value is 1.
# @return [Integer]
#
# @!attribute [rw] max_runtime_per_training_job_in_seconds
# The maximum time, in seconds, that each training job executed inside
# hyperparameter tuning is allowed to run as part of a hyperparameter
# tuning job. For more information, see the [StoppingCondition][1]
# used by the [CreateHyperParameterTuningJob][2] action.
#
# For V2 jobs (jobs created by calling `CreateAutoMLJobV2`), this
# field controls the runtime of the job candidate.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_StoppingCondition.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateHyperParameterTuningJob.html
# @return [Integer]
#
# @!attribute [rw] max_auto_ml_job_runtime_in_seconds
# The maximum runtime, in seconds, an AutoML job has to complete.
#
# If an AutoML job exceeds the maximum runtime, the job is stopped
# automatically and its processing is ended gracefully. The AutoML job
# identifies the best model whose training was completed and marks it
# as the best-performing model. Any unfinished steps of the job, such
# as automatic one-click Autopilot model deployment, are not
# completed.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobCompletionCriteria AWS API Documentation
#
class AutoMLJobCompletionCriteria < Struct.new(
:max_candidates,
:max_runtime_per_training_job_in_seconds,
:max_auto_ml_job_runtime_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings used for an AutoML job.
#
# @!attribute [rw] completion_criteria
# How long an AutoML job is allowed to run, or how many candidates a
# job is allowed to generate.
# @return [Types::AutoMLJobCompletionCriteria]
#
# @!attribute [rw] security_config
# The security configuration for traffic encryption or Amazon VPC
# settings.
# @return [Types::AutoMLSecurityConfig]
#
# @!attribute [rw] data_split_config
# The configuration for splitting the input training dataset.
#
# Type: AutoMLDataSplitConfig
# @return [Types::AutoMLDataSplitConfig]
#
# @!attribute [rw] candidate_generation_config
# The configuration for generating a candidate for an AutoML job
# (optional).
# @return [Types::AutoMLCandidateGenerationConfig]
#
# @!attribute [rw] mode
# The method that Autopilot uses to train the data. You can either
# specify the mode manually or let Autopilot choose for you based on
# the dataset size by selecting `AUTO`. In `AUTO` mode, Autopilot
# chooses `ENSEMBLING` for datasets smaller than 100 MB, and
# `HYPERPARAMETER_TUNING` for larger ones.
#
# The `ENSEMBLING` mode uses a multi-stack ensemble model to predict
# classification and regression tasks directly from your dataset. This
# machine learning mode combines several base models to produce an
# optimal predictive model. It then uses a stacking ensemble method to
# combine predictions from contributing members. A multi-stack
# ensemble model can provide better performance over a single model by
# combining the predictive capabilities of multiple models. See
# [Autopilot algorithm support][1] for a list of algorithms supported
# by `ENSEMBLING` mode.
#
# The `HYPERPARAMETER_TUNING` (HPO) mode uses the best hyperparameters
# to train the best version of a model. HPO automatically selects an
# algorithm for the type of problem you want to solve. Then HPO finds
# the best hyperparameters according to your objective metric. See
# [Autopilot algorithm support][1] for a list of algorithms supported
# by `HYPERPARAMETER_TUNING` mode.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-algorithm-suppprt
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobConfig AWS API Documentation
#
class AutoMLJobConfig < Struct.new(
:completion_criteria,
:security_config,
:data_split_config,
:candidate_generation_config,
:mode)
SENSITIVE = []
include Aws::Structure
end
# Specifies a metric to minimize or maximize as the objective of a job.
# V2 API jobs (for example jobs created by calling `CreateAutoMLJobV2`),
# support `Accuracy` only.
#
# @!attribute [rw] metric_name
# The name of the objective metric used to measure the predictive
# quality of a machine learning system. This metric is optimized
# during training to provide the best estimate for model parameter
# values from data.
#
# Here are the options:
#
# Accuracy
#
# : The ratio of the number of correctly classified items to the total
# number of (correctly and incorrectly) classified items. It is used
# for both binary and multiclass classification. Accuracy measures
# how close the predicted class values are to the actual values.
# Values for accuracy metrics vary between zero (0) and one (1). A
# value of 1 indicates perfect accuracy, and 0 indicates perfect
# inaccuracy.
#
# AUC
#
# : The area under the curve (AUC) metric is used to compare and
# evaluate binary classification by algorithms that return
# probabilities, such as logistic regression. To map the
# probabilities into classifications, these are compared against a
# threshold value.
#
# The relevant curve is the receiver operating characteristic curve
# (ROC curve). The ROC curve plots the true positive rate (TPR) of
# predictions (or recall) against the false positive rate (FPR) as a
# function of the threshold value, above which a prediction is
# considered positive. Increasing the threshold results in fewer
# false positives, but more false negatives.
#
# AUC is the area under this ROC curve. Therefore, AUC provides an
# aggregated measure of the model performance across all possible
# classification thresholds. AUC scores vary between 0 and 1. A
# score of 1 indicates perfect accuracy, and a score of one half
# (0.5) indicates that the prediction is not better than a random
# classifier.
#
# BalancedAccuracy
#
# : `BalancedAccuracy` is a metric that measures the ratio of accurate
# predictions to all predictions. This ratio is calculated after
# normalizing true positives (TP) and true negatives (TN) by the
# total number of positive (P) and negative (N) values. It is used
# in both binary and multiclass classification and is defined as
# follows: 0.5*((TP/P)+(TN/N)), with values ranging from 0 to 1.
# `BalancedAccuracy` gives a better measure of accuracy when the
# number of positives or negatives differ greatly from each other in
# an imbalanced dataset. For example, when only 1% of email is spam.
#
# F1
#
# : The `F1` score is the harmonic mean of the precision and recall,
# defined as follows: F1 = 2 * (precision * recall) / (precision +
# recall). It is used for binary classification into classes
# traditionally referred to as positive and negative. Predictions
# are said to be true when they match their actual (correct) class,
# and false when they do not.
#
# Precision is the ratio of the true positive predictions to all
# positive predictions, and it includes the false positives in a
# dataset. Precision measures the quality of the prediction when it
# predicts the positive class.
#
# Recall (or sensitivity) is the ratio of the true positive
# predictions to all actual positive instances. Recall measures how
# completely a model predicts the actual class members in a dataset.
#
# F1 scores vary between 0 and 1. A score of 1 indicates the best
# possible performance, and 0 indicates the worst.
#
# F1macro
#
# : The `F1macro` score applies F1 scoring to multiclass
# classification problems. It does this by calculating the precision
# and recall, and then taking their harmonic mean to calculate the
# F1 score for each class. Lastly, the F1macro averages the
# individual scores to obtain the `F1macro` score. `F1macro` scores
# vary between 0 and 1. A score of 1 indicates the best possible
# performance, and 0 indicates the worst.
#
# MAE
#
# : The mean absolute error (MAE) is a measure of how different the
# predicted and actual values are, when they're averaged over all
# values. MAE is commonly used in regression analysis to understand
# model prediction error. If there is linear regression, MAE
# represents the average distance from a predicted line to the
# actual value. MAE is defined as the sum of absolute errors divided
# by the number of observations. Values range from 0 to infinity,
# with smaller numbers indicating a better model fit to the data.
#
# MSE
#
# : The mean squared error (MSE) is the average of the squared
# differences between the predicted and actual values. It is used
# for regression. MSE values are always positive. The better a model
# is at predicting the actual values, the smaller the MSE value is
#
# Precision
#
# : Precision measures how well an algorithm predicts the true
# positives (TP) out of all of the positives that it identifies. It
# is defined as follows: Precision = TP/(TP+FP), with values ranging
# from zero (0) to one (1), and is used in binary classification.
# Precision is an important metric when the cost of a false positive
# is high. For example, the cost of a false positive is very high if
# an airplane safety system is falsely deemed safe to fly. A false
# positive (FP) reflects a positive prediction that is actually
# negative in the data.
#
# PrecisionMacro
#
# : The precision macro computes precision for multiclass
# classification problems. It does this by calculating precision for
# each class and averaging scores to obtain precision for several
# classes. `PrecisionMacro` scores range from zero (0) to one (1).
# Higher scores reflect the model's ability to predict true
# positives (TP) out of all of the positives that it identifies,
# averaged across multiple classes.
#
# R2
#
# : R2, also known as the coefficient of determination, is used in
# regression to quantify how much a model can explain the variance
# of a dependent variable. Values range from one (1) to negative one
# (-1). Higher numbers indicate a higher fraction of explained
# variability. `R2` values close to zero (0) indicate that very
# little of the dependent variable can be explained by the model.
# Negative values indicate a poor fit and that the model is
# outperformed by a constant function. For linear regression, this
# is a horizontal line.
#
# Recall
#
# : Recall measures how well an algorithm correctly predicts all of
# the true positives (TP) in a dataset. A true positive is a
# positive prediction that is also an actual positive value in the
# data. Recall is defined as follows: Recall = TP/(TP+FN), with
# values ranging from 0 to 1. Higher scores reflect a better ability
# of the model to predict true positives (TP) in the data, and is
# used in binary classification.
#
# Recall is important when testing for cancer because it's used to
# find all of the true positives. A false positive (FP) reflects a
# positive prediction that is actually negative in the data. It is
# often insufficient to measure only recall, because predicting
# every output as a true positive yield a perfect recall score.
#
# RecallMacro
#
# : The RecallMacro computes recall for multiclass classification
# problems by calculating recall for each class and averaging scores
# to obtain recall for several classes. RecallMacro scores range
# from 0 to 1. Higher scores reflect the model's ability to predict
# true positives (TP) in a dataset. Whereas, a true positive
# reflects a positive prediction that is also an actual positive
# value in the data. It is often insufficient to measure only
# recall, because predicting every output as a true positive yields
# a perfect recall score.
#
# RMSE
#
# : Root mean squared error (RMSE) measures the square root of the
# squared difference between predicted and actual values, and it's
# averaged over all values. It is used in regression analysis to
# understand model prediction error. It's an important metric to
# indicate the presence of large model errors and outliers. Values
# range from zero (0) to infinity, with smaller numbers indicating a
# better model fit to the data. RMSE is dependent on scale, and
# should not be used to compare datasets of different sizes.
#
# If you do not specify a metric explicitly, the default behavior is
# to automatically use:
#
# * `MSE`: for regression.
#
# * `F1`: for binary classification
#
# * `Accuracy`: for multiclass classification.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobObjective AWS API Documentation
#
class AutoMLJobObjective < Struct.new(
:metric_name)
SENSITIVE = []
include Aws::Structure
end
# Metadata for an AutoML job step.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the AutoML job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobStepMetadata AWS API Documentation
#
class AutoMLJobStepMetadata < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# Provides a summary about an AutoML job.
#
# @!attribute [rw] auto_ml_job_name
# The name of the AutoML job you are requesting.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# The ARN of the AutoML job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_status
# The status of the AutoML job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_secondary_status
# The secondary status of the AutoML job.
# @return [String]
#
# @!attribute [rw] creation_time
# When the AutoML job was created.
# @return [Time]
#
# @!attribute [rw] end_time
# The end time of an AutoML job.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# When the AutoML job was last modified.
# @return [Time]
#
# @!attribute [rw] failure_reason
# The failure reason of an AutoML job.
# @return [String]
#
# @!attribute [rw] partial_failure_reasons
# The list of reasons for partial failures within an AutoML job.
# @return [Array<Types::AutoMLPartialFailureReason>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobSummary AWS API Documentation
#
class AutoMLJobSummary < Struct.new(
:auto_ml_job_name,
:auto_ml_job_arn,
:auto_ml_job_status,
:auto_ml_job_secondary_status,
:creation_time,
:end_time,
:last_modified_time,
:failure_reason,
:partial_failure_reasons)
SENSITIVE = []
include Aws::Structure
end
# The output data configuration.
#
# @!attribute [rw] kms_key_id
# The Key Management Service (KMS) encryption key ID.
# @return [String]
#
# @!attribute [rw] s3_output_path
# The Amazon S3 output path. Must be 128 characters or less.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLOutputDataConfig AWS API Documentation
#
class AutoMLOutputDataConfig < Struct.new(
:kms_key_id,
:s3_output_path)
SENSITIVE = []
include Aws::Structure
end
# The reason for a partial failure of an AutoML job.
#
# @!attribute [rw] partial_failure_message
# The message containing the reason for a partial failure of an AutoML
# job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLPartialFailureReason AWS API Documentation
#
class AutoMLPartialFailureReason < Struct.new(
:partial_failure_message)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings specific to the problem type used to
# configure an AutoML job using the V2 API. There must be one and only
# one config of the following type.
#
# @note AutoMLProblemTypeConfig is a union - when making an API calls you must set exactly one of the members.
#
# @note AutoMLProblemTypeConfig is a union - when returned from an API call exactly one value will be set and the returned type will be a subclass of AutoMLProblemTypeConfig corresponding to the set member.
#
# @!attribute [rw] image_classification_job_config
# Settings used to configure an AutoML job using the V2 API for the
# image classification problem type.
# @return [Types::ImageClassificationJobConfig]
#
# @!attribute [rw] text_classification_job_config
# Settings used to configure an AutoML job using the V2 API for the
# text classification problem type.
# @return [Types::TextClassificationJobConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLProblemTypeConfig AWS API Documentation
#
class AutoMLProblemTypeConfig < Struct.new(
:image_classification_job_config,
:text_classification_job_config,
:unknown)
SENSITIVE = []
include Aws::Structure
include Aws::Structure::Union
class ImageClassificationJobConfig < AutoMLProblemTypeConfig; end
class TextClassificationJobConfig < AutoMLProblemTypeConfig; end
class Unknown < AutoMLProblemTypeConfig; end
end
# Describes the Amazon S3 data source.
#
# @!attribute [rw] s3_data_type
# The data type.
#
# * If you choose `S3Prefix`, `S3Uri` identifies a key name prefix.
# SageMaker uses all objects that match the specified key name
# prefix for model training.
#
# The `S3Prefix` should have the following format:
#
# `s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER-OR-FILE`
#
# * If you choose `ManifestFile`, `S3Uri` identifies an object that is
# a manifest file containing a list of object keys that you want
# SageMaker to use for model training.
#
# A `ManifestFile` should have the format shown below:
#
# `[ \{"prefix":
# "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/DOC-EXAMPLE-PREFIX/"\},
# `
#
# `"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-1",`
#
# `"DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-2",`
#
# `... "DOC-EXAMPLE-RELATIVE-PATH/DOC-EXAMPLE-FOLDER/DATA-N" ]`
#
# * If you choose `AugmentedManifestFile`, `S3Uri` identifies an
# object that is an augmented manifest file in JSON lines format.
# This file contains the data you want to use for model training.
# `AugmentedManifestFile` is available for V2 API jobs only (for
# example, for jobs created by calling `CreateAutoMLJobV2`).
#
# Here is a minimal, single-record example of an
# `AugmentedManifestFile`:
#
# `\{"source-ref":
# "s3://DOC-EXAMPLE-BUCKET/DOC-EXAMPLE-FOLDER/cats/cat.jpg",`
#
# `"label-metadata": \{"class-name": "cat"` \\}
#
# For more information on `AugmentedManifestFile`, see [Provide
# Dataset Metadata to Training Jobs with an Augmented Manifest
# File][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/augmented-manifest.html
# @return [String]
#
# @!attribute [rw] s3_uri
# The URL to the Amazon S3 data source. The Uri refers to the Amazon
# S3 prefix or ManifestFile depending on the data type.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLS3DataSource AWS API Documentation
#
class AutoMLS3DataSource < Struct.new(
:s3_data_type,
:s3_uri)
SENSITIVE = []
include Aws::Structure
end
# Security options.
#
# @!attribute [rw] volume_kms_key_id
# The key used to encrypt stored data.
# @return [String]
#
# @!attribute [rw] enable_inter_container_traffic_encryption
# Whether to use traffic encryption between the container layers.
# @return [Boolean]
#
# @!attribute [rw] vpc_config
# The VPC configuration.
# @return [Types::VpcConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLSecurityConfig AWS API Documentation
#
class AutoMLSecurityConfig < Struct.new(
:volume_kms_key_id,
:enable_inter_container_traffic_encryption,
:vpc_config)
SENSITIVE = []
include Aws::Structure
end
# Automatic rollback configuration for handling endpoint deployment
# failures and recovery.
#
# @!attribute [rw] alarms
# List of CloudWatch alarms in your account that are configured to
# monitor metrics on an endpoint. If any alarms are tripped during a
# deployment, SageMaker rolls back the deployment.
# @return [Array<Types::Alarm>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoRollbackConfig AWS API Documentation
#
class AutoRollbackConfig < Struct.new(
:alarms)
SENSITIVE = []
include Aws::Structure
end
# Configuration to control how SageMaker captures inference data for
# batch transform jobs.
#
# @!attribute [rw] destination_s3_uri
# The Amazon S3 location being used to capture the data.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Resource Name (ARN) of a Amazon Web Services Key
# Management Service key that SageMaker uses to encrypt data on the
# storage volume attached to the ML compute instance that hosts the
# batch transform job.
#
# The KmsKeyId can be any of the following formats:
#
# * Key ID: `1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Key ARN:
# `arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Alias name: `alias/ExampleAlias`
#
# * Alias name ARN:
# `arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias`
# @return [String]
#
# @!attribute [rw] generate_inference_id
# Flag that indicates whether to append inference id to the output.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/BatchDataCaptureConfig AWS API Documentation
#
class BatchDataCaptureConfig < Struct.new(
:destination_s3_uri,
:kms_key_id,
:generate_inference_id)
SENSITIVE = []
include Aws::Structure
end
# The error code and error description associated with the resource.
#
# @!attribute [rw] error_code
# @return [String]
#
# @!attribute [rw] error_response
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/BatchDescribeModelPackageError AWS API Documentation
#
class BatchDescribeModelPackageError < Struct.new(
:error_code,
:error_response)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_arn_list
# The list of Amazon Resource Name (ARN) of the model package groups.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/BatchDescribeModelPackageInput AWS API Documentation
#
class BatchDescribeModelPackageInput < Struct.new(
:model_package_arn_list)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_summaries
# The summaries for the model package versions
# @return [Hash<String,Types::BatchDescribeModelPackageSummary>]
#
# @!attribute [rw] batch_describe_model_package_error_map
# A map of the resource and BatchDescribeModelPackageError objects
# reporting the error associated with describing the model package.
# @return [Hash<String,Types::BatchDescribeModelPackageError>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/BatchDescribeModelPackageOutput AWS API Documentation
#
class BatchDescribeModelPackageOutput < Struct.new(
:model_package_summaries,
:batch_describe_model_package_error_map)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information about the model package.
#
# @!attribute [rw] model_package_group_name
# The group name for the model package
# @return [String]
#
# @!attribute [rw] model_package_version
# The version number of a versioned model.
# @return [Integer]
#
# @!attribute [rw] model_package_arn
# The Amazon Resource Name (ARN) of the model package.
# @return [String]
#
# @!attribute [rw] model_package_description
# The description of the model package.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of the mortgage package summary.
# @return [Time]
#
# @!attribute [rw] inference_specification
# Defines how to perform inference generation after a training job is
# run.
# @return [Types::InferenceSpecification]
#
# @!attribute [rw] model_package_status
# The status of the mortgage package.
# @return [String]
#
# @!attribute [rw] model_approval_status
# The approval status of the model.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/BatchDescribeModelPackageSummary AWS API Documentation
#
class BatchDescribeModelPackageSummary < Struct.new(
:model_package_group_name,
:model_package_version,
:model_package_arn,
:model_package_description,
:creation_time,
:inference_specification,
:model_package_status,
:model_approval_status)
SENSITIVE = []
include Aws::Structure
end
# Input object for the batch transform job.
#
# @!attribute [rw] data_captured_destination_s3_uri
# The Amazon S3 location being used to capture the data.
# @return [String]
#
# @!attribute [rw] dataset_format
# The dataset format for your batch transform job.
# @return [Types::MonitoringDatasetFormat]
#
# @!attribute [rw] local_path
# Path to the filesystem where the batch transform data is available
# to the container.
# @return [String]
#
# @!attribute [rw] s3_input_mode
# Whether the `Pipe` or `File` is used as the input mode for
# transferring data for the monitoring job. `Pipe` mode is recommended
# for large datasets. `File` mode is useful for small files that fit
# in memory. Defaults to `File`.
# @return [String]
#
# @!attribute [rw] s3_data_distribution_type
# Whether input data distributed in Amazon S3 is fully replicated or
# sharded by an S3 key. Defaults to `FullyReplicated`
# @return [String]
#
# @!attribute [rw] features_attribute
# The attributes of the input data that are the input features.
# @return [String]
#
# @!attribute [rw] inference_attribute
# The attribute of the input data that represents the ground truth
# label.
# @return [String]
#
# @!attribute [rw] probability_attribute
# In a classification problem, the attribute that represents the class
# probability.
# @return [String]
#
# @!attribute [rw] probability_threshold_attribute
# The threshold for the class probability to be evaluated as a
# positive result.
# @return [Float]
#
# @!attribute [rw] start_time_offset
# If specified, monitoring jobs substract this time from the start
# time. For information about using offsets for scheduling monitoring
# jobs, see [Schedule Model Quality Monitoring Jobs][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html
# @return [String]
#
# @!attribute [rw] end_time_offset
# If specified, monitoring jobs substract this time from the end time.
# For information about using offsets for scheduling monitoring jobs,
# see [Schedule Model Quality Monitoring Jobs][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/BatchTransformInput AWS API Documentation
#
class BatchTransformInput < Struct.new(
:data_captured_destination_s3_uri,
:dataset_format,
:local_path,
:s3_input_mode,
:s3_data_distribution_type,
:features_attribute,
:inference_attribute,
:probability_attribute,
:probability_threshold_attribute,
:start_time_offset,
:end_time_offset)
SENSITIVE = []
include Aws::Structure
end
# A structure that keeps track of which training jobs launched by your
# hyperparameter tuning job are not improving model performance as
# evaluated against an objective function.
#
# @!attribute [rw] max_number_of_training_jobs_not_improving
# The number of training jobs that have failed to improve model
# performance by 1% or greater over prior training jobs as evaluated
# against an objective function.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/BestObjectiveNotImproving AWS API Documentation
#
class BestObjectiveNotImproving < Struct.new(
:max_number_of_training_jobs_not_improving)
SENSITIVE = []
include Aws::Structure
end
# Contains bias metrics for a model.
#
# @!attribute [rw] report
# The bias report for a model
# @return [Types::MetricsSource]
#
# @!attribute [rw] pre_training_report
# The pre-training bias report for a model.
# @return [Types::MetricsSource]
#
# @!attribute [rw] post_training_report
# The post-training bias report for a model.
# @return [Types::MetricsSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Bias AWS API Documentation
#
class Bias < Struct.new(
:report,
:pre_training_report,
:post_training_report)
SENSITIVE = []
include Aws::Structure
end
# Update policy for a blue/green deployment. If this update policy is
# specified, SageMaker creates a new fleet during the deployment while
# maintaining the old fleet. SageMaker flips traffic to the new fleet
# according to the specified traffic routing configuration. Only one
# update policy should be used in the deployment configuration. If no
# update policy is specified, SageMaker uses a blue/green deployment
# strategy with all at once traffic shifting by default.
#
# @!attribute [rw] traffic_routing_configuration
# Defines the traffic routing strategy to shift traffic from the old
# fleet to the new fleet during an endpoint deployment.
# @return [Types::TrafficRoutingConfig]
#
# @!attribute [rw] termination_wait_in_seconds
# Additional waiting time in seconds after the completion of an
# endpoint deployment before terminating the old endpoint fleet.
# Default is 0.
# @return [Integer]
#
# @!attribute [rw] maximum_execution_timeout_in_seconds
# Maximum execution timeout for the deployment. Note that the timeout
# value should be larger than the total waiting time specified in
# `TerminationWaitInSeconds` and `WaitIntervalInSeconds`.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/BlueGreenUpdatePolicy AWS API Documentation
#
class BlueGreenUpdatePolicy < Struct.new(
:traffic_routing_configuration,
:termination_wait_in_seconds,
:maximum_execution_timeout_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# Details on the cache hit of a pipeline execution step.
#
# @!attribute [rw] source_pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CacheHitResult AWS API Documentation
#
class CacheHitResult < Struct.new(
:source_pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# Metadata about a callback step.
#
# @!attribute [rw] callback_token
# The pipeline generated token from the Amazon SQS queue.
# @return [String]
#
# @!attribute [rw] sqs_queue_url
# The URL of the Amazon Simple Queue Service (Amazon SQS) queue used
# by the callback step.
# @return [String]
#
# @!attribute [rw] output_parameters
# A list of the output parameters of the callback step.
# @return [Array<Types::OutputParameter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CallbackStepMetadata AWS API Documentation
#
class CallbackStepMetadata < Struct.new(
:callback_token,
:sqs_queue_url,
:output_parameters)
SENSITIVE = []
include Aws::Structure
end
# The location of artifacts for an AutoML candidate job.
#
# @!attribute [rw] explainability
# The Amazon S3 prefix to the explainability artifacts generated for
# the AutoML candidate.
# @return [String]
#
# @!attribute [rw] model_insights
# The Amazon S3 prefix to the model insight artifacts generated for
# the AutoML candidate.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CandidateArtifactLocations AWS API Documentation
#
class CandidateArtifactLocations < Struct.new(
:explainability,
:model_insights)
SENSITIVE = []
include Aws::Structure
end
# The properties of an AutoML candidate job.
#
# @!attribute [rw] candidate_artifact_locations
# The Amazon S3 prefix to the artifacts generated for an AutoML
# candidate.
# @return [Types::CandidateArtifactLocations]
#
# @!attribute [rw] candidate_metrics
# Information about the candidate metrics for an AutoML job.
# @return [Array<Types::MetricDatum>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CandidateProperties AWS API Documentation
#
class CandidateProperties < Struct.new(
:candidate_artifact_locations,
:candidate_metrics)
SENSITIVE = []
include Aws::Structure
end
# The SageMaker Canvas application settings.
#
# @!attribute [rw] time_series_forecasting_settings
# Time series forecast settings for the Canvas application.
# @return [Types::TimeSeriesForecastingSettings]
#
# @!attribute [rw] model_register_settings
# The model registry settings for the SageMaker Canvas application.
# @return [Types::ModelRegisterSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CanvasAppSettings AWS API Documentation
#
class CanvasAppSettings < Struct.new(
:time_series_forecasting_settings,
:model_register_settings)
SENSITIVE = []
include Aws::Structure
end
# Specifies the endpoint capacity to activate for production.
#
# @!attribute [rw] type
# Specifies the endpoint capacity type.
#
# * `INSTANCE_COUNT`: The endpoint activates based on the number of
# instances.
#
# * `CAPACITY_PERCENT`: The endpoint activates based on the specified
# percentage of capacity.
# @return [String]
#
# @!attribute [rw] value
# Defines the capacity size, either as a number of instances or a
# capacity percentage.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CapacitySize AWS API Documentation
#
class CapacitySize < Struct.new(
:type,
:value)
SENSITIVE = []
include Aws::Structure
end
# Configuration specifying how to treat different headers. If no headers
# are specified SageMaker will by default base64 encode when capturing
# the data.
#
# @!attribute [rw] csv_content_types
# The list of all content type headers that SageMaker will treat as
# CSV and capture accordingly.
# @return [Array<String>]
#
# @!attribute [rw] json_content_types
# The list of all content type headers that SageMaker will treat as
# JSON and capture accordingly.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CaptureContentTypeHeader AWS API Documentation
#
class CaptureContentTypeHeader < Struct.new(
:csv_content_types,
:json_content_types)
SENSITIVE = []
include Aws::Structure
end
# Specifies data Model Monitor will capture.
#
# @!attribute [rw] capture_mode
# Specify the boundary of data to capture.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CaptureOption AWS API Documentation
#
class CaptureOption < Struct.new(
:capture_mode)
SENSITIVE = []
include Aws::Structure
end
# Environment parameters you want to benchmark your load test against.
#
# @!attribute [rw] name
# The Name of the environment variable.
# @return [String]
#
# @!attribute [rw] value
# The list of values you can pass.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CategoricalParameter AWS API Documentation
#
class CategoricalParameter < Struct.new(
:name,
:value)
SENSITIVE = []
include Aws::Structure
end
# A list of categorical hyperparameters to tune.
#
# @!attribute [rw] name
# The name of the categorical hyperparameter to tune.
# @return [String]
#
# @!attribute [rw] values
# A list of the categories for the hyperparameter.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CategoricalParameterRange AWS API Documentation
#
class CategoricalParameterRange < Struct.new(
:name,
:values)
SENSITIVE = []
include Aws::Structure
end
# Defines the possible values for a categorical hyperparameter.
#
# @!attribute [rw] values
# The allowed categories for the hyperparameter.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CategoricalParameterRangeSpecification AWS API Documentation
#
class CategoricalParameterRangeSpecification < Struct.new(
:values)
SENSITIVE = []
include Aws::Structure
end
# A channel is a named input source that training algorithms can
# consume.
#
# @!attribute [rw] channel_name
# The name of the channel.
# @return [String]
#
# @!attribute [rw] data_source
# The location of the channel data.
# @return [Types::DataSource]
#
# @!attribute [rw] content_type
# The MIME type of the data.
# @return [String]
#
# @!attribute [rw] compression_type
# If training data is compressed, the compression type. The default
# value is `None`. `CompressionType` is used only in Pipe input mode.
# In File mode, leave this field unset or set it to None.
# @return [String]
#
# @!attribute [rw] record_wrapper_type
# Specify RecordIO as the value when input data is in raw format but
# the training algorithm requires the RecordIO format. In this case,
# SageMaker wraps each individual S3 object in a RecordIO record. If
# the input data is already in RecordIO format, you don't need to set
# this attribute. For more information, see [Create a Dataset Using
# RecordIO][1].
#
# In File mode, leave this field unset or set it to None.
#
#
#
# [1]: https://mxnet.apache.org/api/architecture/note_data_loading#data-format
# @return [String]
#
# @!attribute [rw] input_mode
# (Optional) The input mode to use for the data channel in a training
# job. If you don't set a value for `InputMode`, SageMaker uses the
# value set for `TrainingInputMode`. Use this parameter to override
# the `TrainingInputMode` setting in a [AlgorithmSpecification][1]
# request when you have a channel that needs a different input mode
# from the training job's general setting. To download the data from
# Amazon Simple Storage Service (Amazon S3) to the provisioned ML
# storage volume, and mount the directory to a Docker volume, use
# `File` input mode. To stream data directly from Amazon S3 to the
# container, choose `Pipe` input mode.
#
# To use a model for incremental training, choose `File` input model.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AlgorithmSpecification.html
# @return [String]
#
# @!attribute [rw] shuffle_config
# A configuration for a shuffle option for input data in a channel. If
# you use `S3Prefix` for `S3DataType`, this shuffles the results of
# the S3 key prefix matches. If you use `ManifestFile`, the order of
# the S3 object references in the `ManifestFile` is shuffled. If you
# use `AugmentedManifestFile`, the order of the JSON lines in the
# `AugmentedManifestFile` is shuffled. The shuffling order is
# determined using the `Seed` value.
#
# For Pipe input mode, 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, it helps reduce bias and possible
# overfitting. In a multi-node training job when ShuffleConfig is
# combined with `S3DataDistributionType` of `ShardedByS3Key`, 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.
# @return [Types::ShuffleConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Channel AWS API Documentation
#
class Channel < Struct.new(
:channel_name,
:data_source,
:content_type,
:compression_type,
:record_wrapper_type,
:input_mode,
:shuffle_config)
SENSITIVE = []
include Aws::Structure
end
# Defines a named input source, called a channel, to be used by an
# algorithm.
#
# @!attribute [rw] name
# The name of the channel.
# @return [String]
#
# @!attribute [rw] description
# A brief description of the channel.
# @return [String]
#
# @!attribute [rw] is_required
# Indicates whether the channel is required by the algorithm.
# @return [Boolean]
#
# @!attribute [rw] supported_content_types
# The supported MIME types for the data.
# @return [Array<String>]
#
# @!attribute [rw] supported_compression_types
# The allowed compression types, if data compression is used.
# @return [Array<String>]
#
# @!attribute [rw] supported_input_modes
# The allowed input mode, either FILE or PIPE.
#
# In FILE mode, Amazon SageMaker copies the data from the input source
# onto the local Amazon Elastic Block Store (Amazon EBS) volumes
# before starting your training algorithm. This is the most commonly
# used input mode.
#
# In PIPE mode, Amazon SageMaker streams input data from the source
# directly to your algorithm without using the EBS volume.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ChannelSpecification AWS API Documentation
#
class ChannelSpecification < Struct.new(
:name,
:description,
:is_required,
:supported_content_types,
:supported_compression_types,
:supported_input_modes)
SENSITIVE = []
include Aws::Structure
end
# Contains information about the output location for managed spot
# training checkpoint data.
#
# @!attribute [rw] s3_uri
# Identifies the S3 path where you want SageMaker to store
# checkpoints. For example, `s3://bucket-name/key-name-prefix`.
# @return [String]
#
# @!attribute [rw] local_path
# (Optional) The local directory where checkpoints are written. The
# default directory is `/opt/ml/checkpoints/`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CheckpointConfig AWS API Documentation
#
class CheckpointConfig < Struct.new(
:s3_uri,
:local_path)
SENSITIVE = []
include Aws::Structure
end
# The container for the metadata for the ClarifyCheck step. For more
# information, see the topic on [ClarifyCheck step][1] in the *Amazon
# SageMaker Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/build-and-manage-steps.html#step-type-clarify-check
#
# @!attribute [rw] check_type
# The type of the Clarify Check step
# @return [String]
#
# @!attribute [rw] baseline_used_for_drift_check_constraints
# The Amazon S3 URI of baseline constraints file to be used for the
# drift check.
# @return [String]
#
# @!attribute [rw] calculated_baseline_constraints
# The Amazon S3 URI of the newly calculated baseline constraints file.
# @return [String]
#
# @!attribute [rw] model_package_group_name
# The model package group name.
# @return [String]
#
# @!attribute [rw] violation_report
# The Amazon S3 URI of the violation report if violations are
# detected.
# @return [String]
#
# @!attribute [rw] check_job_arn
# The Amazon Resource Name (ARN) of the check processing job that was
# run by this step's execution.
# @return [String]
#
# @!attribute [rw] skip_check
# This flag indicates if the drift check against the previous baseline
# will be skipped or not. If it is set to `False`, the previous
# baseline of the configured check type must be available.
# @return [Boolean]
#
# @!attribute [rw] register_new_baseline
# This flag indicates if a newly calculated baseline can be accessed
# through step properties `BaselineUsedForDriftCheckConstraints` and
# `BaselineUsedForDriftCheckStatistics`. If it is set to `False`, the
# previous baseline of the configured check type must also be
# available. These can be accessed through the
# `BaselineUsedForDriftCheckConstraints` property.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClarifyCheckStepMetadata AWS API Documentation
#
class ClarifyCheckStepMetadata < Struct.new(
:check_type,
:baseline_used_for_drift_check_constraints,
:calculated_baseline_constraints,
:model_package_group_name,
:violation_report,
:check_job_arn,
:skip_check,
:register_new_baseline)
SENSITIVE = []
include Aws::Structure
end
# The configuration parameters for the SageMaker Clarify explainer.
#
# @!attribute [rw] enable_explanations
# A JMESPath boolean expression used to filter which records to
# explain. Explanations are activated by default. See [
# `EnableExplanations` ][1]for additional information.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-enable
# @return [String]
#
# @!attribute [rw] inference_config
# The inference configuration parameter for the model container.
# @return [Types::ClarifyInferenceConfig]
#
# @!attribute [rw] shap_config
# The configuration for SHAP analysis.
# @return [Types::ClarifyShapConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClarifyExplainerConfig AWS API Documentation
#
class ClarifyExplainerConfig < Struct.new(
:enable_explanations,
:inference_config,
:shap_config)
SENSITIVE = []
include Aws::Structure
end
# The inference configuration parameter for the model container.
#
# @!attribute [rw] features_attribute
# Provides the JMESPath expression to extract the features from a
# model container input in JSON Lines format. For example, if
# `FeaturesAttribute` is the JMESPath expression `'myfeatures'`, it
# extracts a list of features `[1,2,3]` from request data
# `'\{"myfeatures":[1,2,3]\}'`.
# @return [String]
#
# @!attribute [rw] content_template
# A template string used to format a JSON record into an acceptable
# model container input. For example, a `ContentTemplate` string
# `'\{"myfeatures":$features\}'` will format a list of features
# `[1,2,3]` into the record string `'\{"myfeatures":[1,2,3]\}'`.
# Required only when the model container input is in JSON Lines
# format.
# @return [String]
#
# @!attribute [rw] max_record_count
# The maximum number of records in a request that the model container
# can process when querying the model container for the predictions of
# a [synthetic dataset][1]. A record is a unit of input data that
# inference can be made on, for example, a single line in CSV data. If
# `MaxRecordCount` is `1`, the model container expects one record per
# request. A value of 2 or greater means that the model expects batch
# requests, which can reduce overhead and speed up the inferencing
# process. If this parameter is not provided, the explainer will tune
# the record count per request according to the model container's
# capacity at runtime.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html#clarify-online-explainability-create-endpoint-synthetic
# @return [Integer]
#
# @!attribute [rw] max_payload_in_mb
# The maximum payload size (MB) allowed of a request from the
# explainer to the model container. Defaults to `6` MB.
# @return [Integer]
#
# @!attribute [rw] probability_index
# A zero-based index used to extract a probability value (score) or
# list from model container output in CSV format. If this value is not
# provided, the entire model container output will be treated as a
# probability value (score) or list.
#
# **Example for a single class model:** If the model container output
# consists of a string-formatted prediction label followed by its
# probability: `'1,0.6'`, set `ProbabilityIndex` to `1` to select the
# probability value `0.6`.
#
# **Example for a multiclass model:** If the model container output
# consists of a string-formatted prediction label followed by its
# probability: `'"['cat','dog','fish']","[0.1,0.6,0.3]"'`, set
# `ProbabilityIndex` to `1` to select the probability values
# `[0.1,0.6,0.3]`.
# @return [Integer]
#
# @!attribute [rw] label_index
# A zero-based index used to extract a label header or list of label
# headers from model container output in CSV format.
#
# **Example for a multiclass model:** If the model container output
# consists of label headers followed by probabilities:
# `'"['cat','dog','fish']","[0.1,0.6,0.3]"'`, set `LabelIndex`
# to `0` to select the label headers `['cat','dog','fish']`.
# @return [Integer]
#
# @!attribute [rw] probability_attribute
# A JMESPath expression used to extract the probability (or score)
# from the model container output if the model container is in JSON
# Lines format.
#
# **Example**: If the model container output of a single request is
# `'\{"predicted_label":1,"probability":0.6\}'`, then set
# `ProbabilityAttribute` to `'probability'`.
# @return [String]
#
# @!attribute [rw] label_attribute
# A JMESPath expression used to locate the list of label headers in
# the model container output.
#
# **Example**: If the model container output of a batch request is
# `'\{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]\}'`,
# then set `LabelAttribute` to `'labels'` to extract the list of label
# headers `["cat","dog","fish"]`
# @return [String]
#
# @!attribute [rw] label_headers
# For multiclass classification problems, the label headers are the
# names of the classes. Otherwise, the label header is the name of the
# predicted label. These are used to help readability for the output
# of the `InvokeEndpoint` API. See the [response][1] section under
# **Invoke the endpoint** in the Developer Guide for more information.
# If there are no label headers in the model container output, provide
# them manually using this parameter.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-response
# @return [Array<String>]
#
# @!attribute [rw] feature_headers
# The names of the features. If provided, these are included in the
# endpoint response payload to help readability of the
# `InvokeEndpoint` output. See the [Response][1] section under
# **Invoke the endpoint** in the Developer Guide for more information.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-response
# @return [Array<String>]
#
# @!attribute [rw] feature_types
# A list of data types of the features (optional). Applicable only to
# NLP explainability. If provided, `FeatureTypes` must have at least
# one `'text'` string (for example, `['text']`). If `FeatureTypes` is
# not provided, the explainer infers the feature types based on the
# baseline data. The feature types are included in the endpoint
# response payload. For additional information see the [response][1]
# section under **Invoke the endpoint** in the Developer Guide for
# more information.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-invoke-endpoint.html#clarify-online-explainability-response
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClarifyInferenceConfig AWS API Documentation
#
class ClarifyInferenceConfig < Struct.new(
:features_attribute,
:content_template,
:max_record_count,
:max_payload_in_mb,
:probability_index,
:label_index,
:probability_attribute,
:label_attribute,
:label_headers,
:feature_headers,
:feature_types)
SENSITIVE = []
include Aws::Structure
end
# The configuration for the [SHAP baseline][1] (also called the
# background or reference dataset) of the Kernal SHAP algorithm.
#
# <note markdown="1"> * The number of records in the baseline data determines the size of
# the synthetic dataset, which has an impact on latency of
# explainability requests. For more information, see the **Synthetic
# data** of [Configure and create an endpoint][2].
#
# * `ShapBaseline` and `ShapBaselineUri` are mutually exclusive
# parameters. One or the either is required to configure a SHAP
# baseline.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-feature-attribute-shap-baselines.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html
#
# @!attribute [rw] mime_type
# The MIME type of the baseline data. Choose from `'text/csv'` or
# `'application/jsonlines'`. Defaults to `'text/csv'`.
# @return [String]
#
# @!attribute [rw] shap_baseline
# The inline SHAP baseline data in string format. `ShapBaseline` can
# have one or multiple records to be used as the baseline dataset. The
# format of the SHAP baseline file should be the same format as the
# training dataset. For example, if the training dataset is in CSV
# format and each record contains four features, and all features are
# numerical, then the format of the baseline data should also share
# these characteristics. For natural language processing (NLP) of text
# columns, the baseline value should be the value used to replace the
# unit of text specified by the `Granularity` of the `TextConfig`
# parameter. The size limit for `ShapBasline` is 4 KB. Use the
# `ShapBaselineUri` parameter if you want to provide more than 4 KB of
# baseline data.
# @return [String]
#
# @!attribute [rw] shap_baseline_uri
# The uniform resource identifier (URI) of the S3 bucket where the
# SHAP baseline file is stored. The format of the SHAP baseline file
# should be the same format as the format of the training dataset. For
# example, if the training dataset is in CSV format, and each record
# in the training dataset has four features, and all features are
# numerical, then the baseline file should also have this same format.
# Each record should contain only the features. If you are using a
# virtual private cloud (VPC), the `ShapBaselineUri` should be
# accessible to the VPC. For more information about setting up
# endpoints with Amazon Virtual Private Cloud, see [Give SageMaker
# access to Resources in your Amazon Virtual Private Cloud][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClarifyShapBaselineConfig AWS API Documentation
#
class ClarifyShapBaselineConfig < Struct.new(
:mime_type,
:shap_baseline,
:shap_baseline_uri)
SENSITIVE = []
include Aws::Structure
end
# The configuration for SHAP analysis using SageMaker Clarify Explainer.
#
# @!attribute [rw] shap_baseline_config
# The configuration for the SHAP baseline of the Kernal SHAP
# algorithm.
# @return [Types::ClarifyShapBaselineConfig]
#
# @!attribute [rw] number_of_samples
# The number of samples to be used for analysis by the Kernal SHAP
# algorithm.
#
# <note markdown="1"> The number of samples determines the size of the synthetic dataset,
# which has an impact on latency of explainability requests. For more
# information, see the **Synthetic data** of [Configure and create an
# endpoint][1].
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-create-endpoint.html
# @return [Integer]
#
# @!attribute [rw] use_logit
# A Boolean toggle to indicate if you want to use the logit function
# (true) or log-odds units (false) for model predictions. Defaults to
# false.
# @return [Boolean]
#
# @!attribute [rw] seed
# The starting value used to initialize the random number generator in
# the explainer. Provide a value for this parameter to obtain a
# deterministic SHAP result.
# @return [Integer]
#
# @!attribute [rw] text_config
# A parameter that indicates if text features are treated as text and
# explanations are provided for individual units of text. Required for
# natural language processing (NLP) explainability only.
# @return [Types::ClarifyTextConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClarifyShapConfig AWS API Documentation
#
class ClarifyShapConfig < Struct.new(
:shap_baseline_config,
:number_of_samples,
:use_logit,
:seed,
:text_config)
SENSITIVE = []
include Aws::Structure
end
# A parameter used to configure the SageMaker Clarify explainer to treat
# text features as text so that explanations are provided for individual
# units of text. Required only for natural language processing (NLP)
# explainability.
#
# @!attribute [rw] language
# Specifies the language of the text features in [ISO 639-1](
# https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) or [ISO
# 639-3][1] code of a supported language.
#
# <note markdown="1"> For a mix of multiple languages, use code `'xx'`.
#
# </note>
#
#
#
# [1]: https://en.wikipedia.org/wiki/ISO_639-3
# @return [String]
#
# @!attribute [rw] granularity
# The unit of granularity for the analysis of text features. For
# example, if the unit is `'token'`, then each token (like a word in
# English) of the text is treated as a feature. SHAP values are
# computed for each unit/feature.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClarifyTextConfig AWS API Documentation
#
class ClarifyTextConfig < Struct.new(
:language,
:granularity)
SENSITIVE = []
include Aws::Structure
end
# A Git repository that SageMaker automatically displays to users for
# cloning in the JupyterServer application.
#
# @!attribute [rw] repository_url
# The URL of the Git repository.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CodeRepository AWS API Documentation
#
class CodeRepository < Struct.new(
:repository_url)
SENSITIVE = []
include Aws::Structure
end
# Specifies summary information about a Git repository.
#
# @!attribute [rw] code_repository_name
# The name of the Git repository.
# @return [String]
#
# @!attribute [rw] code_repository_arn
# The Amazon Resource Name (ARN) of the Git repository.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the Git repository was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the Git repository was last modified.
# @return [Time]
#
# @!attribute [rw] git_config
# Configuration details for the Git repository, including the URL
# where it is located and the ARN of the Amazon Web Services Secrets
# Manager secret that contains the credentials used to access the
# repository.
# @return [Types::GitConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CodeRepositorySummary AWS API Documentation
#
class CodeRepositorySummary < Struct.new(
:code_repository_name,
:code_repository_arn,
:creation_time,
:last_modified_time,
:git_config)
SENSITIVE = []
include Aws::Structure
end
# 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][1].
#
#
#
# [1]: https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html
#
# @!attribute [rw] user_pool
# A [ user pool][1] is a user directory in Amazon Cognito. With a user
# pool, your users can sign in to your web or mobile app through
# Amazon Cognito. Your users can also sign in through social identity
# providers like Google, Facebook, Amazon, or Apple, and through SAML
# identity providers.
#
#
#
# [1]: https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html
# @return [String]
#
# @!attribute [rw] client_id
# The client ID for your Amazon Cognito user pool.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CognitoConfig AWS API Documentation
#
class CognitoConfig < Struct.new(
:user_pool,
:client_id)
SENSITIVE = []
include Aws::Structure
end
# Identifies a Amazon Cognito user group. A user group can be used in on
# or more work teams.
#
# @!attribute [rw] user_pool
# An identifier for a user pool. The user pool must be in the same
# region as the service that you are calling.
# @return [String]
#
# @!attribute [rw] user_group
# An identifier for a user group.
# @return [String]
#
# @!attribute [rw] client_id
# An identifier for an application client. You must create the app
# client ID using Amazon Cognito.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CognitoMemberDefinition AWS API Documentation
#
class CognitoMemberDefinition < Struct.new(
:user_pool,
:user_group,
:client_id)
SENSITIVE = []
include Aws::Structure
end
# Configuration information for the Amazon SageMaker Debugger output
# tensor collections.
#
# @!attribute [rw] collection_name
# The name of the tensor collection. The name must be unique relative
# to other rule configuration names.
# @return [String]
#
# @!attribute [rw] collection_parameters
# Parameter values for the tensor collection. The allowed parameters
# are `"name"`, `"include_regex"`, `"reduction_config"`,
# `"save_config"`, `"tensor_names"`, and `"save_histogram"`.
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CollectionConfiguration AWS API Documentation
#
class CollectionConfiguration < Struct.new(
:collection_name,
:collection_parameters)
SENSITIVE = []
include Aws::Structure
end
# A summary of a model compilation job.
#
# @!attribute [rw] compilation_job_name
# The name of the model compilation job that you want a summary for.
# @return [String]
#
# @!attribute [rw] compilation_job_arn
# The Amazon Resource Name (ARN) of the model compilation job.
# @return [String]
#
# @!attribute [rw] creation_time
# The time when the model compilation job was created.
# @return [Time]
#
# @!attribute [rw] compilation_start_time
# The time when the model compilation job started.
# @return [Time]
#
# @!attribute [rw] compilation_end_time
# The time when the model compilation job completed.
# @return [Time]
#
# @!attribute [rw] compilation_target_device
# The type of device that the model will run on after the compilation
# job has completed.
# @return [String]
#
# @!attribute [rw] compilation_target_platform_os
# The type of OS that the model will run on after the compilation job
# has completed.
# @return [String]
#
# @!attribute [rw] compilation_target_platform_arch
# The type of architecture that the model will run on after the
# compilation job has completed.
# @return [String]
#
# @!attribute [rw] compilation_target_platform_accelerator
# The type of accelerator that the model will run on after the
# compilation job has completed.
# @return [String]
#
# @!attribute [rw] last_modified_time
# The time when the model compilation job was last modified.
# @return [Time]
#
# @!attribute [rw] compilation_job_status
# The status of the model compilation job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CompilationJobSummary AWS API Documentation
#
class CompilationJobSummary < Struct.new(
:compilation_job_name,
:compilation_job_arn,
:creation_time,
:compilation_start_time,
:compilation_end_time,
:compilation_target_device,
:compilation_target_platform_os,
:compilation_target_platform_arch,
:compilation_target_platform_accelerator,
:last_modified_time,
:compilation_job_status)
SENSITIVE = []
include Aws::Structure
end
# Metadata for a Condition step.
#
# @!attribute [rw] outcome
# The outcome of the Condition step evaluation.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ConditionStepMetadata AWS API Documentation
#
class ConditionStepMetadata < Struct.new(
:outcome)
SENSITIVE = []
include Aws::Structure
end
# There was a conflict when you attempted to modify a SageMaker entity
# such as an `Experiment` or `Artifact`.
#
# @!attribute [rw] message
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ConflictException AWS API Documentation
#
class ConflictException < Struct.new(
:message)
SENSITIVE = []
include Aws::Structure
end
# Describes the container, as part of model definition.
#
# @!attribute [rw] container_hostname
# This parameter is ignored for models that contain only a
# `PrimaryContainer`.
#
# When a `ContainerDefinition` is part of an inference pipeline, the
# value of the parameter uniquely identifies the container for the
# purposes of logging and metrics. For information, see [Use Logs and
# Metrics to Monitor an Inference Pipeline][1]. If you don't specify
# a value for this parameter for a `ContainerDefinition` that is part
# of an inference pipeline, a unique name is automatically assigned
# based on the position of the `ContainerDefinition` in the pipeline.
# If you specify a value for the `ContainerHostName` for any
# `ContainerDefinition` that is part of an inference pipeline, you
# must specify a value for the `ContainerHostName` parameter of every
# `ContainerDefinition` in that pipeline.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/inference-pipeline-logs-metrics.html
# @return [String]
#
# @!attribute [rw] image
# The path where inference code is stored. This can be either in
# Amazon EC2 Container Registry or in a Docker registry that is
# accessible from the same VPC that you configure for your endpoint.
# If you are using your own custom algorithm instead of an algorithm
# provided by SageMaker, the inference code must meet SageMaker
# requirements. SageMaker supports both `registry/repository[:tag]`
# and `registry/repository[@digest]` image path formats. For more
# information, see [Using Your Own Algorithms with Amazon
# SageMaker][1].
#
# <note markdown="1"> The model artifacts in an Amazon S3 bucket and the Docker image for
# inference container in Amazon EC2 Container Registry must be in the
# same region as the model or endpoint you are creating.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html
# @return [String]
#
# @!attribute [rw] image_config
# Specifies whether the model container is in Amazon ECR or a private
# Docker registry accessible from your Amazon Virtual Private Cloud
# (VPC). For information about storing containers in a private Docker
# registry, see [Use a Private Docker Registry for Real-Time Inference
# Containers][1].
#
# <note markdown="1"> The model artifacts in an Amazon S3 bucket and the Docker image for
# inference container in Amazon EC2 Container Registry must be in the
# same region as the model or endpoint you are creating.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-containers-inference-private.html
# @return [Types::ImageConfig]
#
# @!attribute [rw] mode
# Whether the container hosts a single model or multiple models.
# @return [String]
#
# @!attribute [rw] model_data_url
# The S3 path where the model artifacts, which result from model
# training, are stored. This path must point to a single gzip
# compressed tar archive (.tar.gz suffix). The S3 path is required for
# SageMaker built-in algorithms, but not if you use your own
# algorithms. For more information on built-in algorithms, see [Common
# Parameters][1].
#
# <note markdown="1"> The model artifacts must be in an S3 bucket that is in the same
# region as the model or endpoint you are creating.
#
# </note>
#
# If you provide a value for this parameter, SageMaker uses Amazon Web
# Services Security Token Service to download model artifacts from the
# S3 path you provide. Amazon Web Services STS is activated in your
# Amazon Web Services account by default. If you previously
# deactivated Amazon Web Services STS for a region, you need to
# reactivate Amazon Web Services STS for that region. For more
# information, see [Activating and Deactivating Amazon Web Services
# STS in an Amazon Web Services Region][2] in the *Amazon Web Services
# Identity and Access Management User Guide*.
#
# If you use a built-in algorithm to create a model, SageMaker
# requires that you provide a S3 path to the model artifacts in
# `ModelDataUrl`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html
# [2]: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html
# @return [String]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container. Each key
# and value in the `Environment` string to string map can have length
# of up to 1024. We support up to 16 entries in the map.
# @return [Hash<String,String>]
#
# @!attribute [rw] model_package_name
# The name or Amazon Resource Name (ARN) of the model package to use
# to create the model.
# @return [String]
#
# @!attribute [rw] inference_specification_name
# The inference specification name in the model package version.
# @return [String]
#
# @!attribute [rw] multi_model_config
# Specifies additional configuration for multi-model endpoints.
# @return [Types::MultiModelConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ContainerDefinition AWS API Documentation
#
class ContainerDefinition < Struct.new(
:container_hostname,
:image,
:image_config,
:mode,
:model_data_url,
:environment,
:model_package_name,
:inference_specification_name,
:multi_model_config)
SENSITIVE = []
include Aws::Structure
end
# A structure describing the source of a context.
#
# @!attribute [rw] source_uri
# The URI of the source.
# @return [String]
#
# @!attribute [rw] source_type
# The type of the source.
# @return [String]
#
# @!attribute [rw] source_id
# The ID of the source.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ContextSource AWS API Documentation
#
class ContextSource < Struct.new(
:source_uri,
:source_type,
:source_id)
SENSITIVE = []
include Aws::Structure
end
# Lists a summary of the properties of a context. A context provides a
# logical grouping of other entities.
#
# @!attribute [rw] context_arn
# The Amazon Resource Name (ARN) of the context.
# @return [String]
#
# @!attribute [rw] context_name
# The name of the context.
# @return [String]
#
# @!attribute [rw] source
# The source of the context.
# @return [Types::ContextSource]
#
# @!attribute [rw] context_type
# The type of the context.
# @return [String]
#
# @!attribute [rw] creation_time
# When the context was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# When the context was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ContextSummary AWS API Documentation
#
class ContextSummary < Struct.new(
:context_arn,
:context_name,
:source,
:context_type,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# A list of continuous hyperparameters to tune.
#
# @!attribute [rw] name
# The name of the continuous hyperparameter to tune.
# @return [String]
#
# @!attribute [rw] min_value
# The minimum value for the hyperparameter. The tuning job uses
# floating-point values between this value and `MaxValue`for tuning.
# @return [String]
#
# @!attribute [rw] max_value
# The maximum value for the hyperparameter. The tuning job uses
# floating-point values between `MinValue` value and this value for
# tuning.
# @return [String]
#
# @!attribute [rw] scaling_type
# The scale that hyperparameter tuning uses to search the
# hyperparameter range. For information about choosing a
# hyperparameter scale, see [Hyperparameter Scaling][1]. One of the
# following values:
#
# Auto
#
# : SageMaker hyperparameter tuning chooses the best scale for the
# hyperparameter.
#
# Linear
#
# : Hyperparameter tuning searches the values in the hyperparameter
# range by using a linear scale.
#
# Logarithmic
#
# : Hyperparameter tuning searches the values in the hyperparameter
# range by using a logarithmic scale.
#
# Logarithmic scaling works only for ranges that have only values
# greater than 0.
#
# ReverseLogarithmic
#
# : Hyperparameter tuning searches the values in the hyperparameter
# range by using a reverse logarithmic scale.
#
# Reverse logarithmic scaling works only for ranges that are
# entirely within the range 0<=x<1.0.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-type
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ContinuousParameterRange AWS API Documentation
#
class ContinuousParameterRange < Struct.new(
:name,
:min_value,
:max_value,
:scaling_type)
SENSITIVE = []
include Aws::Structure
end
# Defines the possible values for a continuous hyperparameter.
#
# @!attribute [rw] min_value
# The minimum floating-point value allowed.
# @return [String]
#
# @!attribute [rw] max_value
# The maximum floating-point value allowed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ContinuousParameterRangeSpecification AWS API Documentation
#
class ContinuousParameterRangeSpecification < Struct.new(
:min_value,
:max_value)
SENSITIVE = []
include Aws::Structure
end
# A flag to indicating that automatic model tuning (AMT) has detected
# model convergence, defined as a lack of significant improvement (1% or
# less) against an objective metric.
#
# @!attribute [rw] complete_on_convergence
# A flag to stop a tuning job once AMT has detected that the job has
# converged.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ConvergenceDetected AWS API Documentation
#
class ConvergenceDetected < Struct.new(
:complete_on_convergence)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_name
# The name of the action. Must be unique to your account in an Amazon
# Web Services Region.
# @return [String]
#
# @!attribute [rw] source
# The source type, ID, and URI.
# @return [Types::ActionSource]
#
# @!attribute [rw] action_type
# The action type.
# @return [String]
#
# @!attribute [rw] description
# The description of the action.
# @return [String]
#
# @!attribute [rw] status
# The status of the action.
# @return [String]
#
# @!attribute [rw] properties
# A list of properties to add to the action.
# @return [Hash<String,String>]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] tags
# A list of tags to apply to the action.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateActionRequest AWS API Documentation
#
class CreateActionRequest < Struct.new(
:action_name,
:source,
:action_type,
:description,
:status,
:properties,
:metadata_properties,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_arn
# The Amazon Resource Name (ARN) of the action.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateActionResponse AWS API Documentation
#
class CreateActionResponse < Struct.new(
:action_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] algorithm_name
# The name of the algorithm.
# @return [String]
#
# @!attribute [rw] algorithm_description
# A description of the algorithm.
# @return [String]
#
# @!attribute [rw] training_specification
# Specifies details about training jobs run by this algorithm,
# including the following:
#
# * The Amazon ECR path of the container and the version digest of the
# algorithm.
#
# * The hyperparameters that the algorithm supports.
#
# * The instance types that the algorithm supports for training.
#
# * Whether the algorithm supports distributed training.
#
# * The metrics that the algorithm emits to Amazon CloudWatch.
#
# * Which metrics that the algorithm emits can be used as the
# objective metric for hyperparameter tuning jobs.
#
# * The input channels that the algorithm supports for training data.
# For example, an algorithm might support `train`, `validation`, and
# `test` channels.
# @return [Types::TrainingSpecification]
#
# @!attribute [rw] inference_specification
# Specifies details about inference jobs that the algorithm runs,
# including the following:
#
# * The Amazon ECR paths of containers that contain the inference code
# and model artifacts.
#
# * The instance types that the algorithm supports for transform jobs
# and real-time endpoints used for inference.
#
# * The input and output content formats that the algorithm supports
# for inference.
# @return [Types::InferenceSpecification]
#
# @!attribute [rw] validation_specification
# Specifies configurations for one or more training jobs and that
# SageMaker runs to test the algorithm's training code and,
# optionally, one or more batch transform jobs that SageMaker runs to
# test the algorithm's inference code.
# @return [Types::AlgorithmValidationSpecification]
#
# @!attribute [rw] certify_for_marketplace
# Whether to certify the algorithm so that it can be listed in Amazon
# Web Services Marketplace.
# @return [Boolean]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAlgorithmInput AWS API Documentation
#
class CreateAlgorithmInput < Struct.new(
:algorithm_name,
:algorithm_description,
:training_specification,
:inference_specification,
:validation_specification,
:certify_for_marketplace,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] algorithm_arn
# The Amazon Resource Name (ARN) of the new algorithm.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAlgorithmOutput AWS API Documentation
#
class CreateAlgorithmOutput < Struct.new(
:algorithm_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_image_config_name
# The name of the AppImageConfig. Must be unique to your account.
# @return [String]
#
# @!attribute [rw] tags
# A list of tags to apply to the AppImageConfig.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] kernel_gateway_image_config
# The KernelGatewayImageConfig. You can only specify one image kernel
# in the AppImageConfig API. This kernel will be shown to users before
# the image starts. Once the image runs, all kernels are visible in
# JupyterLab.
# @return [Types::KernelGatewayImageConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAppImageConfigRequest AWS API Documentation
#
class CreateAppImageConfigRequest < Struct.new(
:app_image_config_name,
:tags,
:kernel_gateway_image_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_image_config_arn
# The Amazon Resource Name (ARN) of the AppImageConfig.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAppImageConfigResponse AWS API Documentation
#
class CreateAppImageConfigResponse < Struct.new(
:app_image_config_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name. If this value is not set, then `SpaceName`
# must be set.
# @return [String]
#
# @!attribute [rw] app_type
# The type of app.
# @return [String]
#
# @!attribute [rw] app_name
# The name of the app.
# @return [String]
#
# @!attribute [rw] tags
# Each tag consists of a key and an optional value. Tag keys must be
# unique per resource.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] resource_spec
# The instance type and the Amazon Resource Name (ARN) of the
# SageMaker image created on the instance.
#
# <note markdown="1"> The value of `InstanceType` passed as part of the `ResourceSpec` in
# the `CreateApp` call overrides the value passed as part of the
# `ResourceSpec` configured for the user profile or the domain. If
# `InstanceType` is not specified in any of those three `ResourceSpec`
# values for a `KernelGateway` app, the `CreateApp` call fails with a
# request validation error.
#
# </note>
# @return [Types::ResourceSpec]
#
# @!attribute [rw] space_name
# The name of the space. If this value is not set, then
# `UserProfileName` must be set.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAppRequest AWS API Documentation
#
class CreateAppRequest < Struct.new(
:domain_id,
:user_profile_name,
:app_type,
:app_name,
:tags,
:resource_spec,
:space_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_arn
# The Amazon Resource Name (ARN) of the app.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAppResponse AWS API Documentation
#
class CreateAppResponse < Struct.new(
:app_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_name
# The name of the artifact. Must be unique to your account in an
# Amazon Web Services Region.
# @return [String]
#
# @!attribute [rw] source
# The ID, ID type, and URI of the source.
# @return [Types::ArtifactSource]
#
# @!attribute [rw] artifact_type
# The artifact type.
# @return [String]
#
# @!attribute [rw] properties
# A list of properties to add to the artifact.
# @return [Hash<String,String>]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] tags
# A list of tags to apply to the artifact.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateArtifactRequest AWS API Documentation
#
class CreateArtifactRequest < Struct.new(
:artifact_name,
:source,
:artifact_type,
:properties,
:metadata_properties,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_arn
# The Amazon Resource Name (ARN) of the artifact.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateArtifactResponse AWS API Documentation
#
class CreateArtifactResponse < Struct.new(
:artifact_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_name
# Identifies an Autopilot job. The name must be unique to your account
# and is case insensitive.
# @return [String]
#
# @!attribute [rw] input_data_config
# An array of channel objects that describes the input data and its
# location. Each channel is a named input source. Similar to
# `InputDataConfig` supported by
# [HyperParameterTrainingJobDefinition][1]. Format(s) supported: CSV,
# Parquet. A minimum of 500 rows is required for the training dataset.
# There is not a minimum number of rows required for the validation
# dataset.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html
# @return [Array<Types::AutoMLChannel>]
#
# @!attribute [rw] output_data_config
# Provides information about encryption and the Amazon S3 output path
# needed to store artifacts from an AutoML job. Format(s) supported:
# CSV.
# @return [Types::AutoMLOutputDataConfig]
#
# @!attribute [rw] problem_type
# Defines the type of supervised learning problem available for the
# candidates. For more information, see [ Amazon SageMaker Autopilot
# problem types][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-problem-types
# @return [String]
#
# @!attribute [rw] auto_ml_job_objective
# Defines the objective metric used to measure the predictive quality
# of an AutoML job. You provide an [AutoMLJobObjective$MetricName][1]
# and Autopilot infers whether to minimize or maximize it. For
# [CreateAutoMLJobV2][2], only `Accuracy` is supported.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobObjective.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html
# @return [Types::AutoMLJobObjective]
#
# @!attribute [rw] auto_ml_job_config
# A collection of settings used to configure an AutoML job.
# @return [Types::AutoMLJobConfig]
#
# @!attribute [rw] role_arn
# The ARN of the role that is used to access the data.
# @return [String]
#
# @!attribute [rw] generate_candidate_definitions_only
# Generates possible candidates without training the models. A
# candidate is a combination of data preprocessors, algorithms, and
# algorithm parameter settings.
# @return [Boolean]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web ServicesResources][1]. Tag keys must be unique per
# resource.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] model_deploy_config
# Specifies how to generate the endpoint name for an automatic
# one-click Autopilot model deployment.
# @return [Types::ModelDeployConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAutoMLJobRequest AWS API Documentation
#
class CreateAutoMLJobRequest < Struct.new(
:auto_ml_job_name,
:input_data_config,
:output_data_config,
:problem_type,
:auto_ml_job_objective,
:auto_ml_job_config,
:role_arn,
:generate_candidate_definitions_only,
:tags,
:model_deploy_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_arn
# The unique ARN assigned to the AutoML job when it is created.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAutoMLJobResponse AWS API Documentation
#
class CreateAutoMLJobResponse < Struct.new(
:auto_ml_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_name
# Identifies an Autopilot job. The name must be unique to your account
# and is case insensitive.
# @return [String]
#
# @!attribute [rw] auto_ml_job_input_data_config
# An array of channel objects describing the input data and their
# location. Each channel is a named input source. Similar to
# [InputDataConfig][1] supported by `CreateAutoMLJob`. The supported
# formats depend on the problem type:
#
# * ImageClassification: S3Prefix, `ManifestFile`,
# `AugmentedManifestFile`
#
# * TextClassification: S3Prefix
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJob.html#sagemaker-CreateAutoMLJob-request-InputDataConfig
# @return [Array<Types::AutoMLJobChannel>]
#
# @!attribute [rw] output_data_config
# Provides information about encryption and the Amazon S3 output path
# needed to store artifacts from an AutoML job.
# @return [Types::AutoMLOutputDataConfig]
#
# @!attribute [rw] auto_ml_problem_type_config
# Defines the configuration settings of one of the supported problem
# types.
# @return [Types::AutoMLProblemTypeConfig]
#
# @!attribute [rw] role_arn
# The ARN of the role that is used to access the data.
# @return [String]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, such as by purpose,
# owner, or environment. For more information, see [Tagging Amazon Web
# ServicesResources][1]. Tag keys must be unique per resource.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] security_config
# The security configuration for traffic encryption or Amazon VPC
# settings.
# @return [Types::AutoMLSecurityConfig]
#
# @!attribute [rw] auto_ml_job_objective
# Specifies a metric to minimize or maximize as the objective of a
# job. For [CreateAutoMLJobV2][1], only `Accuracy` is supported.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html
# @return [Types::AutoMLJobObjective]
#
# @!attribute [rw] model_deploy_config
# Specifies how to generate the endpoint name for an automatic
# one-click Autopilot model deployment.
# @return [Types::ModelDeployConfig]
#
# @!attribute [rw] data_split_config
# This structure specifies how to split the data into train and
# validation datasets.
#
# If you are using the V1 API (for example `CreateAutoMLJob`) or the
# V2 API for Natural Language Processing problems (for example
# `CreateAutoMLJobV2` with a `TextClassificationJobConfig` problem
# type), the validation and training datasets must contain the same
# headers. Also, for V1 API jobs, the validation dataset must be less
# than 2 GB in size.
# @return [Types::AutoMLDataSplitConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAutoMLJobV2Request AWS API Documentation
#
class CreateAutoMLJobV2Request < Struct.new(
:auto_ml_job_name,
:auto_ml_job_input_data_config,
:output_data_config,
:auto_ml_problem_type_config,
:role_arn,
:tags,
:security_config,
:auto_ml_job_objective,
:model_deploy_config,
:data_split_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_arn
# The unique ARN assigned to the AutoMLJob when it is created.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAutoMLJobV2Response AWS API Documentation
#
class CreateAutoMLJobV2Response < Struct.new(
:auto_ml_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] code_repository_name
# The name of the Git repository. The name must have 1 to 63
# characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
# @return [String]
#
# @!attribute [rw] git_config
# Specifies details about the repository, including the URL where the
# repository is located, the default branch, and credentials to use to
# access the repository.
# @return [Types::GitConfig]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCodeRepositoryInput AWS API Documentation
#
class CreateCodeRepositoryInput < Struct.new(
:code_repository_name,
:git_config,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] code_repository_arn
# The Amazon Resource Name (ARN) of the new repository.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCodeRepositoryOutput AWS API Documentation
#
class CreateCodeRepositoryOutput < Struct.new(
:code_repository_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] compilation_job_name
# A name for the model compilation job. The name must be unique within
# the Amazon Web Services Region and within your Amazon Web Services
# account.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that enables Amazon
# SageMaker to perform tasks on your behalf.
#
# During model compilation, Amazon SageMaker needs your permission to:
#
# * Read input data from an S3 bucket
#
# * Write model artifacts to an S3 bucket
#
# * Write logs to Amazon CloudWatch Logs
#
# * Publish metrics to Amazon CloudWatch
#
# You grant permissions for all of these tasks to an IAM role. To pass
# this role to Amazon SageMaker, the caller of this API must have the
# `iam:PassRole` permission. For more information, see [Amazon
# SageMaker Roles.][1]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html
# @return [String]
#
# @!attribute [rw] model_package_version_arn
# The Amazon Resource Name (ARN) of a versioned model package. Provide
# either a `ModelPackageVersionArn` or an `InputConfig` object in the
# request syntax. The presence of both objects in the
# `CreateCompilationJob` request will return an exception.
# @return [String]
#
# @!attribute [rw] input_config
# Provides information about the location of input model artifacts,
# the name and shape of the expected data inputs, and the framework in
# which the model was trained.
# @return [Types::InputConfig]
#
# @!attribute [rw] output_config
# Provides information about the output location for the compiled
# model and the target device the model runs on.
# @return [Types::OutputConfig]
#
# @!attribute [rw] vpc_config
# A [VpcConfig][1] object that specifies the VPC that you want your
# compilation job to connect to. Control access to your models by
# configuring the VPC. For more information, see [Protect Compilation
# Jobs by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/neo-vpc.html
# @return [Types::NeoVpcConfig]
#
# @!attribute [rw] stopping_condition
# Specifies a limit to how long a model compilation job can run. When
# the job reaches the time limit, Amazon SageMaker ends the
# compilation job. Use this API to cap model training costs.
# @return [Types::StoppingCondition]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCompilationJobRequest AWS API Documentation
#
class CreateCompilationJobRequest < Struct.new(
:compilation_job_name,
:role_arn,
:model_package_version_arn,
:input_config,
:output_config,
:vpc_config,
:stopping_condition,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] compilation_job_arn
# If the action is successful, the service sends back an HTTP 200
# response. Amazon SageMaker returns the following data in JSON
# format:
#
# * `CompilationJobArn`: The Amazon Resource Name (ARN) of the
# compiled job.
#
# ^
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateCompilationJobResponse AWS API Documentation
#
class CreateCompilationJobResponse < Struct.new(
:compilation_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_name
# The name of the context. Must be unique to your account in an Amazon
# Web Services Region.
# @return [String]
#
# @!attribute [rw] source
# The source type, ID, and URI.
# @return [Types::ContextSource]
#
# @!attribute [rw] context_type
# The context type.
# @return [String]
#
# @!attribute [rw] description
# The description of the context.
# @return [String]
#
# @!attribute [rw] properties
# A list of properties to add to the context.
# @return [Hash<String,String>]
#
# @!attribute [rw] tags
# A list of tags to apply to the context.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateContextRequest AWS API Documentation
#
class CreateContextRequest < Struct.new(
:context_name,
:source,
:context_type,
:description,
:properties,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_arn
# The Amazon Resource Name (ARN) of the context.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateContextResponse AWS API Documentation
#
class CreateContextResponse < Struct.new(
:context_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name for the monitoring job definition.
# @return [String]
#
# @!attribute [rw] data_quality_baseline_config
# Configures the constraints and baselines for the monitoring job.
# @return [Types::DataQualityBaselineConfig]
#
# @!attribute [rw] data_quality_app_specification
# Specifies the container that runs the monitoring job.
# @return [Types::DataQualityAppSpecification]
#
# @!attribute [rw] data_quality_job_input
# A list of inputs for the monitoring job. Currently endpoints are
# supported as monitoring inputs.
# @return [Types::DataQualityJobInput]
#
# @!attribute [rw] data_quality_job_output_config
# The output configuration for monitoring jobs.
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] job_resources
# Identifies the resources to deploy for a monitoring job.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] network_config
# Specifies networking configuration for the monitoring job.
# @return [Types::MonitoringNetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] stopping_condition
# A time limit for how long the monitoring job is allowed to run
# before stopping.
# @return [Types::MonitoringStoppingCondition]
#
# @!attribute [rw] tags
# (Optional) An array of key-value pairs. For more information, see
# [Using Cost Allocation Tags][1] in the *Amazon Web Services Billing
# and Cost Management User Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDataQualityJobDefinitionRequest AWS API Documentation
#
class CreateDataQualityJobDefinitionRequest < Struct.new(
:job_definition_name,
:data_quality_baseline_config,
:data_quality_app_specification,
:data_quality_job_input,
:data_quality_job_output_config,
:job_resources,
:network_config,
:role_arn,
:stopping_condition,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_arn
# The Amazon Resource Name (ARN) of the job definition.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDataQualityJobDefinitionResponse AWS API Documentation
#
class CreateDataQualityJobDefinitionResponse < Struct.new(
:job_definition_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet that the device belongs to.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) that has access to Amazon Web
# Services Internet of Things (IoT).
# @return [String]
#
# @!attribute [rw] description
# A description of the fleet.
# @return [String]
#
# @!attribute [rw] output_config
# The output configuration for storing sample data collected by the
# fleet.
# @return [Types::EdgeOutputConfig]
#
# @!attribute [rw] tags
# Creates tags for the specified fleet.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] enable_iot_role_alias
# Whether to create an Amazon Web Services IoT Role Alias during
# device fleet creation. The name of the role alias generated will
# match this pattern: "SageMakerEdge-\\\{DeviceFleetName\\}".
#
# For example, if your device fleet is called "demo-fleet", the name
# of the role alias will be "SageMakerEdge-demo-fleet".
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDeviceFleetRequest AWS API Documentation
#
class CreateDeviceFleetRequest < Struct.new(
:device_fleet_name,
:role_arn,
:description,
:output_config,
:tags,
:enable_iot_role_alias)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_name
# A name for the domain.
# @return [String]
#
# @!attribute [rw] auth_mode
# The mode of authentication that members use to access the domain.
# @return [String]
#
# @!attribute [rw] default_user_settings
# The default settings to use to create a user profile when
# `UserSettings` isn't specified in the call to the
# `CreateUserProfile` API.
#
# `SecurityGroups` is aggregated when specified in both calls. For all
# other settings in `UserSettings`, the values specified in
# `CreateUserProfile` take precedence over those specified in
# `CreateDomain`.
# @return [Types::UserSettings]
#
# @!attribute [rw] subnet_ids
# The VPC subnets that Studio uses for communication.
# @return [Array<String>]
#
# @!attribute [rw] vpc_id
# The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses
# for communication.
# @return [String]
#
# @!attribute [rw] tags
# Tags to associated with the Domain. Each tag consists of a key and
# an optional value. Tag keys must be unique per resource. Tags are
# searchable using the `Search` API.
#
# Tags that you specify for the Domain are also added to all Apps that
# the Domain launches.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] app_network_access_type
# Specifies the VPC used for non-EFS traffic. The default value is
# `PublicInternetOnly`.
#
# * `PublicInternetOnly` - Non-EFS traffic is through a VPC managed by
# Amazon SageMaker, which allows direct internet access
#
# * `VpcOnly` - All Studio traffic is through the specified VPC and
# subnets
# @return [String]
#
# @!attribute [rw] home_efs_file_system_kms_key_id
# Use `KmsKeyId`.
# @return [String]
#
# @!attribute [rw] kms_key_id
# SageMaker uses Amazon Web Services KMS to encrypt the EFS volume
# attached to the domain with an Amazon Web Services managed key by
# default. For more control, specify a customer managed key.
# @return [String]
#
# @!attribute [rw] app_security_group_management
# The entity that creates and manages the required security groups for
# inter-app communication in `VPCOnly` mode. Required when
# `CreateDomain.AppNetworkAccessType` is `VPCOnly` and
# `DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn`
# is provided.
# @return [String]
#
# @!attribute [rw] domain_settings
# A collection of `Domain` settings.
# @return [Types::DomainSettings]
#
# @!attribute [rw] default_space_settings
# The default settings used to create a space.
# @return [Types::DefaultSpaceSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDomainRequest AWS API Documentation
#
class CreateDomainRequest < Struct.new(
:domain_name,
:auth_mode,
:default_user_settings,
:subnet_ids,
:vpc_id,
:tags,
:app_network_access_type,
:home_efs_file_system_kms_key_id,
:kms_key_id,
:app_security_group_management,
:domain_settings,
:default_space_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_arn
# The Amazon Resource Name (ARN) of the created domain.
# @return [String]
#
# @!attribute [rw] url
# The URL to the created domain.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDomainResponse AWS API Documentation
#
class CreateDomainResponse < Struct.new(
:domain_arn,
:url)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan.
# @return [String]
#
# @!attribute [rw] model_configs
# List of models associated with the edge deployment plan.
# @return [Array<Types::EdgeDeploymentModelConfig>]
#
# @!attribute [rw] device_fleet_name
# The device fleet used for this edge deployment plan.
# @return [String]
#
# @!attribute [rw] stages
# List of stages of the edge deployment plan. The number of stages is
# limited to 10 per deployment.
# @return [Array<Types::DeploymentStage>]
#
# @!attribute [rw] tags
# List of tags with which to tag the edge deployment plan.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEdgeDeploymentPlanRequest AWS API Documentation
#
class CreateEdgeDeploymentPlanRequest < Struct.new(
:edge_deployment_plan_name,
:model_configs,
:device_fleet_name,
:stages,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_arn
# The ARN of the edge deployment plan.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEdgeDeploymentPlanResponse AWS API Documentation
#
class CreateEdgeDeploymentPlanResponse < Struct.new(
:edge_deployment_plan_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan.
# @return [String]
#
# @!attribute [rw] stages
# List of stages to be added to the edge deployment plan.
# @return [Array<Types::DeploymentStage>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEdgeDeploymentStageRequest AWS API Documentation
#
class CreateEdgeDeploymentStageRequest < Struct.new(
:edge_deployment_plan_name,
:stages)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_packaging_job_name
# The name of the edge packaging job.
# @return [String]
#
# @!attribute [rw] compilation_job_name
# The name of the SageMaker Neo compilation job that will be used to
# locate model artifacts for packaging.
# @return [String]
#
# @!attribute [rw] model_name
# The name of the model.
# @return [String]
#
# @!attribute [rw] model_version
# The version of the model.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that enables Amazon
# SageMaker to download and upload the model, and to contact SageMaker
# Neo.
# @return [String]
#
# @!attribute [rw] output_config
# Provides information about the output location for the packaged
# model.
# @return [Types::EdgeOutputConfig]
#
# @!attribute [rw] resource_key
# The Amazon Web Services KMS key to use when encrypting the EBS
# volume the edge packaging job runs on.
# @return [String]
#
# @!attribute [rw] tags
# Creates tags for the packaging job.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEdgePackagingJobRequest AWS API Documentation
#
class CreateEdgePackagingJobRequest < Struct.new(
:edge_packaging_job_name,
:compilation_job_name,
:model_name,
:model_version,
:role_arn,
:output_config,
:resource_key,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_config_name
# The name of the endpoint configuration. You specify this name in a
# [CreateEndpoint][1] request.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html
# @return [String]
#
# @!attribute [rw] production_variants
# An array of `ProductionVariant` objects, one for each model that you
# want to host at this endpoint.
# @return [Array<Types::ProductionVariant>]
#
# @!attribute [rw] data_capture_config
# Configuration to control how SageMaker captures inference data.
# @return [Types::DataCaptureConfig]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] kms_key_id
# The Amazon Resource Name (ARN) of a Amazon Web Services Key
# Management Service key that SageMaker uses to encrypt data on the
# storage volume attached to the ML compute instance that hosts the
# endpoint.
#
# The KmsKeyId can be any of the following formats:
#
# * Key ID: `1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Key ARN:
# `arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Alias name: `alias/ExampleAlias`
#
# * Alias name ARN:
# `arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias`
#
# The KMS key policy must grant permission to the IAM role that you
# specify in your `CreateEndpoint`, `UpdateEndpoint` requests. For
# more information, refer to the Amazon Web Services Key Management
# Service section[ Using Key Policies in Amazon Web Services KMS ][1]
#
# <note markdown="1"> Certain Nitro-based instances include local storage, dependent on
# the instance type. Local storage volumes are encrypted using a
# hardware module on the instance. You can't request a `KmsKeyId`
# when using an instance type with local storage. If any of the models
# that you specify in the `ProductionVariants` parameter use
# nitro-based instances with local storage, do not specify a value for
# the `KmsKeyId` parameter. If you specify a value for `KmsKeyId` when
# using any nitro-based instances with local storage, the call to
# `CreateEndpointConfig` fails.
#
# For a list of instance types that support local instance storage,
# see [Instance Store Volumes][2].
#
# For more information about local instance storage encryption, see
# [SSD Instance Store Volumes][3].
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html
# [2]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes
# [3]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.html
# @return [String]
#
# @!attribute [rw] async_inference_config
# Specifies configuration for how an endpoint performs asynchronous
# inference. This is a required field in order for your Endpoint to be
# invoked using [InvokeEndpointAsync][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_runtime_InvokeEndpointAsync.html
# @return [Types::AsyncInferenceConfig]
#
# @!attribute [rw] explainer_config
# A member of `CreateEndpointConfig` that enables explainers.
# @return [Types::ExplainerConfig]
#
# @!attribute [rw] shadow_production_variants
# An array of `ProductionVariant` objects, one for each model that you
# want to host at this endpoint in shadow mode with production traffic
# replicated from the model specified on `ProductionVariants`. If you
# use this field, you can only specify one variant for
# `ProductionVariants` and one variant for `ShadowProductionVariants`.
# @return [Array<Types::ProductionVariant>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpointConfigInput AWS API Documentation
#
class CreateEndpointConfigInput < Struct.new(
:endpoint_config_name,
:production_variants,
:data_capture_config,
:tags,
:kms_key_id,
:async_inference_config,
:explainer_config,
:shadow_production_variants)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_config_arn
# The Amazon Resource Name (ARN) of the endpoint configuration.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpointConfigOutput AWS API Documentation
#
class CreateEndpointConfigOutput < Struct.new(
:endpoint_config_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# The name of the endpoint.The name must be unique within an Amazon
# Web Services Region in your Amazon Web Services account. The name is
# case-insensitive in `CreateEndpoint`, but the case is preserved and
# must be matched in [InvokeEndpoint][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_runtime_InvokeEndpoint.html
# @return [String]
#
# @!attribute [rw] endpoint_config_name
# The name of an endpoint configuration. For more information, see
# [CreateEndpointConfig][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html
# @return [String]
#
# @!attribute [rw] deployment_config
# The deployment configuration for an endpoint, which contains the
# desired deployment strategy and rollback configurations.
# @return [Types::DeploymentConfig]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpointInput AWS API Documentation
#
class CreateEndpointInput < Struct.new(
:endpoint_name,
:endpoint_config_name,
:deployment_config,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_arn
# The Amazon Resource Name (ARN) of the endpoint.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateEndpointOutput AWS API Documentation
#
class CreateEndpointOutput < Struct.new(
:endpoint_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_name
# The name of the experiment. The name must be unique in your Amazon
# Web Services account and is not case-sensitive.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the experiment as displayed. The name doesn't need to
# be unique. If you don't specify `DisplayName`, the value in
# `ExperimentName` is displayed.
# @return [String]
#
# @!attribute [rw] description
# The description of the experiment.
# @return [String]
#
# @!attribute [rw] tags
# A list of tags to associate with the experiment. You can use
# [Search][1] API to search on the tags.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateExperimentRequest AWS API Documentation
#
class CreateExperimentRequest < Struct.new(
:experiment_name,
:display_name,
:description,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_arn
# The Amazon Resource Name (ARN) of the experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateExperimentResponse AWS API Documentation
#
class CreateExperimentResponse < Struct.new(
:experiment_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_name
# The name of the `FeatureGroup`. The name must be unique within an
# Amazon Web Services Region in an Amazon Web Services account. The
# name:
#
# * Must start and end with an alphanumeric character.
#
# * Can only contain alphanumeric character and hyphens. Spaces are
# not allowed.
# @return [String]
#
# @!attribute [rw] record_identifier_feature_name
# The name of the `Feature` whose value uniquely identifies a `Record`
# defined in the `FeatureStore`. Only the latest record per identifier
# value will be stored in the `OnlineStore`.
# `RecordIdentifierFeatureName` must be one of feature definitions'
# names.
#
# You use the `RecordIdentifierFeatureName` to access data in a
# `FeatureStore`.
#
# This name:
#
# * Must start and end with an alphanumeric character.
#
# * Can only contains alphanumeric characters, hyphens, underscores.
# Spaces are not allowed.
# @return [String]
#
# @!attribute [rw] event_time_feature_name
# The name of the feature that stores the `EventTime` of a `Record` in
# a `FeatureGroup`.
#
# An `EventTime` is a point in time when a new event occurs that
# corresponds to the creation or update of a `Record` in a
# `FeatureGroup`. All `Records` in the `FeatureGroup` must have a
# corresponding `EventTime`.
#
# An `EventTime` can be a `String` or `Fractional`.
#
# * `Fractional`: `EventTime` feature values must be a Unix timestamp
# in seconds.
#
# * `String`: `EventTime` feature values must be an ISO-8601 string in
# the format. The following formats are supported
# `yyyy-MM-dd'T'HH:mm:ssZ` and `yyyy-MM-dd'T'HH:mm:ss.SSSZ` where
# `yyyy`, `MM`, and `dd` represent the year, month, and day
# respectively and `HH`, `mm`, `ss`, and if applicable, `SSS`
# represent the hour, month, second and milliseconds respsectively.
# `'T'` and `Z` are constants.
# @return [String]
#
# @!attribute [rw] feature_definitions
# A list of `Feature` names and types. `Name` and `Type` is compulsory
# per `Feature`.
#
# Valid feature `FeatureType`s are `Integral`, `Fractional` and
# `String`.
#
# `FeatureName`s cannot be any of the following: `is_deleted`,
# `write_time`, `api_invocation_time`
#
# You can create up to 2,500 `FeatureDefinition`s per `FeatureGroup`.
# @return [Array<Types::FeatureDefinition>]
#
# @!attribute [rw] online_store_config
# You can turn the `OnlineStore` on or off by specifying `True` for
# the `EnableOnlineStore` flag in `OnlineStoreConfig`.
#
# You can also include an Amazon Web Services KMS key ID (`KMSKeyId`)
# for at-rest encryption of the `OnlineStore`.
#
# The default value is `False`.
# @return [Types::OnlineStoreConfig]
#
# @!attribute [rw] offline_store_config
# Use this to configure an `OfflineFeatureStore`. This parameter
# allows you to specify:
#
# * The Amazon Simple Storage Service (Amazon S3) location of an
# `OfflineStore`.
#
# * A configuration for an Amazon Web Services Glue or Amazon Web
# Services Hive data catalog.
#
# * An KMS encryption key to encrypt the Amazon S3 location used for
# `OfflineStore`. If KMS encryption key is not specified, by default
# we encrypt all data at rest using Amazon Web Services KMS key. By
# defining your [bucket-level key][1] for SSE, you can reduce Amazon
# Web Services KMS requests costs by up to 99 percent.
#
# * Format for the offline store table. Supported formats are Glue
# (Default) and [Apache Iceberg][2].
#
# To learn more about this parameter, see [OfflineStoreConfig][3].
#
#
#
# [1]: https://docs.aws.amazon.com/AmazonS3/latest/userguide/bucket-key.html
# [2]: https://iceberg.apache.org/
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OfflineStoreConfig.html
# @return [Types::OfflineStoreConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the IAM execution role used to
# persist data into the `OfflineStore` if an `OfflineStoreConfig` is
# provided.
# @return [String]
#
# @!attribute [rw] description
# A free-form description of a `FeatureGroup`.
# @return [String]
#
# @!attribute [rw] tags
# Tags used to identify `Features` in each `FeatureGroup`.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFeatureGroupRequest AWS API Documentation
#
class CreateFeatureGroupRequest < Struct.new(
:feature_group_name,
:record_identifier_feature_name,
:event_time_feature_name,
:feature_definitions,
:online_store_config,
:offline_store_config,
:role_arn,
:description,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_arn
# The Amazon Resource Name (ARN) of the `FeatureGroup`. This is a
# unique identifier for the feature group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFeatureGroupResponse AWS API Documentation
#
class CreateFeatureGroupResponse < Struct.new(
:feature_group_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] flow_definition_name
# The name of your flow definition.
# @return [String]
#
# @!attribute [rw] human_loop_request_source
# Container for configuring the source of human task requests. Use to
# specify if Amazon Rekognition or Amazon Textract is used as an
# integration source.
# @return [Types::HumanLoopRequestSource]
#
# @!attribute [rw] human_loop_activation_config
# An object containing information about the events that trigger a
# human workflow.
# @return [Types::HumanLoopActivationConfig]
#
# @!attribute [rw] human_loop_config
# An object containing information about the tasks the human reviewers
# will perform.
# @return [Types::HumanLoopConfig]
#
# @!attribute [rw] output_config
# An object containing information about where the human review
# results will be uploaded.
# @return [Types::FlowDefinitionOutputConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the role needed to call other
# services on your behalf. For example,
# `arn:aws:iam::1234567890:role/service-role/AmazonSageMaker-ExecutionRole-20180111T151298`.
# @return [String]
#
# @!attribute [rw] tags
# An array of key-value pairs that contain metadata to help you
# categorize and organize a flow definition. Each tag consists of a
# key and a value, both of which you define.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFlowDefinitionRequest AWS API Documentation
#
class CreateFlowDefinitionRequest < Struct.new(
:flow_definition_name,
:human_loop_request_source,
:human_loop_activation_config,
:human_loop_config,
:output_config,
:role_arn,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] flow_definition_arn
# The Amazon Resource Name (ARN) of the flow definition you create.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFlowDefinitionResponse AWS API Documentation
#
class CreateFlowDefinitionResponse < Struct.new(
:flow_definition_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_name
# The name of the hub to create.
# @return [String]
#
# @!attribute [rw] hub_description
# A description of the hub.
# @return [String]
#
# @!attribute [rw] hub_display_name
# The display name of the hub.
# @return [String]
#
# @!attribute [rw] hub_search_keywords
# The searchable keywords for the hub.
# @return [Array<String>]
#
# @!attribute [rw] s3_storage_config
# The Amazon S3 storage configuration for the hub.
# @return [Types::HubS3StorageConfig]
#
# @!attribute [rw] tags
# Any tags to associate with the hub.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHubRequest AWS API Documentation
#
class CreateHubRequest < Struct.new(
:hub_name,
:hub_description,
:hub_display_name,
:hub_search_keywords,
:s3_storage_config,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_arn
# The Amazon Resource Name (ARN) of the hub.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHubResponse AWS API Documentation
#
class CreateHubResponse < Struct.new(
:hub_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] human_task_ui_name
# The name of the user interface you are creating.
# @return [String]
#
# @!attribute [rw] ui_template
# The Liquid template for the worker user interface.
# @return [Types::UiTemplate]
#
# @!attribute [rw] tags
# An array of key-value pairs that contain metadata to help you
# categorize and organize a human review workflow user interface. Each
# tag consists of a key and a value, both of which you define.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHumanTaskUiRequest AWS API Documentation
#
class CreateHumanTaskUiRequest < Struct.new(
:human_task_ui_name,
:ui_template,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] human_task_ui_arn
# The Amazon Resource Name (ARN) of the human review workflow user
# interface you create.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHumanTaskUiResponse AWS API Documentation
#
class CreateHumanTaskUiResponse < Struct.new(
:human_task_ui_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hyper_parameter_tuning_job_name
# The name of the tuning job. This name is the prefix for the names of
# all training jobs that this tuning job launches. The name must be
# unique within the same Amazon Web Services account and Amazon Web
# Services Region. The name must have 1 to 32 characters. Valid
# characters are a-z, A-Z, 0-9, and : + = @ \_ % - (hyphen). The name
# is not case sensitive.
# @return [String]
#
# @!attribute [rw] hyper_parameter_tuning_job_config
# The [HyperParameterTuningJobConfig][1] object that describes the
# tuning job, including the search strategy, the objective metric used
# to evaluate training jobs, ranges of parameters to search, and
# resource limits for the tuning job. For more information, see [How
# Hyperparameter Tuning Works][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.html
# @return [Types::HyperParameterTuningJobConfig]
#
# @!attribute [rw] training_job_definition
# The [HyperParameterTrainingJobDefinition][1] object that describes
# the training jobs that this tuning job launches, including static
# hyperparameters, input data configuration, output data
# configuration, resource configuration, and stopping condition.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html
# @return [Types::HyperParameterTrainingJobDefinition]
#
# @!attribute [rw] training_job_definitions
# A list of the [HyperParameterTrainingJobDefinition][1] objects
# launched for this tuning job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html
# @return [Array<Types::HyperParameterTrainingJobDefinition>]
#
# @!attribute [rw] warm_start_config
# Specifies the configuration for starting the hyperparameter tuning
# job using one or more previous tuning jobs as a starting point. The
# results of previous tuning jobs are used to inform which
# combinations of hyperparameters to search over in the new tuning
# job.
#
# All training jobs launched by the new hyperparameter tuning job are
# evaluated by using the objective metric. If you specify
# `IDENTICAL_DATA_AND_ALGORITHM` as the `WarmStartType` value for the
# warm start configuration, the training job that performs the best in
# the new tuning job is compared to the best training jobs from the
# parent tuning jobs. From these, the training job that performs the
# best as measured by the objective metric is returned as the overall
# best training job.
#
# <note markdown="1"> 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.
#
# </note>
# @return [Types::HyperParameterTuningJobWarmStartConfig]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
# Tags that you specify for the tuning job are also added to all
# training jobs that the tuning job launches.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHyperParameterTuningJobRequest AWS API Documentation
#
class CreateHyperParameterTuningJobRequest < Struct.new(
:hyper_parameter_tuning_job_name,
:hyper_parameter_tuning_job_config,
:training_job_definition,
:training_job_definitions,
:warm_start_config,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hyper_parameter_tuning_job_arn
# The Amazon Resource Name (ARN) of the tuning job. SageMaker assigns
# an ARN to a hyperparameter tuning job when you create it.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHyperParameterTuningJobResponse AWS API Documentation
#
class CreateHyperParameterTuningJobResponse < Struct.new(
:hyper_parameter_tuning_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] description
# The description of the image.
# @return [String]
#
# @!attribute [rw] display_name
# The display name of the image. If not provided, `ImageName` is
# displayed.
# @return [String]
#
# @!attribute [rw] image_name
# The name of the image. Must be unique to your account.
# @return [String]
#
# @!attribute [rw] role_arn
# The ARN of an IAM role that enables Amazon SageMaker to perform
# tasks on your behalf.
# @return [String]
#
# @!attribute [rw] tags
# A list of tags to apply to the image.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateImageRequest AWS API Documentation
#
class CreateImageRequest < Struct.new(
:description,
:display_name,
:image_name,
:role_arn,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_arn
# The ARN of the image.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateImageResponse AWS API Documentation
#
class CreateImageResponse < Struct.new(
:image_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] base_image
# The registry path of the container image to use as the starting
# point for this version. The path is an Amazon Elastic Container
# Registry (ECR) URI in the following format:
#
# `<acct-id>.dkr.ecr.<region>.amazonaws.com/<repo-name[:tag] or
# [@digest]>`
# @return [String]
#
# @!attribute [rw] client_token
# A unique ID. If not specified, the Amazon Web Services CLI and
# Amazon Web Services SDKs, such as the SDK for Python (Boto3), add a
# unique value to the call.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @!attribute [rw] image_name
# The `ImageName` of the `Image` to create a version of.
# @return [String]
#
# @!attribute [rw] aliases
# A list of aliases created with the image version.
# @return [Array<String>]
#
# @!attribute [rw] vendor_guidance
# The stability of the image version, specified by the maintainer.
#
# * `NOT_PROVIDED`: The maintainers did not provide a status for image
# version stability.
#
# * `STABLE`: The image version is stable.
#
# * `TO_BE_ARCHIVED`: The image version is set to be archived. Custom
# image versions that are set to be archived are automatically
# archived after three months.
#
# * `ARCHIVED`: The image version is archived. Archived image versions
# are not searchable and are no longer actively supported.
# @return [String]
#
# @!attribute [rw] job_type
# Indicates SageMaker job type compatibility.
#
# * `TRAINING`: The image version is compatible with SageMaker
# training jobs.
#
# * `INFERENCE`: The image version is compatible with SageMaker
# inference jobs.
#
# * `NOTEBOOK_KERNEL`: The image version is compatible with SageMaker
# notebook kernels.
# @return [String]
#
# @!attribute [rw] ml_framework
# The machine learning framework vended in the image version.
# @return [String]
#
# @!attribute [rw] programming_lang
# The supported programming language and its version.
# @return [String]
#
# @!attribute [rw] processor
# Indicates CPU or GPU compatibility.
#
# * `CPU`: The image version is compatible with CPU.
#
# * `GPU`: The image version is compatible with GPU.
# @return [String]
#
# @!attribute [rw] horovod
# Indicates Horovod compatibility.
# @return [Boolean]
#
# @!attribute [rw] release_notes
# The maintainer description of the image version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateImageVersionRequest AWS API Documentation
#
class CreateImageVersionRequest < Struct.new(
:base_image,
:client_token,
:image_name,
:aliases,
:vendor_guidance,
:job_type,
:ml_framework,
:programming_lang,
:processor,
:horovod,
:release_notes)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_version_arn
# The ARN of the image version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateImageVersionResponse AWS API Documentation
#
class CreateImageVersionResponse < Struct.new(
:image_version_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name
# The name for the inference experiment.
# @return [String]
#
# @!attribute [rw] type
# The type of the inference experiment that you want to run. The
# following types of experiments are possible:
#
# * `ShadowMode`: You can use this type to validate a shadow variant.
# For more information, see [Shadow tests][1].
#
# ^
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/shadow-tests.html
# @return [String]
#
# @!attribute [rw] schedule
# The duration for which you want the inference experiment to run. If
# you don't specify this field, the experiment automatically starts
# immediately upon creation and concludes after 7 days.
# @return [Types::InferenceExperimentSchedule]
#
# @!attribute [rw] description
# A description for the inference experiment.
# @return [String]
#
# @!attribute [rw] role_arn
# The ARN of the IAM role that Amazon SageMaker can assume to access
# model artifacts and container images, and manage Amazon SageMaker
# Inference endpoints for model deployment.
# @return [String]
#
# @!attribute [rw] endpoint_name
# The name of the Amazon SageMaker endpoint on which you want to run
# the inference experiment.
# @return [String]
#
# @!attribute [rw] model_variants
# An array of `ModelVariantConfig` objects. There is one for each
# variant in the inference experiment. Each `ModelVariantConfig`
# object in the array describes the infrastructure configuration for
# the corresponding variant.
# @return [Array<Types::ModelVariantConfig>]
#
# @!attribute [rw] data_storage_config
# The Amazon S3 location and configuration for storing inference
# request and response data.
#
# This is an optional parameter that you can use for data capture. For
# more information, see [Capture data][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-data-capture.html
# @return [Types::InferenceExperimentDataStorageConfig]
#
# @!attribute [rw] shadow_mode_config
# The configuration of `ShadowMode` inference experiment type. Use
# this field to specify a production variant which takes all the
# inference requests, and a shadow variant to which Amazon SageMaker
# replicates a percentage of the inference requests. For the shadow
# variant also specify the percentage of requests that Amazon
# SageMaker replicates.
# @return [Types::ShadowModeConfig]
#
# @!attribute [rw] kms_key
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt data on the storage
# volume attached to the ML compute instance that hosts the endpoint.
# The `KmsKey` can be any of the following formats:
#
# * KMS key ID
#
# `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * Amazon Resource Name (ARN) of a KMS key
#
# `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * KMS key Alias
#
# `"alias/ExampleAlias"`
#
# * Amazon Resource Name (ARN) of a KMS key Alias
#
# `"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"`
#
# If you use a KMS key ID or an alias of your KMS key, the Amazon
# SageMaker execution role must include permissions to call
# `kms:Encrypt`. If you don't provide a KMS key ID, Amazon SageMaker
# uses the default KMS key for Amazon S3 for your role's account.
# Amazon SageMaker uses server-side encryption with KMS managed keys
# for `OutputDataConfig`. If you use a bucket policy with an
# `s3:PutObject` permission that only allows objects with server-side
# encryption, set the condition key of
# `s3:x-amz-server-side-encryption` to `"aws:kms"`. For more
# information, see [KMS managed Encryption Keys][1] in the *Amazon
# Simple Storage Service Developer Guide.*
#
# The KMS key policy must grant permission to the IAM role that you
# specify in your `CreateEndpoint` and `UpdateEndpoint` requests. For
# more information, see [Using Key Policies in Amazon Web Services
# KMS][2] in the *Amazon Web Services Key Management Service Developer
# Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html
# [2]: https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html
# @return [String]
#
# @!attribute [rw] tags
# Array of key-value pairs. You can use tags to categorize your Amazon
# Web Services resources in different ways, for example, by purpose,
# owner, or environment. For more information, see [Tagging your
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/ARG/latest/userguide/tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateInferenceExperimentRequest AWS API Documentation
#
class CreateInferenceExperimentRequest < Struct.new(
:name,
:type,
:schedule,
:description,
:role_arn,
:endpoint_name,
:model_variants,
:data_storage_config,
:shadow_mode_config,
:kms_key,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] inference_experiment_arn
# The ARN for your inference experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateInferenceExperimentResponse AWS API Documentation
#
class CreateInferenceExperimentResponse < Struct.new(
:inference_experiment_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_name
# A name for the recommendation job. The name must be unique within
# the Amazon Web Services Region and within your Amazon Web Services
# account. The job name is passed down to the resources created by the
# recommendation job. The names of resources (such as the model,
# endpoint configuration, endpoint, and compilation) that are prefixed
# with the job name are truncated at 40 characters.
# @return [String]
#
# @!attribute [rw] job_type
# Defines the type of recommendation job. Specify `Default` to
# initiate an instance recommendation and `Advanced` to initiate a
# load test. If left unspecified, Amazon SageMaker Inference
# Recommender will run an instance recommendation (`DEFAULT`) job.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that enables Amazon
# SageMaker to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] input_config
# Provides information about the versioned model package Amazon
# Resource Name (ARN), the traffic pattern, and endpoint
# configurations.
# @return [Types::RecommendationJobInputConfig]
#
# @!attribute [rw] job_description
# Description of the recommendation job.
# @return [String]
#
# @!attribute [rw] stopping_conditions
# A set of conditions for stopping a recommendation job. If any of the
# conditions are met, the job is automatically stopped.
# @return [Types::RecommendationJobStoppingConditions]
#
# @!attribute [rw] output_config
# Provides information about the output artifacts and the KMS key to
# use for Amazon S3 server-side encryption.
# @return [Types::RecommendationJobOutputConfig]
#
# @!attribute [rw] tags
# The metadata that you apply to Amazon Web Services resources to help
# you categorize and organize them. Each tag consists of a key and a
# value, both of which you define. For more information, see [Tagging
# Amazon Web Services Resources][1] in the Amazon Web Services General
# Reference.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateInferenceRecommendationsJobRequest AWS API Documentation
#
class CreateInferenceRecommendationsJobRequest < Struct.new(
:job_name,
:job_type,
:role_arn,
:input_config,
:job_description,
:stopping_conditions,
:output_config,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_arn
# The Amazon Resource Name (ARN) of the recommendation job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateInferenceRecommendationsJobResponse AWS API Documentation
#
class CreateInferenceRecommendationsJobResponse < Struct.new(
:job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] labeling_job_name
# The name of the labeling job. This name is used to identify the job
# in a list of labeling jobs. Labeling job names must be unique within
# an Amazon Web Services account and region. `LabelingJobName` is not
# case sensitive. For example, Example-job and example-job are
# considered the same labeling job name by Ground Truth.
# @return [String]
#
# @!attribute [rw] label_attribute_name
# The attribute name to use for the label in the output manifest file.
# This is the key for the key/value pair formed with the label that a
# worker assigns to the object. The `LabelAttributeName` must meet the
# following requirements.
#
# * The name can't end with "-metadata".
#
# * If you are using one of the following [built-in task types][1],
# the attribute name *must* end with "-ref". If the task type you
# are using is not listed below, the attribute name *must not* end
# with "-ref".
#
# * Image semantic segmentation (`SemanticSegmentation)`, and
# adjustment (`AdjustmentSemanticSegmentation`) and verification
# (`VerificationSemanticSegmentation`) labeling jobs for this task
# type.
#
# * Video frame object detection (`VideoObjectDetection`), and
# adjustment and verification (`AdjustmentVideoObjectDetection`)
# labeling jobs for this task type.
#
# * Video frame object tracking (`VideoObjectTracking`), and
# adjustment and verification (`AdjustmentVideoObjectTracking`)
# labeling jobs for this task type.
#
# * 3D point cloud semantic segmentation
# (`3DPointCloudSemanticSegmentation`), and adjustment and
# verification (`Adjustment3DPointCloudSemanticSegmentation`)
# labeling jobs for this task type.
#
# * 3D point cloud object tracking (`3DPointCloudObjectTracking`),
# and adjustment and verification
# (`Adjustment3DPointCloudObjectTracking`) labeling jobs for this
# task type.
#
#
#
# If you are creating an adjustment or verification labeling job, you
# must use a *different* `LabelAttributeName` than the one used in the
# original labeling job. The original labeling job is the Ground Truth
# labeling job that produced the labels that you want verified or
# adjusted. To learn more about adjustment and verification labeling
# jobs, see [Verify and Adjust Labels][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.html
# @return [String]
#
# @!attribute [rw] input_config
# Input data for the labeling job, such as the Amazon S3 location of
# the data objects and the location of the manifest file that
# describes the data objects.
#
# You must specify at least one of the following: `S3DataSource` or
# `SnsDataSource`.
#
# * Use `SnsDataSource` to 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 that stops after
# all data objects in the input manifest file have been labeled.
#
# * Use `S3DataSource` to specify an input manifest file for both
# streaming and one-time labeling jobs. Adding an `S3DataSource` is
# optional if you use `SnsDataSource` to create a streaming labeling
# job.
#
# If you use the Amazon Mechanical Turk workforce, your input data
# should not include confidential information, personal information or
# protected health information. Use `ContentClassifiers` to specify
# that your data is free of personally identifiable information and
# adult content.
# @return [Types::LabelingJobInputConfig]
#
# @!attribute [rw] output_config
# The location of the output data and the Amazon Web Services Key
# Management Service key ID for the key used to encrypt the output
# data, if any.
# @return [Types::LabelingJobOutputConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Number (ARN) that Amazon SageMaker assumes to
# perform tasks on your behalf during data labeling. You must grant
# this role the necessary permissions so that Amazon SageMaker can
# successfully complete data labeling.
# @return [String]
#
# @!attribute [rw] label_category_config_s3_uri
# The S3 URI of the file, referred to as a *label category
# configuration file*, that defines the categories used to label the
# data objects.
#
# For 3D point cloud and video frame task types, you can add label
# category attributes and frame attributes to your label category
# configuration file. To learn how, see [Create a Labeling Category
# Configuration File for 3D Point Cloud Labeling Jobs][1].
#
# For named entity recognition jobs, in addition to `"labels"`, you
# must provide worker instructions in the label category configuration
# file using the `"instructions"` parameter: `"instructions":
# \{"shortInstruction":"<h1>Add header</h1><p>Add Instructions</p>",
# "fullInstruction":"<p>Add additional instructions.</p>"\}`. For
# details and an example, see [Create a Named Entity Recognition
# Labeling Job (API) ][2].
#
# For all other [built-in task types][3] and [custom tasks][4], your
# label category configuration file must be a JSON file in the
# following format. Identify the labels you want to use by replacing
# `label_1`, `label_2`,`...`,`label_n` with your label categories.
#
# `\{ `
#
# `"document-version": "2018-11-28",`
#
# `"labels": [\{"label": "label_1"\},\{"label":
# "label_2"\},...\{"label": "label_n"\}]`
#
# `\}`
#
# Note the following about the label category configuration file:
#
# * For image classification and text classification (single and
# multi-label) you must specify at least two label categories. For
# all other task types, the minimum number of label categories
# required is one.
#
# * Each label category must be unique, you cannot specify duplicate
# label categories.
#
# * If you create a 3D point cloud or video frame adjustment or
# verification labeling job, you must include
# `auditLabelAttributeName` in the label category configuration. Use
# this parameter to enter the [ `LabelAttributeName` ][5] of the
# labeling job you want to adjust or verify annotations of.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-label-category-config.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-named-entity-recg.html#sms-creating-ner-api
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html
# [4]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates.html
# [5]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateLabelingJob.html#sagemaker-CreateLabelingJob-request-LabelAttributeName
# @return [String]
#
# @!attribute [rw] stopping_conditions
# A set of conditions for stopping the labeling job. If any of the
# conditions are met, the job is automatically stopped. You can use
# these conditions to control the cost of data labeling.
# @return [Types::LabelingJobStoppingConditions]
#
# @!attribute [rw] labeling_job_algorithms_config
# Configures the information required to perform automated data
# labeling.
# @return [Types::LabelingJobAlgorithmsConfig]
#
# @!attribute [rw] human_task_config
# Configures the labeling task and how it is presented to workers;
# including, but not limited to price, keywords, and batch size (task
# count).
# @return [Types::HumanTaskConfig]
#
# @!attribute [rw] tags
# An array of key/value pairs. For more information, see [Using Cost
# Allocation Tags][1] in the *Amazon Web Services Billing and Cost
# Management User Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateLabelingJobRequest AWS API Documentation
#
class CreateLabelingJobRequest < Struct.new(
:labeling_job_name,
:label_attribute_name,
:input_config,
:output_config,
:role_arn,
:label_category_config_s3_uri,
:stopping_conditions,
:labeling_job_algorithms_config,
:human_task_config,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] labeling_job_arn
# The Amazon Resource Name (ARN) of the labeling job. You use this ARN
# to identify the labeling job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateLabelingJobResponse AWS API Documentation
#
class CreateLabelingJobResponse < Struct.new(
:labeling_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the bias job definition. The name must be unique within
# an Amazon Web Services Region in the Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] model_bias_baseline_config
# The baseline configuration for a model bias job.
# @return [Types::ModelBiasBaselineConfig]
#
# @!attribute [rw] model_bias_app_specification
# Configures the model bias job to run a specified Docker container
# image.
# @return [Types::ModelBiasAppSpecification]
#
# @!attribute [rw] model_bias_job_input
# Inputs for the model bias job.
# @return [Types::ModelBiasJobInput]
#
# @!attribute [rw] model_bias_job_output_config
# The output configuration for monitoring jobs.
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] job_resources
# Identifies the resources to deploy for a monitoring job.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] network_config
# Networking options for a model bias job.
# @return [Types::MonitoringNetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] stopping_condition
# A time limit for how long the monitoring job is allowed to run
# before stopping.
# @return [Types::MonitoringStoppingCondition]
#
# @!attribute [rw] tags
# (Optional) An array of key-value pairs. For more information, see
# [Using Cost Allocation Tags][1] in the *Amazon Web Services Billing
# and Cost Management User Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelBiasJobDefinitionRequest AWS API Documentation
#
class CreateModelBiasJobDefinitionRequest < Struct.new(
:job_definition_name,
:model_bias_baseline_config,
:model_bias_app_specification,
:model_bias_job_input,
:model_bias_job_output_config,
:job_resources,
:network_config,
:role_arn,
:stopping_condition,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_arn
# The Amazon Resource Name (ARN) of the model bias job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelBiasJobDefinitionResponse AWS API Documentation
#
class CreateModelBiasJobDefinitionResponse < Struct.new(
:job_definition_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_name
# The name of the model card to export.
# @return [String]
#
# @!attribute [rw] model_card_version
# The version of the model card to export. If a version is not
# provided, then the latest version of the model card is exported.
# @return [Integer]
#
# @!attribute [rw] model_card_export_job_name
# The name of the model card export job.
# @return [String]
#
# @!attribute [rw] output_config
# The model card output configuration that specifies the Amazon S3
# path for exporting.
# @return [Types::ModelCardExportOutputConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelCardExportJobRequest AWS API Documentation
#
class CreateModelCardExportJobRequest < Struct.new(
:model_card_name,
:model_card_version,
:model_card_export_job_name,
:output_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_export_job_arn
# The Amazon Resource Name (ARN) of the model card export job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelCardExportJobResponse AWS API Documentation
#
class CreateModelCardExportJobResponse < Struct.new(
:model_card_export_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_name
# The unique name of the model card.
# @return [String]
#
# @!attribute [rw] security_config
# An optional Key Management Service key to encrypt, decrypt, and
# re-encrypt model card content for regulated workloads with highly
# sensitive data.
# @return [Types::ModelCardSecurityConfig]
#
# @!attribute [rw] content
# The content of the model card. Content must be in [model card JSON
# schema][1] and provided as a string.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards.html#model-cards-json-schema
# @return [String]
#
# @!attribute [rw] model_card_status
# The approval status of the model card within your organization.
# Different organizations might have different criteria for model card
# review and approval.
#
# * `Draft`: The model card is a work in progress.
#
# * `PendingReview`: The model card is pending review.
#
# * `Approved`: The model card is approved.
#
# * `Archived`: The model card is archived. No more updates should be
# made to the model card, but it can still be exported.
# @return [String]
#
# @!attribute [rw] tags
# Key-value pairs used to manage metadata for model cards.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelCardRequest AWS API Documentation
#
class CreateModelCardRequest < Struct.new(
:model_card_name,
:security_config,
:content,
:model_card_status,
:tags)
SENSITIVE = [:content]
include Aws::Structure
end
# @!attribute [rw] model_card_arn
# The Amazon Resource Name (ARN) of the successfully created model
# card.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelCardResponse AWS API Documentation
#
class CreateModelCardResponse < Struct.new(
:model_card_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the model explainability job definition. The name must
# be unique within an Amazon Web Services Region in the Amazon Web
# Services account.
# @return [String]
#
# @!attribute [rw] model_explainability_baseline_config
# The baseline configuration for a model explainability job.
# @return [Types::ModelExplainabilityBaselineConfig]
#
# @!attribute [rw] model_explainability_app_specification
# Configures the model explainability job to run a specified Docker
# container image.
# @return [Types::ModelExplainabilityAppSpecification]
#
# @!attribute [rw] model_explainability_job_input
# Inputs for the model explainability job.
# @return [Types::ModelExplainabilityJobInput]
#
# @!attribute [rw] model_explainability_job_output_config
# The output configuration for monitoring jobs.
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] job_resources
# Identifies the resources to deploy for a monitoring job.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] network_config
# Networking options for a model explainability job.
# @return [Types::MonitoringNetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] stopping_condition
# A time limit for how long the monitoring job is allowed to run
# before stopping.
# @return [Types::MonitoringStoppingCondition]
#
# @!attribute [rw] tags
# (Optional) An array of key-value pairs. For more information, see
# [Using Cost Allocation Tags][1] in the *Amazon Web Services Billing
# and Cost Management User Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelExplainabilityJobDefinitionRequest AWS API Documentation
#
class CreateModelExplainabilityJobDefinitionRequest < Struct.new(
:job_definition_name,
:model_explainability_baseline_config,
:model_explainability_app_specification,
:model_explainability_job_input,
:model_explainability_job_output_config,
:job_resources,
:network_config,
:role_arn,
:stopping_condition,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_arn
# The Amazon Resource Name (ARN) of the model explainability job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelExplainabilityJobDefinitionResponse AWS API Documentation
#
class CreateModelExplainabilityJobDefinitionResponse < Struct.new(
:job_definition_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_name
# The name of the new model.
# @return [String]
#
# @!attribute [rw] primary_container
# The location of the primary docker image containing inference code,
# associated artifacts, and custom environment map that the inference
# code uses when the model is deployed for predictions.
# @return [Types::ContainerDefinition]
#
# @!attribute [rw] containers
# Specifies the containers in the inference pipeline.
# @return [Array<Types::ContainerDefinition>]
#
# @!attribute [rw] inference_execution_config
# Specifies details of how containers in a multi-container endpoint
# are called.
# @return [Types::InferenceExecutionConfig]
#
# @!attribute [rw] execution_role_arn
# The Amazon Resource Name (ARN) of the IAM role that SageMaker can
# assume to access model artifacts and docker image for deployment on
# ML compute instances or for batch transform jobs. Deploying on ML
# compute instances is part of model hosting. For more information,
# see [SageMaker Roles][1].
#
# <note markdown="1"> To be able to pass this role to SageMaker, the caller of this API
# must have the `iam:PassRole` permission.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html
# @return [String]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] vpc_config
# A [VpcConfig][1] object that specifies the VPC that you want your
# model to connect to. Control access to and from your model container
# by configuring the VPC. `VpcConfig` is used in hosting services and
# in batch transform. For more information, see [Protect Endpoints by
# Using an Amazon Virtual Private Cloud][2] and [Protect Data in Batch
# Transform Jobs by Using an Amazon Virtual Private Cloud][3].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-vpc.html
# @return [Types::VpcConfig]
#
# @!attribute [rw] enable_network_isolation
# Isolates the model container. No inbound or outbound network calls
# can be made to or from the model container.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelInput AWS API Documentation
#
class CreateModelInput < Struct.new(
:model_name,
:primary_container,
:containers,
:inference_execution_config,
:execution_role_arn,
:tags,
:vpc_config,
:enable_network_isolation)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_arn
# The ARN of the model created in SageMaker.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelOutput AWS API Documentation
#
class CreateModelOutput < Struct.new(
:model_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_name
# The name of the model group.
# @return [String]
#
# @!attribute [rw] model_package_group_description
# A description for the model group.
# @return [String]
#
# @!attribute [rw] tags
# A list of key value pairs associated with the model group. For more
# information, see [Tagging Amazon Web Services resources][1] in the
# *Amazon Web Services General Reference Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelPackageGroupInput AWS API Documentation
#
class CreateModelPackageGroupInput < Struct.new(
:model_package_group_name,
:model_package_group_description,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_arn
# The Amazon Resource Name (ARN) of the model group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelPackageGroupOutput AWS API Documentation
#
class CreateModelPackageGroupOutput < Struct.new(
:model_package_group_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_name
# The name of the model package. The name must have 1 to 63
# characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
#
# This parameter is required for unversioned models. It is not
# applicable to versioned models.
# @return [String]
#
# @!attribute [rw] model_package_group_name
# The name or Amazon Resource Name (ARN) of the model package group
# that this model version belongs to.
#
# This parameter is required for versioned models, and does not apply
# to unversioned models.
# @return [String]
#
# @!attribute [rw] model_package_description
# A description of the model package.
# @return [String]
#
# @!attribute [rw] inference_specification
# Specifies details about inference jobs that can be run with models
# based on this model package, including the following:
#
# * The Amazon ECR paths of containers that contain the inference code
# and model artifacts.
#
# * The instance types that the model package supports for transform
# jobs and real-time endpoints used for inference.
#
# * The input and output content formats that the model package
# supports for inference.
# @return [Types::InferenceSpecification]
#
# @!attribute [rw] validation_specification
# Specifies configurations for one or more transform jobs that
# SageMaker runs to test the model package.
# @return [Types::ModelPackageValidationSpecification]
#
# @!attribute [rw] source_algorithm_specification
# Details about the algorithm that was used to create the model
# package.
# @return [Types::SourceAlgorithmSpecification]
#
# @!attribute [rw] certify_for_marketplace
# Whether to certify the model package for listing on Amazon Web
# Services Marketplace.
#
# This parameter is optional for unversioned models, and does not
# apply to versioned models.
# @return [Boolean]
#
# @!attribute [rw] tags
# A list of key value pairs associated with the model. For more
# information, see [Tagging Amazon Web Services resources][1] in the
# *Amazon Web Services General Reference Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] model_approval_status
# Whether the model is approved for deployment.
#
# This parameter is optional for versioned models, and does not apply
# to unversioned models.
#
# For versioned models, the value of this parameter must be set to
# `Approved` to deploy the model.
# @return [String]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] model_metrics
# A structure that contains model metrics reports.
# @return [Types::ModelMetrics]
#
# @!attribute [rw] client_token
# A unique token that guarantees that the call to this API is
# idempotent.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @!attribute [rw] customer_metadata_properties
# The metadata properties associated with the model package versions.
# @return [Hash<String,String>]
#
# @!attribute [rw] drift_check_baselines
# Represents the drift check baselines that can be used when the model
# monitor is set using the model package. For more information, see
# the topic on [Drift Detection against Previous Baselines in
# SageMaker Pipelines][1] in the *Amazon SageMaker Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detection
# @return [Types::DriftCheckBaselines]
#
# @!attribute [rw] domain
# The machine learning domain of your model package and its
# components. Common machine learning domains include computer vision
# and natural language processing.
# @return [String]
#
# @!attribute [rw] task
# The machine learning task your model package accomplishes. Common
# machine learning tasks include object detection and image
# classification. The following tasks are supported by Inference
# Recommender: `"IMAGE_CLASSIFICATION"` \| `"OBJECT_DETECTION"` \|
# `"TEXT_GENERATION"` \|`"IMAGE_SEGMENTATION"` \| `"FILL_MASK"` \|
# `"CLASSIFICATION"` \| `"REGRESSION"` \| `"OTHER"`.
#
# Specify "OTHER" if none of the tasks listed fit your use case.
# @return [String]
#
# @!attribute [rw] sample_payload_url
# The Amazon Simple Storage Service (Amazon S3) path where the sample
# payload is stored. This path must point to a single gzip compressed
# tar archive (.tar.gz suffix). This archive can hold multiple files
# that are all equally used in the load test. Each file in the archive
# must satisfy the size constraints of the [InvokeEndpoint][1] call.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_runtime_InvokeEndpoint.html#API_runtime_InvokeEndpoint_RequestSyntax
# @return [String]
#
# @!attribute [rw] additional_inference_specifications
# An array of additional Inference Specification objects. Each
# additional Inference Specification specifies artifacts based on this
# model package that can be used on inference endpoints. Generally
# used with SageMaker Neo to store the compiled artifacts.
# @return [Array<Types::AdditionalInferenceSpecificationDefinition>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelPackageInput AWS API Documentation
#
class CreateModelPackageInput < Struct.new(
:model_package_name,
:model_package_group_name,
:model_package_description,
:inference_specification,
:validation_specification,
:source_algorithm_specification,
:certify_for_marketplace,
:tags,
:model_approval_status,
:metadata_properties,
:model_metrics,
:client_token,
:customer_metadata_properties,
:drift_check_baselines,
:domain,
:task,
:sample_payload_url,
:additional_inference_specifications)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_arn
# The Amazon Resource Name (ARN) of the new model package.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelPackageOutput AWS API Documentation
#
class CreateModelPackageOutput < Struct.new(
:model_package_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the monitoring job definition.
# @return [String]
#
# @!attribute [rw] model_quality_baseline_config
# Specifies the constraints and baselines for the monitoring job.
# @return [Types::ModelQualityBaselineConfig]
#
# @!attribute [rw] model_quality_app_specification
# The container that runs the monitoring job.
# @return [Types::ModelQualityAppSpecification]
#
# @!attribute [rw] model_quality_job_input
# A list of the inputs that are monitored. Currently endpoints are
# supported.
# @return [Types::ModelQualityJobInput]
#
# @!attribute [rw] model_quality_job_output_config
# The output configuration for monitoring jobs.
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] job_resources
# Identifies the resources to deploy for a monitoring job.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] network_config
# Specifies the network configuration for the monitoring job.
# @return [Types::MonitoringNetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] stopping_condition
# A time limit for how long the monitoring job is allowed to run
# before stopping.
# @return [Types::MonitoringStoppingCondition]
#
# @!attribute [rw] tags
# (Optional) An array of key-value pairs. For more information, see
# [Using Cost Allocation Tags][1] in the *Amazon Web Services Billing
# and Cost Management User Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelQualityJobDefinitionRequest AWS API Documentation
#
class CreateModelQualityJobDefinitionRequest < Struct.new(
:job_definition_name,
:model_quality_baseline_config,
:model_quality_app_specification,
:model_quality_job_input,
:model_quality_job_output_config,
:job_resources,
:network_config,
:role_arn,
:stopping_condition,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_arn
# The Amazon Resource Name (ARN) of the model quality monitoring job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateModelQualityJobDefinitionResponse AWS API Documentation
#
class CreateModelQualityJobDefinitionResponse < Struct.new(
:job_definition_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# The name of the monitoring schedule. The name must be unique within
# an Amazon Web Services Region within an Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_config
# The configuration object that specifies the monitoring schedule and
# defines the monitoring job.
# @return [Types::MonitoringScheduleConfig]
#
# @!attribute [rw] tags
# (Optional) An array of key-value pairs. For more information, see
# [Using Cost Allocation Tags](
# https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL)
# in the *Amazon Web Services Billing and Cost Management User Guide*.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateMonitoringScheduleRequest AWS API Documentation
#
class CreateMonitoringScheduleRequest < Struct.new(
:monitoring_schedule_name,
:monitoring_schedule_config,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_arn
# The Amazon Resource Name (ARN) of the monitoring schedule.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateMonitoringScheduleResponse AWS API Documentation
#
class CreateMonitoringScheduleResponse < Struct.new(
:monitoring_schedule_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_name
# The name of the new notebook instance.
# @return [String]
#
# @!attribute [rw] instance_type
# The type of ML compute instance to launch for the notebook instance.
# @return [String]
#
# @!attribute [rw] subnet_id
# The ID of the subnet in a VPC to which you would like to have a
# connectivity from your ML compute instance.
# @return [String]
#
# @!attribute [rw] security_group_ids
# The VPC security group IDs, in the form sg-xxxxxxxx. The security
# groups must be for the same VPC as specified in the subnet.
# @return [Array<String>]
#
# @!attribute [rw] role_arn
# When you send any requests to Amazon Web Services resources from the
# notebook instance, SageMaker assumes this role to perform tasks on
# your behalf. You must grant this role necessary permissions so
# SageMaker can perform these tasks. The policy must allow the
# SageMaker service principal (sagemaker.amazonaws.com) permissions to
# assume this role. For more information, see [SageMaker Roles][1].
#
# <note markdown="1"> To be able to pass this role to SageMaker, the caller of this API
# must have the `iam:PassRole` permission.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Resource Name (ARN) of a Amazon Web Services Key
# Management Service key that SageMaker uses to encrypt data on the
# storage volume attached to your notebook instance. The KMS key you
# provide must be enabled. For information, see [Enabling and
# Disabling Keys][1] in the *Amazon Web Services Key Management
# Service Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/kms/latest/developerguide/enabling-keys.html
# @return [String]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] lifecycle_config_name
# The name of a lifecycle configuration to associate with the notebook
# instance. For information about lifestyle configurations, see [Step
# 2.1: (Optional) Customize a Notebook Instance][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html
# @return [String]
#
# @!attribute [rw] direct_internet_access
# Sets whether SageMaker provides internet access to the notebook
# instance. If you set this to `Disabled` this notebook instance is
# able to access resources only in your VPC, and is not be able to
# connect to SageMaker training and endpoint services unless you
# configure a NAT Gateway in your VPC.
#
# For more information, see [Notebook Instances Are Internet-Enabled
# by Default][1]. You can set the value of this parameter to
# `Disabled` only if you set a value for the `SubnetId` parameter.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access
# @return [String]
#
# @!attribute [rw] volume_size_in_gb
# The size, in GB, of the ML storage volume to attach to the notebook
# instance. The default value is 5 GB.
# @return [Integer]
#
# @!attribute [rw] accelerator_types
# A list of Elastic Inference (EI) instance types to associate with
# this notebook instance. Currently, only one instance type can be
# associated with a notebook instance. For more information, see
# [Using Elastic Inference in Amazon SageMaker][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
# @return [Array<String>]
#
# @!attribute [rw] default_code_repository
# A Git repository to associate with the notebook instance as its
# default code repository. This can be either the name of a Git
# repository stored as a resource in your account, or the URL of a Git
# repository in [Amazon Web Services CodeCommit][1] or in any other
# Git repository. When you open a notebook instance, it opens in the
# directory that contains this repository. For more information, see
# [Associating Git Repositories with SageMaker Notebook Instances][2].
#
#
#
# [1]: https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html
# @return [String]
#
# @!attribute [rw] additional_code_repositories
# An array of up to three Git repositories to associate with the
# notebook instance. These can be either the names of Git repositories
# stored as resources in your account, or the URL of Git repositories
# in [Amazon Web Services CodeCommit][1] or in any other Git
# repository. These repositories are cloned at the same level as the
# default repository of your notebook instance. For more information,
# see [Associating Git Repositories with SageMaker Notebook
# Instances][2].
#
#
#
# [1]: https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html
# @return [Array<String>]
#
# @!attribute [rw] root_access
# Whether root access is enabled or disabled for users of the notebook
# instance. The default value is `Enabled`.
#
# <note markdown="1"> Lifecycle configurations need root access to be able to set up a
# notebook instance. Because of this, lifecycle configurations
# associated with a notebook instance always run with root access even
# if you disable root access for users.
#
# </note>
# @return [String]
#
# @!attribute [rw] platform_identifier
# The platform identifier of the notebook instance runtime
# environment.
# @return [String]
#
# @!attribute [rw] instance_metadata_service_configuration
# Information on the IMDS configuration of the notebook instance
# @return [Types::InstanceMetadataServiceConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstanceInput AWS API Documentation
#
class CreateNotebookInstanceInput < Struct.new(
:notebook_instance_name,
:instance_type,
:subnet_id,
:security_group_ids,
:role_arn,
:kms_key_id,
:tags,
:lifecycle_config_name,
:direct_internet_access,
:volume_size_in_gb,
:accelerator_types,
:default_code_repository,
:additional_code_repositories,
:root_access,
:platform_identifier,
:instance_metadata_service_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_lifecycle_config_name
# The name of the lifecycle configuration.
# @return [String]
#
# @!attribute [rw] on_create
# A shell script that runs only once, when you create a notebook
# instance. The shell script must be a base64-encoded string.
# @return [Array<Types::NotebookInstanceLifecycleHook>]
#
# @!attribute [rw] on_start
# A shell script that runs every time you start a notebook instance,
# including when you create the notebook instance. The shell script
# must be a base64-encoded string.
# @return [Array<Types::NotebookInstanceLifecycleHook>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstanceLifecycleConfigInput AWS API Documentation
#
class CreateNotebookInstanceLifecycleConfigInput < Struct.new(
:notebook_instance_lifecycle_config_name,
:on_create,
:on_start)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_lifecycle_config_arn
# The Amazon Resource Name (ARN) of the lifecycle configuration.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstanceLifecycleConfigOutput AWS API Documentation
#
class CreateNotebookInstanceLifecycleConfigOutput < Struct.new(
:notebook_instance_lifecycle_config_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_arn
# The Amazon Resource Name (ARN) of the notebook instance.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateNotebookInstanceOutput AWS API Documentation
#
class CreateNotebookInstanceOutput < Struct.new(
:notebook_instance_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_name
# The name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_display_name
# The display name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_definition
# The JSON pipeline definition of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_definition_s3_location
# The location of the pipeline definition stored in Amazon S3. If
# specified, SageMaker will retrieve the pipeline definition from this
# location.
# @return [Types::PipelineDefinitionS3Location]
#
# @!attribute [rw] pipeline_description
# A description of the pipeline.
# @return [String]
#
# @!attribute [rw] client_request_token
# A unique, case-sensitive identifier that you provide to ensure the
# idempotency of the operation. An idempotent operation completes no
# more than one time.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the role used by the pipeline to
# access and create resources.
# @return [String]
#
# @!attribute [rw] tags
# A list of tags to apply to the created pipeline.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] parallelism_configuration
# This is the configuration that controls the parallelism of the
# pipeline. If specified, it applies to all runs of this pipeline by
# default.
# @return [Types::ParallelismConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePipelineRequest AWS API Documentation
#
class CreatePipelineRequest < Struct.new(
:pipeline_name,
:pipeline_display_name,
:pipeline_definition,
:pipeline_definition_s3_location,
:pipeline_description,
:client_request_token,
:role_arn,
:tags,
:parallelism_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_arn
# The Amazon Resource Name (ARN) of the created pipeline.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePipelineResponse AWS API Documentation
#
class CreatePipelineResponse < Struct.new(
:pipeline_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The name of the UserProfile to sign-in as.
# @return [String]
#
# @!attribute [rw] session_expiration_duration_in_seconds
# The session expiration duration in seconds. This value defaults to
# 43200.
# @return [Integer]
#
# @!attribute [rw] expires_in_seconds
# The number of seconds until the pre-signed URL expires. This value
# defaults to 300.
# @return [Integer]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedDomainUrlRequest AWS API Documentation
#
class CreatePresignedDomainUrlRequest < Struct.new(
:domain_id,
:user_profile_name,
:session_expiration_duration_in_seconds,
:expires_in_seconds,
:space_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] authorized_url
# The presigned URL.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedDomainUrlResponse AWS API Documentation
#
class CreatePresignedDomainUrlResponse < Struct.new(
:authorized_url)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_name
# The name of the notebook instance.
# @return [String]
#
# @!attribute [rw] session_expiration_duration_in_seconds
# The duration of the session, in seconds. The default is 12 hours.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedNotebookInstanceUrlInput AWS API Documentation
#
class CreatePresignedNotebookInstanceUrlInput < Struct.new(
:notebook_instance_name,
:session_expiration_duration_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] authorized_url
# A JSON object that contains the URL string.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreatePresignedNotebookInstanceUrlOutput AWS API Documentation
#
class CreatePresignedNotebookInstanceUrlOutput < Struct.new(
:authorized_url)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] processing_inputs
# An array of inputs configuring the data to download into the
# processing container.
# @return [Array<Types::ProcessingInput>]
#
# @!attribute [rw] processing_output_config
# Output configuration for the processing job.
# @return [Types::ProcessingOutputConfig]
#
# @!attribute [rw] processing_job_name
# The name of the processing job. The name must be unique within an
# Amazon Web Services Region in the Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] 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.
# @return [Types::ProcessingResources]
#
# @!attribute [rw] stopping_condition
# The time limit for how long the processing job is allowed to run.
# @return [Types::ProcessingStoppingCondition]
#
# @!attribute [rw] app_specification
# Configures the processing job to run a specified Docker container
# image.
# @return [Types::AppSpecification]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container. Up to 100
# key and values entries in the map are supported.
# @return [Hash<String,String>]
#
# @!attribute [rw] network_config
# Networking options for a processing job, such as whether to allow
# inbound and outbound network calls to and from processing
# containers, and the VPC subnets and security groups to use for
# VPC-enabled processing jobs.
# @return [Types::NetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] tags
# (Optional) An array of key-value pairs. For more information, see
# [Using Cost Allocation Tags][1] in the *Amazon Web Services Billing
# and Cost Management User Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL
# @return [Array<Types::Tag>]
#
# @!attribute [rw] experiment_config
# Associates a SageMaker job as a trial component with an experiment
# and trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
# @return [Types::ExperimentConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateProcessingJobRequest AWS API Documentation
#
class CreateProcessingJobRequest < Struct.new(
:processing_inputs,
:processing_output_config,
:processing_job_name,
:processing_resources,
:stopping_condition,
:app_specification,
:environment,
:network_config,
:role_arn,
:tags,
:experiment_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] processing_job_arn
# The Amazon Resource Name (ARN) of the processing job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateProcessingJobResponse AWS API Documentation
#
class CreateProcessingJobResponse < Struct.new(
:processing_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_name
# The name of the project.
# @return [String]
#
# @!attribute [rw] project_description
# A description for the project.
# @return [String]
#
# @!attribute [rw] service_catalog_provisioning_details
# The product ID and provisioning artifact ID to provision a service
# catalog. The provisioning artifact ID will default to the latest
# provisioning artifact ID of the product, if you don't provide the
# provisioning artifact ID. For more information, see [What is Amazon
# Web Services Service Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
# @return [Types::ServiceCatalogProvisioningDetails]
#
# @!attribute [rw] tags
# An array of key-value pairs that you want to use to organize and
# track your Amazon Web Services resource costs. For more information,
# see [Tagging Amazon Web Services resources][1] in the *Amazon Web
# Services General Reference Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateProjectInput AWS API Documentation
#
class CreateProjectInput < Struct.new(
:project_name,
:project_description,
:service_catalog_provisioning_details,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project.
# @return [String]
#
# @!attribute [rw] project_id
# The ID of the new project.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateProjectOutput AWS API Documentation
#
class CreateProjectOutput < Struct.new(
:project_arn,
:project_id)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The ID of the associated Domain.
# @return [String]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @!attribute [rw] tags
# Tags to associated with the space. Each tag consists of a key and an
# optional value. Tag keys must be unique for each resource. Tags are
# searchable using the `Search` API.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] space_settings
# A collection of space settings.
# @return [Types::SpaceSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateSpaceRequest AWS API Documentation
#
class CreateSpaceRequest < Struct.new(
:domain_id,
:space_name,
:tags,
:space_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] space_arn
# The space's Amazon Resource Name (ARN).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateSpaceResponse AWS API Documentation
#
class CreateSpaceResponse < Struct.new(
:space_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] studio_lifecycle_config_name
# The name of the Studio Lifecycle Configuration to create.
# @return [String]
#
# @!attribute [rw] studio_lifecycle_config_content
# The content of your Studio Lifecycle Configuration script. This
# content must be base64 encoded.
# @return [String]
#
# @!attribute [rw] studio_lifecycle_config_app_type
# The App type that the Lifecycle Configuration is attached to.
# @return [String]
#
# @!attribute [rw] tags
# Tags to be associated with the Lifecycle Configuration. Each tag
# consists of a key and an optional value. Tag keys must be unique per
# resource. Tags are searchable using the Search API.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateStudioLifecycleConfigRequest AWS API Documentation
#
class CreateStudioLifecycleConfigRequest < Struct.new(
:studio_lifecycle_config_name,
:studio_lifecycle_config_content,
:studio_lifecycle_config_app_type,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] studio_lifecycle_config_arn
# The ARN of your created Lifecycle Configuration.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateStudioLifecycleConfigResponse AWS API Documentation
#
class CreateStudioLifecycleConfigResponse < Struct.new(
:studio_lifecycle_config_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_name
# The name of the training job. The name must be unique within an
# Amazon Web Services Region in an Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] hyper_parameters
# Algorithm-specific parameters that influence the quality of the
# model. You set hyperparameters before you start the learning
# process. For a list of hyperparameters for each training algorithm
# provided by SageMaker, see [Algorithms][1].
#
# You can specify a maximum of 100 hyperparameters. Each
# hyperparameter is a key-value pair. Each key and value is limited to
# 256 characters, as specified by the `Length Constraint`.
#
# Do not include any security-sensitive information including account
# access IDs, secrets or tokens in any hyperparameter field. If the
# use of security-sensitive credentials are detected, SageMaker will
# reject your training job request and return an exception error.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
# @return [Hash<String,String>]
#
# @!attribute [rw] algorithm_specification
# The registry path of the Docker image that contains the training
# algorithm and algorithm-specific metadata, including the input mode.
# For more information about algorithms provided by SageMaker, see
# [Algorithms][1]. For information about providing your own
# algorithms, see [Using Your Own Algorithms with Amazon
# SageMaker][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html
# @return [Types::AlgorithmSpecification]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that SageMaker can
# assume to perform tasks on your behalf.
#
# During model training, SageMaker needs your permission to read input
# data from an S3 bucket, download a Docker image that contains
# training code, write model artifacts to an S3 bucket, write logs to
# Amazon CloudWatch Logs, and publish metrics to Amazon CloudWatch.
# You grant permissions for all of these tasks to an IAM role. For
# more information, see [SageMaker Roles][1].
#
# <note markdown="1"> To be able to pass this role to SageMaker, the caller of this API
# must have the `iam:PassRole` permission.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html
# @return [String]
#
# @!attribute [rw] input_data_config
# An array of `Channel` objects. Each channel is a named input source.
# `InputDataConfig` describes the input data and its location.
#
# Algorithms can accept input data from one or more channels. For
# example, an algorithm might have two channels of input data,
# `training_data` and `validation_data`. The configuration for each
# channel provides the S3, EFS, or FSx location where the input data
# is stored. It also provides information about the stored data: the
# MIME type, compression method, and whether the data is wrapped in
# RecordIO format.
#
# Depending on the input mode that the algorithm supports, SageMaker
# either copies input data files from an S3 bucket to a local
# directory in the Docker container, or makes it available as input
# streams. For example, if you specify an EFS location, input data
# files are available as input streams. They do not need to be
# downloaded.
# @return [Array<Types::Channel>]
#
# @!attribute [rw] output_data_config
# Specifies the path to the S3 location where you want to store model
# artifacts. SageMaker creates subfolders for the artifacts.
# @return [Types::OutputDataConfig]
#
# @!attribute [rw] resource_config
# The resources, including the ML compute instances and ML storage
# volumes, to use for model training.
#
# ML storage volumes store model artifacts and incremental states.
# Training algorithms might also use ML storage volumes for scratch
# space. If you want SageMaker to use the ML storage volume to store
# the training data, choose `File` as the `TrainingInputMode` in the
# algorithm specification. For distributed training algorithms,
# specify an instance count greater than 1.
# @return [Types::ResourceConfig]
#
# @!attribute [rw] vpc_config
# A [VpcConfig][1] object that specifies the VPC that you want your
# training job to connect to. Control access to and from your training
# container by configuring the VPC. For more information, see [Protect
# Training Jobs by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
# @return [Types::VpcConfig]
#
# @!attribute [rw] stopping_condition
# Specifies a limit to how long a model training job can run. It also
# specifies how long a managed Spot training job has to complete. When
# the job reaches the time limit, SageMaker ends the training job. Use
# this API to cap model training costs.
#
# To stop a job, SageMaker sends the algorithm the `SIGTERM` signal,
# which delays job termination for 120 seconds. Algorithms can use
# this 120-second window to save the model artifacts, so the results
# of training are not lost.
# @return [Types::StoppingCondition]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] enable_network_isolation
# Isolates the training container. No inbound or outbound network
# calls can be made, except for calls between peers within a training
# cluster for distributed training. If you enable network isolation
# for training jobs that are configured to use a VPC, SageMaker
# downloads and uploads customer data and model artifacts through the
# specified VPC, but the training container does not have network
# access.
# @return [Boolean]
#
# @!attribute [rw] enable_inter_container_traffic_encryption
# To encrypt all communications between ML compute instances in
# distributed training, choose `True`. Encryption provides greater
# security for distributed training, but training might take longer.
# How long it takes depends on the amount of communication between
# compute instances, especially if you use a deep learning algorithm
# in distributed training. For more information, see [Protect
# Communications Between ML Compute Instances in a Distributed
# Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-encrypt.html
# @return [Boolean]
#
# @!attribute [rw] enable_managed_spot_training
# To train models using managed spot training, choose `True`. Managed
# spot training provides a fully managed and scalable infrastructure
# for training machine learning models. this option is useful when
# training jobs can be interrupted and when there is flexibility when
# the training job is run.
#
# The complete and intermediate results of jobs are stored in an
# Amazon S3 bucket, and can be used as a starting point to train
# models incrementally. Amazon SageMaker provides metrics and logs in
# CloudWatch. They can be used to see when managed spot training jobs
# are running, interrupted, resumed, or completed.
# @return [Boolean]
#
# @!attribute [rw] checkpoint_config
# Contains information about the output location for managed spot
# training checkpoint data.
# @return [Types::CheckpointConfig]
#
# @!attribute [rw] debug_hook_config
# Configuration information for the Amazon SageMaker Debugger hook
# parameters, metric and tensor collections, and storage paths. To
# learn more about how to configure the `DebugHookConfig` parameter,
# see [Use the SageMaker and Debugger Configuration API Operations to
# Create, Update, and Debug Your Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html
# @return [Types::DebugHookConfig]
#
# @!attribute [rw] debug_rule_configurations
# Configuration information for Amazon SageMaker Debugger rules for
# debugging output tensors.
# @return [Array<Types::DebugRuleConfiguration>]
#
# @!attribute [rw] tensor_board_output_config
# Configuration of storage locations for the Amazon SageMaker Debugger
# TensorBoard output data.
# @return [Types::TensorBoardOutputConfig]
#
# @!attribute [rw] experiment_config
# Associates a SageMaker job as a trial component with an experiment
# and trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
# @return [Types::ExperimentConfig]
#
# @!attribute [rw] profiler_config
# Configuration information for Amazon SageMaker Debugger system
# monitoring, framework profiling, and storage paths.
# @return [Types::ProfilerConfig]
#
# @!attribute [rw] profiler_rule_configurations
# Configuration information for Amazon SageMaker Debugger rules for
# profiling system and framework metrics.
# @return [Array<Types::ProfilerRuleConfiguration>]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container.
# @return [Hash<String,String>]
#
# @!attribute [rw] retry_strategy
# The number of times to retry the job when the job fails due to an
# `InternalServerError`.
# @return [Types::RetryStrategy]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrainingJobRequest AWS API Documentation
#
class CreateTrainingJobRequest < Struct.new(
:training_job_name,
:hyper_parameters,
:algorithm_specification,
:role_arn,
:input_data_config,
:output_data_config,
:resource_config,
:vpc_config,
:stopping_condition,
:tags,
:enable_network_isolation,
:enable_inter_container_traffic_encryption,
:enable_managed_spot_training,
:checkpoint_config,
:debug_hook_config,
:debug_rule_configurations,
:tensor_board_output_config,
:experiment_config,
:profiler_config,
:profiler_rule_configurations,
:environment,
:retry_strategy)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_arn
# The Amazon Resource Name (ARN) of the training job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrainingJobResponse AWS API Documentation
#
class CreateTrainingJobResponse < Struct.new(
:training_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] transform_job_name
# The name of the transform job. The name must be unique within an
# Amazon Web Services Region in an Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] model_name
# The name of the model that you want to use for the transform job.
# `ModelName` must be the name of an existing Amazon SageMaker model
# within an Amazon Web Services Region in an Amazon Web Services
# account.
# @return [String]
#
# @!attribute [rw] max_concurrent_transforms
# The maximum number of parallel requests that can be sent to each
# instance in a transform job. If `MaxConcurrentTransforms` is set to
# `0` or left unset, Amazon SageMaker checks the optional
# execution-parameters to determine the settings for your chosen
# algorithm. If the execution-parameters endpoint is not enabled, the
# default value is `1`. For more information on execution-parameters,
# see [How Containers Serve Requests][1]. For built-in algorithms, you
# don't need to set a value for `MaxConcurrentTransforms`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requests
# @return [Integer]
#
# @!attribute [rw] model_client_config
# Configures the timeout and maximum number of retries for processing
# a transform job invocation.
# @return [Types::ModelClientConfig]
#
# @!attribute [rw] max_payload_in_mb
# The maximum allowed size of the payload, in MB. A *payload* is the
# data portion of a record (without metadata). The value in
# `MaxPayloadInMB` must be greater than, or equal to, the size of a
# single record. To estimate the size of a record in MB, divide the
# size of your dataset by the number of records. To ensure that the
# records fit within the maximum payload size, we recommend using a
# slightly larger value. The default value is `6` MB.
#
# The value of `MaxPayloadInMB` cannot be greater than 100 MB. If you
# specify the `MaxConcurrentTransforms` parameter, the value of
# `(MaxConcurrentTransforms * MaxPayloadInMB)` also cannot exceed 100
# MB.
#
# For cases where the payload might be arbitrarily large and is
# transmitted using HTTP chunked encoding, set the value to `0`. This
# feature works only in supported algorithms. Currently, Amazon
# SageMaker built-in algorithms do not support HTTP chunked encoding.
# @return [Integer]
#
# @!attribute [rw] batch_strategy
# Specifies the number of records to include in a mini-batch for an
# HTTP inference request. A *record* ** is a single unit of input data
# that inference can be made on. For example, a single line in a CSV
# file is a record.
#
# To enable the batch strategy, you must set the `SplitType` property
# to `Line`, `RecordIO`, or `TFRecord`.
#
# To use only one record when making an HTTP invocation request to a
# container, set `BatchStrategy` to `SingleRecord` and `SplitType` to
# `Line`.
#
# To fit as many records in a mini-batch as can fit within the
# `MaxPayloadInMB` limit, set `BatchStrategy` to `MultiRecord` and
# `SplitType` to `Line`.
# @return [String]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container. We support
# up to 16 key and values entries in the map.
# @return [Hash<String,String>]
#
# @!attribute [rw] transform_input
# Describes the input source and the way the transform job consumes
# it.
# @return [Types::TransformInput]
#
# @!attribute [rw] transform_output
# Describes the results of the transform job.
# @return [Types::TransformOutput]
#
# @!attribute [rw] data_capture_config
# Configuration to control how SageMaker captures inference data.
# @return [Types::BatchDataCaptureConfig]
#
# @!attribute [rw] transform_resources
# Describes the resources, including ML instance types and ML instance
# count, to use for the transform job.
# @return [Types::TransformResources]
#
# @!attribute [rw] 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][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html
# @return [Types::DataProcessing]
#
# @!attribute [rw] tags
# (Optional) An array of key-value pairs. For more information, see
# [Using Cost Allocation Tags][1] in the *Amazon Web Services Billing
# and Cost Management User Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what
# @return [Array<Types::Tag>]
#
# @!attribute [rw] experiment_config
# Associates a SageMaker job as a trial component with an experiment
# and trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
# @return [Types::ExperimentConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTransformJobRequest AWS API Documentation
#
class CreateTransformJobRequest < Struct.new(
:transform_job_name,
:model_name,
:max_concurrent_transforms,
:model_client_config,
:max_payload_in_mb,
:batch_strategy,
:environment,
:transform_input,
:transform_output,
:data_capture_config,
:transform_resources,
:data_processing,
:tags,
:experiment_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] transform_job_arn
# The Amazon Resource Name (ARN) of the transform job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTransformJobResponse AWS API Documentation
#
class CreateTransformJobResponse < Struct.new(
:transform_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_name
# The name of the component. The name must be unique in your Amazon
# Web Services account and is not case-sensitive.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the component as displayed. The name doesn't need to be
# unique. If `DisplayName` isn't specified, `TrialComponentName` is
# displayed.
# @return [String]
#
# @!attribute [rw] status
# The status of the component. States include:
#
# * InProgress
#
# * Completed
#
# * Failed
# @return [Types::TrialComponentStatus]
#
# @!attribute [rw] start_time
# When the component started.
# @return [Time]
#
# @!attribute [rw] end_time
# When the component ended.
# @return [Time]
#
# @!attribute [rw] parameters
# The hyperparameters for the component.
# @return [Hash<String,Types::TrialComponentParameterValue>]
#
# @!attribute [rw] input_artifacts
# The input artifacts for the component. Examples of input artifacts
# are datasets, algorithms, hyperparameters, source code, and instance
# types.
# @return [Hash<String,Types::TrialComponentArtifact>]
#
# @!attribute [rw] output_artifacts
# The output artifacts for the component. Examples of output artifacts
# are metrics, snapshots, logs, and images.
# @return [Hash<String,Types::TrialComponentArtifact>]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] tags
# A list of tags to associate with the component. You can use
# [Search][1] API to search on the tags.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrialComponentRequest AWS API Documentation
#
class CreateTrialComponentRequest < Struct.new(
:trial_component_name,
:display_name,
:status,
:start_time,
:end_time,
:parameters,
:input_artifacts,
:output_artifacts,
:metadata_properties,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the trial component.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrialComponentResponse AWS API Documentation
#
class CreateTrialComponentResponse < Struct.new(
:trial_component_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_name
# The name of the trial. The name must be unique in your Amazon Web
# Services account and is not case-sensitive.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the trial as displayed. The name doesn't need to be
# unique. If `DisplayName` isn't specified, `TrialName` is displayed.
# @return [String]
#
# @!attribute [rw] experiment_name
# The name of the experiment to associate the trial with.
# @return [String]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] tags
# A list of tags to associate with the trial. You can use [Search][1]
# API to search on the tags.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrialRequest AWS API Documentation
#
class CreateTrialRequest < Struct.new(
:trial_name,
:display_name,
:experiment_name,
:metadata_properties,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_arn
# The Amazon Resource Name (ARN) of the trial.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrialResponse AWS API Documentation
#
class CreateTrialResponse < Struct.new(
:trial_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The ID of the associated Domain.
# @return [String]
#
# @!attribute [rw] user_profile_name
# A name for the UserProfile. This value is not case sensitive.
# @return [String]
#
# @!attribute [rw] single_sign_on_user_identifier
# A specifier for the type of value specified in
# SingleSignOnUserValue. Currently, the only supported value is
# "UserName". If the Domain's AuthMode is IAM Identity Center, this
# field is required. If the Domain's AuthMode is not IAM Identity
# Center, this field cannot be specified.
# @return [String]
#
# @!attribute [rw] single_sign_on_user_value
# The username of the associated Amazon Web Services Single Sign-On
# User for this UserProfile. If the Domain's AuthMode is IAM Identity
# Center, this field is required, and must match a valid username of a
# user in your directory. If the Domain's AuthMode is not IAM
# Identity Center, this field cannot be specified.
# @return [String]
#
# @!attribute [rw] tags
# Each tag consists of a key and an optional value. Tag keys must be
# unique per resource.
#
# Tags that you specify for the User Profile are also added to all
# Apps that the User Profile launches.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] user_settings
# A collection of settings.
# @return [Types::UserSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateUserProfileRequest AWS API Documentation
#
class CreateUserProfileRequest < Struct.new(
:domain_id,
:user_profile_name,
:single_sign_on_user_identifier,
:single_sign_on_user_value,
:tags,
:user_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] user_profile_arn
# The user profile Amazon Resource Name (ARN).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateUserProfileResponse AWS API Documentation
#
class CreateUserProfileResponse < Struct.new(
:user_profile_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] cognito_config
# Use this parameter to configure an Amazon Cognito private workforce.
# A single Cognito workforce is created using and corresponds to a
# single [ Amazon Cognito user pool][1].
#
# Do not use `OidcConfig` if you specify values for `CognitoConfig`.
#
#
#
# [1]: https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html
# @return [Types::CognitoConfig]
#
# @!attribute [rw] oidc_config
# Use this parameter to configure a private workforce using your own
# OIDC Identity Provider.
#
# Do not use `CognitoConfig` if you specify values for `OidcConfig`.
# @return [Types::OidcConfig]
#
# @!attribute [rw] source_ip_config
# A list of IP address ranges ([CIDRs][1]). 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.
#
#
#
# [1]: https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html
# @return [Types::SourceIpConfig]
#
# @!attribute [rw] workforce_name
# The name of the private workforce.
# @return [String]
#
# @!attribute [rw] tags
# An array of key-value pairs that contain metadata to help you
# categorize and organize our workforce. Each tag consists of a key
# and a value, both of which you define.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] workforce_vpc_config
# Use this parameter to configure a workforce using VPC.
# @return [Types::WorkforceVpcConfigRequest]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkforceRequest AWS API Documentation
#
class CreateWorkforceRequest < Struct.new(
:cognito_config,
:oidc_config,
:source_ip_config,
:workforce_name,
:tags,
:workforce_vpc_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workforce_arn
# The Amazon Resource Name (ARN) of the workforce.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkforceResponse AWS API Documentation
#
class CreateWorkforceResponse < Struct.new(
:workforce_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteam_name
# The name of the work team. Use this name to identify the work team.
# @return [String]
#
# @!attribute [rw] workforce_name
# The name of the workforce.
# @return [String]
#
# @!attribute [rw] member_definitions
# A list of `MemberDefinition` objects that contains objects that
# identify the workers that make up the work team.
#
# Workforces can be created using Amazon Cognito or your own OIDC
# Identity Provider (IdP). For private workforces created using Amazon
# Cognito use `CognitoMemberDefinition`. For workforces created using
# your own OIDC identity provider (IdP) use `OidcMemberDefinition`. Do
# not provide input for both of these parameters in a single request.
#
# For workforces created using Amazon Cognito, private work teams
# correspond to Amazon Cognito *user groups* within the user pool used
# to create a workforce. All of the `CognitoMemberDefinition` objects
# that make up the member definition must have the same `ClientId` and
# `UserPool` values. To add a Amazon Cognito user group to an existing
# worker pool, see [Adding groups to a User Pool](). For more
# information about user pools, see [Amazon Cognito User Pools][1].
#
# For workforces created using your own OIDC IdP, specify the user
# groups that you want to include in your private work team in
# `OidcMemberDefinition` by listing those groups in `Groups`.
#
#
#
# [1]: https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html
# @return [Array<Types::MemberDefinition>]
#
# @!attribute [rw] description
# A description of the work team.
# @return [String]
#
# @!attribute [rw] notification_configuration
# Configures notification of workers regarding available or expiring
# work items.
# @return [Types::NotificationConfiguration]
#
# @!attribute [rw] tags
# An array of key-value pairs.
#
# For more information, see [Resource Tag][1] and [Using Cost
# Allocation Tags][2] in the <i> Amazon Web Services Billing and Cost
# Management User Guide</i>.
#
#
#
# [1]: https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-resource-tags.html
# [2]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkteamRequest AWS API Documentation
#
class CreateWorkteamRequest < Struct.new(
:workteam_name,
:workforce_name,
:member_definitions,
:description,
:notification_configuration,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteam_arn
# The Amazon Resource Name (ARN) of the work team. You can use this
# ARN to identify the work team.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateWorkteamResponse AWS API Documentation
#
class CreateWorkteamResponse < Struct.new(
:workteam_arn)
SENSITIVE = []
include Aws::Structure
end
# A custom SageMaker image. For more information, see [Bring your own
# SageMaker image][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/studio-byoi.html
#
# @!attribute [rw] image_name
# The name of the CustomImage. Must be unique to your account.
# @return [String]
#
# @!attribute [rw] image_version_number
# The version number of the CustomImage.
# @return [Integer]
#
# @!attribute [rw] app_image_config_name
# The name of the AppImageConfig.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CustomImage AWS API Documentation
#
class CustomImage < Struct.new(
:image_name,
:image_version_number,
:app_image_config_name)
SENSITIVE = []
include Aws::Structure
end
# Configuration to control how SageMaker captures inference data.
#
# @!attribute [rw] enable_capture
# Whether data capture should be enabled or disabled (defaults to
# enabled).
# @return [Boolean]
#
# @!attribute [rw] initial_sampling_percentage
# The percentage of requests SageMaker will capture. A lower value is
# recommended for Endpoints with high traffic.
# @return [Integer]
#
# @!attribute [rw] destination_s3_uri
# The Amazon S3 location used to capture the data.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Resource Name (ARN) of a Amazon Web Services Key
# Management Service key that SageMaker uses to encrypt the captured
# data at rest using Amazon S3 server-side encryption.
#
# The KmsKeyId can be any of the following formats:
#
# * Key ID: `1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Key ARN:
# `arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Alias name: `alias/ExampleAlias`
#
# * Alias name ARN:
# `arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias`
# @return [String]
#
# @!attribute [rw] capture_options
# Specifies data Model Monitor will capture. You can configure whether
# to collect only input, only output, or both
# @return [Array<Types::CaptureOption>]
#
# @!attribute [rw] capture_content_type_header
# Configuration specifying how to treat different headers. If no
# headers are specified SageMaker will by default base64 encode when
# capturing the data.
# @return [Types::CaptureContentTypeHeader]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataCaptureConfig AWS API Documentation
#
class DataCaptureConfig < Struct.new(
:enable_capture,
:initial_sampling_percentage,
:destination_s3_uri,
:kms_key_id,
:capture_options,
:capture_content_type_header)
SENSITIVE = []
include Aws::Structure
end
# The currently active data capture configuration used by your Endpoint.
#
# @!attribute [rw] enable_capture
# Whether data capture is enabled or disabled.
# @return [Boolean]
#
# @!attribute [rw] capture_status
# Whether data capture is currently functional.
# @return [String]
#
# @!attribute [rw] current_sampling_percentage
# The percentage of requests being captured by your Endpoint.
# @return [Integer]
#
# @!attribute [rw] destination_s3_uri
# The Amazon S3 location being used to capture the data.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The KMS key being used to encrypt the data in Amazon S3.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataCaptureConfigSummary AWS API Documentation
#
class DataCaptureConfigSummary < Struct.new(
:enable_capture,
:capture_status,
:current_sampling_percentage,
:destination_s3_uri,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# The meta data of the Glue table which serves as data catalog for the
# `OfflineStore`.
#
# @!attribute [rw] table_name
# The name of the Glue table.
# @return [String]
#
# @!attribute [rw] catalog
# The name of the Glue table catalog.
# @return [String]
#
# @!attribute [rw] database
# The name of the Glue table database.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataCatalogConfig AWS API Documentation
#
class DataCatalogConfig < Struct.new(
:table_name,
:catalog,
:database)
SENSITIVE = []
include Aws::Structure
end
# 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][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html
#
# @!attribute [rw] input_filter
# A [JSONPath][1] expression used to select a portion of the input
# data to pass to the algorithm. Use the `InputFilter` parameter to
# exclude fields, such as an ID column, from the input. If you want
# SageMaker to pass the entire input dataset to the algorithm, accept
# the default value `$`.
#
# Examples: `"$"`, `"$[1:]"`, `"$.features"`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators
# @return [String]
#
# @!attribute [rw] output_filter
# A [JSONPath][1] expression used to select a portion of the joined
# dataset to save in the output file for a batch transform job. If you
# want SageMaker to store the entire input dataset in the output file,
# leave the default value, `$`. If you specify indexes that aren't
# within the dimension size of the joined dataset, you get an error.
#
# Examples: `"$"`, `"$[0,5:]"`, `"$['id','SageMakerOutput']"`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators
# @return [String]
#
# @!attribute [rw] join_source
# Specifies the source of the data to join with the transformed data.
# The valid values are `None` and `Input`. The default value is
# `None`, which specifies not to join the input with the transformed
# data. If you want the batch transform job to join the original input
# data with the transformed data, set `JoinSource` to `Input`. You can
# specify `OutputFilter` as an additional filter to select a portion
# of the joined dataset and store it in the output file.
#
# For JSON or JSONLines objects, such as a JSON array, SageMaker adds
# the transformed data to the input JSON object in an attribute called
# `SageMakerOutput`. The joined result for JSON must be a key-value
# pair object. If the input is not a key-value pair object, SageMaker
# creates a new JSON file. In the new JSON file, and the input data is
# stored under the `SageMakerInput` key and the results are stored in
# `SageMakerOutput`.
#
# For CSV data, SageMaker takes each row as a JSON array and joins the
# transformed data with the input by appending each transformed row to
# the end of the input. The joined data has the original input data
# followed by the transformed data and the output is a CSV file.
#
# For information on how joining in applied, see [Workflow for
# Associating Inferences with Input Records][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#batch-transform-data-processing-workflow
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataProcessing AWS API Documentation
#
class DataProcessing < Struct.new(
:input_filter,
:output_filter,
:join_source)
SENSITIVE = []
include Aws::Structure
end
# Information about the container that a data quality monitoring job
# runs.
#
# @!attribute [rw] image_uri
# The container image that the data quality monitoring job runs.
# @return [String]
#
# @!attribute [rw] container_entrypoint
# The entrypoint for a container used to run a monitoring job.
# @return [Array<String>]
#
# @!attribute [rw] container_arguments
# The arguments to send to the container that the monitoring job runs.
# @return [Array<String>]
#
# @!attribute [rw] record_preprocessor_source_uri
# An Amazon S3 URI to a script that is called per row prior to running
# analysis. It can base64 decode the payload and convert it into a
# flatted json so that the built-in container can use the converted
# data. Applicable only for the built-in (first party) containers.
# @return [String]
#
# @!attribute [rw] post_analytics_processor_source_uri
# An Amazon S3 URI to a script that is called after analysis has been
# performed. Applicable only for the built-in (first party)
# containers.
# @return [String]
#
# @!attribute [rw] environment
# Sets the environment variables in the container that the monitoring
# job runs.
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataQualityAppSpecification AWS API Documentation
#
class DataQualityAppSpecification < Struct.new(
:image_uri,
:container_entrypoint,
:container_arguments,
:record_preprocessor_source_uri,
:post_analytics_processor_source_uri,
:environment)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] baselining_job_name
# The name of the job that performs baselining for the data quality
# monitoring job.
# @return [String]
#
# @!attribute [rw] constraints_resource
# The constraints resource for a monitoring job.
# @return [Types::MonitoringConstraintsResource]
#
# @!attribute [rw] statistics_resource
# The statistics resource for a monitoring job.
# @return [Types::MonitoringStatisticsResource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataQualityBaselineConfig AWS API Documentation
#
class DataQualityBaselineConfig < Struct.new(
:baselining_job_name,
:constraints_resource,
:statistics_resource)
SENSITIVE = []
include Aws::Structure
end
# The input for the data quality monitoring job. Currently endpoints are
# supported for input.
#
# @!attribute [rw] endpoint_input
# Input object for the endpoint
# @return [Types::EndpointInput]
#
# @!attribute [rw] batch_transform_input
# Input object for the batch transform job.
# @return [Types::BatchTransformInput]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataQualityJobInput AWS API Documentation
#
class DataQualityJobInput < Struct.new(
:endpoint_input,
:batch_transform_input)
SENSITIVE = []
include Aws::Structure
end
# Describes the location of the channel data.
#
# @!attribute [rw] s3_data_source
# The S3 location of the data source that is associated with a
# channel.
# @return [Types::S3DataSource]
#
# @!attribute [rw] file_system_data_source
# The file system that is associated with a channel.
# @return [Types::FileSystemDataSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataSource AWS API Documentation
#
class DataSource < Struct.new(
:s3_data_source,
:file_system_data_source)
SENSITIVE = []
include Aws::Structure
end
# Configuration for Dataset Definition inputs. The Dataset Definition
# input must specify exactly one of either `AthenaDatasetDefinition` or
# `RedshiftDatasetDefinition` types.
#
# @!attribute [rw] athena_dataset_definition
# Configuration for Athena Dataset Definition input.
# @return [Types::AthenaDatasetDefinition]
#
# @!attribute [rw] redshift_dataset_definition
# Configuration for Redshift Dataset Definition input.
# @return [Types::RedshiftDatasetDefinition]
#
# @!attribute [rw] local_path
# The local path where you want Amazon SageMaker to download the
# Dataset Definition inputs to run a processing job. `LocalPath` is an
# absolute path to the input data. This is a required parameter when
# `AppManaged` is `False` (default).
# @return [String]
#
# @!attribute [rw] data_distribution_type
# Whether the generated dataset is `FullyReplicated` or
# `ShardedByS3Key` (default).
# @return [String]
#
# @!attribute [rw] input_mode
# Whether to use `File` or `Pipe` input mode. In `File` (default)
# mode, Amazon SageMaker copies the data from the input source onto
# the local Amazon Elastic Block Store (Amazon EBS) volumes before
# starting your training algorithm. This is the most commonly used
# input mode. In `Pipe` mode, Amazon SageMaker streams input data from
# the source directly to your algorithm without using the EBS volume.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DatasetDefinition AWS API Documentation
#
class DatasetDefinition < Struct.new(
:athena_dataset_definition,
:redshift_dataset_definition,
:local_path,
:data_distribution_type,
:input_mode)
SENSITIVE = []
include Aws::Structure
end
# Configuration information for the Amazon SageMaker Debugger hook
# parameters, metric and tensor collections, and storage paths. To learn
# more about how to configure the `DebugHookConfig` parameter, see [Use
# the SageMaker and Debugger Configuration API Operations to Create,
# Update, and Debug Your Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html
#
# @!attribute [rw] local_path
# Path to local storage location for metrics and tensors. Defaults to
# `/opt/ml/output/tensors/`.
# @return [String]
#
# @!attribute [rw] s3_output_path
# Path to Amazon S3 storage location for metrics and tensors.
# @return [String]
#
# @!attribute [rw] hook_parameters
# Configuration information for the Amazon SageMaker Debugger hook
# parameters.
# @return [Hash<String,String>]
#
# @!attribute [rw] collection_configurations
# Configuration information for Amazon SageMaker Debugger tensor
# collections. To learn more about how to configure the
# `CollectionConfiguration` parameter, see [Use the SageMaker and
# Debugger Configuration API Operations to Create, Update, and Debug
# Your Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html
# @return [Array<Types::CollectionConfiguration>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DebugHookConfig AWS API Documentation
#
class DebugHookConfig < Struct.new(
:local_path,
:s3_output_path,
:hook_parameters,
:collection_configurations)
SENSITIVE = []
include Aws::Structure
end
# Configuration information for SageMaker Debugger rules for debugging.
# To learn more about how to configure the `DebugRuleConfiguration`
# parameter, see [Use the SageMaker and Debugger Configuration API
# Operations to Create, Update, and Debug Your Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html
#
# @!attribute [rw] rule_configuration_name
# The name of the rule configuration. It must be unique relative to
# other rule configuration names.
# @return [String]
#
# @!attribute [rw] local_path
# Path to local storage location for output of rules. Defaults to
# `/opt/ml/processing/output/rule/`.
# @return [String]
#
# @!attribute [rw] s3_output_path
# Path to Amazon S3 storage location for rules.
# @return [String]
#
# @!attribute [rw] rule_evaluator_image
# The Amazon Elastic Container (ECR) Image for the managed rule
# evaluation.
# @return [String]
#
# @!attribute [rw] instance_type
# The instance type to deploy a custom rule for debugging a training
# job.
# @return [String]
#
# @!attribute [rw] volume_size_in_gb
# The size, in GB, of the ML storage volume attached to the processing
# instance.
# @return [Integer]
#
# @!attribute [rw] rule_parameters
# Runtime configuration for rule container.
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DebugRuleConfiguration AWS API Documentation
#
class DebugRuleConfiguration < Struct.new(
:rule_configuration_name,
:local_path,
:s3_output_path,
:rule_evaluator_image,
:instance_type,
:volume_size_in_gb,
:rule_parameters)
SENSITIVE = []
include Aws::Structure
end
# Information about the status of the rule evaluation.
#
# @!attribute [rw] rule_configuration_name
# The name of the rule configuration.
# @return [String]
#
# @!attribute [rw] rule_evaluation_job_arn
# The Amazon Resource Name (ARN) of the rule evaluation job.
# @return [String]
#
# @!attribute [rw] rule_evaluation_status
# Status of the rule evaluation.
# @return [String]
#
# @!attribute [rw] status_details
# Details from the rule evaluation.
# @return [String]
#
# @!attribute [rw] last_modified_time
# Timestamp when the rule evaluation status was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DebugRuleEvaluationStatus AWS API Documentation
#
class DebugRuleEvaluationStatus < Struct.new(
:rule_configuration_name,
:rule_evaluation_job_arn,
:rule_evaluation_status,
:status_details,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings that apply to spaces created in the Domain.
#
# @!attribute [rw] execution_role
# The ARN of the execution role for the space.
# @return [String]
#
# @!attribute [rw] security_groups
# The security group IDs for the Amazon Virtual Private Cloud that the
# space uses for communication.
# @return [Array<String>]
#
# @!attribute [rw] jupyter_server_app_settings
# The JupyterServer app settings.
# @return [Types::JupyterServerAppSettings]
#
# @!attribute [rw] kernel_gateway_app_settings
# The KernelGateway app settings.
# @return [Types::KernelGatewayAppSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DefaultSpaceSettings AWS API Documentation
#
class DefaultSpaceSettings < Struct.new(
:execution_role,
:security_groups,
:jupyter_server_app_settings,
:kernel_gateway_app_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_name
# The name of the action to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteActionRequest AWS API Documentation
#
class DeleteActionRequest < Struct.new(
:action_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_arn
# The Amazon Resource Name (ARN) of the action.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteActionResponse AWS API Documentation
#
class DeleteActionResponse < Struct.new(
:action_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] algorithm_name
# The name of the algorithm to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAlgorithmInput AWS API Documentation
#
class DeleteAlgorithmInput < Struct.new(
:algorithm_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_image_config_name
# The name of the AppImageConfig to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAppImageConfigRequest AWS API Documentation
#
class DeleteAppImageConfigRequest < Struct.new(
:app_image_config_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name. If this value is not set, then `SpaceName`
# must be set.
# @return [String]
#
# @!attribute [rw] app_type
# The type of app.
# @return [String]
#
# @!attribute [rw] app_name
# The name of the app.
# @return [String]
#
# @!attribute [rw] space_name
# The name of the space. If this value is not set, then
# `UserProfileName` must be set.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAppRequest AWS API Documentation
#
class DeleteAppRequest < Struct.new(
:domain_id,
:user_profile_name,
:app_type,
:app_name,
:space_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_arn
# The Amazon Resource Name (ARN) of the artifact to delete.
# @return [String]
#
# @!attribute [rw] source
# The URI of the source.
# @return [Types::ArtifactSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteArtifactRequest AWS API Documentation
#
class DeleteArtifactRequest < Struct.new(
:artifact_arn,
:source)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_arn
# The Amazon Resource Name (ARN) of the artifact.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteArtifactResponse AWS API Documentation
#
class DeleteArtifactResponse < Struct.new(
:artifact_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_arn
# The ARN of the source.
# @return [String]
#
# @!attribute [rw] destination_arn
# The Amazon Resource Name (ARN) of the destination.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAssociationRequest AWS API Documentation
#
class DeleteAssociationRequest < Struct.new(
:source_arn,
:destination_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_arn
# The ARN of the source.
# @return [String]
#
# @!attribute [rw] destination_arn
# The Amazon Resource Name (ARN) of the destination.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAssociationResponse AWS API Documentation
#
class DeleteAssociationResponse < Struct.new(
:source_arn,
:destination_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] code_repository_name
# The name of the Git repository to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteCodeRepositoryInput AWS API Documentation
#
class DeleteCodeRepositoryInput < Struct.new(
:code_repository_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_name
# The name of the context to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteContextRequest AWS API Documentation
#
class DeleteContextRequest < Struct.new(
:context_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_arn
# The Amazon Resource Name (ARN) of the context.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteContextResponse AWS API Documentation
#
class DeleteContextResponse < Struct.new(
:context_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the data quality monitoring job definition to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteDataQualityJobDefinitionRequest AWS API Documentation
#
class DeleteDataQualityJobDefinitionRequest < Struct.new(
:job_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteDeviceFleetRequest AWS API Documentation
#
class DeleteDeviceFleetRequest < Struct.new(
:device_fleet_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] retention_policy
# The retention policy for this domain, which specifies whether
# resources will be retained after the Domain is deleted. By default,
# all resources are retained (not automatically deleted).
# @return [Types::RetentionPolicy]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteDomainRequest AWS API Documentation
#
class DeleteDomainRequest < Struct.new(
:domain_id,
:retention_policy)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEdgeDeploymentPlanRequest AWS API Documentation
#
class DeleteEdgeDeploymentPlanRequest < Struct.new(
:edge_deployment_plan_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan from which the stage will be
# deleted.
# @return [String]
#
# @!attribute [rw] stage_name
# The name of the stage.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEdgeDeploymentStageRequest AWS API Documentation
#
class DeleteEdgeDeploymentStageRequest < Struct.new(
:edge_deployment_plan_name,
:stage_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_config_name
# The name of the endpoint configuration that you want to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEndpointConfigInput AWS API Documentation
#
class DeleteEndpointConfigInput < Struct.new(
:endpoint_config_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# The name of the endpoint that you want to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteEndpointInput AWS API Documentation
#
class DeleteEndpointInput < Struct.new(
:endpoint_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_name
# The name of the experiment to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteExperimentRequest AWS API Documentation
#
class DeleteExperimentRequest < Struct.new(
:experiment_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_arn
# The Amazon Resource Name (ARN) of the experiment that is being
# deleted.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteExperimentResponse AWS API Documentation
#
class DeleteExperimentResponse < Struct.new(
:experiment_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_name
# The name of the `FeatureGroup` you want to delete. The name must be
# unique within an Amazon Web Services Region in an Amazon Web
# Services account.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteFeatureGroupRequest AWS API Documentation
#
class DeleteFeatureGroupRequest < Struct.new(
:feature_group_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] flow_definition_name
# The name of the flow definition you are deleting.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteFlowDefinitionRequest AWS API Documentation
#
class DeleteFlowDefinitionRequest < Struct.new(
:flow_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteFlowDefinitionResponse AWS API Documentation
#
class DeleteFlowDefinitionResponse < Aws::EmptyStructure; end
# @!attribute [rw] hub_name
# The name of the hub that you want to delete content in.
# @return [String]
#
# @!attribute [rw] hub_content_type
# The type of content that you want to delete from a hub.
# @return [String]
#
# @!attribute [rw] hub_content_name
# The name of the content that you want to delete from a hub.
# @return [String]
#
# @!attribute [rw] hub_content_version
# The version of the content that you want to delete from a hub.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteHubContentRequest AWS API Documentation
#
class DeleteHubContentRequest < Struct.new(
:hub_name,
:hub_content_type,
:hub_content_name,
:hub_content_version)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_name
# The name of the hub to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteHubRequest AWS API Documentation
#
class DeleteHubRequest < Struct.new(
:hub_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] human_task_ui_name
# The name of the human task user interface (work task template) you
# want to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteHumanTaskUiRequest AWS API Documentation
#
class DeleteHumanTaskUiRequest < Struct.new(
:human_task_ui_name)
SENSITIVE = []
include Aws::Structure
end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteHumanTaskUiResponse AWS API Documentation
#
class DeleteHumanTaskUiResponse < Aws::EmptyStructure; end
# @!attribute [rw] image_name
# The name of the image to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteImageRequest AWS API Documentation
#
class DeleteImageRequest < Struct.new(
:image_name)
SENSITIVE = []
include Aws::Structure
end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteImageResponse AWS API Documentation
#
class DeleteImageResponse < Aws::EmptyStructure; end
# @!attribute [rw] image_name
# The name of the image to delete.
# @return [String]
#
# @!attribute [rw] version
# The version to delete.
# @return [Integer]
#
# @!attribute [rw] alias
# The alias of the image to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteImageVersionRequest AWS API Documentation
#
class DeleteImageVersionRequest < Struct.new(
:image_name,
:version,
:alias)
SENSITIVE = []
include Aws::Structure
end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteImageVersionResponse AWS API Documentation
#
class DeleteImageVersionResponse < Aws::EmptyStructure; end
# @!attribute [rw] name
# The name of the inference experiment you want to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteInferenceExperimentRequest AWS API Documentation
#
class DeleteInferenceExperimentRequest < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] inference_experiment_arn
# The ARN of the deleted inference experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteInferenceExperimentResponse AWS API Documentation
#
class DeleteInferenceExperimentResponse < Struct.new(
:inference_experiment_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the model bias job definition to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelBiasJobDefinitionRequest AWS API Documentation
#
class DeleteModelBiasJobDefinitionRequest < Struct.new(
:job_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_name
# The name of the model card to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelCardRequest AWS API Documentation
#
class DeleteModelCardRequest < Struct.new(
:model_card_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the model explainability job definition to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelExplainabilityJobDefinitionRequest AWS API Documentation
#
class DeleteModelExplainabilityJobDefinitionRequest < Struct.new(
:job_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_name
# The name of the model to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelInput AWS API Documentation
#
class DeleteModelInput < Struct.new(
:model_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_name
# The name of the model group to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelPackageGroupInput AWS API Documentation
#
class DeleteModelPackageGroupInput < Struct.new(
:model_package_group_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_name
# The name of the model group for which to delete the policy.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelPackageGroupPolicyInput AWS API Documentation
#
class DeleteModelPackageGroupPolicyInput < Struct.new(
:model_package_group_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_name
# The name or Amazon Resource Name (ARN) of the model package to
# delete.
#
# When you specify a name, the name must have 1 to 63 characters.
# Valid characters are a-z, A-Z, 0-9, and - (hyphen).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelPackageInput AWS API Documentation
#
class DeleteModelPackageInput < Struct.new(
:model_package_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the model quality monitoring job definition to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteModelQualityJobDefinitionRequest AWS API Documentation
#
class DeleteModelQualityJobDefinitionRequest < Struct.new(
:job_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# The name of the monitoring schedule to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteMonitoringScheduleRequest AWS API Documentation
#
class DeleteMonitoringScheduleRequest < Struct.new(
:monitoring_schedule_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_name
# The name of the SageMaker notebook instance to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteNotebookInstanceInput AWS API Documentation
#
class DeleteNotebookInstanceInput < Struct.new(
:notebook_instance_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_lifecycle_config_name
# The name of the lifecycle configuration to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteNotebookInstanceLifecycleConfigInput AWS API Documentation
#
class DeleteNotebookInstanceLifecycleConfigInput < Struct.new(
:notebook_instance_lifecycle_config_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_name
# The name of the pipeline to delete.
# @return [String]
#
# @!attribute [rw] client_request_token
# A unique, case-sensitive identifier that you provide to ensure the
# idempotency of the operation. An idempotent operation completes no
# more than one time.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeletePipelineRequest AWS API Documentation
#
class DeletePipelineRequest < Struct.new(
:pipeline_name,
:client_request_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_arn
# The Amazon Resource Name (ARN) of the pipeline to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeletePipelineResponse AWS API Documentation
#
class DeletePipelineResponse < Struct.new(
:pipeline_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_name
# The name of the project to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteProjectInput AWS API Documentation
#
class DeleteProjectInput < Struct.new(
:project_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The ID of the associated Domain.
# @return [String]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteSpaceRequest AWS API Documentation
#
class DeleteSpaceRequest < Struct.new(
:domain_id,
:space_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] studio_lifecycle_config_name
# The name of the Studio Lifecycle Configuration to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteStudioLifecycleConfigRequest AWS API Documentation
#
class DeleteStudioLifecycleConfigRequest < Struct.new(
:studio_lifecycle_config_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] resource_arn
# The Amazon Resource Name (ARN) of the resource whose tags you want
# to delete.
# @return [String]
#
# @!attribute [rw] tag_keys
# An array or one or more tag keys to delete.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTagsInput AWS API Documentation
#
class DeleteTagsInput < Struct.new(
:resource_arn,
:tag_keys)
SENSITIVE = []
include Aws::Structure
end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTagsOutput AWS API Documentation
#
class DeleteTagsOutput < Aws::EmptyStructure; end
# @!attribute [rw] trial_component_name
# The name of the component to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrialComponentRequest AWS API Documentation
#
class DeleteTrialComponentRequest < Struct.new(
:trial_component_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the component is being deleted.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrialComponentResponse AWS API Documentation
#
class DeleteTrialComponentResponse < Struct.new(
:trial_component_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_name
# The name of the trial to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrialRequest AWS API Documentation
#
class DeleteTrialRequest < Struct.new(
:trial_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_arn
# The Amazon Resource Name (ARN) of the trial that is being deleted.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteTrialResponse AWS API Documentation
#
class DeleteTrialResponse < Struct.new(
:trial_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteUserProfileRequest AWS API Documentation
#
class DeleteUserProfileRequest < Struct.new(
:domain_id,
:user_profile_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workforce_name
# The name of the workforce.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkforceRequest AWS API Documentation
#
class DeleteWorkforceRequest < Struct.new(
:workforce_name)
SENSITIVE = []
include Aws::Structure
end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkforceResponse AWS API Documentation
#
class DeleteWorkforceResponse < Aws::EmptyStructure; end
# @!attribute [rw] workteam_name
# The name of the work team to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkteamRequest AWS API Documentation
#
class DeleteWorkteamRequest < Struct.new(
:workteam_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] success
# Returns `true` if the work team was successfully deleted; otherwise,
# returns `false`.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteWorkteamResponse AWS API Documentation
#
class DeleteWorkteamResponse < Struct.new(
:success)
SENSITIVE = []
include Aws::Structure
end
# Gets the Amazon EC2 Container Registry path of the docker image of the
# model that is hosted in this [ProductionVariant][1].
#
# If you used the `registry/repository[:tag]` form to specify the image
# path of the primary container when you created the model hosted in
# this `ProductionVariant`, the path resolves to a path of the form
# `registry/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][2] in the *Amazon ECR User
# Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ProductionVariant.html
# [2]: https://docs.aws.amazon.com/AmazonECR/latest/userguide/docker-pull-ecr-image.html
#
# @!attribute [rw] specified_image
# The image path you specified when you created the model.
# @return [String]
#
# @!attribute [rw] resolved_image
# The specific digest path of the image hosted in this
# `ProductionVariant`.
# @return [String]
#
# @!attribute [rw] resolution_time
# The date and time when the image path for the model resolved to the
# `ResolvedImage`
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeployedImage AWS API Documentation
#
class DeployedImage < Struct.new(
:specified_image,
:resolved_image,
:resolution_time)
SENSITIVE = []
include Aws::Structure
end
# The deployment configuration for an endpoint, which contains the
# desired deployment strategy and rollback configurations.
#
# @!attribute [rw] blue_green_update_policy
# Update policy for a blue/green deployment. If this update policy is
# specified, SageMaker creates a new fleet during the deployment while
# maintaining the old fleet. SageMaker flips traffic to the new fleet
# according to the specified traffic routing configuration. Only one
# update policy should be used in the deployment configuration. If no
# update policy is specified, SageMaker uses a blue/green deployment
# strategy with all at once traffic shifting by default.
# @return [Types::BlueGreenUpdatePolicy]
#
# @!attribute [rw] auto_rollback_configuration
# Automatic rollback configuration for handling endpoint deployment
# failures and recovery.
# @return [Types::AutoRollbackConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeploymentConfig AWS API Documentation
#
class DeploymentConfig < Struct.new(
:blue_green_update_policy,
:auto_rollback_configuration)
SENSITIVE = []
include Aws::Structure
end
# Contains information about a stage in an edge deployment plan.
#
# @!attribute [rw] stage_name
# The name of the stage.
# @return [String]
#
# @!attribute [rw] device_selection_config
# Configuration of the devices in the stage.
# @return [Types::DeviceSelectionConfig]
#
# @!attribute [rw] deployment_config
# Configuration of the deployment details.
# @return [Types::EdgeDeploymentConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeploymentStage AWS API Documentation
#
class DeploymentStage < Struct.new(
:stage_name,
:device_selection_config,
:deployment_config)
SENSITIVE = []
include Aws::Structure
end
# Contains information summarizing the deployment stage results.
#
# @!attribute [rw] stage_name
# The name of the stage.
# @return [String]
#
# @!attribute [rw] device_selection_config
# Configuration of the devices in the stage.
# @return [Types::DeviceSelectionConfig]
#
# @!attribute [rw] deployment_config
# Configuration of the deployment details.
# @return [Types::EdgeDeploymentConfig]
#
# @!attribute [rw] deployment_status
# General status of the current state.
# @return [Types::EdgeDeploymentStatus]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeploymentStageStatusSummary AWS API Documentation
#
class DeploymentStageStatusSummary < Struct.new(
:stage_name,
:device_selection_config,
:deployment_config,
:deployment_status)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet the devices belong to.
# @return [String]
#
# @!attribute [rw] device_names
# The unique IDs of the devices.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeregisterDevicesRequest AWS API Documentation
#
class DeregisterDevicesRequest < Struct.new(
:device_fleet_name,
:device_names)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_name
# The name of the action to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeActionRequest AWS API Documentation
#
class DescribeActionRequest < Struct.new(
:action_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_name
# The name of the action.
# @return [String]
#
# @!attribute [rw] action_arn
# The Amazon Resource Name (ARN) of the action.
# @return [String]
#
# @!attribute [rw] source
# The source of the action.
# @return [Types::ActionSource]
#
# @!attribute [rw] action_type
# The type of the action.
# @return [String]
#
# @!attribute [rw] description
# The description of the action.
# @return [String]
#
# @!attribute [rw] status
# The status of the action.
# @return [String]
#
# @!attribute [rw] properties
# A list of the action's properties.
# @return [Hash<String,String>]
#
# @!attribute [rw] creation_time
# When the action was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the action was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] lineage_group_arn
# The Amazon Resource Name (ARN) of the lineage group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeActionResponse AWS API Documentation
#
class DescribeActionResponse < Struct.new(
:action_name,
:action_arn,
:source,
:action_type,
:description,
:status,
:properties,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:metadata_properties,
:lineage_group_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] algorithm_name
# The name of the algorithm to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAlgorithmInput AWS API Documentation
#
class DescribeAlgorithmInput < Struct.new(
:algorithm_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] algorithm_name
# The name of the algorithm being described.
# @return [String]
#
# @!attribute [rw] algorithm_arn
# The Amazon Resource Name (ARN) of the algorithm.
# @return [String]
#
# @!attribute [rw] algorithm_description
# A brief summary about the algorithm.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp specifying when the algorithm was created.
# @return [Time]
#
# @!attribute [rw] training_specification
# Details about training jobs run by this algorithm.
# @return [Types::TrainingSpecification]
#
# @!attribute [rw] inference_specification
# Details about inference jobs that the algorithm runs.
# @return [Types::InferenceSpecification]
#
# @!attribute [rw] validation_specification
# Details about configurations for one or more training jobs that
# SageMaker runs to test the algorithm.
# @return [Types::AlgorithmValidationSpecification]
#
# @!attribute [rw] algorithm_status
# The current status of the algorithm.
# @return [String]
#
# @!attribute [rw] algorithm_status_details
# Details about the current status of the algorithm.
# @return [Types::AlgorithmStatusDetails]
#
# @!attribute [rw] product_id
# The product identifier of the algorithm.
# @return [String]
#
# @!attribute [rw] certify_for_marketplace
# Whether the algorithm is certified to be listed in Amazon Web
# Services Marketplace.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAlgorithmOutput AWS API Documentation
#
class DescribeAlgorithmOutput < Struct.new(
:algorithm_name,
:algorithm_arn,
:algorithm_description,
:creation_time,
:training_specification,
:inference_specification,
:validation_specification,
:algorithm_status,
:algorithm_status_details,
:product_id,
:certify_for_marketplace)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_image_config_name
# The name of the AppImageConfig to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAppImageConfigRequest AWS API Documentation
#
class DescribeAppImageConfigRequest < Struct.new(
:app_image_config_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_image_config_arn
# The Amazon Resource Name (ARN) of the AppImageConfig.
# @return [String]
#
# @!attribute [rw] app_image_config_name
# The name of the AppImageConfig.
# @return [String]
#
# @!attribute [rw] creation_time
# When the AppImageConfig was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# When the AppImageConfig was last modified.
# @return [Time]
#
# @!attribute [rw] kernel_gateway_image_config
# The configuration of a KernelGateway app.
# @return [Types::KernelGatewayImageConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAppImageConfigResponse AWS API Documentation
#
class DescribeAppImageConfigResponse < Struct.new(
:app_image_config_arn,
:app_image_config_name,
:creation_time,
:last_modified_time,
:kernel_gateway_image_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name. If this value is not set, then `SpaceName`
# must be set.
# @return [String]
#
# @!attribute [rw] app_type
# The type of app.
# @return [String]
#
# @!attribute [rw] app_name
# The name of the app.
# @return [String]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAppRequest AWS API Documentation
#
class DescribeAppRequest < Struct.new(
:domain_id,
:user_profile_name,
:app_type,
:app_name,
:space_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_arn
# The Amazon Resource Name (ARN) of the app.
# @return [String]
#
# @!attribute [rw] app_type
# The type of app.
# @return [String]
#
# @!attribute [rw] app_name
# The name of the app.
# @return [String]
#
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name.
# @return [String]
#
# @!attribute [rw] status
# The status.
# @return [String]
#
# @!attribute [rw] last_health_check_timestamp
# The timestamp of the last health check.
# @return [Time]
#
# @!attribute [rw] last_user_activity_timestamp
# The timestamp of the last user's activity.
# `LastUserActivityTimestamp` is also updated when SageMaker performs
# health checks without user activity. As a result, this value is set
# to the same value as `LastHealthCheckTimestamp`.
# @return [Time]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] failure_reason
# The failure reason.
# @return [String]
#
# @!attribute [rw] resource_spec
# The instance type and the Amazon Resource Name (ARN) of the
# SageMaker image created on the instance.
# @return [Types::ResourceSpec]
#
# @!attribute [rw] space_name
# The name of the space. If this value is not set, then
# `UserProfileName` must be set.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAppResponse AWS API Documentation
#
class DescribeAppResponse < Struct.new(
:app_arn,
:app_type,
:app_name,
:domain_id,
:user_profile_name,
:status,
:last_health_check_timestamp,
:last_user_activity_timestamp,
:creation_time,
:failure_reason,
:resource_spec,
:space_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_arn
# The Amazon Resource Name (ARN) of the artifact to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeArtifactRequest AWS API Documentation
#
class DescribeArtifactRequest < Struct.new(
:artifact_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_name
# The name of the artifact.
# @return [String]
#
# @!attribute [rw] artifact_arn
# The Amazon Resource Name (ARN) of the artifact.
# @return [String]
#
# @!attribute [rw] source
# The source of the artifact.
# @return [Types::ArtifactSource]
#
# @!attribute [rw] artifact_type
# The type of the artifact.
# @return [String]
#
# @!attribute [rw] properties
# A list of the artifact's properties.
# @return [Hash<String,String>]
#
# @!attribute [rw] creation_time
# When the artifact was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the artifact was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] lineage_group_arn
# The Amazon Resource Name (ARN) of the lineage group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeArtifactResponse AWS API Documentation
#
class DescribeArtifactResponse < Struct.new(
:artifact_name,
:artifact_arn,
:source,
:artifact_type,
:properties,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:metadata_properties,
:lineage_group_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_name
# Requests information about an AutoML job using its unique name.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAutoMLJobRequest AWS API Documentation
#
class DescribeAutoMLJobRequest < Struct.new(
:auto_ml_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_name
# Returns the name of the AutoML job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# Returns the ARN of the AutoML job.
# @return [String]
#
# @!attribute [rw] input_data_config
# Returns the input data configuration for the AutoML job.
# @return [Array<Types::AutoMLChannel>]
#
# @!attribute [rw] output_data_config
# Returns the job's output data config.
# @return [Types::AutoMLOutputDataConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the Identity and Access Management
# (IAM) role that has read permission to the input data location and
# write permission to the output data location in Amazon S3.
# @return [String]
#
# @!attribute [rw] auto_ml_job_objective
# Returns the job's objective.
# @return [Types::AutoMLJobObjective]
#
# @!attribute [rw] problem_type
# Returns the job's problem type.
# @return [String]
#
# @!attribute [rw] auto_ml_job_config
# Returns the configuration for the AutoML job.
# @return [Types::AutoMLJobConfig]
#
# @!attribute [rw] creation_time
# Returns the creation time of the AutoML job.
# @return [Time]
#
# @!attribute [rw] end_time
# Returns the end time of the AutoML job.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# Returns the job's last modified time.
# @return [Time]
#
# @!attribute [rw] failure_reason
# Returns the failure reason for an AutoML job, when applicable.
# @return [String]
#
# @!attribute [rw] partial_failure_reasons
# Returns a list of reasons for partial failures within an AutoML job.
# @return [Array<Types::AutoMLPartialFailureReason>]
#
# @!attribute [rw] best_candidate
# The best model candidate selected by SageMaker Autopilot using both
# the best objective metric and lowest [InferenceLatency][1] for an
# experiment.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.html
# @return [Types::AutoMLCandidate]
#
# @!attribute [rw] auto_ml_job_status
# Returns the status of the AutoML job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_secondary_status
# Returns the secondary status of the AutoML job.
# @return [String]
#
# @!attribute [rw] generate_candidate_definitions_only
# Indicates whether the output for an AutoML job generates candidate
# definitions only.
# @return [Boolean]
#
# @!attribute [rw] auto_ml_job_artifacts
# Returns information on the job's artifacts found in
# `AutoMLJobArtifacts`.
# @return [Types::AutoMLJobArtifacts]
#
# @!attribute [rw] resolved_attributes
# Contains `ProblemType`, `AutoMLJobObjective`, and
# `CompletionCriteria`. If you do not provide these values, they are
# auto-inferred. If you do provide them, the values used are the ones
# you provide.
# @return [Types::ResolvedAttributes]
#
# @!attribute [rw] model_deploy_config
# Indicates whether the model was deployed automatically to an
# endpoint and the name of that endpoint if deployed automatically.
# @return [Types::ModelDeployConfig]
#
# @!attribute [rw] model_deploy_result
# Provides information about endpoint for the model deployment.
# @return [Types::ModelDeployResult]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAutoMLJobResponse AWS API Documentation
#
class DescribeAutoMLJobResponse < Struct.new(
:auto_ml_job_name,
:auto_ml_job_arn,
:input_data_config,
:output_data_config,
:role_arn,
:auto_ml_job_objective,
:problem_type,
:auto_ml_job_config,
:creation_time,
:end_time,
:last_modified_time,
:failure_reason,
:partial_failure_reasons,
:best_candidate,
:auto_ml_job_status,
:auto_ml_job_secondary_status,
:generate_candidate_definitions_only,
:auto_ml_job_artifacts,
:resolved_attributes,
:model_deploy_config,
:model_deploy_result)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_name
# Requests information about an AutoML V2 job using its unique name.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAutoMLJobV2Request AWS API Documentation
#
class DescribeAutoMLJobV2Request < Struct.new(
:auto_ml_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_name
# Returns the name of the AutoML V2 job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# Returns the Amazon Resource Name (ARN) of the AutoML V2 job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_input_data_config
# Returns an array of channel objects describing the input data and
# their location.
# @return [Array<Types::AutoMLJobChannel>]
#
# @!attribute [rw] output_data_config
# Returns the job's output data config.
# @return [Types::AutoMLOutputDataConfig]
#
# @!attribute [rw] role_arn
# The ARN of the Identity and Access Management role that has read
# permission to the input data location and write permission to the
# output data location in Amazon S3.
# @return [String]
#
# @!attribute [rw] auto_ml_job_objective
# Returns the job's objective.
# @return [Types::AutoMLJobObjective]
#
# @!attribute [rw] auto_ml_problem_type_config
# Returns the configuration settings of the problem type set for the
# AutoML V2 job.
# @return [Types::AutoMLProblemTypeConfig]
#
# @!attribute [rw] creation_time
# Returns the creation time of the AutoML V2 job.
# @return [Time]
#
# @!attribute [rw] end_time
# Returns the end time of the AutoML V2 job.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# Returns the job's last modified time.
# @return [Time]
#
# @!attribute [rw] failure_reason
# Returns the reason for the failure of the AutoML V2 job, when
# applicable.
# @return [String]
#
# @!attribute [rw] partial_failure_reasons
# Returns a list of reasons for partial failures within an AutoML V2
# job.
# @return [Array<Types::AutoMLPartialFailureReason>]
#
# @!attribute [rw] best_candidate
# Information about the candidate produced by an AutoML training job
# V2, including its status, steps, and other properties.
# @return [Types::AutoMLCandidate]
#
# @!attribute [rw] auto_ml_job_status
# Returns the status of the AutoML V2 job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_secondary_status
# Returns the secondary status of the AutoML V2 job.
# @return [String]
#
# @!attribute [rw] model_deploy_config
# Indicates whether the model was deployed automatically to an
# endpoint and the name of that endpoint if deployed automatically.
# @return [Types::ModelDeployConfig]
#
# @!attribute [rw] model_deploy_result
# Provides information about endpoint for the model deployment.
# @return [Types::ModelDeployResult]
#
# @!attribute [rw] data_split_config
# Returns the configuration settings of how the data are split into
# train and validation datasets.
# @return [Types::AutoMLDataSplitConfig]
#
# @!attribute [rw] security_config
# Returns the security configuration for traffic encryption or Amazon
# VPC settings.
# @return [Types::AutoMLSecurityConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAutoMLJobV2Response AWS API Documentation
#
class DescribeAutoMLJobV2Response < Struct.new(
:auto_ml_job_name,
:auto_ml_job_arn,
:auto_ml_job_input_data_config,
:output_data_config,
:role_arn,
:auto_ml_job_objective,
:auto_ml_problem_type_config,
:creation_time,
:end_time,
:last_modified_time,
:failure_reason,
:partial_failure_reasons,
:best_candidate,
:auto_ml_job_status,
:auto_ml_job_secondary_status,
:model_deploy_config,
:model_deploy_result,
:data_split_config,
:security_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] code_repository_name
# The name of the Git repository to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCodeRepositoryInput AWS API Documentation
#
class DescribeCodeRepositoryInput < Struct.new(
:code_repository_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] code_repository_name
# The name of the Git repository.
# @return [String]
#
# @!attribute [rw] code_repository_arn
# The Amazon Resource Name (ARN) of the Git repository.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the repository was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the repository was last changed.
# @return [Time]
#
# @!attribute [rw] git_config
# Configuration details about the repository, including the URL where
# the repository is located, the default branch, and the Amazon
# Resource Name (ARN) of the Amazon Web Services Secrets Manager
# secret that contains the credentials used to access the repository.
# @return [Types::GitConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCodeRepositoryOutput AWS API Documentation
#
class DescribeCodeRepositoryOutput < Struct.new(
:code_repository_name,
:code_repository_arn,
:creation_time,
:last_modified_time,
:git_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] compilation_job_name
# The name of the model compilation job that you want information
# about.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCompilationJobRequest AWS API Documentation
#
class DescribeCompilationJobRequest < Struct.new(
:compilation_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] compilation_job_name
# The name of the model compilation job.
# @return [String]
#
# @!attribute [rw] compilation_job_arn
# The Amazon Resource Name (ARN) of the model compilation job.
# @return [String]
#
# @!attribute [rw] compilation_job_status
# The status of the model compilation job.
# @return [String]
#
# @!attribute [rw] compilation_start_time
# The time when the model compilation job started the `CompilationJob`
# instances.
#
# You are billed for the time between this timestamp and the timestamp
# in the `CompilationEndTime` field. In Amazon CloudWatch Logs, the
# start time might be later than this time. That's because it takes
# time to download the compilation job, which depends on the size of
# the compilation job container.
# @return [Time]
#
# @!attribute [rw] compilation_end_time
# The time when the model compilation job on a compilation job
# instance ended. For a successful or stopped job, this is when the
# job's model artifacts have finished uploading. For a failed job,
# this is when Amazon SageMaker detected that the job failed.
# @return [Time]
#
# @!attribute [rw] stopping_condition
# Specifies a limit to how long a model compilation job can run. When
# the job reaches the time limit, Amazon SageMaker ends the
# compilation job. Use this API to cap model training costs.
# @return [Types::StoppingCondition]
#
# @!attribute [rw] inference_image
# The inference image to use when compiling a model. Specify an image
# only if the target device is a cloud instance.
# @return [String]
#
# @!attribute [rw] model_package_version_arn
# The Amazon Resource Name (ARN) of the versioned model package that
# was provided to SageMaker Neo when you initiated a compilation job.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the model compilation job was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time that the status of the model compilation job was last
# modified.
# @return [Time]
#
# @!attribute [rw] failure_reason
# If a model compilation job failed, the reason it failed.
# @return [String]
#
# @!attribute [rw] model_artifacts
# Information about the location in Amazon S3 that has been configured
# for storing the model artifacts used in the compilation job.
# @return [Types::ModelArtifacts]
#
# @!attribute [rw] model_digests
# Provides a BLAKE2 hash value that identifies the compiled model
# artifacts in Amazon S3.
# @return [Types::ModelDigests]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# assumes to perform the model compilation job.
# @return [String]
#
# @!attribute [rw] input_config
# Information about the location in Amazon S3 of the input model
# artifacts, the name and shape of the expected data inputs, and the
# framework in which the model was trained.
# @return [Types::InputConfig]
#
# @!attribute [rw] output_config
# Information about the output location for the compiled model and the
# target device that the model runs on.
# @return [Types::OutputConfig]
#
# @!attribute [rw] vpc_config
# A [VpcConfig][1] object that specifies the VPC that you want your
# compilation job to connect to. Control access to your models by
# configuring the VPC. For more information, see [Protect Compilation
# Jobs by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/neo-vpc.html
# @return [Types::NeoVpcConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeCompilationJobResponse AWS API Documentation
#
class DescribeCompilationJobResponse < Struct.new(
:compilation_job_name,
:compilation_job_arn,
:compilation_job_status,
:compilation_start_time,
:compilation_end_time,
:stopping_condition,
:inference_image,
:model_package_version_arn,
:creation_time,
:last_modified_time,
:failure_reason,
:model_artifacts,
:model_digests,
:role_arn,
:input_config,
:output_config,
:vpc_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_name
# The name of the context to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeContextRequest AWS API Documentation
#
class DescribeContextRequest < Struct.new(
:context_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_name
# The name of the context.
# @return [String]
#
# @!attribute [rw] context_arn
# The Amazon Resource Name (ARN) of the context.
# @return [String]
#
# @!attribute [rw] source
# The source of the context.
# @return [Types::ContextSource]
#
# @!attribute [rw] context_type
# The type of the context.
# @return [String]
#
# @!attribute [rw] description
# The description of the context.
# @return [String]
#
# @!attribute [rw] properties
# A list of the context's properties.
# @return [Hash<String,String>]
#
# @!attribute [rw] creation_time
# When the context was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the context was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] lineage_group_arn
# The Amazon Resource Name (ARN) of the lineage group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeContextResponse AWS API Documentation
#
class DescribeContextResponse < Struct.new(
:context_name,
:context_arn,
:source,
:context_type,
:description,
:properties,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:lineage_group_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the data quality monitoring job definition to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDataQualityJobDefinitionRequest AWS API Documentation
#
class DescribeDataQualityJobDefinitionRequest < Struct.new(
:job_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_arn
# The Amazon Resource Name (ARN) of the data quality monitoring job
# definition.
# @return [String]
#
# @!attribute [rw] job_definition_name
# The name of the data quality monitoring job definition.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the data quality monitoring job definition was
# created.
# @return [Time]
#
# @!attribute [rw] data_quality_baseline_config
# The constraints and baselines for the data quality monitoring job
# definition.
# @return [Types::DataQualityBaselineConfig]
#
# @!attribute [rw] data_quality_app_specification
# Information about the container that runs the data quality
# monitoring job.
# @return [Types::DataQualityAppSpecification]
#
# @!attribute [rw] data_quality_job_input
# The list of inputs for the data quality monitoring job. Currently
# endpoints are supported.
# @return [Types::DataQualityJobInput]
#
# @!attribute [rw] data_quality_job_output_config
# The output configuration for monitoring jobs.
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] job_resources
# Identifies the resources to deploy for a monitoring job.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] network_config
# The networking configuration for the data quality monitoring job.
# @return [Types::MonitoringNetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] stopping_condition
# A time limit for how long the monitoring job is allowed to run
# before stopping.
# @return [Types::MonitoringStoppingCondition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDataQualityJobDefinitionResponse AWS API Documentation
#
class DescribeDataQualityJobDefinitionResponse < Struct.new(
:job_definition_arn,
:job_definition_name,
:creation_time,
:data_quality_baseline_config,
:data_quality_app_specification,
:data_quality_job_input,
:data_quality_job_output_config,
:job_resources,
:network_config,
:role_arn,
:stopping_condition)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDeviceFleetRequest AWS API Documentation
#
class DescribeDeviceFleetRequest < Struct.new(
:device_fleet_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet.
# @return [String]
#
# @!attribute [rw] device_fleet_arn
# The The Amazon Resource Name (ARN) of the fleet.
# @return [String]
#
# @!attribute [rw] output_config
# The output configuration for storing sampled data.
# @return [Types::EdgeOutputConfig]
#
# @!attribute [rw] description
# A description of the fleet.
# @return [String]
#
# @!attribute [rw] creation_time
# Timestamp of when the device fleet was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# Timestamp of when the device fleet was last updated.
# @return [Time]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) that has access to Amazon Web
# Services Internet of Things (IoT).
# @return [String]
#
# @!attribute [rw] iot_role_alias
# The Amazon Resource Name (ARN) alias created in Amazon Web Services
# Internet of Things (IoT).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDeviceFleetResponse AWS API Documentation
#
class DescribeDeviceFleetResponse < Struct.new(
:device_fleet_name,
:device_fleet_arn,
:output_config,
:description,
:creation_time,
:last_modified_time,
:role_arn,
:iot_role_alias)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# Next token of device description.
# @return [String]
#
# @!attribute [rw] device_name
# The unique ID of the device.
# @return [String]
#
# @!attribute [rw] device_fleet_name
# The name of the fleet the devices belong to.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDeviceRequest AWS API Documentation
#
class DescribeDeviceRequest < Struct.new(
:next_token,
:device_name,
:device_fleet_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_arn
# The Amazon Resource Name (ARN) of the device.
# @return [String]
#
# @!attribute [rw] device_name
# The unique identifier of the device.
# @return [String]
#
# @!attribute [rw] description
# A description of the device.
# @return [String]
#
# @!attribute [rw] device_fleet_name
# The name of the fleet the device belongs to.
# @return [String]
#
# @!attribute [rw] iot_thing_name
# The Amazon Web Services Internet of Things (IoT) object thing name
# associated with the device.
# @return [String]
#
# @!attribute [rw] registration_time
# The timestamp of the last registration or de-reregistration.
# @return [Time]
#
# @!attribute [rw] latest_heartbeat
# The last heartbeat received from the device.
# @return [Time]
#
# @!attribute [rw] models
# Models on the device.
# @return [Array<Types::EdgeModel>]
#
# @!attribute [rw] max_models
# The maximum number of models.
# @return [Integer]
#
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to need tokening.
# @return [String]
#
# @!attribute [rw] agent_version
# Edge Manager agent version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDeviceResponse AWS API Documentation
#
class DescribeDeviceResponse < Struct.new(
:device_arn,
:device_name,
:description,
:device_fleet_name,
:iot_thing_name,
:registration_time,
:latest_heartbeat,
:models,
:max_models,
:next_token,
:agent_version)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDomainRequest AWS API Documentation
#
class DescribeDomainRequest < Struct.new(
:domain_id)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_arn
# The domain's Amazon Resource Name (ARN).
# @return [String]
#
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] domain_name
# The domain name.
# @return [String]
#
# @!attribute [rw] home_efs_file_system_id
# The ID of the Amazon Elastic File System (EFS) managed by this
# Domain.
# @return [String]
#
# @!attribute [rw] single_sign_on_managed_application_instance_id
# The IAM Identity Center managed application instance ID.
# @return [String]
#
# @!attribute [rw] status
# The status.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last modified time.
# @return [Time]
#
# @!attribute [rw] failure_reason
# The failure reason.
# @return [String]
#
# @!attribute [rw] auth_mode
# The domain's authentication mode.
# @return [String]
#
# @!attribute [rw] default_user_settings
# Settings which are applied to UserProfiles in this domain if
# settings are not explicitly specified in a given UserProfile.
# @return [Types::UserSettings]
#
# @!attribute [rw] app_network_access_type
# Specifies the VPC used for non-EFS traffic. The default value is
# `PublicInternetOnly`.
#
# * `PublicInternetOnly` - Non-EFS traffic is through a VPC managed by
# Amazon SageMaker, which allows direct internet access
#
# * `VpcOnly` - All Studio traffic is through the specified VPC and
# subnets
# @return [String]
#
# @!attribute [rw] home_efs_file_system_kms_key_id
# Use `KmsKeyId`.
# @return [String]
#
# @!attribute [rw] subnet_ids
# The VPC subnets that Studio uses for communication.
# @return [Array<String>]
#
# @!attribute [rw] url
# The domain's URL.
# @return [String]
#
# @!attribute [rw] vpc_id
# The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses
# for communication.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services KMS customer managed key used to encrypt the
# EFS volume attached to the domain.
# @return [String]
#
# @!attribute [rw] domain_settings
# A collection of `Domain` settings.
# @return [Types::DomainSettings]
#
# @!attribute [rw] app_security_group_management
# The entity that creates and manages the required security groups for
# inter-app communication in `VPCOnly` mode. Required when
# `CreateDomain.AppNetworkAccessType` is `VPCOnly` and
# `DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn`
# is provided.
# @return [String]
#
# @!attribute [rw] security_group_id_for_domain_boundary
# The ID of the security group that authorizes traffic between the
# `RSessionGateway` apps and the `RStudioServerPro` app.
# @return [String]
#
# @!attribute [rw] default_space_settings
# The default settings used to create a space.
# @return [Types::DefaultSpaceSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDomainResponse AWS API Documentation
#
class DescribeDomainResponse < Struct.new(
:domain_arn,
:domain_id,
:domain_name,
:home_efs_file_system_id,
:single_sign_on_managed_application_instance_id,
:status,
:creation_time,
:last_modified_time,
:failure_reason,
:auth_mode,
:default_user_settings,
:app_network_access_type,
:home_efs_file_system_kms_key_id,
:subnet_ids,
:url,
:vpc_id,
:kms_key_id,
:domain_settings,
:app_security_group_management,
:security_group_id_for_domain_boundary,
:default_space_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_name
# The name of the deployment plan to describe.
# @return [String]
#
# @!attribute [rw] next_token
# If the edge deployment plan has enough stages to require tokening,
# then this is the response from the last list of stages returned.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to select (50 by default).
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEdgeDeploymentPlanRequest AWS API Documentation
#
class DescribeEdgeDeploymentPlanRequest < Struct.new(
:edge_deployment_plan_name,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_arn
# The ARN of edge deployment plan.
# @return [String]
#
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan.
# @return [String]
#
# @!attribute [rw] model_configs
# List of models associated with the edge deployment plan.
# @return [Array<Types::EdgeDeploymentModelConfig>]
#
# @!attribute [rw] device_fleet_name
# The device fleet used for this edge deployment plan.
# @return [String]
#
# @!attribute [rw] edge_deployment_success
# The number of edge devices with the successful deployment.
# @return [Integer]
#
# @!attribute [rw] edge_deployment_pending
# The number of edge devices yet to pick up deployment, or in
# progress.
# @return [Integer]
#
# @!attribute [rw] edge_deployment_failed
# The number of edge devices that failed the deployment.
# @return [Integer]
#
# @!attribute [rw] stages
# List of stages in the edge deployment plan.
# @return [Array<Types::DeploymentStageStatusSummary>]
#
# @!attribute [rw] next_token
# Token to use when calling the next set of stages in the edge
# deployment plan.
# @return [String]
#
# @!attribute [rw] creation_time
# The time when the edge deployment plan was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time when the edge deployment plan was last updated.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEdgeDeploymentPlanResponse AWS API Documentation
#
class DescribeEdgeDeploymentPlanResponse < Struct.new(
:edge_deployment_plan_arn,
:edge_deployment_plan_name,
:model_configs,
:device_fleet_name,
:edge_deployment_success,
:edge_deployment_pending,
:edge_deployment_failed,
:stages,
:next_token,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_packaging_job_name
# The name of the edge packaging job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEdgePackagingJobRequest AWS API Documentation
#
class DescribeEdgePackagingJobRequest < Struct.new(
:edge_packaging_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_packaging_job_arn
# The Amazon Resource Name (ARN) of the edge packaging job.
# @return [String]
#
# @!attribute [rw] edge_packaging_job_name
# The name of the edge packaging job.
# @return [String]
#
# @!attribute [rw] compilation_job_name
# The name of the SageMaker Neo compilation job that is used to locate
# model artifacts that are being packaged.
# @return [String]
#
# @!attribute [rw] model_name
# The name of the model.
# @return [String]
#
# @!attribute [rw] model_version
# The version of the model.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that enables Amazon
# SageMaker to download and upload the model, and to contact Neo.
# @return [String]
#
# @!attribute [rw] output_config
# The output configuration for the edge packaging job.
# @return [Types::EdgeOutputConfig]
#
# @!attribute [rw] resource_key
# The Amazon Web Services KMS key to use when encrypting the EBS
# volume the job run on.
# @return [String]
#
# @!attribute [rw] edge_packaging_job_status
# The current status of the packaging job.
# @return [String]
#
# @!attribute [rw] edge_packaging_job_status_message
# Returns a message describing the job status and error messages.
# @return [String]
#
# @!attribute [rw] creation_time
# The timestamp of when the packaging job was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The timestamp of when the job was last updated.
# @return [Time]
#
# @!attribute [rw] model_artifact
# The Amazon Simple Storage (S3) URI where model artifacts ares
# stored.
# @return [String]
#
# @!attribute [rw] model_signature
# The signature document of files in the model artifact.
# @return [String]
#
# @!attribute [rw] preset_deployment_output
# The output of a SageMaker Edge Manager deployable resource.
# @return [Types::EdgePresetDeploymentOutput]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEdgePackagingJobResponse AWS API Documentation
#
class DescribeEdgePackagingJobResponse < Struct.new(
:edge_packaging_job_arn,
:edge_packaging_job_name,
:compilation_job_name,
:model_name,
:model_version,
:role_arn,
:output_config,
:resource_key,
:edge_packaging_job_status,
:edge_packaging_job_status_message,
:creation_time,
:last_modified_time,
:model_artifact,
:model_signature,
:preset_deployment_output)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_config_name
# The name of the endpoint configuration.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpointConfigInput AWS API Documentation
#
class DescribeEndpointConfigInput < Struct.new(
:endpoint_config_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_config_name
# Name of the SageMaker endpoint configuration.
# @return [String]
#
# @!attribute [rw] endpoint_config_arn
# The Amazon Resource Name (ARN) of the endpoint configuration.
# @return [String]
#
# @!attribute [rw] production_variants
# An array of `ProductionVariant` objects, one for each model that you
# want to host at this endpoint.
# @return [Array<Types::ProductionVariant>]
#
# @!attribute [rw] data_capture_config
# Configuration to control how SageMaker captures inference data.
# @return [Types::DataCaptureConfig]
#
# @!attribute [rw] kms_key_id
# Amazon Web Services KMS key ID Amazon SageMaker uses to encrypt data
# when storing it on the ML storage volume attached to the instance.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the endpoint configuration was created.
# @return [Time]
#
# @!attribute [rw] async_inference_config
# Returns the description of an endpoint configuration created using
# the [ `CreateEndpointConfig` ][1] API.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html
# @return [Types::AsyncInferenceConfig]
#
# @!attribute [rw] explainer_config
# The configuration parameters for an explainer.
# @return [Types::ExplainerConfig]
#
# @!attribute [rw] shadow_production_variants
# An array of `ProductionVariant` objects, one for each model that you
# want to host at this endpoint in shadow mode with production traffic
# replicated from the model specified on `ProductionVariants`.
# @return [Array<Types::ProductionVariant>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpointConfigOutput AWS API Documentation
#
class DescribeEndpointConfigOutput < Struct.new(
:endpoint_config_name,
:endpoint_config_arn,
:production_variants,
:data_capture_config,
:kms_key_id,
:creation_time,
:async_inference_config,
:explainer_config,
:shadow_production_variants)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# The name of the endpoint.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpointInput AWS API Documentation
#
class DescribeEndpointInput < Struct.new(
:endpoint_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# Name of the endpoint.
# @return [String]
#
# @!attribute [rw] endpoint_arn
# The Amazon Resource Name (ARN) of the endpoint.
# @return [String]
#
# @!attribute [rw] endpoint_config_name
# The name of the endpoint configuration associated with this
# endpoint.
# @return [String]
#
# @!attribute [rw] production_variants
# An array of [ProductionVariantSummary][1] objects, one for each
# model hosted behind this endpoint.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ProductionVariantSummary.html
# @return [Array<Types::ProductionVariantSummary>]
#
# @!attribute [rw] data_capture_config
# The currently active data capture configuration used by your
# Endpoint.
# @return [Types::DataCaptureConfigSummary]
#
# @!attribute [rw] endpoint_status
# The status of the endpoint.
#
# * `OutOfService`: Endpoint is not available to take incoming
# requests.
#
# * `Creating`: [CreateEndpoint][1] is executing.
#
# * `Updating`: [UpdateEndpoint][2] or
# [UpdateEndpointWeightsAndCapacities][3] is executing.
#
# * `SystemUpdating`: Endpoint is undergoing maintenance and cannot be
# updated or deleted or re-scaled until it has completed. This
# maintenance operation does not change any customer-specified
# values such as VPC config, KMS encryption, model, instance type,
# or instance count.
#
# * `RollingBack`: Endpoint fails to scale up or down or change its
# variant weight and is in the process of rolling back to its
# previous configuration. Once the rollback completes, endpoint
# returns to an `InService` status. This transitional status only
# applies to an endpoint that has autoscaling enabled and is
# undergoing variant weight or capacity changes as part of an
# [UpdateEndpointWeightsAndCapacities][3] call or when the
# [UpdateEndpointWeightsAndCapacities][3] operation is called
# explicitly.
#
# * `InService`: Endpoint is available to process incoming requests.
#
# * `Deleting`: [DeleteEndpoint][4] is executing.
#
# * `Failed`: Endpoint could not be created, updated, or re-scaled.
# Use the `FailureReason` value returned by [DescribeEndpoint][5]
# for information about the failure. [DeleteEndpoint][4] is the only
# operation that can be performed on a failed endpoint.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateEndpoint.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateEndpointWeightsAndCapacities.html
# [4]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DeleteEndpoint.html
# [5]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeEndpoint.html
# @return [String]
#
# @!attribute [rw] failure_reason
# If the status of the endpoint is `Failed`, the reason why it failed.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the endpoint was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that shows when the endpoint was last modified.
# @return [Time]
#
# @!attribute [rw] last_deployment_config
# The most recent deployment configuration for the endpoint.
# @return [Types::DeploymentConfig]
#
# @!attribute [rw] async_inference_config
# Returns the description of an endpoint configuration created using
# the [ `CreateEndpointConfig` ][1] API.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html
# @return [Types::AsyncInferenceConfig]
#
# @!attribute [rw] pending_deployment_summary
# Returns the summary of an in-progress deployment. This field is only
# returned when the endpoint is creating or updating with a new
# endpoint configuration.
# @return [Types::PendingDeploymentSummary]
#
# @!attribute [rw] explainer_config
# The configuration parameters for an explainer.
# @return [Types::ExplainerConfig]
#
# @!attribute [rw] shadow_production_variants
# An array of [ProductionVariantSummary][1] objects, one for each
# model that you want to host at this endpoint in shadow mode with
# production traffic replicated from the model specified on
# `ProductionVariants`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ProductionVariantSummary.html
# @return [Array<Types::ProductionVariantSummary>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeEndpointOutput AWS API Documentation
#
class DescribeEndpointOutput < Struct.new(
:endpoint_name,
:endpoint_arn,
:endpoint_config_name,
:production_variants,
:data_capture_config,
:endpoint_status,
:failure_reason,
:creation_time,
:last_modified_time,
:last_deployment_config,
:async_inference_config,
:pending_deployment_summary,
:explainer_config,
:shadow_production_variants)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_name
# The name of the experiment to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeExperimentRequest AWS API Documentation
#
class DescribeExperimentRequest < Struct.new(
:experiment_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_name
# The name of the experiment.
# @return [String]
#
# @!attribute [rw] experiment_arn
# The Amazon Resource Name (ARN) of the experiment.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the experiment as displayed. If `DisplayName` isn't
# specified, `ExperimentName` is displayed.
# @return [String]
#
# @!attribute [rw] source
# The Amazon Resource Name (ARN) of the source and, optionally, the
# type.
# @return [Types::ExperimentSource]
#
# @!attribute [rw] description
# The description of the experiment.
# @return [String]
#
# @!attribute [rw] creation_time
# When the experiment was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Who created the experiment.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the experiment was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Who last modified the experiment.
# @return [Types::UserContext]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeExperimentResponse AWS API Documentation
#
class DescribeExperimentResponse < Struct.new(
:experiment_name,
:experiment_arn,
:display_name,
:source,
:description,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_name
# The name of the `FeatureGroup` you want described.
# @return [String]
#
# @!attribute [rw] next_token
# A token to resume pagination of the list of `Features`
# (`FeatureDefinitions`). 2,500 `Features` are returned by default.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFeatureGroupRequest AWS API Documentation
#
class DescribeFeatureGroupRequest < Struct.new(
:feature_group_name,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_arn
# The Amazon Resource Name (ARN) of the `FeatureGroup`.
# @return [String]
#
# @!attribute [rw] feature_group_name
# he name of the `FeatureGroup`.
# @return [String]
#
# @!attribute [rw] record_identifier_feature_name
# The name of the `Feature` used for `RecordIdentifier`, whose value
# uniquely identifies a record stored in the feature store.
# @return [String]
#
# @!attribute [rw] event_time_feature_name
# The name of the feature that stores the `EventTime` of a Record in a
# `FeatureGroup`.
#
# An `EventTime` is a point in time when a new event occurs that
# corresponds to the creation or update of a `Record` in a
# `FeatureGroup`. All `Records` in the `FeatureGroup` have a
# corresponding `EventTime`.
# @return [String]
#
# @!attribute [rw] feature_definitions
# A list of the `Features` in the `FeatureGroup`. Each feature is
# defined by a `FeatureName` and `FeatureType`.
# @return [Array<Types::FeatureDefinition>]
#
# @!attribute [rw] creation_time
# A timestamp indicating when SageMaker created the `FeatureGroup`.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp indicating when the feature group was last updated.
# @return [Time]
#
# @!attribute [rw] online_store_config
# The configuration for the `OnlineStore`.
# @return [Types::OnlineStoreConfig]
#
# @!attribute [rw] offline_store_config
# The configuration of the offline store. It includes the following
# configurations:
#
# * Amazon S3 location of the offline store.
#
# * Configuration of the Glue data catalog.
#
# * Table format of the offline store.
#
# * Option to disable the automatic creation of a Glue table for the
# offline store.
#
# * Encryption configuration.
# @return [Types::OfflineStoreConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the IAM execution role used to
# persist data into the OfflineStore if an OfflineStoreConfig is
# provided.
# @return [String]
#
# @!attribute [rw] feature_group_status
# The status of the feature group.
# @return [String]
#
# @!attribute [rw] offline_store_status
# The status of the `OfflineStore`. Notifies you if replicating data
# into the `OfflineStore` has failed. Returns either: `Active` or
# `Blocked`
# @return [Types::OfflineStoreStatus]
#
# @!attribute [rw] last_update_status
# A value indicating whether the update made to the feature group was
# successful.
# @return [Types::LastUpdateStatus]
#
# @!attribute [rw] failure_reason
# The reason that the `FeatureGroup` failed to be replicated in the
# `OfflineStore`. This is failure can occur because:
#
# * The `FeatureGroup` could not be created in the `OfflineStore`.
#
# * The `FeatureGroup` could not be deleted from the `OfflineStore`.
# @return [String]
#
# @!attribute [rw] description
# A free form description of the feature group.
# @return [String]
#
# @!attribute [rw] next_token
# A token to resume pagination of the list of `Features`
# (`FeatureDefinitions`).
# @return [String]
#
# @!attribute [rw] online_store_total_size_bytes
# The size of the `OnlineStore` in bytes.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFeatureGroupResponse AWS API Documentation
#
class DescribeFeatureGroupResponse < Struct.new(
:feature_group_arn,
:feature_group_name,
:record_identifier_feature_name,
:event_time_feature_name,
:feature_definitions,
:creation_time,
:last_modified_time,
:online_store_config,
:offline_store_config,
:role_arn,
:feature_group_status,
:offline_store_status,
:last_update_status,
:failure_reason,
:description,
:next_token,
:online_store_total_size_bytes)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_name
# The name of the feature group containing the feature.
# @return [String]
#
# @!attribute [rw] feature_name
# The name of the feature.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFeatureMetadataRequest AWS API Documentation
#
class DescribeFeatureMetadataRequest < Struct.new(
:feature_group_name,
:feature_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_arn
# The Amazon Resource Number (ARN) of the feature group that contains
# the feature.
# @return [String]
#
# @!attribute [rw] feature_group_name
# The name of the feature group that you've specified.
# @return [String]
#
# @!attribute [rw] feature_name
# The name of the feature that you've specified.
# @return [String]
#
# @!attribute [rw] feature_type
# The data type of the feature.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp indicating when the feature was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp indicating when the metadata for the feature group was
# modified. For example, if you add a parameter describing the
# feature, the timestamp changes to reflect the last time you
# @return [Time]
#
# @!attribute [rw] description
# The description you added to describe the feature.
# @return [String]
#
# @!attribute [rw] parameters
# The key-value pairs that you added to describe the feature.
# @return [Array<Types::FeatureParameter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFeatureMetadataResponse AWS API Documentation
#
class DescribeFeatureMetadataResponse < Struct.new(
:feature_group_arn,
:feature_group_name,
:feature_name,
:feature_type,
:creation_time,
:last_modified_time,
:description,
:parameters)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] flow_definition_name
# The name of the flow definition.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFlowDefinitionRequest AWS API Documentation
#
class DescribeFlowDefinitionRequest < Struct.new(
:flow_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] flow_definition_arn
# The Amazon Resource Name (ARN) of the flow defintion.
# @return [String]
#
# @!attribute [rw] flow_definition_name
# The Amazon Resource Name (ARN) of the flow definition.
# @return [String]
#
# @!attribute [rw] flow_definition_status
# The status of the flow definition. Valid values are listed below.
# @return [String]
#
# @!attribute [rw] creation_time
# The timestamp when the flow definition was created.
# @return [Time]
#
# @!attribute [rw] human_loop_request_source
# Container for configuring the source of human task requests. Used to
# specify if Amazon Rekognition or Amazon Textract is used as an
# integration source.
# @return [Types::HumanLoopRequestSource]
#
# @!attribute [rw] human_loop_activation_config
# An object containing information about what triggers a human review
# workflow.
# @return [Types::HumanLoopActivationConfig]
#
# @!attribute [rw] human_loop_config
# An object containing information about who works on the task, the
# workforce task price, and other task details.
# @return [Types::HumanLoopConfig]
#
# @!attribute [rw] output_config
# An object containing information about the output file.
# @return [Types::FlowDefinitionOutputConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the Amazon Web Services Identity
# and Access Management (IAM) execution role for the flow definition.
# @return [String]
#
# @!attribute [rw] failure_reason
# The reason your flow definition failed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFlowDefinitionResponse AWS API Documentation
#
class DescribeFlowDefinitionResponse < Struct.new(
:flow_definition_arn,
:flow_definition_name,
:flow_definition_status,
:creation_time,
:human_loop_request_source,
:human_loop_activation_config,
:human_loop_config,
:output_config,
:role_arn,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_name
# The name of the hub that contains the content to describe.
# @return [String]
#
# @!attribute [rw] hub_content_type
# The type of content in the hub.
# @return [String]
#
# @!attribute [rw] hub_content_name
# The name of the content to describe.
# @return [String]
#
# @!attribute [rw] hub_content_version
# The version of the content to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHubContentRequest AWS API Documentation
#
class DescribeHubContentRequest < Struct.new(
:hub_name,
:hub_content_type,
:hub_content_name,
:hub_content_version)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_content_name
# The name of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_arn
# The Amazon Resource Name (ARN) of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_version
# The version of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_type
# The type of hub content.
# @return [String]
#
# @!attribute [rw] document_schema_version
# The document schema version for the hub content.
# @return [String]
#
# @!attribute [rw] hub_name
# The name of the hub that contains the content.
# @return [String]
#
# @!attribute [rw] hub_arn
# The Amazon Resource Name (ARN) of the hub that contains the content.
# @return [String]
#
# @!attribute [rw] hub_content_display_name
# The display name of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_description
# A description of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_markdown
# A string that provides a description of the hub content. This string
# can include links, tables, and standard markdown formating.
# @return [String]
#
# @!attribute [rw] hub_content_document
# The hub content document that describes information about the hub
# content such as type, associated containers, scripts, and more.
# @return [String]
#
# @!attribute [rw] hub_content_search_keywords
# The searchable keywords for the hub content.
# @return [Array<String>]
#
# @!attribute [rw] hub_content_dependencies
# The location of any dependencies that the hub content has, such as
# scripts, model artifacts, datasets, or notebooks.
# @return [Array<Types::HubContentDependency>]
#
# @!attribute [rw] hub_content_status
# The status of the hub content.
# @return [String]
#
# @!attribute [rw] failure_reason
# The failure reason if importing hub content failed.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that hub content was created.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHubContentResponse AWS API Documentation
#
class DescribeHubContentResponse < Struct.new(
:hub_content_name,
:hub_content_arn,
:hub_content_version,
:hub_content_type,
:document_schema_version,
:hub_name,
:hub_arn,
:hub_content_display_name,
:hub_content_description,
:hub_content_markdown,
:hub_content_document,
:hub_content_search_keywords,
:hub_content_dependencies,
:hub_content_status,
:failure_reason,
:creation_time)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_name
# The name of the hub to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHubRequest AWS API Documentation
#
class DescribeHubRequest < Struct.new(
:hub_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_name
# The name of the hub.
# @return [String]
#
# @!attribute [rw] hub_arn
# The Amazon Resource Name (ARN) of the hub.
# @return [String]
#
# @!attribute [rw] hub_display_name
# The display name of the hub.
# @return [String]
#
# @!attribute [rw] hub_description
# A description of the hub.
# @return [String]
#
# @!attribute [rw] hub_search_keywords
# The searchable keywords for the hub.
# @return [Array<String>]
#
# @!attribute [rw] s3_storage_config
# The Amazon S3 storage configuration for the hub.
# @return [Types::HubS3StorageConfig]
#
# @!attribute [rw] hub_status
# The status of the hub.
# @return [String]
#
# @!attribute [rw] failure_reason
# The failure reason if importing hub content failed.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the hub was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the hub was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHubResponse AWS API Documentation
#
class DescribeHubResponse < Struct.new(
:hub_name,
:hub_arn,
:hub_display_name,
:hub_description,
:hub_search_keywords,
:s3_storage_config,
:hub_status,
:failure_reason,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] human_task_ui_name
# The name of the human task user interface (worker task template) you
# want information about.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHumanTaskUiRequest AWS API Documentation
#
class DescribeHumanTaskUiRequest < Struct.new(
:human_task_ui_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] human_task_ui_arn
# The Amazon Resource Name (ARN) of the human task user interface
# (worker task template).
# @return [String]
#
# @!attribute [rw] human_task_ui_name
# The name of the human task user interface (worker task template).
# @return [String]
#
# @!attribute [rw] human_task_ui_status
# The status of the human task user interface (worker task template).
# Valid values are listed below.
# @return [String]
#
# @!attribute [rw] creation_time
# The timestamp when the human task user interface was created.
# @return [Time]
#
# @!attribute [rw] ui_template
# Container for user interface template information.
# @return [Types::UiTemplateInfo]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHumanTaskUiResponse AWS API Documentation
#
class DescribeHumanTaskUiResponse < Struct.new(
:human_task_ui_arn,
:human_task_ui_name,
:human_task_ui_status,
:creation_time,
:ui_template)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hyper_parameter_tuning_job_name
# The name of the tuning job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHyperParameterTuningJobRequest AWS API Documentation
#
class DescribeHyperParameterTuningJobRequest < Struct.new(
:hyper_parameter_tuning_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hyper_parameter_tuning_job_name
# The name of the tuning job.
# @return [String]
#
# @!attribute [rw] hyper_parameter_tuning_job_arn
# The Amazon Resource Name (ARN) of the tuning job.
# @return [String]
#
# @!attribute [rw] hyper_parameter_tuning_job_config
# The [HyperParameterTuningJobConfig][1] object that specifies the
# configuration of the tuning job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html
# @return [Types::HyperParameterTuningJobConfig]
#
# @!attribute [rw] training_job_definition
# The [HyperParameterTrainingJobDefinition][1] object that specifies
# the definition of the training jobs that this tuning job launches.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html
# @return [Types::HyperParameterTrainingJobDefinition]
#
# @!attribute [rw] training_job_definitions
# A list of the [HyperParameterTrainingJobDefinition][1] objects
# launched for this tuning job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html
# @return [Array<Types::HyperParameterTrainingJobDefinition>]
#
# @!attribute [rw] hyper_parameter_tuning_job_status
# The status of the tuning job: InProgress, Completed, Failed,
# Stopping, or Stopped.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the tuning job started.
# @return [Time]
#
# @!attribute [rw] hyper_parameter_tuning_end_time
# The date and time that the tuning job ended.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the status of the tuning job was modified.
# @return [Time]
#
# @!attribute [rw] training_job_status_counters
# The [TrainingJobStatusCounters][1] object that specifies the number
# of training jobs, categorized by status, that this tuning job
# launched.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobStatusCounters.html
# @return [Types::TrainingJobStatusCounters]
#
# @!attribute [rw] objective_status_counters
# The [ObjectiveStatusCounters][1] object that specifies the number of
# training jobs, categorized by the status of their final objective
# metric, that this tuning job launched.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ObjectiveStatusCounters.html
# @return [Types::ObjectiveStatusCounters]
#
# @!attribute [rw] best_training_job
# A [TrainingJobSummary][1] object that describes the training job
# that completed with the best current
# [HyperParameterTuningJobObjective][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobSummary.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobObjective.html
# @return [Types::HyperParameterTrainingJobSummary]
#
# @!attribute [rw] overall_best_training_job
# If the hyperparameter tuning job is an warm start tuning job with a
# `WarmStartType` of `IDENTICAL_DATA_AND_ALGORITHM`, this is the
# [TrainingJobSummary][1] for the training job with the best objective
# metric value of all training jobs launched by this tuning job and
# all parent jobs specified for the warm start tuning job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobSummary.html
# @return [Types::HyperParameterTrainingJobSummary]
#
# @!attribute [rw] warm_start_config
# The configuration for starting the hyperparameter parameter tuning
# job using one or more previous tuning jobs as a starting point. The
# results of previous tuning jobs are used to inform which
# combinations of hyperparameters to search over in the new tuning
# job.
# @return [Types::HyperParameterTuningJobWarmStartConfig]
#
# @!attribute [rw] failure_reason
# If the tuning job failed, the reason it failed.
# @return [String]
#
# @!attribute [rw] tuning_job_completion_details
# Tuning job completion information returned as the response from a
# hyperparameter tuning job. This information tells if your tuning job
# has or has not converged. It also includes the number of training
# jobs that have not improved model performance as evaluated against
# the objective function.
# @return [Types::HyperParameterTuningJobCompletionDetails]
#
# @!attribute [rw] consumed_resources
# The total resources consumed by your hyperparameter tuning job.
# @return [Types::HyperParameterTuningJobConsumedResources]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHyperParameterTuningJobResponse AWS API Documentation
#
class DescribeHyperParameterTuningJobResponse < Struct.new(
:hyper_parameter_tuning_job_name,
:hyper_parameter_tuning_job_arn,
:hyper_parameter_tuning_job_config,
:training_job_definition,
:training_job_definitions,
:hyper_parameter_tuning_job_status,
:creation_time,
:hyper_parameter_tuning_end_time,
:last_modified_time,
:training_job_status_counters,
:objective_status_counters,
:best_training_job,
:overall_best_training_job,
:warm_start_config,
:failure_reason,
:tuning_job_completion_details,
:consumed_resources)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_name
# The name of the image to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeImageRequest AWS API Documentation
#
class DescribeImageRequest < Struct.new(
:image_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time
# When the image was created.
# @return [Time]
#
# @!attribute [rw] description
# The description of the image.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the image as displayed.
# @return [String]
#
# @!attribute [rw] failure_reason
# When a create, update, or delete operation fails, the reason for the
# failure.
# @return [String]
#
# @!attribute [rw] image_arn
# The ARN of the image.
# @return [String]
#
# @!attribute [rw] image_name
# The name of the image.
# @return [String]
#
# @!attribute [rw] image_status
# The status of the image.
# @return [String]
#
# @!attribute [rw] last_modified_time
# When the image was last modified.
# @return [Time]
#
# @!attribute [rw] role_arn
# The ARN of the IAM role that enables Amazon SageMaker to perform
# tasks on your behalf.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeImageResponse AWS API Documentation
#
class DescribeImageResponse < Struct.new(
:creation_time,
:description,
:display_name,
:failure_reason,
:image_arn,
:image_name,
:image_status,
:last_modified_time,
:role_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_name
# The name of the image.
# @return [String]
#
# @!attribute [rw] version
# The version of the image. If not specified, the latest version is
# described.
# @return [Integer]
#
# @!attribute [rw] alias
# The alias of the image version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeImageVersionRequest AWS API Documentation
#
class DescribeImageVersionRequest < Struct.new(
:image_name,
:version,
:alias)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] base_image
# The registry path of the container image on which this image version
# is based.
# @return [String]
#
# @!attribute [rw] container_image
# The registry path of the container image that contains this image
# version.
# @return [String]
#
# @!attribute [rw] creation_time
# When the version was created.
# @return [Time]
#
# @!attribute [rw] failure_reason
# When a create or delete operation fails, the reason for the failure.
# @return [String]
#
# @!attribute [rw] image_arn
# The ARN of the image the version is based on.
# @return [String]
#
# @!attribute [rw] image_version_arn
# The ARN of the version.
# @return [String]
#
# @!attribute [rw] image_version_status
# The status of the version.
# @return [String]
#
# @!attribute [rw] last_modified_time
# When the version was last modified.
# @return [Time]
#
# @!attribute [rw] version
# The version number.
# @return [Integer]
#
# @!attribute [rw] vendor_guidance
# The stability of the image version specified by the maintainer.
#
# * `NOT_PROVIDED`: The maintainers did not provide a status for image
# version stability.
#
# * `STABLE`: The image version is stable.
#
# * `TO_BE_ARCHIVED`: The image version is set to be archived. Custom
# image versions that are set to be archived are automatically
# archived after three months.
#
# * `ARCHIVED`: The image version is archived. Archived image versions
# are not searchable and are no longer actively supported.
# @return [String]
#
# @!attribute [rw] job_type
# Indicates SageMaker job type compatibility.
#
# * `TRAINING`: The image version is compatible with SageMaker
# training jobs.
#
# * `INFERENCE`: The image version is compatible with SageMaker
# inference jobs.
#
# * `NOTEBOOK_KERNEL`: The image version is compatible with SageMaker
# notebook kernels.
# @return [String]
#
# @!attribute [rw] ml_framework
# The machine learning framework vended in the image version.
# @return [String]
#
# @!attribute [rw] programming_lang
# The supported programming language and its version.
# @return [String]
#
# @!attribute [rw] processor
# Indicates CPU or GPU compatibility.
#
# * `CPU`: The image version is compatible with CPU.
#
# * `GPU`: The image version is compatible with GPU.
# @return [String]
#
# @!attribute [rw] horovod
# Indicates Horovod compatibility.
# @return [Boolean]
#
# @!attribute [rw] release_notes
# The maintainer description of the image version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeImageVersionResponse AWS API Documentation
#
class DescribeImageVersionResponse < Struct.new(
:base_image,
:container_image,
:creation_time,
:failure_reason,
:image_arn,
:image_version_arn,
:image_version_status,
:last_modified_time,
:version,
:vendor_guidance,
:job_type,
:ml_framework,
:programming_lang,
:processor,
:horovod,
:release_notes)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name
# The name of the inference experiment to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeInferenceExperimentRequest AWS API Documentation
#
class DescribeInferenceExperimentRequest < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] arn
# The ARN of the inference experiment being described.
# @return [String]
#
# @!attribute [rw] name
# The name of the inference experiment.
# @return [String]
#
# @!attribute [rw] type
# The type of the inference experiment.
# @return [String]
#
# @!attribute [rw] schedule
# The duration for which the inference experiment ran or will run.
# @return [Types::InferenceExperimentSchedule]
#
# @!attribute [rw] status
# The status of the inference experiment. The following are the
# possible statuses for an inference experiment:
#
# * `Creating` - Amazon SageMaker is creating your experiment.
#
# * `Created` - Amazon SageMaker has finished the creation of your
# experiment and will begin the experiment at the scheduled time.
#
# * `Updating` - When you make changes to your experiment, your
# experiment shows as updating.
#
# * `Starting` - Amazon SageMaker is beginning your experiment.
#
# * `Running` - Your experiment is in progress.
#
# * `Stopping` - Amazon SageMaker is stopping your experiment.
#
# * `Completed` - Your experiment has completed.
#
# * `Cancelled` - When you conclude your experiment early using the
# [StopInferenceExperiment][1] API, or if any operation fails with
# an unexpected error, it shows as cancelled.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_StopInferenceExperiment.html
# @return [String]
#
# @!attribute [rw] status_reason
# The error message or client-specified `Reason` from the
# [StopInferenceExperiment][1] API, that explains the status of the
# inference experiment.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_StopInferenceExperiment.html
# @return [String]
#
# @!attribute [rw] description
# The description of the inference experiment.
# @return [String]
#
# @!attribute [rw] creation_time
# The timestamp at which you created the inference experiment.
# @return [Time]
#
# @!attribute [rw] completion_time
# The timestamp at which the inference experiment was completed.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The timestamp at which you last modified the inference experiment.
# @return [Time]
#
# @!attribute [rw] role_arn
# The ARN of the IAM role that Amazon SageMaker can assume to access
# model artifacts and container images, and manage Amazon SageMaker
# Inference endpoints for model deployment.
# @return [String]
#
# @!attribute [rw] endpoint_metadata
# The metadata of the endpoint on which the inference experiment ran.
# @return [Types::EndpointMetadata]
#
# @!attribute [rw] model_variants
# An array of `ModelVariantConfigSummary` objects. There is one for
# each variant in the inference experiment. Each
# `ModelVariantConfigSummary` object in the array describes the
# infrastructure configuration for deploying the corresponding
# variant.
# @return [Array<Types::ModelVariantConfigSummary>]
#
# @!attribute [rw] data_storage_config
# The Amazon S3 location and configuration for storing inference
# request and response data.
# @return [Types::InferenceExperimentDataStorageConfig]
#
# @!attribute [rw] shadow_mode_config
# The configuration of `ShadowMode` inference experiment type, which
# shows the production variant that takes all the inference requests,
# and the shadow variant to which Amazon SageMaker replicates a
# percentage of the inference requests. For the shadow variant it also
# shows the percentage of requests that Amazon SageMaker replicates.
# @return [Types::ShadowModeConfig]
#
# @!attribute [rw] kms_key
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt data on the storage
# volume attached to the ML compute instance that hosts the endpoint.
# For more information, see [CreateInferenceExperiment][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceExperiment.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeInferenceExperimentResponse AWS API Documentation
#
class DescribeInferenceExperimentResponse < Struct.new(
:arn,
:name,
:type,
:schedule,
:status,
:status_reason,
:description,
:creation_time,
:completion_time,
:last_modified_time,
:role_arn,
:endpoint_metadata,
:model_variants,
:data_storage_config,
:shadow_mode_config,
:kms_key)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_name
# The name of the job. The name must be unique within an Amazon Web
# Services Region in the Amazon Web Services account.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeInferenceRecommendationsJobRequest AWS API Documentation
#
class DescribeInferenceRecommendationsJobRequest < Struct.new(
:job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_name
# The name of the job. The name must be unique within an Amazon Web
# Services Region in the Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] job_description
# The job description that you provided when you initiated the job.
# @return [String]
#
# @!attribute [rw] job_type
# The job type that you provided when you initiated the job.
# @return [String]
#
# @!attribute [rw] job_arn
# The Amazon Resource Name (ARN) of the job.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the Amazon Web Services Identity
# and Access Management (IAM) role you provided when you initiated the
# job.
# @return [String]
#
# @!attribute [rw] status
# The status of the job.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the job was created.
# @return [Time]
#
# @!attribute [rw] completion_time
# A timestamp that shows when the job completed.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that shows when the job was last modified.
# @return [Time]
#
# @!attribute [rw] failure_reason
# If the job fails, provides information why the job failed.
# @return [String]
#
# @!attribute [rw] input_config
# Returns information about the versioned model package Amazon
# Resource Name (ARN), the traffic pattern, and endpoint
# configurations you provided when you initiated the job.
# @return [Types::RecommendationJobInputConfig]
#
# @!attribute [rw] stopping_conditions
# The stopping conditions that you provided when you initiated the
# job.
# @return [Types::RecommendationJobStoppingConditions]
#
# @!attribute [rw] inference_recommendations
# The recommendations made by Inference Recommender.
# @return [Array<Types::InferenceRecommendation>]
#
# @!attribute [rw] endpoint_performances
# The performance results from running an Inference Recommender job on
# an existing endpoint.
# @return [Array<Types::EndpointPerformance>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeInferenceRecommendationsJobResponse AWS API Documentation
#
class DescribeInferenceRecommendationsJobResponse < Struct.new(
:job_name,
:job_description,
:job_type,
:job_arn,
:role_arn,
:status,
:creation_time,
:completion_time,
:last_modified_time,
:failure_reason,
:input_config,
:stopping_conditions,
:inference_recommendations,
:endpoint_performances)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] labeling_job_name
# The name of the labeling job to return information for.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeLabelingJobRequest AWS API Documentation
#
class DescribeLabelingJobRequest < Struct.new(
:labeling_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] labeling_job_status
# The processing status of the labeling job.
# @return [String]
#
# @!attribute [rw] label_counters
# Provides a breakdown of the number of data objects labeled by
# humans, the number of objects labeled by machine, the number of
# objects than couldn't be labeled, and the total number of objects
# labeled.
# @return [Types::LabelCounters]
#
# @!attribute [rw] failure_reason
# If the job failed, the reason that it failed.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the labeling job was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the labeling job was last updated.
# @return [Time]
#
# @!attribute [rw] job_reference_code
# A unique identifier for work done as part of a labeling job.
# @return [String]
#
# @!attribute [rw] labeling_job_name
# The name assigned to the labeling job when it was created.
# @return [String]
#
# @!attribute [rw] labeling_job_arn
# The Amazon Resource Name (ARN) of the labeling job.
# @return [String]
#
# @!attribute [rw] label_attribute_name
# The attribute used as the label in the output manifest file.
# @return [String]
#
# @!attribute [rw] input_config
# Input configuration information for the labeling job, such as the
# Amazon S3 location of the data objects and the location of the
# manifest file that describes the data objects.
# @return [Types::LabelingJobInputConfig]
#
# @!attribute [rw] output_config
# The location of the job's output data and the Amazon Web Services
# Key Management Service key ID for the key used to encrypt the output
# data, if any.
# @return [Types::LabelingJobOutputConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) that SageMaker assumes to perform
# tasks on your behalf during data labeling.
# @return [String]
#
# @!attribute [rw] label_category_config_s3_uri
# The S3 location of the JSON file that defines the categories used to
# label data objects. Please note the following label-category limits:
#
# * Semantic segmentation labeling jobs using automated labeling: 20
# labels
#
# * Box bounding labeling jobs (all): 10 labels
#
# The file is a JSON structure in the following format:
#
# `\{`
#
# ` "document-version": "2018-11-28"`
#
# ` "labels": [`
#
# ` \{`
#
# ` "label": "label 1"`
#
# ` \},`
#
# ` \{`
#
# ` "label": "label 2"`
#
# ` \},`
#
# ` ...`
#
# ` \{`
#
# ` "label": "label n"`
#
# ` \}`
#
# ` ]`
#
# `\}`
# @return [String]
#
# @!attribute [rw] stopping_conditions
# A set of conditions for stopping a labeling job. If any of the
# conditions are met, the job is automatically stopped.
# @return [Types::LabelingJobStoppingConditions]
#
# @!attribute [rw] labeling_job_algorithms_config
# Configuration information for automated data labeling.
# @return [Types::LabelingJobAlgorithmsConfig]
#
# @!attribute [rw] human_task_config
# Configuration information required for human workers to complete a
# labeling task.
# @return [Types::HumanTaskConfig]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] labeling_job_output
# The location of the output produced by the labeling job.
# @return [Types::LabelingJobOutput]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeLabelingJobResponse AWS API Documentation
#
class DescribeLabelingJobResponse < Struct.new(
:labeling_job_status,
:label_counters,
:failure_reason,
:creation_time,
:last_modified_time,
:job_reference_code,
:labeling_job_name,
:labeling_job_arn,
:label_attribute_name,
:input_config,
:output_config,
:role_arn,
:label_category_config_s3_uri,
:stopping_conditions,
:labeling_job_algorithms_config,
:human_task_config,
:tags,
:labeling_job_output)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] lineage_group_name
# The name of the lineage group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeLineageGroupRequest AWS API Documentation
#
class DescribeLineageGroupRequest < Struct.new(
:lineage_group_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] lineage_group_name
# The name of the lineage group.
# @return [String]
#
# @!attribute [rw] lineage_group_arn
# The Amazon Resource Name (ARN) of the lineage group.
# @return [String]
#
# @!attribute [rw] display_name
# The display name of the lineage group.
# @return [String]
#
# @!attribute [rw] description
# The description of the lineage group.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of lineage group.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# The last modified time of the lineage group.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeLineageGroupResponse AWS API Documentation
#
class DescribeLineageGroupResponse < Struct.new(
:lineage_group_name,
:lineage_group_arn,
:display_name,
:description,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the model bias job definition. The name must be unique
# within an Amazon Web Services Region in the Amazon Web Services
# account.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelBiasJobDefinitionRequest AWS API Documentation
#
class DescribeModelBiasJobDefinitionRequest < Struct.new(
:job_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_arn
# The Amazon Resource Name (ARN) of the model bias job.
# @return [String]
#
# @!attribute [rw] job_definition_name
# The name of the bias job definition. The name must be unique within
# an Amazon Web Services Region in the Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] creation_time
# The time at which the model bias job was created.
# @return [Time]
#
# @!attribute [rw] model_bias_baseline_config
# The baseline configuration for a model bias job.
# @return [Types::ModelBiasBaselineConfig]
#
# @!attribute [rw] model_bias_app_specification
# Configures the model bias job to run a specified Docker container
# image.
# @return [Types::ModelBiasAppSpecification]
#
# @!attribute [rw] model_bias_job_input
# Inputs for the model bias job.
# @return [Types::ModelBiasJobInput]
#
# @!attribute [rw] model_bias_job_output_config
# The output configuration for monitoring jobs.
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] job_resources
# Identifies the resources to deploy for a monitoring job.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] network_config
# Networking options for a model bias job.
# @return [Types::MonitoringNetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the Amazon Web Services Identity
# and Access Management (IAM) role that has read permission to the
# input data location and write permission to the output data location
# in Amazon S3.
# @return [String]
#
# @!attribute [rw] stopping_condition
# A time limit for how long the monitoring job is allowed to run
# before stopping.
# @return [Types::MonitoringStoppingCondition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelBiasJobDefinitionResponse AWS API Documentation
#
class DescribeModelBiasJobDefinitionResponse < Struct.new(
:job_definition_arn,
:job_definition_name,
:creation_time,
:model_bias_baseline_config,
:model_bias_app_specification,
:model_bias_job_input,
:model_bias_job_output_config,
:job_resources,
:network_config,
:role_arn,
:stopping_condition)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_export_job_arn
# The Amazon Resource Name (ARN) of the model card export job to
# describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelCardExportJobRequest AWS API Documentation
#
class DescribeModelCardExportJobRequest < Struct.new(
:model_card_export_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_export_job_name
# The name of the model card export job to describe.
# @return [String]
#
# @!attribute [rw] model_card_export_job_arn
# The Amazon Resource Name (ARN) of the model card export job.
# @return [String]
#
# @!attribute [rw] status
# The completion status of the model card export job.
#
# * `InProgress`: The model card export job is in progress.
#
# * `Completed`: The model card export job is complete.
#
# * `Failed`: The model card export job failed. To see the reason for
# the failure, see the `FailureReason` field in the response to a
# `DescribeModelCardExportJob` call.
# @return [String]
#
# @!attribute [rw] model_card_name
# The name of the model card that the model export job exports.
# @return [String]
#
# @!attribute [rw] model_card_version
# The version of the model card that the model export job exports.
# @return [Integer]
#
# @!attribute [rw] output_config
# The export output details for the model card.
# @return [Types::ModelCardExportOutputConfig]
#
# @!attribute [rw] created_at
# The date and time that the model export job was created.
# @return [Time]
#
# @!attribute [rw] last_modified_at
# The date and time that the model export job was last modified.
# @return [Time]
#
# @!attribute [rw] failure_reason
# The failure reason if the model export job fails.
# @return [String]
#
# @!attribute [rw] export_artifacts
# The exported model card artifacts.
# @return [Types::ModelCardExportArtifacts]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelCardExportJobResponse AWS API Documentation
#
class DescribeModelCardExportJobResponse < Struct.new(
:model_card_export_job_name,
:model_card_export_job_arn,
:status,
:model_card_name,
:model_card_version,
:output_config,
:created_at,
:last_modified_at,
:failure_reason,
:export_artifacts)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_name
# The name of the model card to describe.
# @return [String]
#
# @!attribute [rw] model_card_version
# The version of the model card to describe. If a version is not
# provided, then the latest version of the model card is described.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelCardRequest AWS API Documentation
#
class DescribeModelCardRequest < Struct.new(
:model_card_name,
:model_card_version)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_arn
# The Amazon Resource Name (ARN) of the model card.
# @return [String]
#
# @!attribute [rw] model_card_name
# The name of the model card.
# @return [String]
#
# @!attribute [rw] model_card_version
# The version of the model card.
# @return [Integer]
#
# @!attribute [rw] content
# The content of the model card.
# @return [String]
#
# @!attribute [rw] model_card_status
# The approval status of the model card within your organization.
# Different organizations might have different criteria for model card
# review and approval.
#
# * `Draft`: The model card is a work in progress.
#
# * `PendingReview`: The model card is pending review.
#
# * `Approved`: The model card is approved.
#
# * `Archived`: The model card is archived. No more updates should be
# made to the model card, but it can still be exported.
# @return [String]
#
# @!attribute [rw] security_config
# The security configuration used to protect model card content.
# @return [Types::ModelCardSecurityConfig]
#
# @!attribute [rw] creation_time
# The date and time the model card was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# The date and time the model card was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] model_card_processing_status
# The processing status of model card deletion. The
# `ModelCardProcessingStatus` updates throughout the different
# deletion steps.
#
# * `DeletePending`: Model card deletion request received.
#
# * `DeleteInProgress`: Model card deletion is in progress.
#
# * `ContentDeleted`: Deleted model card content.
#
# * `ExportJobsDeleted`: Deleted all export jobs associated with the
# model card.
#
# * `DeleteCompleted`: Successfully deleted the model card.
#
# * `DeleteFailed`: The model card failed to delete.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelCardResponse AWS API Documentation
#
class DescribeModelCardResponse < Struct.new(
:model_card_arn,
:model_card_name,
:model_card_version,
:content,
:model_card_status,
:security_config,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:model_card_processing_status)
SENSITIVE = [:content]
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the model explainability job definition. The name must
# be unique within an Amazon Web Services Region in the Amazon Web
# Services account.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelExplainabilityJobDefinitionRequest AWS API Documentation
#
class DescribeModelExplainabilityJobDefinitionRequest < Struct.new(
:job_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_arn
# The Amazon Resource Name (ARN) of the model explainability job.
# @return [String]
#
# @!attribute [rw] job_definition_name
# The name of the explainability job definition. The name must be
# unique within an Amazon Web Services Region in the Amazon Web
# Services account.
# @return [String]
#
# @!attribute [rw] creation_time
# The time at which the model explainability job was created.
# @return [Time]
#
# @!attribute [rw] model_explainability_baseline_config
# The baseline configuration for a model explainability job.
# @return [Types::ModelExplainabilityBaselineConfig]
#
# @!attribute [rw] model_explainability_app_specification
# Configures the model explainability job to run a specified Docker
# container image.
# @return [Types::ModelExplainabilityAppSpecification]
#
# @!attribute [rw] model_explainability_job_input
# Inputs for the model explainability job.
# @return [Types::ModelExplainabilityJobInput]
#
# @!attribute [rw] model_explainability_job_output_config
# The output configuration for monitoring jobs.
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] job_resources
# Identifies the resources to deploy for a monitoring job.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] network_config
# Networking options for a model explainability job.
# @return [Types::MonitoringNetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the Amazon Web Services Identity
# and Access Management (IAM) role that has read permission to the
# input data location and write permission to the output data location
# in Amazon S3.
# @return [String]
#
# @!attribute [rw] stopping_condition
# A time limit for how long the monitoring job is allowed to run
# before stopping.
# @return [Types::MonitoringStoppingCondition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelExplainabilityJobDefinitionResponse AWS API Documentation
#
class DescribeModelExplainabilityJobDefinitionResponse < Struct.new(
:job_definition_arn,
:job_definition_name,
:creation_time,
:model_explainability_baseline_config,
:model_explainability_app_specification,
:model_explainability_job_input,
:model_explainability_job_output_config,
:job_resources,
:network_config,
:role_arn,
:stopping_condition)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_name
# The name of the model.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelInput AWS API Documentation
#
class DescribeModelInput < Struct.new(
:model_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_name
# Name of the SageMaker model.
# @return [String]
#
# @!attribute [rw] primary_container
# The location of the primary inference code, associated artifacts,
# and custom environment map that the inference code uses when it is
# deployed in production.
# @return [Types::ContainerDefinition]
#
# @!attribute [rw] containers
# The containers in the inference pipeline.
# @return [Array<Types::ContainerDefinition>]
#
# @!attribute [rw] inference_execution_config
# Specifies details of how containers in a multi-container endpoint
# are called.
# @return [Types::InferenceExecutionConfig]
#
# @!attribute [rw] execution_role_arn
# The Amazon Resource Name (ARN) of the IAM role that you specified
# for the model.
# @return [String]
#
# @!attribute [rw] vpc_config
# A [VpcConfig][1] object that specifies the VPC that this model has
# access to. For more information, see [Protect Endpoints by Using an
# Amazon Virtual Private Cloud][2]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html
# @return [Types::VpcConfig]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the model was created.
# @return [Time]
#
# @!attribute [rw] model_arn
# The Amazon Resource Name (ARN) of the model.
# @return [String]
#
# @!attribute [rw] enable_network_isolation
# If `True`, no inbound or outbound network calls can be made to or
# from the model container.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelOutput AWS API Documentation
#
class DescribeModelOutput < Struct.new(
:model_name,
:primary_container,
:containers,
:inference_execution_config,
:execution_role_arn,
:vpc_config,
:creation_time,
:model_arn,
:enable_network_isolation)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_name
# The name of gthe model group to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelPackageGroupInput AWS API Documentation
#
class DescribeModelPackageGroupInput < Struct.new(
:model_package_group_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_name
# The name of the model group.
# @return [String]
#
# @!attribute [rw] model_package_group_arn
# The Amazon Resource Name (ARN) of the model group.
# @return [String]
#
# @!attribute [rw] model_package_group_description
# A description of the model group.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the model group was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] model_package_group_status
# The status of the model group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelPackageGroupOutput AWS API Documentation
#
class DescribeModelPackageGroupOutput < Struct.new(
:model_package_group_name,
:model_package_group_arn,
:model_package_group_description,
:creation_time,
:created_by,
:model_package_group_status)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_name
# The name or Amazon Resource Name (ARN) of the model package to
# describe.
#
# When you specify a name, the name must have 1 to 63 characters.
# Valid characters are a-z, A-Z, 0-9, and - (hyphen).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelPackageInput AWS API Documentation
#
class DescribeModelPackageInput < Struct.new(
:model_package_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_name
# The name of the model package being described.
# @return [String]
#
# @!attribute [rw] model_package_group_name
# If the model is a versioned model, the name of the model group that
# the versioned model belongs to.
# @return [String]
#
# @!attribute [rw] model_package_version
# The version of the model package.
# @return [Integer]
#
# @!attribute [rw] model_package_arn
# The Amazon Resource Name (ARN) of the model package.
# @return [String]
#
# @!attribute [rw] model_package_description
# A brief summary of the model package.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp specifying when the model package was created.
# @return [Time]
#
# @!attribute [rw] inference_specification
# Details about inference jobs that can be run with models based on
# this model package.
# @return [Types::InferenceSpecification]
#
# @!attribute [rw] source_algorithm_specification
# Details about the algorithm that was used to create the model
# package.
# @return [Types::SourceAlgorithmSpecification]
#
# @!attribute [rw] validation_specification
# Configurations for one or more transform jobs that SageMaker runs to
# test the model package.
# @return [Types::ModelPackageValidationSpecification]
#
# @!attribute [rw] model_package_status
# The current status of the model package.
# @return [String]
#
# @!attribute [rw] model_package_status_details
# Details about the current status of the model package.
# @return [Types::ModelPackageStatusDetails]
#
# @!attribute [rw] certify_for_marketplace
# Whether the model package is certified for listing on Amazon Web
# Services Marketplace.
# @return [Boolean]
#
# @!attribute [rw] model_approval_status
# The approval status of the model package.
# @return [String]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] model_metrics
# Metrics for the model.
# @return [Types::ModelMetrics]
#
# @!attribute [rw] last_modified_time
# The last time that the model package was modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] approval_description
# A description provided for the model approval.
# @return [String]
#
# @!attribute [rw] customer_metadata_properties
# The metadata properties associated with the model package versions.
# @return [Hash<String,String>]
#
# @!attribute [rw] drift_check_baselines
# Represents the drift check baselines that can be used when the model
# monitor is set using the model package. For more information, see
# the topic on [Drift Detection against Previous Baselines in
# SageMaker Pipelines][1] in the *Amazon SageMaker Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-quality-clarify-baseline-lifecycle.html#pipelines-quality-clarify-baseline-drift-detection
# @return [Types::DriftCheckBaselines]
#
# @!attribute [rw] domain
# The machine learning domain of the model package you specified.
# Common machine learning domains include computer vision and natural
# language processing.
# @return [String]
#
# @!attribute [rw] task
# The machine learning task you specified that your model package
# accomplishes. Common machine learning tasks include object detection
# and image classification.
# @return [String]
#
# @!attribute [rw] sample_payload_url
# The Amazon Simple Storage Service (Amazon S3) path where the sample
# payload are stored. This path points to a single gzip compressed tar
# archive (.tar.gz suffix).
# @return [String]
#
# @!attribute [rw] additional_inference_specifications
# An array of additional Inference Specification objects. Each
# additional Inference Specification specifies artifacts based on this
# model package that can be used on inference endpoints. Generally
# used with SageMaker Neo to store the compiled artifacts.
# @return [Array<Types::AdditionalInferenceSpecificationDefinition>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelPackageOutput AWS API Documentation
#
class DescribeModelPackageOutput < Struct.new(
:model_package_name,
:model_package_group_name,
:model_package_version,
:model_package_arn,
:model_package_description,
:creation_time,
:inference_specification,
:source_algorithm_specification,
:validation_specification,
:model_package_status,
:model_package_status_details,
:certify_for_marketplace,
:model_approval_status,
:created_by,
:metadata_properties,
:model_metrics,
:last_modified_time,
:last_modified_by,
:approval_description,
:customer_metadata_properties,
:drift_check_baselines,
:domain,
:task,
:sample_payload_url,
:additional_inference_specifications)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_name
# The name of the model quality job. The name must be unique within an
# Amazon Web Services Region in the Amazon Web Services account.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelQualityJobDefinitionRequest AWS API Documentation
#
class DescribeModelQualityJobDefinitionRequest < Struct.new(
:job_definition_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_arn
# The Amazon Resource Name (ARN) of the model quality job.
# @return [String]
#
# @!attribute [rw] job_definition_name
# The name of the quality job definition. The name must be unique
# within an Amazon Web Services Region in the Amazon Web Services
# account.
# @return [String]
#
# @!attribute [rw] creation_time
# The time at which the model quality job was created.
# @return [Time]
#
# @!attribute [rw] model_quality_baseline_config
# The baseline configuration for a model quality job.
# @return [Types::ModelQualityBaselineConfig]
#
# @!attribute [rw] model_quality_app_specification
# Configures the model quality job to run a specified Docker container
# image.
# @return [Types::ModelQualityAppSpecification]
#
# @!attribute [rw] model_quality_job_input
# Inputs for the model quality job.
# @return [Types::ModelQualityJobInput]
#
# @!attribute [rw] model_quality_job_output_config
# The output configuration for monitoring jobs.
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] job_resources
# Identifies the resources to deploy for a monitoring job.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] network_config
# Networking options for a model quality job.
# @return [Types::MonitoringNetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] stopping_condition
# A time limit for how long the monitoring job is allowed to run
# before stopping.
# @return [Types::MonitoringStoppingCondition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelQualityJobDefinitionResponse AWS API Documentation
#
class DescribeModelQualityJobDefinitionResponse < Struct.new(
:job_definition_arn,
:job_definition_name,
:creation_time,
:model_quality_baseline_config,
:model_quality_app_specification,
:model_quality_job_input,
:model_quality_job_output_config,
:job_resources,
:network_config,
:role_arn,
:stopping_condition)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# Name of a previously created monitoring schedule.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeMonitoringScheduleRequest AWS API Documentation
#
class DescribeMonitoringScheduleRequest < Struct.new(
:monitoring_schedule_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_arn
# The Amazon Resource Name (ARN) of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_name
# Name of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_status
# The status of an monitoring job.
# @return [String]
#
# @!attribute [rw] monitoring_type
# The type of the monitoring job that this schedule runs. This is one
# of the following values.
#
# * `DATA_QUALITY` - The schedule is for a data quality monitoring
# job.
#
# * `MODEL_QUALITY` - The schedule is for a model quality monitoring
# job.
#
# * `MODEL_BIAS` - The schedule is for a bias monitoring job.
#
# * `MODEL_EXPLAINABILITY` - The schedule is for an explainability
# monitoring job.
# @return [String]
#
# @!attribute [rw] failure_reason
# A string, up to one KB in size, that contains the reason a
# monitoring job failed, if it failed.
# @return [String]
#
# @!attribute [rw] creation_time
# The time at which the monitoring job was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time at which the monitoring job was last modified.
# @return [Time]
#
# @!attribute [rw] monitoring_schedule_config
# The configuration object that specifies the monitoring schedule and
# defines the monitoring job.
# @return [Types::MonitoringScheduleConfig]
#
# @!attribute [rw] endpoint_name
# The name of the endpoint for the monitoring job.
# @return [String]
#
# @!attribute [rw] last_monitoring_execution_summary
# Describes metadata on the last execution to run, if there was one.
# @return [Types::MonitoringExecutionSummary]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeMonitoringScheduleResponse AWS API Documentation
#
class DescribeMonitoringScheduleResponse < Struct.new(
:monitoring_schedule_arn,
:monitoring_schedule_name,
:monitoring_schedule_status,
:monitoring_type,
:failure_reason,
:creation_time,
:last_modified_time,
:monitoring_schedule_config,
:endpoint_name,
:last_monitoring_execution_summary)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_name
# The name of the notebook instance that you want information about.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstanceInput AWS API Documentation
#
class DescribeNotebookInstanceInput < Struct.new(
:notebook_instance_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_lifecycle_config_name
# The name of the lifecycle configuration to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstanceLifecycleConfigInput AWS API Documentation
#
class DescribeNotebookInstanceLifecycleConfigInput < Struct.new(
:notebook_instance_lifecycle_config_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_lifecycle_config_arn
# The Amazon Resource Name (ARN) of the lifecycle configuration.
# @return [String]
#
# @!attribute [rw] notebook_instance_lifecycle_config_name
# The name of the lifecycle configuration.
# @return [String]
#
# @!attribute [rw] on_create
# The shell script that runs only once, when you create a notebook
# instance.
# @return [Array<Types::NotebookInstanceLifecycleHook>]
#
# @!attribute [rw] on_start
# The shell script that runs every time you start a notebook instance,
# including when you create the notebook instance.
# @return [Array<Types::NotebookInstanceLifecycleHook>]
#
# @!attribute [rw] last_modified_time
# A timestamp that tells when the lifecycle configuration was last
# modified.
# @return [Time]
#
# @!attribute [rw] creation_time
# A timestamp that tells when the lifecycle configuration was created.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstanceLifecycleConfigOutput AWS API Documentation
#
class DescribeNotebookInstanceLifecycleConfigOutput < Struct.new(
:notebook_instance_lifecycle_config_arn,
:notebook_instance_lifecycle_config_name,
:on_create,
:on_start,
:last_modified_time,
:creation_time)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_arn
# The Amazon Resource Name (ARN) of the notebook instance.
# @return [String]
#
# @!attribute [rw] notebook_instance_name
# The name of the SageMaker notebook instance.
# @return [String]
#
# @!attribute [rw] notebook_instance_status
# The status of the notebook instance.
# @return [String]
#
# @!attribute [rw] failure_reason
# If status is `Failed`, the reason it failed.
# @return [String]
#
# @!attribute [rw] url
# The URL that you use to connect to the Jupyter notebook that is
# running in your notebook instance.
# @return [String]
#
# @!attribute [rw] instance_type
# The type of ML compute instance running on the notebook instance.
# @return [String]
#
# @!attribute [rw] subnet_id
# The ID of the VPC subnet.
# @return [String]
#
# @!attribute [rw] security_groups
# The IDs of the VPC security groups.
# @return [Array<String>]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the IAM role associated with the
# instance.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services KMS key ID SageMaker uses to encrypt data
# when storing it on the ML storage volume attached to the instance.
# @return [String]
#
# @!attribute [rw] network_interface_id
# The network interface IDs that SageMaker created at the time of
# creating the instance.
# @return [String]
#
# @!attribute [rw] last_modified_time
# A timestamp. Use this parameter to retrieve the time when the
# notebook instance was last modified.
# @return [Time]
#
# @!attribute [rw] creation_time
# A timestamp. Use this parameter to return the time when the notebook
# instance was created
# @return [Time]
#
# @!attribute [rw] notebook_instance_lifecycle_config_name
# Returns the name of a notebook instance lifecycle configuration.
#
# For information about notebook instance lifestyle configurations,
# see [Step 2.1: (Optional) Customize a Notebook Instance][1]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html
# @return [String]
#
# @!attribute [rw] direct_internet_access
# Describes whether SageMaker provides internet access to the notebook
# instance. If this value is set to *Disabled*, the notebook instance
# does not have internet access, and cannot connect to SageMaker
# training and endpoint services.
#
# For more information, see [Notebook Instances Are Internet-Enabled
# by Default][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access
# @return [String]
#
# @!attribute [rw] volume_size_in_gb
# The size, in GB, of the ML storage volume attached to the notebook
# instance.
# @return [Integer]
#
# @!attribute [rw] accelerator_types
# A list of the Elastic Inference (EI) instance types associated with
# this notebook instance. Currently only one EI instance type can be
# associated with a notebook instance. For more information, see
# [Using Elastic Inference in Amazon SageMaker][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
# @return [Array<String>]
#
# @!attribute [rw] default_code_repository
# The Git repository associated with the notebook instance as its
# default code repository. This can be either the name of a Git
# repository stored as a resource in your account, or the URL of a Git
# repository in [Amazon Web Services CodeCommit][1] or in any other
# Git repository. When you open a notebook instance, it opens in the
# directory that contains this repository. For more information, see
# [Associating Git Repositories with SageMaker Notebook Instances][2].
#
#
#
# [1]: https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html
# @return [String]
#
# @!attribute [rw] additional_code_repositories
# An array of up to three Git repositories associated with the
# notebook instance. These can be either the names of Git repositories
# stored as resources in your account, or the URL of Git repositories
# in [Amazon Web Services CodeCommit][1] or in any other Git
# repository. These repositories are cloned at the same level as the
# default repository of your notebook instance. For more information,
# see [Associating Git Repositories with SageMaker Notebook
# Instances][2].
#
#
#
# [1]: https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html
# @return [Array<String>]
#
# @!attribute [rw] root_access
# Whether root access is enabled or disabled for users of the notebook
# instance.
#
# <note markdown="1"> Lifecycle configurations need root access to be able to set up a
# notebook instance. Because of this, lifecycle configurations
# associated with a notebook instance always run with root access even
# if you disable root access for users.
#
# </note>
# @return [String]
#
# @!attribute [rw] platform_identifier
# The platform identifier of the notebook instance runtime
# environment.
# @return [String]
#
# @!attribute [rw] instance_metadata_service_configuration
# Information on the IMDS configuration of the notebook instance
# @return [Types::InstanceMetadataServiceConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeNotebookInstanceOutput AWS API Documentation
#
class DescribeNotebookInstanceOutput < Struct.new(
:notebook_instance_arn,
:notebook_instance_name,
:notebook_instance_status,
:failure_reason,
:url,
:instance_type,
:subnet_id,
:security_groups,
:role_arn,
:kms_key_id,
:network_interface_id,
:last_modified_time,
:creation_time,
:notebook_instance_lifecycle_config_name,
:direct_internet_access,
:volume_size_in_gb,
:accelerator_types,
:default_code_repository,
:additional_code_repositories,
:root_access,
:platform_identifier,
:instance_metadata_service_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribePipelineDefinitionForExecutionRequest AWS API Documentation
#
class DescribePipelineDefinitionForExecutionRequest < Struct.new(
:pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_definition
# The JSON pipeline definition.
# @return [String]
#
# @!attribute [rw] creation_time
# The time when the pipeline was created.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribePipelineDefinitionForExecutionResponse AWS API Documentation
#
class DescribePipelineDefinitionForExecutionResponse < Struct.new(
:pipeline_definition,
:creation_time)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribePipelineExecutionRequest AWS API Documentation
#
class DescribePipelineExecutionRequest < Struct.new(
:pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_arn
# The Amazon Resource Name (ARN) of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_display_name
# The display name of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_status
# The status of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_description
# The description of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_experiment_config
# Specifies the names of the experiment and trial created by a
# pipeline.
# @return [Types::PipelineExperimentConfig]
#
# @!attribute [rw] failure_reason
# If the execution failed, a message describing why.
# @return [String]
#
# @!attribute [rw] creation_time
# The time when the pipeline execution was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time when the pipeline execution was modified last.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] parallelism_configuration
# The parallelism configuration applied to the pipeline.
# @return [Types::ParallelismConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribePipelineExecutionResponse AWS API Documentation
#
class DescribePipelineExecutionResponse < Struct.new(
:pipeline_arn,
:pipeline_execution_arn,
:pipeline_execution_display_name,
:pipeline_execution_status,
:pipeline_execution_description,
:pipeline_experiment_config,
:failure_reason,
:creation_time,
:last_modified_time,
:created_by,
:last_modified_by,
:parallelism_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_name
# The name of the pipeline to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribePipelineRequest AWS API Documentation
#
class DescribePipelineRequest < Struct.new(
:pipeline_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_arn
# The Amazon Resource Name (ARN) of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_name
# The name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_display_name
# The display name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_definition
# The JSON pipeline definition.
# @return [String]
#
# @!attribute [rw] pipeline_description
# The description of the pipeline.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) that the pipeline uses to execute.
# @return [String]
#
# @!attribute [rw] pipeline_status
# The status of the pipeline execution.
# @return [String]
#
# @!attribute [rw] creation_time
# The time when the pipeline was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time when the pipeline was last modified.
# @return [Time]
#
# @!attribute [rw] last_run_time
# The time when the pipeline was last run.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] parallelism_configuration
# Lists the parallelism configuration applied to the pipeline.
# @return [Types::ParallelismConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribePipelineResponse AWS API Documentation
#
class DescribePipelineResponse < Struct.new(
:pipeline_arn,
:pipeline_name,
:pipeline_display_name,
:pipeline_definition,
:pipeline_description,
:role_arn,
:pipeline_status,
:creation_time,
:last_modified_time,
:last_run_time,
:created_by,
:last_modified_by,
:parallelism_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] processing_job_name
# The name of the processing job. The name must be unique within an
# Amazon Web Services Region in the Amazon Web Services account.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeProcessingJobRequest AWS API Documentation
#
class DescribeProcessingJobRequest < Struct.new(
:processing_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] processing_inputs
# The inputs for a processing job.
# @return [Array<Types::ProcessingInput>]
#
# @!attribute [rw] processing_output_config
# Output configuration for the processing job.
# @return [Types::ProcessingOutputConfig]
#
# @!attribute [rw] processing_job_name
# The name of the processing job. The name must be unique within an
# Amazon Web Services Region in the Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] 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.
# @return [Types::ProcessingResources]
#
# @!attribute [rw] stopping_condition
# The time limit for how long the processing job is allowed to run.
# @return [Types::ProcessingStoppingCondition]
#
# @!attribute [rw] app_specification
# Configures the processing job to run a specified container image.
# @return [Types::AppSpecification]
#
# @!attribute [rw] environment
# The environment variables set in the Docker container.
# @return [Hash<String,String>]
#
# @!attribute [rw] network_config
# Networking options for a processing job.
# @return [Types::NetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] experiment_config
# The configuration information used to create an experiment.
# @return [Types::ExperimentConfig]
#
# @!attribute [rw] processing_job_arn
# The Amazon Resource Name (ARN) of the processing job.
# @return [String]
#
# @!attribute [rw] processing_job_status
# Provides the status of a processing job.
# @return [String]
#
# @!attribute [rw] exit_message
# An optional string, up to one KB in size, that contains metadata
# from the processing container when the processing job exits.
# @return [String]
#
# @!attribute [rw] failure_reason
# A string, up to one KB in size, that contains the reason a
# processing job failed, if it failed.
# @return [String]
#
# @!attribute [rw] processing_end_time
# The time at which the processing job completed.
# @return [Time]
#
# @!attribute [rw] processing_start_time
# The time at which the processing job started.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time at which the processing job was last modified.
# @return [Time]
#
# @!attribute [rw] creation_time
# The time at which the processing job was created.
# @return [Time]
#
# @!attribute [rw] monitoring_schedule_arn
# The ARN of a monitoring schedule for an endpoint associated with
# this processing job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# The ARN of an AutoML job associated with this processing job.
# @return [String]
#
# @!attribute [rw] training_job_arn
# The ARN of a training job associated with this processing job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeProcessingJobResponse AWS API Documentation
#
class DescribeProcessingJobResponse < Struct.new(
:processing_inputs,
:processing_output_config,
:processing_job_name,
:processing_resources,
:stopping_condition,
:app_specification,
:environment,
:network_config,
:role_arn,
:experiment_config,
:processing_job_arn,
:processing_job_status,
:exit_message,
:failure_reason,
:processing_end_time,
:processing_start_time,
:last_modified_time,
:creation_time,
:monitoring_schedule_arn,
:auto_ml_job_arn,
:training_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_name
# The name of the project to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeProjectInput AWS API Documentation
#
class DescribeProjectInput < Struct.new(
:project_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project.
# @return [String]
#
# @!attribute [rw] project_name
# The name of the project.
# @return [String]
#
# @!attribute [rw] project_id
# The ID of the project.
# @return [String]
#
# @!attribute [rw] project_description
# The description of the project.
# @return [String]
#
# @!attribute [rw] service_catalog_provisioning_details
# Information used to provision a service catalog product. For
# information, see [What is Amazon Web Services Service Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
# @return [Types::ServiceCatalogProvisioningDetails]
#
# @!attribute [rw] service_catalog_provisioned_product_details
# Information about a provisioned service catalog product.
# @return [Types::ServiceCatalogProvisionedProductDetails]
#
# @!attribute [rw] project_status
# The status of the project.
# @return [String]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] creation_time
# The time when the project was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The timestamp when project was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeProjectOutput AWS API Documentation
#
class DescribeProjectOutput < Struct.new(
:project_arn,
:project_name,
:project_id,
:project_description,
:service_catalog_provisioning_details,
:service_catalog_provisioned_product_details,
:project_status,
:created_by,
:creation_time,
:last_modified_time,
:last_modified_by)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The ID of the associated Domain.
# @return [String]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeSpaceRequest AWS API Documentation
#
class DescribeSpaceRequest < Struct.new(
:domain_id,
:space_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The ID of the associated Domain.
# @return [String]
#
# @!attribute [rw] space_arn
# The space's Amazon Resource Name (ARN).
# @return [String]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @!attribute [rw] home_efs_file_system_uid
# The ID of the space's profile in the Amazon Elastic File System
# volume.
# @return [String]
#
# @!attribute [rw] status
# The status.
# @return [String]
#
# @!attribute [rw] last_modified_time
# The last modified time.
# @return [Time]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] failure_reason
# The failure reason.
# @return [String]
#
# @!attribute [rw] space_settings
# A collection of space settings.
# @return [Types::SpaceSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeSpaceResponse AWS API Documentation
#
class DescribeSpaceResponse < Struct.new(
:domain_id,
:space_arn,
:space_name,
:home_efs_file_system_uid,
:status,
:last_modified_time,
:creation_time,
:failure_reason,
:space_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] studio_lifecycle_config_name
# The name of the Studio Lifecycle Configuration to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeStudioLifecycleConfigRequest AWS API Documentation
#
class DescribeStudioLifecycleConfigRequest < Struct.new(
:studio_lifecycle_config_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] studio_lifecycle_config_arn
# The ARN of the Lifecycle Configuration to describe.
# @return [String]
#
# @!attribute [rw] studio_lifecycle_config_name
# The name of the Studio Lifecycle Configuration that is described.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of the Studio Lifecycle Configuration.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# This value is equivalent to CreationTime because Studio Lifecycle
# Configurations are immutable.
# @return [Time]
#
# @!attribute [rw] studio_lifecycle_config_content
# The content of your Studio Lifecycle Configuration script.
# @return [String]
#
# @!attribute [rw] studio_lifecycle_config_app_type
# The App type that the Lifecycle Configuration is attached to.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeStudioLifecycleConfigResponse AWS API Documentation
#
class DescribeStudioLifecycleConfigResponse < Struct.new(
:studio_lifecycle_config_arn,
:studio_lifecycle_config_name,
:creation_time,
:last_modified_time,
:studio_lifecycle_config_content,
:studio_lifecycle_config_app_type)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteam_arn
# The Amazon Resource Name (ARN) of the subscribed work team to
# describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeSubscribedWorkteamRequest AWS API Documentation
#
class DescribeSubscribedWorkteamRequest < Struct.new(
:workteam_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] subscribed_workteam
# A `Workteam` instance that contains information about the work team.
# @return [Types::SubscribedWorkteam]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeSubscribedWorkteamResponse AWS API Documentation
#
class DescribeSubscribedWorkteamResponse < Struct.new(
:subscribed_workteam)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_name
# The name of the training job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrainingJobRequest AWS API Documentation
#
class DescribeTrainingJobRequest < Struct.new(
:training_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_name
# Name of the model training job.
# @return [String]
#
# @!attribute [rw] training_job_arn
# The Amazon Resource Name (ARN) of the training job.
# @return [String]
#
# @!attribute [rw] tuning_job_arn
# The Amazon Resource Name (ARN) of the associated hyperparameter
# tuning job if the training job was launched by a hyperparameter
# tuning job.
# @return [String]
#
# @!attribute [rw] labeling_job_arn
# The Amazon Resource Name (ARN) of the SageMaker Ground Truth
# labeling job that created the transform or training job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# The Amazon Resource Name (ARN) of an AutoML job.
# @return [String]
#
# @!attribute [rw] model_artifacts
# Information about the Amazon S3 location that is configured for
# storing model artifacts.
# @return [Types::ModelArtifacts]
#
# @!attribute [rw] training_job_status
# The status of the training job.
#
# SageMaker provides the following training job statuses:
#
# * `InProgress` - The training is in progress.
#
# * `Completed` - The training job has completed.
#
# * `Failed` - The training job has failed. To see the reason for the
# failure, see the `FailureReason` field in the response to a
# `DescribeTrainingJobResponse` call.
#
# * `Stopping` - The training job is stopping.
#
# * `Stopped` - The training job has stopped.
#
# For more detailed information, see `SecondaryStatus`.
# @return [String]
#
# @!attribute [rw] secondary_status
# Provides detailed information about the state of the training job.
# For detailed information on the secondary status of the training
# job, see `StatusMessage` under [SecondaryStatusTransition][1].
#
# SageMaker provides primary statuses and secondary statuses that
# apply to each of them:
#
# InProgress
# : * `Starting` - Starting the training job.
#
# * `Downloading` - An optional stage for algorithms that support
# `File` training input mode. It indicates that data is being
# downloaded to the ML storage volumes.
#
# * `Training` - Training is in progress.
#
# * `Interrupted` - The job stopped because the managed spot
# training instances were interrupted.
#
# * `Uploading` - Training is complete and the model artifacts are
# being uploaded to the S3 location.
#
# Completed
# : * `Completed` - The training job has completed.
#
# ^
#
# Failed
# : * `Failed` - The training job has failed. The reason for the
# failure is returned in the `FailureReason` field of
# `DescribeTrainingJobResponse`.
#
# ^
#
# Stopped
# : * `MaxRuntimeExceeded` - The job stopped because it exceeded the
# maximum allowed runtime.
#
# * `MaxWaitTimeExceeded` - The job stopped because it exceeded the
# maximum allowed wait time.
#
# * `Stopped` - The training job has stopped.
#
# Stopping
# : * `Stopping` - Stopping the training job.
#
# ^
#
# Valid values for `SecondaryStatus` are subject to change.
#
# We no longer support the following secondary statuses:
#
# * `LaunchingMLInstances`
#
# * `PreparingTraining`
#
# * `DownloadingTrainingImage`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_SecondaryStatusTransition.html
# @return [String]
#
# @!attribute [rw] failure_reason
# If the training job failed, the reason it failed.
# @return [String]
#
# @!attribute [rw] hyper_parameters
# Algorithm-specific parameters.
# @return [Hash<String,String>]
#
# @!attribute [rw] algorithm_specification
# Information about the algorithm used for training, and algorithm
# metadata.
# @return [Types::AlgorithmSpecification]
#
# @!attribute [rw] role_arn
# The Amazon Web Services Identity and Access Management (IAM) role
# configured for the training job.
# @return [String]
#
# @!attribute [rw] input_data_config
# An array of `Channel` objects that describes each data input
# channel.
# @return [Array<Types::Channel>]
#
# @!attribute [rw] output_data_config
# The S3 path where model artifacts that you configured when creating
# the job are stored. SageMaker creates subfolders for model
# artifacts.
# @return [Types::OutputDataConfig]
#
# @!attribute [rw] resource_config
# Resources, including ML compute instances and ML storage volumes,
# that are configured for model training.
# @return [Types::ResourceConfig]
#
# @!attribute [rw] vpc_config
# A [VpcConfig][1] object that specifies the VPC that this training
# job has access to. For more information, see [Protect Training Jobs
# by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
# @return [Types::VpcConfig]
#
# @!attribute [rw] stopping_condition
# Specifies a limit to how long a model training job can run. It also
# specifies how long a managed Spot training job has to complete. When
# the job reaches the time limit, SageMaker ends the training job. Use
# this API to cap model training costs.
#
# To stop a job, SageMaker sends the algorithm the `SIGTERM` signal,
# which delays job termination for 120 seconds. Algorithms can use
# this 120-second window to save the model artifacts, so the results
# of training are not lost.
# @return [Types::StoppingCondition]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when the training job was created.
# @return [Time]
#
# @!attribute [rw] training_start_time
# Indicates the time when the training job starts on training
# instances. You are billed for the time interval between this time
# and the value of `TrainingEndTime`. The start time in CloudWatch
# Logs might be later than this time. The difference is due to the
# time it takes to download the training data and to the size of the
# training container.
# @return [Time]
#
# @!attribute [rw] training_end_time
# Indicates the time when the training job ends on training instances.
# You are billed for the time interval between the value of
# `TrainingStartTime` and this time. For successful jobs and stopped
# jobs, this is the time after model artifacts are uploaded. For
# failed jobs, this is the time when SageMaker detects a job failure.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that indicates when the status of the training job was
# last modified.
# @return [Time]
#
# @!attribute [rw] secondary_status_transitions
# A history of all of the secondary statuses that the training job has
# transitioned through.
# @return [Array<Types::SecondaryStatusTransition>]
#
# @!attribute [rw] final_metric_data_list
# A collection of `MetricData` objects that specify the names, values,
# and dates and times that the training algorithm emitted to Amazon
# CloudWatch.
# @return [Array<Types::MetricData>]
#
# @!attribute [rw] enable_network_isolation
# If you want to allow inbound or outbound network calls, except for
# calls between peers within a training cluster for distributed
# training, choose `True`. If you enable network isolation for
# training jobs that are configured to use a VPC, SageMaker downloads
# and uploads customer data and model artifacts through the specified
# VPC, but the training container does not have network access.
# @return [Boolean]
#
# @!attribute [rw] enable_inter_container_traffic_encryption
# To encrypt all communications between ML compute instances in
# distributed training, choose `True`. Encryption provides greater
# security for distributed training, but training might take longer.
# How long it takes depends on the amount of communication between
# compute instances, especially if you use a deep learning algorithms
# in distributed training.
# @return [Boolean]
#
# @!attribute [rw] enable_managed_spot_training
# A Boolean indicating whether managed spot training is enabled
# (`True`) or not (`False`).
# @return [Boolean]
#
# @!attribute [rw] checkpoint_config
# Contains information about the output location for managed spot
# training checkpoint data.
# @return [Types::CheckpointConfig]
#
# @!attribute [rw] training_time_in_seconds
# The training time in seconds.
# @return [Integer]
#
# @!attribute [rw] billable_time_in_seconds
# The billable time in seconds. Billable time refers to the absolute
# wall-clock time.
#
# Multiply `BillableTimeInSeconds` by the number of instances
# (`InstanceCount`) in your training cluster to get the total compute
# time SageMaker bills you if you run distributed training. The
# formula is as follows: `BillableTimeInSeconds * InstanceCount` .
#
# You can calculate the savings from using managed spot training using
# the formula `(1 - BillableTimeInSeconds / TrainingTimeInSeconds) *
# 100`. For example, if `BillableTimeInSeconds` is 100 and
# `TrainingTimeInSeconds` is 500, the savings is 80%.
# @return [Integer]
#
# @!attribute [rw] debug_hook_config
# Configuration information for the Amazon SageMaker Debugger hook
# parameters, metric and tensor collections, and storage paths. To
# learn more about how to configure the `DebugHookConfig` parameter,
# see [Use the SageMaker and Debugger Configuration API Operations to
# Create, Update, and Debug Your Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html
# @return [Types::DebugHookConfig]
#
# @!attribute [rw] experiment_config
# Associates a SageMaker job as a trial component with an experiment
# and trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
# @return [Types::ExperimentConfig]
#
# @!attribute [rw] debug_rule_configurations
# Configuration information for Amazon SageMaker Debugger rules for
# debugging output tensors.
# @return [Array<Types::DebugRuleConfiguration>]
#
# @!attribute [rw] tensor_board_output_config
# Configuration of storage locations for the Amazon SageMaker Debugger
# TensorBoard output data.
# @return [Types::TensorBoardOutputConfig]
#
# @!attribute [rw] debug_rule_evaluation_statuses
# Evaluation status of Amazon SageMaker Debugger rules for debugging
# on a training job.
# @return [Array<Types::DebugRuleEvaluationStatus>]
#
# @!attribute [rw] profiler_config
# Configuration information for Amazon SageMaker Debugger system
# monitoring, framework profiling, and storage paths.
# @return [Types::ProfilerConfig]
#
# @!attribute [rw] profiler_rule_configurations
# Configuration information for Amazon SageMaker Debugger rules for
# profiling system and framework metrics.
# @return [Array<Types::ProfilerRuleConfiguration>]
#
# @!attribute [rw] profiler_rule_evaluation_statuses
# Evaluation status of Amazon SageMaker Debugger rules for profiling
# on a training job.
# @return [Array<Types::ProfilerRuleEvaluationStatus>]
#
# @!attribute [rw] profiling_status
# Profiling status of a training job.
# @return [String]
#
# @!attribute [rw] retry_strategy
# The number of times to retry the job when the job fails due to an
# `InternalServerError`.
# @return [Types::RetryStrategy]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container.
# @return [Hash<String,String>]
#
# @!attribute [rw] warm_pool_status
# The status of the warm pool associated with the training job.
# @return [Types::WarmPoolStatus]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrainingJobResponse AWS API Documentation
#
class DescribeTrainingJobResponse < Struct.new(
:training_job_name,
:training_job_arn,
:tuning_job_arn,
:labeling_job_arn,
:auto_ml_job_arn,
:model_artifacts,
:training_job_status,
:secondary_status,
:failure_reason,
:hyper_parameters,
:algorithm_specification,
:role_arn,
:input_data_config,
:output_data_config,
:resource_config,
:vpc_config,
:stopping_condition,
:creation_time,
:training_start_time,
:training_end_time,
:last_modified_time,
:secondary_status_transitions,
:final_metric_data_list,
:enable_network_isolation,
:enable_inter_container_traffic_encryption,
:enable_managed_spot_training,
:checkpoint_config,
:training_time_in_seconds,
:billable_time_in_seconds,
:debug_hook_config,
:experiment_config,
:debug_rule_configurations,
:tensor_board_output_config,
:debug_rule_evaluation_statuses,
:profiler_config,
:profiler_rule_configurations,
:profiler_rule_evaluation_statuses,
:profiling_status,
:retry_strategy,
:environment,
:warm_pool_status)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] transform_job_name
# The name of the transform job that you want to view details of.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTransformJobRequest AWS API Documentation
#
class DescribeTransformJobRequest < Struct.new(
:transform_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] transform_job_name
# The name of the transform job.
# @return [String]
#
# @!attribute [rw] transform_job_arn
# The Amazon Resource Name (ARN) of the transform job.
# @return [String]
#
# @!attribute [rw] transform_job_status
# The status of the transform job. If the transform job failed, the
# reason is returned in the `FailureReason` field.
# @return [String]
#
# @!attribute [rw] failure_reason
# If the transform job failed, `FailureReason` describes why it
# failed. A transform job creates a log file, which includes error
# messages, and stores it as an Amazon S3 object. For more
# information, see [Log Amazon SageMaker Events with Amazon
# CloudWatch][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/logging-cloudwatch.html
# @return [String]
#
# @!attribute [rw] model_name
# The name of the model used in the transform job.
# @return [String]
#
# @!attribute [rw] max_concurrent_transforms
# The maximum number of parallel requests on each instance node that
# can be launched in a transform job. The default value is 1.
# @return [Integer]
#
# @!attribute [rw] model_client_config
# The timeout and maximum number of retries for processing a transform
# job invocation.
# @return [Types::ModelClientConfig]
#
# @!attribute [rw] max_payload_in_mb
# The maximum payload size, in MB, used in the transform job.
# @return [Integer]
#
# @!attribute [rw] batch_strategy
# Specifies the number of records to include in a mini-batch for an
# HTTP inference request. A *record* ** is a single unit of input data
# that inference can be made on. For example, a single line in a CSV
# file is a record.
#
# To enable the batch strategy, you must set `SplitType` to `Line`,
# `RecordIO`, or `TFRecord`.
# @return [String]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container. We support
# up to 16 key and values entries in the map.
# @return [Hash<String,String>]
#
# @!attribute [rw] transform_input
# Describes the dataset to be transformed and the Amazon S3 location
# where it is stored.
# @return [Types::TransformInput]
#
# @!attribute [rw] transform_output
# Identifies the Amazon S3 location where you want Amazon SageMaker to
# save the results from the transform job.
# @return [Types::TransformOutput]
#
# @!attribute [rw] data_capture_config
# Configuration to control how SageMaker captures inference data.
# @return [Types::BatchDataCaptureConfig]
#
# @!attribute [rw] transform_resources
# Describes the resources, including ML instance types and ML instance
# count, to use for the transform job.
# @return [Types::TransformResources]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the transform Job was created.
# @return [Time]
#
# @!attribute [rw] transform_start_time
# Indicates when the transform job starts on ML instances. You are
# billed for the time interval between this time and the value of
# `TransformEndTime`.
# @return [Time]
#
# @!attribute [rw] transform_end_time
# Indicates when the transform job has been completed, or has stopped
# or failed. You are billed for the time interval between this time
# and the value of `TransformStartTime`.
# @return [Time]
#
# @!attribute [rw] labeling_job_arn
# The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth
# labeling job that created the transform or training job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# The Amazon Resource Name (ARN) of the AutoML transform job.
# @return [String]
#
# @!attribute [rw] 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][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html
# @return [Types::DataProcessing]
#
# @!attribute [rw] experiment_config
# Associates a SageMaker job as a trial component with an experiment
# and trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
# @return [Types::ExperimentConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTransformJobResponse AWS API Documentation
#
class DescribeTransformJobResponse < Struct.new(
:transform_job_name,
:transform_job_arn,
:transform_job_status,
:failure_reason,
:model_name,
:max_concurrent_transforms,
:model_client_config,
:max_payload_in_mb,
:batch_strategy,
:environment,
:transform_input,
:transform_output,
:data_capture_config,
:transform_resources,
:creation_time,
:transform_start_time,
:transform_end_time,
:labeling_job_arn,
:auto_ml_job_arn,
:data_processing,
:experiment_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_name
# The name of the trial component to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrialComponentRequest AWS API Documentation
#
class DescribeTrialComponentRequest < Struct.new(
:trial_component_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_name
# The name of the trial component.
# @return [String]
#
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the trial component.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the component as displayed. If `DisplayName` isn't
# specified, `TrialComponentName` is displayed.
# @return [String]
#
# @!attribute [rw] source
# The Amazon Resource Name (ARN) of the source and, optionally, the
# job type.
# @return [Types::TrialComponentSource]
#
# @!attribute [rw] status
# The status of the component. States include:
#
# * InProgress
#
# * Completed
#
# * Failed
# @return [Types::TrialComponentStatus]
#
# @!attribute [rw] start_time
# When the component started.
# @return [Time]
#
# @!attribute [rw] end_time
# When the component ended.
# @return [Time]
#
# @!attribute [rw] creation_time
# When the component was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Who created the trial component.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the component was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Who last modified the component.
# @return [Types::UserContext]
#
# @!attribute [rw] parameters
# The hyperparameters of the component.
# @return [Hash<String,Types::TrialComponentParameterValue>]
#
# @!attribute [rw] input_artifacts
# The input artifacts of the component.
# @return [Hash<String,Types::TrialComponentArtifact>]
#
# @!attribute [rw] output_artifacts
# The output artifacts of the component.
# @return [Hash<String,Types::TrialComponentArtifact>]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] metrics
# The metrics for the component.
# @return [Array<Types::TrialComponentMetricSummary>]
#
# @!attribute [rw] lineage_group_arn
# The Amazon Resource Name (ARN) of the lineage group.
# @return [String]
#
# @!attribute [rw] sources
# A list of ARNs and, if applicable, job types for multiple sources of
# an experiment run.
# @return [Array<Types::TrialComponentSource>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrialComponentResponse AWS API Documentation
#
class DescribeTrialComponentResponse < Struct.new(
:trial_component_name,
:trial_component_arn,
:display_name,
:source,
:status,
:start_time,
:end_time,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:parameters,
:input_artifacts,
:output_artifacts,
:metadata_properties,
:metrics,
:lineage_group_arn,
:sources)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_name
# The name of the trial to describe.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrialRequest AWS API Documentation
#
class DescribeTrialRequest < Struct.new(
:trial_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_name
# The name of the trial.
# @return [String]
#
# @!attribute [rw] trial_arn
# The Amazon Resource Name (ARN) of the trial.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the trial as displayed. If `DisplayName` isn't
# specified, `TrialName` is displayed.
# @return [String]
#
# @!attribute [rw] experiment_name
# The name of the experiment the trial is part of.
# @return [String]
#
# @!attribute [rw] source
# The Amazon Resource Name (ARN) of the source and, optionally, the
# job type.
# @return [Types::TrialSource]
#
# @!attribute [rw] creation_time
# When the trial was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Who created the trial.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the trial was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Who last modified the trial.
# @return [Types::UserContext]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrialResponse AWS API Documentation
#
class DescribeTrialResponse < Struct.new(
:trial_name,
:trial_arn,
:display_name,
:experiment_name,
:source,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:metadata_properties)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name. This value is not case sensitive.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeUserProfileRequest AWS API Documentation
#
class DescribeUserProfileRequest < Struct.new(
:domain_id,
:user_profile_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The ID of the domain that contains the profile.
# @return [String]
#
# @!attribute [rw] user_profile_arn
# The user profile Amazon Resource Name (ARN).
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name.
# @return [String]
#
# @!attribute [rw] home_efs_file_system_uid
# The ID of the user's profile in the Amazon Elastic File System
# (EFS) volume.
# @return [String]
#
# @!attribute [rw] status
# The status.
# @return [String]
#
# @!attribute [rw] last_modified_time
# The last modified time.
# @return [Time]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] failure_reason
# The failure reason.
# @return [String]
#
# @!attribute [rw] single_sign_on_user_identifier
# The IAM Identity Center user identifier.
# @return [String]
#
# @!attribute [rw] single_sign_on_user_value
# The IAM Identity Center user value.
# @return [String]
#
# @!attribute [rw] user_settings
# A collection of settings.
# @return [Types::UserSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeUserProfileResponse AWS API Documentation
#
class DescribeUserProfileResponse < Struct.new(
:domain_id,
:user_profile_arn,
:user_profile_name,
:home_efs_file_system_uid,
:status,
:last_modified_time,
:creation_time,
:failure_reason,
:single_sign_on_user_identifier,
:single_sign_on_user_value,
:user_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workforce_name
# The name of the private workforce whose access you want to restrict.
# `WorkforceName` is automatically set to `default` when a workforce
# is created and cannot be modified.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkforceRequest AWS API Documentation
#
class DescribeWorkforceRequest < Struct.new(
:workforce_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] 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 Amazon Web Services 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][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html
# @return [Types::Workforce]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkforceResponse AWS API Documentation
#
class DescribeWorkforceResponse < Struct.new(
:workforce)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteam_name
# The name of the work team to return a description of.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkteamRequest AWS API Documentation
#
class DescribeWorkteamRequest < Struct.new(
:workteam_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteam
# A `Workteam` instance that contains information about the work team.
# @return [Types::Workteam]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeWorkteamResponse AWS API Documentation
#
class DescribeWorkteamResponse < Struct.new(
:workteam)
SENSITIVE = []
include Aws::Structure
end
# Specifies weight and capacity values for a production variant.
#
# @!attribute [rw] variant_name
# The name of the variant to update.
# @return [String]
#
# @!attribute [rw] desired_weight
# The variant's weight.
# @return [Float]
#
# @!attribute [rw] desired_instance_count
# The variant's capacity.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DesiredWeightAndCapacity AWS API Documentation
#
class DesiredWeightAndCapacity < Struct.new(
:variant_name,
:desired_weight,
:desired_instance_count)
SENSITIVE = []
include Aws::Structure
end
# Information of a particular device.
#
# @!attribute [rw] device_name
# The name of the device.
# @return [String]
#
# @!attribute [rw] description
# Description of the device.
# @return [String]
#
# @!attribute [rw] iot_thing_name
# Amazon Web Services Internet of Things (IoT) object name.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Device AWS API Documentation
#
class Device < Struct.new(
:device_name,
:description,
:iot_thing_name)
SENSITIVE = []
include Aws::Structure
end
# Contains information summarizing device details and deployment status.
#
# @!attribute [rw] edge_deployment_plan_arn
# The ARN of the edge deployment plan.
# @return [String]
#
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan.
# @return [String]
#
# @!attribute [rw] stage_name
# The name of the stage in the edge deployment plan.
# @return [String]
#
# @!attribute [rw] deployed_stage_name
# The name of the deployed stage.
# @return [String]
#
# @!attribute [rw] device_fleet_name
# The name of the fleet to which the device belongs to.
# @return [String]
#
# @!attribute [rw] device_name
# The name of the device.
# @return [String]
#
# @!attribute [rw] device_arn
# The ARN of the device.
# @return [String]
#
# @!attribute [rw] device_deployment_status
# The deployment status of the device.
# @return [String]
#
# @!attribute [rw] device_deployment_status_message
# The detailed error message for the deployoment status result.
# @return [String]
#
# @!attribute [rw] description
# The description of the device.
# @return [String]
#
# @!attribute [rw] deployment_start_time
# The time when the deployment on the device started.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeviceDeploymentSummary AWS API Documentation
#
class DeviceDeploymentSummary < Struct.new(
:edge_deployment_plan_arn,
:edge_deployment_plan_name,
:stage_name,
:deployed_stage_name,
:device_fleet_name,
:device_name,
:device_arn,
:device_deployment_status,
:device_deployment_status_message,
:description,
:deployment_start_time)
SENSITIVE = []
include Aws::Structure
end
# Summary of the device fleet.
#
# @!attribute [rw] device_fleet_arn
# Amazon Resource Name (ARN) of the device fleet.
# @return [String]
#
# @!attribute [rw] device_fleet_name
# Name of the device fleet.
# @return [String]
#
# @!attribute [rw] creation_time
# Timestamp of when the device fleet was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# Timestamp of when the device fleet was last updated.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeviceFleetSummary AWS API Documentation
#
class DeviceFleetSummary < Struct.new(
:device_fleet_arn,
:device_fleet_name,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# Contains information about the configurations of selected devices.
#
# @!attribute [rw] device_subset_type
# Type of device subsets to deploy to the current stage.
# @return [String]
#
# @!attribute [rw] percentage
# Percentage of devices in the fleet to deploy to the current stage.
# @return [Integer]
#
# @!attribute [rw] device_names
# List of devices chosen to deploy.
# @return [Array<String>]
#
# @!attribute [rw] device_name_contains
# A filter to select devices with names containing this name.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeviceSelectionConfig AWS API Documentation
#
class DeviceSelectionConfig < Struct.new(
:device_subset_type,
:percentage,
:device_names,
:device_name_contains)
SENSITIVE = []
include Aws::Structure
end
# Status of devices.
#
# @!attribute [rw] connected_device_count
# The number of devices connected with a heartbeat.
# @return [Integer]
#
# @!attribute [rw] registered_device_count
# The number of registered devices.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeviceStats AWS API Documentation
#
class DeviceStats < Struct.new(
:connected_device_count,
:registered_device_count)
SENSITIVE = []
include Aws::Structure
end
# Summary of the device.
#
# @!attribute [rw] device_name
# The unique identifier of the device.
# @return [String]
#
# @!attribute [rw] device_arn
# Amazon Resource Name (ARN) of the device.
# @return [String]
#
# @!attribute [rw] description
# A description of the device.
# @return [String]
#
# @!attribute [rw] device_fleet_name
# The name of the fleet the device belongs to.
# @return [String]
#
# @!attribute [rw] iot_thing_name
# The Amazon Web Services Internet of Things (IoT) object thing name
# associated with the device..
# @return [String]
#
# @!attribute [rw] registration_time
# The timestamp of the last registration or de-reregistration.
# @return [Time]
#
# @!attribute [rw] latest_heartbeat
# The last heartbeat received from the device.
# @return [Time]
#
# @!attribute [rw] models
# Models on the device.
# @return [Array<Types::EdgeModelSummary>]
#
# @!attribute [rw] agent_version
# Edge Manager agent version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeviceSummary AWS API Documentation
#
class DeviceSummary < Struct.new(
:device_name,
:device_arn,
:description,
:device_fleet_name,
:iot_thing_name,
:registration_time,
:latest_heartbeat,
:models,
:agent_version)
SENSITIVE = []
include Aws::Structure
end
# @api private
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DisableSagemakerServicecatalogPortfolioInput AWS API Documentation
#
class DisableSagemakerServicecatalogPortfolioInput < Aws::EmptyStructure; end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DisableSagemakerServicecatalogPortfolioOutput AWS API Documentation
#
class DisableSagemakerServicecatalogPortfolioOutput < Aws::EmptyStructure; end
# @!attribute [rw] trial_component_name
# The name of the component to disassociate from the trial.
# @return [String]
#
# @!attribute [rw] trial_name
# The name of the trial to disassociate from.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DisassociateTrialComponentRequest AWS API Documentation
#
class DisassociateTrialComponentRequest < Struct.new(
:trial_component_name,
:trial_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the trial component.
# @return [String]
#
# @!attribute [rw] trial_arn
# The Amazon Resource Name (ARN) of the trial.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DisassociateTrialComponentResponse AWS API Documentation
#
class DisassociateTrialComponentResponse < Struct.new(
:trial_component_arn,
:trial_arn)
SENSITIVE = []
include Aws::Structure
end
# The domain's details.
#
# @!attribute [rw] domain_arn
# The domain's Amazon Resource Name (ARN).
# @return [String]
#
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] domain_name
# The domain name.
# @return [String]
#
# @!attribute [rw] status
# The status.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last modified time.
# @return [Time]
#
# @!attribute [rw] url
# The domain's URL.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DomainDetails AWS API Documentation
#
class DomainDetails < Struct.new(
:domain_arn,
:domain_id,
:domain_name,
:status,
:creation_time,
:last_modified_time,
:url)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings that apply to the `SageMaker Domain`. These
# settings are specified through the `CreateDomain` API call.
#
# @!attribute [rw] security_group_ids
# The security groups for the Amazon Virtual Private Cloud that the
# `Domain` uses for communication between Domain-level apps and user
# apps.
# @return [Array<String>]
#
# @!attribute [rw] r_studio_server_pro_domain_settings
# A collection of settings that configure the `RStudioServerPro`
# Domain-level app.
# @return [Types::RStudioServerProDomainSettings]
#
# @!attribute [rw] execution_role_identity_config
# The configuration for attaching a SageMaker user profile name to the
# execution role as a [sts:SourceIdentity key][1].
#
#
#
# [1]: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_control-access_monitor.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DomainSettings AWS API Documentation
#
class DomainSettings < Struct.new(
:security_group_ids,
:r_studio_server_pro_domain_settings,
:execution_role_identity_config)
SENSITIVE = []
include Aws::Structure
end
# A collection of `Domain` configuration settings to update.
#
# @!attribute [rw] r_studio_server_pro_domain_settings_for_update
# A collection of `RStudioServerPro` Domain-level app settings to
# update.
# @return [Types::RStudioServerProDomainSettingsForUpdate]
#
# @!attribute [rw] execution_role_identity_config
# The configuration for attaching a SageMaker user profile name to the
# execution role as a [sts:SourceIdentity key][1]. This configuration
# can only be modified if there are no apps in the `InService` or
# `Pending` state.
#
#
#
# [1]: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_control-access_monitor.html
# @return [String]
#
# @!attribute [rw] security_group_ids
# The security groups for the Amazon Virtual Private Cloud that the
# `Domain` uses for communication between Domain-level apps and user
# apps.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DomainSettingsForUpdate AWS API Documentation
#
class DomainSettingsForUpdate < Struct.new(
:r_studio_server_pro_domain_settings_for_update,
:execution_role_identity_config,
:security_group_ids)
SENSITIVE = []
include Aws::Structure
end
# Represents the drift check baselines that can be used when the model
# monitor is set using the model package.
#
# @!attribute [rw] bias
# Represents the drift check bias baselines that can be used when the
# model monitor is set using the model package.
# @return [Types::DriftCheckBias]
#
# @!attribute [rw] explainability
# Represents the drift check explainability baselines that can be used
# when the model monitor is set using the model package.
# @return [Types::DriftCheckExplainability]
#
# @!attribute [rw] model_quality
# Represents the drift check model quality baselines that can be used
# when the model monitor is set using the model package.
# @return [Types::DriftCheckModelQuality]
#
# @!attribute [rw] model_data_quality
# Represents the drift check model data quality baselines that can be
# used when the model monitor is set using the model package.
# @return [Types::DriftCheckModelDataQuality]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DriftCheckBaselines AWS API Documentation
#
class DriftCheckBaselines < Struct.new(
:bias,
:explainability,
:model_quality,
:model_data_quality)
SENSITIVE = []
include Aws::Structure
end
# Represents the drift check bias baselines that can be used when the
# model monitor is set using the model package.
#
# @!attribute [rw] config_file
# The bias config file for a model.
# @return [Types::FileSource]
#
# @!attribute [rw] pre_training_constraints
# The pre-training constraints.
# @return [Types::MetricsSource]
#
# @!attribute [rw] post_training_constraints
# The post-training constraints.
# @return [Types::MetricsSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DriftCheckBias AWS API Documentation
#
class DriftCheckBias < Struct.new(
:config_file,
:pre_training_constraints,
:post_training_constraints)
SENSITIVE = []
include Aws::Structure
end
# Represents the drift check explainability baselines that can be used
# when the model monitor is set using the model package.
#
# @!attribute [rw] constraints
# The drift check explainability constraints.
# @return [Types::MetricsSource]
#
# @!attribute [rw] config_file
# The explainability config file for the model.
# @return [Types::FileSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DriftCheckExplainability AWS API Documentation
#
class DriftCheckExplainability < Struct.new(
:constraints,
:config_file)
SENSITIVE = []
include Aws::Structure
end
# Represents the drift check data quality baselines that can be used
# when the model monitor is set using the model package.
#
# @!attribute [rw] statistics
# The drift check model data quality statistics.
# @return [Types::MetricsSource]
#
# @!attribute [rw] constraints
# The drift check model data quality constraints.
# @return [Types::MetricsSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DriftCheckModelDataQuality AWS API Documentation
#
class DriftCheckModelDataQuality < Struct.new(
:statistics,
:constraints)
SENSITIVE = []
include Aws::Structure
end
# Represents the drift check model quality baselines that can be used
# when the model monitor is set using the model package.
#
# @!attribute [rw] statistics
# The drift check model quality statistics.
# @return [Types::MetricsSource]
#
# @!attribute [rw] constraints
# The drift check model quality constraints.
# @return [Types::MetricsSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DriftCheckModelQuality AWS API Documentation
#
class DriftCheckModelQuality < Struct.new(
:statistics,
:constraints)
SENSITIVE = []
include Aws::Structure
end
# The configurations and outcomes of an Amazon EMR step execution.
#
# @!attribute [rw] cluster_id
# The identifier of the EMR cluster.
# @return [String]
#
# @!attribute [rw] step_id
# The identifier of the EMR cluster step.
# @return [String]
#
# @!attribute [rw] step_name
# The name of the EMR cluster step.
# @return [String]
#
# @!attribute [rw] log_file_path
# The path to the log file where the cluster step's failure root
# cause is recorded.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EMRStepMetadata AWS API Documentation
#
class EMRStepMetadata < Struct.new(
:cluster_id,
:step_id,
:step_name,
:log_file_path)
SENSITIVE = []
include Aws::Structure
end
# A directed edge connecting two lineage entities.
#
# @!attribute [rw] source_arn
# The Amazon Resource Name (ARN) of the source lineage entity of the
# directed edge.
# @return [String]
#
# @!attribute [rw] destination_arn
# The Amazon Resource Name (ARN) of the destination lineage entity of
# the directed edge.
# @return [String]
#
# @!attribute [rw] association_type
# The type of the Association(Edge) between the source and
# destination. For example `ContributedTo`, `Produced`, or
# `DerivedFrom`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Edge AWS API Documentation
#
class Edge < Struct.new(
:source_arn,
:destination_arn,
:association_type)
SENSITIVE = []
include Aws::Structure
end
# Contains information about the configuration of a deployment.
#
# @!attribute [rw] failure_handling_policy
# Toggle that determines whether to rollback to previous configuration
# if the current deployment fails. By default this is turned on. You
# may turn this off if you want to investigate the errors yourself.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgeDeploymentConfig AWS API Documentation
#
class EdgeDeploymentConfig < Struct.new(
:failure_handling_policy)
SENSITIVE = []
include Aws::Structure
end
# Contains information about the configuration of a model in a
# deployment.
#
# @!attribute [rw] model_handle
# The name the device application uses to reference this model.
# @return [String]
#
# @!attribute [rw] edge_packaging_job_name
# The edge packaging job associated with this deployment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgeDeploymentModelConfig AWS API Documentation
#
class EdgeDeploymentModelConfig < Struct.new(
:model_handle,
:edge_packaging_job_name)
SENSITIVE = []
include Aws::Structure
end
# Contains information summarizing an edge deployment plan.
#
# @!attribute [rw] edge_deployment_plan_arn
# The ARN of the edge deployment plan.
# @return [String]
#
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan.
# @return [String]
#
# @!attribute [rw] device_fleet_name
# The name of the device fleet used for the deployment.
# @return [String]
#
# @!attribute [rw] edge_deployment_success
# The number of edge devices with the successful deployment.
# @return [Integer]
#
# @!attribute [rw] edge_deployment_pending
# The number of edge devices yet to pick up the deployment, or in
# progress.
# @return [Integer]
#
# @!attribute [rw] edge_deployment_failed
# The number of edge devices that failed the deployment.
# @return [Integer]
#
# @!attribute [rw] creation_time
# The time when the edge deployment plan was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time when the edge deployment plan was last updated.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgeDeploymentPlanSummary AWS API Documentation
#
class EdgeDeploymentPlanSummary < Struct.new(
:edge_deployment_plan_arn,
:edge_deployment_plan_name,
:device_fleet_name,
:edge_deployment_success,
:edge_deployment_pending,
:edge_deployment_failed,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# Contains information summarizing the deployment stage results.
#
# @!attribute [rw] stage_status
# The general status of the current stage.
# @return [String]
#
# @!attribute [rw] edge_deployment_success_in_stage
# The number of edge devices with the successful deployment in the
# current stage.
# @return [Integer]
#
# @!attribute [rw] edge_deployment_pending_in_stage
# The number of edge devices yet to pick up the deployment in current
# stage, or in progress.
# @return [Integer]
#
# @!attribute [rw] edge_deployment_failed_in_stage
# The number of edge devices that failed the deployment in current
# stage.
# @return [Integer]
#
# @!attribute [rw] edge_deployment_status_message
# A detailed message about deployment status in current stage.
# @return [String]
#
# @!attribute [rw] edge_deployment_stage_start_time
# The time when the deployment API started.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgeDeploymentStatus AWS API Documentation
#
class EdgeDeploymentStatus < Struct.new(
:stage_status,
:edge_deployment_success_in_stage,
:edge_deployment_pending_in_stage,
:edge_deployment_failed_in_stage,
:edge_deployment_status_message,
:edge_deployment_stage_start_time)
SENSITIVE = []
include Aws::Structure
end
# The model on the edge device.
#
# @!attribute [rw] model_name
# The name of the model.
# @return [String]
#
# @!attribute [rw] model_version
# The model version.
# @return [String]
#
# @!attribute [rw] latest_sample_time
# The timestamp of the last data sample taken.
# @return [Time]
#
# @!attribute [rw] latest_inference
# The timestamp of the last inference that was made.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgeModel AWS API Documentation
#
class EdgeModel < Struct.new(
:model_name,
:model_version,
:latest_sample_time,
:latest_inference)
SENSITIVE = []
include Aws::Structure
end
# Status of edge devices with this model.
#
# @!attribute [rw] model_name
# The name of the model.
# @return [String]
#
# @!attribute [rw] model_version
# The model version.
# @return [String]
#
# @!attribute [rw] offline_device_count
# The number of devices that have this model version and do not have a
# heart beat.
# @return [Integer]
#
# @!attribute [rw] connected_device_count
# The number of devices that have this model version and have a heart
# beat.
# @return [Integer]
#
# @!attribute [rw] active_device_count
# The number of devices that have this model version, a heart beat,
# and are currently running.
# @return [Integer]
#
# @!attribute [rw] sampling_device_count
# The number of devices with this model version and are producing
# sample data.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgeModelStat AWS API Documentation
#
class EdgeModelStat < Struct.new(
:model_name,
:model_version,
:offline_device_count,
:connected_device_count,
:active_device_count,
:sampling_device_count)
SENSITIVE = []
include Aws::Structure
end
# Summary of model on edge device.
#
# @!attribute [rw] model_name
# The name of the model.
# @return [String]
#
# @!attribute [rw] model_version
# The version model.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgeModelSummary AWS API Documentation
#
class EdgeModelSummary < Struct.new(
:model_name,
:model_version)
SENSITIVE = []
include Aws::Structure
end
# The output configuration.
#
# @!attribute [rw] s3_output_location
# The Amazon Simple Storage (S3) bucker URI.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt data on the storage
# volume after compilation job. If you don't provide a KMS key ID,
# Amazon SageMaker uses the default KMS key for Amazon S3 for your
# role's account.
# @return [String]
#
# @!attribute [rw] preset_deployment_type
# The deployment type SageMaker Edge Manager will create. Currently
# only supports Amazon Web Services IoT Greengrass Version 2
# components.
# @return [String]
#
# @!attribute [rw] preset_deployment_config
# The configuration used to create deployment artifacts. Specify
# configuration options with a JSON string. The available
# configuration options for each type are:
#
# * `ComponentName` (optional) - Name of the GreenGrass V2 component.
# If not specified, the default name generated consists of
# "SagemakerEdgeManager" and the name of your SageMaker Edge
# Manager packaging job.
#
# * `ComponentDescription` (optional) - Description of the component.
#
# * `ComponentVersion` (optional) - The version of the component.
#
# <note markdown="1"> Amazon Web Services IoT Greengrass uses semantic versions for
# components. Semantic versions follow a<i> major.minor.patch</i>
# number system. For example, version 1.0.0 represents the first
# major release for a component. For more information, see the
# [semantic version specification][1].
#
# </note>
#
# * `PlatformOS` (optional) - The name of the operating system for the
# platform. Supported platforms include Windows and Linux.
#
# * `PlatformArchitecture` (optional) - The processor architecture for
# the platform.
#
# Supported architectures Windows include: Windows32\_x86,
# Windows64\_x64.
#
# Supported architectures for Linux include: Linux x86\_64, Linux
# ARMV8.
#
#
#
# [1]: https://semver.org/
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgeOutputConfig AWS API Documentation
#
class EdgeOutputConfig < Struct.new(
:s3_output_location,
:kms_key_id,
:preset_deployment_type,
:preset_deployment_config)
SENSITIVE = []
include Aws::Structure
end
# Summary of edge packaging job.
#
# @!attribute [rw] edge_packaging_job_arn
# The Amazon Resource Name (ARN) of the edge packaging job.
# @return [String]
#
# @!attribute [rw] edge_packaging_job_name
# The name of the edge packaging job.
# @return [String]
#
# @!attribute [rw] edge_packaging_job_status
# The status of the edge packaging job.
# @return [String]
#
# @!attribute [rw] compilation_job_name
# The name of the SageMaker Neo compilation job.
# @return [String]
#
# @!attribute [rw] model_name
# The name of the model.
# @return [String]
#
# @!attribute [rw] model_version
# The version of the model.
# @return [String]
#
# @!attribute [rw] creation_time
# The timestamp of when the job was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The timestamp of when the edge packaging job was last updated.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgePackagingJobSummary AWS API Documentation
#
class EdgePackagingJobSummary < Struct.new(
:edge_packaging_job_arn,
:edge_packaging_job_name,
:edge_packaging_job_status,
:compilation_job_name,
:model_name,
:model_version,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# The output of a SageMaker Edge Manager deployable resource.
#
# @!attribute [rw] type
# The deployment type created by SageMaker Edge Manager. Currently
# only supports Amazon Web Services IoT Greengrass Version 2
# components.
# @return [String]
#
# @!attribute [rw] artifact
# The Amazon Resource Name (ARN) of the generated deployable resource.
# @return [String]
#
# @!attribute [rw] status
# The status of the deployable resource.
# @return [String]
#
# @!attribute [rw] status_message
# Returns a message describing the status of the deployed resource.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EdgePresetDeploymentOutput AWS API Documentation
#
class EdgePresetDeploymentOutput < Struct.new(
:type,
:artifact,
:status,
:status_message)
SENSITIVE = []
include Aws::Structure
end
# @api private
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EnableSagemakerServicecatalogPortfolioInput AWS API Documentation
#
class EnableSagemakerServicecatalogPortfolioInput < Aws::EmptyStructure; end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EnableSagemakerServicecatalogPortfolioOutput AWS API Documentation
#
class EnableSagemakerServicecatalogPortfolioOutput < Aws::EmptyStructure; end
# A hosted endpoint for real-time inference.
#
# @!attribute [rw] endpoint_name
# The name of the endpoint.
# @return [String]
#
# @!attribute [rw] endpoint_arn
# The Amazon Resource Name (ARN) of the endpoint.
# @return [String]
#
# @!attribute [rw] endpoint_config_name
# The endpoint configuration associated with the endpoint.
# @return [String]
#
# @!attribute [rw] production_variants
# A list of the production variants hosted on the endpoint. Each
# production variant is a model.
# @return [Array<Types::ProductionVariantSummary>]
#
# @!attribute [rw] data_capture_config
# The currently active data capture configuration used by your
# Endpoint.
# @return [Types::DataCaptureConfigSummary]
#
# @!attribute [rw] endpoint_status
# The status of the endpoint.
# @return [String]
#
# @!attribute [rw] failure_reason
# If the endpoint failed, the reason it failed.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the endpoint was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last time the endpoint was modified.
# @return [Time]
#
# @!attribute [rw] monitoring_schedules
# A list of monitoring schedules for the endpoint. For information
# about model monitoring, see [Amazon SageMaker Model Monitor][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.html
# @return [Array<Types::MonitoringSchedule>]
#
# @!attribute [rw] tags
# A list of the tags associated with the endpoint. For more
# information, see [Tagging Amazon Web Services resources][1] in the
# *Amazon Web Services General Reference Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] shadow_production_variants
# A list of the shadow variants hosted on the endpoint. Each shadow
# variant is a model in shadow mode with production traffic replicated
# from the production variant.
# @return [Array<Types::ProductionVariantSummary>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Endpoint AWS API Documentation
#
class Endpoint < Struct.new(
:endpoint_name,
:endpoint_arn,
:endpoint_config_name,
:production_variants,
:data_capture_config,
:endpoint_status,
:failure_reason,
:creation_time,
:last_modified_time,
:monitoring_schedules,
:tags,
:shadow_production_variants)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information for an endpoint configuration.
#
# @!attribute [rw] endpoint_config_name
# The name of the endpoint configuration.
# @return [String]
#
# @!attribute [rw] endpoint_config_arn
# The Amazon Resource Name (ARN) of the endpoint configuration.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the endpoint configuration was created.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointConfigSummary AWS API Documentation
#
class EndpointConfigSummary < Struct.new(
:endpoint_config_name,
:endpoint_config_arn,
:creation_time)
SENSITIVE = []
include Aws::Structure
end
# Details about a customer endpoint that was compared in an Inference
# Recommender job.
#
# @!attribute [rw] endpoint_name
# The name of a customer's endpoint.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointInfo AWS API Documentation
#
class EndpointInfo < Struct.new(
:endpoint_name)
SENSITIVE = []
include Aws::Structure
end
# Input object for the endpoint
#
# @!attribute [rw] endpoint_name
# An endpoint in customer's account which has enabled
# `DataCaptureConfig` enabled.
# @return [String]
#
# @!attribute [rw] local_path
# Path to the filesystem where the endpoint data is available to the
# container.
# @return [String]
#
# @!attribute [rw] s3_input_mode
# Whether the `Pipe` or `File` is used as the input mode for
# transferring data for the monitoring job. `Pipe` mode is recommended
# for large datasets. `File` mode is useful for small files that fit
# in memory. Defaults to `File`.
# @return [String]
#
# @!attribute [rw] s3_data_distribution_type
# Whether input data distributed in Amazon S3 is fully replicated or
# sharded by an S3 key. Defaults to `FullyReplicated`
# @return [String]
#
# @!attribute [rw] features_attribute
# The attributes of the input data that are the input features.
# @return [String]
#
# @!attribute [rw] inference_attribute
# The attribute of the input data that represents the ground truth
# label.
# @return [String]
#
# @!attribute [rw] probability_attribute
# In a classification problem, the attribute that represents the class
# probability.
# @return [String]
#
# @!attribute [rw] probability_threshold_attribute
# The threshold for the class probability to be evaluated as a
# positive result.
# @return [Float]
#
# @!attribute [rw] start_time_offset
# If specified, monitoring jobs substract this time from the start
# time. For information about using offsets for scheduling monitoring
# jobs, see [Schedule Model Quality Monitoring Jobs][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html
# @return [String]
#
# @!attribute [rw] end_time_offset
# If specified, monitoring jobs substract this time from the end time.
# For information about using offsets for scheduling monitoring jobs,
# see [Schedule Model Quality Monitoring Jobs][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointInput AWS API Documentation
#
class EndpointInput < Struct.new(
:endpoint_name,
:local_path,
:s3_input_mode,
:s3_data_distribution_type,
:features_attribute,
:inference_attribute,
:probability_attribute,
:probability_threshold_attribute,
:start_time_offset,
:end_time_offset)
SENSITIVE = []
include Aws::Structure
end
# The endpoint configuration for the load test.
#
# @!attribute [rw] instance_type
# The instance types to use for the load test.
# @return [String]
#
# @!attribute [rw] inference_specification_name
# The inference specification name in the model package version.
# @return [String]
#
# @!attribute [rw] environment_parameter_ranges
# The parameter you want to benchmark against.
# @return [Types::EnvironmentParameterRanges]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointInputConfiguration AWS API Documentation
#
class EndpointInputConfiguration < Struct.new(
:instance_type,
:inference_specification_name,
:environment_parameter_ranges)
SENSITIVE = []
include Aws::Structure
end
# The metadata of the endpoint.
#
# @!attribute [rw] endpoint_name
# The name of the endpoint.
# @return [String]
#
# @!attribute [rw] endpoint_config_name
# The name of the endpoint configuration.
# @return [String]
#
# @!attribute [rw] endpoint_status
# The status of the endpoint. For possible values of the status of an
# endpoint, see [EndpointSummary][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_EndpointSummary.html
# @return [String]
#
# @!attribute [rw] failure_reason
# If the status of the endpoint is `Failed`, or the status is
# `InService` but update operation fails, this provides the reason why
# it failed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointMetadata AWS API Documentation
#
class EndpointMetadata < Struct.new(
:endpoint_name,
:endpoint_config_name,
:endpoint_status,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# The endpoint configuration made by Inference Recommender during a
# recommendation job.
#
# @!attribute [rw] endpoint_name
# The name of the endpoint made during a recommendation job.
# @return [String]
#
# @!attribute [rw] variant_name
# The name of the production variant (deployed model) made during a
# recommendation job.
# @return [String]
#
# @!attribute [rw] instance_type
# The instance type recommended by Amazon SageMaker Inference
# Recommender.
# @return [String]
#
# @!attribute [rw] initial_instance_count
# The number of instances recommended to launch initially.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointOutputConfiguration AWS API Documentation
#
class EndpointOutputConfiguration < Struct.new(
:endpoint_name,
:variant_name,
:instance_type,
:initial_instance_count)
SENSITIVE = []
include Aws::Structure
end
# The performance results from running an Inference Recommender job on
# an existing endpoint.
#
# @!attribute [rw] metrics
# The metrics for an existing endpoint.
# @return [Types::InferenceMetrics]
#
# @!attribute [rw] endpoint_info
# Details about a customer endpoint that was compared in an Inference
# Recommender job.
# @return [Types::EndpointInfo]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointPerformance AWS API Documentation
#
class EndpointPerformance < Struct.new(
:metrics,
:endpoint_info)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information for an endpoint.
#
# @!attribute [rw] endpoint_name
# The name of the endpoint.
# @return [String]
#
# @!attribute [rw] endpoint_arn
# The Amazon Resource Name (ARN) of the endpoint.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the endpoint was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that shows when the endpoint was last modified.
# @return [Time]
#
# @!attribute [rw] endpoint_status
# The status of the endpoint.
#
# * `OutOfService`: Endpoint is not available to take incoming
# requests.
#
# * `Creating`: [CreateEndpoint][1] is executing.
#
# * `Updating`: [UpdateEndpoint][2] or
# [UpdateEndpointWeightsAndCapacities][3] is executing.
#
# * `SystemUpdating`: Endpoint is undergoing maintenance and cannot be
# updated or deleted or re-scaled until it has completed. This
# maintenance operation does not change any customer-specified
# values such as VPC config, KMS encryption, model, instance type,
# or instance count.
#
# * `RollingBack`: Endpoint fails to scale up or down or change its
# variant weight and is in the process of rolling back to its
# previous configuration. Once the rollback completes, endpoint
# returns to an `InService` status. This transitional status only
# applies to an endpoint that has autoscaling enabled and is
# undergoing variant weight or capacity changes as part of an
# [UpdateEndpointWeightsAndCapacities][3] call or when the
# [UpdateEndpointWeightsAndCapacities][3] operation is called
# explicitly.
#
# * `InService`: Endpoint is available to process incoming requests.
#
# * `Deleting`: [DeleteEndpoint][4] is executing.
#
# * `Failed`: Endpoint could not be created, updated, or re-scaled.
# Use `DescribeEndpointOutput$FailureReason` for information about
# the failure. [DeleteEndpoint][4] is the only operation that can be
# performed on a failed endpoint.
#
# To get a list of endpoints with a specified status, use the
# `StatusEquals` filter with a call to [ListEndpoints][5].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateEndpoint.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateEndpointWeightsAndCapacities.html
# [4]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DeleteEndpoint.html
# [5]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListEndpoints.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointSummary AWS API Documentation
#
class EndpointSummary < Struct.new(
:endpoint_name,
:endpoint_arn,
:creation_time,
:last_modified_time,
:endpoint_status)
SENSITIVE = []
include Aws::Structure
end
# A list of environment parameters suggested by the Amazon SageMaker
# Inference Recommender.
#
# @!attribute [rw] key
# The environment key suggested by the Amazon SageMaker Inference
# Recommender.
# @return [String]
#
# @!attribute [rw] value_type
# The value type suggested by the Amazon SageMaker Inference
# Recommender.
# @return [String]
#
# @!attribute [rw] value
# The value suggested by the Amazon SageMaker Inference Recommender.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EnvironmentParameter AWS API Documentation
#
class EnvironmentParameter < Struct.new(
:key,
:value_type,
:value)
SENSITIVE = []
include Aws::Structure
end
# Specifies the range of environment parameters
#
# @!attribute [rw] categorical_parameter_ranges
# Specified a list of parameters for each category.
# @return [Array<Types::CategoricalParameter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EnvironmentParameterRanges AWS API Documentation
#
class EnvironmentParameterRanges < Struct.new(
:categorical_parameter_ranges)
SENSITIVE = []
include Aws::Structure
end
# The properties of an experiment as returned by the [Search][1] API.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
#
# @!attribute [rw] experiment_name
# The name of the experiment.
# @return [String]
#
# @!attribute [rw] experiment_arn
# The Amazon Resource Name (ARN) of the experiment.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the experiment as displayed. If `DisplayName` isn't
# specified, `ExperimentName` is displayed.
# @return [String]
#
# @!attribute [rw] source
# The source of the experiment.
# @return [Types::ExperimentSource]
#
# @!attribute [rw] description
# The description of the experiment.
# @return [String]
#
# @!attribute [rw] creation_time
# When the experiment was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Who created the experiment.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the experiment was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] tags
# The list of tags that are associated with the experiment. You can
# use [Search][1] API to search on the tags.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Experiment AWS API Documentation
#
class Experiment < Struct.new(
:experiment_name,
:experiment_arn,
:display_name,
:source,
:description,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:tags)
SENSITIVE = []
include Aws::Structure
end
# Associates a SageMaker job as a trial component with an experiment and
# trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
#
# @!attribute [rw] experiment_name
# The name of an existing experiment to associate with the trial
# component.
# @return [String]
#
# @!attribute [rw] trial_name
# The name of an existing trial to associate the trial component with.
# If not specified, a new trial is created.
# @return [String]
#
# @!attribute [rw] trial_component_display_name
# The display name for the trial component. If this key isn't
# specified, the display name is the trial component name.
# @return [String]
#
# @!attribute [rw] run_name
# The name of the experiment run to associate with the trial
# component.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ExperimentConfig AWS API Documentation
#
class ExperimentConfig < Struct.new(
:experiment_name,
:trial_name,
:trial_component_display_name,
:run_name)
SENSITIVE = []
include Aws::Structure
end
# The source of the experiment.
#
# @!attribute [rw] source_arn
# The Amazon Resource Name (ARN) of the source.
# @return [String]
#
# @!attribute [rw] source_type
# The source type.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ExperimentSource AWS API Documentation
#
class ExperimentSource < Struct.new(
:source_arn,
:source_type)
SENSITIVE = []
include Aws::Structure
end
# A summary of the properties of an experiment. To get the complete set
# of properties, call the [DescribeExperiment][1] API and provide the
# `ExperimentName`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeExperiment.html
#
# @!attribute [rw] experiment_arn
# The Amazon Resource Name (ARN) of the experiment.
# @return [String]
#
# @!attribute [rw] experiment_name
# The name of the experiment.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the experiment as displayed. If `DisplayName` isn't
# specified, `ExperimentName` is displayed.
# @return [String]
#
# @!attribute [rw] experiment_source
# The source of the experiment.
# @return [Types::ExperimentSource]
#
# @!attribute [rw] creation_time
# When the experiment was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# When the experiment was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ExperimentSummary AWS API Documentation
#
class ExperimentSummary < Struct.new(
:experiment_arn,
:experiment_name,
:display_name,
:experiment_source,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# Contains explainability metrics for a model.
#
# @!attribute [rw] report
# The explainability report for a model.
# @return [Types::MetricsSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Explainability AWS API Documentation
#
class Explainability < Struct.new(
:report)
SENSITIVE = []
include Aws::Structure
end
# A parameter to activate explainers.
#
# @!attribute [rw] clarify_explainer_config
# A member of `ExplainerConfig` that contains configuration parameters
# for the SageMaker Clarify explainer.
# @return [Types::ClarifyExplainerConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ExplainerConfig AWS API Documentation
#
class ExplainerConfig < Struct.new(
:clarify_explainer_config)
SENSITIVE = []
include Aws::Structure
end
# The container for the metadata for Fail step.
#
# @!attribute [rw] error_message
# A message that you define and then is processed and rendered by the
# Fail step when the error occurs.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FailStepMetadata AWS API Documentation
#
class FailStepMetadata < Struct.new(
:error_message)
SENSITIVE = []
include Aws::Structure
end
# A list of features. You must include `FeatureName` and `FeatureType`.
# Valid feature `FeatureType`s are `Integral`, `Fractional` and
# `String`.
#
# @!attribute [rw] feature_name
# The name of a feature. The type must be a string. `FeatureName`
# cannot be any of the following: `is_deleted`, `write_time`,
# `api_invocation_time`.
# @return [String]
#
# @!attribute [rw] feature_type
# The value type of a feature. Valid values are Integral, Fractional,
# or String.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FeatureDefinition AWS API Documentation
#
class FeatureDefinition < Struct.new(
:feature_name,
:feature_type)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] feature_group_arn
# The Amazon Resource Name (ARN) of a `FeatureGroup`.
# @return [String]
#
# @!attribute [rw] feature_group_name
# The name of the `FeatureGroup`.
# @return [String]
#
# @!attribute [rw] record_identifier_feature_name
# The name of the `Feature` whose value uniquely identifies a `Record`
# defined in the `FeatureGroup` `FeatureDefinitions`.
# @return [String]
#
# @!attribute [rw] event_time_feature_name
# The name of the feature that stores the `EventTime` of a Record in a
# `FeatureGroup`.
#
# A `EventTime` is point in time when a new event occurs that
# corresponds to the creation or update of a `Record` in
# `FeatureGroup`. All `Records` in the `FeatureGroup` must have a
# corresponding `EventTime`.
# @return [String]
#
# @!attribute [rw] feature_definitions
# A list of `Feature`s. Each `Feature` must include a `FeatureName`
# and a `FeatureType`.
#
# Valid `FeatureType`s are `Integral`, `Fractional` and `String`.
#
# `FeatureName`s cannot be any of the following: `is_deleted`,
# `write_time`, `api_invocation_time`.
#
# You can create up to 2,500 `FeatureDefinition`s per `FeatureGroup`.
# @return [Array<Types::FeatureDefinition>]
#
# @!attribute [rw] creation_time
# The time a `FeatureGroup` was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp indicating the last time you updated the feature group.
# @return [Time]
#
# @!attribute [rw] online_store_config
# Use this to specify the Amazon Web Services Key Management Service
# (KMS) Key ID, or `KMSKeyId`, for at rest data encryption. You can
# turn `OnlineStore` on or off by specifying the `EnableOnlineStore`
# flag at General Assembly.
#
# The default value is `False`.
# @return [Types::OnlineStoreConfig]
#
# @!attribute [rw] offline_store_config
# The configuration of an `OfflineStore`.
#
# Provide an `OfflineStoreConfig` in a request to `CreateFeatureGroup`
# to create an `OfflineStore`.
#
# To encrypt an `OfflineStore` using at rest data encryption, specify
# Amazon Web Services Key Management Service (KMS) key ID, or
# `KMSKeyId`, in `S3StorageConfig`.
# @return [Types::OfflineStoreConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the IAM execution role used to
# create the feature group.
# @return [String]
#
# @!attribute [rw] feature_group_status
# A `FeatureGroup` status.
# @return [String]
#
# @!attribute [rw] offline_store_status
# The status of `OfflineStore`.
# @return [Types::OfflineStoreStatus]
#
# @!attribute [rw] last_update_status
# A value that indicates whether the feature group was updated
# successfully.
# @return [Types::LastUpdateStatus]
#
# @!attribute [rw] failure_reason
# The reason that the `FeatureGroup` failed to be replicated in the
# `OfflineStore`. This is failure may be due to a failure to create a
# `FeatureGroup` in or delete a `FeatureGroup` from the
# `OfflineStore`.
# @return [String]
#
# @!attribute [rw] description
# A free form description of a `FeatureGroup`.
# @return [String]
#
# @!attribute [rw] tags
# Tags used to define a `FeatureGroup`.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FeatureGroup AWS API Documentation
#
class FeatureGroup < Struct.new(
:feature_group_arn,
:feature_group_name,
:record_identifier_feature_name,
:event_time_feature_name,
:feature_definitions,
:creation_time,
:last_modified_time,
:online_store_config,
:offline_store_config,
:role_arn,
:feature_group_status,
:offline_store_status,
:last_update_status,
:failure_reason,
:description,
:tags)
SENSITIVE = []
include Aws::Structure
end
# The name, Arn, `CreationTime`, `FeatureGroup` values,
# `LastUpdatedTime` and `EnableOnlineStorage` status of a
# `FeatureGroup`.
#
# @!attribute [rw] feature_group_name
# The name of `FeatureGroup`.
# @return [String]
#
# @!attribute [rw] feature_group_arn
# Unique identifier for the `FeatureGroup`.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp indicating the time of creation time of the
# `FeatureGroup`.
# @return [Time]
#
# @!attribute [rw] feature_group_status
# The status of a FeatureGroup. The status can be any of the
# following: `Creating`, `Created`, `CreateFail`, `Deleting` or
# `DetailFail`.
# @return [String]
#
# @!attribute [rw] offline_store_status
# Notifies you if replicating data into the `OfflineStore` has failed.
# Returns either: `Active` or `Blocked`.
# @return [Types::OfflineStoreStatus]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FeatureGroupSummary AWS API Documentation
#
class FeatureGroupSummary < Struct.new(
:feature_group_name,
:feature_group_arn,
:creation_time,
:feature_group_status,
:offline_store_status)
SENSITIVE = []
include Aws::Structure
end
# The metadata for a feature. It can either be metadata that you
# specify, or metadata that is updated automatically.
#
# @!attribute [rw] feature_group_arn
# The Amazon Resource Number (ARN) of the feature group.
# @return [String]
#
# @!attribute [rw] feature_group_name
# The name of the feature group containing the feature.
# @return [String]
#
# @!attribute [rw] feature_name
# The name of feature.
# @return [String]
#
# @!attribute [rw] feature_type
# The data type of the feature.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp indicating when the feature was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp indicating when the feature was last modified.
# @return [Time]
#
# @!attribute [rw] description
# An optional description that you specify to better describe the
# feature.
# @return [String]
#
# @!attribute [rw] parameters
# Optional key-value pairs that you specify to better describe the
# feature.
# @return [Array<Types::FeatureParameter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FeatureMetadata AWS API Documentation
#
class FeatureMetadata < Struct.new(
:feature_group_arn,
:feature_group_name,
:feature_name,
:feature_type,
:creation_time,
:last_modified_time,
:description,
:parameters)
SENSITIVE = []
include Aws::Structure
end
# A key-value pair that you specify to describe the feature.
#
# @!attribute [rw] key
# A key that must contain a value to describe the feature.
# @return [String]
#
# @!attribute [rw] value
# The value that belongs to a key.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FeatureParameter AWS API Documentation
#
class FeatureParameter < Struct.new(
:key,
:value)
SENSITIVE = []
include Aws::Structure
end
# Contains details regarding the file source.
#
# @!attribute [rw] content_type
# The type of content stored in the file source.
# @return [String]
#
# @!attribute [rw] content_digest
# The digest of the file source.
# @return [String]
#
# @!attribute [rw] s3_uri
# The Amazon S3 URI for the file source.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FileSource AWS API Documentation
#
class FileSource < Struct.new(
:content_type,
:content_digest,
:s3_uri)
SENSITIVE = []
include Aws::Structure
end
# The Amazon Elastic File System (EFS) storage configuration for a
# SageMaker image.
#
# @!attribute [rw] mount_path
# The path within the image to mount the user's EFS home directory.
# The directory should be empty. If not specified, defaults to
# */home/sagemaker-user*.
# @return [String]
#
# @!attribute [rw] default_uid
# The default POSIX user ID (UID). If not specified, defaults to
# `1000`.
# @return [Integer]
#
# @!attribute [rw] default_gid
# The default POSIX group ID (GID). If not specified, defaults to
# `100`.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FileSystemConfig AWS API Documentation
#
class FileSystemConfig < Struct.new(
:mount_path,
:default_uid,
:default_gid)
SENSITIVE = []
include Aws::Structure
end
# Specifies a file system data source for a channel.
#
# @!attribute [rw] file_system_id
# The file system id.
# @return [String]
#
# @!attribute [rw] file_system_access_mode
# The access mode of the mount of the directory associated with the
# channel. A directory can be mounted either in `ro` (read-only) or
# `rw` (read-write) mode.
# @return [String]
#
# @!attribute [rw] file_system_type
# The file system type.
# @return [String]
#
# @!attribute [rw] directory_path
# The full path to the directory to associate with the channel.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FileSystemDataSource AWS API Documentation
#
class FileSystemDataSource < Struct.new(
:file_system_id,
:file_system_access_mode,
:file_system_type,
:directory_path)
SENSITIVE = []
include Aws::Structure
end
# 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][1]
# API.
#
# If you specify a `Value`, but not an `Operator`, 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 specified `Value` is
# also a decimal value. If the specified `Value` is an integer, the
# decimal hyperparameter values are treated as integers. For example,
# the following filter is satisfied by training jobs with a
# `"learning_rate"` hyperparameter that is less than `"0.5"`:
#
# ` \{`
#
# ` "Name": "HyperParameters.learning_rate",`
#
# ` "Operator": "LessThan",`
#
# ` "Value": "0.5"`
#
# ` \}`
#
# Tags
#
# : To define a tag filter, enter a value with the form `Tags.<key>`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
#
# @!attribute [rw] name
# A resource property name. For example, `TrainingJobName`. For valid
# property names, see [SearchRecord][1]. You must specify a valid
# property for the resource.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_SearchRecord.html
# @return [String]
#
# @!attribute [rw] operator
# A Boolean binary operator that is used to evaluate the filter. The
# operator field contains one of the following values:
#
# Equals
#
# : The value of `Name` equals `Value`.
#
# NotEquals
#
# : The value of `Name` doesn't equal `Value`.
#
# Exists
#
# : The `Name` property exists.
#
# NotExists
#
# : The `Name` property does not exist.
#
# GreaterThan
#
# : The value of `Name` is greater than `Value`. Not supported for
# text properties.
#
# GreaterThanOrEqualTo
#
# : The value of `Name` is greater than or equal to `Value`. Not
# supported for text properties.
#
# LessThan
#
# : The value of `Name` is less than `Value`. Not supported for text
# properties.
#
# LessThanOrEqualTo
#
# : The value of `Name` is less than or equal to `Value`. Not
# supported for text properties.
#
# In
#
# : The value of `Name` is one of the comma delimited strings in
# `Value`. Only supported for text properties.
#
# Contains
#
# : The value of `Name` contains the string `Value`. Only supported
# for text properties.
#
# A `SearchExpression` can include the `Contains` operator multiple
# times when the value of `Name` is one of the following:
#
# * `Experiment.DisplayName`
#
# * `Experiment.ExperimentName`
#
# * `Experiment.Tags`
#
# * `Trial.DisplayName`
#
# * `Trial.TrialName`
#
# * `Trial.Tags`
#
# * `TrialComponent.DisplayName`
#
# * `TrialComponent.TrialComponentName`
#
# * `TrialComponent.Tags`
#
# * `TrialComponent.InputArtifacts`
#
# * `TrialComponent.OutputArtifacts`
#
# A `SearchExpression` can include only one `Contains` operator for
# all other values of `Name`. In these cases, if you include
# multiple `Contains` operators in the `SearchExpression`, the
# result is the following error message: "`'CONTAINS' operator
# usage limit of 1 exceeded.`"
# @return [String]
#
# @!attribute [rw] value
# A value used with `Name` and `Operator` to determine which resources
# satisfy the filter's condition. For numerical properties, `Value`
# must be an integer or floating-point decimal. For timestamp
# properties, `Value` must be an ISO 8601 date-time string of the
# following format: `YYYY-mm-dd'T'HH:MM:SS`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Filter AWS API Documentation
#
class Filter < Struct.new(
:name,
:operator,
:value)
SENSITIVE = []
include Aws::Structure
end
# The best candidate result from an AutoML training job.
#
# @!attribute [rw] type
# The type of metric with the best result.
# @return [String]
#
# @!attribute [rw] metric_name
# The name of the metric with the best result. For a description of
# the possible objective metrics, see
# [AutoMLJobObjective$MetricName][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobObjective.html
# @return [String]
#
# @!attribute [rw] value
# The value of the metric with the best result.
# @return [Float]
#
# @!attribute [rw] standard_metric_name
# The name of the standard metric. For a description of the standard
# metrics, see [Autopilot candidate metrics][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.html#autopilot-metrics
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FinalAutoMLJobObjectiveMetric AWS API Documentation
#
class FinalAutoMLJobObjectiveMetric < Struct.new(
:type,
:metric_name,
:value,
:standard_metric_name)
SENSITIVE = []
include Aws::Structure
end
# Shows the latest objective metric emitted by a training job that was
# launched by a hyperparameter tuning job. You define the objective
# metric in the `HyperParameterTuningJobObjective` parameter of
# [HyperParameterTuningJobConfig][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html
#
# @!attribute [rw] type
# Select if you want to minimize or maximize the objective metric
# during hyperparameter tuning.
# @return [String]
#
# @!attribute [rw] metric_name
# The name of the objective metric. For SageMaker built-in algorithms,
# metrics are defined per algorithm. See the [metrics for XGBoost][1]
# as an example. You can also use a custom algorithm for training and
# define your own metrics. For more information, see [Define metrics
# and environment variables][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/xgboost-tuning.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics-variables.html
# @return [String]
#
# @!attribute [rw] value
# The value of the objective metric.
# @return [Float]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FinalHyperParameterTuningJobObjectiveMetric AWS API Documentation
#
class FinalHyperParameterTuningJobObjectiveMetric < Struct.new(
:type,
:metric_name,
:value)
SENSITIVE = []
include Aws::Structure
end
# Contains information about where human output will be stored.
#
# @!attribute [rw] s3_output_path
# The Amazon S3 path where the object containing human output will be
# made available.
#
# To learn more about the format of Amazon A2I output data, see
# [Amazon A2I Output Data][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-output-data.html
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Key Management Service (KMS) key ID for server-side
# encryption.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FlowDefinitionOutputConfig AWS API Documentation
#
class FlowDefinitionOutputConfig < Struct.new(
:s3_output_path,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# Contains summary information about the flow definition.
#
# @!attribute [rw] flow_definition_name
# The name of the flow definition.
# @return [String]
#
# @!attribute [rw] flow_definition_arn
# The Amazon Resource Name (ARN) of the flow definition.
# @return [String]
#
# @!attribute [rw] flow_definition_status
# The status of the flow definition. Valid values:
# @return [String]
#
# @!attribute [rw] creation_time
# The timestamp when SageMaker created the flow definition.
# @return [Time]
#
# @!attribute [rw] failure_reason
# The reason why the flow definition creation failed. A failure reason
# is returned only when the flow definition status is `Failed`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FlowDefinitionSummary AWS API Documentation
#
class FlowDefinitionSummary < Struct.new(
:flow_definition_name,
:flow_definition_arn,
:flow_definition_status,
:creation_time,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetDeviceFleetReportRequest AWS API Documentation
#
class GetDeviceFleetReportRequest < Struct.new(
:device_fleet_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_arn
# The Amazon Resource Name (ARN) of the device.
# @return [String]
#
# @!attribute [rw] device_fleet_name
# The name of the fleet.
# @return [String]
#
# @!attribute [rw] output_config
# The output configuration for storing sample data collected by the
# fleet.
# @return [Types::EdgeOutputConfig]
#
# @!attribute [rw] description
# Description of the fleet.
# @return [String]
#
# @!attribute [rw] report_generated
# Timestamp of when the report was generated.
# @return [Time]
#
# @!attribute [rw] device_stats
# Status of devices.
# @return [Types::DeviceStats]
#
# @!attribute [rw] agent_versions
# The versions of Edge Manager agent deployed on the fleet.
# @return [Array<Types::AgentVersion>]
#
# @!attribute [rw] model_stats
# Status of model on device.
# @return [Array<Types::EdgeModelStat>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetDeviceFleetReportResponse AWS API Documentation
#
class GetDeviceFleetReportResponse < Struct.new(
:device_fleet_arn,
:device_fleet_name,
:output_config,
:description,
:report_generated,
:device_stats,
:agent_versions,
:model_stats)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] lineage_group_name
# The name or Amazon Resource Name (ARN) of the lineage group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetLineageGroupPolicyRequest AWS API Documentation
#
class GetLineageGroupPolicyRequest < Struct.new(
:lineage_group_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] lineage_group_arn
# The Amazon Resource Name (ARN) of the lineage group.
# @return [String]
#
# @!attribute [rw] resource_policy
# The resource policy that gives access to the lineage group in
# another account.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetLineageGroupPolicyResponse AWS API Documentation
#
class GetLineageGroupPolicyResponse < Struct.new(
:lineage_group_arn,
:resource_policy)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_name
# The name of the model group for which to get the resource policy.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetModelPackageGroupPolicyInput AWS API Documentation
#
class GetModelPackageGroupPolicyInput < Struct.new(
:model_package_group_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] resource_policy
# The resource policy for the model group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetModelPackageGroupPolicyOutput AWS API Documentation
#
class GetModelPackageGroupPolicyOutput < Struct.new(
:resource_policy)
SENSITIVE = []
include Aws::Structure
end
# @api private
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetSagemakerServicecatalogPortfolioStatusInput AWS API Documentation
#
class GetSagemakerServicecatalogPortfolioStatusInput < Aws::EmptyStructure; end
# @!attribute [rw] status
# Whether Service Catalog is enabled or disabled in SageMaker.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetSagemakerServicecatalogPortfolioStatusOutput AWS API Documentation
#
class GetSagemakerServicecatalogPortfolioStatusOutput < Struct.new(
:status)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] resource
# The name of the SageMaker resource to search for.
# @return [String]
#
# @!attribute [rw] suggestion_query
# Limits the property names that are included in the response.
# @return [Types::SuggestionQuery]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetSearchSuggestionsRequest AWS API Documentation
#
class GetSearchSuggestionsRequest < Struct.new(
:resource,
:suggestion_query)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] property_name_suggestions
# A list of property names for a `Resource` that match a
# `SuggestionQuery`.
# @return [Array<Types::PropertyNameSuggestion>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetSearchSuggestionsResponse AWS API Documentation
#
class GetSearchSuggestionsResponse < Struct.new(
:property_name_suggestions)
SENSITIVE = []
include Aws::Structure
end
# Specifies configuration details for a Git repository in your Amazon
# Web Services account.
#
# @!attribute [rw] repository_url
# The URL where the Git repository is located.
# @return [String]
#
# @!attribute [rw] branch
# The default branch for the Git repository.
# @return [String]
#
# @!attribute [rw] secret_arn
# The Amazon Resource Name (ARN) of the Amazon Web Services Secrets
# Manager secret that contains the credentials used to access the git
# repository. The secret must have a staging label of `AWSCURRENT` and
# must be in the following format:
#
# `\{"username": UserName, "password": Password\}`
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GitConfig AWS API Documentation
#
class GitConfig < Struct.new(
:repository_url,
:branch,
:secret_arn)
SENSITIVE = []
include Aws::Structure
end
# Specifies configuration details for a Git repository when the
# repository is updated.
#
# @!attribute [rw] secret_arn
# The Amazon Resource Name (ARN) of the Amazon Web Services Secrets
# Manager secret that contains the credentials used to access the git
# repository. The secret must have a staging label of `AWSCURRENT` and
# must be in the following format:
#
# `\{"username": UserName, "password": Password\}`
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GitConfigForUpdate AWS API Documentation
#
class GitConfigForUpdate < Struct.new(
:secret_arn)
SENSITIVE = []
include Aws::Structure
end
# Any dependencies related to hub content, such as scripts, model
# artifacts, datasets, or notebooks.
#
# @!attribute [rw] dependency_origin_path
# The hub content dependency origin path.
# @return [String]
#
# @!attribute [rw] dependency_copy_path
# The hub content dependency copy path.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HubContentDependency AWS API Documentation
#
class HubContentDependency < Struct.new(
:dependency_origin_path,
:dependency_copy_path)
SENSITIVE = []
include Aws::Structure
end
# Information about hub content.
#
# @!attribute [rw] hub_content_name
# The name of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_arn
# The Amazon Resource Name (ARN) of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_version
# The version of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_type
# The type of hub content.
# @return [String]
#
# @!attribute [rw] document_schema_version
# The version of the hub content document schema.
# @return [String]
#
# @!attribute [rw] hub_content_display_name
# The display name of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_description
# A description of the hub content.
# @return [String]
#
# @!attribute [rw] hub_content_search_keywords
# The searchable keywords for the hub content.
# @return [Array<String>]
#
# @!attribute [rw] hub_content_status
# The status of the hub content.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the hub content was created.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HubContentInfo AWS API Documentation
#
class HubContentInfo < Struct.new(
:hub_content_name,
:hub_content_arn,
:hub_content_version,
:hub_content_type,
:document_schema_version,
:hub_content_display_name,
:hub_content_description,
:hub_content_search_keywords,
:hub_content_status,
:creation_time)
SENSITIVE = []
include Aws::Structure
end
# Information about a hub.
#
# @!attribute [rw] hub_name
# The name of the hub.
# @return [String]
#
# @!attribute [rw] hub_arn
# The Amazon Resource Name (ARN) of the hub.
# @return [String]
#
# @!attribute [rw] hub_display_name
# The display name of the hub.
# @return [String]
#
# @!attribute [rw] hub_description
# A description of the hub.
# @return [String]
#
# @!attribute [rw] hub_search_keywords
# The searchable keywords for the hub.
# @return [Array<String>]
#
# @!attribute [rw] hub_status
# The status of the hub.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the hub was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the hub was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HubInfo AWS API Documentation
#
class HubInfo < Struct.new(
:hub_name,
:hub_arn,
:hub_display_name,
:hub_description,
:hub_search_keywords,
:hub_status,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# The Amazon S3 storage configuration of a hub.
#
# @!attribute [rw] s3_output_path
# The Amazon S3 bucket prefix for hosting hub content.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HubS3StorageConfig AWS API Documentation
#
class HubS3StorageConfig < Struct.new(
:s3_output_path)
SENSITIVE = []
include Aws::Structure
end
# Defines under what conditions SageMaker creates a human loop. Used
# within [CreateFlowDefinition][1]. See
# [HumanLoopActivationConditionsConfig][2] for the required format of
# activation conditions.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateFlowDefinition.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HumanLoopActivationConditionsConfig.html
#
# @!attribute [rw] human_loop_activation_conditions
# JSON expressing use-case specific conditions declaratively. If any
# condition is matched, atomic tasks are created against the
# configured work team. The set of conditions is different for
# Rekognition and Textract. For more information about how to
# structure the JSON, see [JSON Schema for Human Loop Activation
# Conditions in Amazon Augmented AI][1] in the *Amazon SageMaker
# Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-human-fallback-conditions-json-schema.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HumanLoopActivationConditionsConfig AWS API Documentation
#
class HumanLoopActivationConditionsConfig < Struct.new(
:human_loop_activation_conditions)
SENSITIVE = []
include Aws::Structure
end
# Provides information about how and under what conditions SageMaker
# creates a human loop. If `HumanLoopActivationConfig` is not given,
# then all requests go to humans.
#
# @!attribute [rw] human_loop_activation_conditions_config
# Container structure for defining under what conditions SageMaker
# creates a human loop.
# @return [Types::HumanLoopActivationConditionsConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HumanLoopActivationConfig AWS API Documentation
#
class HumanLoopActivationConfig < Struct.new(
:human_loop_activation_conditions_config)
SENSITIVE = []
include Aws::Structure
end
# Describes the work to be performed by human workers.
#
# @!attribute [rw] workteam_arn
# Amazon Resource Name (ARN) of a team of workers. To learn more about
# the types of workforces and work teams you can create and use with
# Amazon A2I, see [Create and Manage Workforces][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-management.html
# @return [String]
#
# @!attribute [rw] human_task_ui_arn
# The Amazon Resource Name (ARN) of the human task user interface.
#
# You can use standard HTML and Crowd HTML Elements to create a custom
# worker task template. You use this template to create a human task
# UI.
#
# To learn how to create a custom HTML template, see [Create Custom
# Worker Task Template][1].
#
# To learn how to create a human task UI, which is a worker task
# template that can be used in a flow definition, see [Create and
# Delete a Worker Task Templates][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-custom-templates.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/a2i-worker-template-console.html
# @return [String]
#
# @!attribute [rw] task_title
# A title for the human worker task.
# @return [String]
#
# @!attribute [rw] task_description
# A description for the human worker task.
# @return [String]
#
# @!attribute [rw] task_count
# The number of distinct workers who will perform the same task on
# each object. For example, if `TaskCount` is set to `3` for an image
# classification labeling job, three workers will classify each input
# image. Increasing `TaskCount` can improve label accuracy.
# @return [Integer]
#
# @!attribute [rw] task_availability_lifetime_in_seconds
# The length of time that a task remains available for review by human
# workers.
# @return [Integer]
#
# @!attribute [rw] task_time_limit_in_seconds
# The amount of time that a worker has to complete a task. The default
# value is 3,600 seconds (1 hour).
# @return [Integer]
#
# @!attribute [rw] task_keywords
# Keywords used to describe the task so that workers can discover the
# task.
# @return [Array<String>]
#
# @!attribute [rw] 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
# @return [Types::PublicWorkforceTaskPrice]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HumanLoopConfig AWS API Documentation
#
class HumanLoopConfig < Struct.new(
:workteam_arn,
:human_task_ui_arn,
:task_title,
:task_description,
:task_count,
:task_availability_lifetime_in_seconds,
:task_time_limit_in_seconds,
:task_keywords,
:public_workforce_task_price)
SENSITIVE = []
include Aws::Structure
end
# Container for configuring the source of human task requests.
#
# @!attribute [rw] aws_managed_human_loop_request_source
# Specifies whether Amazon Rekognition or Amazon Textract are used as
# the integration source. The default field settings and JSON parsing
# rules are different based on the integration source. Valid values:
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HumanLoopRequestSource AWS API Documentation
#
class HumanLoopRequestSource < Struct.new(
:aws_managed_human_loop_request_source)
SENSITIVE = []
include Aws::Structure
end
# Information required for human workers to complete a labeling task.
#
# @!attribute [rw] workteam_arn
# The Amazon Resource Name (ARN) of the work team assigned to complete
# the tasks.
# @return [String]
#
# @!attribute [rw] ui_config
# Information about the user interface that workers use to complete
# the labeling task.
# @return [Types::UiConfig]
#
# @!attribute [rw] pre_human_task_lambda_arn
# The Amazon Resource Name (ARN) of a Lambda function that is run
# before a data object is sent to a human worker. Use this function to
# provide input to a custom labeling job.
#
# For [built-in task types][1], use one of the following Amazon
# SageMaker Ground Truth Lambda function ARNs for
# `PreHumanTaskLambdaArn`. For custom labeling workflows, see
# [Pre-annotation Lambda][2].
#
# **Bounding box** - Finds the most similar boxes from different
# workers based on the Jaccard index of the boxes.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-BoundingBox`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-BoundingBox`
#
# **Image classification** - Uses a variant of the Expectation
# Maximization approach to estimate the true class of an image based
# on annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClass`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClass`
#
# **Multi-label image classification** - Uses a variant of the
# Expectation Maximization approach to estimate the true classes of an
# image based on annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-ImageMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-ImageMultiClassMultiLabel`
#
# **Semantic segmentation** - Treats each pixel in an image as a
# multi-class classification and treats pixel annotations from workers
# as "votes" for the correct label.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-SemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-SemanticSegmentation`
#
# **Text classification** - Uses a variant of the Expectation
# Maximization approach to estimate the true class of text based on
# annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClass`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClass`
#
# **Multi-label text classification** - Uses a variant of the
# Expectation Maximization approach to estimate the true classes of
# text based on annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-TextMultiClassMultiLabel`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-TextMultiClassMultiLabel`
#
# **Named entity recognition** - Groups similar selections and
# calculates aggregate boundaries, resolving to most-assigned label.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-NamedEntityRecognition`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-NamedEntityRecognition`
#
# **Video Classification** - Use this task type when you need workers
# to classify videos using predefined labels that you specify. Workers
# are shown videos and are asked to choose one label for each video.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoMultiClass`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoMultiClass`
#
# **Video Frame Object Detection** - Use this task type to have
# workers identify and locate objects in a sequence of video frames
# (images extracted from a video) using bounding boxes. For example,
# you can use this task to ask workers to identify and localize
# various objects in a series of video frames, such as cars, bikes,
# and pedestrians.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectDetection`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectDetection`
#
# **Video Frame Object Tracking** - Use this task type to have workers
# track the movement of objects in a sequence of video frames (images
# extracted from a video) using bounding boxes. For example, you can
# use this task to ask workers to track the movement of objects, such
# as cars, bikes, and pedestrians.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VideoObjectTracking`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-VideoObjectTracking`
#
# **3D Point Cloud Modalities**
#
# Use the following pre-annotation lambdas for 3D point cloud labeling
# modality tasks. See [3D Point Cloud Task types ][3] to learn more.
#
# **3D Point Cloud Object Detection** - Use this task type when you
# want workers to classify objects in a 3D point cloud by drawing 3D
# cuboids around objects. For example, you can use this task type to
# ask workers to identify different types of objects in a point cloud,
# such as cars, bikes, and pedestrians.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectDetection`
#
# **3D Point Cloud Object Tracking** - Use this task type when you
# want workers to draw 3D cuboids around objects that appear in a
# sequence of 3D point cloud frames. For example, you can use this
# task type to ask workers to track the movement of vehicles across
# multiple point cloud frames.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudObjectTracking`
#
# **3D Point Cloud Semantic Segmentation** - Use this task type when
# you want workers to create a point-level semantic segmentation masks
# by painting objects in a 3D point cloud using different colors where
# each color is assigned to one of the classes you specify.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-3DPointCloudSemanticSegmentation`
#
# **Use the following ARNs for Label Verification and Adjustment
# Jobs**
#
# Use label verification and adjustment jobs to review and adjust
# labels. To learn more, see [Verify and Adjust Labels ][4].
#
# **Bounding box verification** - Uses a variant of the Expectation
# Maximization approach to estimate the true class of verification
# judgement for bounding box labels based on annotations from
# individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationBoundingBox`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationBoundingBox`
#
# **Bounding box adjustment** - Finds the most similar boxes from
# different workers based on the Jaccard index of the adjusted
# annotations.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentBoundingBox`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentBoundingBox`
#
# **Semantic segmentation verification** - Uses a variant of the
# Expectation Maximization approach to estimate the true class of
# verification judgment for semantic segmentation labels based on
# annotations from individual workers.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-VerificationSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-VerificationSemanticSegmentation`
#
# **Semantic segmentation adjustment** - Treats each pixel in an image
# as a multi-class classification and treats pixel adjusted
# annotations from workers as "votes" for the correct label.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentSemanticSegmentation`
#
# **Video Frame Object Detection Adjustment** - Use this task type
# when you want workers to adjust bounding boxes that workers have
# added to video frames to classify and localize objects in a sequence
# of video frames.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectDetection`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectDetection`
#
# **Video Frame Object Tracking Adjustment** - Use this task type when
# you want workers to adjust bounding boxes that workers have added to
# video frames to track object movement across a sequence of video
# frames.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-AdjustmentVideoObjectTracking`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-AdjustmentVideoObjectTracking`
#
# **3D point cloud object detection adjustment** - Adjust 3D cuboids
# in a point cloud frame.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectDetection`
#
# **3D point cloud object tracking adjustment** - Adjust 3D cuboids
# across a sequence of point cloud frames.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudObjectTracking`
#
# **3D point cloud semantic segmentation adjustment** - Adjust
# semantic segmentation masks in a 3D point cloud.
#
# * `arn:aws:lambda:us-east-1:432418664414:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-east-2:266458841044:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:us-west-2:081040173940:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-1:568282634449:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-1:477331159723:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-2:454466003867:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-south-1:565803892007:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-central-1:203001061592:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-northeast-2:845288260483:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:eu-west-2:487402164563:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ap-southeast-1:377565633583:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
# * `arn:aws:lambda:ca-central-1:918755190332:function:PRE-Adjustment3DPointCloudSemanticSegmentation`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-prelambda
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud-task-types.html
# [4]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.html
# @return [String]
#
# @!attribute [rw] task_keywords
# Keywords used to describe the task so that workers on Amazon
# Mechanical Turk can discover the task.
# @return [Array<String>]
#
# @!attribute [rw] task_title
# A title for the task for your human workers.
# @return [String]
#
# @!attribute [rw] task_description
# A description of the task for your human workers.
# @return [String]
#
# @!attribute [rw] number_of_human_workers_per_data_object
# The number of human workers that will label an object.
# @return [Integer]
#
# @!attribute [rw] task_time_limit_in_seconds
# The amount of time that a worker has to complete a task.
#
# If you create a custom labeling job, the maximum value for this
# parameter is 8 hours (28,800 seconds).
#
# If you create a labeling job using a [built-in task type][1] the
# maximum for this parameter depends on the task type you use:
#
# * For [image][2] and [text][3] labeling jobs, the maximum is 8 hours
# (28,800 seconds).
#
# * For [3D point cloud][4] and [video frame][5] labeling jobs, the
# maximum is 30 days (2952,000 seconds) for non-AL mode. For most
# users, the maximum is also 30 days.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-images.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-label-text.html
# [4]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-point-cloud.html
# [5]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-video.html
# @return [Integer]
#
# @!attribute [rw] task_availability_lifetime_in_seconds
# The length of time that a task remains available for labeling by
# human workers. The default and maximum values for this parameter
# depend on the type of workforce you use.
#
# * If you choose the Amazon Mechanical Turk workforce, the maximum is
# 12 hours (43,200 seconds). The default is 6 hours (21,600
# seconds).
#
# * If you choose a private or vendor workforce, the default value is
# 30 days (2592,000 seconds) for non-AL mode. For most users, the
# maximum is also 30 days.
# @return [Integer]
#
# @!attribute [rw] max_concurrent_task_count
# Defines the maximum number of data objects that can be labeled by
# human workers at the same time. Also referred to as batch size. Each
# object may have more than one worker at one time. The default value
# is 1000 objects. To increase the maximum value to 5000 objects,
# contact Amazon Web Services Support.
# @return [Integer]
#
# @!attribute [rw] annotation_consolidation_config
# Configures how labels are consolidated across human workers.
# @return [Types::AnnotationConsolidationConfig]
#
# @!attribute [rw] public_workforce_task_price
# The price that you pay for each task performed by an Amazon
# Mechanical Turk worker.
# @return [Types::PublicWorkforceTaskPrice]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HumanTaskConfig AWS API Documentation
#
class HumanTaskConfig < Struct.new(
:workteam_arn,
:ui_config,
:pre_human_task_lambda_arn,
:task_keywords,
:task_title,
:task_description,
:number_of_human_workers_per_data_object,
:task_time_limit_in_seconds,
:task_availability_lifetime_in_seconds,
:max_concurrent_task_count,
:annotation_consolidation_config,
:public_workforce_task_price)
SENSITIVE = []
include Aws::Structure
end
# Container for human task user interface information.
#
# @!attribute [rw] human_task_ui_name
# The name of the human task user interface.
# @return [String]
#
# @!attribute [rw] human_task_ui_arn
# The Amazon Resource Name (ARN) of the human task user interface.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp when SageMaker created the human task user interface.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HumanTaskUiSummary AWS API Documentation
#
class HumanTaskUiSummary < Struct.new(
:human_task_ui_name,
:human_task_ui_arn,
:creation_time)
SENSITIVE = []
include Aws::Structure
end
# Specifies which training algorithm to use for training jobs that a
# hyperparameter tuning job launches and the metrics to monitor.
#
# @!attribute [rw] training_image
# The registry path of the Docker image that contains the training
# algorithm. For information about Docker registry paths for built-in
# algorithms, see [Algorithms Provided by Amazon SageMaker: Common
# Parameters][1]. SageMaker supports both `registry/repository[:tag]`
# and `registry/repository[@digest]` image path formats. For more
# information, see [Using Your Own Algorithms with Amazon
# SageMaker][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html
# @return [String]
#
# @!attribute [rw] training_input_mode
# The training input mode that the algorithm supports. For more
# information about input modes, see [Algorithms][1].
#
# **Pipe mode**
#
# If an algorithm supports `Pipe` mode, Amazon SageMaker streams data
# directly from Amazon S3 to the container.
#
# **File mode**
#
# If an algorithm supports `File` mode, SageMaker downloads the
# training data from S3 to the provisioned ML storage volume, and
# mounts the directory to the Docker volume for the training
# container.
#
# You must provision the ML storage volume with sufficient capacity to
# accommodate the data downloaded from S3. In addition to the training
# data, the ML storage volume also stores the output model. The
# algorithm container uses the ML storage volume to also store
# intermediate information, if any.
#
# For distributed algorithms, training data is distributed uniformly.
# Your training duration is predictable if the input data objects
# sizes are approximately the same. SageMaker does not split the files
# any further for model training. If the object sizes are skewed,
# training won't be optimal as the data distribution is also skewed
# when one host in a training cluster is overloaded, thus becoming a
# bottleneck in training.
#
# **FastFile mode**
#
# If an algorithm supports `FastFile` mode, SageMaker streams data
# directly from S3 to the container with no code changes, and provides
# file system access to the data. Users can author their training
# script to interact with these files as if they were stored on disk.
#
# `FastFile` mode works best when the data is read sequentially.
# Augmented manifest files aren't supported. The startup time is
# lower when there are fewer files in the S3 bucket provided.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
# @return [String]
#
# @!attribute [rw] algorithm_name
# The name of the resource algorithm to use for the hyperparameter
# tuning job. If you specify a value for this parameter, do not
# specify a value for `TrainingImage`.
# @return [String]
#
# @!attribute [rw] metric_definitions
# An array of [MetricDefinition][1] objects that specify the metrics
# that the algorithm emits.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_MetricDefinition.html
# @return [Array<Types::MetricDefinition>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterAlgorithmSpecification AWS API Documentation
#
class HyperParameterAlgorithmSpecification < Struct.new(
:training_image,
:training_input_mode,
:algorithm_name,
:metric_definitions)
SENSITIVE = []
include Aws::Structure
end
# Defines a hyperparameter to be used by an algorithm.
#
# @!attribute [rw] name
# The name of this hyperparameter. The name must be unique.
# @return [String]
#
# @!attribute [rw] description
# A brief description of the hyperparameter.
# @return [String]
#
# @!attribute [rw] type
# The type of this hyperparameter. The valid types are `Integer`,
# `Continuous`, `Categorical`, and `FreeText`.
# @return [String]
#
# @!attribute [rw] range
# The allowed range for this hyperparameter.
# @return [Types::ParameterRange]
#
# @!attribute [rw] is_tunable
# Indicates whether this hyperparameter is tunable in a hyperparameter
# tuning job.
# @return [Boolean]
#
# @!attribute [rw] is_required
# Indicates whether this hyperparameter is required.
# @return [Boolean]
#
# @!attribute [rw] default_value
# The default value for this hyperparameter. If a default value is
# specified, a hyperparameter cannot be required.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterSpecification AWS API Documentation
#
class HyperParameterSpecification < Struct.new(
:name,
:description,
:type,
:range,
:is_tunable,
:is_required,
:default_value)
SENSITIVE = []
include Aws::Structure
end
# Defines the training jobs launched by a hyperparameter tuning job.
#
# @!attribute [rw] definition_name
# The job definition name.
# @return [String]
#
# @!attribute [rw] tuning_objective
# Defines the objective metric for a hyperparameter tuning job.
# Hyperparameter tuning uses the value of this metric to evaluate the
# training jobs it launches, and returns the training job that results
# in either the highest or lowest value for this metric, depending on
# the value you specify for the `Type` parameter.
# @return [Types::HyperParameterTuningJobObjective]
#
# @!attribute [rw] hyper_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.
#
# <note markdown="1"> The maximum number of items specified for `Array Members` refers to
# the maximum number of hyperparameters for each range and also the
# maximum for the hyperparameter tuning job itself. That is, the sum
# of the number of hyperparameters for all the ranges can't exceed
# the maximum number specified.
#
# </note>
# @return [Types::ParameterRanges]
#
# @!attribute [rw] static_hyper_parameters
# Specifies the values of hyperparameters that do not change for the
# tuning job.
# @return [Hash<String,String>]
#
# @!attribute [rw] algorithm_specification
# The [HyperParameterAlgorithmSpecification][1] object that specifies
# the resource algorithm to use for the training jobs that the tuning
# job launches.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterAlgorithmSpecification.html
# @return [Types::HyperParameterAlgorithmSpecification]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the IAM role associated with the
# training jobs that the tuning job launches.
# @return [String]
#
# @!attribute [rw] input_data_config
# An array of [Channel][1] objects that specify the input for the
# training jobs that the tuning job launches.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Channel.html
# @return [Array<Types::Channel>]
#
# @!attribute [rw] vpc_config
# The [VpcConfig][1] object that specifies the VPC that you want the
# training jobs that this hyperparameter tuning job launches to
# connect to. Control access to and from your training container by
# configuring the VPC. For more information, see [Protect Training
# Jobs by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
# @return [Types::VpcConfig]
#
# @!attribute [rw] output_data_config
# Specifies the path to the Amazon S3 bucket where you store model
# artifacts from the training jobs that the tuning job launches.
# @return [Types::OutputDataConfig]
#
# @!attribute [rw] resource_config
# The resources, including the compute instances and storage volumes,
# to use for the training jobs that the tuning job launches.
#
# Storage volumes store model artifacts and incremental states.
# Training algorithms might also use storage volumes for scratch
# space. If you want SageMaker to use the storage volume to store the
# training data, choose `File` as the `TrainingInputMode` in the
# algorithm specification. For distributed training algorithms,
# specify an instance count greater than 1.
#
# <note markdown="1"> If you want to use hyperparameter optimization with instance type
# flexibility, use `HyperParameterTuningResourceConfig` instead.
#
# </note>
# @return [Types::ResourceConfig]
#
# @!attribute [rw] stopping_condition
# Specifies a limit to how long a model hyperparameter training job
# can run. It also specifies how long a managed spot training job has
# to complete. When the job reaches the time limit, SageMaker ends the
# training job. Use this API to cap model training costs.
# @return [Types::StoppingCondition]
#
# @!attribute [rw] enable_network_isolation
# Isolates the training container. No inbound or outbound network
# calls can be made, except for calls between peers within a training
# cluster for distributed training. If network isolation is used for
# training jobs that are configured to use a VPC, SageMaker downloads
# and uploads customer data and model artifacts through the specified
# VPC, but the training container does not have network access.
# @return [Boolean]
#
# @!attribute [rw] enable_inter_container_traffic_encryption
# To encrypt all communications between ML compute instances in
# distributed training, choose `True`. Encryption provides greater
# security for distributed training, but training might take longer.
# How long it takes depends on the amount of communication between
# compute instances, especially if you use a deep learning algorithm
# in distributed training.
# @return [Boolean]
#
# @!attribute [rw] enable_managed_spot_training
# A Boolean indicating whether managed spot training is enabled
# (`True`) or not (`False`).
# @return [Boolean]
#
# @!attribute [rw] checkpoint_config
# Contains information about the output location for managed spot
# training checkpoint data.
# @return [Types::CheckpointConfig]
#
# @!attribute [rw] retry_strategy
# The number of times to retry the job when the job fails due to an
# `InternalServerError`.
# @return [Types::RetryStrategy]
#
# @!attribute [rw] hyper_parameter_tuning_resource_config
# The configuration for the hyperparameter tuning resources, including
# the compute instances and storage volumes, used for training jobs
# launched by the tuning job. By default, storage volumes hold model
# artifacts and incremental states. Choose `File` for
# `TrainingInputMode` in the `AlgorithmSpecification` parameter to
# additionally store training data in the storage volume (optional).
# @return [Types::HyperParameterTuningResourceConfig]
#
# @!attribute [rw] environment
# An environment variable that you can pass into the SageMaker
# [CreateTrainingJob][1] API. You can use an existing [environment
# variable from the training container][2] or use your own. See
# [Define metrics and variables][3] for more information.
#
# <note markdown="1"> The maximum number of items specified for `Map Entries` refers to
# the maximum number of environment variables for each
# `TrainingJobDefinition` and also the maximum for the hyperparameter
# tuning job itself. That is, the sum of the number of environment
# variables for all the training job definitions can't exceed the
# maximum number specified.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html#sagemaker-CreateTrainingJob-request-Environment
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics-variables.html
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTrainingJobDefinition AWS API Documentation
#
class HyperParameterTrainingJobDefinition < Struct.new(
:definition_name,
:tuning_objective,
:hyper_parameter_ranges,
:static_hyper_parameters,
:algorithm_specification,
:role_arn,
:input_data_config,
:vpc_config,
:output_data_config,
:resource_config,
:stopping_condition,
:enable_network_isolation,
:enable_inter_container_traffic_encryption,
:enable_managed_spot_training,
:checkpoint_config,
:retry_strategy,
:hyper_parameter_tuning_resource_config,
:environment)
SENSITIVE = []
include Aws::Structure
end
# The container for the summary information about a training job.
#
# @!attribute [rw] training_job_definition_name
# The training job definition name.
# @return [String]
#
# @!attribute [rw] training_job_name
# The name of the training job.
# @return [String]
#
# @!attribute [rw] training_job_arn
# The Amazon Resource Name (ARN) of the training job.
# @return [String]
#
# @!attribute [rw] tuning_job_name
# The HyperParameter tuning job that launched the training job.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the training job was created.
# @return [Time]
#
# @!attribute [rw] training_start_time
# The date and time that the training job started.
# @return [Time]
#
# @!attribute [rw] training_end_time
# Specifies the time when the training job ends on training instances.
# You are billed for the time interval between the value of
# `TrainingStartTime` and this time. For successful jobs and stopped
# jobs, this is the time after model artifacts are uploaded. For
# failed jobs, this is the time when SageMaker detects a job failure.
# @return [Time]
#
# @!attribute [rw] training_job_status
# The status of the training job.
# @return [String]
#
# @!attribute [rw] tuned_hyper_parameters
# A list of the hyperparameters for which you specified ranges to
# search.
# @return [Hash<String,String>]
#
# @!attribute [rw] failure_reason
# The reason that the training job failed.
# @return [String]
#
# @!attribute [rw] final_hyper_parameter_tuning_job_objective_metric
# The [FinalHyperParameterTuningJobObjectiveMetric][1] object that
# specifies the value of the objective metric of the tuning job that
# launched this training job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_FinalHyperParameterTuningJobObjectiveMetric.html
# @return [Types::FinalHyperParameterTuningJobObjectiveMetric]
#
# @!attribute [rw] objective_status
# The status of the objective metric for the training job:
#
# * Succeeded: The final objective metric for the training job was
# evaluated by the hyperparameter tuning job and used in the
# hyperparameter tuning process.
#
# ^
# ^
#
# * Pending: The training job is in progress and evaluation of its
# final objective metric is pending.
#
# ^
# ^
#
# * Failed: The final objective metric for the training job was not
# evaluated, and was not used in the hyperparameter tuning process.
# This typically occurs when the training job failed or did not emit
# an objective metric.
#
# ^
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTrainingJobSummary AWS API Documentation
#
class HyperParameterTrainingJobSummary < Struct.new(
:training_job_definition_name,
:training_job_name,
:training_job_arn,
:tuning_job_name,
:creation_time,
:training_start_time,
:training_end_time,
:training_job_status,
:tuned_hyper_parameters,
:failure_reason,
:final_hyper_parameter_tuning_job_objective_metric,
:objective_status)
SENSITIVE = []
include Aws::Structure
end
# The configuration for hyperparameter tuning resources for use in
# training jobs launched by the tuning job. These resources include
# compute instances and storage volumes. Specify one or more compute
# instance configurations and allocation strategies to select resources
# (optional).
#
# @!attribute [rw] instance_type
# The instance type used for processing of hyperparameter optimization
# jobs. Choose from general purpose (no GPUs) instance types:
# ml.m5.xlarge, ml.m5.2xlarge, and ml.m5.4xlarge or compute optimized
# (no GPUs) instance types: ml.c5.xlarge and ml.c5.2xlarge. For more
# information about instance types, see [instance type
# descriptions][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebooks-available-instance-types.html
# @return [String]
#
# @!attribute [rw] instance_count
# The number of instances of the type specified by `InstanceType`.
# Choose an instance count larger than 1 for distributed training
# algorithms. See [SageMaker distributed training jobs][1] for more
# information.
#
#
#
# [1]: https://docs.aws.amazon.com/data-parallel-use-api.html
# @return [Integer]
#
# @!attribute [rw] volume_size_in_gb
# The volume size in GB of the data to be processed for hyperparameter
# optimization (optional).
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningInstanceConfig AWS API Documentation
#
class HyperParameterTuningInstanceConfig < Struct.new(
:instance_type,
:instance_count,
:volume_size_in_gb)
SENSITIVE = []
include Aws::Structure
end
# A structure that contains runtime information about both current and
# completed hyperparameter tuning jobs.
#
# @!attribute [rw] number_of_training_jobs_objective_not_improving
# The number of training jobs launched by a tuning job that are not
# improving (1% or less) as measured by model performance evaluated
# against an objective function.
# @return [Integer]
#
# @!attribute [rw] convergence_detected_time
# The time in timestamp format that AMT detected model convergence, as
# defined by a lack of significant improvement over time based on
# criteria developed over a wide range of diverse benchmarking tests.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobCompletionDetails AWS API Documentation
#
class HyperParameterTuningJobCompletionDetails < Struct.new(
:number_of_training_jobs_objective_not_improving,
:convergence_detected_time)
SENSITIVE = []
include Aws::Structure
end
# Configures a hyperparameter tuning job.
#
# @!attribute [rw] strategy
# Specifies how hyperparameter tuning chooses the combinations of
# hyperparameter values to use for the training job it launches. For
# information about search strategies, see [How Hyperparameter Tuning
# Works][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.html
# @return [String]
#
# @!attribute [rw] strategy_config
# The configuration for the `Hyperband` optimization strategy. This
# parameter should be provided only if `Hyperband` is selected as the
# strategy for `HyperParameterTuningJobConfig`.
# @return [Types::HyperParameterTuningJobStrategyConfig]
#
# @!attribute [rw] hyper_parameter_tuning_job_objective
# The [HyperParameterTuningJobObjective][1] specifies the objective
# metric used to evaluate the performance of training jobs launched by
# this tuning job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobObjective.html
# @return [Types::HyperParameterTuningJobObjective]
#
# @!attribute [rw] resource_limits
# The [ResourceLimits][1] object that specifies the maximum number of
# training and parallel training jobs that can be used for this
# hyperparameter tuning job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ResourceLimits.html
# @return [Types::ResourceLimits]
#
# @!attribute [rw] parameter_ranges
# The [ParameterRanges][1] object that specifies the ranges of
# hyperparameters that this tuning job searches over to find the
# optimal configuration for the highest model performance against your
# chosen objective metric.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ParameterRanges.html
# @return [Types::ParameterRanges]
#
# @!attribute [rw] training_job_early_stopping_type
# Specifies whether to use early stopping for training jobs launched
# by the hyperparameter tuning job. Because the `Hyperband` strategy
# has its own advanced internal early stopping mechanism,
# `TrainingJobEarlyStoppingType` must be `OFF` to use `Hyperband`.
# This parameter can take on one of the following values (the default
# value is `OFF`):
#
# OFF
#
# : Training jobs launched by the hyperparameter tuning job do not use
# early stopping.
#
# AUTO
#
# : SageMaker stops training jobs launched by the hyperparameter
# tuning job when they are unlikely to perform better than
# previously completed training jobs. For more information, see
# [Stop Training Jobs Early][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-early-stopping.html
# @return [String]
#
# @!attribute [rw] tuning_job_completion_criteria
# The tuning job's completion criteria.
# @return [Types::TuningJobCompletionCriteria]
#
# @!attribute [rw] random_seed
# A value used to initialize a pseudo-random number generator. Setting
# a random seed and using the same seed later for the same tuning job
# will allow hyperparameter optimization to find more a consistent
# hyperparameter configuration between the two runs.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobConfig AWS API Documentation
#
class HyperParameterTuningJobConfig < Struct.new(
:strategy,
:strategy_config,
:hyper_parameter_tuning_job_objective,
:resource_limits,
:parameter_ranges,
:training_job_early_stopping_type,
:tuning_job_completion_criteria,
:random_seed)
SENSITIVE = []
include Aws::Structure
end
# The total resources consumed by your hyperparameter tuning job.
#
# @!attribute [rw] runtime_in_seconds
# The wall clock runtime in seconds used by your hyperparameter tuning
# job.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobConsumedResources AWS API Documentation
#
class HyperParameterTuningJobConsumedResources < Struct.new(
:runtime_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# Defines the objective metric for a hyperparameter tuning job.
# Hyperparameter tuning uses the value of this metric to evaluate the
# training jobs it launches, and returns the training job that results
# in either the highest or lowest value for this metric, depending on
# the value you specify for the `Type` parameter.
#
# @!attribute [rw] type
# Whether to minimize or maximize the objective metric.
# @return [String]
#
# @!attribute [rw] metric_name
# The name of the metric to use for the objective metric.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobObjective AWS API Documentation
#
class HyperParameterTuningJobObjective < Struct.new(
:type,
:metric_name)
SENSITIVE = []
include Aws::Structure
end
# An entity returned by the [SearchRecord][1] API containing the
# properties of a hyperparameter tuning job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_SearchRecord.html
#
# @!attribute [rw] hyper_parameter_tuning_job_name
# The name of a hyperparameter tuning job.
# @return [String]
#
# @!attribute [rw] hyper_parameter_tuning_job_arn
# The Amazon Resource Name (ARN) of a hyperparameter tuning job.
# @return [String]
#
# @!attribute [rw] hyper_parameter_tuning_job_config
# Configures a hyperparameter tuning job.
# @return [Types::HyperParameterTuningJobConfig]
#
# @!attribute [rw] training_job_definition
# Defines the training jobs launched by a hyperparameter tuning job.
# @return [Types::HyperParameterTrainingJobDefinition]
#
# @!attribute [rw] training_job_definitions
# The job definitions included in a hyperparameter tuning job.
# @return [Array<Types::HyperParameterTrainingJobDefinition>]
#
# @!attribute [rw] hyper_parameter_tuning_job_status
# The status of a hyperparameter tuning job.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that a hyperparameter tuning job was created.
# @return [Time]
#
# @!attribute [rw] hyper_parameter_tuning_end_time
# The time that a hyperparameter tuning job ended.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time that a hyperparameter tuning job was last modified.
# @return [Time]
#
# @!attribute [rw] training_job_status_counters
# The numbers of training jobs launched by a hyperparameter tuning
# job, categorized by status.
# @return [Types::TrainingJobStatusCounters]
#
# @!attribute [rw] 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.
# @return [Types::ObjectiveStatusCounters]
#
# @!attribute [rw] best_training_job
# The container for the summary information about a training job.
# @return [Types::HyperParameterTrainingJobSummary]
#
# @!attribute [rw] overall_best_training_job
# The container for the summary information about a training job.
# @return [Types::HyperParameterTrainingJobSummary]
#
# @!attribute [rw] warm_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.
#
# <note markdown="1"> 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.
#
# </note>
# @return [Types::HyperParameterTuningJobWarmStartConfig]
#
# @!attribute [rw] failure_reason
# The error that was created when a hyperparameter tuning job failed.
# @return [String]
#
# @!attribute [rw] tags
# The tags associated with a hyperparameter tuning job. For more
# information see [Tagging Amazon Web Services resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] tuning_job_completion_details
# Information about either a current or completed hyperparameter
# tuning job.
# @return [Types::HyperParameterTuningJobCompletionDetails]
#
# @!attribute [rw] consumed_resources
# The total amount of resources consumed by a hyperparameter tuning
# job.
# @return [Types::HyperParameterTuningJobConsumedResources]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobSearchEntity AWS API Documentation
#
class HyperParameterTuningJobSearchEntity < Struct.new(
:hyper_parameter_tuning_job_name,
:hyper_parameter_tuning_job_arn,
:hyper_parameter_tuning_job_config,
:training_job_definition,
:training_job_definitions,
:hyper_parameter_tuning_job_status,
:creation_time,
:hyper_parameter_tuning_end_time,
:last_modified_time,
:training_job_status_counters,
:objective_status_counters,
:best_training_job,
:overall_best_training_job,
:warm_start_config,
:failure_reason,
:tags,
:tuning_job_completion_details,
:consumed_resources)
SENSITIVE = []
include Aws::Structure
end
# The configuration for a training job launched by a hyperparameter
# tuning job. Choose `Bayesian` for Bayesian optimization, and `Random`
# for random search optimization. For more advanced use cases, use
# `Hyperband`, which evaluates objective metrics for training jobs after
# every epoch. For more information about strategies, see [How
# Hyperparameter Tuning Works][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-how-it-works.html
#
# @!attribute [rw] hyperband_strategy_config
# The configuration for the object that specifies the `Hyperband`
# strategy. This parameter is only supported for the `Hyperband`
# selection for `Strategy` within the `HyperParameterTuningJobConfig`
# API.
# @return [Types::HyperbandStrategyConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobStrategyConfig AWS API Documentation
#
class HyperParameterTuningJobStrategyConfig < Struct.new(
:hyperband_strategy_config)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information about a hyperparameter tuning job.
#
# @!attribute [rw] hyper_parameter_tuning_job_name
# The name of the tuning job.
# @return [String]
#
# @!attribute [rw] hyper_parameter_tuning_job_arn
# The Amazon Resource Name (ARN) of the tuning job.
# @return [String]
#
# @!attribute [rw] hyper_parameter_tuning_job_status
# The status of the tuning job.
# @return [String]
#
# @!attribute [rw] strategy
# Specifies the search strategy hyperparameter tuning uses to choose
# which hyperparameters to evaluate at each iteration.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the tuning job was created.
# @return [Time]
#
# @!attribute [rw] hyper_parameter_tuning_end_time
# The date and time that the tuning job ended.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the tuning job was modified.
# @return [Time]
#
# @!attribute [rw] training_job_status_counters
# The [TrainingJobStatusCounters][1] object that specifies the numbers
# of training jobs, categorized by status, that this tuning job
# launched.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobStatusCounters.html
# @return [Types::TrainingJobStatusCounters]
#
# @!attribute [rw] objective_status_counters
# The [ObjectiveStatusCounters][1] object that specifies the numbers
# of training jobs, categorized by objective metric status, that this
# tuning job launched.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ObjectiveStatusCounters.html
# @return [Types::ObjectiveStatusCounters]
#
# @!attribute [rw] resource_limits
# The [ResourceLimits][1] object that specifies the maximum number of
# training jobs and parallel training jobs allowed for this tuning
# job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ResourceLimits.html
# @return [Types::ResourceLimits]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobSummary AWS API Documentation
#
class HyperParameterTuningJobSummary < Struct.new(
:hyper_parameter_tuning_job_name,
:hyper_parameter_tuning_job_arn,
:hyper_parameter_tuning_job_status,
:strategy,
:creation_time,
:hyper_parameter_tuning_end_time,
:last_modified_time,
:training_job_status_counters,
:objective_status_counters,
:resource_limits)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# <note markdown="1"> 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.
#
# </note>
#
# @!attribute [rw] parent_hyper_parameter_tuning_jobs
# An array of hyperparameter tuning jobs that are used as the starting
# point for the new hyperparameter tuning job. For more information
# about warm starting a hyperparameter tuning job, see [Using a
# Previous Hyperparameter Tuning Job as a Starting Point][1].
#
# Hyperparameter tuning jobs created before October 1, 2018 cannot be
# used as parent jobs for warm start tuning jobs.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-warm-start.html
# @return [Array<Types::ParentHyperParameterTuningJob>]
#
# @!attribute [rw] warm_start_type
# Specifies one of the following:
#
# IDENTICAL\_DATA\_AND\_ALGORITHM
#
# : The new hyperparameter tuning job uses the same input data and
# training image as the parent tuning jobs. You can change the
# hyperparameter ranges to search and the maximum number of training
# jobs that the hyperparameter tuning job launches. You cannot use a
# new version of the training algorithm, unless the changes in the
# new version do not affect the algorithm itself. For example,
# changes that improve logging or adding support for a different
# data format are allowed. You can also change hyperparameters from
# tunable to static, and from static to tunable, but the total
# number of static plus tunable hyperparameters must remain the same
# as it is in all parent jobs. The objective metric for the new
# tuning job must be the same as for all parent jobs.
#
# TRANSFER\_LEARNING
#
# : The new hyperparameter tuning job can include input data,
# hyperparameter ranges, maximum number of concurrent training jobs,
# and maximum number of training jobs that are different than those
# of its parent hyperparameter tuning jobs. The training image can
# also be a different version from the version used in the parent
# hyperparameter tuning job. You can also change hyperparameters
# from tunable to static, and from static to tunable, but the total
# number of static plus tunable hyperparameters must remain the same
# as it is in all parent jobs. The objective metric for the new
# tuning job must be the same as for all parent jobs.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobWarmStartConfig AWS API Documentation
#
class HyperParameterTuningJobWarmStartConfig < Struct.new(
:parent_hyper_parameter_tuning_jobs,
:warm_start_type)
SENSITIVE = []
include Aws::Structure
end
# The configuration of resources, including compute instances and
# storage volumes for use in training jobs launched by hyperparameter
# tuning jobs. `HyperParameterTuningResourceConfig` is similar to
# `ResourceConfig`, but has the additional `InstanceConfigs` and
# `AllocationStrategy` fields to allow for flexible instance management.
# Specify one or more instance types, count, and the allocation strategy
# for instance selection.
#
# <note markdown="1"> `HyperParameterTuningResourceConfig` supports the capabilities of
# `ResourceConfig` with the exception of `KeepAlivePeriodInSeconds`.
# Hyperparameter tuning jobs use warm pools by default, which reuse
# clusters between training jobs.
#
# </note>
#
# @!attribute [rw] instance_type
# The instance type used to run hyperparameter optimization tuning
# jobs. See [ descriptions of instance types][1] for more information.
#
#
#
# [1]: https://docs.aws.amazon.com/notebooks-available-instance-types.html
# @return [String]
#
# @!attribute [rw] instance_count
# The number of compute instances of type `InstanceType` to use. For
# [distributed training][1], select a value greater than 1.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/data-parallel-use-api.html
# @return [Integer]
#
# @!attribute [rw] volume_size_in_gb
# The volume size in GB for the storage volume to be used in
# processing hyperparameter optimization jobs (optional). These
# volumes store model artifacts, incremental states and optionally,
# scratch space for training algorithms. Do not provide a value for
# this parameter if a value for `InstanceConfigs` is also specified.
#
# Some instance types have a fixed total local storage size. If you
# select one of these instances for training, `VolumeSizeInGB` cannot
# be greater than this total size. For a list of instance types with
# local instance storage and their sizes, see [instance store
# volumes][1].
#
# <note markdown="1"> SageMaker supports only the [General Purpose SSD (gp2)][2] storage
# volume type.
#
# </note>
#
#
#
# [1]: http://aws.amazon.com/releasenotes/host-instance-storage-volumes-table/
# [2]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-volume-types.html
# @return [Integer]
#
# @!attribute [rw] volume_kms_key_id
# A key used by Amazon Web Services Key Management Service to encrypt
# data on the storage volume attached to the compute instances used to
# run the training job. You can use either of the following formats to
# specify a key.
#
# KMS Key ID:
#
# `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# Amazon Resource Name (ARN) of a KMS key:
#
# `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# Some instances use local storage, which use a [hardware module to
# encrypt][1] storage volumes. If you choose one of these instance
# types, you cannot request a `VolumeKmsKeyId`. For a list of instance
# types that use local storage, see [instance store volumes][2]. For
# more information about Amazon Web Services Key Management Service,
# see [KMS encryption][3] for more information.
#
#
#
# [1]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.html
# [2]: http://aws.amazon.com/releasenotes/host-instance-storage-volumes-table/
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security-kms-permissions.html
# @return [String]
#
# @!attribute [rw] allocation_strategy
# The strategy that determines the order of preference for resources
# specified in `InstanceConfigs` used in hyperparameter optimization.
# @return [String]
#
# @!attribute [rw] instance_configs
# A list containing the configuration(s) for one or more resources for
# processing hyperparameter jobs. These resources include compute
# instances and storage volumes to use in model training jobs launched
# by hyperparameter tuning jobs. The `AllocationStrategy` controls the
# order in which multiple configurations provided in `InstanceConfigs`
# are used.
#
# <note markdown="1"> If you only want to use a single instance configuration inside the
# `HyperParameterTuningResourceConfig` API, do not provide a value for
# `InstanceConfigs`. Instead, use `InstanceType`, `VolumeSizeInGB` and
# `InstanceCount`. If you use `InstanceConfigs`, do not provide values
# for `InstanceType`, `VolumeSizeInGB` or `InstanceCount`.
#
# </note>
# @return [Array<Types::HyperParameterTuningInstanceConfig>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningResourceConfig AWS API Documentation
#
class HyperParameterTuningResourceConfig < Struct.new(
:instance_type,
:instance_count,
:volume_size_in_gb,
:volume_kms_key_id,
:allocation_strategy,
:instance_configs)
SENSITIVE = []
include Aws::Structure
end
# The configuration for `Hyperband`, a multi-fidelity based
# hyperparameter tuning strategy. `Hyperband` uses the final and
# intermediate results of a training job to dynamically allocate
# resources to utilized hyperparameter configurations while
# automatically stopping under-performing configurations. This parameter
# should be provided only if `Hyperband` is selected as the
# `StrategyConfig` under the `HyperParameterTuningJobConfig` API.
#
# @!attribute [rw] min_resource
# The minimum number of resources (such as epochs) that can be used by
# a training job launched by a hyperparameter tuning job. If the value
# for `MinResource` has not been reached, the training job is not
# stopped by `Hyperband`.
# @return [Integer]
#
# @!attribute [rw] max_resource
# The maximum number of resources (such as epochs) that can be used by
# a training job launched by a hyperparameter tuning job. Once a job
# reaches the `MaxResource` value, it is stopped. If a value for
# `MaxResource` is not provided, and `Hyperband` is selected as the
# hyperparameter tuning strategy, `HyperbandTrainingJ` attempts to
# infer `MaxResource` from the following keys (if present) in
# [StaticsHyperParameters][1]:
#
# * `epochs`
#
# * `numepochs`
#
# * `n-epochs`
#
# * `n_epochs`
#
# * `num_epochs`
#
# If `HyperbandStrategyConfig` is unable to infer a value for
# `MaxResource`, it generates a validation error. The maximum value is
# 20,000 epochs. All metrics that correspond to an objective metric
# are used to derive [early stopping decisions][2]. For
# [distributive][3] training jobs, ensure that duplicate metrics are
# not printed in the logs across the individual nodes in a training
# job. If multiple nodes are publishing duplicate or incorrect
# metrics, training jobs may make an incorrect stopping decision and
# stop the job prematurely.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html#sagemaker-Type-HyperParameterTrainingJobDefinition-StaticHyperParameters
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-early-stopping.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/distributed-training.html
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperbandStrategyConfig AWS API Documentation
#
class HyperbandStrategyConfig < Struct.new(
:min_resource,
:max_resource)
SENSITIVE = []
include Aws::Structure
end
# The IAM Identity details associated with the user. These details are
# associated with model package groups, model packages and project
# entities only.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the IAM identity.
# @return [String]
#
# @!attribute [rw] principal_id
# The ID of the principal that assumes the IAM identity.
# @return [String]
#
# @!attribute [rw] source_identity
# The person or application which assumes the IAM identity.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/IamIdentity AWS API Documentation
#
class IamIdentity < Struct.new(
:arn,
:principal_id,
:source_identity)
SENSITIVE = []
include Aws::Structure
end
# 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`.
#
# @!attribute [rw] creation_time
# When the image was created.
# @return [Time]
#
# @!attribute [rw] description
# The description of the image.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the image as displayed.
# @return [String]
#
# @!attribute [rw] failure_reason
# When a create, update, or delete operation fails, the reason for the
# failure.
# @return [String]
#
# @!attribute [rw] image_arn
# The ARN of the image.
# @return [String]
#
# @!attribute [rw] image_name
# The name of the image.
# @return [String]
#
# @!attribute [rw] image_status
# The status of the image.
# @return [String]
#
# @!attribute [rw] last_modified_time
# When the image was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Image AWS API Documentation
#
class Image < Struct.new(
:creation_time,
:description,
:display_name,
:failure_reason,
:image_arn,
:image_name,
:image_status,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# Stores the configuration information for the image classification
# problem of an AutoML job using the V2 API.
#
# @!attribute [rw] completion_criteria
# How long a job is allowed to run, or how many candidates a job is
# allowed to generate.
# @return [Types::AutoMLJobCompletionCriteria]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ImageClassificationJobConfig AWS API Documentation
#
class ImageClassificationJobConfig < Struct.new(
:completion_criteria)
SENSITIVE = []
include Aws::Structure
end
# Specifies whether the model container is in Amazon ECR or a private
# Docker registry accessible from your Amazon Virtual Private Cloud
# (VPC).
#
# @!attribute [rw] repository_access_mode
# Set this to one of the following values:
#
# * `Platform` - The model image is hosted in Amazon ECR.
#
# * `Vpc` - The model image is hosted in a private Docker registry in
# your VPC.
# @return [String]
#
# @!attribute [rw] repository_auth_config
# (Optional) 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 `Vpc` as the value for the
# `RepositoryAccessMode` field, and the private Docker registry where
# the model image is hosted requires authentication.
# @return [Types::RepositoryAuthConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ImageConfig AWS API Documentation
#
class ImageConfig < Struct.new(
:repository_access_mode,
:repository_auth_config)
SENSITIVE = []
include Aws::Structure
end
# A version of a SageMaker `Image`. A version represents an existing
# container image.
#
# @!attribute [rw] creation_time
# When the version was created.
# @return [Time]
#
# @!attribute [rw] failure_reason
# When a create or delete operation fails, the reason for the failure.
# @return [String]
#
# @!attribute [rw] image_arn
# The ARN of the image the version is based on.
# @return [String]
#
# @!attribute [rw] image_version_arn
# The ARN of the version.
# @return [String]
#
# @!attribute [rw] image_version_status
# The status of the version.
# @return [String]
#
# @!attribute [rw] last_modified_time
# When the version was last modified.
# @return [Time]
#
# @!attribute [rw] version
# The version number.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ImageVersion AWS API Documentation
#
class ImageVersion < Struct.new(
:creation_time,
:failure_reason,
:image_arn,
:image_version_arn,
:image_version_status,
:last_modified_time,
:version)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_content_name
# The name of the hub content to import.
# @return [String]
#
# @!attribute [rw] hub_content_version
# The version of the hub content to import.
# @return [String]
#
# @!attribute [rw] hub_content_type
# The type of hub content to import.
# @return [String]
#
# @!attribute [rw] document_schema_version
# The version of the hub content schema to import.
# @return [String]
#
# @!attribute [rw] hub_name
# The name of the hub to import content into.
# @return [String]
#
# @!attribute [rw] hub_content_display_name
# The display name of the hub content to import.
# @return [String]
#
# @!attribute [rw] hub_content_description
# A description of the hub content to import.
# @return [String]
#
# @!attribute [rw] hub_content_markdown
# A string that provides a description of the hub content. This string
# can include links, tables, and standard markdown formating.
# @return [String]
#
# @!attribute [rw] hub_content_document
# The hub content document that describes information about the hub
# content such as type, associated containers, scripts, and more.
# @return [String]
#
# @!attribute [rw] hub_content_search_keywords
# The searchable keywords of the hub content.
# @return [Array<String>]
#
# @!attribute [rw] tags
# Any tags associated with the hub content.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ImportHubContentRequest AWS API Documentation
#
class ImportHubContentRequest < Struct.new(
:hub_content_name,
:hub_content_version,
:hub_content_type,
:document_schema_version,
:hub_name,
:hub_content_display_name,
:hub_content_description,
:hub_content_markdown,
:hub_content_document,
:hub_content_search_keywords,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_arn
# The ARN of the hub that the content was imported into.
# @return [String]
#
# @!attribute [rw] hub_content_arn
# The ARN of the hub content that was imported.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ImportHubContentResponse AWS API Documentation
#
class ImportHubContentResponse < Struct.new(
:hub_arn,
:hub_content_arn)
SENSITIVE = []
include Aws::Structure
end
# Specifies details about how containers in a multi-container endpoint
# are run.
#
# @!attribute [rw] mode
# How containers in a multi-container are run. The following values
# are valid.
#
# * `SERIAL` - Containers run as a serial pipeline.
#
# * `DIRECT` - Only the individual container that you specify is run.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceExecutionConfig AWS API Documentation
#
class InferenceExecutionConfig < Struct.new(
:mode)
SENSITIVE = []
include Aws::Structure
end
# The Amazon S3 location and configuration for storing inference request
# and response data.
#
# @!attribute [rw] destination
# The Amazon S3 bucket where the inference request and response data
# is stored.
# @return [String]
#
# @!attribute [rw] kms_key
# The Amazon Web Services Key Management Service key that Amazon
# SageMaker uses to encrypt captured data at rest using Amazon S3
# server-side encryption.
# @return [String]
#
# @!attribute [rw] content_type
# Configuration specifying how to treat different headers. If no
# headers are specified SageMaker will by default base64 encode when
# capturing the data.
# @return [Types::CaptureContentTypeHeader]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceExperimentDataStorageConfig AWS API Documentation
#
class InferenceExperimentDataStorageConfig < Struct.new(
:destination,
:kms_key,
:content_type)
SENSITIVE = []
include Aws::Structure
end
# The start and end times of an inference experiment.
#
# The maximum duration that you can set for an inference experiment is
# 30 days.
#
# @!attribute [rw] start_time
# The timestamp at which the inference experiment started or will
# start.
# @return [Time]
#
# @!attribute [rw] end_time
# The timestamp at which the inference experiment ended or will end.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceExperimentSchedule AWS API Documentation
#
class InferenceExperimentSchedule < Struct.new(
:start_time,
:end_time)
SENSITIVE = []
include Aws::Structure
end
# Lists a summary of properties of an inference experiment.
#
# @!attribute [rw] name
# The name of the inference experiment.
# @return [String]
#
# @!attribute [rw] type
# The type of the inference experiment.
# @return [String]
#
# @!attribute [rw] schedule
# The duration for which the inference experiment ran or will run.
#
# The maximum duration that you can set for an inference experiment is
# 30 days.
# @return [Types::InferenceExperimentSchedule]
#
# @!attribute [rw] status
# The status of the inference experiment.
# @return [String]
#
# @!attribute [rw] status_reason
# The error message for the inference experiment status result.
# @return [String]
#
# @!attribute [rw] description
# The description of the inference experiment.
# @return [String]
#
# @!attribute [rw] creation_time
# The timestamp at which the inference experiment was created.
# @return [Time]
#
# @!attribute [rw] completion_time
# The timestamp at which the inference experiment was completed.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The timestamp when you last modified the inference experiment.
# @return [Time]
#
# @!attribute [rw] role_arn
# The ARN of the IAM role that Amazon SageMaker can assume to access
# model artifacts and container images, and manage Amazon SageMaker
# Inference endpoints for model deployment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceExperimentSummary AWS API Documentation
#
class InferenceExperimentSummary < Struct.new(
:name,
:type,
:schedule,
:status,
:status_reason,
:description,
:creation_time,
:completion_time,
:last_modified_time,
:role_arn)
SENSITIVE = []
include Aws::Structure
end
# The metrics for an existing endpoint compared in an Inference
# Recommender job.
#
# @!attribute [rw] max_invocations
# The expected maximum number of requests per minute for the instance.
# @return [Integer]
#
# @!attribute [rw] model_latency
# The expected model latency at maximum invocations per minute for the
# instance.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceMetrics AWS API Documentation
#
class InferenceMetrics < Struct.new(
:max_invocations,
:model_latency)
SENSITIVE = []
include Aws::Structure
end
# A list of recommendations made by Amazon SageMaker Inference
# Recommender.
#
# @!attribute [rw] metrics
# The metrics used to decide what recommendation to make.
# @return [Types::RecommendationMetrics]
#
# @!attribute [rw] endpoint_configuration
# Defines the endpoint configuration parameters.
# @return [Types::EndpointOutputConfiguration]
#
# @!attribute [rw] model_configuration
# Defines the model configuration.
# @return [Types::ModelConfiguration]
#
# @!attribute [rw] recommendation_id
# The recommendation ID which uniquely identifies each recommendation.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceRecommendation AWS API Documentation
#
class InferenceRecommendation < Struct.new(
:metrics,
:endpoint_configuration,
:model_configuration,
:recommendation_id)
SENSITIVE = []
include Aws::Structure
end
# A structure that contains a list of recommendation jobs.
#
# @!attribute [rw] job_name
# The name of the job.
# @return [String]
#
# @!attribute [rw] job_description
# The job description.
# @return [String]
#
# @!attribute [rw] job_type
# The recommendation job type.
# @return [String]
#
# @!attribute [rw] job_arn
# The Amazon Resource Name (ARN) of the recommendation job.
# @return [String]
#
# @!attribute [rw] status
# The status of the job.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the job was created.
# @return [Time]
#
# @!attribute [rw] completion_time
# A timestamp that shows when the job completed.
# @return [Time]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that enables Amazon
# SageMaker to perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] last_modified_time
# A timestamp that shows when the job was last modified.
# @return [Time]
#
# @!attribute [rw] failure_reason
# If the job fails, provides information why the job failed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceRecommendationsJob AWS API Documentation
#
class InferenceRecommendationsJob < Struct.new(
:job_name,
:job_description,
:job_type,
:job_arn,
:status,
:creation_time,
:completion_time,
:role_arn,
:last_modified_time,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# A returned array object for the `Steps` response field in the
# [ListInferenceRecommendationsJobSteps][1] API command.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListInferenceRecommendationsJobSteps.html
#
# @!attribute [rw] step_type
# The type of the subtask.
#
# `BENCHMARK`: Evaluate the performance of your model on different
# instance types.
# @return [String]
#
# @!attribute [rw] job_name
# The name of the Inference Recommender job.
# @return [String]
#
# @!attribute [rw] status
# The current status of the benchmark.
# @return [String]
#
# @!attribute [rw] inference_benchmark
# The details for a specific benchmark.
# @return [Types::RecommendationJobInferenceBenchmark]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceRecommendationsJobStep AWS API Documentation
#
class InferenceRecommendationsJobStep < Struct.new(
:step_type,
:job_name,
:status,
:inference_benchmark)
SENSITIVE = []
include Aws::Structure
end
# Defines how to perform inference generation after a training job is
# run.
#
# @!attribute [rw] containers
# The Amazon ECR registry path of the Docker image that contains the
# inference code.
# @return [Array<Types::ModelPackageContainerDefinition>]
#
# @!attribute [rw] supported_transform_instance_types
# A list of the instance types on which a transformation job can be
# run or on which an endpoint can be deployed.
#
# This parameter is required for unversioned models, and optional for
# versioned models.
# @return [Array<String>]
#
# @!attribute [rw] supported_realtime_inference_instance_types
# A list of the instance types that are used to generate inferences in
# real-time.
#
# This parameter is required for unversioned models, and optional for
# versioned models.
# @return [Array<String>]
#
# @!attribute [rw] supported_content_types
# The supported MIME types for the input data.
# @return [Array<String>]
#
# @!attribute [rw] supported_response_mime_types
# The supported MIME types for the output data.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceSpecification AWS API Documentation
#
class InferenceSpecification < Struct.new(
:containers,
:supported_transform_instance_types,
:supported_realtime_inference_instance_types,
:supported_content_types,
:supported_response_mime_types)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] s3_uri
# The S3 path where the model artifacts, which result from model
# training, are stored. This path must point to a single gzip
# compressed tar archive (.tar.gz suffix).
# @return [String]
#
# @!attribute [rw] data_input_config
# Specifies the name and shape of the expected data inputs for your
# trained model with a JSON dictionary form. The data inputs are
# `Framework` specific.
#
# * `TensorFlow`: You must specify the name and shape (NHWC format) of
# the expected data inputs using a dictionary format for your
# trained model. The dictionary formats required for the console and
# CLI are different.
#
# * Examples for one input:
#
# * If using the console, `\{"input":[1,1024,1024,3]\}`
#
# * If using the CLI, `\{"input":[1,1024,1024,3]\}`
#
# * Examples for two inputs:
#
# * If using the console, `\{"data1": [1,28,28,1],
# "data2":[1,28,28,1]\}`
#
# * If using the CLI, `\{"data1": [1,28,28,1],
# "data2":[1,28,28,1]\}`
#
# * `KERAS`: You must specify the name and shape (NCHW format) of
# expected data inputs using a dictionary format for your trained
# model. Note that while Keras model artifacts should be uploaded in
# NHWC (channel-last) format, `DataInputConfig` should be specified
# in NCHW (channel-first) format. The dictionary formats required
# for the console and CLI are different.
#
# * Examples for one input:
#
# * If using the console, `\{"input_1":[1,3,224,224]\}`
#
# * If using the CLI, `\{"input_1":[1,3,224,224]\}`
#
# * Examples for two inputs:
#
# * If using the console, `\{"input_1": [1,3,224,224],
# "input_2":[1,3,224,224]\} `
#
# * If using the CLI, `\{"input_1": [1,3,224,224],
# "input_2":[1,3,224,224]\}`
#
# * `MXNET/ONNX/DARKNET`: You must specify the name and shape (NCHW
# format) of the expected data inputs in order using a dictionary
# format for your trained model. The dictionary formats required for
# the console and CLI are different.
#
# * Examples for one input:
#
# * If using the console, `\{"data":[1,3,1024,1024]\}`
#
# * If using the CLI, `\{"data":[1,3,1024,1024]\}`
#
# * Examples for two inputs:
#
# * If using the console, `\{"var1": [1,1,28,28],
# "var2":[1,1,28,28]\} `
#
# * If using the CLI, `\{"var1": [1,1,28,28],
# "var2":[1,1,28,28]\}`
#
# * `PyTorch`: You can either specify the name and shape (NCHW format)
# of expected data inputs in order using a dictionary format for
# your trained model or you can specify the shape only using a list
# format. The dictionary formats required for the console and CLI
# are different. The list formats for the console and CLI are the
# same.
#
# * Examples for one input in dictionary format:
#
# * If using the console, `\{"input0":[1,3,224,224]\}`
#
# * If using the CLI, `\{"input0":[1,3,224,224]\}`
#
# * Example for one input in list format: `[[1,3,224,224]]`
#
# * Examples for two inputs in dictionary format:
#
# * If using the console, `\{"input0":[1,3,224,224],
# "input1":[1,3,224,224]\}`
#
# * If using the CLI, `\{"input0":[1,3,224,224],
# "input1":[1,3,224,224]\} `
#
# * Example for two inputs in list format: `[[1,3,224,224],
# [1,3,224,224]]`
#
# * `XGBOOST`: input data name and shape are not needed.
#
# `DataInputConfig` supports the following parameters for `CoreML`
# `TargetDevice` (ML Model format):
#
# * `shape`: Input shape, for example `\{"input_1": \{"shape":
# [1,224,224,3]\}\}`. In addition to static input shapes, CoreML
# converter supports Flexible input shapes:
#
# * Range Dimension. You can use the Range Dimension feature if you
# know the input shape will be within some specific interval in
# that dimension, for example: `\{"input_1": \{"shape": ["1..10",
# 224, 224, 3]\}\}`
#
# * Enumerated shapes. Sometimes, the models are trained to work
# only on a select set of inputs. You can enumerate all supported
# input shapes, for example: `\{"input_1": \{"shape": [[1, 224,
# 224, 3], [1, 160, 160, 3]]\}\}`
#
# * `default_shape`: Default input shape. You can set a default shape
# during conversion for both Range Dimension and Enumerated Shapes.
# For example `\{"input_1": \{"shape": ["1..10", 224, 224, 3],
# "default_shape": [1, 224, 224, 3]\}\}`
#
# * `type`: Input type. Allowed values: `Image` and `Tensor`. By
# default, the converter generates an ML Model with inputs of type
# Tensor (MultiArray). User can set input type to be Image. Image
# input type requires additional input parameters such as `bias` and
# `scale`.
#
# * `bias`: If the input type is an Image, you need to provide the
# bias vector.
#
# * `scale`: If the input type is an Image, you need to provide a
# scale factor.
#
# CoreML `ClassifierConfig` parameters can be specified using
# [OutputConfig][1] `CompilerOptions`. CoreML converter supports
# Tensorflow and PyTorch models. CoreML conversion examples:
#
# * Tensor type input:
#
# * `"DataInputConfig": \{"input_1": \{"shape": [[1,224,224,3],
# [1,160,160,3]], "default_shape": [1,224,224,3]\}\}`
#
# ^
#
# * Tensor type input without input name (PyTorch):
#
# * `"DataInputConfig": [\{"shape": [[1,3,224,224], [1,3,160,160]],
# "default_shape": [1,3,224,224]\}]`
#
# ^
#
# * Image type input:
#
# * `"DataInputConfig": \{"input_1": \{"shape": [[1,224,224,3],
# [1,160,160,3]], "default_shape": [1,224,224,3], "type": "Image",
# "bias": [-1,-1,-1], "scale": 0.007843137255\}\}`
#
# * `"CompilerOptions": \{"class_labels":
# "imagenet_labels_1000.txt"\}`
#
# * Image type input without input name (PyTorch):
#
# * `"DataInputConfig": [\{"shape": [[1,3,224,224], [1,3,160,160]],
# "default_shape": [1,3,224,224], "type": "Image", "bias":
# [-1,-1,-1], "scale": 0.007843137255\}]`
#
# * `"CompilerOptions": \{"class_labels":
# "imagenet_labels_1000.txt"\}`
#
# Depending on the model format, `DataInputConfig` requires the
# following parameters for `ml_eia2` [OutputConfig:TargetDevice][2].
#
# * For TensorFlow models saved in the SavedModel format, specify the
# input names from `signature_def_key` and the input model shapes
# for `DataInputConfig`. Specify the `signature_def_key` in [
# `OutputConfig:CompilerOptions` ][3] if the model does not use
# TensorFlow's default signature def key. For example:
#
# * `"DataInputConfig": \{"inputs": [1, 224, 224, 3]\}`
#
# * `"CompilerOptions": \{"signature_def_key": "serving_custom"\}`
#
# * For TensorFlow models saved as a frozen graph, specify the input
# tensor names and shapes in `DataInputConfig` and the output tensor
# names for `output_names` in [ `OutputConfig:CompilerOptions` ][3].
# For example:
#
# * `"DataInputConfig": \{"input_tensor:0": [1, 224, 224, 3]\}`
#
# * `"CompilerOptions": \{"output_names": ["output_tensor:0"]\}`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-TargetDevice
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html#sagemaker-Type-OutputConfig-CompilerOptions
# @return [String]
#
# @!attribute [rw] framework
# Identifies the framework in which the model was trained. For
# example: TENSORFLOW.
# @return [String]
#
# @!attribute [rw] framework_version
# Specifies the framework version to use. This API field is only
# supported for the MXNet, PyTorch, TensorFlow and TensorFlow Lite
# frameworks.
#
# For information about framework versions supported for cloud targets
# and edge devices, see [Cloud Supported Instance Types and
# Frameworks][1] and [Edge Supported Frameworks][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/neo-supported-cloud.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/neo-supported-devices-edge-frameworks.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InputConfig AWS API Documentation
#
class InputConfig < Struct.new(
:s3_uri,
:data_input_config,
:framework,
:framework_version)
SENSITIVE = []
include Aws::Structure
end
# Defines an instance group for heterogeneous cluster training. When
# requesting a training job using the [CreateTrainingJob][1] API, you
# can configure multiple instance groups .
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
#
# @!attribute [rw] instance_type
# Specifies the instance type of the instance group.
# @return [String]
#
# @!attribute [rw] instance_count
# Specifies the number of instances of the instance group.
# @return [Integer]
#
# @!attribute [rw] instance_group_name
# Specifies the name of the instance group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InstanceGroup AWS API Documentation
#
class InstanceGroup < Struct.new(
:instance_type,
:instance_count,
:instance_group_name)
SENSITIVE = []
include Aws::Structure
end
# Information on the IMDS configuration of the notebook instance
#
# @!attribute [rw] minimum_instance_metadata_service_version
# Indicates the minimum IMDS version that the notebook instance
# supports. When passed as part of `CreateNotebookInstance`, if no
# value is selected, then it defaults to IMDSv1. This means that both
# IMDSv1 and IMDSv2 are supported. If passed as part of
# `UpdateNotebookInstance`, there is no default.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InstanceMetadataServiceConfiguration AWS API Documentation
#
class InstanceMetadataServiceConfiguration < Struct.new(
:minimum_instance_metadata_service_version)
SENSITIVE = []
include Aws::Structure
end
# For a hyperparameter of the integer type, specifies the range that a
# hyperparameter tuning job searches.
#
# @!attribute [rw] name
# The name of the hyperparameter to search.
# @return [String]
#
# @!attribute [rw] min_value
# The minimum value of the hyperparameter to search.
# @return [String]
#
# @!attribute [rw] max_value
# The maximum value of the hyperparameter to search.
# @return [String]
#
# @!attribute [rw] scaling_type
# The scale that hyperparameter tuning uses to search the
# hyperparameter range. For information about choosing a
# hyperparameter scale, see [Hyperparameter Scaling][1]. One of the
# following values:
#
# Auto
#
# : SageMaker hyperparameter tuning chooses the best scale for the
# hyperparameter.
#
# Linear
#
# : Hyperparameter tuning searches the values in the hyperparameter
# range by using a linear scale.
#
# Logarithmic
#
# : Hyperparameter tuning searches the values in the hyperparameter
# range by using a logarithmic scale.
#
# Logarithmic scaling works only for ranges that have only values
# greater than 0.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-ranges.html#scaling-type
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/IntegerParameterRange AWS API Documentation
#
class IntegerParameterRange < Struct.new(
:name,
:min_value,
:max_value,
:scaling_type)
SENSITIVE = []
include Aws::Structure
end
# Defines the possible values for an integer hyperparameter.
#
# @!attribute [rw] min_value
# The minimum integer value allowed.
# @return [String]
#
# @!attribute [rw] max_value
# The maximum integer value allowed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/IntegerParameterRangeSpecification AWS API Documentation
#
class IntegerParameterRangeSpecification < Struct.new(
:min_value,
:max_value)
SENSITIVE = []
include Aws::Structure
end
# The JupyterServer app settings.
#
# @!attribute [rw] default_resource_spec
# The default instance type and the Amazon Resource Name (ARN) of the
# default SageMaker image used by the JupyterServer app. If you use
# the `LifecycleConfigArns` parameter, then this parameter is also
# required.
# @return [Types::ResourceSpec]
#
# @!attribute [rw] lifecycle_config_arns
# The Amazon Resource Name (ARN) of the Lifecycle Configurations
# attached to the JupyterServerApp. If you use this parameter, the
# `DefaultResourceSpec` parameter is also required.
#
# <note markdown="1"> To remove a Lifecycle Config, you must set `LifecycleConfigArns` to
# an empty list.
#
# </note>
# @return [Array<String>]
#
# @!attribute [rw] code_repositories
# A list of Git repositories that SageMaker automatically displays to
# users for cloning in the JupyterServer application.
# @return [Array<Types::CodeRepository>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/JupyterServerAppSettings AWS API Documentation
#
class JupyterServerAppSettings < Struct.new(
:default_resource_spec,
:lifecycle_config_arns,
:code_repositories)
SENSITIVE = []
include Aws::Structure
end
# The KernelGateway app settings.
#
# @!attribute [rw] default_resource_spec
# The default instance type and the Amazon Resource Name (ARN) of the
# default SageMaker image used by the KernelGateway app.
#
# <note markdown="1"> The Amazon SageMaker Studio UI does not use the default instance
# type value set here. The default instance type set here is used when
# Apps are created using the Amazon Web Services Command Line
# Interface or Amazon Web Services CloudFormation and the instance
# type parameter value is not passed.
#
# </note>
# @return [Types::ResourceSpec]
#
# @!attribute [rw] custom_images
# A list of custom SageMaker images that are configured to run as a
# KernelGateway app.
# @return [Array<Types::CustomImage>]
#
# @!attribute [rw] lifecycle_config_arns
# The Amazon Resource Name (ARN) of the Lifecycle Configurations
# attached to the the user profile or domain.
#
# <note markdown="1"> To remove a Lifecycle Config, you must set `LifecycleConfigArns` to
# an empty list.
#
# </note>
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/KernelGatewayAppSettings AWS API Documentation
#
class KernelGatewayAppSettings < Struct.new(
:default_resource_spec,
:custom_images,
:lifecycle_config_arns)
SENSITIVE = []
include Aws::Structure
end
# The configuration for the file system and kernels in a SageMaker image
# running as a KernelGateway app.
#
# @!attribute [rw] kernel_specs
# The specification of the Jupyter kernels in the image.
# @return [Array<Types::KernelSpec>]
#
# @!attribute [rw] file_system_config
# The Amazon Elastic File System (EFS) storage configuration for a
# SageMaker image.
# @return [Types::FileSystemConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/KernelGatewayImageConfig AWS API Documentation
#
class KernelGatewayImageConfig < Struct.new(
:kernel_specs,
:file_system_config)
SENSITIVE = []
include Aws::Structure
end
# The specification of a Jupyter kernel.
#
# @!attribute [rw] name
# The name of the Jupyter kernel in the image. This value is case
# sensitive.
# @return [String]
#
# @!attribute [rw] display_name
# The display name of the kernel.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/KernelSpec AWS API Documentation
#
class KernelSpec < Struct.new(
:name,
:display_name)
SENSITIVE = []
include Aws::Structure
end
# Provides a breakdown of the number of objects labeled.
#
# @!attribute [rw] total_labeled
# The total number of objects labeled.
# @return [Integer]
#
# @!attribute [rw] human_labeled
# The total number of objects labeled by a human worker.
# @return [Integer]
#
# @!attribute [rw] machine_labeled
# The total number of objects labeled by automated data labeling.
# @return [Integer]
#
# @!attribute [rw] failed_non_retryable_error
# The total number of objects that could not be labeled due to an
# error.
# @return [Integer]
#
# @!attribute [rw] unlabeled
# The total number of objects not yet labeled.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelCounters AWS API Documentation
#
class LabelCounters < Struct.new(
:total_labeled,
:human_labeled,
:machine_labeled,
:failed_non_retryable_error,
:unlabeled)
SENSITIVE = []
include Aws::Structure
end
# Provides counts for human-labeled tasks in the labeling job.
#
# @!attribute [rw] human_labeled
# The total number of data objects labeled by a human worker.
# @return [Integer]
#
# @!attribute [rw] pending_human
# The total number of data objects that need to be labeled by a human
# worker.
# @return [Integer]
#
# @!attribute [rw] total
# The total number of tasks in the labeling job.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelCountersForWorkteam AWS API Documentation
#
class LabelCountersForWorkteam < Struct.new(
:human_labeled,
:pending_human,
:total)
SENSITIVE = []
include Aws::Structure
end
# Provides configuration information for auto-labeling of your data
# objects. A `LabelingJobAlgorithmsConfig` object must be supplied in
# order to use auto-labeling.
#
# @!attribute [rw] labeling_job_algorithm_specification_arn
# Specifies the Amazon Resource Name (ARN) of the algorithm used for
# auto-labeling. You must select one of the following ARNs:
#
# * *Image classification*
#
# `arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/image-classification`
#
# * *Text classification*
#
# `arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/text-classification`
#
# * *Object detection*
#
# `arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/object-detection`
#
# * *Semantic Segmentation*
#
# `arn:aws:sagemaker:region:027400017018:labeling-job-algorithm-specification/semantic-segmentation`
# @return [String]
#
# @!attribute [rw] initial_active_learning_model_arn
# At the end of an auto-label job Ground Truth sends the Amazon
# Resource Name (ARN) of the final model used for auto-labeling. You
# can use this model as the starting point for subsequent similar jobs
# by providing the ARN of the model here.
# @return [String]
#
# @!attribute [rw] labeling_job_resource_config
# Provides configuration information for a labeling job.
# @return [Types::LabelingJobResourceConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobAlgorithmsConfig AWS API Documentation
#
class LabelingJobAlgorithmsConfig < Struct.new(
:labeling_job_algorithm_specification_arn,
:initial_active_learning_model_arn,
:labeling_job_resource_config)
SENSITIVE = []
include Aws::Structure
end
# Attributes of the data specified by the customer. Use these to
# describe the data to be labeled.
#
# @!attribute [rw] content_classifiers
# Declares that your content is free of personally identifiable
# information or adult content. SageMaker may restrict the Amazon
# Mechanical Turk workers that can view your task based on this
# information.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobDataAttributes AWS API Documentation
#
class LabelingJobDataAttributes < Struct.new(
:content_classifiers)
SENSITIVE = []
include Aws::Structure
end
# Provides information about the location of input data.
#
# You must specify at least one of the following: `S3DataSource` or
# `SnsDataSource`.
#
# Use `SnsDataSource` to 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 `S3DataSource` to specify an input manifest file for both
# streaming and one-time labeling jobs. Adding an `S3DataSource` is
# optional if you use `SnsDataSource` to create a streaming labeling
# job.
#
# @!attribute [rw] s3_data_source
# The Amazon S3 location of the input data objects.
# @return [Types::LabelingJobS3DataSource]
#
# @!attribute [rw] sns_data_source
# An Amazon SNS data source used for streaming labeling jobs. To learn
# more, see [Send Data to a Streaming Labeling Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-send-data
# @return [Types::LabelingJobSnsDataSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobDataSource AWS API Documentation
#
class LabelingJobDataSource < Struct.new(
:s3_data_source,
:sns_data_source)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information for a work team.
#
# @!attribute [rw] labeling_job_name
# The name of the labeling job that the work team is assigned to.
# @return [String]
#
# @!attribute [rw] job_reference_code
# A unique identifier for a labeling job. You can use this to refer to
# a specific labeling job.
# @return [String]
#
# @!attribute [rw] work_requester_account_id
# The Amazon Web Services account ID of the account used to start the
# labeling job.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the labeling job was created.
# @return [Time]
#
# @!attribute [rw] label_counters
# Provides information about the progress of a labeling job.
# @return [Types::LabelCountersForWorkteam]
#
# @!attribute [rw] number_of_human_workers_per_data_object
# The configured number of workers per data object.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobForWorkteamSummary AWS API Documentation
#
class LabelingJobForWorkteamSummary < Struct.new(
:labeling_job_name,
:job_reference_code,
:work_requester_account_id,
:creation_time,
:label_counters,
:number_of_human_workers_per_data_object)
SENSITIVE = []
include Aws::Structure
end
# Input configuration information for a labeling job.
#
# @!attribute [rw] data_source
# The location of the input data.
# @return [Types::LabelingJobDataSource]
#
# @!attribute [rw] data_attributes
# Attributes of the data specified by the customer.
# @return [Types::LabelingJobDataAttributes]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobInputConfig AWS API Documentation
#
class LabelingJobInputConfig < Struct.new(
:data_source,
:data_attributes)
SENSITIVE = []
include Aws::Structure
end
# Specifies the location of the output produced by the labeling job.
#
# @!attribute [rw] output_dataset_s3_uri
# The Amazon S3 bucket location of the manifest file for labeled data.
# @return [String]
#
# @!attribute [rw] final_active_learning_model_arn
# The Amazon Resource Name (ARN) for the most recent SageMaker model
# trained as part of automated data labeling.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobOutput AWS API Documentation
#
class LabelingJobOutput < Struct.new(
:output_dataset_s3_uri,
:final_active_learning_model_arn)
SENSITIVE = []
include Aws::Structure
end
# Output configuration information for a labeling job.
#
# @!attribute [rw] s3_output_path
# The Amazon S3 location to write output data.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service ID of the key used to
# encrypt the output data, if any.
#
# If you provide your own KMS key ID, you must add the required
# permissions to your KMS key described in [Encrypt Output Data and
# Storage Volume with Amazon Web Services KMS][1].
#
# If you don't provide a KMS key ID, Amazon SageMaker uses the
# default Amazon Web Services KMS key for Amazon S3 for your role's
# account to encrypt your output data.
#
# If you use a bucket policy with an `s3:PutObject` permission that
# only allows objects with server-side encryption, set the condition
# key of `s3:x-amz-server-side-encryption` to `"aws:kms"`. For more
# information, see [KMS-Managed Encryption Keys][2] in the *Amazon
# Simple Storage Service Developer Guide.*
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security-permission.html#sms-security-kms-permissions
# [2]: https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html
# @return [String]
#
# @!attribute [rw] sns_topic_arn
# An Amazon Simple Notification Service (Amazon SNS) output topic ARN.
# Provide a `SnsTopicArn` if you want to do real time chaining to
# another streaming job and receive an Amazon SNS notifications each
# time a data object is submitted by a worker.
#
# If you provide an `SnsTopicArn` in `OutputConfig`, when workers
# complete labeling tasks, Ground Truth will send labeling task output
# data to the SNS output topic you specify here.
#
# To learn more, see [Receive Output Data from a Streaming Labeling
# Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-streaming-labeling-job.html#sms-streaming-how-it-works-output-data
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobOutputConfig AWS API Documentation
#
class LabelingJobOutputConfig < Struct.new(
:s3_output_path,
:kms_key_id,
:sns_topic_arn)
SENSITIVE = []
include Aws::Structure
end
# Configure encryption on the storage volume attached to the ML compute
# instance used to run automated data labeling model training and
# inference.
#
# @!attribute [rw] volume_kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt data on the storage
# volume attached to the ML compute instance(s) that run the training
# and inference jobs used for automated data labeling.
#
# You can only specify a `VolumeKmsKeyId` when you create a labeling
# job with automated data labeling enabled using the API operation
# `CreateLabelingJob`. You cannot specify an Amazon Web Services KMS
# key to encrypt the storage volume used for automated data labeling
# model training and inference when you create a labeling job using
# the console. To learn more, see [Output Data and Storage Volume
# Encryption][1].
#
# The `VolumeKmsKeyId` can be any of the following formats:
#
# * KMS Key ID
#
# `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * Amazon Resource Name (ARN) of a KMS Key
#
# `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-security.html
# @return [String]
#
# @!attribute [rw] vpc_config
# 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][1] and
# [Protect Training Jobs by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
# @return [Types::VpcConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobResourceConfig AWS API Documentation
#
class LabelingJobResourceConfig < Struct.new(
:volume_kms_key_id,
:vpc_config)
SENSITIVE = []
include Aws::Structure
end
# The Amazon S3 location of the input data objects.
#
# @!attribute [rw] manifest_s3_uri
# The Amazon S3 location of the manifest file that describes the input
# data objects.
#
# The input manifest file referenced in `ManifestS3Uri` must contain
# one of the following keys: `source-ref` or `source`. The value of
# the keys are interpreted as follows:
#
# * `source-ref`: The source of the object is the Amazon S3 object
# specified in the value. Use this value when the object is a binary
# object, such as an image.
#
# * `source`: The source of the object is the value. Use this value
# when the object is a text value.
#
# If you are a new user of Ground Truth, it is recommended you review
# [Use an Input Manifest File ][1] in the Amazon SageMaker Developer
# Guide to learn how to create an input manifest file.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-input-data-input-manifest.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobS3DataSource AWS API Documentation
#
class LabelingJobS3DataSource < Struct.new(
:manifest_s3_uri)
SENSITIVE = []
include Aws::Structure
end
# An Amazon SNS data source used for streaming labeling jobs.
#
# @!attribute [rw] sns_topic_arn
# The Amazon SNS input topic Amazon Resource Name (ARN). Specify the
# ARN of the input topic you will use to send new data objects to a
# streaming labeling job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobSnsDataSource AWS API Documentation
#
class LabelingJobSnsDataSource < Struct.new(
:sns_topic_arn)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# <note markdown="1"> Labeling jobs fail after 30 days with an appropriate client error
# message.
#
# </note>
#
# @!attribute [rw] max_human_labeled_object_count
# The maximum number of objects that can be labeled by human workers.
# @return [Integer]
#
# @!attribute [rw] max_percentage_of_input_dataset_labeled
# The maximum number of input data objects that should be labeled.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobStoppingConditions AWS API Documentation
#
class LabelingJobStoppingConditions < Struct.new(
:max_human_labeled_object_count,
:max_percentage_of_input_dataset_labeled)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information about a labeling job.
#
# @!attribute [rw] labeling_job_name
# The name of the labeling job.
# @return [String]
#
# @!attribute [rw] labeling_job_arn
# The Amazon Resource Name (ARN) assigned to the labeling job when it
# was created.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the job was created (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the job was last modified (timestamp).
# @return [Time]
#
# @!attribute [rw] labeling_job_status
# The current status of the labeling job.
# @return [String]
#
# @!attribute [rw] label_counters
# Counts showing the progress of the labeling job.
# @return [Types::LabelCounters]
#
# @!attribute [rw] workteam_arn
# The Amazon Resource Name (ARN) of the work team assigned to the job.
# @return [String]
#
# @!attribute [rw] pre_human_task_lambda_arn
# The Amazon Resource Name (ARN) of a Lambda function. The function is
# run before each data object is sent to a worker.
# @return [String]
#
# @!attribute [rw] annotation_consolidation_lambda_arn
# The Amazon Resource Name (ARN) of the Lambda function used to
# consolidate the annotations from individual workers into a label for
# a data object. For more information, see [Annotation
# Consolidation][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.html
# @return [String]
#
# @!attribute [rw] failure_reason
# If the `LabelingJobStatus` field is `Failed`, this field contains a
# description of the error.
# @return [String]
#
# @!attribute [rw] labeling_job_output
# The location of the output produced by the labeling job.
# @return [Types::LabelingJobOutput]
#
# @!attribute [rw] input_config
# Input configuration for the labeling job.
# @return [Types::LabelingJobInputConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobSummary AWS API Documentation
#
class LabelingJobSummary < Struct.new(
:labeling_job_name,
:labeling_job_arn,
:creation_time,
:last_modified_time,
:labeling_job_status,
:label_counters,
:workteam_arn,
:pre_human_task_lambda_arn,
:annotation_consolidation_lambda_arn,
:failure_reason,
:labeling_job_output,
:input_config)
SENSITIVE = []
include Aws::Structure
end
# Metadata for a Lambda step.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the Lambda function that was run
# by this step execution.
# @return [String]
#
# @!attribute [rw] output_parameters
# A list of the output parameters of the Lambda step.
# @return [Array<Types::OutputParameter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LambdaStepMetadata AWS API Documentation
#
class LambdaStepMetadata < Struct.new(
:arn,
:output_parameters)
SENSITIVE = []
include Aws::Structure
end
# A value that indicates whether the update was successful.
#
# @!attribute [rw] status
# A value that indicates whether the update was made successful.
# @return [String]
#
# @!attribute [rw] failure_reason
# If the update wasn't successful, indicates the reason why it
# failed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LastUpdateStatus AWS API Documentation
#
class LastUpdateStatus < Struct.new(
:status,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# Lists a summary of the properties of a lineage group. A lineage group
# provides a group of shareable lineage entity resources.
#
# @!attribute [rw] lineage_group_arn
# The Amazon Resource Name (ARN) of the lineage group resource.
# @return [String]
#
# @!attribute [rw] lineage_group_name
# The name or Amazon Resource Name (ARN) of the lineage group.
# @return [String]
#
# @!attribute [rw] display_name
# The display name of the lineage group summary.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of the lineage group summary.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last modified time of the lineage group summary.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LineageGroupSummary AWS API Documentation
#
class LineageGroupSummary < Struct.new(
:lineage_group_arn,
:lineage_group_name,
:display_name,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_uri
# A filter that returns only actions with the specified source URI.
# @return [String]
#
# @!attribute [rw] action_type
# A filter that returns only actions of the specified type.
# @return [String]
#
# @!attribute [rw] created_after
# A filter that returns only actions created on or after the specified
# time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns only actions created on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous call to `ListActions` didn't return the full set of
# actions, the call returns a token for getting the next set of
# actions.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of actions to return in the response. The default
# value is 10.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListActionsRequest AWS API Documentation
#
class ListActionsRequest < Struct.new(
:source_uri,
:action_type,
:created_after,
:created_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_summaries
# A list of actions and their properties.
# @return [Array<Types::ActionSummary>]
#
# @!attribute [rw] next_token
# A token for getting the next set of actions, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListActionsResponse AWS API Documentation
#
class ListActionsResponse < Struct.new(
:action_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only algorithms created after the specified
# time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only algorithms created before the specified
# time (timestamp).
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of algorithms to return in the response.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in the algorithm name. This filter returns only algorithms
# whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] next_token
# If the response to a previous `ListAlgorithms` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of algorithms, use the token in the next request.
# @return [String]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results. The default is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for the results. The default is `Ascending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAlgorithmsInput AWS API Documentation
#
class ListAlgorithmsInput < Struct.new(
:creation_time_after,
:creation_time_before,
:max_results,
:name_contains,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] algorithm_summary_list
# >An array of `AlgorithmSummary` objects, each of which lists an
# algorithm.
# @return [Array<Types::AlgorithmSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of algorithms, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAlgorithmsOutput AWS API Documentation
#
class ListAlgorithmsOutput < Struct.new(
:algorithm_summary_list,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_name
# The name of the image.
# @return [String]
#
# @!attribute [rw] alias
# The alias of the image version.
# @return [String]
#
# @!attribute [rw] version
# The version of the image. If image version is not specified, the
# aliases of all versions of the image are listed.
# @return [Integer]
#
# @!attribute [rw] max_results
# The maximum number of aliases to return.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous call to `ListAliases` didn't return the full set of
# aliases, the call returns a token for retrieving the next set of
# aliases.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAliasesRequest AWS API Documentation
#
class ListAliasesRequest < Struct.new(
:image_name,
:alias,
:version,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] sage_maker_image_version_aliases
# A list of SageMaker image version aliases.
# @return [Array<String>]
#
# @!attribute [rw] next_token
# A token for getting the next set of aliases, if more aliases exist.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAliasesResponse AWS API Documentation
#
class ListAliasesResponse < Struct.new(
:sage_maker_image_version_aliases,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] max_results
# The maximum number of AppImageConfigs to return in the response. The
# default value is 10.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous call to `ListImages` didn't return the full set of
# AppImageConfigs, the call returns a token for getting the next set
# of AppImageConfigs.
# @return [String]
#
# @!attribute [rw] name_contains
# A filter that returns only AppImageConfigs whose name contains the
# specified string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only AppImageConfigs created on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only AppImageConfigs created on or after the
# specified time.
# @return [Time]
#
# @!attribute [rw] modified_time_before
# A filter that returns only AppImageConfigs modified on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] modified_time_after
# A filter that returns only AppImageConfigs modified on or after the
# specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `Descending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAppImageConfigsRequest AWS API Documentation
#
class ListAppImageConfigsRequest < Struct.new(
:max_results,
:next_token,
:name_contains,
:creation_time_before,
:creation_time_after,
:modified_time_before,
:modified_time_after,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# A token for getting the next set of AppImageConfigs, if there are
# any.
# @return [String]
#
# @!attribute [rw] app_image_configs
# A list of AppImageConfigs and their properties.
# @return [Array<Types::AppImageConfigDetails>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAppImageConfigsResponse AWS API Documentation
#
class ListAppImageConfigsResponse < Struct.new(
:next_token,
:app_image_configs)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the previous response was truncated, you will receive this token.
# Use it in your next request to receive the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# Returns a list up to a specified limit.
# @return [Integer]
#
# @!attribute [rw] sort_order
# The sort order for the results. The default is Ascending.
# @return [String]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results. The default is
# CreationTime.
# @return [String]
#
# @!attribute [rw] domain_id_equals
# A parameter to search for the domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name_equals
# A parameter to search by user profile name. If `SpaceNameEquals` is
# set, then this value cannot be set.
# @return [String]
#
# @!attribute [rw] space_name_equals
# A parameter to search by space name. If `UserProfileNameEquals` is
# set, then this value cannot be set.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAppsRequest AWS API Documentation
#
class ListAppsRequest < Struct.new(
:next_token,
:max_results,
:sort_order,
:sort_by,
:domain_id_equals,
:user_profile_name_equals,
:space_name_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] apps
# The list of apps.
# @return [Array<Types::AppDetails>]
#
# @!attribute [rw] next_token
# If the previous response was truncated, you will receive this token.
# Use it in your next request to receive the next set of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAppsResponse AWS API Documentation
#
class ListAppsResponse < Struct.new(
:apps,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_uri
# A filter that returns only artifacts with the specified source URI.
# @return [String]
#
# @!attribute [rw] artifact_type
# A filter that returns only artifacts of the specified type.
# @return [String]
#
# @!attribute [rw] created_after
# A filter that returns only artifacts created on or after the
# specified time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns only artifacts created on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous call to `ListArtifacts` didn't return the full set
# of artifacts, the call returns a token for getting the next set of
# artifacts.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of artifacts to return in the response. The
# default value is 10.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListArtifactsRequest AWS API Documentation
#
class ListArtifactsRequest < Struct.new(
:source_uri,
:artifact_type,
:created_after,
:created_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_summaries
# A list of artifacts and their properties.
# @return [Array<Types::ArtifactSummary>]
#
# @!attribute [rw] next_token
# A token for getting the next set of artifacts, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListArtifactsResponse AWS API Documentation
#
class ListArtifactsResponse < Struct.new(
:artifact_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_arn
# A filter that returns only associations with the specified source
# ARN.
# @return [String]
#
# @!attribute [rw] destination_arn
# A filter that returns only associations with the specified
# destination Amazon Resource Name (ARN).
# @return [String]
#
# @!attribute [rw] source_type
# A filter that returns only associations with the specified source
# type.
# @return [String]
#
# @!attribute [rw] destination_type
# A filter that returns only associations with the specified
# destination type.
# @return [String]
#
# @!attribute [rw] association_type
# A filter that returns only associations of the specified type.
# @return [String]
#
# @!attribute [rw] created_after
# A filter that returns only associations created on or after the
# specified time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns only associations created on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous call to `ListAssociations` didn't return the full
# set of associations, the call returns a token for getting the next
# set of associations.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of associations to return in the response. The
# default value is 10.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAssociationsRequest AWS API Documentation
#
class ListAssociationsRequest < Struct.new(
:source_arn,
:destination_arn,
:source_type,
:destination_type,
:association_type,
:created_after,
:created_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] association_summaries
# A list of associations and their properties.
# @return [Array<Types::AssociationSummary>]
#
# @!attribute [rw] next_token
# A token for getting the next set of associations, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAssociationsResponse AWS API Documentation
#
class ListAssociationsResponse < Struct.new(
:association_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# Request a list of jobs, using a filter for time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Request a list of jobs, using a filter for time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# Request a list of jobs, using a filter for time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# Request a list of jobs, using a filter for time.
# @return [Time]
#
# @!attribute [rw] name_contains
# Request a list of jobs, using a search filter for name.
# @return [String]
#
# @!attribute [rw] status_equals
# Request a list of jobs, using a filter for status.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for the results. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results. The default is `Name`.
# @return [String]
#
# @!attribute [rw] max_results
# Request a list of jobs up to a specified limit.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was truncated, you receive this token. Use
# it in your next request to receive the next set of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAutoMLJobsRequest AWS API Documentation
#
class ListAutoMLJobsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:status_equals,
:sort_order,
:sort_by,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_summaries
# Returns a summary list of jobs.
# @return [Array<Types::AutoMLJobSummary>]
#
# @!attribute [rw] next_token
# If the previous response was truncated, you receive this token. Use
# it in your next request to receive the next set of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAutoMLJobsResponse AWS API Documentation
#
class ListAutoMLJobsResponse < Struct.new(
:auto_ml_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_name
# List the candidates created for the job by providing the job's
# name.
# @return [String]
#
# @!attribute [rw] status_equals
# List the candidates for the job and filter by status.
# @return [String]
#
# @!attribute [rw] candidate_name_equals
# List the candidates for the job and filter by candidate name.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for the results. The default is `Ascending`.
# @return [String]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results. The default is
# `Descending`.
# @return [String]
#
# @!attribute [rw] max_results
# List the job's candidates up to a specified limit.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous response was truncated, you receive this token. Use
# it in your next request to receive the next set of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCandidatesForAutoMLJobRequest AWS API Documentation
#
class ListCandidatesForAutoMLJobRequest < Struct.new(
:auto_ml_job_name,
:status_equals,
:candidate_name_equals,
:sort_order,
:sort_by,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] candidates
# Summaries about the `AutoMLCandidates`.
# @return [Array<Types::AutoMLCandidate>]
#
# @!attribute [rw] next_token
# If the previous response was truncated, you receive this token. Use
# it in your next request to receive the next set of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCandidatesForAutoMLJobResponse AWS API Documentation
#
class ListCandidatesForAutoMLJobResponse < Struct.new(
:candidates,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only Git repositories that were created after
# the specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only Git repositories that were created before
# the specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only Git repositories that were last modified
# after the specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only Git repositories that were last modified
# before the specified time.
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of Git repositories to return in the response.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in the Git repositories name. This filter returns only
# repositories whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of a `ListCodeRepositoriesOutput` request was
# truncated, the response includes a `NextToken`. To get the next set
# of Git repositories, use the token in the next request.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `Name`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCodeRepositoriesInput AWS API Documentation
#
class ListCodeRepositoriesInput < Struct.new(
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:max_results,
:name_contains,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] code_repository_summary_list
# Gets a list of summaries of the Git repositories. Each summary
# specifies the following values for the repository:
#
# * Name
#
# * Amazon Resource Name (ARN)
#
# * Creation time
#
# * Last modified time
#
# * Configuration information, including the URL location of the
# repository and the ARN of the Amazon Web Services Secrets Manager
# secret that contains the credentials used to access the
# repository.
# @return [Array<Types::CodeRepositorySummary>]
#
# @!attribute [rw] next_token
# If the result of a `ListCodeRepositoriesOutput` request was
# truncated, the response includes a `NextToken`. To get the next set
# of Git repositories, use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCodeRepositoriesOutput AWS API Documentation
#
class ListCodeRepositoriesOutput < Struct.new(
:code_repository_summary_list,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the result of the previous `ListCompilationJobs` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of model compilation jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of model compilation jobs to return in the
# response.
# @return [Integer]
#
# @!attribute [rw] creation_time_after
# A filter that returns the model compilation jobs that were created
# after a specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns the model compilation jobs that were created
# before a specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns the model compilation jobs that were modified
# after a specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns the model compilation jobs that were modified
# before a specified time.
# @return [Time]
#
# @!attribute [rw] name_contains
# A filter that returns the model compilation jobs whose name contains
# a specified string.
# @return [String]
#
# @!attribute [rw] status_equals
# A filter that retrieves model compilation jobs with a specific
# `CompilationJobStatus` status.
# @return [String]
#
# @!attribute [rw] sort_by
# The field by which to sort results. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCompilationJobsRequest AWS API Documentation
#
class ListCompilationJobsRequest < Struct.new(
:next_token,
:max_results,
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:status_equals,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] compilation_job_summaries
# An array of [CompilationJobSummary][1] objects, each describing a
# model compilation job.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CompilationJobSummary.html
# @return [Array<Types::CompilationJobSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this
# `NextToken`. To retrieve the next set of model compilation jobs, use
# this token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListCompilationJobsResponse AWS API Documentation
#
class ListCompilationJobsResponse < Struct.new(
:compilation_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] source_uri
# A filter that returns only contexts with the specified source URI.
# @return [String]
#
# @!attribute [rw] context_type
# A filter that returns only contexts of the specified type.
# @return [String]
#
# @!attribute [rw] created_after
# A filter that returns only contexts created on or after the
# specified time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns only contexts created on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous call to `ListContexts` didn't return the full set
# of contexts, the call returns a token for getting the next set of
# contexts.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of contexts to return in the response. The
# default value is 10.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListContextsRequest AWS API Documentation
#
class ListContextsRequest < Struct.new(
:source_uri,
:context_type,
:created_after,
:created_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_summaries
# A list of contexts and their properties.
# @return [Array<Types::ContextSummary>]
#
# @!attribute [rw] next_token
# A token for getting the next set of contexts, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListContextsResponse AWS API Documentation
#
class ListContextsResponse < Struct.new(
:context_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# A filter that lists the data quality job definitions associated with
# the specified endpoint.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListDataQualityJobDefinitions`
# request was truncated, the response includes a `NextToken`. To
# retrieve the next set of transform jobs, use the token in the next
# request.>
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of data quality monitoring job definitions to
# return in the response.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in the data quality monitoring job definition name. This
# filter returns only data quality monitoring job definitions whose
# name contains the specified string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only data quality monitoring job definitions
# created before the specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only data quality monitoring job definitions
# created after the specified time.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDataQualityJobDefinitionsRequest AWS API Documentation
#
class ListDataQualityJobDefinitionsRequest < Struct.new(
:endpoint_name,
:sort_by,
:sort_order,
:next_token,
:max_results,
:name_contains,
:creation_time_before,
:creation_time_after)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_summaries
# A list of data quality monitoring job definitions.
# @return [Array<Types::MonitoringJobDefinitionSummary>]
#
# @!attribute [rw] next_token
# If the result of the previous `ListDataQualityJobDefinitions`
# request was truncated, the response includes a `NextToken`. To
# retrieve the next set of data quality monitoring job definitions,
# use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDataQualityJobDefinitionsResponse AWS API Documentation
#
class ListDataQualityJobDefinitionsResponse < Struct.new(
:job_definition_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to need tokening.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to select.
# @return [Integer]
#
# @!attribute [rw] creation_time_after
# Filter fleets where packaging job was created after specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Filter fleets where the edge packaging job was created before
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# Select fleets where the job was updated after X
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# Select fleets where the job was updated before X
# @return [Time]
#
# @!attribute [rw] name_contains
# Filter for fleets containing this name in their fleet device name.
# @return [String]
#
# @!attribute [rw] sort_by
# The column to sort by.
# @return [String]
#
# @!attribute [rw] sort_order
# What direction to sort in.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDeviceFleetsRequest AWS API Documentation
#
class ListDeviceFleetsRequest < Struct.new(
:next_token,
:max_results,
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_summaries
# Summary of the device fleet.
# @return [Array<Types::DeviceFleetSummary>]
#
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to need tokening.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDeviceFleetsResponse AWS API Documentation
#
class ListDeviceFleetsResponse < Struct.new(
:device_fleet_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to need tokening.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to select.
# @return [Integer]
#
# @!attribute [rw] latest_heartbeat_after
# Select fleets where the job was updated after X
# @return [Time]
#
# @!attribute [rw] model_name
# A filter that searches devices that contains this name in any of
# their models.
# @return [String]
#
# @!attribute [rw] device_fleet_name
# Filter for fleets containing this name in their device fleet name.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDevicesRequest AWS API Documentation
#
class ListDevicesRequest < Struct.new(
:next_token,
:max_results,
:latest_heartbeat_after,
:model_name,
:device_fleet_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_summaries
# Summary of devices.
# @return [Array<Types::DeviceSummary>]
#
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to need tokening.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDevicesResponse AWS API Documentation
#
class ListDevicesResponse < Struct.new(
:device_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the previous response was truncated, you will receive this token.
# Use it in your next request to receive the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# Returns a list up to a specified limit.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDomainsRequest AWS API Documentation
#
class ListDomainsRequest < Struct.new(
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domains
# The list of domains.
# @return [Array<Types::DomainDetails>]
#
# @!attribute [rw] next_token
# If the previous response was truncated, you will receive this token.
# Use it in your next request to receive the next set of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDomainsResponse AWS API Documentation
#
class ListDomainsResponse < Struct.new(
:domains,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to need tokening.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to select (50 by default).
# @return [Integer]
#
# @!attribute [rw] creation_time_after
# Selects edge deployment plans created after this time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Selects edge deployment plans created before this time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# Selects edge deployment plans that were last updated after this
# time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# Selects edge deployment plans that were last updated before this
# time.
# @return [Time]
#
# @!attribute [rw] name_contains
# Selects edge deployment plans with names containing this name.
# @return [String]
#
# @!attribute [rw] device_fleet_name_contains
# Selects edge deployment plans with a device fleet name containing
# this name.
# @return [String]
#
# @!attribute [rw] sort_by
# The column by which to sort the edge deployment plans. Can be one of
# `NAME`, `DEVICEFLEETNAME`, `CREATIONTIME`, `LASTMODIFIEDTIME`.
# @return [String]
#
# @!attribute [rw] sort_order
# The direction of the sorting (ascending or descending).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEdgeDeploymentPlansRequest AWS API Documentation
#
class ListEdgeDeploymentPlansRequest < Struct.new(
:next_token,
:max_results,
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:device_fleet_name_contains,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_summaries
# List of summaries of edge deployment plans.
# @return [Array<Types::EdgeDeploymentPlanSummary>]
#
# @!attribute [rw] next_token
# The token to use when calling the next page of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEdgeDeploymentPlansResponse AWS API Documentation
#
class ListEdgeDeploymentPlansResponse < Struct.new(
:edge_deployment_plan_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to need tokening.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of results to select.
# @return [Integer]
#
# @!attribute [rw] creation_time_after
# Select jobs where the job was created after specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Select jobs where the job was created before specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# Select jobs where the job was updated after specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# Select jobs where the job was updated before specified time.
# @return [Time]
#
# @!attribute [rw] name_contains
# Filter for jobs containing this name in their packaging job name.
# @return [String]
#
# @!attribute [rw] model_name_contains
# Filter for jobs where the model name contains this string.
# @return [String]
#
# @!attribute [rw] status_equals
# The job status to filter for.
# @return [String]
#
# @!attribute [rw] sort_by
# Use to specify what column to sort by.
# @return [String]
#
# @!attribute [rw] sort_order
# What direction to sort by.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEdgePackagingJobsRequest AWS API Documentation
#
class ListEdgePackagingJobsRequest < Struct.new(
:next_token,
:max_results,
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:model_name_contains,
:status_equals,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_packaging_job_summaries
# Summaries of edge packaging jobs.
# @return [Array<Types::EdgePackagingJobSummary>]
#
# @!attribute [rw] next_token
# Token to use when calling the next page of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEdgePackagingJobsResponse AWS API Documentation
#
class ListEdgePackagingJobsResponse < Struct.new(
:edge_packaging_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListEndpointConfig` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of endpoint configurations, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of training jobs to return in the response.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in the endpoint configuration name. This filter returns
# only endpoint configurations whose name contains the specified
# string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only endpoint configurations created before
# the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only endpoint configurations with a creation
# time greater than or equal to the specified time (timestamp).
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpointConfigsInput AWS API Documentation
#
class ListEndpointConfigsInput < Struct.new(
:sort_by,
:sort_order,
:next_token,
:max_results,
:name_contains,
:creation_time_before,
:creation_time_after)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_configs
# An array of endpoint configurations.
# @return [Array<Types::EndpointConfigSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of endpoint configurations, use it in the
# subsequent request
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpointConfigsOutput AWS API Documentation
#
class ListEndpointConfigsOutput < Struct.new(
:endpoint_configs,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] sort_by
# Sorts the list of results. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of a `ListEndpoints` request was truncated, the
# response includes a `NextToken`. To retrieve the next set of
# endpoints, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of endpoints to return in the response. This
# value defaults to 10.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in endpoint names. This filter returns only endpoints whose
# name contains the specified string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only endpoints that were created before the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only endpoints with a creation time greater
# than or equal to the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only endpoints that were modified before the
# specified timestamp.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only endpoints that were modified after the
# specified timestamp.
# @return [Time]
#
# @!attribute [rw] status_equals
# A filter that returns only endpoints with the specified status.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpointsInput AWS API Documentation
#
class ListEndpointsInput < Struct.new(
:sort_by,
:sort_order,
:next_token,
:max_results,
:name_contains,
:creation_time_before,
:creation_time_after,
:last_modified_time_before,
:last_modified_time_after,
:status_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoints
# An array or endpoint objects.
# @return [Array<Types::EndpointSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of training jobs, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListEndpointsOutput AWS API Documentation
#
class ListEndpointsOutput < Struct.new(
:endpoints,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] created_after
# A filter that returns only experiments created after the specified
# time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns only experiments created before the specified
# time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous call to `ListExperiments` didn't return the full
# set of experiments, the call returns a token for getting the next
# set of experiments.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of experiments to return in the response. The
# default value is 10.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListExperimentsRequest AWS API Documentation
#
class ListExperimentsRequest < Struct.new(
:created_after,
:created_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_summaries
# A list of the summaries of your experiments.
# @return [Array<Types::ExperimentSummary>]
#
# @!attribute [rw] next_token
# A token for getting the next set of experiments, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListExperimentsResponse AWS API Documentation
#
class ListExperimentsResponse < Struct.new(
:experiment_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name_contains
# A string that partially matches one or more `FeatureGroup`s names.
# Filters `FeatureGroup`s by name.
# @return [String]
#
# @!attribute [rw] feature_group_status_equals
# A `FeatureGroup` status. Filters by `FeatureGroup` status.
# @return [String]
#
# @!attribute [rw] offline_store_status_equals
# An `OfflineStore` status. Filters by `OfflineStore` status.
# @return [String]
#
# @!attribute [rw] creation_time_after
# Use this parameter to search for `FeatureGroups`s created after a
# specific date and time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Use this parameter to search for `FeatureGroups`s created before a
# specific date and time.
# @return [Time]
#
# @!attribute [rw] sort_order
# The order in which feature groups are listed.
# @return [String]
#
# @!attribute [rw] sort_by
# The value on which the feature group list is sorted.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results returned by `ListFeatureGroups`.
# @return [Integer]
#
# @!attribute [rw] next_token
# A token to resume pagination of `ListFeatureGroups` results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListFeatureGroupsRequest AWS API Documentation
#
class ListFeatureGroupsRequest < Struct.new(
:name_contains,
:feature_group_status_equals,
:offline_store_status_equals,
:creation_time_after,
:creation_time_before,
:sort_order,
:sort_by,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_summaries
# A summary of feature groups.
# @return [Array<Types::FeatureGroupSummary>]
#
# @!attribute [rw] next_token
# A token to resume pagination of `ListFeatureGroups` results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListFeatureGroupsResponse AWS API Documentation
#
class ListFeatureGroupsResponse < Struct.new(
:feature_group_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only flow definitions with a creation time
# greater than or equal to the specified timestamp.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only flow definitions that were created before
# the specified timestamp.
# @return [Time]
#
# @!attribute [rw] sort_order
# An optional value that specifies whether you want the results sorted
# in `Ascending` or `Descending` order.
# @return [String]
#
# @!attribute [rw] next_token
# A token to resume pagination.
# @return [String]
#
# @!attribute [rw] max_results
# The total number of items to return. If the total number of
# available items is more than the value specified in `MaxResults`,
# then a `NextToken` will be provided in the output that you can use
# to resume pagination.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListFlowDefinitionsRequest AWS API Documentation
#
class ListFlowDefinitionsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] flow_definition_summaries
# An array of objects describing the flow definitions.
# @return [Array<Types::FlowDefinitionSummary>]
#
# @!attribute [rw] next_token
# A token to resume pagination.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListFlowDefinitionsResponse AWS API Documentation
#
class ListFlowDefinitionsResponse < Struct.new(
:flow_definition_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_name
# The name of the hub to list the content versions of.
# @return [String]
#
# @!attribute [rw] hub_content_type
# The type of hub content to list versions of.
# @return [String]
#
# @!attribute [rw] hub_content_name
# The name of the hub content.
# @return [String]
#
# @!attribute [rw] min_version
# The lower bound of the hub content versions to list.
# @return [String]
#
# @!attribute [rw] max_schema_version
# The upper bound of the hub content schema version.
# @return [String]
#
# @!attribute [rw] creation_time_before
# Only list hub content versions that were created before the time
# specified.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# Only list hub content versions that were created after the time
# specified.
# @return [Time]
#
# @!attribute [rw] sort_by
# Sort hub content versions by either name or creation time.
# @return [String]
#
# @!attribute [rw] sort_order
# Sort hub content versions by ascending or descending order.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of hub content versions to list.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the response to a previous `ListHubContentVersions` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of hub content versions, use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHubContentVersionsRequest AWS API Documentation
#
class ListHubContentVersionsRequest < Struct.new(
:hub_name,
:hub_content_type,
:hub_content_name,
:min_version,
:max_schema_version,
:creation_time_before,
:creation_time_after,
:sort_by,
:sort_order,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_content_summaries
# The summaries of the listed hub content versions.
# @return [Array<Types::HubContentInfo>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of hub content versions, use it in the
# subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHubContentVersionsResponse AWS API Documentation
#
class ListHubContentVersionsResponse < Struct.new(
:hub_content_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_name
# The name of the hub to list the contents of.
# @return [String]
#
# @!attribute [rw] hub_content_type
# The type of hub content to list.
# @return [String]
#
# @!attribute [rw] name_contains
# Only list hub content if the name contains the specified string.
# @return [String]
#
# @!attribute [rw] max_schema_version
# The upper bound of the hub content schema verion.
# @return [String]
#
# @!attribute [rw] creation_time_before
# Only list hub content that was created before the time specified.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# Only list hub content that was created after the time specified.
# @return [Time]
#
# @!attribute [rw] sort_by
# Sort hub content versions by either name or creation time.
# @return [String]
#
# @!attribute [rw] sort_order
# Sort hubs by ascending or descending order.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum amount of hub content to list.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the response to a previous `ListHubContents` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of hub content, use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHubContentsRequest AWS API Documentation
#
class ListHubContentsRequest < Struct.new(
:hub_name,
:hub_content_type,
:name_contains,
:max_schema_version,
:creation_time_before,
:creation_time_after,
:sort_by,
:sort_order,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_content_summaries
# The summaries of the listed hub content.
# @return [Array<Types::HubContentInfo>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of hub content, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHubContentsResponse AWS API Documentation
#
class ListHubContentsResponse < Struct.new(
:hub_content_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name_contains
# Only list hubs with names that contain the specified string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# Only list hubs that were created before the time specified.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# Only list hubs that were created after the time specified.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# Only list hubs that were last modified before the time specified.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# Only list hubs that were last modified after the time specified.
# @return [Time]
#
# @!attribute [rw] sort_by
# Sort hubs by either name or creation time.
# @return [String]
#
# @!attribute [rw] sort_order
# Sort hubs by ascending or descending order.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of hubs to list.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the response to a previous `ListHubs` request was truncated, the
# response includes a `NextToken`. To retrieve the next set of hubs,
# use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHubsRequest AWS API Documentation
#
class ListHubsRequest < Struct.new(
:name_contains,
:creation_time_before,
:creation_time_after,
:last_modified_time_before,
:last_modified_time_after,
:sort_by,
:sort_order,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_summaries
# The summaries of the listed hubs.
# @return [Array<Types::HubInfo>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of hubs, use it in the subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHubsResponse AWS API Documentation
#
class ListHubsResponse < Struct.new(
:hub_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only human task user interfaces with a
# creation time greater than or equal to the specified timestamp.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only human task user interfaces that were
# created before the specified timestamp.
# @return [Time]
#
# @!attribute [rw] sort_order
# An optional value that specifies whether you want the results sorted
# in `Ascending` or `Descending` order.
# @return [String]
#
# @!attribute [rw] next_token
# A token to resume pagination.
# @return [String]
#
# @!attribute [rw] max_results
# The total number of items to return. If the total number of
# available items is more than the value specified in `MaxResults`,
# then a `NextToken` will be provided in the output that you can use
# to resume pagination.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHumanTaskUisRequest AWS API Documentation
#
class ListHumanTaskUisRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] human_task_ui_summaries
# An array of objects describing the human task user interfaces.
# @return [Array<Types::HumanTaskUiSummary>]
#
# @!attribute [rw] next_token
# A token to resume pagination.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHumanTaskUisResponse AWS API Documentation
#
class ListHumanTaskUisResponse < Struct.new(
:human_task_ui_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the result of the previous `ListHyperParameterTuningJobs` request
# was truncated, the response includes a `NextToken`. To retrieve the
# next set of tuning jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of tuning jobs to return. The default value is
# 10.
# @return [Integer]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `Name`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @!attribute [rw] name_contains
# A string in the tuning job name. This filter returns only tuning
# jobs whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] creation_time_after
# A filter that returns only tuning jobs that were created after the
# specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only tuning jobs that were created before the
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only tuning jobs that were modified after the
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only tuning jobs that were modified before the
# specified time.
# @return [Time]
#
# @!attribute [rw] status_equals
# A filter that returns only tuning jobs with the specified status.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHyperParameterTuningJobsRequest AWS API Documentation
#
class ListHyperParameterTuningJobsRequest < Struct.new(
:next_token,
:max_results,
:sort_by,
:sort_order,
:name_contains,
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:status_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hyper_parameter_tuning_job_summaries
# A list of [HyperParameterTuningJobSummary][1] objects that describe
# the tuning jobs that the `ListHyperParameterTuningJobs` request
# returned.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobSummary.html
# @return [Array<Types::HyperParameterTuningJobSummary>]
#
# @!attribute [rw] next_token
# If the result of this `ListHyperParameterTuningJobs` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of tuning jobs, use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListHyperParameterTuningJobsResponse AWS API Documentation
#
class ListHyperParameterTuningJobsResponse < Struct.new(
:hyper_parameter_tuning_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only versions created on or after the
# specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only versions created on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] image_name
# The name of the image to list the versions of.
# @return [String]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only versions modified on or after the
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only versions modified on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of versions to return in the response. The
# default value is 10.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous call to `ListImageVersions` didn't return the full
# set of versions, the call returns a token for getting the next set
# of versions.
# @return [String]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CREATION_TIME`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `DESCENDING`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListImageVersionsRequest AWS API Documentation
#
class ListImageVersionsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:image_name,
:last_modified_time_after,
:last_modified_time_before,
:max_results,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_versions
# A list of versions and their properties.
# @return [Array<Types::ImageVersion>]
#
# @!attribute [rw] next_token
# A token for getting the next set of versions, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListImageVersionsResponse AWS API Documentation
#
class ListImageVersionsResponse < Struct.new(
:image_versions,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only images created on or after the specified
# time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only images created on or before the specified
# time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only images modified on or after the specified
# time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only images modified on or before the
# specified time.
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of images to return in the response. The default
# value is 10.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A filter that returns only images whose name contains the specified
# string.
# @return [String]
#
# @!attribute [rw] next_token
# If the previous call to `ListImages` didn't return the full set of
# images, the call returns a token for getting the next set of images.
# @return [String]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CREATION_TIME`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `DESCENDING`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListImagesRequest AWS API Documentation
#
class ListImagesRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:max_results,
:name_contains,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] images
# A list of images and their properties.
# @return [Array<Types::Image>]
#
# @!attribute [rw] next_token
# A token for getting the next set of images, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListImagesResponse AWS API Documentation
#
class ListImagesResponse < Struct.new(
:images,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name_contains
# Selects inference experiments whose names contain this name.
# @return [String]
#
# @!attribute [rw] type
# Selects inference experiments of this type. For the possible types
# of inference experiments, see [CreateInferenceExperiment][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceExperiment.html
# @return [String]
#
# @!attribute [rw] status_equals
# Selects inference experiments which are in this status. For the
# possible statuses, see [DescribeInferenceExperiment][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeInferenceExperiment.html
# @return [String]
#
# @!attribute [rw] creation_time_after
# Selects inference experiments which were created after this
# timestamp.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Selects inference experiments which were created before this
# timestamp.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# Selects inference experiments which were last modified after this
# timestamp.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# Selects inference experiments which were last modified before this
# timestamp.
# @return [Time]
#
# @!attribute [rw] sort_by
# The column by which to sort the listed inference experiments.
# @return [String]
#
# @!attribute [rw] sort_order
# The direction of sorting (ascending or descending).
# @return [String]
#
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to need tokening.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to select.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListInferenceExperimentsRequest AWS API Documentation
#
class ListInferenceExperimentsRequest < Struct.new(
:name_contains,
:type,
:status_equals,
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] inference_experiments
# List of inference experiments.
# @return [Array<Types::InferenceExperimentSummary>]
#
# @!attribute [rw] next_token
# The token to use when calling the next page of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListInferenceExperimentsResponse AWS API Documentation
#
class ListInferenceExperimentsResponse < Struct.new(
:inference_experiments,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_name
# The name for the Inference Recommender job.
# @return [String]
#
# @!attribute [rw] status
# A filter to return benchmarks of a specified status. If this field
# is left empty, then all benchmarks are returned.
# @return [String]
#
# @!attribute [rw] step_type
# A filter to return details about the specified type of subtask.
#
# `BENCHMARK`: Evaluate the performance of your model on different
# instance types.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to return.
# @return [Integer]
#
# @!attribute [rw] next_token
# A token that you can specify to return more results from the list.
# Specify this field if you have a token that was returned from a
# previous request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListInferenceRecommendationsJobStepsRequest AWS API Documentation
#
class ListInferenceRecommendationsJobStepsRequest < Struct.new(
:job_name,
:status,
:step_type,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] steps
# A list of all subtask details in Inference Recommender.
# @return [Array<Types::InferenceRecommendationsJobStep>]
#
# @!attribute [rw] next_token
# A token that you can specify in your next request to return more
# results from the list.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListInferenceRecommendationsJobStepsResponse AWS API Documentation
#
class ListInferenceRecommendationsJobStepsResponse < Struct.new(
:steps,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only jobs created after the specified time
# (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only jobs created before the specified time
# (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only jobs that were last modified after the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only jobs that were last modified before the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] name_contains
# A string in the job name. This filter returns only recommendations
# whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] status_equals
# A filter that retrieves only inference recommendations jobs with a
# specific status.
# @return [String]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for the results.
# @return [String]
#
# @!attribute [rw] next_token
# If the response to a previous
# `ListInferenceRecommendationsJobsRequest` request was truncated, the
# response includes a `NextToken`. To retrieve the next set of
# recommendations, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of recommendations to return in the response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListInferenceRecommendationsJobsRequest AWS API Documentation
#
class ListInferenceRecommendationsJobsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:status_equals,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] inference_recommendations_jobs
# The recommendations created from the Amazon SageMaker Inference
# Recommender job.
# @return [Array<Types::InferenceRecommendationsJob>]
#
# @!attribute [rw] next_token
# A token for getting the next set of recommendations, if there are
# any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListInferenceRecommendationsJobsResponse AWS API Documentation
#
class ListInferenceRecommendationsJobsResponse < Struct.new(
:inference_recommendations_jobs,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteam_arn
# The Amazon Resource Name (ARN) of the work team for which you want
# to see labeling jobs for.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of labeling jobs to return in each page of the
# response.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the result of the previous `ListLabelingJobsForWorkteam` request
# was truncated, the response includes a `NextToken`. To retrieve the
# next set of labeling jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] creation_time_after
# A filter that returns only labeling jobs created after the specified
# time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only labeling jobs created before the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] job_reference_code_contains
# A filter the limits jobs to only the ones whose job reference code
# contains the specified string.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobsForWorkteamRequest AWS API Documentation
#
class ListLabelingJobsForWorkteamRequest < Struct.new(
:workteam_arn,
:max_results,
:next_token,
:creation_time_after,
:creation_time_before,
:job_reference_code_contains,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] labeling_job_summary_list
# An array of `LabelingJobSummary` objects, each describing a labeling
# job.
# @return [Array<Types::LabelingJobForWorkteamSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of labeling jobs, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobsForWorkteamResponse AWS API Documentation
#
class ListLabelingJobsForWorkteamResponse < Struct.new(
:labeling_job_summary_list,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only labeling jobs created after the specified
# time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only labeling jobs created before the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only labeling jobs modified after the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only labeling jobs modified before the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of labeling jobs to return in each page of the
# response.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the result of the previous `ListLabelingJobs` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of labeling jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] name_contains
# A string in the labeling job name. This filter returns only labeling
# jobs whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @!attribute [rw] status_equals
# A filter that retrieves only labeling jobs with a specific status.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobsRequest AWS API Documentation
#
class ListLabelingJobsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:max_results,
:next_token,
:name_contains,
:sort_by,
:sort_order,
:status_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] labeling_job_summary_list
# An array of `LabelingJobSummary` objects, each describing a labeling
# job.
# @return [Array<Types::LabelingJobSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of labeling jobs, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLabelingJobsResponse AWS API Documentation
#
class ListLabelingJobsResponse < Struct.new(
:labeling_job_summary_list,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] created_after
# A timestamp to filter against lineage groups created after a certain
# point in time.
# @return [Time]
#
# @!attribute [rw] created_before
# A timestamp to filter against lineage groups created before a
# certain point in time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results. The default is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for the results. The default is `Ascending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of algorithms, use it in the subsequent
# request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of endpoints to return in the response. This
# value defaults to 10.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLineageGroupsRequest AWS API Documentation
#
class ListLineageGroupsRequest < Struct.new(
:created_after,
:created_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] lineage_group_summaries
# A list of lineage groups and their properties.
# @return [Array<Types::LineageGroupSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of algorithms, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListLineageGroupsResponse AWS API Documentation
#
class ListLineageGroupsResponse < Struct.new(
:lineage_group_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# Name of the endpoint to monitor for model bias.
# @return [String]
#
# @!attribute [rw] sort_by
# Whether to sort results by the `Name` or `CreationTime` field. The
# default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# Whether to sort the results in `Ascending` or `Descending` order.
# The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# The token returned if the response is truncated. To retrieve the
# next set of job executions, use it in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of model bias jobs to return in the response. The
# default value is 10.
# @return [Integer]
#
# @!attribute [rw] name_contains
# Filter for model bias jobs whose name contains a specified string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only model bias jobs created before a
# specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only model bias jobs created after a specified
# time.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelBiasJobDefinitionsRequest AWS API Documentation
#
class ListModelBiasJobDefinitionsRequest < Struct.new(
:endpoint_name,
:sort_by,
:sort_order,
:next_token,
:max_results,
:name_contains,
:creation_time_before,
:creation_time_after)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_summaries
# A JSON array in which each element is a summary for a model bias
# jobs.
# @return [Array<Types::MonitoringJobDefinitionSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of jobs, use it in the subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelBiasJobDefinitionsResponse AWS API Documentation
#
class ListModelBiasJobDefinitionsResponse < Struct.new(
:job_definition_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_name
# List export jobs for the model card with the specified name.
# @return [String]
#
# @!attribute [rw] model_card_version
# List export jobs for the model card with the specified version.
# @return [Integer]
#
# @!attribute [rw] creation_time_after
# Only list model card export jobs that were created after the time
# specified.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Only list model card export jobs that were created before the time
# specified.
# @return [Time]
#
# @!attribute [rw] model_card_export_job_name_contains
# Only list model card export jobs with names that contain the
# specified string.
# @return [String]
#
# @!attribute [rw] status_equals
# Only list model card export jobs with the specified status.
# @return [String]
#
# @!attribute [rw] sort_by
# Sort model card export jobs by either name or creation time. Sorts
# by creation time by default.
# @return [String]
#
# @!attribute [rw] sort_order
# Sort model card export jobs by ascending or descending order.
# @return [String]
#
# @!attribute [rw] next_token
# If the response to a previous `ListModelCardExportJobs` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of model card export jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of model card export jobs to list.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelCardExportJobsRequest AWS API Documentation
#
class ListModelCardExportJobsRequest < Struct.new(
:model_card_name,
:model_card_version,
:creation_time_after,
:creation_time_before,
:model_card_export_job_name_contains,
:status_equals,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_export_job_summaries
# The summaries of the listed model card export jobs.
# @return [Array<Types::ModelCardExportJobSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of model card export jobs, use it in the
# subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelCardExportJobsResponse AWS API Documentation
#
class ListModelCardExportJobsResponse < Struct.new(
:model_card_export_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# Only list model card versions that were created after the time
# specified.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Only list model card versions that were created before the time
# specified.
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of model card versions to list.
# @return [Integer]
#
# @!attribute [rw] model_card_name
# List model card versions for the model card with the specified name.
# @return [String]
#
# @!attribute [rw] model_card_status
# Only list model card versions with the specified approval status.
# @return [String]
#
# @!attribute [rw] next_token
# If the response to a previous `ListModelCardVersions` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of model card versions, use the token in the next request.
# @return [String]
#
# @!attribute [rw] sort_by
# Sort listed model card versions by version. Sorts by version by
# default.
# @return [String]
#
# @!attribute [rw] sort_order
# Sort model card versions by ascending or descending order.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelCardVersionsRequest AWS API Documentation
#
class ListModelCardVersionsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:max_results,
:model_card_name,
:model_card_status,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_version_summary_list
# The summaries of the listed versions of the model card.
# @return [Array<Types::ModelCardVersionSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of model card versions, use it in the
# subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelCardVersionsResponse AWS API Documentation
#
class ListModelCardVersionsResponse < Struct.new(
:model_card_version_summary_list,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# Only list model cards that were created after the time specified.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# Only list model cards that were created before the time specified.
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of model cards to list.
# @return [Integer]
#
# @!attribute [rw] name_contains
# Only list model cards with names that contain the specified string.
# @return [String]
#
# @!attribute [rw] model_card_status
# Only list model cards with the specified approval status.
# @return [String]
#
# @!attribute [rw] next_token
# If the response to a previous `ListModelCards` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of model cards, use the token in the next request.
# @return [String]
#
# @!attribute [rw] sort_by
# Sort model cards by either name or creation time. Sorts by creation
# time by default.
# @return [String]
#
# @!attribute [rw] sort_order
# Sort model cards by ascending or descending order.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelCardsRequest AWS API Documentation
#
class ListModelCardsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:max_results,
:name_contains,
:model_card_status,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_summaries
# The summaries of the listed model cards.
# @return [Array<Types::ModelCardSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of model cards, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelCardsResponse AWS API Documentation
#
class ListModelCardsResponse < Struct.new(
:model_card_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# Name of the endpoint to monitor for model explainability.
# @return [String]
#
# @!attribute [rw] sort_by
# Whether to sort results by the `Name` or `CreationTime` field. The
# default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# Whether to sort the results in `Ascending` or `Descending` order.
# The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# The token returned if the response is truncated. To retrieve the
# next set of job executions, use it in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of jobs to return in the response. The default
# value is 10.
# @return [Integer]
#
# @!attribute [rw] name_contains
# Filter for model explainability jobs whose name contains a specified
# string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only model explainability jobs created before
# a specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only model explainability jobs created after a
# specified time.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelExplainabilityJobDefinitionsRequest AWS API Documentation
#
class ListModelExplainabilityJobDefinitionsRequest < Struct.new(
:endpoint_name,
:sort_by,
:sort_order,
:next_token,
:max_results,
:name_contains,
:creation_time_before,
:creation_time_after)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_summaries
# A JSON array in which each element is a summary for a explainability
# bias jobs.
# @return [Array<Types::MonitoringJobDefinitionSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of jobs, use it in the subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelExplainabilityJobDefinitionsResponse AWS API Documentation
#
class ListModelExplainabilityJobDefinitionsResponse < Struct.new(
:job_definition_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] search_expression
# One or more filters 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. Specify
# the Framework, FrameworkVersion, Domain or Task to filter supported.
# Filter names and values are case-sensitive.
# @return [Types::ModelMetadataSearchExpression]
#
# @!attribute [rw] next_token
# If the response to a previous `ListModelMetadataResponse` request
# was truncated, the response includes a NextToken. To retrieve the
# next set of model metadata, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of models to return in the response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelMetadataRequest AWS API Documentation
#
class ListModelMetadataRequest < Struct.new(
:search_expression,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_metadata_summaries
# A structure that holds model metadata.
# @return [Array<Types::ModelMetadataSummary>]
#
# @!attribute [rw] next_token
# A token for getting the next set of recommendations, if there are
# any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelMetadataResponse AWS API Documentation
#
class ListModelMetadataResponse < Struct.new(
:model_metadata_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only model groups created after the specified
# time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only model groups created before the specified
# time.
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of results to return in the response.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in the model group name. This filter returns only model
# groups whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListModelPackageGroups` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of model groups, use the token in the next request.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelPackageGroupsInput AWS API Documentation
#
class ListModelPackageGroupsInput < Struct.new(
:creation_time_after,
:creation_time_before,
:max_results,
:name_contains,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_summary_list
# A list of summaries of the model groups in your Amazon Web Services
# account.
# @return [Array<Types::ModelPackageGroupSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of model groups, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelPackageGroupsOutput AWS API Documentation
#
class ListModelPackageGroupsOutput < Struct.new(
:model_package_group_summary_list,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only model packages created after the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only model packages created before the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of model packages to return in the response.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in the model package name. This filter returns only model
# packages whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] model_approval_status
# A filter that returns only the model packages with the specified
# approval status.
# @return [String]
#
# @!attribute [rw] model_package_group_name
# A filter that returns only model versions that belong to the
# specified model group.
# @return [String]
#
# @!attribute [rw] model_package_type
# A filter that returns only the model packages of the specified type.
# This can be one of the following values.
#
# * `UNVERSIONED` - List only unversioined models. This is the default
# value if no `ModelPackageType` is specified.
#
# * `VERSIONED` - List only versioned models.
#
# * `BOTH` - List both versioned and unversioned models.
# @return [String]
#
# @!attribute [rw] next_token
# If the response to a previous `ListModelPackages` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of model packages, use the token in the next request.
# @return [String]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results. The default is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for the results. The default is `Ascending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelPackagesInput AWS API Documentation
#
class ListModelPackagesInput < Struct.new(
:creation_time_after,
:creation_time_before,
:max_results,
:name_contains,
:model_approval_status,
:model_package_group_name,
:model_package_type,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_summary_list
# An array of `ModelPackageSummary` objects, each of which lists a
# model package.
# @return [Array<Types::ModelPackageSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of model packages, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelPackagesOutput AWS API Documentation
#
class ListModelPackagesOutput < Struct.new(
:model_package_summary_list,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# A filter that returns only model quality monitoring job definitions
# that are associated with the specified endpoint.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListModelQualityJobDefinitions`
# request was truncated, the response includes a `NextToken`. To
# retrieve the next set of model quality monitoring job definitions,
# use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to return in a call to
# `ListModelQualityJobDefinitions`.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in the transform job name. This filter returns only model
# quality monitoring job definitions whose name contains the specified
# string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only model quality monitoring job definitions
# created before the specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only model quality monitoring job definitions
# created after the specified time.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelQualityJobDefinitionsRequest AWS API Documentation
#
class ListModelQualityJobDefinitionsRequest < Struct.new(
:endpoint_name,
:sort_by,
:sort_order,
:next_token,
:max_results,
:name_contains,
:creation_time_before,
:creation_time_after)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_definition_summaries
# A list of summaries of model quality monitoring job definitions.
# @return [Array<Types::MonitoringJobDefinitionSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of model quality monitoring job
# definitions, use it in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelQualityJobDefinitionsResponse AWS API Documentation
#
class ListModelQualityJobDefinitionsResponse < Struct.new(
:job_definition_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] sort_by
# Sorts the list of results. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the response to a previous `ListModels` request was truncated,
# the response includes a `NextToken`. To retrieve the next set of
# models, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of models to return in the response.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A string in the model name. This filter returns only models whose
# name contains the specified string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only models created before the specified time
# (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only models with a creation time greater than
# or equal to the specified time (timestamp).
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelsInput AWS API Documentation
#
class ListModelsInput < Struct.new(
:sort_by,
:sort_order,
:next_token,
:max_results,
:name_contains,
:creation_time_before,
:creation_time_after)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] models
# An array of `ModelSummary` objects, each of which lists a model.
# @return [Array<Types::ModelSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of models, use it in the subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelsOutput AWS API Documentation
#
class ListModelsOutput < Struct.new(
:models,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# The name of a monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_alert_name
# The name of a monitoring alert.
# @return [String]
#
# @!attribute [rw] sort_by
# The field used to sort results. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order, whether `Ascending` or `Descending`, of the alert
# history. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListMonitoringAlertHistory` request
# was truncated, the response includes a `NextToken`. To retrieve the
# next set of alerts in the history, use the token in the next
# request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to display. The default is 100.
# @return [Integer]
#
# @!attribute [rw] creation_time_before
# A filter that returns only alerts created on or before the specified
# time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only alerts created on or after the specified
# time.
# @return [Time]
#
# @!attribute [rw] status_equals
# A filter that retrieves only alerts with a specific status.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringAlertHistoryRequest AWS API Documentation
#
class ListMonitoringAlertHistoryRequest < Struct.new(
:monitoring_schedule_name,
:monitoring_alert_name,
:sort_by,
:sort_order,
:next_token,
:max_results,
:creation_time_before,
:creation_time_after,
:status_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_alert_history
# An alert history for a model monitoring schedule.
# @return [Array<Types::MonitoringAlertHistorySummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of alerts, use it in the subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringAlertHistoryResponse AWS API Documentation
#
class ListMonitoringAlertHistoryResponse < Struct.new(
:monitoring_alert_history,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# The name of a monitoring schedule.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListMonitoringAlerts` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of alerts in the history, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to display. The default is 100.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringAlertsRequest AWS API Documentation
#
class ListMonitoringAlertsRequest < Struct.new(
:monitoring_schedule_name,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_alert_summaries
# A JSON array where each element is a summary for a monitoring alert.
# @return [Array<Types::MonitoringAlertSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of alerts, use it in the subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringAlertsResponse AWS API Documentation
#
class ListMonitoringAlertsResponse < Struct.new(
:monitoring_alert_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# Name of a specific schedule to fetch jobs for.
# @return [String]
#
# @!attribute [rw] endpoint_name
# Name of a specific endpoint to fetch jobs for.
# @return [String]
#
# @!attribute [rw] sort_by
# Whether to sort results by `Status`, `CreationTime`, `ScheduledTime`
# field. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# Whether to sort the results in `Ascending` or `Descending` order.
# The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# The token returned if the response is truncated. To retrieve the
# next set of job executions, use it in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of jobs to return in the response. The default
# value is 10.
# @return [Integer]
#
# @!attribute [rw] scheduled_time_before
# Filter for jobs scheduled before a specified time.
# @return [Time]
#
# @!attribute [rw] scheduled_time_after
# Filter for jobs scheduled after a specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only jobs created before a specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only jobs created after a specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only jobs modified after a specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only jobs modified before a specified time.
# @return [Time]
#
# @!attribute [rw] status_equals
# A filter that retrieves only jobs with a specific status.
# @return [String]
#
# @!attribute [rw] monitoring_job_definition_name
# Gets a list of the monitoring job runs of the specified monitoring
# job definitions.
# @return [String]
#
# @!attribute [rw] monitoring_type_equals
# A filter that returns only the monitoring job runs of the specified
# monitoring type.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringExecutionsRequest AWS API Documentation
#
class ListMonitoringExecutionsRequest < Struct.new(
:monitoring_schedule_name,
:endpoint_name,
:sort_by,
:sort_order,
:next_token,
:max_results,
:scheduled_time_before,
:scheduled_time_after,
:creation_time_before,
:creation_time_after,
:last_modified_time_before,
:last_modified_time_after,
:status_equals,
:monitoring_job_definition_name,
:monitoring_type_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_execution_summaries
# A JSON array in which each element is a summary for a monitoring
# execution.
# @return [Array<Types::MonitoringExecutionSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of jobs, use it in the subsequent reques
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringExecutionsResponse AWS API Documentation
#
class ListMonitoringExecutionsResponse < Struct.new(
:monitoring_execution_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# Name of a specific endpoint to fetch schedules for.
# @return [String]
#
# @!attribute [rw] sort_by
# Whether to sort results by `Status`, `CreationTime`, `ScheduledTime`
# field. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# Whether to sort the results in `Ascending` or `Descending` order.
# The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# The token returned if the response is truncated. To retrieve the
# next set of job executions, use it in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of jobs to return in the response. The default
# value is 10.
# @return [Integer]
#
# @!attribute [rw] name_contains
# Filter for monitoring schedules whose name contains a specified
# string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only monitoring schedules created before a
# specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only monitoring schedules created after a
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only monitoring schedules modified before a
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only monitoring schedules modified after a
# specified time.
# @return [Time]
#
# @!attribute [rw] status_equals
# A filter that returns only monitoring schedules modified before a
# specified time.
# @return [String]
#
# @!attribute [rw] monitoring_job_definition_name
# Gets a list of the monitoring schedules for the specified monitoring
# job definition.
# @return [String]
#
# @!attribute [rw] monitoring_type_equals
# A filter that returns only the monitoring schedules for the
# specified monitoring type.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringSchedulesRequest AWS API Documentation
#
class ListMonitoringSchedulesRequest < Struct.new(
:endpoint_name,
:sort_by,
:sort_order,
:next_token,
:max_results,
:name_contains,
:creation_time_before,
:creation_time_after,
:last_modified_time_before,
:last_modified_time_after,
:status_equals,
:monitoring_job_definition_name,
:monitoring_type_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_summaries
# A JSON array in which each element is a summary for a monitoring
# schedule.
# @return [Array<Types::MonitoringScheduleSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of jobs, use it in the subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringSchedulesResponse AWS API Documentation
#
class ListMonitoringSchedulesResponse < Struct.new(
:monitoring_schedule_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the result of a `ListNotebookInstanceLifecycleConfigs` request
# was truncated, the response includes a `NextToken`. To get the next
# set of lifecycle configurations, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of lifecycle configurations to return in the
# response.
# @return [Integer]
#
# @!attribute [rw] sort_by
# Sorts the list of results. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results.
# @return [String]
#
# @!attribute [rw] name_contains
# A string in the lifecycle configuration name. This filter returns
# only lifecycle configurations whose name contains the specified
# string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only lifecycle configurations that were
# created before the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only lifecycle configurations that were
# created after the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only lifecycle configurations that were
# modified before the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only lifecycle configurations that were
# modified after the specified time (timestamp).
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstanceLifecycleConfigsInput AWS API Documentation
#
class ListNotebookInstanceLifecycleConfigsInput < Struct.new(
:next_token,
:max_results,
:sort_by,
:sort_order,
:name_contains,
:creation_time_before,
:creation_time_after,
:last_modified_time_before,
:last_modified_time_after)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To get
# the next set of lifecycle configurations, use it in the next
# request.
# @return [String]
#
# @!attribute [rw] notebook_instance_lifecycle_configs
# An array of `NotebookInstanceLifecycleConfiguration` objects, each
# listing a lifecycle configuration.
# @return [Array<Types::NotebookInstanceLifecycleConfigSummary>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstanceLifecycleConfigsOutput AWS API Documentation
#
class ListNotebookInstanceLifecycleConfigsOutput < Struct.new(
:next_token,
:notebook_instance_lifecycle_configs)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the previous call to the `ListNotebookInstances` is truncated,
# the response includes a `NextToken`. You can use this token in your
# subsequent `ListNotebookInstances` request to fetch the next set of
# notebook instances.
#
# <note markdown="1"> You might specify a filter or a sort order in your request. When
# response is truncated, you must use the same values for the filer
# and sort order in the next request.
#
# </note>
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of notebook instances to return.
# @return [Integer]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `Name`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results.
# @return [String]
#
# @!attribute [rw] name_contains
# A string in the notebook instances' name. This filter returns only
# notebook instances whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only notebook instances that were created
# before the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only notebook instances that were created
# after the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only notebook instances that were modified
# before the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only notebook instances that were modified
# after the specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] status_equals
# A filter that returns only notebook instances with the specified
# status.
# @return [String]
#
# @!attribute [rw] notebook_instance_lifecycle_config_name_contains
# A string in the name of a notebook instances lifecycle configuration
# associated with this notebook instance. This filter returns only
# notebook instances associated with a lifecycle configuration with a
# name that contains the specified string.
# @return [String]
#
# @!attribute [rw] default_code_repository_contains
# A string in the name or URL of a Git repository associated with this
# notebook instance. This filter returns only notebook instances
# associated with a git repository with a name that contains the
# specified string.
# @return [String]
#
# @!attribute [rw] additional_code_repository_equals
# A filter that returns only notebook instances with associated with
# the specified git repository.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstancesInput AWS API Documentation
#
class ListNotebookInstancesInput < Struct.new(
:next_token,
:max_results,
:sort_by,
:sort_order,
:name_contains,
:creation_time_before,
:creation_time_after,
:last_modified_time_before,
:last_modified_time_after,
:status_equals,
:notebook_instance_lifecycle_config_name_contains,
:default_code_repository_contains,
:additional_code_repository_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the response to the previous `ListNotebookInstances` request was
# truncated, SageMaker returns this token. To retrieve the next set of
# notebook instances, use the token in the next request.
# @return [String]
#
# @!attribute [rw] notebook_instances
# An array of `NotebookInstanceSummary` objects, one for each notebook
# instance.
# @return [Array<Types::NotebookInstanceSummary>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListNotebookInstancesOutput AWS API Documentation
#
class ListNotebookInstancesOutput < Struct.new(
:next_token,
:notebook_instances)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListPipelineExecutionSteps` request
# was truncated, the response includes a `NextToken`. To retrieve the
# next set of pipeline execution steps, use the token in the next
# request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of pipeline execution steps to return in the
# response.
# @return [Integer]
#
# @!attribute [rw] sort_order
# The field by which to sort results. The default is `CreatedTime`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelineExecutionStepsRequest AWS API Documentation
#
class ListPipelineExecutionStepsRequest < Struct.new(
:pipeline_execution_arn,
:next_token,
:max_results,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_steps
# A list of `PipeLineExecutionStep` objects. Each
# `PipeLineExecutionStep` consists of StepName, StartTime, EndTime,
# StepStatus, and Metadata. Metadata is an object with properties for
# each job that contains relevant information about the job created by
# the step.
# @return [Array<Types::PipelineExecutionStep>]
#
# @!attribute [rw] next_token
# If the result of the previous `ListPipelineExecutionSteps` request
# was truncated, the response includes a `NextToken`. To retrieve the
# next set of pipeline execution steps, use the token in the next
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelineExecutionStepsResponse AWS API Documentation
#
class ListPipelineExecutionStepsResponse < Struct.new(
:pipeline_execution_steps,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_name
# The name of the pipeline.
# @return [String]
#
# @!attribute [rw] created_after
# A filter that returns the pipeline executions that were created
# after a specified time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns the pipeline executions that were created
# before a specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The field by which to sort results. The default is `CreatedTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListPipelineExecutions` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of pipeline executions, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of pipeline executions to return in the response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelineExecutionsRequest AWS API Documentation
#
class ListPipelineExecutionsRequest < Struct.new(
:pipeline_name,
:created_after,
:created_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_summaries
# Contains a sorted list of pipeline execution summary objects
# matching the specified filters. Each run summary includes the Amazon
# Resource Name (ARN) of the pipeline execution, the run date, and the
# status. This list can be empty.
# @return [Array<Types::PipelineExecutionSummary>]
#
# @!attribute [rw] next_token
# If the result of the previous `ListPipelineExecutions` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of pipeline executions, use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelineExecutionsResponse AWS API Documentation
#
class ListPipelineExecutionsResponse < Struct.new(
:pipeline_execution_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListPipelineParametersForExecution`
# request was truncated, the response includes a `NextToken`. To
# retrieve the next set of parameters, use the token in the next
# request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of parameters to return in the response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelineParametersForExecutionRequest AWS API Documentation
#
class ListPipelineParametersForExecutionRequest < Struct.new(
:pipeline_execution_arn,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_parameters
# Contains a list of pipeline parameters. This list can be empty.
# @return [Array<Types::Parameter>]
#
# @!attribute [rw] next_token
# If the result of the previous `ListPipelineParametersForExecution`
# request was truncated, the response includes a `NextToken`. To
# retrieve the next set of parameters, use the token in the next
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelineParametersForExecutionResponse AWS API Documentation
#
class ListPipelineParametersForExecutionResponse < Struct.new(
:pipeline_parameters,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_name_prefix
# The prefix of the pipeline name.
# @return [String]
#
# @!attribute [rw] created_after
# A filter that returns the pipelines that were created after a
# specified time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns the pipelines that were created before a
# specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The field by which to sort results. The default is `CreatedTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListPipelines` request was truncated,
# the response includes a `NextToken`. To retrieve the next set of
# pipelines, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of pipelines to return in the response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelinesRequest AWS API Documentation
#
class ListPipelinesRequest < Struct.new(
:pipeline_name_prefix,
:created_after,
:created_before,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_summaries
# Contains a sorted list of `PipelineSummary` objects matching the
# specified filters. Each `PipelineSummary` consists of PipelineArn,
# PipelineName, ExperimentName, PipelineDescription, CreationTime,
# LastModifiedTime, LastRunTime, and RoleArn. This list can be empty.
# @return [Array<Types::PipelineSummary>]
#
# @!attribute [rw] next_token
# If the result of the previous `ListPipelines` request was truncated,
# the response includes a `NextToken`. To retrieve the next set of
# pipelines, use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelinesResponse AWS API Documentation
#
class ListPipelinesResponse < Struct.new(
:pipeline_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only processing jobs created after the
# specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only processing jobs created after the
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only processing jobs modified after the
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only processing jobs modified before the
# specified time.
# @return [Time]
#
# @!attribute [rw] name_contains
# A string in the processing job name. This filter returns only
# processing jobs whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] status_equals
# A filter that retrieves only processing jobs with a specific status.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListProcessingJobs` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of processing jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of processing jobs to return in the response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListProcessingJobsRequest AWS API Documentation
#
class ListProcessingJobsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:status_equals,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] processing_job_summaries
# An array of `ProcessingJobSummary` objects, each listing a
# processing job.
# @return [Array<Types::ProcessingJobSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of processing jobs, use it in the
# subsequent request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListProcessingJobsResponse AWS API Documentation
#
class ListProcessingJobsResponse < Struct.new(
:processing_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns the projects that were created after a
# specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns the projects that were created before a
# specified time.
# @return [Time]
#
# @!attribute [rw] max_results
# The maximum number of projects to return in the response.
# @return [Integer]
#
# @!attribute [rw] name_contains
# A filter that returns the projects whose name contains a specified
# string.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListProjects` request was truncated,
# the response includes a `NextToken`. To retrieve the next set of
# projects, use the token in the next request.
# @return [String]
#
# @!attribute [rw] sort_by
# The field by which to sort results. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListProjectsInput AWS API Documentation
#
class ListProjectsInput < Struct.new(
:creation_time_after,
:creation_time_before,
:max_results,
:name_contains,
:next_token,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_summary_list
# A list of summaries of projects.
# @return [Array<Types::ProjectSummary>]
#
# @!attribute [rw] next_token
# If the result of the previous `ListCompilationJobs` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of model compilation jobs, use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListProjectsOutput AWS API Documentation
#
class ListProjectsOutput < Struct.new(
:project_summary_list,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the previous response was truncated, you will receive this token.
# Use it in your next request to receive the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# Returns a list up to a specified limit.
# @return [Integer]
#
# @!attribute [rw] sort_order
# The sort order for the results. The default is `Ascending`.
# @return [String]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results. The default is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] domain_id_equals
# A parameter to search for the Domain ID.
# @return [String]
#
# @!attribute [rw] space_name_contains
# A parameter by which to filter the results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListSpacesRequest AWS API Documentation
#
class ListSpacesRequest < Struct.new(
:next_token,
:max_results,
:sort_order,
:sort_by,
:domain_id_equals,
:space_name_contains)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] spaces
# The list of spaces.
# @return [Array<Types::SpaceDetails>]
#
# @!attribute [rw] next_token
# If the previous response was truncated, you will receive this token.
# Use it in your next request to receive the next set of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListSpacesResponse AWS API Documentation
#
class ListSpacesResponse < Struct.new(
:spaces,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# The response from the last list when returning a list large enough
# to neeed tokening.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of requests to select.
# @return [Integer]
#
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan.
# @return [String]
#
# @!attribute [rw] exclude_devices_deployed_in_other_stage
# Toggle for excluding devices deployed in other stages.
# @return [Boolean]
#
# @!attribute [rw] stage_name
# The name of the stage in the deployment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListStageDevicesRequest AWS API Documentation
#
class ListStageDevicesRequest < Struct.new(
:next_token,
:max_results,
:edge_deployment_plan_name,
:exclude_devices_deployed_in_other_stage,
:stage_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_deployment_summaries
# List of summaries of devices allocated to the stage.
# @return [Array<Types::DeviceDeploymentSummary>]
#
# @!attribute [rw] next_token
# The token to use when calling the next page of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListStageDevicesResponse AWS API Documentation
#
class ListStageDevicesResponse < Struct.new(
:device_deployment_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] max_results
# The maximum number of Studio Lifecycle Configurations to return in
# the response. The default value is 10.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous call to ListStudioLifecycleConfigs didn't return
# the full set of Lifecycle Configurations, the call returns a token
# for getting the next set of Lifecycle Configurations.
# @return [String]
#
# @!attribute [rw] name_contains
# A string in the Lifecycle Configuration name. This filter returns
# only Lifecycle Configurations whose name contains the specified
# string.
# @return [String]
#
# @!attribute [rw] app_type_equals
# A parameter to search for the App Type to which the Lifecycle
# Configuration is attached.
# @return [String]
#
# @!attribute [rw] creation_time_before
# A filter that returns only Lifecycle Configurations created on or
# before the specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_after
# A filter that returns only Lifecycle Configurations created on or
# after the specified time.
# @return [Time]
#
# @!attribute [rw] modified_time_before
# A filter that returns only Lifecycle Configurations modified before
# the specified time.
# @return [Time]
#
# @!attribute [rw] modified_time_after
# A filter that returns only Lifecycle Configurations modified after
# the specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# CreationTime.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is Descending.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListStudioLifecycleConfigsRequest AWS API Documentation
#
class ListStudioLifecycleConfigsRequest < Struct.new(
:max_results,
:next_token,
:name_contains,
:app_type_equals,
:creation_time_before,
:creation_time_after,
:modified_time_before,
:modified_time_after,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# A token for getting the next set of actions, if there are any.
# @return [String]
#
# @!attribute [rw] studio_lifecycle_configs
# A list of Lifecycle Configurations and their properties.
# @return [Array<Types::StudioLifecycleConfigDetails>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListStudioLifecycleConfigsResponse AWS API Documentation
#
class ListStudioLifecycleConfigsResponse < Struct.new(
:next_token,
:studio_lifecycle_configs)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name_contains
# A string in the work team name. This filter returns only work teams
# whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListSubscribedWorkteams` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of labeling jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of work teams to return in each page of the
# response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListSubscribedWorkteamsRequest AWS API Documentation
#
class ListSubscribedWorkteamsRequest < Struct.new(
:name_contains,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] subscribed_workteams
# An array of `Workteam` objects, each describing a work team.
# @return [Array<Types::SubscribedWorkteam>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of work teams, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListSubscribedWorkteamsResponse AWS API Documentation
#
class ListSubscribedWorkteamsResponse < Struct.new(
:subscribed_workteams,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] resource_arn
# The Amazon Resource Name (ARN) of the resource whose tags you want
# to retrieve.
# @return [String]
#
# @!attribute [rw] next_token
# If the response to the previous `ListTags` request is truncated,
# SageMaker returns this token. To retrieve the next set of tags, use
# it in the subsequent request.
# @return [String]
#
# @!attribute [rw] max_results
# Maximum number of tags to return.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTagsInput AWS API Documentation
#
class ListTagsInput < Struct.new(
:resource_arn,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] tags
# An array of `Tag` objects, each with a tag key and a value.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] next_token
# If response is truncated, SageMaker includes a token in the
# response. You can use this token in your subsequent request to fetch
# next set of tokens.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTagsOutput AWS API Documentation
#
class ListTagsOutput < Struct.new(
:tags,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hyper_parameter_tuning_job_name
# The name of the tuning job whose training jobs you want to list.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous
# `ListTrainingJobsForHyperParameterTuningJob` request was truncated,
# the response includes a `NextToken`. To retrieve the next set of
# training jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of training jobs to return. The default value is
# 10.
# @return [Integer]
#
# @!attribute [rw] status_equals
# A filter that returns only training jobs with the specified status.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `Name`.
#
# If the value of this field is `FinalObjectiveMetricValue`, any
# training jobs that did not return an objective metric are not
# listed.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobsForHyperParameterTuningJobRequest AWS API Documentation
#
class ListTrainingJobsForHyperParameterTuningJobRequest < Struct.new(
:hyper_parameter_tuning_job_name,
:next_token,
:max_results,
:status_equals,
:sort_by,
:sort_order)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_summaries
# A list of [TrainingJobSummary][1] objects that describe the training
# jobs that the `ListTrainingJobsForHyperParameterTuningJob` request
# returned.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobSummary.html
# @return [Array<Types::HyperParameterTrainingJobSummary>]
#
# @!attribute [rw] next_token
# If the result of this `ListTrainingJobsForHyperParameterTuningJob`
# request was truncated, the response includes a `NextToken`. To
# retrieve the next set of training jobs, use the token in the next
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobsForHyperParameterTuningJobResponse AWS API Documentation
#
class ListTrainingJobsForHyperParameterTuningJobResponse < Struct.new(
:training_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the result of the previous `ListTrainingJobs` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of training jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of training jobs to return in the response.
# @return [Integer]
#
# @!attribute [rw] creation_time_after
# A filter that returns only training jobs created after the specified
# time (timestamp).
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only training jobs created before the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only training jobs modified after the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only training jobs modified before the
# specified time (timestamp).
# @return [Time]
#
# @!attribute [rw] name_contains
# A string in the training job name. This filter returns only training
# jobs whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] status_equals
# A filter that retrieves only training jobs with a specific status.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @!attribute [rw] warm_pool_status_equals
# A filter that retrieves only training jobs with a specific warm pool
# status.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobsRequest AWS API Documentation
#
class ListTrainingJobsRequest < Struct.new(
:next_token,
:max_results,
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:status_equals,
:sort_by,
:sort_order,
:warm_pool_status_equals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_summaries
# An array of `TrainingJobSummary` objects, each listing a training
# job.
# @return [Array<Types::TrainingJobSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, SageMaker returns this token. To
# retrieve the next set of training jobs, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobsResponse AWS API Documentation
#
class ListTrainingJobsResponse < Struct.new(
:training_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] creation_time_after
# A filter that returns only transform jobs created after the
# specified time.
# @return [Time]
#
# @!attribute [rw] creation_time_before
# A filter that returns only transform jobs created before the
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_after
# A filter that returns only transform jobs modified after the
# specified time.
# @return [Time]
#
# @!attribute [rw] last_modified_time_before
# A filter that returns only transform jobs modified before the
# specified time.
# @return [Time]
#
# @!attribute [rw] name_contains
# A string in the transform job name. This filter returns only
# transform jobs whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] status_equals
# A filter that retrieves only transform jobs with a specific status.
# @return [String]
#
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListTransformJobs` request was
# truncated, the response includes a `NextToken`. To retrieve the next
# set of transform jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of transform jobs to return in the response. The
# default value is `10`.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTransformJobsRequest AWS API Documentation
#
class ListTransformJobsRequest < Struct.new(
:creation_time_after,
:creation_time_before,
:last_modified_time_after,
:last_modified_time_before,
:name_contains,
:status_equals,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] transform_job_summaries
# An array of `TransformJobSummary` objects.
# @return [Array<Types::TransformJobSummary>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of transform jobs, use it in the next
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTransformJobsResponse AWS API Documentation
#
class ListTransformJobsResponse < Struct.new(
:transform_job_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_name
# A filter that returns only components that are part of the specified
# experiment. If you specify `ExperimentName`, you can't filter by
# `SourceArn` or `TrialName`.
# @return [String]
#
# @!attribute [rw] trial_name
# A filter that returns only components that are part of the specified
# trial. If you specify `TrialName`, you can't filter by
# `ExperimentName` or `SourceArn`.
# @return [String]
#
# @!attribute [rw] source_arn
# A filter that returns only components that have the specified source
# Amazon Resource Name (ARN). If you specify `SourceArn`, you can't
# filter by `ExperimentName` or `TrialName`.
# @return [String]
#
# @!attribute [rw] created_after
# A filter that returns only components created after the specified
# time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns only components created before the specified
# time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `Descending`.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of components to return in the response. The
# default value is 10.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous call to `ListTrialComponents` didn't return the
# full set of components, the call returns a token for getting the
# next set of components.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrialComponentsRequest AWS API Documentation
#
class ListTrialComponentsRequest < Struct.new(
:experiment_name,
:trial_name,
:source_arn,
:created_after,
:created_before,
:sort_by,
:sort_order,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_summaries
# A list of the summaries of your trial components.
# @return [Array<Types::TrialComponentSummary>]
#
# @!attribute [rw] next_token
# A token for getting the next set of components, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrialComponentsResponse AWS API Documentation
#
class ListTrialComponentsResponse < Struct.new(
:trial_component_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_name
# A filter that returns only trials that are part of the specified
# experiment.
# @return [String]
#
# @!attribute [rw] trial_component_name
# A filter that returns only trials that are associated with the
# specified trial component.
# @return [String]
#
# @!attribute [rw] created_after
# A filter that returns only trials created after the specified time.
# @return [Time]
#
# @!attribute [rw] created_before
# A filter that returns only trials created before the specified time.
# @return [Time]
#
# @!attribute [rw] sort_by
# The property used to sort results. The default value is
# `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order. The default value is `Descending`.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of trials to return in the response. The default
# value is 10.
# @return [Integer]
#
# @!attribute [rw] next_token
# If the previous call to `ListTrials` didn't return the full set of
# trials, the call returns a token for getting the next set of trials.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrialsRequest AWS API Documentation
#
class ListTrialsRequest < Struct.new(
:experiment_name,
:trial_component_name,
:created_after,
:created_before,
:sort_by,
:sort_order,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_summaries
# A list of the summaries of your trials.
# @return [Array<Types::TrialSummary>]
#
# @!attribute [rw] next_token
# A token for getting the next set of trials, if there are any.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrialsResponse AWS API Documentation
#
class ListTrialsResponse < Struct.new(
:trial_summaries,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] next_token
# If the previous response was truncated, you will receive this token.
# Use it in your next request to receive the next set of results.
# @return [String]
#
# @!attribute [rw] max_results
# Returns a list up to a specified limit.
# @return [Integer]
#
# @!attribute [rw] sort_order
# The sort order for the results. The default is Ascending.
# @return [String]
#
# @!attribute [rw] sort_by
# The parameter by which to sort the results. The default is
# CreationTime.
# @return [String]
#
# @!attribute [rw] domain_id_equals
# A parameter by which to filter the results.
# @return [String]
#
# @!attribute [rw] user_profile_name_contains
# A parameter by which to filter the results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListUserProfilesRequest AWS API Documentation
#
class ListUserProfilesRequest < Struct.new(
:next_token,
:max_results,
:sort_order,
:sort_by,
:domain_id_equals,
:user_profile_name_contains)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] user_profiles
# The list of user profiles.
# @return [Array<Types::UserProfileDetails>]
#
# @!attribute [rw] next_token
# If the previous response was truncated, you will receive this token.
# Use it in your next request to receive the next set of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListUserProfilesResponse AWS API Documentation
#
class ListUserProfilesResponse < Struct.new(
:user_profiles,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] sort_by
# Sort workforces using the workforce name or creation date.
# @return [String]
#
# @!attribute [rw] sort_order
# Sort workforces in ascending or descending order.
# @return [String]
#
# @!attribute [rw] name_contains
# A filter you can use to search for workforces using part of the
# workforce name.
# @return [String]
#
# @!attribute [rw] next_token
# A token to resume pagination.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of workforces returned in the response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkforcesRequest AWS API Documentation
#
class ListWorkforcesRequest < Struct.new(
:sort_by,
:sort_order,
:name_contains,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workforces
# A list containing information about your workforce.
# @return [Array<Types::Workforce>]
#
# @!attribute [rw] next_token
# A token to resume pagination.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkforcesResponse AWS API Documentation
#
class ListWorkforcesResponse < Struct.new(
:workforces,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] sort_by
# The field to sort results by. The default is `CreationTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# The sort order for results. The default is `Ascending`.
# @return [String]
#
# @!attribute [rw] name_contains
# A string in the work team's name. This filter returns only work
# teams whose name contains the specified string.
# @return [String]
#
# @!attribute [rw] next_token
# If the result of the previous `ListWorkteams` request was truncated,
# the response includes a `NextToken`. To retrieve the next set of
# labeling jobs, use the token in the next request.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of work teams to return in each page of the
# response.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkteamsRequest AWS API Documentation
#
class ListWorkteamsRequest < Struct.new(
:sort_by,
:sort_order,
:name_contains,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteams
# An array of `Workteam` objects, each describing a work team.
# @return [Array<Types::Workteam>]
#
# @!attribute [rw] next_token
# If the response is truncated, Amazon SageMaker returns this token.
# To retrieve the next set of work teams, use it in the subsequent
# request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListWorkteamsResponse AWS API Documentation
#
class ListWorkteamsResponse < Struct.new(
:workteams,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# Defines an Amazon Cognito or your own OIDC IdP user group that is part
# of a work team.
#
# @!attribute [rw] cognito_member_definition
# The Amazon Cognito user group that is part of the work team.
# @return [Types::CognitoMemberDefinition]
#
# @!attribute [rw] oidc_member_definition
# A list 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.
# @return [Types::OidcMemberDefinition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MemberDefinition AWS API Documentation
#
class MemberDefinition < Struct.new(
:cognito_member_definition,
:oidc_member_definition)
SENSITIVE = []
include Aws::Structure
end
# Metadata properties of the tracking entity, trial, or trial component.
#
# @!attribute [rw] commit_id
# The commit ID.
# @return [String]
#
# @!attribute [rw] repository
# The repository.
# @return [String]
#
# @!attribute [rw] generated_by
# The entity this entity was generated by.
# @return [String]
#
# @!attribute [rw] project_id
# The project ID.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MetadataProperties AWS API Documentation
#
class MetadataProperties < Struct.new(
:commit_id,
:repository,
:generated_by,
:project_id)
SENSITIVE = []
include Aws::Structure
end
# The name, value, and date and time of a metric that was emitted to
# Amazon CloudWatch.
#
# @!attribute [rw] metric_name
# The name of the metric.
# @return [String]
#
# @!attribute [rw] value
# The value of the metric.
# @return [Float]
#
# @!attribute [rw] timestamp
# The date and time that the algorithm emitted the metric.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MetricData AWS API Documentation
#
class MetricData < Struct.new(
:metric_name,
:value,
:timestamp)
SENSITIVE = []
include Aws::Structure
end
# Information about the metric for a candidate produced by an AutoML
# job.
#
# @!attribute [rw] metric_name
# The name of the metric.
# @return [String]
#
# @!attribute [rw] value
# The value of the metric.
# @return [Float]
#
# @!attribute [rw] set
# The dataset split from which the AutoML job produced the metric.
# @return [String]
#
# @!attribute [rw] standard_metric_name
# The name of the standard metric.
#
# <note markdown="1"> For definitions of the standard metrics, see [ `Autopilot candidate
# metrics` ][1].
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-model-support-validation.html#autopilot-metrics
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MetricDatum AWS API Documentation
#
class MetricDatum < Struct.new(
:metric_name,
:value,
:set,
:standard_metric_name)
SENSITIVE = []
include Aws::Structure
end
# Specifies a metric that the training algorithm writes to `stderr` or
# `stdout`. You can view these logs to understand how your training job
# performs and check for any errors encountered during training.
# SageMaker hyperparameter tuning captures all defined metrics. Specify
# one of the defined metrics to use as an objective metric using the
# [TuningObjective][1] parameter in the
# `HyperParameterTrainingJobDefinition` API to evaluate job performance
# during hyperparameter tuning.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html#sagemaker-Type-HyperParameterTrainingJobDefinition-TuningObjective
#
# @!attribute [rw] name
# The name of the metric.
# @return [String]
#
# @!attribute [rw] regex
# A regular expression that searches the output of a training job and
# gets the value of the metric. For more information about using
# regular expressions to define metrics, see [Defining metrics and
# environment variables][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics-variables.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MetricDefinition AWS API Documentation
#
class MetricDefinition < Struct.new(
:name,
:regex)
SENSITIVE = []
include Aws::Structure
end
# Details about the metrics source.
#
# @!attribute [rw] content_type
# The metric source content type.
# @return [String]
#
# @!attribute [rw] content_digest
# The hash key used for the metrics source.
# @return [String]
#
# @!attribute [rw] s3_uri
# The S3 URI for the metrics source.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MetricsSource AWS API Documentation
#
class MetricsSource < Struct.new(
:content_type,
:content_digest,
:s3_uri)
SENSITIVE = []
include Aws::Structure
end
# The properties of a model as returned by the [Search][1] API.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
#
# @!attribute [rw] model_name
# The name of the model.
# @return [String]
#
# @!attribute [rw] primary_container
# Describes the container, as part of model definition.
# @return [Types::ContainerDefinition]
#
# @!attribute [rw] containers
# The containers in the inference pipeline.
# @return [Array<Types::ContainerDefinition>]
#
# @!attribute [rw] inference_execution_config
# Specifies details about how containers in a multi-container endpoint
# are run.
# @return [Types::InferenceExecutionConfig]
#
# @!attribute [rw] execution_role_arn
# The Amazon Resource Name (ARN) of the IAM role that you specified
# for the model.
# @return [String]
#
# @!attribute [rw] vpc_config
# 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][1] and
# [Protect Training Jobs by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
# @return [Types::VpcConfig]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when the model was created.
# @return [Time]
#
# @!attribute [rw] model_arn
# The Amazon Resource Name (ARN) of the model.
# @return [String]
#
# @!attribute [rw] enable_network_isolation
# Isolates the model container. No inbound or outbound network calls
# can be made to or from the model container.
# @return [Boolean]
#
# @!attribute [rw] tags
# A list of key-value pairs associated with the model. For more
# information, see [Tagging Amazon Web Services resources][1] in the
# *Amazon Web Services General Reference Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Model AWS API Documentation
#
class Model < Struct.new(
:model_name,
:primary_container,
:containers,
:inference_execution_config,
:execution_role_arn,
:vpc_config,
:creation_time,
:model_arn,
:enable_network_isolation,
:tags)
SENSITIVE = []
include Aws::Structure
end
# 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 definition that
# describes how to compute inferences, and other metadata.
#
# @!attribute [rw] s3_model_artifacts
# The path of the S3 object that contains the model artifacts. For
# example, `s3://bucket-name/keynameprefix/model.tar.gz`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelArtifacts AWS API Documentation
#
class ModelArtifacts < Struct.new(
:s3_model_artifacts)
SENSITIVE = []
include Aws::Structure
end
# Docker container image configuration object for the model bias job.
#
# @!attribute [rw] image_uri
# The container image to be run by the model bias job.
# @return [String]
#
# @!attribute [rw] config_uri
# JSON formatted S3 file that defines bias parameters. For more
# information on this JSON configuration file, see [Configure bias
# parameters][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-config-json-monitor-bias-parameters.html
# @return [String]
#
# @!attribute [rw] environment
# Sets the environment variables in the Docker container.
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelBiasAppSpecification AWS API Documentation
#
class ModelBiasAppSpecification < Struct.new(
:image_uri,
:config_uri,
:environment)
SENSITIVE = []
include Aws::Structure
end
# The configuration for a baseline model bias job.
#
# @!attribute [rw] baselining_job_name
# The name of the baseline model bias job.
# @return [String]
#
# @!attribute [rw] constraints_resource
# The constraints resource for a monitoring job.
# @return [Types::MonitoringConstraintsResource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelBiasBaselineConfig AWS API Documentation
#
class ModelBiasBaselineConfig < Struct.new(
:baselining_job_name,
:constraints_resource)
SENSITIVE = []
include Aws::Structure
end
# Inputs for the model bias job.
#
# @!attribute [rw] endpoint_input
# Input object for the endpoint
# @return [Types::EndpointInput]
#
# @!attribute [rw] batch_transform_input
# Input object for the batch transform job.
# @return [Types::BatchTransformInput]
#
# @!attribute [rw] ground_truth_s3_input
# Location of ground truth labels to use in model bias job.
# @return [Types::MonitoringGroundTruthS3Input]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelBiasJobInput AWS API Documentation
#
class ModelBiasJobInput < Struct.new(
:endpoint_input,
:batch_transform_input,
:ground_truth_s3_input)
SENSITIVE = []
include Aws::Structure
end
# An Amazon SageMaker Model Card.
#
# @!attribute [rw] model_card_arn
# The Amazon Resource Name (ARN) of the model card.
# @return [String]
#
# @!attribute [rw] model_card_name
# The unique name of the model card.
# @return [String]
#
# @!attribute [rw] model_card_version
# The version of the model card.
# @return [Integer]
#
# @!attribute [rw] content
# The content of the model card. Content uses the [model card JSON
# schema][1] and provided as a string.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards.html#model-cards-json-schema
# @return [String]
#
# @!attribute [rw] model_card_status
# The approval status of the model card within your organization.
# Different organizations might have different criteria for model card
# review and approval.
#
# * `Draft`: The model card is a work in progress.
#
# * `PendingReview`: The model card is pending review.
#
# * `Approved`: The model card is approved.
#
# * `Archived`: The model card is archived. No more updates should be
# made to the model card, but it can still be exported.
# @return [String]
#
# @!attribute [rw] security_config
# The security configuration used to protect model card data.
# @return [Types::ModelCardSecurityConfig]
#
# @!attribute [rw] creation_time
# The date and time that the model card was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# The date and time that the model card was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] tags
# Key-value pairs used to manage metadata for the model card.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] model_id
# The unique name (ID) of the model.
# @return [String]
#
# @!attribute [rw] risk_rating
# The risk rating of the model. Different organizations might have
# different criteria for model card risk ratings. For more
# information, see [Risk ratings][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards-risk-rating.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelCard AWS API Documentation
#
class ModelCard < Struct.new(
:model_card_arn,
:model_card_name,
:model_card_version,
:content,
:model_card_status,
:security_config,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:tags,
:model_id,
:risk_rating)
SENSITIVE = [:content]
include Aws::Structure
end
# The artifacts of the model card export job.
#
# @!attribute [rw] s3_export_artifacts
# The Amazon S3 URI of the exported model artifacts.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelCardExportArtifacts AWS API Documentation
#
class ModelCardExportArtifacts < Struct.new(
:s3_export_artifacts)
SENSITIVE = []
include Aws::Structure
end
# The summary of the Amazon SageMaker Model Card export job.
#
# @!attribute [rw] model_card_export_job_name
# The name of the model card export job.
# @return [String]
#
# @!attribute [rw] model_card_export_job_arn
# The Amazon Resource Name (ARN) of the model card export job.
# @return [String]
#
# @!attribute [rw] status
# The completion status of the model card export job.
# @return [String]
#
# @!attribute [rw] model_card_name
# The name of the model card that the export job exports.
# @return [String]
#
# @!attribute [rw] model_card_version
# The version of the model card that the export job exports.
# @return [Integer]
#
# @!attribute [rw] created_at
# The date and time that the model card export job was created.
# @return [Time]
#
# @!attribute [rw] last_modified_at
# The date and time that the model card export job was last modified..
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelCardExportJobSummary AWS API Documentation
#
class ModelCardExportJobSummary < Struct.new(
:model_card_export_job_name,
:model_card_export_job_arn,
:status,
:model_card_name,
:model_card_version,
:created_at,
:last_modified_at)
SENSITIVE = []
include Aws::Structure
end
# Configure the export output details for an Amazon SageMaker Model
# Card.
#
# @!attribute [rw] s3_output_path
# The Amazon S3 output path to export your model card PDF.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelCardExportOutputConfig AWS API Documentation
#
class ModelCardExportOutputConfig < Struct.new(
:s3_output_path)
SENSITIVE = []
include Aws::Structure
end
# Configure the security settings to protect model card data.
#
# @!attribute [rw] kms_key_id
# A Key Management Service [key ID][1] to use for encrypting a model
# card.
#
#
#
# [1]: https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-id
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelCardSecurityConfig AWS API Documentation
#
class ModelCardSecurityConfig < Struct.new(
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# A summary of the model card.
#
# @!attribute [rw] model_card_name
# The name of the model card.
# @return [String]
#
# @!attribute [rw] model_card_arn
# The Amazon Resource Name (ARN) of the model card.
# @return [String]
#
# @!attribute [rw] model_card_status
# The approval status of the model card within your organization.
# Different organizations might have different criteria for model card
# review and approval.
#
# * `Draft`: The model card is a work in progress.
#
# * `PendingReview`: The model card is pending review.
#
# * `Approved`: The model card is approved.
#
# * `Archived`: The model card is archived. No more updates should be
# made to the model card, but it can still be exported.
# @return [String]
#
# @!attribute [rw] creation_time
# The date and time that the model card was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The date and time that the model card was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelCardSummary AWS API Documentation
#
class ModelCardSummary < Struct.new(
:model_card_name,
:model_card_arn,
:model_card_status,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# A summary of a specific version of the model card.
#
# @!attribute [rw] model_card_name
# The name of the model card.
# @return [String]
#
# @!attribute [rw] model_card_arn
# The Amazon Resource Name (ARN) of the model card.
# @return [String]
#
# @!attribute [rw] model_card_status
# The approval status of the model card version within your
# organization. Different organizations might have different criteria
# for model card review and approval.
#
# * `Draft`: The model card is a work in progress.
#
# * `PendingReview`: The model card is pending review.
#
# * `Approved`: The model card is approved.
#
# * `Archived`: The model card is archived. No more updates should be
# made to the model card, but it can still be exported.
# @return [String]
#
# @!attribute [rw] model_card_version
# A version of the model card.
# @return [Integer]
#
# @!attribute [rw] creation_time
# The date and time that the model card version was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time date and time that the model card version was last
# modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelCardVersionSummary AWS API Documentation
#
class ModelCardVersionSummary < Struct.new(
:model_card_name,
:model_card_arn,
:model_card_status,
:model_card_version,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# Configures the timeout and maximum number of retries for processing a
# transform job invocation.
#
# @!attribute [rw] invocations_timeout_in_seconds
# The timeout value in seconds for an invocation request. The default
# value is 600.
# @return [Integer]
#
# @!attribute [rw] invocations_max_retries
# The maximum number of retries when invocation requests are failing.
# The default value is 3.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelClientConfig AWS API Documentation
#
class ModelClientConfig < Struct.new(
:invocations_timeout_in_seconds,
:invocations_max_retries)
SENSITIVE = []
include Aws::Structure
end
# Defines the model configuration. Includes the specification name and
# environment parameters.
#
# @!attribute [rw] inference_specification_name
# The inference specification name in the model package version.
# @return [String]
#
# @!attribute [rw] environment_parameters
# Defines the environment parameters that includes key, value types,
# and values.
# @return [Array<Types::EnvironmentParameter>]
#
# @!attribute [rw] compilation_job_name
# The name of the compilation job used to create the recommended model
# artifacts.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelConfiguration AWS API Documentation
#
class ModelConfiguration < Struct.new(
:inference_specification_name,
:environment_parameters,
:compilation_job_name)
SENSITIVE = []
include Aws::Structure
end
# An endpoint that hosts a model displayed in the Amazon SageMaker Model
# Dashboard.
#
# @!attribute [rw] endpoint_name
# The endpoint name.
# @return [String]
#
# @!attribute [rw] endpoint_arn
# The Amazon Resource Name (ARN) of the endpoint.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when the endpoint was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last time the endpoint was modified.
# @return [Time]
#
# @!attribute [rw] endpoint_status
# The endpoint status.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDashboardEndpoint AWS API Documentation
#
class ModelDashboardEndpoint < Struct.new(
:endpoint_name,
:endpoint_arn,
:creation_time,
:last_modified_time,
:endpoint_status)
SENSITIVE = []
include Aws::Structure
end
# An alert action taken to light up an icon on the Amazon SageMaker
# Model Dashboard when an alert goes into `InAlert` status.
#
# @!attribute [rw] enabled
# Indicates whether the alert action is turned on.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDashboardIndicatorAction AWS API Documentation
#
class ModelDashboardIndicatorAction < Struct.new(
:enabled)
SENSITIVE = []
include Aws::Structure
end
# A model displayed in the Amazon SageMaker Model Dashboard.
#
# @!attribute [rw] model
# A model displayed in the Model Dashboard.
# @return [Types::Model]
#
# @!attribute [rw] endpoints
# The endpoints that host a model.
# @return [Array<Types::ModelDashboardEndpoint>]
#
# @!attribute [rw] last_batch_transform_job
# A batch transform job. For information about SageMaker batch
# transform, see [Use Batch Transform][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html
# @return [Types::TransformJob]
#
# @!attribute [rw] monitoring_schedules
# The monitoring schedules for a model.
# @return [Array<Types::ModelDashboardMonitoringSchedule>]
#
# @!attribute [rw] model_card
# The model card for a model.
# @return [Types::ModelDashboardModelCard]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDashboardModel AWS API Documentation
#
class ModelDashboardModel < Struct.new(
:model,
:endpoints,
:last_batch_transform_job,
:monitoring_schedules,
:model_card)
SENSITIVE = []
include Aws::Structure
end
# The model card for a model displayed in the Amazon SageMaker Model
# Dashboard.
#
# @!attribute [rw] model_card_arn
# The Amazon Resource Name (ARN) for a model card.
# @return [String]
#
# @!attribute [rw] model_card_name
# The name of a model card.
# @return [String]
#
# @!attribute [rw] model_card_version
# The model card version.
# @return [Integer]
#
# @!attribute [rw] model_card_status
# The model card status.
# @return [String]
#
# @!attribute [rw] security_config
# The KMS Key ID (`KMSKeyId`) for encryption of model card
# information.
# @return [Types::ModelCardSecurityConfig]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when the model card was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# A timestamp that indicates when the model card was last updated.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] tags
# The tags associated with a model card.
# @return [Array<Types::Tag>]
#
# @!attribute [rw] model_id
# For models created in SageMaker, this is the model ARN. For models
# created outside of SageMaker, this is a user-customized string.
# @return [String]
#
# @!attribute [rw] risk_rating
# A model card's risk rating. Can be low, medium, or high.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDashboardModelCard AWS API Documentation
#
class ModelDashboardModelCard < Struct.new(
:model_card_arn,
:model_card_name,
:model_card_version,
:model_card_status,
:security_config,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:tags,
:model_id,
:risk_rating)
SENSITIVE = []
include Aws::Structure
end
# A monitoring schedule for a model displayed in the Amazon SageMaker
# Model Dashboard.
#
# @!attribute [rw] monitoring_schedule_arn
# The Amazon Resource Name (ARN) of a monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_name
# The name of a monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_status
# The status of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_type
# The monitor type of a model monitor.
# @return [String]
#
# @!attribute [rw] failure_reason
# If a monitoring job failed, provides the reason.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when the monitoring schedule was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that indicates when the monitoring schedule was last
# updated.
# @return [Time]
#
# @!attribute [rw] monitoring_schedule_config
# Configures the monitoring schedule and defines the monitoring job.
# @return [Types::MonitoringScheduleConfig]
#
# @!attribute [rw] endpoint_name
# The endpoint which is monitored.
# @return [String]
#
# @!attribute [rw] monitoring_alert_summaries
# A JSON array where each element is a summary for a monitoring alert.
# @return [Array<Types::MonitoringAlertSummary>]
#
# @!attribute [rw] last_monitoring_execution_summary
# Summary of information about the last monitoring job to run.
# @return [Types::MonitoringExecutionSummary]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDashboardMonitoringSchedule AWS API Documentation
#
class ModelDashboardMonitoringSchedule < Struct.new(
:monitoring_schedule_arn,
:monitoring_schedule_name,
:monitoring_schedule_status,
:monitoring_type,
:failure_reason,
:creation_time,
:last_modified_time,
:monitoring_schedule_config,
:endpoint_name,
:monitoring_alert_summaries,
:last_monitoring_execution_summary)
SENSITIVE = []
include Aws::Structure
end
# Data quality constraints and statistics for a model.
#
# @!attribute [rw] statistics
# Data quality statistics for a model.
# @return [Types::MetricsSource]
#
# @!attribute [rw] constraints
# Data quality constraints for a model.
# @return [Types::MetricsSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDataQuality AWS API Documentation
#
class ModelDataQuality < Struct.new(
:statistics,
:constraints)
SENSITIVE = []
include Aws::Structure
end
# Specifies how to generate the endpoint name for an automatic one-click
# Autopilot model deployment.
#
# @!attribute [rw] auto_generate_endpoint_name
# Set to `True` to automatically generate an endpoint name for a
# one-click Autopilot model deployment; set to `False` otherwise. The
# default value is `False`.
#
# <note markdown="1"> If you set `AutoGenerateEndpointName` to `True`, do not specify the
# `EndpointName`; otherwise a 400 error is thrown.
#
# </note>
# @return [Boolean]
#
# @!attribute [rw] endpoint_name
# Specifies the endpoint name to use for a one-click Autopilot model
# deployment if the endpoint name is not generated automatically.
#
# <note markdown="1"> Specify the `EndpointName` if and only if you set
# `AutoGenerateEndpointName` to `False`; otherwise a 400 error is
# thrown.
#
# </note>
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDeployConfig AWS API Documentation
#
class ModelDeployConfig < Struct.new(
:auto_generate_endpoint_name,
:endpoint_name)
SENSITIVE = []
include Aws::Structure
end
# Provides information about the endpoint of the model deployment.
#
# @!attribute [rw] endpoint_name
# The name of the endpoint to which the model has been deployed.
#
# <note markdown="1"> If model deployment fails, this field is omitted from the response.
#
# </note>
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDeployResult AWS API Documentation
#
class ModelDeployResult < Struct.new(
:endpoint_name)
SENSITIVE = []
include Aws::Structure
end
# Provides information to verify the integrity of stored model
# artifacts.
#
# @!attribute [rw] artifact_digest
# Provides a hash value that uniquely identifies the stored model
# artifacts.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDigests AWS API Documentation
#
class ModelDigests < Struct.new(
:artifact_digest)
SENSITIVE = []
include Aws::Structure
end
# Docker container image configuration object for the model
# explainability job.
#
# @!attribute [rw] image_uri
# The container image to be run by the model explainability job.
# @return [String]
#
# @!attribute [rw] config_uri
# JSON formatted S3 file that defines explainability parameters. For
# more information on this JSON configuration file, see [Configure
# model explainability parameters][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-config-json-monitor-model-explainability-parameters.html
# @return [String]
#
# @!attribute [rw] environment
# Sets the environment variables in the Docker container.
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelExplainabilityAppSpecification AWS API Documentation
#
class ModelExplainabilityAppSpecification < Struct.new(
:image_uri,
:config_uri,
:environment)
SENSITIVE = []
include Aws::Structure
end
# The configuration for a baseline model explainability job.
#
# @!attribute [rw] baselining_job_name
# The name of the baseline model explainability job.
# @return [String]
#
# @!attribute [rw] constraints_resource
# The constraints resource for a monitoring job.
# @return [Types::MonitoringConstraintsResource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelExplainabilityBaselineConfig AWS API Documentation
#
class ModelExplainabilityBaselineConfig < Struct.new(
:baselining_job_name,
:constraints_resource)
SENSITIVE = []
include Aws::Structure
end
# Inputs for the model explainability job.
#
# @!attribute [rw] endpoint_input
# Input object for the endpoint
# @return [Types::EndpointInput]
#
# @!attribute [rw] batch_transform_input
# Input object for the batch transform job.
# @return [Types::BatchTransformInput]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelExplainabilityJobInput AWS API Documentation
#
class ModelExplainabilityJobInput < Struct.new(
:endpoint_input,
:batch_transform_input)
SENSITIVE = []
include Aws::Structure
end
# The configuration for the infrastructure that the model will be
# deployed to.
#
# @!attribute [rw] infrastructure_type
# The inference option to which to deploy your model. Possible values
# are the following:
#
# * `RealTime`: Deploy to real-time inference.
#
# ^
# @return [String]
#
# @!attribute [rw] real_time_inference_config
# The infrastructure configuration for deploying the model to
# real-time inference.
# @return [Types::RealTimeInferenceConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelInfrastructureConfig AWS API Documentation
#
class ModelInfrastructureConfig < Struct.new(
:infrastructure_type,
:real_time_inference_config)
SENSITIVE = []
include Aws::Structure
end
# Input object for the model.
#
# @!attribute [rw] data_input_config
# The input configuration object for the model.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelInput AWS API Documentation
#
class ModelInput < Struct.new(
:data_input_config)
SENSITIVE = []
include Aws::Structure
end
# The model latency threshold.
#
# @!attribute [rw] percentile
# The model latency percentile threshold.
# @return [String]
#
# @!attribute [rw] value_in_milliseconds
# The model latency percentile value in milliseconds.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelLatencyThreshold AWS API Documentation
#
class ModelLatencyThreshold < Struct.new(
:percentile,
:value_in_milliseconds)
SENSITIVE = []
include Aws::Structure
end
# Part of the search expression. You can specify the name and value
# (domain, task, framework, framework version, task, and model).
#
# @!attribute [rw] name
# The name of the of the model to filter by.
# @return [String]
#
# @!attribute [rw] value
# The value to filter the model metadata.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelMetadataFilter AWS API Documentation
#
class ModelMetadataFilter < Struct.new(
:name,
:value)
SENSITIVE = []
include Aws::Structure
end
# One or more filters 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
#
# @!attribute [rw] filters
# A list of filter objects.
# @return [Array<Types::ModelMetadataFilter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelMetadataSearchExpression AWS API Documentation
#
class ModelMetadataSearchExpression < Struct.new(
:filters)
SENSITIVE = []
include Aws::Structure
end
# A summary of the model metadata.
#
# @!attribute [rw] domain
# The machine learning domain of the model.
# @return [String]
#
# @!attribute [rw] framework
# The machine learning framework of the model.
# @return [String]
#
# @!attribute [rw] task
# The machine learning task of the model.
# @return [String]
#
# @!attribute [rw] model
# The name of the model.
# @return [String]
#
# @!attribute [rw] framework_version
# The framework version of the model.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelMetadataSummary AWS API Documentation
#
class ModelMetadataSummary < Struct.new(
:domain,
:framework,
:task,
:model,
:framework_version)
SENSITIVE = []
include Aws::Structure
end
# Contains metrics captured from a model.
#
# @!attribute [rw] model_quality
# Metrics that measure the quality of a model.
# @return [Types::ModelQuality]
#
# @!attribute [rw] model_data_quality
# Metrics that measure the quality of the input data for a model.
# @return [Types::ModelDataQuality]
#
# @!attribute [rw] bias
# Metrics that measure bais in a model.
# @return [Types::Bias]
#
# @!attribute [rw] explainability
# Metrics that help explain a model.
# @return [Types::Explainability]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelMetrics AWS API Documentation
#
class ModelMetrics < Struct.new(
:model_quality,
:model_data_quality,
:bias,
:explainability)
SENSITIVE = []
include Aws::Structure
end
# A versioned model that can be deployed for SageMaker inference.
#
# @!attribute [rw] model_package_name
# The name of the model.
# @return [String]
#
# @!attribute [rw] model_package_group_name
# The model group to which the model belongs.
# @return [String]
#
# @!attribute [rw] model_package_version
# The version number of a versioned model.
# @return [Integer]
#
# @!attribute [rw] model_package_arn
# The Amazon Resource Name (ARN) of the model package.
# @return [String]
#
# @!attribute [rw] model_package_description
# The description of the model package.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the model package was created.
# @return [Time]
#
# @!attribute [rw] inference_specification
# Defines how to perform inference generation after a training job is
# run.
# @return [Types::InferenceSpecification]
#
# @!attribute [rw] source_algorithm_specification
# A list of algorithms that were used to create a model package.
# @return [Types::SourceAlgorithmSpecification]
#
# @!attribute [rw] validation_specification
# Specifies batch transform jobs that SageMaker runs to validate your
# model package.
# @return [Types::ModelPackageValidationSpecification]
#
# @!attribute [rw] model_package_status
# The status of the model package. This can be one of the following
# values.
#
# * `PENDING` - The model package is pending being created.
#
# * `IN_PROGRESS` - The model package is in the process of being
# created.
#
# * `COMPLETED` - The model package was successfully created.
#
# * `FAILED` - The model package failed.
#
# * `DELETING` - The model package is in the process of being deleted.
# @return [String]
#
# @!attribute [rw] model_package_status_details
# Specifies the validation and image scan statuses of the model
# package.
# @return [Types::ModelPackageStatusDetails]
#
# @!attribute [rw] certify_for_marketplace
# Whether the model package is to be certified to be listed on Amazon
# Web Services Marketplace. For information about listing model
# packages on Amazon Web Services Marketplace, see [List Your
# Algorithm or Model Package on Amazon Web Services Marketplace][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-mkt-list.html
# @return [Boolean]
#
# @!attribute [rw] model_approval_status
# The approval status of the model. This can be one of the following
# values.
#
# * `APPROVED` - The model is approved
#
# * `REJECTED` - The model is rejected.
#
# * `PENDING_MANUAL_APPROVAL` - The model is waiting for manual
# approval.
# @return [String]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, or project.
# @return [Types::UserContext]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] model_metrics
# Metrics for the model.
# @return [Types::ModelMetrics]
#
# @!attribute [rw] last_modified_time
# The last time the model package was modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, or project.
# @return [Types::UserContext]
#
# @!attribute [rw] approval_description
# A description provided when the model approval is set.
# @return [String]
#
# @!attribute [rw] domain
# The machine learning domain of your model package and its
# components. Common machine learning domains include computer vision
# and natural language processing.
# @return [String]
#
# @!attribute [rw] task
# The machine learning task your model package accomplishes. Common
# machine learning tasks include object detection and image
# classification.
# @return [String]
#
# @!attribute [rw] sample_payload_url
# The Amazon Simple Storage Service path where the sample payload are
# stored. This path must point to a single gzip compressed tar archive
# (.tar.gz suffix).
# @return [String]
#
# @!attribute [rw] additional_inference_specifications
# An array of additional Inference Specification objects.
# @return [Array<Types::AdditionalInferenceSpecificationDefinition>]
#
# @!attribute [rw] tags
# A list of the tags associated with the model package. For more
# information, see [Tagging Amazon Web Services resources][1] in the
# *Amazon Web Services General Reference Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] customer_metadata_properties
# The metadata properties for the model package.
# @return [Hash<String,String>]
#
# @!attribute [rw] drift_check_baselines
# Represents the drift check baselines that can be used when the model
# monitor is set using the model package.
# @return [Types::DriftCheckBaselines]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackage AWS API Documentation
#
class ModelPackage < Struct.new(
:model_package_name,
:model_package_group_name,
:model_package_version,
:model_package_arn,
:model_package_description,
:creation_time,
:inference_specification,
:source_algorithm_specification,
:validation_specification,
:model_package_status,
:model_package_status_details,
:certify_for_marketplace,
:model_approval_status,
:created_by,
:metadata_properties,
:model_metrics,
:last_modified_time,
:last_modified_by,
:approval_description,
:domain,
:task,
:sample_payload_url,
:additional_inference_specifications,
:tags,
:customer_metadata_properties,
:drift_check_baselines)
SENSITIVE = []
include Aws::Structure
end
# Describes the Docker container for the model package.
#
# @!attribute [rw] container_hostname
# The DNS host name for the Docker container.
# @return [String]
#
# @!attribute [rw] image
# The Amazon EC2 Container Registry (Amazon ECR) path where inference
# code is stored.
#
# If you are using your own custom algorithm instead of an algorithm
# provided by SageMaker, the inference code must meet SageMaker
# requirements. SageMaker supports both `registry/repository[:tag]`
# and `registry/repository[@digest]` image path formats. For more
# information, see [Using Your Own Algorithms with Amazon
# SageMaker][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html
# @return [String]
#
# @!attribute [rw] image_digest
# An MD5 hash of the training algorithm that identifies the Docker
# image used for training.
# @return [String]
#
# @!attribute [rw] model_data_url
# The Amazon S3 path where the model artifacts, which result from
# model training, are stored. This path must point to a single `gzip`
# compressed tar archive (`.tar.gz` suffix).
#
# <note markdown="1"> The model artifacts must be in an S3 bucket that is in the same
# region as the model package.
#
# </note>
# @return [String]
#
# @!attribute [rw] product_id
# The Amazon Web Services Marketplace product ID of the model package.
# @return [String]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container. Each key
# and value in the `Environment` string to string map can have length
# of up to 1024. We support up to 16 entries in the map.
# @return [Hash<String,String>]
#
# @!attribute [rw] model_input
# A structure with Model Input details.
# @return [Types::ModelInput]
#
# @!attribute [rw] framework
# The machine learning framework of the model package container image.
# @return [String]
#
# @!attribute [rw] framework_version
# The framework version of the Model Package Container Image.
# @return [String]
#
# @!attribute [rw] nearest_model_name
# The name of a pre-trained machine learning benchmarked by Amazon
# SageMaker Inference Recommender model that matches your model. You
# can find a list of benchmarked models by calling
# `ListModelMetadata`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageContainerDefinition AWS API Documentation
#
class ModelPackageContainerDefinition < Struct.new(
:container_hostname,
:image,
:image_digest,
:model_data_url,
:product_id,
:environment,
:model_input,
:framework,
:framework_version,
:nearest_model_name)
SENSITIVE = []
include Aws::Structure
end
# A group of versioned models in the model registry.
#
# @!attribute [rw] model_package_group_name
# The name of the model group.
# @return [String]
#
# @!attribute [rw] model_package_group_arn
# The Amazon Resource Name (ARN) of the model group.
# @return [String]
#
# @!attribute [rw] model_package_group_description
# The description for the model group.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the model group was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] model_package_group_status
# The status of the model group. This can be one of the following
# values.
#
# * `PENDING` - The model group is pending being created.
#
# * `IN_PROGRESS` - The model group is in the process of being
# created.
#
# * `COMPLETED` - The model group was successfully created.
#
# * `FAILED` - The model group failed.
#
# * `DELETING` - The model group is in the process of being deleted.
#
# * `DELETE_FAILED` - SageMaker failed to delete the model group.
# @return [String]
#
# @!attribute [rw] tags
# A list of the tags associated with the model group. For more
# information, see [Tagging Amazon Web Services resources][1] in the
# *Amazon Web Services General Reference Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageGroup AWS API Documentation
#
class ModelPackageGroup < Struct.new(
:model_package_group_name,
:model_package_group_arn,
:model_package_group_description,
:creation_time,
:created_by,
:model_package_group_status,
:tags)
SENSITIVE = []
include Aws::Structure
end
# Summary information about a model group.
#
# @!attribute [rw] model_package_group_name
# The name of the model group.
# @return [String]
#
# @!attribute [rw] model_package_group_arn
# The Amazon Resource Name (ARN) of the model group.
# @return [String]
#
# @!attribute [rw] model_package_group_description
# A description of the model group.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the model group was created.
# @return [Time]
#
# @!attribute [rw] model_package_group_status
# The status of the model group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageGroupSummary AWS API Documentation
#
class ModelPackageGroupSummary < Struct.new(
:model_package_group_name,
:model_package_group_arn,
:model_package_group_description,
:creation_time,
:model_package_group_status)
SENSITIVE = []
include Aws::Structure
end
# Specifies the validation and image scan statuses of the model package.
#
# @!attribute [rw] validation_statuses
# The validation status of the model package.
# @return [Array<Types::ModelPackageStatusItem>]
#
# @!attribute [rw] image_scan_statuses
# The status of the scan of the Docker image container for the model
# package.
# @return [Array<Types::ModelPackageStatusItem>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageStatusDetails AWS API Documentation
#
class ModelPackageStatusDetails < Struct.new(
:validation_statuses,
:image_scan_statuses)
SENSITIVE = []
include Aws::Structure
end
# Represents the overall status of a model package.
#
# @!attribute [rw] name
# The name of the model package for which the overall status is being
# reported.
# @return [String]
#
# @!attribute [rw] status
# The current status.
# @return [String]
#
# @!attribute [rw] failure_reason
# if the overall status is `Failed`, the reason for the failure.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageStatusItem AWS API Documentation
#
class ModelPackageStatusItem < Struct.new(
:name,
:status,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information about a model package.
#
# @!attribute [rw] model_package_name
# The name of the model package.
# @return [String]
#
# @!attribute [rw] model_package_group_name
# If the model package is a versioned model, the model group that the
# versioned model belongs to.
# @return [String]
#
# @!attribute [rw] model_package_version
# If the model package is a versioned model, the version of the model.
# @return [Integer]
#
# @!attribute [rw] model_package_arn
# The Amazon Resource Name (ARN) of the model package.
# @return [String]
#
# @!attribute [rw] model_package_description
# A brief description of the model package.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the model package was created.
# @return [Time]
#
# @!attribute [rw] model_package_status
# The overall status of the model package.
# @return [String]
#
# @!attribute [rw] model_approval_status
# The approval status of the model. This can be one of the following
# values.
#
# * `APPROVED` - The model is approved
#
# * `REJECTED` - The model is rejected.
#
# * `PENDING_MANUAL_APPROVAL` - The model is waiting for manual
# approval.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageSummary AWS API Documentation
#
class ModelPackageSummary < Struct.new(
:model_package_name,
:model_package_group_name,
:model_package_version,
:model_package_arn,
:model_package_description,
:creation_time,
:model_package_status,
:model_approval_status)
SENSITIVE = []
include Aws::Structure
end
# 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 Amazon Web Services Marketplace.
#
# @!attribute [rw] profile_name
# The name of the profile for the model package.
# @return [String]
#
# @!attribute [rw] transform_job_definition
# The `TransformJobDefinition` object that describes the transform job
# used for the validation of the model package.
# @return [Types::TransformJobDefinition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageValidationProfile AWS API Documentation
#
class ModelPackageValidationProfile < Struct.new(
:profile_name,
:transform_job_definition)
SENSITIVE = []
include Aws::Structure
end
# Specifies batch transform jobs that SageMaker runs to validate your
# model package.
#
# @!attribute [rw] validation_role
# The IAM roles to be used for the validation of the model package.
# @return [String]
#
# @!attribute [rw] validation_profiles
# An array of `ModelPackageValidationProfile` objects, each of which
# specifies a batch transform job that SageMaker runs to validate your
# model package.
# @return [Array<Types::ModelPackageValidationProfile>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageValidationSpecification AWS API Documentation
#
class ModelPackageValidationSpecification < Struct.new(
:validation_role,
:validation_profiles)
SENSITIVE = []
include Aws::Structure
end
# Model quality statistics and constraints.
#
# @!attribute [rw] statistics
# Model quality statistics.
# @return [Types::MetricsSource]
#
# @!attribute [rw] constraints
# Model quality constraints.
# @return [Types::MetricsSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelQuality AWS API Documentation
#
class ModelQuality < Struct.new(
:statistics,
:constraints)
SENSITIVE = []
include Aws::Structure
end
# Container image configuration object for the monitoring job.
#
# @!attribute [rw] image_uri
# The address of the container image that the monitoring job runs.
# @return [String]
#
# @!attribute [rw] container_entrypoint
# Specifies the entrypoint for a container that the monitoring job
# runs.
# @return [Array<String>]
#
# @!attribute [rw] container_arguments
# An array of arguments for the container used to run the monitoring
# job.
# @return [Array<String>]
#
# @!attribute [rw] record_preprocessor_source_uri
# An Amazon S3 URI to a script that is called per row prior to running
# analysis. It can base64 decode the payload and convert it into a
# flatted json so that the built-in container can use the converted
# data. Applicable only for the built-in (first party) containers.
# @return [String]
#
# @!attribute [rw] post_analytics_processor_source_uri
# An Amazon S3 URI to a script that is called after analysis has been
# performed. Applicable only for the built-in (first party)
# containers.
# @return [String]
#
# @!attribute [rw] problem_type
# The machine learning problem type of the model that the monitoring
# job monitors.
# @return [String]
#
# @!attribute [rw] environment
# Sets the environment variables in the container that the monitoring
# job runs.
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelQualityAppSpecification AWS API Documentation
#
class ModelQualityAppSpecification < Struct.new(
:image_uri,
:container_entrypoint,
:container_arguments,
:record_preprocessor_source_uri,
:post_analytics_processor_source_uri,
:problem_type,
:environment)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] baselining_job_name
# The name of the job that performs baselining for the monitoring job.
# @return [String]
#
# @!attribute [rw] constraints_resource
# The constraints resource for a monitoring job.
# @return [Types::MonitoringConstraintsResource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelQualityBaselineConfig AWS API Documentation
#
class ModelQualityBaselineConfig < Struct.new(
:baselining_job_name,
:constraints_resource)
SENSITIVE = []
include Aws::Structure
end
# The input for the model quality monitoring job. Currently endponts are
# supported for input for model quality monitoring jobs.
#
# @!attribute [rw] endpoint_input
# Input object for the endpoint
# @return [Types::EndpointInput]
#
# @!attribute [rw] batch_transform_input
# Input object for the batch transform job.
# @return [Types::BatchTransformInput]
#
# @!attribute [rw] ground_truth_s3_input
# The ground truth label provided for the model.
# @return [Types::MonitoringGroundTruthS3Input]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelQualityJobInput AWS API Documentation
#
class ModelQualityJobInput < Struct.new(
:endpoint_input,
:batch_transform_input,
:ground_truth_s3_input)
SENSITIVE = []
include Aws::Structure
end
# The model registry settings for the SageMaker Canvas application.
#
# @!attribute [rw] status
# Describes whether the integration to the model registry is enabled
# or disabled in the Canvas application.
# @return [String]
#
# @!attribute [rw] cross_account_model_register_role_arn
# The Amazon Resource Name (ARN) of the SageMaker model registry
# account. Required only to register model versions created by a
# different SageMaker Canvas AWS account than the AWS account in which
# SageMaker model registry is set up.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelRegisterSettings AWS API Documentation
#
class ModelRegisterSettings < Struct.new(
:status,
:cross_account_model_register_role_arn)
SENSITIVE = []
include Aws::Structure
end
# Metadata for Model steps.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the created model.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelStepMetadata AWS API Documentation
#
class ModelStepMetadata < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information about a model.
#
# @!attribute [rw] model_name
# The name of the model that you want a summary for.
# @return [String]
#
# @!attribute [rw] model_arn
# The Amazon Resource Name (ARN) of the model.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when the model was created.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelSummary AWS API Documentation
#
class ModelSummary < Struct.new(
:model_name,
:model_arn,
:creation_time)
SENSITIVE = []
include Aws::Structure
end
# Contains information about the deployment options of a model.
#
# @!attribute [rw] model_name
# The name of the Amazon SageMaker Model entity.
# @return [String]
#
# @!attribute [rw] variant_name
# The name of the variant.
# @return [String]
#
# @!attribute [rw] infrastructure_config
# The configuration for the infrastructure that the model will be
# deployed to.
# @return [Types::ModelInfrastructureConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelVariantConfig AWS API Documentation
#
class ModelVariantConfig < Struct.new(
:model_name,
:variant_name,
:infrastructure_config)
SENSITIVE = []
include Aws::Structure
end
# Summary of the deployment configuration of a model.
#
# @!attribute [rw] model_name
# The name of the Amazon SageMaker Model entity.
# @return [String]
#
# @!attribute [rw] variant_name
# The name of the variant.
# @return [String]
#
# @!attribute [rw] infrastructure_config
# The configuration of the infrastructure that the model has been
# deployed to.
# @return [Types::ModelInfrastructureConfig]
#
# @!attribute [rw] status
# The status of deployment for the model variant on the hosted
# inference endpoint.
#
# * `Creating` - Amazon SageMaker is preparing the model variant on
# the hosted inference endpoint.
#
# * `InService` - The model variant is running on the hosted inference
# endpoint.
#
# * `Updating` - Amazon SageMaker is updating the model variant on the
# hosted inference endpoint.
#
# * `Deleting` - Amazon SageMaker is deleting the model variant on the
# hosted inference endpoint.
#
# * `Deleted` - The model variant has been deleted on the hosted
# inference endpoint. This can only happen after stopping the
# experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelVariantConfigSummary AWS API Documentation
#
class ModelVariantConfigSummary < Struct.new(
:model_name,
:variant_name,
:infrastructure_config,
:status)
SENSITIVE = []
include Aws::Structure
end
# A list of alert actions taken in response to an alert going into
# `InAlert` status.
#
# @!attribute [rw] model_dashboard_indicator
# An alert action taken to light up an icon on the Model Dashboard
# when an alert goes into `InAlert` status.
# @return [Types::ModelDashboardIndicatorAction]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringAlertActions AWS API Documentation
#
class MonitoringAlertActions < Struct.new(
:model_dashboard_indicator)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information of an alert's history.
#
# @!attribute [rw] monitoring_schedule_name
# The name of a monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_alert_name
# The name of a monitoring alert.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when the first alert transition occurred
# in an alert history. An alert transition can be from status
# `InAlert` to `OK`, or from `OK` to `InAlert`.
# @return [Time]
#
# @!attribute [rw] alert_status
# The current alert status of an alert.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringAlertHistorySummary AWS API Documentation
#
class MonitoringAlertHistorySummary < Struct.new(
:monitoring_schedule_name,
:monitoring_alert_name,
:creation_time,
:alert_status)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information about a monitor alert.
#
# @!attribute [rw] monitoring_alert_name
# The name of a monitoring alert.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when a monitor alert was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that indicates when a monitor alert was last updated.
# @return [Time]
#
# @!attribute [rw] alert_status
# The current status of an alert.
# @return [String]
#
# @!attribute [rw] datapoints_to_alert
# Within `EvaluationPeriod`, how many execution failures will raise an
# alert.
# @return [Integer]
#
# @!attribute [rw] evaluation_period
# The number of most recent monitoring executions to consider when
# evaluating alert status.
# @return [Integer]
#
# @!attribute [rw] actions
# A list of alert actions taken in response to an alert going into
# `InAlert` status.
# @return [Types::MonitoringAlertActions]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringAlertSummary AWS API Documentation
#
class MonitoringAlertSummary < Struct.new(
:monitoring_alert_name,
:creation_time,
:last_modified_time,
:alert_status,
:datapoints_to_alert,
:evaluation_period,
:actions)
SENSITIVE = []
include Aws::Structure
end
# Container image configuration object for the monitoring job.
#
# @!attribute [rw] image_uri
# The container image to be run by the monitoring job.
# @return [String]
#
# @!attribute [rw] container_entrypoint
# Specifies the entrypoint for a container used to run the monitoring
# job.
# @return [Array<String>]
#
# @!attribute [rw] container_arguments
# An array of arguments for the container used to run the monitoring
# job.
# @return [Array<String>]
#
# @!attribute [rw] record_preprocessor_source_uri
# An Amazon S3 URI to a script that is called per row prior to running
# analysis. It can base64 decode the payload and convert it into a
# flatted json so that the built-in container can use the converted
# data. Applicable only for the built-in (first party) containers.
# @return [String]
#
# @!attribute [rw] post_analytics_processor_source_uri
# An Amazon S3 URI to a script that is called after analysis has been
# performed. Applicable only for the built-in (first party)
# containers.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringAppSpecification AWS API Documentation
#
class MonitoringAppSpecification < Struct.new(
:image_uri,
:container_entrypoint,
:container_arguments,
:record_preprocessor_source_uri,
:post_analytics_processor_source_uri)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] baselining_job_name
# The name of the job that performs baselining for the monitoring job.
# @return [String]
#
# @!attribute [rw] constraints_resource
# The baseline constraint file in Amazon S3 that the current
# monitoring job should validated against.
# @return [Types::MonitoringConstraintsResource]
#
# @!attribute [rw] statistics_resource
# The baseline statistics file in Amazon S3 that the current
# monitoring job should be validated against.
# @return [Types::MonitoringStatisticsResource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringBaselineConfig AWS API Documentation
#
class MonitoringBaselineConfig < Struct.new(
:baselining_job_name,
:constraints_resource,
:statistics_resource)
SENSITIVE = []
include Aws::Structure
end
# Configuration for the cluster used to run model monitoring jobs.
#
# @!attribute [rw] instance_count
# The number of ML compute instances to use in the model monitoring
# job. For distributed processing jobs, specify a value greater than
# 1. The default value is 1.
# @return [Integer]
#
# @!attribute [rw] instance_type
# The ML compute instance type for the processing job.
# @return [String]
#
# @!attribute [rw] volume_size_in_gb
# The size of the ML storage volume, in gigabytes, that you want to
# provision. You must specify sufficient ML storage for your scenario.
# @return [Integer]
#
# @!attribute [rw] volume_kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt data on the storage
# volume attached to the ML compute instance(s) that run the model
# monitoring job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringClusterConfig AWS API Documentation
#
class MonitoringClusterConfig < Struct.new(
:instance_count,
:instance_type,
:volume_size_in_gb,
:volume_kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# The constraints resource for a monitoring job.
#
# @!attribute [rw] s3_uri
# The Amazon S3 URI for the constraints resource.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringConstraintsResource AWS API Documentation
#
class MonitoringConstraintsResource < Struct.new(
:s3_uri)
SENSITIVE = []
include Aws::Structure
end
# Represents the CSV dataset format used when running a monitoring job.
#
# @!attribute [rw] header
# Indicates if the CSV data has a header.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringCsvDatasetFormat AWS API Documentation
#
class MonitoringCsvDatasetFormat < Struct.new(
:header)
SENSITIVE = []
include Aws::Structure
end
# Represents the dataset format used when running a monitoring job.
#
# @!attribute [rw] csv
# The CSV dataset used in the monitoring job.
# @return [Types::MonitoringCsvDatasetFormat]
#
# @!attribute [rw] json
# The JSON dataset used in the monitoring job
# @return [Types::MonitoringJsonDatasetFormat]
#
# @!attribute [rw] parquet
# The Parquet dataset used in the monitoring job
# @return [Types::MonitoringParquetDatasetFormat]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringDatasetFormat AWS API Documentation
#
class MonitoringDatasetFormat < Struct.new(
:csv,
:json,
:parquet)
SENSITIVE = []
include Aws::Structure
end
# Summary of information about the last monitoring job to run.
#
# @!attribute [rw] monitoring_schedule_name
# The name of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] scheduled_time
# The time the monitoring job was scheduled.
# @return [Time]
#
# @!attribute [rw] creation_time
# The time at which the monitoring job was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that indicates the last time the monitoring job was
# modified.
# @return [Time]
#
# @!attribute [rw] monitoring_execution_status
# The status of the monitoring job.
# @return [String]
#
# @!attribute [rw] processing_job_arn
# The Amazon Resource Name (ARN) of the monitoring job.
# @return [String]
#
# @!attribute [rw] endpoint_name
# The name of the endpoint used to run the monitoring job.
# @return [String]
#
# @!attribute [rw] failure_reason
# Contains the reason a monitoring job failed, if it failed.
# @return [String]
#
# @!attribute [rw] monitoring_job_definition_name
# The name of the monitoring job.
# @return [String]
#
# @!attribute [rw] monitoring_type
# The type of the monitoring job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringExecutionSummary AWS API Documentation
#
class MonitoringExecutionSummary < Struct.new(
:monitoring_schedule_name,
:scheduled_time,
:creation_time,
:last_modified_time,
:monitoring_execution_status,
:processing_job_arn,
:endpoint_name,
:failure_reason,
:monitoring_job_definition_name,
:monitoring_type)
SENSITIVE = []
include Aws::Structure
end
# The ground truth labels for the dataset used for the monitoring job.
#
# @!attribute [rw] s3_uri
# The address of the Amazon S3 location of the ground truth labels.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringGroundTruthS3Input AWS API Documentation
#
class MonitoringGroundTruthS3Input < Struct.new(
:s3_uri)
SENSITIVE = []
include Aws::Structure
end
# The inputs for a monitoring job.
#
# @!attribute [rw] endpoint_input
# The endpoint for a monitoring job.
# @return [Types::EndpointInput]
#
# @!attribute [rw] batch_transform_input
# Input object for the batch transform job.
# @return [Types::BatchTransformInput]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringInput AWS API Documentation
#
class MonitoringInput < Struct.new(
:endpoint_input,
:batch_transform_input)
SENSITIVE = []
include Aws::Structure
end
# Defines the monitoring job.
#
# @!attribute [rw] baseline_config
# Baseline configuration used to validate that the data conforms to
# the specified constraints and statistics
# @return [Types::MonitoringBaselineConfig]
#
# @!attribute [rw] monitoring_inputs
# The array of inputs for the monitoring job. Currently we support
# monitoring an Amazon SageMaker Endpoint.
# @return [Array<Types::MonitoringInput>]
#
# @!attribute [rw] monitoring_output_config
# The array of outputs from the monitoring job to be uploaded to
# Amazon Simple Storage Service (Amazon S3).
# @return [Types::MonitoringOutputConfig]
#
# @!attribute [rw] monitoring_resources
# Identifies the resources, ML compute instances, and ML storage
# volumes to deploy for a monitoring job. In distributed processing,
# you specify more than one instance.
# @return [Types::MonitoringResources]
#
# @!attribute [rw] monitoring_app_specification
# Configures the monitoring job to run a specified Docker container
# image.
# @return [Types::MonitoringAppSpecification]
#
# @!attribute [rw] stopping_condition
# Specifies a time limit for how long the monitoring job is allowed to
# run.
# @return [Types::MonitoringStoppingCondition]
#
# @!attribute [rw] environment
# Sets the environment variables in the Docker container.
# @return [Hash<String,String>]
#
# @!attribute [rw] network_config
# Specifies networking options for an monitoring job.
# @return [Types::NetworkConfig]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker
# can assume to perform tasks on your behalf.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringJobDefinition AWS API Documentation
#
class MonitoringJobDefinition < Struct.new(
:baseline_config,
:monitoring_inputs,
:monitoring_output_config,
:monitoring_resources,
:monitoring_app_specification,
:stopping_condition,
:environment,
:network_config,
:role_arn)
SENSITIVE = []
include Aws::Structure
end
# Summary information about a monitoring job.
#
# @!attribute [rw] monitoring_job_definition_name
# The name of the monitoring job.
# @return [String]
#
# @!attribute [rw] monitoring_job_definition_arn
# The Amazon Resource Name (ARN) of the monitoring job.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the monitoring job was created.
# @return [Time]
#
# @!attribute [rw] endpoint_name
# The name of the endpoint that the job monitors.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringJobDefinitionSummary AWS API Documentation
#
class MonitoringJobDefinitionSummary < Struct.new(
:monitoring_job_definition_name,
:monitoring_job_definition_arn,
:creation_time,
:endpoint_name)
SENSITIVE = []
include Aws::Structure
end
# Represents the JSON dataset format used when running a monitoring job.
#
# @!attribute [rw] line
# Indicates if the file should be read as a json object per line.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringJsonDatasetFormat AWS API Documentation
#
class MonitoringJsonDatasetFormat < Struct.new(
:line)
SENSITIVE = []
include Aws::Structure
end
# The networking configuration for the monitoring job.
#
# @!attribute [rw] enable_inter_container_traffic_encryption
# Whether to encrypt all communications between the instances used for
# the monitoring jobs. Choose `True` to encrypt communications.
# Encryption provides greater security for distributed jobs, but the
# processing might take longer.
# @return [Boolean]
#
# @!attribute [rw] enable_network_isolation
# Whether to allow inbound and outbound network calls to and from the
# containers used for the monitoring job.
# @return [Boolean]
#
# @!attribute [rw] vpc_config
# 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][1] and
# [Protect Training Jobs by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
# @return [Types::VpcConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringNetworkConfig AWS API Documentation
#
class MonitoringNetworkConfig < Struct.new(
:enable_inter_container_traffic_encryption,
:enable_network_isolation,
:vpc_config)
SENSITIVE = []
include Aws::Structure
end
# The output object for a monitoring job.
#
# @!attribute [rw] s3_output
# The Amazon S3 storage location where the results of a monitoring job
# are saved.
# @return [Types::MonitoringS3Output]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringOutput AWS API Documentation
#
class MonitoringOutput < Struct.new(
:s3_output)
SENSITIVE = []
include Aws::Structure
end
# The output configuration for monitoring jobs.
#
# @!attribute [rw] monitoring_outputs
# Monitoring outputs for monitoring jobs. This is where the output of
# the periodic monitoring jobs is uploaded.
# @return [Array<Types::MonitoringOutput>]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt the model artifacts
# at rest using Amazon S3 server-side encryption.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringOutputConfig AWS API Documentation
#
class MonitoringOutputConfig < Struct.new(
:monitoring_outputs,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# Represents the Parquet dataset format used when running a monitoring
# job.
#
# @api private
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringParquetDatasetFormat AWS API Documentation
#
class MonitoringParquetDatasetFormat < Aws::EmptyStructure; end
# Identifies the resources to deploy for a monitoring job.
#
# @!attribute [rw] cluster_config
# The configuration for the cluster resources used to run the
# processing job.
# @return [Types::MonitoringClusterConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringResources AWS API Documentation
#
class MonitoringResources < Struct.new(
:cluster_config)
SENSITIVE = []
include Aws::Structure
end
# Information about where and how you want to store the results of a
# monitoring job.
#
# @!attribute [rw] s3_uri
# A URI that identifies the Amazon S3 storage location where Amazon
# SageMaker saves the results of a monitoring job.
# @return [String]
#
# @!attribute [rw] local_path
# The local path to the Amazon S3 storage location where Amazon
# SageMaker saves the results of a monitoring job. LocalPath is an
# absolute path for the output data.
# @return [String]
#
# @!attribute [rw] s3_upload_mode
# Whether to upload the results of the monitoring job continuously or
# after the job completes.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringS3Output AWS API Documentation
#
class MonitoringS3Output < Struct.new(
:s3_uri,
:local_path,
:s3_upload_mode)
SENSITIVE = []
include Aws::Structure
end
# A schedule for a model monitoring job. For information about model
# monitor, see [Amazon SageMaker Model Monitor][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor.html
#
# @!attribute [rw] monitoring_schedule_arn
# The Amazon Resource Name (ARN) of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_name
# The name of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_status
# The status of the monitoring schedule. This can be one of the
# following values.
#
# * `PENDING` - The schedule is pending being created.
#
# * `FAILED` - The schedule failed.
#
# * `SCHEDULED` - The schedule was successfully created.
#
# * `STOPPED` - The schedule was stopped.
# @return [String]
#
# @!attribute [rw] monitoring_type
# The type of the monitoring job definition to schedule.
# @return [String]
#
# @!attribute [rw] failure_reason
# If the monitoring schedule failed, the reason it failed.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the monitoring schedule was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last time the monitoring schedule was changed.
# @return [Time]
#
# @!attribute [rw] monitoring_schedule_config
# Configures the monitoring schedule and defines the monitoring job.
# @return [Types::MonitoringScheduleConfig]
#
# @!attribute [rw] endpoint_name
# The endpoint that hosts the model being monitored.
# @return [String]
#
# @!attribute [rw] last_monitoring_execution_summary
# Summary of information about the last monitoring job to run.
# @return [Types::MonitoringExecutionSummary]
#
# @!attribute [rw] tags
# A list of the tags associated with the monitoring schedlue. For more
# information, see [Tagging Amazon Web Services resources][1] in the
# *Amazon Web Services General Reference Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringSchedule AWS API Documentation
#
class MonitoringSchedule < Struct.new(
:monitoring_schedule_arn,
:monitoring_schedule_name,
:monitoring_schedule_status,
:monitoring_type,
:failure_reason,
:creation_time,
:last_modified_time,
:monitoring_schedule_config,
:endpoint_name,
:last_monitoring_execution_summary,
:tags)
SENSITIVE = []
include Aws::Structure
end
# Configures the monitoring schedule and defines the monitoring job.
#
# @!attribute [rw] schedule_config
# Configures the monitoring schedule.
# @return [Types::ScheduleConfig]
#
# @!attribute [rw] monitoring_job_definition
# Defines the monitoring job.
# @return [Types::MonitoringJobDefinition]
#
# @!attribute [rw] monitoring_job_definition_name
# The name of the monitoring job definition to schedule.
# @return [String]
#
# @!attribute [rw] monitoring_type
# The type of the monitoring job definition to schedule.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringScheduleConfig AWS API Documentation
#
class MonitoringScheduleConfig < Struct.new(
:schedule_config,
:monitoring_job_definition,
:monitoring_job_definition_name,
:monitoring_type)
SENSITIVE = []
include Aws::Structure
end
# Summarizes the monitoring schedule.
#
# @!attribute [rw] monitoring_schedule_name
# The name of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_arn
# The Amazon Resource Name (ARN) of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of the monitoring schedule.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last time the monitoring schedule was modified.
# @return [Time]
#
# @!attribute [rw] monitoring_schedule_status
# The status of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] endpoint_name
# The name of the endpoint using the monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_job_definition_name
# The name of the monitoring job definition that the schedule is for.
# @return [String]
#
# @!attribute [rw] monitoring_type
# The type of the monitoring job definition that the schedule is for.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringScheduleSummary AWS API Documentation
#
class MonitoringScheduleSummary < Struct.new(
:monitoring_schedule_name,
:monitoring_schedule_arn,
:creation_time,
:last_modified_time,
:monitoring_schedule_status,
:endpoint_name,
:monitoring_job_definition_name,
:monitoring_type)
SENSITIVE = []
include Aws::Structure
end
# The statistics resource for a monitoring job.
#
# @!attribute [rw] s3_uri
# The Amazon S3 URI for the statistics resource.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringStatisticsResource AWS API Documentation
#
class MonitoringStatisticsResource < Struct.new(
:s3_uri)
SENSITIVE = []
include Aws::Structure
end
# A time limit for how long the monitoring job is allowed to run before
# stopping.
#
# @!attribute [rw] max_runtime_in_seconds
# The maximum runtime allowed in seconds.
#
# <note markdown="1"> The `MaxRuntimeInSeconds` cannot exceed the frequency of the job.
# For data quality and model explainability, this can be up to 3600
# seconds for an hourly schedule. For model bias and model quality
# hourly schedules, this can be up to 1800 seconds.
#
# </note>
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringStoppingCondition AWS API Documentation
#
class MonitoringStoppingCondition < Struct.new(
:max_runtime_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# Specifies additional configuration for hosting multi-model endpoints.
#
# @!attribute [rw] model_cache_setting
# Whether to cache models for a multi-model endpoint. By default,
# multi-model endpoints cache models so that a model does not have to
# be loaded into memory each time it is invoked. Some use cases do not
# benefit from model caching. For example, if an endpoint hosts a
# large number of models that are each invoked infrequently, the
# endpoint might perform better if you disable model caching. To
# disable model caching, set the value of this parameter to
# `Disabled`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MultiModelConfig AWS API Documentation
#
class MultiModelConfig < Struct.new(
:model_cache_setting)
SENSITIVE = []
include Aws::Structure
end
# The [VpcConfig][1] configuration object that specifies the VPC that
# you want the compilation jobs to connect to. For more information on
# controlling access to your Amazon S3 buckets used for compilation job,
# see [Give Amazon SageMaker Compilation Jobs Access to Resources in
# Your Amazon VPC][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/neo-vpc.html
#
# @!attribute [rw] security_group_ids
# The VPC security group IDs. IDs have the form of `sg-xxxxxxxx`.
# Specify the security groups for the VPC that is specified in the
# `Subnets` field.
# @return [Array<String>]
#
# @!attribute [rw] subnets
# The ID of the subnets in the VPC that you want to connect the
# compilation job to for accessing the model in Amazon S3.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NeoVpcConfig AWS API Documentation
#
class NeoVpcConfig < Struct.new(
:security_group_ids,
:subnets)
SENSITIVE = []
include Aws::Structure
end
# A list of nested [Filter][1] objects. A resource must satisfy the
# conditions of all filters to be included in the results returned from
# the [Search][2] API.
#
# For example, to filter on a training job's `InputDataConfig` property
# with a specific channel name and `S3Uri` prefix, define the following
# filters:
#
# * `'\{Name:"InputDataConfig.ChannelName", "Operator":"Equals",
# "Value":"train"\}',`
#
# * `'\{Name:"InputDataConfig.DataSource.S3DataSource.S3Uri",
# "Operator":"Contains", "Value":"mybucket/catdata"\}'`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Filter.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
#
# @!attribute [rw] nested_property_name
# The name of the property to use in the nested filters. The value
# must match a listed property name, such as `InputDataConfig`.
# @return [String]
#
# @!attribute [rw] filters
# A list of filters. Each filter acts on a property. Filters must
# contain at least one `Filters` value. For example, a `NestedFilters`
# call might include a filter on the `PropertyName` parameter of the
# `InputDataConfig` property:
# `InputDataConfig.DataSource.S3DataSource.S3Uri`.
# @return [Array<Types::Filter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NestedFilters AWS API Documentation
#
class NestedFilters < Struct.new(
:nested_property_name,
:filters)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] enable_inter_container_traffic_encryption
# Whether to encrypt all communications between distributed processing
# jobs. Choose `True` to encrypt communications. Encryption provides
# greater security for distributed processing jobs, but the processing
# might take longer.
# @return [Boolean]
#
# @!attribute [rw] enable_network_isolation
# Whether to allow inbound and outbound network calls to and from the
# containers used for the processing job.
# @return [Boolean]
#
# @!attribute [rw] vpc_config
# 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][1] and
# [Protect Training Jobs by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
# @return [Types::VpcConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NetworkConfig AWS API Documentation
#
class NetworkConfig < Struct.new(
:enable_inter_container_traffic_encryption,
:enable_network_isolation,
:vpc_config)
SENSITIVE = []
include Aws::Structure
end
# Provides a summary of a notebook instance lifecycle configuration.
#
# @!attribute [rw] notebook_instance_lifecycle_config_name
# The name of the lifecycle configuration.
# @return [String]
#
# @!attribute [rw] notebook_instance_lifecycle_config_arn
# The Amazon Resource Name (ARN) of the lifecycle configuration.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that tells when the lifecycle configuration was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that tells when the lifecycle configuration was last
# modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NotebookInstanceLifecycleConfigSummary AWS API Documentation
#
class NotebookInstanceLifecycleConfigSummary < Struct.new(
:notebook_instance_lifecycle_config_name,
:notebook_instance_lifecycle_config_arn,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# Contains the notebook instance lifecycle configuration script.
#
# Each lifecycle configuration script has a limit of 16384 characters.
#
# The value of the `$PATH` environment variable that is available to
# both scripts is `/sbin:bin:/usr/sbin:/usr/bin`.
#
# View CloudWatch Logs for notebook instance lifecycle configurations in
# log group `/aws/sagemaker/NotebookInstances` in log stream
# `[notebook-instance-name]/[LifecycleConfigHook]`.
#
# Lifecycle configuration scripts cannot run for longer than 5 minutes.
# If a script runs for longer than 5 minutes, it fails and the notebook
# instance is not created or started.
#
# For information about notebook instance lifestyle configurations, see
# [Step 2.1: (Optional) Customize a Notebook Instance][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html
#
# @!attribute [rw] content
# A base64-encoded string that contains a shell script for a notebook
# instance lifecycle configuration.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NotebookInstanceLifecycleHook AWS API Documentation
#
class NotebookInstanceLifecycleHook < Struct.new(
:content)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information for an SageMaker notebook instance.
#
# @!attribute [rw] notebook_instance_name
# The name of the notebook instance that you want a summary for.
# @return [String]
#
# @!attribute [rw] notebook_instance_arn
# The Amazon Resource Name (ARN) of the notebook instance.
# @return [String]
#
# @!attribute [rw] notebook_instance_status
# The status of the notebook instance.
# @return [String]
#
# @!attribute [rw] url
# The URL that you use to connect to the Jupyter notebook running in
# your notebook instance.
# @return [String]
#
# @!attribute [rw] instance_type
# The type of ML compute instance that the notebook instance is
# running on.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the notebook instance was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that shows when the notebook instance was last modified.
# @return [Time]
#
# @!attribute [rw] notebook_instance_lifecycle_config_name
# The name of a notebook instance lifecycle configuration associated
# with this notebook instance.
#
# For information about notebook instance lifestyle configurations,
# see [Step 2.1: (Optional) Customize a Notebook Instance][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html
# @return [String]
#
# @!attribute [rw] default_code_repository
# The Git repository associated with the notebook instance as its
# default code repository. This can be either the name of a Git
# repository stored as a resource in your account, or the URL of a Git
# repository in [Amazon Web Services CodeCommit][1] or in any other
# Git repository. When you open a notebook instance, it opens in the
# directory that contains this repository. For more information, see
# [Associating Git Repositories with SageMaker Notebook Instances][2].
#
#
#
# [1]: https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html
# @return [String]
#
# @!attribute [rw] additional_code_repositories
# An array of up to three Git repositories associated with the
# notebook instance. These can be either the names of Git repositories
# stored as resources in your account, or the URL of Git repositories
# in [Amazon Web Services CodeCommit][1] or in any other Git
# repository. These repositories are cloned at the same level as the
# default repository of your notebook instance. For more information,
# see [Associating Git Repositories with SageMaker Notebook
# Instances][2].
#
#
#
# [1]: https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NotebookInstanceSummary AWS API Documentation
#
class NotebookInstanceSummary < Struct.new(
:notebook_instance_name,
:notebook_instance_arn,
:notebook_instance_status,
:url,
:instance_type,
:creation_time,
:last_modified_time,
:notebook_instance_lifecycle_config_name,
:default_code_repository,
:additional_code_repositories)
SENSITIVE = []
include Aws::Structure
end
# Configures Amazon SNS notifications of available or expiring work
# items for work teams.
#
# @!attribute [rw] notification_topic_arn
# The ARN for the Amazon SNS topic to which notifications should be
# published.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NotificationConfiguration AWS API Documentation
#
class NotificationConfiguration < Struct.new(
:notification_topic_arn)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] succeeded
# The number of training jobs whose final objective metric was
# evaluated by the hyperparameter tuning job and used in the
# hyperparameter tuning process.
# @return [Integer]
#
# @!attribute [rw] pending
# The number of training jobs that are in progress and pending
# evaluation of their final objective metric.
# @return [Integer]
#
# @!attribute [rw] failed
# The number of training jobs whose final objective metric was not
# evaluated and used in the hyperparameter tuning process. This
# typically occurs when the training job failed or did not emit an
# objective metric.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ObjectiveStatusCounters AWS API Documentation
#
class ObjectiveStatusCounters < Struct.new(
:succeeded,
:pending,
:failed)
SENSITIVE = []
include Aws::Structure
end
# The configuration of an `OfflineStore`.
#
# Provide an `OfflineStoreConfig` in a request to `CreateFeatureGroup`
# to create an `OfflineStore`.
#
# To encrypt an `OfflineStore` using at rest data encryption, specify
# Amazon Web Services Key Management Service (KMS) key ID, or
# `KMSKeyId`, in `S3StorageConfig`.
#
# @!attribute [rw] s3_storage_config
# The Amazon Simple Storage (Amazon S3) location of `OfflineStore`.
# @return [Types::S3StorageConfig]
#
# @!attribute [rw] disable_glue_table_creation
# Set to `True` to disable the automatic creation of an Amazon Web
# Services Glue table when configuring an `OfflineStore`. If set to
# `False`, Feature Store will name the `OfflineStore` Glue table
# following [Athena's naming recommendations][1].
#
# The default value is `False`.
#
#
#
# [1]: https://docs.aws.amazon.com/athena/latest/ug/tables-databases-columns-names.html
# @return [Boolean]
#
# @!attribute [rw] data_catalog_config
# The meta data of the Glue table that is autogenerated when an
# `OfflineStore` is created.
# @return [Types::DataCatalogConfig]
#
# @!attribute [rw] table_format
# Format for the offline store table. Supported formats are Glue
# (Default) and [Apache Iceberg][1].
#
#
#
# [1]: https://iceberg.apache.org/
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OfflineStoreConfig AWS API Documentation
#
class OfflineStoreConfig < Struct.new(
:s3_storage_config,
:disable_glue_table_creation,
:data_catalog_config,
:table_format)
SENSITIVE = []
include Aws::Structure
end
# The status of `OfflineStore`.
#
# @!attribute [rw] status
# An `OfflineStore` status.
# @return [String]
#
# @!attribute [rw] blocked_reason
# The justification for why the OfflineStoreStatus is Blocked (if
# applicable).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OfflineStoreStatus AWS API Documentation
#
class OfflineStoreStatus < Struct.new(
:status,
:blocked_reason)
SENSITIVE = []
include Aws::Structure
end
# Use this parameter to configure your OIDC Identity Provider (IdP).
#
# @!attribute [rw] client_id
# The OIDC IdP client ID used to configure your private workforce.
# @return [String]
#
# @!attribute [rw] client_secret
# The OIDC IdP client secret used to configure your private workforce.
# @return [String]
#
# @!attribute [rw] issuer
# The OIDC IdP issuer used to configure your private workforce.
# @return [String]
#
# @!attribute [rw] authorization_endpoint
# The OIDC IdP authorization endpoint used to configure your private
# workforce.
# @return [String]
#
# @!attribute [rw] token_endpoint
# The OIDC IdP token endpoint used to configure your private
# workforce.
# @return [String]
#
# @!attribute [rw] user_info_endpoint
# The OIDC IdP user information endpoint used to configure your
# private workforce.
# @return [String]
#
# @!attribute [rw] logout_endpoint
# The OIDC IdP logout endpoint used to configure your private
# workforce.
# @return [String]
#
# @!attribute [rw] jwks_uri
# The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your
# private workforce.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OidcConfig AWS API Documentation
#
class OidcConfig < Struct.new(
:client_id,
:client_secret,
:issuer,
:authorization_endpoint,
:token_endpoint,
:user_info_endpoint,
:logout_endpoint,
:jwks_uri)
SENSITIVE = [:client_secret]
include Aws::Structure
end
# Your OIDC IdP workforce configuration.
#
# @!attribute [rw] client_id
# The OIDC IdP client ID used to configure your private workforce.
# @return [String]
#
# @!attribute [rw] issuer
# The OIDC IdP issuer used to configure your private workforce.
# @return [String]
#
# @!attribute [rw] authorization_endpoint
# The OIDC IdP authorization endpoint used to configure your private
# workforce.
# @return [String]
#
# @!attribute [rw] token_endpoint
# The OIDC IdP token endpoint used to configure your private
# workforce.
# @return [String]
#
# @!attribute [rw] user_info_endpoint
# The OIDC IdP user information endpoint used to configure your
# private workforce.
# @return [String]
#
# @!attribute [rw] logout_endpoint
# The OIDC IdP logout endpoint used to configure your private
# workforce.
# @return [String]
#
# @!attribute [rw] jwks_uri
# The OIDC IdP JSON Web Key Set (Jwks) URI used to configure your
# private workforce.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OidcConfigForResponse AWS API Documentation
#
class OidcConfigForResponse < Struct.new(
:client_id,
:issuer,
:authorization_endpoint,
:token_endpoint,
:user_info_endpoint,
:logout_endpoint,
:jwks_uri)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] groups
# A list of comma seperated strings that identifies user groups in
# your OIDC IdP. Each user group is made up of a group of private
# workers.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OidcMemberDefinition AWS API Documentation
#
class OidcMemberDefinition < Struct.new(
:groups)
SENSITIVE = []
include Aws::Structure
end
# Use this to specify the Amazon Web Services Key Management Service
# (KMS) Key ID, or `KMSKeyId`, for at rest data encryption. You can turn
# `OnlineStore` on or off by specifying the `EnableOnlineStore` flag at
# General Assembly.
#
# The default value is `False`.
#
# @!attribute [rw] security_config
# Use to specify KMS Key ID (`KMSKeyId`) for at-rest encryption of
# your `OnlineStore`.
# @return [Types::OnlineStoreSecurityConfig]
#
# @!attribute [rw] enable_online_store
# Turn `OnlineStore` off by specifying `False` for the
# `EnableOnlineStore` flag. Turn `OnlineStore` on by specifying `True`
# for the `EnableOnlineStore` flag.
#
# The default value is `False`.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OnlineStoreConfig AWS API Documentation
#
class OnlineStoreConfig < Struct.new(
:security_config,
:enable_online_store)
SENSITIVE = []
include Aws::Structure
end
# The security configuration for `OnlineStore`.
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (KMS) key ARN that
# SageMaker Feature Store uses to encrypt the Amazon S3 objects at
# rest using Amazon S3 server-side encryption.
#
# The caller (either user or IAM role) of `CreateFeatureGroup` must
# have below permissions to the `OnlineStore` `KmsKeyId`:
#
# * `"kms:Encrypt"`
#
# * `"kms:Decrypt"`
#
# * `"kms:DescribeKey"`
#
# * `"kms:CreateGrant"`
#
# * `"kms:RetireGrant"`
#
# * `"kms:ReEncryptFrom"`
#
# * `"kms:ReEncryptTo"`
#
# * `"kms:GenerateDataKey"`
#
# * `"kms:ListAliases"`
#
# * `"kms:ListGrants"`
#
# * `"kms:RevokeGrant"`
#
# The caller (either user or IAM role) to all DataPlane operations
# (`PutRecord`, `GetRecord`, `DeleteRecord`) must have the following
# permissions to the `KmsKeyId`:
#
# * `"kms:Decrypt"`
#
# ^
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OnlineStoreSecurityConfig AWS API Documentation
#
class OnlineStoreSecurityConfig < Struct.new(
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# Contains information about the output location for the compiled model
# and the target device that the model runs on. `TargetDevice` and
# `TargetPlatform` are mutually exclusive, so you need to choose one
# between the two to specify your target device or platform. If you
# cannot find your device you want to use from the `TargetDevice` list,
# use `TargetPlatform` to describe the platform of your edge device and
# `CompilerOptions` if there are specific settings that are required or
# recommended to use for particular TargetPlatform.
#
# @!attribute [rw] s3_output_location
# Identifies the S3 bucket where you want Amazon SageMaker to store
# the model artifacts. For example,
# `s3://bucket-name/key-name-prefix`.
# @return [String]
#
# @!attribute [rw] target_device
# Identifies the target device or the machine learning instance that
# you want to run your model on after the compilation has completed.
# Alternatively, you can specify OS, architecture, and accelerator
# using [TargetPlatform][1] fields. It can be used instead of
# `TargetPlatform`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TargetPlatform.html
# @return [String]
#
# @!attribute [rw] 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`.
#
# The following examples show how to configure the `TargetPlatform`
# and `CompilerOptions` JSON strings for popular target platforms:
#
# * Raspberry Pi 3 Model B+
#
# `"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM_EABIHF"\},`
#
# ` "CompilerOptions": \{'mattr': ['+neon']\}`
#
# * Jetson TX2
#
# `"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM64",
# "Accelerator": "NVIDIA"\},`
#
# ` "CompilerOptions": \{'gpu-code': 'sm_62', 'trt-ver': '6.0.1',
# 'cuda-ver': '10.0'\}`
#
# * EC2 m5.2xlarge instance OS
#
# `"TargetPlatform": \{"Os": "LINUX", "Arch": "X86_64",
# "Accelerator": "NVIDIA"\},`
#
# ` "CompilerOptions": \{'mcpu': 'skylake-avx512'\}`
#
# * RK3399
#
# `"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM64",
# "Accelerator": "MALI"\}`
#
# * ARMv7 phone (CPU)
#
# `"TargetPlatform": \{"Os": "ANDROID", "Arch": "ARM_EABI"\},`
#
# ` "CompilerOptions": \{'ANDROID_PLATFORM': 25, 'mattr':
# ['+neon']\}`
#
# * ARMv8 phone (CPU)
#
# `"TargetPlatform": \{"Os": "ANDROID", "Arch": "ARM64"\},`
#
# ` "CompilerOptions": \{'ANDROID_PLATFORM': 29\}`
# @return [Types::TargetPlatform]
#
# @!attribute [rw] compiler_options
# Specifies additional parameters for compiler options in JSON format.
# The compiler options are `TargetPlatform` specific. It is required
# for NVIDIA accelerators and highly recommended for CPU compilations.
# For any other cases, it is optional to specify `CompilerOptions.`
#
# * `DTYPE`: Specifies the data type for the input. When compiling for
# `ml_*` (except for `ml_inf`) instances using PyTorch framework,
# provide the data type (dtype) of the model's input. `"float32"`
# is used if `"DTYPE"` is not specified. Options for data type are:
#
# * float32: Use either `"float"` or `"float32"`.
#
# * int64: Use either `"int64"` or `"long"`.
#
# For example, `\{"dtype" : "float32"\}`.
#
# * `CPU`: Compilation for CPU supports the following compiler
# options.
#
# * `mcpu`: CPU micro-architecture. For example, `\{'mcpu':
# 'skylake-avx512'\}`
#
# * `mattr`: CPU flags. For example, `\{'mattr': ['+neon',
# '+vfpv4']\}`
#
# * `ARM`: Details of ARM CPU compilations.
#
# * `NEON`: NEON is an implementation of the Advanced SIMD extension
# used in ARMv7 processors.
#
# For example, add `\{'mattr': ['+neon']\}` to the compiler
# options if compiling for ARM 32-bit platform with the NEON
# support.
#
# * `NVIDIA`: Compilation for NVIDIA GPU supports the following
# compiler options.
#
# * `gpu_code`: Specifies the targeted architecture.
#
# * `trt-ver`: Specifies the TensorRT versions in x.y.z. format.
#
# * `cuda-ver`: Specifies the CUDA version in x.y format.
#
# For example, `\{'gpu-code': 'sm_72', 'trt-ver': '6.0.1',
# 'cuda-ver': '10.1'\}`
#
# * `ANDROID`: Compilation for the Android OS supports the following
# compiler options:
#
# * `ANDROID_PLATFORM`: Specifies the Android API levels. Available
# levels range from 21 to 29. For example, `\{'ANDROID_PLATFORM':
# 28\}`.
#
# * `mattr`: Add `\{'mattr': ['+neon']\}` to compiler options if
# compiling for ARM 32-bit platform with NEON support.
#
# * `INFERENTIA`: Compilation for target ml\_inf1 uses compiler
# options passed in as a JSON string. For example,
# `"CompilerOptions": ""--verbose 1 --num-neuroncores 2 -O2""`.
#
# For information about supported compiler options, see [ Neuron
# Compiler CLI][1].
#
# * `CoreML`: Compilation for the CoreML [OutputConfig][2]
# `TargetDevice` supports the following compiler options:
#
# * `class_labels`: Specifies the classification labels file name
# inside input tar.gz file. For example, `\{"class_labels":
# "imagenet_labels_1000.txt"\}`. Labels inside the txt file should
# be separated by newlines.
#
# ^
#
# * `EIA`: Compilation for the Elastic Inference Accelerator supports
# the following compiler options:
#
# * `precision_mode`: Specifies the precision of compiled artifacts.
# Supported values are `"FP16"` and `"FP32"`. Default is `"FP32"`.
#
# * `signature_def_key`: Specifies the signature to use for models
# in SavedModel format. Defaults is TensorFlow's default
# signature def key.
#
# * `output_names`: Specifies a list of output tensor names for
# models in FrozenGraph format. Set at most one API field, either:
# `signature_def_key` or `output_names`.
#
# For example: `\{"precision_mode": "FP32", "output_names":
# ["output:0"]\}`
#
#
#
# [1]: https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-cc/command-line-reference.md
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OutputConfig.html
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service key (Amazon Web
# Services KMS) that Amazon SageMaker uses to encrypt your output
# models with Amazon S3 server-side encryption after compilation job.
# If you don't provide a KMS key ID, Amazon SageMaker uses the
# default KMS key for Amazon S3 for your role's account. For more
# information, see [KMS-Managed Encryption Keys][1] in the *Amazon
# Simple Storage Service Developer Guide.*
#
# The KmsKeyId can be any of the following formats:
#
# * Key ID: `1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Key ARN:
# `arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Alias name: `alias/ExampleAlias`
#
# * Alias name ARN:
# `arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias`
#
#
#
# [1]: https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OutputConfig AWS API Documentation
#
class OutputConfig < Struct.new(
:s3_output_location,
:target_device,
:target_platform,
:compiler_options,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# Provides information about how to store model training results (model
# artifacts).
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that SageMaker uses to encrypt the model artifacts at rest
# using Amazon S3 server-side encryption. The `KmsKeyId` can be any of
# the following formats:
#
# * // KMS Key ID
#
# `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * // Amazon Resource Name (ARN) of a KMS Key
#
# `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * // KMS Key Alias
#
# `"alias/ExampleAlias"`
#
# * // Amazon Resource Name (ARN) of a KMS Key Alias
#
# `"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"`
#
# If you use a KMS key ID or an alias of your KMS key, the SageMaker
# execution role must include permissions to call `kms:Encrypt`. If
# you don't provide a KMS key ID, SageMaker uses the default KMS key
# for Amazon S3 for your role's account. SageMaker uses server-side
# encryption with KMS-managed keys for `OutputDataConfig`. If you use
# a bucket policy with an `s3:PutObject` permission that only allows
# objects with server-side encryption, set the condition key of
# `s3:x-amz-server-side-encryption` to `"aws:kms"`. For more
# information, see [KMS-Managed Encryption Keys][1] in the *Amazon
# Simple Storage Service Developer Guide.*
#
# The KMS key policy must grant permission to the IAM role that you
# specify in your `CreateTrainingJob`, `CreateTransformJob`, or
# `CreateHyperParameterTuningJob` requests. For more information, see
# [Using Key Policies in Amazon Web Services KMS][2] in the *Amazon
# Web Services Key Management Service Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingKMSEncryption.html
# [2]: https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html
# @return [String]
#
# @!attribute [rw] s3_output_path
# Identifies the S3 path where you want SageMaker to store the model
# artifacts. For example, `s3://bucket-name/key-name-prefix`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OutputDataConfig AWS API Documentation
#
class OutputDataConfig < Struct.new(
:kms_key_id,
:s3_output_path)
SENSITIVE = []
include Aws::Structure
end
# An output parameter of a pipeline step.
#
# @!attribute [rw] name
# The name of the output parameter.
# @return [String]
#
# @!attribute [rw] value
# The value of the output parameter.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OutputParameter AWS API Documentation
#
class OutputParameter < Struct.new(
:name,
:value)
SENSITIVE = []
include Aws::Structure
end
# Configuration that controls the parallelism of the pipeline. By
# default, the parallelism configuration specified applies to all
# executions of the pipeline unless overridden.
#
# @!attribute [rw] max_parallel_execution_steps
# The max number of steps that can be executed in parallel.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ParallelismConfiguration AWS API Documentation
#
class ParallelismConfiguration < Struct.new(
:max_parallel_execution_steps)
SENSITIVE = []
include Aws::Structure
end
# Assigns a value to a named Pipeline parameter.
#
# @!attribute [rw] name
# The name of the parameter to assign a value to. This parameter name
# must match a named parameter in the pipeline definition.
# @return [String]
#
# @!attribute [rw] value
# The literal value for the parameter.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Parameter AWS API Documentation
#
class Parameter < Struct.new(
:name,
:value)
SENSITIVE = []
include Aws::Structure
end
# Defines the possible values for categorical, continuous, and integer
# hyperparameters to be used by an algorithm.
#
# @!attribute [rw] integer_parameter_range_specification
# A `IntegerParameterRangeSpecification` object that defines the
# possible values for an integer hyperparameter.
# @return [Types::IntegerParameterRangeSpecification]
#
# @!attribute [rw] continuous_parameter_range_specification
# A `ContinuousParameterRangeSpecification` object that defines the
# possible values for a continuous hyperparameter.
# @return [Types::ContinuousParameterRangeSpecification]
#
# @!attribute [rw] categorical_parameter_range_specification
# A `CategoricalParameterRangeSpecification` object that defines the
# possible values for a categorical hyperparameter.
# @return [Types::CategoricalParameterRangeSpecification]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ParameterRange AWS API Documentation
#
class ParameterRange < Struct.new(
:integer_parameter_range_specification,
:continuous_parameter_range_specification,
:categorical_parameter_range_specification)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# <note markdown="1"> The maximum number of items specified for `Array Members` refers to
# the maximum number of hyperparameters for each range and also the
# maximum for the hyperparameter tuning job itself. That is, the sum of
# the number of hyperparameters for all the ranges can't exceed the
# maximum number specified.
#
# </note>
#
# @!attribute [rw] integer_parameter_ranges
# The array of [IntegerParameterRange][1] objects that specify ranges
# of integer hyperparameters that a hyperparameter tuning job
# searches.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_IntegerParameterRange.html
# @return [Array<Types::IntegerParameterRange>]
#
# @!attribute [rw] continuous_parameter_ranges
# The array of [ContinuousParameterRange][1] objects that specify
# ranges of continuous hyperparameters that a hyperparameter tuning
# job searches.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContinuousParameterRange.html
# @return [Array<Types::ContinuousParameterRange>]
#
# @!attribute [rw] categorical_parameter_ranges
# The array of [CategoricalParameterRange][1] objects that specify
# ranges of categorical hyperparameters that a hyperparameter tuning
# job searches.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CategoricalParameterRange.html
# @return [Array<Types::CategoricalParameterRange>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ParameterRanges AWS API Documentation
#
class ParameterRanges < Struct.new(
:integer_parameter_ranges,
:continuous_parameter_ranges,
:categorical_parameter_ranges)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] trial_name
# The name of the trial.
# @return [String]
#
# @!attribute [rw] experiment_name
# The name of the experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Parent AWS API Documentation
#
class Parent < Struct.new(
:trial_name,
:experiment_name)
SENSITIVE = []
include Aws::Structure
end
# A previously completed or stopped hyperparameter tuning job to be used
# as a starting point for a new hyperparameter tuning job.
#
# @!attribute [rw] hyper_parameter_tuning_job_name
# The name of the hyperparameter tuning job to be used as a starting
# point for a new hyperparameter tuning job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ParentHyperParameterTuningJob AWS API Documentation
#
class ParentHyperParameterTuningJob < Struct.new(
:hyper_parameter_tuning_job_name)
SENSITIVE = []
include Aws::Structure
end
# The summary of an in-progress deployment when an endpoint is creating
# or updating with a new endpoint configuration.
#
# @!attribute [rw] endpoint_config_name
# The name of the endpoint configuration used in the deployment.
# @return [String]
#
# @!attribute [rw] production_variants
# An array of [PendingProductionVariantSummary][1] objects, one for
# each model hosted behind this endpoint for the in-progress
# deployment.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_PendingProductionVariantSummary.html
# @return [Array<Types::PendingProductionVariantSummary>]
#
# @!attribute [rw] start_time
# The start time of the deployment.
# @return [Time]
#
# @!attribute [rw] shadow_production_variants
# An array of [PendingProductionVariantSummary][1] objects, one for
# each model hosted behind this endpoint in shadow mode with
# production traffic replicated from the model specified on
# `ProductionVariants` for the in-progress deployment.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_PendingProductionVariantSummary.html
# @return [Array<Types::PendingProductionVariantSummary>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PendingDeploymentSummary AWS API Documentation
#
class PendingDeploymentSummary < Struct.new(
:endpoint_config_name,
:production_variants,
:start_time,
:shadow_production_variants)
SENSITIVE = []
include Aws::Structure
end
# The production variant summary for a deployment when an endpoint is
# creating or updating with the [CreateEndpoint][1] or
# [UpdateEndpoint][2] operations. Describes the `VariantStatus `, weight
# and capacity for a production variant associated with an endpoint.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateEndpoint.html
#
# @!attribute [rw] variant_name
# The name of the variant.
# @return [String]
#
# @!attribute [rw] deployed_images
# An array of `DeployedImage` objects that specify the Amazon EC2
# Container Registry paths of the inference images deployed on
# instances of this `ProductionVariant`.
# @return [Array<Types::DeployedImage>]
#
# @!attribute [rw] current_weight
# The weight associated with the variant.
# @return [Float]
#
# @!attribute [rw] desired_weight
# The requested weight for the variant in this deployment, as
# specified in the endpoint configuration for the endpoint. The value
# is taken from the request to the [CreateEndpointConfig][1]
# operation.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html
# @return [Float]
#
# @!attribute [rw] current_instance_count
# The number of instances associated with the variant.
# @return [Integer]
#
# @!attribute [rw] desired_instance_count
# The number of instances requested in this deployment, as specified
# in the endpoint configuration for the endpoint. The value is taken
# from the request to the [CreateEndpointConfig][1] operation.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html
# @return [Integer]
#
# @!attribute [rw] instance_type
# The type of instances associated with the variant.
# @return [String]
#
# @!attribute [rw] accelerator_type
# The size of the Elastic Inference (EI) instance to use for the
# production variant. EI instances provide on-demand GPU computing for
# inference. For more information, see [Using Elastic Inference in
# Amazon SageMaker][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
# @return [String]
#
# @!attribute [rw] variant_status
# The endpoint variant status which describes the current deployment
# stage status or operational status.
# @return [Array<Types::ProductionVariantStatus>]
#
# @!attribute [rw] current_serverless_config
# The serverless configuration for the endpoint.
# @return [Types::ProductionVariantServerlessConfig]
#
# @!attribute [rw] desired_serverless_config
# The serverless configuration requested for this deployment, as
# specified in the endpoint configuration for the endpoint.
# @return [Types::ProductionVariantServerlessConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PendingProductionVariantSummary AWS API Documentation
#
class PendingProductionVariantSummary < Struct.new(
:variant_name,
:deployed_images,
:current_weight,
:desired_weight,
:current_instance_count,
:desired_instance_count,
:instance_type,
:accelerator_type,
:variant_status,
:current_serverless_config,
:desired_serverless_config)
SENSITIVE = []
include Aws::Structure
end
# Defines the traffic pattern.
#
# @!attribute [rw] initial_number_of_users
# Specifies how many concurrent users to start with.
# @return [Integer]
#
# @!attribute [rw] spawn_rate
# Specified how many new users to spawn in a minute.
# @return [Integer]
#
# @!attribute [rw] duration_in_seconds
# Specifies how long traffic phase should be.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Phase AWS API Documentation
#
class Phase < Struct.new(
:initial_number_of_users,
:spawn_rate,
:duration_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# A SageMaker Model Building Pipeline instance.
#
# @!attribute [rw] pipeline_arn
# The Amazon Resource Name (ARN) of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_name
# The name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_display_name
# The display name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_description
# The description of the pipeline.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the role that created the
# pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_status
# The status of the pipeline.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of the pipeline.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time that the pipeline was last modified.
# @return [Time]
#
# @!attribute [rw] last_run_time
# The time when the pipeline was last run.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] parallelism_configuration
# The parallelism configuration applied to the pipeline.
# @return [Types::ParallelismConfiguration]
#
# @!attribute [rw] tags
# A list of tags that apply to the pipeline.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Pipeline AWS API Documentation
#
class Pipeline < Struct.new(
:pipeline_arn,
:pipeline_name,
:pipeline_display_name,
:pipeline_description,
:role_arn,
:pipeline_status,
:creation_time,
:last_modified_time,
:last_run_time,
:created_by,
:last_modified_by,
:parallelism_configuration,
:tags)
SENSITIVE = []
include Aws::Structure
end
# The location of the pipeline definition stored in Amazon S3.
#
# @!attribute [rw] bucket
# Name of the S3 bucket.
# @return [String]
#
# @!attribute [rw] object_key
# The object key (or key name) uniquely identifies the object in an S3
# bucket.
# @return [String]
#
# @!attribute [rw] version_id
# Version Id of the pipeline definition file. If not specified, Amazon
# SageMaker will retrieve the latest version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineDefinitionS3Location AWS API Documentation
#
class PipelineDefinitionS3Location < Struct.new(
:bucket,
:object_key,
:version_id)
SENSITIVE = []
include Aws::Structure
end
# An execution of a pipeline.
#
# @!attribute [rw] pipeline_arn
# The Amazon Resource Name (ARN) of the pipeline that was executed.
# @return [String]
#
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_display_name
# The display name of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_status
# The status of the pipeline status.
# @return [String]
#
# @!attribute [rw] pipeline_execution_description
# The description of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_experiment_config
# Specifies the names of the experiment and trial created by a
# pipeline.
# @return [Types::PipelineExperimentConfig]
#
# @!attribute [rw] failure_reason
# If the execution failed, a message describing why.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of the pipeline execution.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time that the pipeline execution was last modified.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] parallelism_configuration
# The parallelism configuration applied to the pipeline execution.
# @return [Types::ParallelismConfiguration]
#
# @!attribute [rw] pipeline_parameters
# Contains a list of pipeline parameters. This list can be empty.
# @return [Array<Types::Parameter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineExecution AWS API Documentation
#
class PipelineExecution < Struct.new(
:pipeline_arn,
:pipeline_execution_arn,
:pipeline_execution_display_name,
:pipeline_execution_status,
:pipeline_execution_description,
:pipeline_experiment_config,
:failure_reason,
:creation_time,
:last_modified_time,
:created_by,
:last_modified_by,
:parallelism_configuration,
:pipeline_parameters)
SENSITIVE = []
include Aws::Structure
end
# An execution of a step in a pipeline.
#
# @!attribute [rw] step_name
# The name of the step that is executed.
# @return [String]
#
# @!attribute [rw] step_display_name
# The display name of the step.
# @return [String]
#
# @!attribute [rw] step_description
# The description of the step.
# @return [String]
#
# @!attribute [rw] start_time
# The time that the step started executing.
# @return [Time]
#
# @!attribute [rw] end_time
# The time that the step stopped executing.
# @return [Time]
#
# @!attribute [rw] step_status
# The status of the step execution.
# @return [String]
#
# @!attribute [rw] cache_hit_result
# If this pipeline execution step was cached, details on the cache
# hit.
# @return [Types::CacheHitResult]
#
# @!attribute [rw] attempt_count
# The current attempt of the execution step. For more information, see
# [Retry Policy for SageMaker Pipelines steps][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-retry-policy.html
# @return [Integer]
#
# @!attribute [rw] failure_reason
# The reason why the step failed execution. This is only returned if
# the step failed its execution.
# @return [String]
#
# @!attribute [rw] metadata
# Metadata to run the pipeline step.
# @return [Types::PipelineExecutionStepMetadata]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineExecutionStep AWS API Documentation
#
class PipelineExecutionStep < Struct.new(
:step_name,
:step_display_name,
:step_description,
:start_time,
:end_time,
:step_status,
:cache_hit_result,
:attempt_count,
:failure_reason,
:metadata)
SENSITIVE = []
include Aws::Structure
end
# Metadata for a step execution.
#
# @!attribute [rw] training_job
# The Amazon Resource Name (ARN) of the training job that was run by
# this step execution.
# @return [Types::TrainingJobStepMetadata]
#
# @!attribute [rw] processing_job
# The Amazon Resource Name (ARN) of the processing job that was run by
# this step execution.
# @return [Types::ProcessingJobStepMetadata]
#
# @!attribute [rw] transform_job
# The Amazon Resource Name (ARN) of the transform job that was run by
# this step execution.
# @return [Types::TransformJobStepMetadata]
#
# @!attribute [rw] tuning_job
# The Amazon Resource Name (ARN) of the tuning job that was run by
# this step execution.
# @return [Types::TuningJobStepMetaData]
#
# @!attribute [rw] model
# The Amazon Resource Name (ARN) of the model that was created by this
# step execution.
# @return [Types::ModelStepMetadata]
#
# @!attribute [rw] register_model
# The Amazon Resource Name (ARN) of the model package that the model
# was registered to by this step execution.
# @return [Types::RegisterModelStepMetadata]
#
# @!attribute [rw] condition
# The outcome of the condition evaluation that was run by this step
# execution.
# @return [Types::ConditionStepMetadata]
#
# @!attribute [rw] callback
# The URL of the Amazon SQS queue used by this step execution, the
# pipeline generated token, and a list of output parameters.
# @return [Types::CallbackStepMetadata]
#
# @!attribute [rw] lambda
# The Amazon Resource Name (ARN) of the Lambda function that was run
# by this step execution and a list of output parameters.
# @return [Types::LambdaStepMetadata]
#
# @!attribute [rw] quality_check
# The configurations and outcomes of the check step execution. This
# includes:
#
# * The type of the check conducted.
#
# * The Amazon S3 URIs of baseline constraints and statistics files to
# be used for the drift check.
#
# * The Amazon S3 URIs of newly calculated baseline constraints and
# statistics.
#
# * The model package group name provided.
#
# * The Amazon S3 URI of the violation report if violations detected.
#
# * The Amazon Resource Name (ARN) of check processing job initiated
# by the step execution.
#
# * The Boolean flags indicating if the drift check is skipped.
#
# * If step property `BaselineUsedForDriftCheck` is set the same as
# `CalculatedBaseline`.
# @return [Types::QualityCheckStepMetadata]
#
# @!attribute [rw] clarify_check
# Container for the metadata for a Clarify check step. The
# configurations and outcomes of the check step execution. This
# includes:
#
# * The type of the check conducted,
#
# * The Amazon S3 URIs of baseline constraints and statistics files to
# be used for the drift check.
#
# * The Amazon S3 URIs of newly calculated baseline constraints and
# statistics.
#
# * The model package group name provided.
#
# * The Amazon S3 URI of the violation report if violations detected.
#
# * The Amazon Resource Name (ARN) of check processing job initiated
# by the step execution.
#
# * The boolean flags indicating if the drift check is skipped.
#
# * If step property `BaselineUsedForDriftCheck` is set the same as
# `CalculatedBaseline`.
# @return [Types::ClarifyCheckStepMetadata]
#
# @!attribute [rw] emr
# The configurations and outcomes of an Amazon EMR step execution.
# @return [Types::EMRStepMetadata]
#
# @!attribute [rw] fail
# The configurations and outcomes of a Fail step execution.
# @return [Types::FailStepMetadata]
#
# @!attribute [rw] auto_ml_job
# The Amazon Resource Name (ARN) of the AutoML job that was run by
# this step.
# @return [Types::AutoMLJobStepMetadata]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineExecutionStepMetadata AWS API Documentation
#
class PipelineExecutionStepMetadata < Struct.new(
:training_job,
:processing_job,
:transform_job,
:tuning_job,
:model,
:register_model,
:condition,
:callback,
:lambda,
:quality_check,
:clarify_check,
:emr,
:fail,
:auto_ml_job)
SENSITIVE = []
include Aws::Structure
end
# A pipeline execution summary.
#
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @!attribute [rw] start_time
# The start time of the pipeline execution.
# @return [Time]
#
# @!attribute [rw] pipeline_execution_status
# The status of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_description
# The description of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_display_name
# The display name of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_failure_reason
# A message generated by SageMaker Pipelines describing why the
# pipeline execution failed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineExecutionSummary AWS API Documentation
#
class PipelineExecutionSummary < Struct.new(
:pipeline_execution_arn,
:start_time,
:pipeline_execution_status,
:pipeline_execution_description,
:pipeline_execution_display_name,
:pipeline_execution_failure_reason)
SENSITIVE = []
include Aws::Structure
end
# Specifies the names of the experiment and trial created by a pipeline.
#
# @!attribute [rw] experiment_name
# The name of the experiment.
# @return [String]
#
# @!attribute [rw] trial_name
# The name of the trial.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineExperimentConfig AWS API Documentation
#
class PipelineExperimentConfig < Struct.new(
:experiment_name,
:trial_name)
SENSITIVE = []
include Aws::Structure
end
# A summary of a pipeline.
#
# @!attribute [rw] pipeline_arn
# The Amazon Resource Name (ARN) of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_name
# The name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_display_name
# The display name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_description
# The description of the pipeline.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) that the pipeline used to execute.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of the pipeline.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time that the pipeline was last modified.
# @return [Time]
#
# @!attribute [rw] last_execution_time
# The last time that a pipeline execution began.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineSummary AWS API Documentation
#
class PipelineSummary < Struct.new(
:pipeline_arn,
:pipeline_name,
:pipeline_display_name,
:pipeline_description,
:role_arn,
:creation_time,
:last_modified_time,
:last_execution_time)
SENSITIVE = []
include Aws::Structure
end
# Configuration for the cluster used to run a processing job.
#
# @!attribute [rw] instance_count
# The number of ML compute instances to use in the processing job. For
# distributed processing jobs, specify a value greater than 1. The
# default value is 1.
# @return [Integer]
#
# @!attribute [rw] instance_type
# The ML compute instance type for the processing job.
# @return [String]
#
# @!attribute [rw] volume_size_in_gb
# The size of the ML storage volume in gigabytes that you want to
# provision. You must specify sufficient ML storage for your scenario.
#
# <note markdown="1"> Certain Nitro-based instances include local storage with a fixed
# total size, dependent on the instance type. When using these
# instances for processing, Amazon SageMaker mounts the local instance
# storage instead of Amazon EBS gp2 storage. You can't request a
# `VolumeSizeInGB` greater than the total size of the local instance
# storage.
#
# For a list of instance types that support local instance storage,
# including the total size per instance type, see [Instance Store
# Volumes][1].
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes
# @return [Integer]
#
# @!attribute [rw] volume_kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt data on the storage
# volume attached to the ML compute instance(s) that run the
# processing job.
#
# <note markdown="1"> Certain Nitro-based instances include local storage, dependent on
# the instance type. Local storage volumes are encrypted using a
# hardware module on the instance. You can't request a
# `VolumeKmsKeyId` when using an instance type with local storage.
#
# For a list of instance types that support local instance storage,
# see [Instance Store Volumes][1].
#
# For more information about local instance storage encryption, see
# [SSD Instance Store Volumes][2].
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes
# [2]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingClusterConfig AWS API Documentation
#
class ProcessingClusterConfig < Struct.new(
:instance_count,
:instance_type,
:volume_size_in_gb,
:volume_kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# Configuration for processing job outputs in Amazon SageMaker Feature
# Store.
#
# @!attribute [rw] feature_group_name
# The name of the Amazon SageMaker FeatureGroup to use as the
# destination for processing job output. Note that your processing
# script is responsible for putting records into your Feature Store.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingFeatureStoreOutput AWS API Documentation
#
class ProcessingFeatureStoreOutput < Struct.new(
:feature_group_name)
SENSITIVE = []
include Aws::Structure
end
# The inputs for a processing job. The processing input must specify
# exactly one of either `S3Input` or `DatasetDefinition` types.
#
# @!attribute [rw] input_name
# The name for the processing job input.
# @return [String]
#
# @!attribute [rw] app_managed
# When `True`, input operations such as data download are managed
# natively by the processing job application. When `False` (default),
# input operations are managed by Amazon SageMaker.
# @return [Boolean]
#
# @!attribute [rw] s3_input
# Configuration for downloading input data from Amazon S3 into the
# processing container.
# @return [Types::ProcessingS3Input]
#
# @!attribute [rw] dataset_definition
# Configuration for a Dataset Definition input.
# @return [Types::DatasetDefinition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingInput AWS API Documentation
#
class ProcessingInput < Struct.new(
:input_name,
:app_managed,
:s3_input,
:dataset_definition)
SENSITIVE = []
include Aws::Structure
end
# An Amazon SageMaker processing job that is used to analyze data and
# evaluate models. For more information, see [Process Data and Evaluate
# Models][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/processing-job.html
#
# @!attribute [rw] processing_inputs
# List of input configurations for the processing job.
# @return [Array<Types::ProcessingInput>]
#
# @!attribute [rw] processing_output_config
# Configuration for uploading output from the processing container.
# @return [Types::ProcessingOutputConfig]
#
# @!attribute [rw] processing_job_name
# The name of the processing job.
# @return [String]
#
# @!attribute [rw] 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.
# @return [Types::ProcessingResources]
#
# @!attribute [rw] 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.
# @return [Types::ProcessingStoppingCondition]
#
# @!attribute [rw] app_specification
# Configuration to run a processing job in a specified container
# image.
# @return [Types::AppSpecification]
#
# @!attribute [rw] environment
# Sets the environment variables in the Docker container.
# @return [Hash<String,String>]
#
# @!attribute [rw] 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.
# @return [Types::NetworkConfig]
#
# @!attribute [rw] role_arn
# The ARN of the role used to create the processing job.
# @return [String]
#
# @!attribute [rw] experiment_config
# Associates a SageMaker job as a trial component with an experiment
# and trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
# @return [Types::ExperimentConfig]
#
# @!attribute [rw] processing_job_arn
# The ARN of the processing job.
# @return [String]
#
# @!attribute [rw] processing_job_status
# The status of the processing job.
# @return [String]
#
# @!attribute [rw] exit_message
# A string, up to one KB in size, that contains metadata from the
# processing container when the processing job exits.
# @return [String]
#
# @!attribute [rw] failure_reason
# A string, up to one KB in size, that contains the reason a
# processing job failed, if it failed.
# @return [String]
#
# @!attribute [rw] processing_end_time
# The time that the processing job ended.
# @return [Time]
#
# @!attribute [rw] processing_start_time
# The time that the processing job started.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The time the processing job was last modified.
# @return [Time]
#
# @!attribute [rw] creation_time
# The time the processing job was created.
# @return [Time]
#
# @!attribute [rw] monitoring_schedule_arn
# The ARN of a monitoring schedule for an endpoint associated with
# this processing job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# The Amazon Resource Name (ARN) of the AutoML job associated with
# this processing job.
# @return [String]
#
# @!attribute [rw] training_job_arn
# The ARN of the training job associated with this processing job.
# @return [String]
#
# @!attribute [rw] tags
# An array of key-value pairs. For more information, see [Using Cost
# Allocation Tags][1] in the *Amazon Web Services Billing and Cost
# Management User Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-whatURL
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingJob AWS API Documentation
#
class ProcessingJob < Struct.new(
:processing_inputs,
:processing_output_config,
:processing_job_name,
:processing_resources,
:stopping_condition,
:app_specification,
:environment,
:network_config,
:role_arn,
:experiment_config,
:processing_job_arn,
:processing_job_status,
:exit_message,
:failure_reason,
:processing_end_time,
:processing_start_time,
:last_modified_time,
:creation_time,
:monitoring_schedule_arn,
:auto_ml_job_arn,
:training_job_arn,
:tags)
SENSITIVE = []
include Aws::Structure
end
# Metadata for a processing job step.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the processing job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingJobStepMetadata AWS API Documentation
#
class ProcessingJobStepMetadata < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# Summary of information about a processing job.
#
# @!attribute [rw] processing_job_name
# The name of the processing job.
# @return [String]
#
# @!attribute [rw] processing_job_arn
# The Amazon Resource Name (ARN) of the processing job..
# @return [String]
#
# @!attribute [rw] creation_time
# The time at which the processing job was created.
# @return [Time]
#
# @!attribute [rw] processing_end_time
# The time at which the processing job completed.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that indicates the last time the processing job was
# modified.
# @return [Time]
#
# @!attribute [rw] processing_job_status
# The status of the processing job.
# @return [String]
#
# @!attribute [rw] failure_reason
# A string, up to one KB in size, that contains the reason a
# processing job failed, if it failed.
# @return [String]
#
# @!attribute [rw] exit_message
# An optional string, up to one KB in size, that contains metadata
# from the processing container when the processing job exits.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingJobSummary AWS API Documentation
#
class ProcessingJobSummary < Struct.new(
:processing_job_name,
:processing_job_arn,
:creation_time,
:processing_end_time,
:last_modified_time,
:processing_job_status,
:failure_reason,
:exit_message)
SENSITIVE = []
include Aws::Structure
end
# Describes the results of a processing job. The processing output must
# specify exactly one of either `S3Output` or `FeatureStoreOutput`
# types.
#
# @!attribute [rw] output_name
# The name for the processing job output.
# @return [String]
#
# @!attribute [rw] s3_output
# Configuration for processing job outputs in Amazon S3.
# @return [Types::ProcessingS3Output]
#
# @!attribute [rw] feature_store_output
# Configuration for processing job outputs in Amazon SageMaker Feature
# Store. This processing output type is only supported when
# `AppManaged` is specified.
# @return [Types::ProcessingFeatureStoreOutput]
#
# @!attribute [rw] app_managed
# When `True`, output operations such as data upload are managed
# natively by the processing job application. When `False` (default),
# output operations are managed by Amazon SageMaker.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingOutput AWS API Documentation
#
class ProcessingOutput < Struct.new(
:output_name,
:s3_output,
:feature_store_output,
:app_managed)
SENSITIVE = []
include Aws::Structure
end
# Configuration for uploading output from the processing container.
#
# @!attribute [rw] outputs
# An array of outputs configuring the data to upload from the
# processing container.
# @return [Array<Types::ProcessingOutput>]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt the processing job
# output. `KmsKeyId` can be an ID of a KMS key, ARN of a KMS key,
# alias of a KMS key, or alias of a KMS key. The `KmsKeyId` is applied
# to all outputs.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingOutputConfig AWS API Documentation
#
class ProcessingOutputConfig < Struct.new(
:outputs,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] cluster_config
# The configuration for the resources in a cluster used to run the
# processing job.
# @return [Types::ProcessingClusterConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingResources AWS API Documentation
#
class ProcessingResources < Struct.new(
:cluster_config)
SENSITIVE = []
include Aws::Structure
end
# Configuration for downloading input data from Amazon S3 into the
# processing container.
#
# @!attribute [rw] s3_uri
# The URI of the Amazon S3 prefix Amazon SageMaker downloads data
# required to run a processing job.
# @return [String]
#
# @!attribute [rw] local_path
# The local path in your container where you want Amazon SageMaker to
# write input data to. `LocalPath` is an absolute path to the input
# data and must begin with `/opt/ml/processing/`. `LocalPath` is a
# required parameter when `AppManaged` is `False` (default).
# @return [String]
#
# @!attribute [rw] s3_data_type
# Whether you use an `S3Prefix` or a `ManifestFile` for the data type.
# If you choose `S3Prefix`, `S3Uri` identifies a key name prefix.
# Amazon SageMaker uses all objects with the specified key name prefix
# for the processing job. If you choose `ManifestFile`, `S3Uri`
# identifies an object that is a manifest file containing a list of
# object keys that you want Amazon SageMaker to use for the processing
# job.
# @return [String]
#
# @!attribute [rw] s3_input_mode
# Whether to use `File` or `Pipe` input mode. In File mode, Amazon
# SageMaker copies the data from the input source onto the local ML
# storage volume before starting your processing container. This is
# the most commonly used input mode. In `Pipe` mode, Amazon SageMaker
# streams input data from the source directly to your processing
# container into named pipes without using the ML storage volume.
# @return [String]
#
# @!attribute [rw] s3_data_distribution_type
# Whether to distribute the data from Amazon S3 to all processing
# instances with `FullyReplicated`, or whether the data from Amazon S3
# is shared by Amazon S3 key, downloading one shard of data to each
# processing instance.
# @return [String]
#
# @!attribute [rw] s3_compression_type
# Whether to GZIP-decompress the data in Amazon S3 as it is streamed
# into the processing container. `Gzip` can only be used when `Pipe`
# mode is specified as the `S3InputMode`. In `Pipe` mode, Amazon
# SageMaker streams input data from the source directly to your
# container without using the EBS volume.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingS3Input AWS API Documentation
#
class ProcessingS3Input < Struct.new(
:s3_uri,
:local_path,
:s3_data_type,
:s3_input_mode,
:s3_data_distribution_type,
:s3_compression_type)
SENSITIVE = []
include Aws::Structure
end
# Configuration for uploading output data to Amazon S3 from the
# processing container.
#
# @!attribute [rw] s3_uri
# A URI that identifies the Amazon S3 bucket where you want Amazon
# SageMaker to save the results of a processing job.
# @return [String]
#
# @!attribute [rw] local_path
# The local path of a directory where you want Amazon SageMaker to
# upload its contents to Amazon S3. `LocalPath` is an absolute path to
# a directory containing output files. This directory will be created
# by the platform and exist when your container's entrypoint is
# invoked.
# @return [String]
#
# @!attribute [rw] s3_upload_mode
# Whether to upload the results of the processing job continuously or
# after the job completes.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingS3Output AWS API Documentation
#
class ProcessingS3Output < Struct.new(
:s3_uri,
:local_path,
:s3_upload_mode)
SENSITIVE = []
include Aws::Structure
end
# 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.
#
# @!attribute [rw] max_runtime_in_seconds
# Specifies the maximum runtime in seconds.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProcessingStoppingCondition AWS API Documentation
#
class ProcessingStoppingCondition < Struct.new(
:max_runtime_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# Identifies a model that you want to host and the resources chosen to
# deploy for hosting it. If you are deploying multiple models, tell
# SageMaker how to distribute traffic among the models by specifying
# variant weights. For more information on production variants, check [
# Production variants][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-ab-testing.html
#
# @!attribute [rw] variant_name
# The name of the production variant.
# @return [String]
#
# @!attribute [rw] model_name
# The name of the model that you want to host. This is the name that
# you specified when creating the model.
# @return [String]
#
# @!attribute [rw] initial_instance_count
# Number of instances to launch initially.
# @return [Integer]
#
# @!attribute [rw] instance_type
# The ML compute instance type.
# @return [String]
#
# @!attribute [rw] initial_variant_weight
# Determines initial traffic distribution among all of the models that
# you specify in the endpoint configuration. The traffic to a
# production variant is determined by the ratio of the `VariantWeight`
# to the sum of all `VariantWeight` values across all
# ProductionVariants. If unspecified, it defaults to 1.0.
# @return [Float]
#
# @!attribute [rw] accelerator_type
# The size of the Elastic Inference (EI) instance to use for the
# production variant. EI instances provide on-demand GPU computing for
# inference. For more information, see [Using Elastic Inference in
# Amazon SageMaker][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
# @return [String]
#
# @!attribute [rw] core_dump_config
# Specifies configuration for a core dump from the model container
# when the process crashes.
# @return [Types::ProductionVariantCoreDumpConfig]
#
# @!attribute [rw] serverless_config
# The serverless configuration for an endpoint. Specifies a serverless
# endpoint configuration instead of an instance-based endpoint
# configuration.
# @return [Types::ProductionVariantServerlessConfig]
#
# @!attribute [rw] volume_size_in_gb
# The size, in GB, of the ML storage volume attached to individual
# inference instance associated with the production variant. Currently
# only Amazon EBS gp2 storage volumes are supported.
# @return [Integer]
#
# @!attribute [rw] model_data_download_timeout_in_seconds
# The timeout value, in seconds, to download and extract the model
# that you want to host from Amazon S3 to the individual inference
# instance associated with this production variant.
# @return [Integer]
#
# @!attribute [rw] container_startup_health_check_timeout_in_seconds
# The timeout value, in seconds, for your inference container to pass
# health check by SageMaker Hosting. For more information about health
# check, see [How Your Container Should Respond to Health Check (Ping)
# Requests][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-inference-code.html#your-algorithms-inference-algo-ping-requests
# @return [Integer]
#
# @!attribute [rw] enable_ssm_access
# You can use this parameter to turn on native Amazon Web Services
# Systems Manager (SSM) access for a production variant behind an
# endpoint. By default, SSM access is disabled for all production
# variants behind an endpoint. You can turn on or turn off SSM access
# for a production variant behind an existing endpoint by creating a
# new endpoint configuration and calling `UpdateEndpoint`.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProductionVariant AWS API Documentation
#
class ProductionVariant < Struct.new(
:variant_name,
:model_name,
:initial_instance_count,
:instance_type,
:initial_variant_weight,
:accelerator_type,
:core_dump_config,
:serverless_config,
:volume_size_in_gb,
:model_data_download_timeout_in_seconds,
:container_startup_health_check_timeout_in_seconds,
:enable_ssm_access)
SENSITIVE = []
include Aws::Structure
end
# Specifies configuration for a core dump from the model container when
# the process crashes.
#
# @!attribute [rw] destination_s3_uri
# The Amazon S3 bucket to send the core dump to.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that SageMaker uses to encrypt the core dump data at rest
# using Amazon S3 server-side encryption. The `KmsKeyId` can be any of
# the following formats:
#
# * // KMS Key ID
#
# `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * // Amazon Resource Name (ARN) of a KMS Key
#
# `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * // KMS Key Alias
#
# `"alias/ExampleAlias"`
#
# * // Amazon Resource Name (ARN) of a KMS Key Alias
#
# `"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"`
#
# If you use a KMS key ID or an alias of your KMS key, the SageMaker
# execution role must include permissions to call `kms:Encrypt`. If
# you don't provide a KMS key ID, SageMaker uses the default KMS key
# for Amazon S3 for your role's account. SageMaker uses server-side
# encryption with KMS-managed keys for `OutputDataConfig`. If you use
# a bucket policy with an `s3:PutObject` permission that only allows
# objects with server-side encryption, set the condition key of
# `s3:x-amz-server-side-encryption` to `"aws:kms"`. For more
# information, see [KMS-Managed Encryption Keys][1] in the *Amazon
# Simple Storage Service Developer Guide.*
#
# The KMS key policy must grant permission to the IAM role that you
# specify in your `CreateEndpoint` and `UpdateEndpoint` requests. For
# more information, see [Using Key Policies in Amazon Web Services
# KMS][2] in the *Amazon Web Services Key Management Service Developer
# Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html
# [2]: https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProductionVariantCoreDumpConfig AWS API Documentation
#
class ProductionVariantCoreDumpConfig < Struct.new(
:destination_s3_uri,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# Specifies the serverless configuration for an endpoint variant.
#
# @!attribute [rw] memory_size_in_mb
# The memory size of your serverless endpoint. Valid values are in 1
# GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144
# MB.
# @return [Integer]
#
# @!attribute [rw] max_concurrency
# The maximum number of concurrent invocations your serverless
# endpoint can process.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProductionVariantServerlessConfig AWS API Documentation
#
class ProductionVariantServerlessConfig < Struct.new(
:memory_size_in_mb,
:max_concurrency)
SENSITIVE = []
include Aws::Structure
end
# Describes the status of the production variant.
#
# @!attribute [rw] status
# The endpoint variant status which describes the current deployment
# stage status or operational status.
#
# * `Creating`: Creating inference resources for the production
# variant.
#
# * `Deleting`: Terminating inference resources for the production
# variant.
#
# * `Updating`: Updating capacity for the production variant.
#
# * `ActivatingTraffic`: Turning on traffic for the production
# variant.
#
# * `Baking`: Waiting period to monitor the CloudWatch alarms in the
# automatic rollback configuration.
# @return [String]
#
# @!attribute [rw] status_message
# A message that describes the status of the production variant.
# @return [String]
#
# @!attribute [rw] start_time
# The start time of the current status change.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProductionVariantStatus AWS API Documentation
#
class ProductionVariantStatus < Struct.new(
:status,
:status_message,
:start_time)
SENSITIVE = []
include Aws::Structure
end
# Describes weight and capacities for a production variant associated
# with an endpoint. If you sent a request to the
# `UpdateEndpointWeightsAndCapacities` API and the endpoint status is
# `Updating`, you get different desired and current values.
#
# @!attribute [rw] variant_name
# The name of the variant.
# @return [String]
#
# @!attribute [rw] deployed_images
# An array of `DeployedImage` objects that specify the Amazon EC2
# Container Registry paths of the inference images deployed on
# instances of this `ProductionVariant`.
# @return [Array<Types::DeployedImage>]
#
# @!attribute [rw] current_weight
# The weight associated with the variant.
# @return [Float]
#
# @!attribute [rw] desired_weight
# The requested weight, as specified in the
# `UpdateEndpointWeightsAndCapacities` request.
# @return [Float]
#
# @!attribute [rw] current_instance_count
# The number of instances associated with the variant.
# @return [Integer]
#
# @!attribute [rw] desired_instance_count
# The number of instances requested in the
# `UpdateEndpointWeightsAndCapacities` request.
# @return [Integer]
#
# @!attribute [rw] variant_status
# The endpoint variant status which describes the current deployment
# stage status or operational status.
# @return [Array<Types::ProductionVariantStatus>]
#
# @!attribute [rw] current_serverless_config
# The serverless configuration for the endpoint.
# @return [Types::ProductionVariantServerlessConfig]
#
# @!attribute [rw] desired_serverless_config
# The serverless configuration requested for the endpoint update.
# @return [Types::ProductionVariantServerlessConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProductionVariantSummary AWS API Documentation
#
class ProductionVariantSummary < Struct.new(
:variant_name,
:deployed_images,
:current_weight,
:desired_weight,
:current_instance_count,
:desired_instance_count,
:variant_status,
:current_serverless_config,
:desired_serverless_config)
SENSITIVE = []
include Aws::Structure
end
# Configuration information for Amazon SageMaker Debugger system
# monitoring, framework profiling, and storage paths.
#
# @!attribute [rw] s3_output_path
# Path to Amazon S3 storage location for system and framework metrics.
# @return [String]
#
# @!attribute [rw] profiling_interval_in_milliseconds
# A time interval for capturing system metrics in milliseconds.
# Available values are 100, 200, 500, 1000 (1 second), 5000 (5
# seconds), and 60000 (1 minute) milliseconds. The default value is
# 500 milliseconds.
# @return [Integer]
#
# @!attribute [rw] profiling_parameters
# Configuration information for capturing framework metrics. Available
# key strings for different profiling options are
# `DetailedProfilingConfig`, `PythonProfilingConfig`, and
# `DataLoaderProfilingConfig`. The following codes are configuration
# structures for the `ProfilingParameters` parameter. To learn more
# about how to configure the `ProfilingParameters` parameter, see [Use
# the SageMaker and Debugger Configuration API Operations to Create,
# Update, and Debug Your Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html
# @return [Hash<String,String>]
#
# @!attribute [rw] disable_profiler
# Configuration to turn off Amazon SageMaker Debugger's system
# monitoring and profiling functionality. To turn it off, set to
# `True`.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProfilerConfig AWS API Documentation
#
class ProfilerConfig < Struct.new(
:s3_output_path,
:profiling_interval_in_milliseconds,
:profiling_parameters,
:disable_profiler)
SENSITIVE = []
include Aws::Structure
end
# Configuration information for updating the Amazon SageMaker Debugger
# profile parameters, system and framework metrics configurations, and
# storage paths.
#
# @!attribute [rw] s3_output_path
# Path to Amazon S3 storage location for system and framework metrics.
# @return [String]
#
# @!attribute [rw] profiling_interval_in_milliseconds
# A time interval for capturing system metrics in milliseconds.
# Available values are 100, 200, 500, 1000 (1 second), 5000 (5
# seconds), and 60000 (1 minute) milliseconds. The default value is
# 500 milliseconds.
# @return [Integer]
#
# @!attribute [rw] profiling_parameters
# Configuration information for capturing framework metrics. Available
# key strings for different profiling options are
# `DetailedProfilingConfig`, `PythonProfilingConfig`, and
# `DataLoaderProfilingConfig`. The following codes are configuration
# structures for the `ProfilingParameters` parameter. To learn more
# about how to configure the `ProfilingParameters` parameter, see [Use
# the SageMaker and Debugger Configuration API Operations to Create,
# Update, and Debug Your Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html
# @return [Hash<String,String>]
#
# @!attribute [rw] disable_profiler
# To turn off Amazon SageMaker Debugger monitoring and profiling while
# a training job is in progress, set to `True`.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProfilerConfigForUpdate AWS API Documentation
#
class ProfilerConfigForUpdate < Struct.new(
:s3_output_path,
:profiling_interval_in_milliseconds,
:profiling_parameters,
:disable_profiler)
SENSITIVE = []
include Aws::Structure
end
# Configuration information for profiling rules.
#
# @!attribute [rw] rule_configuration_name
# The name of the rule configuration. It must be unique relative to
# other rule configuration names.
# @return [String]
#
# @!attribute [rw] local_path
# Path to local storage location for output of rules. Defaults to
# `/opt/ml/processing/output/rule/`.
# @return [String]
#
# @!attribute [rw] s3_output_path
# Path to Amazon S3 storage location for rules.
# @return [String]
#
# @!attribute [rw] rule_evaluator_image
# The Amazon Elastic Container Registry Image for the managed rule
# evaluation.
# @return [String]
#
# @!attribute [rw] instance_type
# The instance type to deploy a custom rule for profiling a training
# job.
# @return [String]
#
# @!attribute [rw] volume_size_in_gb
# The size, in GB, of the ML storage volume attached to the processing
# instance.
# @return [Integer]
#
# @!attribute [rw] rule_parameters
# Runtime configuration for rule container.
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProfilerRuleConfiguration AWS API Documentation
#
class ProfilerRuleConfiguration < Struct.new(
:rule_configuration_name,
:local_path,
:s3_output_path,
:rule_evaluator_image,
:instance_type,
:volume_size_in_gb,
:rule_parameters)
SENSITIVE = []
include Aws::Structure
end
# Information about the status of the rule evaluation.
#
# @!attribute [rw] rule_configuration_name
# The name of the rule configuration.
# @return [String]
#
# @!attribute [rw] rule_evaluation_job_arn
# The Amazon Resource Name (ARN) of the rule evaluation job.
# @return [String]
#
# @!attribute [rw] rule_evaluation_status
# Status of the rule evaluation.
# @return [String]
#
# @!attribute [rw] status_details
# Details from the rule evaluation.
# @return [String]
#
# @!attribute [rw] last_modified_time
# Timestamp when the rule evaluation status was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProfilerRuleEvaluationStatus AWS API Documentation
#
class ProfilerRuleEvaluationStatus < Struct.new(
:rule_configuration_name,
:rule_evaluation_job_arn,
:rule_evaluation_status,
:status_details,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# The properties of a project as returned by the Search API.
#
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project.
# @return [String]
#
# @!attribute [rw] project_name
# The name of the project.
# @return [String]
#
# @!attribute [rw] project_id
# The ID of the project.
# @return [String]
#
# @!attribute [rw] project_description
# The description of the project.
# @return [String]
#
# @!attribute [rw] service_catalog_provisioning_details
# Details that you specify to provision a service catalog product. For
# information about service catalog, see [What is Amazon Web Services
# Service Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
# @return [Types::ServiceCatalogProvisioningDetails]
#
# @!attribute [rw] service_catalog_provisioned_product_details
# Details of a provisioned service catalog product. For information
# about service catalog, see [What is Amazon Web Services Service
# Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
# @return [Types::ServiceCatalogProvisionedProductDetails]
#
# @!attribute [rw] project_status
# The status of the project.
# @return [String]
#
# @!attribute [rw] created_by
# Who created the project.
# @return [Types::UserContext]
#
# @!attribute [rw] creation_time
# A timestamp specifying when the project was created.
# @return [Time]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] last_modified_time
# A timestamp container for when the project was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Project AWS API Documentation
#
class Project < Struct.new(
:project_arn,
:project_name,
:project_id,
:project_description,
:service_catalog_provisioning_details,
:service_catalog_provisioned_product_details,
:project_status,
:created_by,
:creation_time,
:tags,
:last_modified_time,
:last_modified_by)
SENSITIVE = []
include Aws::Structure
end
# Information about a project.
#
# @!attribute [rw] project_name
# The name of the project.
# @return [String]
#
# @!attribute [rw] project_description
# The description of the project.
# @return [String]
#
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project.
# @return [String]
#
# @!attribute [rw] project_id
# The ID of the project.
# @return [String]
#
# @!attribute [rw] creation_time
# The time that the project was created.
# @return [Time]
#
# @!attribute [rw] project_status
# The status of the project.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProjectSummary AWS API Documentation
#
class ProjectSummary < Struct.new(
:project_name,
:project_description,
:project_arn,
:project_id,
:creation_time,
:project_status)
SENSITIVE = []
include Aws::Structure
end
# Part of the `SuggestionQuery` type. Specifies a hint for retrieving
# property names that begin with the specified text.
#
# @!attribute [rw] property_name_hint
# Text that begins a property's name.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PropertyNameQuery AWS API Documentation
#
class PropertyNameQuery < Struct.new(
:property_name_hint)
SENSITIVE = []
include Aws::Structure
end
# A property name returned from a `GetSearchSuggestions` call that
# specifies a value in the `PropertyNameQuery` field.
#
# @!attribute [rw] property_name
# A suggested property name based on what you entered in the search
# textbox in the SageMaker console.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PropertyNameSuggestion AWS API Documentation
#
class PropertyNameSuggestion < Struct.new(
:property_name)
SENSITIVE = []
include Aws::Structure
end
# A key value pair used when you provision a project as a service
# catalog product. For information, see [What is Amazon Web Services
# Service Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
#
# @!attribute [rw] key
# The key that identifies a provisioning parameter.
# @return [String]
#
# @!attribute [rw] value
# The value of the provisioning parameter.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProvisioningParameter AWS API Documentation
#
class ProvisioningParameter < Struct.new(
:key,
:value)
SENSITIVE = []
include Aws::Structure
end
# 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
#
# @!attribute [rw] amount_in_usd
# Defines the amount of money paid to an Amazon Mechanical Turk worker
# in United States dollars.
# @return [Types::USD]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PublicWorkforceTaskPrice AWS API Documentation
#
class PublicWorkforceTaskPrice < Struct.new(
:amount_in_usd)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_name
# The name of the model group to add a resource policy to.
# @return [String]
#
# @!attribute [rw] resource_policy
# The resource policy for the model group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PutModelPackageGroupPolicyInput AWS API Documentation
#
class PutModelPackageGroupPolicyInput < Struct.new(
:model_package_group_name,
:resource_policy)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_group_arn
# The Amazon Resource Name (ARN) of the model package group.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PutModelPackageGroupPolicyOutput AWS API Documentation
#
class PutModelPackageGroupPolicyOutput < Struct.new(
:model_package_group_arn)
SENSITIVE = []
include Aws::Structure
end
# Container for the metadata for a Quality check step. For more
# information, see the topic on [QualityCheck step][1] in the *Amazon
# SageMaker Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/build-and-manage-steps.html#step-type-quality-check
#
# @!attribute [rw] check_type
# The type of the Quality check step.
# @return [String]
#
# @!attribute [rw] baseline_used_for_drift_check_statistics
# The Amazon S3 URI of the baseline statistics file used for the drift
# check.
# @return [String]
#
# @!attribute [rw] baseline_used_for_drift_check_constraints
# The Amazon S3 URI of the baseline constraints file used for the
# drift check.
# @return [String]
#
# @!attribute [rw] calculated_baseline_statistics
# The Amazon S3 URI of the newly calculated baseline statistics file.
# @return [String]
#
# @!attribute [rw] calculated_baseline_constraints
# The Amazon S3 URI of the newly calculated baseline constraints file.
# @return [String]
#
# @!attribute [rw] model_package_group_name
# The model package group name.
# @return [String]
#
# @!attribute [rw] violation_report
# The Amazon S3 URI of violation report if violations are detected.
# @return [String]
#
# @!attribute [rw] check_job_arn
# The Amazon Resource Name (ARN) of the Quality check processing job
# that was run by this step execution.
# @return [String]
#
# @!attribute [rw] skip_check
# This flag indicates if the drift check against the previous baseline
# will be skipped or not. If it is set to `False`, the previous
# baseline of the configured check type must be available.
# @return [Boolean]
#
# @!attribute [rw] register_new_baseline
# This flag indicates if a newly calculated baseline can be accessed
# through step properties `BaselineUsedForDriftCheckConstraints` and
# `BaselineUsedForDriftCheckStatistics`. If it is set to `False`, the
# previous baseline of the configured check type must also be
# available. These can be accessed through the
# `BaselineUsedForDriftCheckConstraints` and `
# BaselineUsedForDriftCheckStatistics` properties.
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/QualityCheckStepMetadata AWS API Documentation
#
class QualityCheckStepMetadata < Struct.new(
:check_type,
:baseline_used_for_drift_check_statistics,
:baseline_used_for_drift_check_constraints,
:calculated_baseline_statistics,
:calculated_baseline_constraints,
:model_package_group_name,
:violation_report,
:check_job_arn,
:skip_check,
:register_new_baseline)
SENSITIVE = []
include Aws::Structure
end
# A set of filters to narrow the set of lineage entities connected to
# the `StartArn`(s) returned by the `QueryLineage` API action.
#
# @!attribute [rw] types
# Filter the lineage entities connected to the `StartArn` by type. For
# example: `DataSet`, `Model`, `Endpoint`, or `ModelDeployment`.
# @return [Array<String>]
#
# @!attribute [rw] lineage_types
# Filter the lineage entities connected to the `StartArn`(s) by the
# type of the lineage entity.
# @return [Array<String>]
#
# @!attribute [rw] created_before
# Filter the lineage entities connected to the `StartArn`(s) by
# created date.
# @return [Time]
#
# @!attribute [rw] created_after
# Filter the lineage entities connected to the `StartArn`(s) after the
# create date.
# @return [Time]
#
# @!attribute [rw] modified_before
# Filter the lineage entities connected to the `StartArn`(s) before
# the last modified date.
# @return [Time]
#
# @!attribute [rw] modified_after
# Filter the lineage entities connected to the `StartArn`(s) after the
# last modified date.
# @return [Time]
#
# @!attribute [rw] properties
# Filter the lineage entities connected to the `StartArn`(s) by a set
# if property key value pairs. If multiple pairs are provided, an
# entity is included in the results if it matches any of the provided
# pairs.
# @return [Hash<String,String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/QueryFilters AWS API Documentation
#
class QueryFilters < Struct.new(
:types,
:lineage_types,
:created_before,
:created_after,
:modified_before,
:modified_after,
:properties)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] start_arns
# A list of resource Amazon Resource Name (ARN) that represent the
# starting point for your lineage query.
# @return [Array<String>]
#
# @!attribute [rw] direction
# Associations between lineage entities have a direction. This
# parameter determines the direction from the StartArn(s) that the
# query traverses.
# @return [String]
#
# @!attribute [rw] include_edges
# Setting this value to `True` retrieves not only the entities of
# interest but also the [Associations][1] and lineage entities on the
# path. Set to `False` to only return lineage entities that match your
# query.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/lineage-tracking-entities.html
# @return [Boolean]
#
# @!attribute [rw] filters
# A set of filtering parameters that allow you to specify which
# entities should be returned.
#
# * Properties - Key-value pairs to match on the lineage entities'
# properties.
#
# * LineageTypes - A set of lineage entity types to match on. For
# example: `TrialComponent`, `Artifact`, or `Context`.
#
# * CreatedBefore - Filter entities created before this date.
#
# * ModifiedBefore - Filter entities modified before this date.
#
# * ModifiedAfter - Filter entities modified after this date.
# @return [Types::QueryFilters]
#
# @!attribute [rw] max_depth
# The maximum depth in lineage relationships from the `StartArns` that
# are traversed. Depth is a measure of the number of `Associations`
# from the `StartArn` entity to the matched results.
# @return [Integer]
#
# @!attribute [rw] max_results
# Limits the number of vertices in the results. Use the `NextToken` in
# a response to to retrieve the next page of results.
# @return [Integer]
#
# @!attribute [rw] next_token
# Limits the number of vertices in the request. Use the `NextToken` in
# a response to to retrieve the next page of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/QueryLineageRequest AWS API Documentation
#
class QueryLineageRequest < Struct.new(
:start_arns,
:direction,
:include_edges,
:filters,
:max_depth,
:max_results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] vertices
# A list of vertices connected to the start entity(ies) in the lineage
# graph.
# @return [Array<Types::Vertex>]
#
# @!attribute [rw] edges
# A list of edges that connect vertices in the response.
# @return [Array<Types::Edge>]
#
# @!attribute [rw] next_token
# Limits the number of vertices in the response. Use the `NextToken`
# in a response to to retrieve the next page of results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/QueryLineageResponse AWS API Documentation
#
class QueryLineageResponse < Struct.new(
:vertices,
:edges,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings that apply to an `RSessionGateway` app.
#
# @!attribute [rw] default_resource_spec
# Specifies the ARN's of a SageMaker image and SageMaker image
# version, and the instance type that the version runs on.
# @return [Types::ResourceSpec]
#
# @!attribute [rw] custom_images
# A list of custom SageMaker images that are configured to run as a
# RSession app.
# @return [Array<Types::CustomImage>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RSessionAppSettings AWS API Documentation
#
class RSessionAppSettings < Struct.new(
:default_resource_spec,
:custom_images)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings that configure user interaction with the
# `RStudioServerPro` app. `RStudioServerProAppSettings` cannot be
# updated. The `RStudioServerPro` app must be deleted and a new one
# created to make any changes.
#
# @!attribute [rw] access_status
# Indicates whether the current user has access to the
# `RStudioServerPro` app.
# @return [String]
#
# @!attribute [rw] user_group
# The level of permissions that the user has within the
# `RStudioServerPro` app. This value defaults to `User`. The
# `Admin` value allows the user access to the RStudio Administrative
# Dashboard.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RStudioServerProAppSettings AWS API Documentation
#
class RStudioServerProAppSettings < Struct.new(
:access_status,
:user_group)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings that configure the `RStudioServerPro`
# Domain-level app.
#
# @!attribute [rw] domain_execution_role_arn
# The ARN of the execution role for the `RStudioServerPro`
# Domain-level app.
# @return [String]
#
# @!attribute [rw] r_studio_connect_url
# A URL pointing to an RStudio Connect server.
# @return [String]
#
# @!attribute [rw] r_studio_package_manager_url
# A URL pointing to an RStudio Package Manager server.
# @return [String]
#
# @!attribute [rw] default_resource_spec
# Specifies the ARN's of a SageMaker image and SageMaker image
# version, and the instance type that the version runs on.
# @return [Types::ResourceSpec]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RStudioServerProDomainSettings AWS API Documentation
#
class RStudioServerProDomainSettings < Struct.new(
:domain_execution_role_arn,
:r_studio_connect_url,
:r_studio_package_manager_url,
:default_resource_spec)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings that update the current configuration for the
# `RStudioServerPro` Domain-level app.
#
# @!attribute [rw] domain_execution_role_arn
# The execution role for the `RStudioServerPro` Domain-level app.
# @return [String]
#
# @!attribute [rw] default_resource_spec
# Specifies the ARN's of a SageMaker image and SageMaker image
# version, and the instance type that the version runs on.
# @return [Types::ResourceSpec]
#
# @!attribute [rw] r_studio_connect_url
# A URL pointing to an RStudio Connect server.
# @return [String]
#
# @!attribute [rw] r_studio_package_manager_url
# A URL pointing to an RStudio Package Manager server.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RStudioServerProDomainSettingsForUpdate AWS API Documentation
#
class RStudioServerProDomainSettingsForUpdate < Struct.new(
:domain_execution_role_arn,
:default_resource_spec,
:r_studio_connect_url,
:r_studio_package_manager_url)
SENSITIVE = []
include Aws::Structure
end
# The infrastructure configuration for deploying the model to a
# real-time inference endpoint.
#
# @!attribute [rw] instance_type
# The instance type the model is deployed to.
# @return [String]
#
# @!attribute [rw] instance_count
# The number of instances of the type specified by `InstanceType`.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RealTimeInferenceConfig AWS API Documentation
#
class RealTimeInferenceConfig < Struct.new(
:instance_type,
:instance_count)
SENSITIVE = []
include Aws::Structure
end
# Provides information about the output configuration for the compiled
# model.
#
# @!attribute [rw] s3_output_uri
# Identifies the Amazon S3 bucket where you want SageMaker to store
# the compiled model artifacts.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobCompiledOutputConfig AWS API Documentation
#
class RecommendationJobCompiledOutputConfig < Struct.new(
:s3_output_uri)
SENSITIVE = []
include Aws::Structure
end
# Specifies mandatory fields for running an Inference Recommender job
# directly in the [CreateInferenceRecommendationsJob][1] API. The fields
# specified in `ContainerConfig` override the corresponding fields in
# the model package. Use `ContainerConfig` if you want to specify these
# fields for the recommendation job but don't want to edit them in your
# model package.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceRecommendationsJob.html
#
# @!attribute [rw] domain
# The machine learning domain of the model and its components.
#
# Valid Values: `COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING |
# MACHINE_LEARNING`
# @return [String]
#
# @!attribute [rw] task
# The machine learning task that the model accomplishes.
#
# Valid Values: `IMAGE_CLASSIFICATION | OBJECT_DETECTION |
# TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION |
# REGRESSION | OTHER`
# @return [String]
#
# @!attribute [rw] framework
# The machine learning framework of the container image.
#
# Valid Values: `TENSORFLOW | PYTORCH | XGBOOST |
# SAGEMAKER-SCIKIT-LEARN`
# @return [String]
#
# @!attribute [rw] framework_version
# The framework version of the container image.
# @return [String]
#
# @!attribute [rw] payload_config
# Specifies the `SamplePayloadUrl` and all other sample
# payload-related fields.
# @return [Types::RecommendationJobPayloadConfig]
#
# @!attribute [rw] nearest_model_name
# The name of a pre-trained machine learning model benchmarked by
# Amazon SageMaker Inference Recommender that matches your model.
#
# Valid Values: `efficientnetb7 | unet | xgboost |
# faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 |
# mask-rcnn | sagemaker-scikit-learn | densenet201-gluon |
# resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 |
# bert-base-cased | xceptionV1-keras | resnet50 | retinanet`
# @return [String]
#
# @!attribute [rw] supported_instance_types
# A list of the instance types that are used to generate inferences in
# real-time.
# @return [Array<String>]
#
# @!attribute [rw] data_input_config
# Specifies the name and shape of the expected data inputs for your
# trained model with a JSON dictionary form. This field is used for
# optimizing your model using SageMaker Neo. For more information, see
# [DataInputConfig][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_InputConfig.html#sagemaker-Type-InputConfig-DataInputConfig
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobContainerConfig AWS API Documentation
#
class RecommendationJobContainerConfig < Struct.new(
:domain,
:task,
:framework,
:framework_version,
:payload_config,
:nearest_model_name,
:supported_instance_types,
:data_input_config)
SENSITIVE = []
include Aws::Structure
end
# The details for a specific benchmark from an Inference Recommender
# job.
#
# @!attribute [rw] metrics
# The metrics of recommendations.
# @return [Types::RecommendationMetrics]
#
# @!attribute [rw] endpoint_configuration
# The endpoint configuration made by Inference Recommender during a
# recommendation job.
# @return [Types::EndpointOutputConfiguration]
#
# @!attribute [rw] model_configuration
# Defines the model configuration. Includes the specification name and
# environment parameters.
# @return [Types::ModelConfiguration]
#
# @!attribute [rw] failure_reason
# The reason why a benchmark failed.
# @return [String]
#
# @!attribute [rw] endpoint_metrics
# The metrics for an existing endpoint compared in an Inference
# Recommender job.
# @return [Types::InferenceMetrics]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobInferenceBenchmark AWS API Documentation
#
class RecommendationJobInferenceBenchmark < Struct.new(
:metrics,
:endpoint_configuration,
:model_configuration,
:failure_reason,
:endpoint_metrics)
SENSITIVE = []
include Aws::Structure
end
# The input configuration of the recommendation job.
#
# @!attribute [rw] model_package_version_arn
# The Amazon Resource Name (ARN) of a versioned model package.
# @return [String]
#
# @!attribute [rw] job_duration_in_seconds
# Specifies the maximum duration of the job, in seconds.>
# @return [Integer]
#
# @!attribute [rw] traffic_pattern
# Specifies the traffic pattern of the job.
# @return [Types::TrafficPattern]
#
# @!attribute [rw] resource_limit
# Defines the resource limit of the job.
# @return [Types::RecommendationJobResourceLimit]
#
# @!attribute [rw] endpoint_configurations
# Specifies the endpoint configuration to use for a job.
# @return [Array<Types::EndpointInputConfiguration>]
#
# @!attribute [rw] volume_kms_key_id
# The Amazon Resource Name (ARN) of a Amazon Web Services Key
# Management Service (Amazon Web Services KMS) key that Amazon
# SageMaker uses to encrypt data on the storage volume attached to the
# ML compute instance that hosts the endpoint. This key will be passed
# to SageMaker Hosting for endpoint creation.
#
# The SageMaker execution role must have `kms:CreateGrant` permission
# in order to encrypt data on the storage volume of the endpoints
# created for inference recommendation. The inference recommendation
# job will fail asynchronously during endpoint configuration creation
# if the role passed does not have `kms:CreateGrant` permission.
#
# The `KmsKeyId` can be any of the following formats:
#
# * // KMS Key ID
#
# `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * // Amazon Resource Name (ARN) of a KMS Key
#
# `"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"`
#
# * // KMS Key Alias
#
# `"alias/ExampleAlias"`
#
# * // Amazon Resource Name (ARN) of a KMS Key Alias
#
# `"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"`
#
# For more information about key identifiers, see [Key identifiers
# (KeyID)][1] in the Amazon Web Services Key Management Service
# (Amazon Web Services KMS) documentation.
#
#
#
# [1]: https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-id
# @return [String]
#
# @!attribute [rw] container_config
# Specifies mandatory fields for running an Inference Recommender job.
# The fields specified in `ContainerConfig` override the corresponding
# fields in the model package.
# @return [Types::RecommendationJobContainerConfig]
#
# @!attribute [rw] endpoints
# Existing customer endpoints on which to run an Inference Recommender
# job.
# @return [Array<Types::EndpointInfo>]
#
# @!attribute [rw] vpc_config
# Inference Recommender provisions SageMaker endpoints with access to
# VPC in the inference recommendation job.
# @return [Types::RecommendationJobVpcConfig]
#
# @!attribute [rw] model_name
# The name of the created model.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobInputConfig AWS API Documentation
#
class RecommendationJobInputConfig < Struct.new(
:model_package_version_arn,
:job_duration_in_seconds,
:traffic_pattern,
:resource_limit,
:endpoint_configurations,
:volume_kms_key_id,
:container_config,
:endpoints,
:vpc_config,
:model_name)
SENSITIVE = []
include Aws::Structure
end
# Provides information about the output configuration for the compiled
# model.
#
# @!attribute [rw] kms_key_id
# The Amazon Resource Name (ARN) of a Amazon Web Services Key
# Management Service (Amazon Web Services KMS) key that Amazon
# SageMaker uses to encrypt your output artifacts with Amazon S3
# server-side encryption. The SageMaker execution role must have
# `kms:GenerateDataKey` permission.
#
# The `KmsKeyId` can be any of the following formats:
#
# * // KMS Key ID
#
# `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * // Amazon Resource Name (ARN) of a KMS Key
#
# `"arn:aws:kms:<region>:<account>:key/<key-id-12ab-34cd-56ef-1234567890ab>"`
#
# * // KMS Key Alias
#
# `"alias/ExampleAlias"`
#
# * // Amazon Resource Name (ARN) of a KMS Key Alias
#
# `"arn:aws:kms:<region>:<account>:alias/<ExampleAlias>"`
#
# For more information about key identifiers, see [Key identifiers
# (KeyID)][1] in the Amazon Web Services Key Management Service
# (Amazon Web Services KMS) documentation.
#
#
#
# [1]: https://docs.aws.amazon.com/kms/latest/developerguide/concepts.html#key-id-key-id
# @return [String]
#
# @!attribute [rw] compiled_output_config
# Provides information about the output configuration for the compiled
# model.
# @return [Types::RecommendationJobCompiledOutputConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobOutputConfig AWS API Documentation
#
class RecommendationJobOutputConfig < Struct.new(
:kms_key_id,
:compiled_output_config)
SENSITIVE = []
include Aws::Structure
end
# The configuration for the payload for a recommendation job.
#
# @!attribute [rw] sample_payload_url
# The Amazon Simple Storage Service (Amazon S3) path where the sample
# payload is stored. This path must point to a single gzip compressed
# tar archive (.tar.gz suffix).
# @return [String]
#
# @!attribute [rw] supported_content_types
# The supported MIME types for the input data.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobPayloadConfig AWS API Documentation
#
class RecommendationJobPayloadConfig < Struct.new(
:sample_payload_url,
:supported_content_types)
SENSITIVE = []
include Aws::Structure
end
# Specifies the maximum number of jobs that can run in parallel and the
# maximum number of jobs that can run.
#
# @!attribute [rw] max_number_of_tests
# Defines the maximum number of load tests.
# @return [Integer]
#
# @!attribute [rw] max_parallel_of_tests
# Defines the maximum number of parallel load tests.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobResourceLimit AWS API Documentation
#
class RecommendationJobResourceLimit < Struct.new(
:max_number_of_tests,
:max_parallel_of_tests)
SENSITIVE = []
include Aws::Structure
end
# Specifies conditions for stopping a job. When a job reaches a stopping
# condition limit, SageMaker ends the job.
#
# @!attribute [rw] max_invocations
# The maximum number of requests per minute expected for the endpoint.
# @return [Integer]
#
# @!attribute [rw] model_latency_thresholds
# The interval of time taken by a model to respond as viewed from
# SageMaker. The interval includes the local communication time taken
# to send the request and to fetch the response from the container of
# a model and the time taken to complete the inference in the
# container.
# @return [Array<Types::ModelLatencyThreshold>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobStoppingConditions AWS API Documentation
#
class RecommendationJobStoppingConditions < Struct.new(
:max_invocations,
:model_latency_thresholds)
SENSITIVE = []
include Aws::Structure
end
# Inference Recommender provisions SageMaker endpoints with access to
# VPC in the inference recommendation job.
#
# @!attribute [rw] security_group_ids
# The VPC security group IDs. IDs have the form of `sg-xxxxxxxx`.
# Specify the security groups for the VPC that is specified in the
# `Subnets` field.
# @return [Array<String>]
#
# @!attribute [rw] subnets
# The ID of the subnets in the VPC to which you want to connect your
# model.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobVpcConfig AWS API Documentation
#
class RecommendationJobVpcConfig < Struct.new(
:security_group_ids,
:subnets)
SENSITIVE = []
include Aws::Structure
end
# The metrics of recommendations.
#
# @!attribute [rw] cost_per_hour
# Defines the cost per hour for the instance.
# @return [Float]
#
# @!attribute [rw] cost_per_inference
# Defines the cost per inference for the instance .
# @return [Float]
#
# @!attribute [rw] max_invocations
# The expected maximum number of requests per minute for the instance.
# @return [Integer]
#
# @!attribute [rw] model_latency
# The expected model latency at maximum invocation per minute for the
# instance.
# @return [Integer]
#
# @!attribute [rw] cpu_utilization
# The expected CPU utilization at maximum invocations per minute for
# the instance.
#
# `NaN` indicates that the value is not available.
# @return [Float]
#
# @!attribute [rw] memory_utilization
# The expected memory utilization at maximum invocations per minute
# for the instance.
#
# `NaN` indicates that the value is not available.
# @return [Float]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationMetrics AWS API Documentation
#
class RecommendationMetrics < Struct.new(
:cost_per_hour,
:cost_per_inference,
:max_invocations,
:model_latency,
:cpu_utilization,
:memory_utilization)
SENSITIVE = []
include Aws::Structure
end
# Configuration for Redshift Dataset Definition input.
#
# @!attribute [rw] cluster_id
# The Redshift cluster Identifier.
# @return [String]
#
# @!attribute [rw] database
# The name of the Redshift database used in Redshift query execution.
# @return [String]
#
# @!attribute [rw] db_user
# The database user name used in Redshift query execution.
# @return [String]
#
# @!attribute [rw] query_string
# The SQL query statements to be executed.
# @return [String]
#
# @!attribute [rw] cluster_role_arn
# The IAM role attached to your Redshift cluster that Amazon SageMaker
# uses to generate datasets.
# @return [String]
#
# @!attribute [rw] output_s3_uri
# The location in Amazon S3 where the Redshift query results are
# stored.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt data from a Redshift
# execution.
# @return [String]
#
# @!attribute [rw] output_format
# The data storage format for Redshift query results.
# @return [String]
#
# @!attribute [rw] output_compression
# The compression used for Redshift query results.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RedshiftDatasetDefinition AWS API Documentation
#
class RedshiftDatasetDefinition < Struct.new(
:cluster_id,
:database,
:db_user,
:query_string,
:cluster_role_arn,
:output_s3_uri,
:kms_key_id,
:output_format,
:output_compression)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet.
# @return [String]
#
# @!attribute [rw] devices
# A list of devices to register with SageMaker Edge Manager.
# @return [Array<Types::Device>]
#
# @!attribute [rw] tags
# The tags associated with devices.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RegisterDevicesRequest AWS API Documentation
#
class RegisterDevicesRequest < Struct.new(
:device_fleet_name,
:devices,
:tags)
SENSITIVE = []
include Aws::Structure
end
# Metadata for a register model job step.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the model package.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RegisterModelStepMetadata AWS API Documentation
#
class RegisterModelStepMetadata < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] ui_template
# A `Template` object containing the worker UI template to render.
# @return [Types::UiTemplate]
#
# @!attribute [rw] task
# A `RenderableTask` object containing a representative task to
# render.
# @return [Types::RenderableTask]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) that has access to the S3 objects
# that are used by the template.
# @return [String]
#
# @!attribute [rw] human_task_ui_arn
# The `HumanTaskUiArn` of the worker UI that you want to render. Do
# not provide a `HumanTaskUiArn` if you use the `UiTemplate`
# parameter.
#
# See a list of available Human Ui Amazon Resource Names (ARNs) in
# [UiConfig][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UiConfig.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RenderUiTemplateRequest AWS API Documentation
#
class RenderUiTemplateRequest < Struct.new(
:ui_template,
:task,
:role_arn,
:human_task_ui_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] rendered_content
# A Liquid template that renders the HTML for the worker UI.
# @return [String]
#
# @!attribute [rw] errors
# A list of one or more `RenderingError` objects if any were
# encountered while rendering the template. If there were no errors,
# the list is empty.
# @return [Array<Types::RenderingError>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RenderUiTemplateResponse AWS API Documentation
#
class RenderUiTemplateResponse < Struct.new(
:rendered_content,
:errors)
SENSITIVE = []
include Aws::Structure
end
# Contains input values for a task.
#
# @!attribute [rw] input
# A JSON object that contains values for the variables defined in the
# template. It is made available to the template under the
# substitution variable `task.input`. For example, if you define a
# variable `task.input.text` in your template, you can supply the
# variable in the JSON object as `"text": "sample text"`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RenderableTask AWS API Documentation
#
class RenderableTask < Struct.new(
:input)
SENSITIVE = []
include Aws::Structure
end
# A description of an error that occurred while rendering the template.
#
# @!attribute [rw] code
# A unique identifier for a specific class of errors.
# @return [String]
#
# @!attribute [rw] message
# A human-readable message describing the error.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RenderingError AWS API Documentation
#
class RenderingError < Struct.new(
:code,
:message)
SENSITIVE = []
include Aws::Structure
end
# 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 `Vpc` as the value for the
# `RepositoryAccessMode` field of the `ImageConfig` object that you
# passed to a call to `CreateModel` and the private Docker registry
# where the model image is hosted requires authentication.
#
# @!attribute [rw] repository_credentials_provider_arn
# The Amazon Resource Name (ARN) of an Amazon Web Services Lambda
# function that provides credentials to authenticate to the private
# Docker registry where your model image is hosted. For information
# about how to create an Amazon Web Services Lambda function, see
# [Create a Lambda function with the console][1] in the *Amazon Web
# Services Lambda Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/lambda/latest/dg/getting-started-create-function.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RepositoryAuthConfig AWS API Documentation
#
class RepositoryAuthConfig < Struct.new(
:repository_credentials_provider_arn)
SENSITIVE = []
include Aws::Structure
end
# The resolved attributes.
#
# @!attribute [rw] auto_ml_job_objective
# Specifies a metric to minimize or maximize as the objective of a
# job. V2 API jobs (for example jobs created by calling
# `CreateAutoMLJobV2`), support `Accuracy` only.
# @return [Types::AutoMLJobObjective]
#
# @!attribute [rw] problem_type
# The problem type.
# @return [String]
#
# @!attribute [rw] completion_criteria
# How long a job is allowed to run, or how many candidates a job is
# allowed to generate.
# @return [Types::AutoMLJobCompletionCriteria]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResolvedAttributes AWS API Documentation
#
class ResolvedAttributes < Struct.new(
:auto_ml_job_objective,
:problem_type,
:completion_criteria)
SENSITIVE = []
include Aws::Structure
end
# Describes the resources, including machine learning (ML) compute
# instances and ML storage volumes, to use for model training.
#
# @!attribute [rw] instance_type
# The ML compute instance type.
#
# <note markdown="1"> SageMaker Training on Amazon Elastic Compute Cloud (EC2) P4de
# instances is in preview release starting December 9th, 2022.
#
# [Amazon EC2 P4de instances][1] (currently in preview) are powered by
# 8 NVIDIA A100 GPUs with 80GB high-performance HBM2e GPU memory,
# which accelerate the speed of training ML models that need to be
# trained on large datasets of high-resolution data. In this preview
# release, Amazon SageMaker supports ML training jobs on P4de
# instances (`ml.p4de.24xlarge`) to reduce model training time. The
# `ml.p4de.24xlarge` instances are available in the following Amazon
# Web Services Regions.
#
# * US East (N. Virginia) (us-east-1)
#
# * US West (Oregon) (us-west-2)
#
# To request quota limit increase and start using P4de instances,
# contact the SageMaker Training service team through your account
# team.
#
# </note>
#
#
#
# [1]: http://aws.amazon.com/ec2/instance-types/p4/
# @return [String]
#
# @!attribute [rw] instance_count
# The number of ML compute instances to use. For distributed training,
# provide a value greater than 1.
# @return [Integer]
#
# @!attribute [rw] volume_size_in_gb
# The size of the ML storage volume that you want to provision.
#
# ML storage volumes store model artifacts and incremental states.
# Training algorithms might also use the ML storage volume for scratch
# space. If you want to store the training data in the ML storage
# volume, choose `File` as the `TrainingInputMode` in the algorithm
# specification.
#
# When using an ML instance with [NVMe SSD volumes][1], SageMaker
# doesn't provision Amazon EBS General Purpose SSD (gp2) storage.
# Available storage is fixed to the NVMe-type instance's storage
# capacity. SageMaker configures storage paths for training datasets,
# checkpoints, model artifacts, and outputs to use the entire capacity
# of the instance storage. For example, ML instance families with the
# NVMe-type instance storage include `ml.p4d`, `ml.g4dn`, and `ml.g5`.
#
# When using an ML instance with the EBS-only storage option and
# without instance storage, you must define the size of EBS volume
# through `VolumeSizeInGB` in the `ResourceConfig` API. For example,
# ML instance families that use EBS volumes include `ml.c5` and
# `ml.p2`.
#
# To look up instance types and their instance storage types and
# volumes, see [Amazon EC2 Instance Types][2].
#
# To find the default local paths defined by the SageMaker training
# platform, see [Amazon SageMaker Training Storage Folders for
# Training Datasets, Checkpoints, Model Artifacts, and Outputs][3].
#
#
#
# [1]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.html#nvme-ssd-volumes
# [2]: http://aws.amazon.com/ec2/instance-types/
# [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-train-storage.html
# @return [Integer]
#
# @!attribute [rw] volume_kms_key_id
# The Amazon Web Services KMS key that SageMaker uses to encrypt data
# on the storage volume attached to the ML compute instance(s) that
# run the training job.
#
# <note markdown="1"> Certain Nitro-based instances include local storage, dependent on
# the instance type. Local storage volumes are encrypted using a
# hardware module on the instance. You can't request a
# `VolumeKmsKeyId` when using an instance type with local storage.
#
# For a list of instance types that support local instance storage,
# see [Instance Store Volumes][1].
#
# For more information about local instance storage encryption, see
# [SSD Instance Store Volumes][2].
#
# </note>
#
# The `VolumeKmsKeyId` can be in any of the following formats:
#
# * // KMS Key ID
#
# `"1234abcd-12ab-34cd-56ef-1234567890ab"`
#
# * // Amazon Resource Name (ARN) of a KMS Key
#
# `"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab"`
#
#
#
# [1]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes
# [2]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.html
# @return [String]
#
# @!attribute [rw] instance_groups
# The configuration of a heterogeneous cluster in JSON format.
# @return [Array<Types::InstanceGroup>]
#
# @!attribute [rw] keep_alive_period_in_seconds
# The duration of time in seconds to retain configured resources in a
# warm pool for subsequent training jobs.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceConfig AWS API Documentation
#
class ResourceConfig < Struct.new(
:instance_type,
:instance_count,
:volume_size_in_gb,
:volume_kms_key_id,
:instance_groups,
:keep_alive_period_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# The `ResourceConfig` to update `KeepAlivePeriodInSeconds`. Other
# fields in the `ResourceConfig` cannot be updated.
#
# @!attribute [rw] keep_alive_period_in_seconds
# The `KeepAlivePeriodInSeconds` value specified in the
# `ResourceConfig` to update.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceConfigForUpdate AWS API Documentation
#
class ResourceConfigForUpdate < Struct.new(
:keep_alive_period_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# Resource being accessed is in use.
#
# @!attribute [rw] message
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceInUse AWS API Documentation
#
class ResourceInUse < Struct.new(
:message)
SENSITIVE = []
include Aws::Structure
end
# You have exceeded an SageMaker resource limit. For example, you might
# have too many training jobs created.
#
# @!attribute [rw] message
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceLimitExceeded AWS API Documentation
#
class ResourceLimitExceeded < Struct.new(
:message)
SENSITIVE = []
include Aws::Structure
end
# Specifies the maximum number of training jobs and parallel training
# jobs that a hyperparameter tuning job can launch.
#
# @!attribute [rw] max_number_of_training_jobs
# The maximum number of training jobs that a hyperparameter tuning job
# can launch.
# @return [Integer]
#
# @!attribute [rw] max_parallel_training_jobs
# The maximum number of concurrent training jobs that a hyperparameter
# tuning job can launch.
# @return [Integer]
#
# @!attribute [rw] max_runtime_in_seconds
# The maximum time in seconds that a hyperparameter tuning job can
# run.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceLimits AWS API Documentation
#
class ResourceLimits < Struct.new(
:max_number_of_training_jobs,
:max_parallel_training_jobs,
:max_runtime_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# Resource being access is not found.
#
# @!attribute [rw] message
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceNotFound AWS API Documentation
#
class ResourceNotFound < Struct.new(
:message)
SENSITIVE = []
include Aws::Structure
end
# Specifies the ARN's of a SageMaker image and SageMaker image version,
# and the instance type that the version runs on.
#
# @!attribute [rw] sage_maker_image_arn
# The ARN of the SageMaker image that the image version belongs to.
# @return [String]
#
# @!attribute [rw] sage_maker_image_version_arn
# The ARN of the image version created on the instance.
# @return [String]
#
# @!attribute [rw] instance_type
# The instance type that the image version runs on.
#
# <note markdown="1"> **JupyterServer apps** only support the `system` value.
#
# For **KernelGateway apps**, the `system` value is translated to
# `ml.t3.medium`. KernelGateway apps also support all other values for
# available instance types.
#
# </note>
# @return [String]
#
# @!attribute [rw] lifecycle_config_arn
# The Amazon Resource Name (ARN) of the Lifecycle Configuration
# attached to the Resource.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceSpec AWS API Documentation
#
class ResourceSpec < Struct.new(
:sage_maker_image_arn,
:sage_maker_image_version_arn,
:instance_type,
:lifecycle_config_arn)
SENSITIVE = []
include Aws::Structure
end
# The retention policy for data stored on an Amazon Elastic File System
# (EFS) volume.
#
# @!attribute [rw] home_efs_file_system
# The default is `Retain`, which specifies to keep the data stored on
# the EFS volume.
#
# Specify `Delete` to delete the data stored on the EFS volume.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RetentionPolicy AWS API Documentation
#
class RetentionPolicy < Struct.new(
:home_efs_file_system)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @!attribute [rw] client_request_token
# A unique, case-sensitive identifier that you provide to ensure the
# idempotency of the operation. An idempotent operation completes no
# more than once.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @!attribute [rw] parallelism_configuration
# This configuration, if specified, overrides the parallelism
# configuration of the parent pipeline.
# @return [Types::ParallelismConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RetryPipelineExecutionRequest AWS API Documentation
#
class RetryPipelineExecutionRequest < Struct.new(
:pipeline_execution_arn,
:client_request_token,
:parallelism_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RetryPipelineExecutionResponse AWS API Documentation
#
class RetryPipelineExecutionResponse < Struct.new(
:pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# The retry strategy to use when a training job fails due to an
# `InternalServerError`. `RetryStrategy` is specified as part of the
# `CreateTrainingJob` and `CreateHyperParameterTuningJob` requests. You
# can add the `StoppingCondition` parameter to the request to limit the
# training time for the complete job.
#
# @!attribute [rw] maximum_retry_attempts
# The number of times to retry the job. When the job is retried, it's
# `SecondaryStatus` is changed to `STARTING`.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RetryStrategy AWS API Documentation
#
class RetryStrategy < Struct.new(
:maximum_retry_attempts)
SENSITIVE = []
include Aws::Structure
end
# Describes the S3 data source.
#
# @!attribute [rw] s3_data_type
# If you choose `S3Prefix`, `S3Uri` identifies a key name prefix.
# SageMaker uses all objects that match the specified key name prefix
# for model training.
#
# If you choose `ManifestFile`, `S3Uri` identifies an object that is a
# manifest file containing a list of object keys that you want
# SageMaker to use for model training.
#
# If you choose `AugmentedManifestFile`, S3Uri identifies an object
# that is an augmented manifest file in JSON lines format. This file
# contains the data you want to use for model training.
# `AugmentedManifestFile` can only be used if the Channel's input
# mode is `Pipe`.
# @return [String]
#
# @!attribute [rw] s3_uri
# Depending on the value specified for the `S3DataType`, identifies
# either a key name prefix or a manifest. For example:
#
# * A key name prefix might look like this:
# `s3://bucketname/exampleprefix`
#
# * A manifest might look like this:
# `s3://bucketname/example.manifest`
#
# A manifest is an S3 object which is a JSON file consisting of an
# array of elements. The first element is a prefix which is followed
# by one or more suffixes. SageMaker appends the suffix elements to
# the prefix to get a full set of `S3Uri`. Note that the prefix must
# be a valid non-empty `S3Uri` that precludes users from specifying
# a manifest whose individual `S3Uri` is sourced from different S3
# buckets.
#
# The following code example shows a valid manifest format:
#
# `[ \{"prefix": "s3://customer_bucket/some/prefix/"\},`
#
# ` "relative/path/to/custdata-1",`
#
# ` "relative/path/custdata-2",`
#
# ` ...`
#
# ` "relative/path/custdata-N"`
#
# `]`
#
# This JSON is equivalent to the following `S3Uri` list:
#
# `s3://customer_bucket/some/prefix/relative/path/to/custdata-1`
#
# `s3://customer_bucket/some/prefix/relative/path/custdata-2`
#
# `...`
#
# `s3://customer_bucket/some/prefix/relative/path/custdata-N`
#
# The complete set of `S3Uri` in this manifest is the input data for
# the channel for this data source. The object that each `S3Uri`
# points to must be readable by the IAM role that SageMaker uses to
# perform tasks on your behalf.
# @return [String]
#
# @!attribute [rw] s3_data_distribution_type
# If you want SageMaker to replicate the entire dataset on each ML
# compute instance that is launched for model training, specify
# `FullyReplicated`.
#
# If you want SageMaker to replicate a subset of data on each ML
# compute instance that is launched for model training, specify
# `ShardedByS3Key`. If there are *n* ML compute instances launched for
# a training job, each instance gets approximately 1/*n* of the number
# of S3 objects. In this case, model training on each machine uses
# only the subset of training data.
#
# Don't choose more ML compute instances for training than available
# S3 objects. If you do, some nodes won't get any data and you will
# pay for nodes that aren't getting any training data. This applies
# in both File and Pipe modes. Keep this in mind when developing
# algorithms.
#
# In distributed training, where you use multiple ML compute EC2
# instances, you might choose `ShardedByS3Key`. If the algorithm
# requires copying training data to the ML storage volume (when
# `TrainingInputMode` is set to `File`), this copies 1/*n* of the
# number of objects.
# @return [String]
#
# @!attribute [rw] attribute_names
# A list of one or more attribute names to use that are found in a
# specified augmented manifest file.
# @return [Array<String>]
#
# @!attribute [rw] instance_group_names
# A list of names of instance groups that get data from the S3 data
# source.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/S3DataSource AWS API Documentation
#
class S3DataSource < Struct.new(
:s3_data_type,
:s3_uri,
:s3_data_distribution_type,
:attribute_names,
:instance_group_names)
SENSITIVE = []
include Aws::Structure
end
# The Amazon Simple Storage (Amazon S3) location and and security
# configuration for `OfflineStore`.
#
# @!attribute [rw] s3_uri
# The S3 URI, or location in Amazon S3, of `OfflineStore`.
#
# S3 URIs have a format similar to the following:
# `s3://example-bucket/prefix/`.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (KMS) key ARN of the
# key used to encrypt any objects written into the `OfflineStore` S3
# location.
#
# The IAM `roleARN` that is passed as a parameter to
# `CreateFeatureGroup` must have below permissions to the `KmsKeyId`:
#
# * `"kms:GenerateDataKey"`
#
# ^
# @return [String]
#
# @!attribute [rw] resolved_output_s3_uri
# The S3 path where offline records are written.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/S3StorageConfig AWS API Documentation
#
class S3StorageConfig < Struct.new(
:s3_uri,
:kms_key_id,
:resolved_output_s3_uri)
SENSITIVE = []
include Aws::Structure
end
# Configuration details about the monitoring schedule.
#
# @!attribute [rw] schedule_expression
# A cron expression that describes details about the monitoring
# schedule.
#
# Currently the only supported cron expressions are:
#
# * If you want to set the job to start every hour, please use the
# following:
#
# `Hourly: cron(0 * ? * * *)`
#
# * If you want to start the job daily:
#
# `cron(0 [00-23] ? * * *)`
#
# For example, the following are valid cron expressions:
#
# * Daily at noon UTC: `cron(0 12 ? * * *)`
#
# * Daily at midnight UTC: `cron(0 0 ? * * *)`
#
# To support running every 6, 12 hours, the following are also
# supported:
#
# `cron(0 [00-23]/[01-24] ? * * *)`
#
# For example, the following are valid cron expressions:
#
# * Every 12 hours, starting at 5pm UTC: `cron(0 17/12 ? * * *)`
#
# * Every two hours starting at midnight: `cron(0 0/2 ? * * *)`
#
# <note markdown="1"> * Even though the cron expression is set to start at 5PM UTC, note
# that there could be a delay of 0-20 minutes from the actual
# requested time to run the execution.
#
# * We recommend that if you would like a daily schedule, you do not
# provide this parameter. Amazon SageMaker will pick a time for
# running every day.
#
# </note>
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ScheduleConfig AWS API Documentation
#
class ScheduleConfig < Struct.new(
:schedule_expression)
SENSITIVE = []
include Aws::Structure
end
# A multi-expression that searches for the specified resource or
# resources in a search. All resource objects that satisfy the
# expression's condition are included in the search results. You must
# specify at least one subexpression, filter, or nested filter. A
# `SearchExpression` can contain up to twenty elements.
#
# A `SearchExpression` contains the following components:
#
# * A list of `Filter` objects. Each filter defines a simple Boolean
# expression comprised of a resource property name, Boolean operator,
# and value.
#
# * A list of `NestedFilter` objects. 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 `SearchExpression` objects. A search expression object can
# be nested in a list of search expression objects.
#
# * A Boolean operator: `And` or `Or`.
#
# @!attribute [rw] filters
# A list of filter objects.
# @return [Array<Types::Filter>]
#
# @!attribute [rw] nested_filters
# A list of nested filter objects.
# @return [Array<Types::NestedFilters>]
#
# @!attribute [rw] sub_expressions
# A list of search expression objects.
# @return [Array<Types::SearchExpression>]
#
# @!attribute [rw] operator
# A Boolean operator used to evaluate the search expression. If you
# want every conditional statement in all lists to be satisfied for
# the entire search expression to be true, specify `And`. If only a
# single conditional statement needs to be true for the entire search
# expression to be true, specify `Or`. The default value is `And`.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SearchExpression AWS API Documentation
#
class SearchExpression < Struct.new(
:filters,
:nested_filters,
:sub_expressions,
:operator)
SENSITIVE = []
include Aws::Structure
end
# A single resource returned as part of the [Search][1] API response.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
#
# @!attribute [rw] training_job
# The properties of a training job.
# @return [Types::TrainingJob]
#
# @!attribute [rw] experiment
# The properties of an experiment.
# @return [Types::Experiment]
#
# @!attribute [rw] trial
# The properties of a trial.
# @return [Types::Trial]
#
# @!attribute [rw] trial_component
# The properties of a trial component.
# @return [Types::TrialComponent]
#
# @!attribute [rw] endpoint
# A hosted endpoint for real-time inference.
# @return [Types::Endpoint]
#
# @!attribute [rw] model_package
# A versioned model that can be deployed for SageMaker inference.
# @return [Types::ModelPackage]
#
# @!attribute [rw] model_package_group
# A group of versioned models in the model registry.
# @return [Types::ModelPackageGroup]
#
# @!attribute [rw] pipeline
# A SageMaker Model Building Pipeline instance.
# @return [Types::Pipeline]
#
# @!attribute [rw] pipeline_execution
# An execution of a pipeline.
# @return [Types::PipelineExecution]
#
# @!attribute [rw] 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.
# @return [Types::FeatureGroup]
#
# @!attribute [rw] project
# The properties of a project.
# @return [Types::Project]
#
# @!attribute [rw] feature_metadata
# The feature metadata used to search through the features.
# @return [Types::FeatureMetadata]
#
# @!attribute [rw] hyper_parameter_tuning_job
# The properties of a hyperparameter tuning job.
# @return [Types::HyperParameterTuningJobSearchEntity]
#
# @!attribute [rw] model
# A model displayed in the Amazon SageMaker Model Dashboard.
# @return [Types::ModelDashboardModel]
#
# @!attribute [rw] model_card
# An Amazon SageMaker Model Card that documents details about a
# machine learning model.
# @return [Types::ModelCard]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SearchRecord AWS API Documentation
#
class SearchRecord < Struct.new(
:training_job,
:experiment,
:trial,
:trial_component,
:endpoint,
:model_package,
:model_package_group,
:pipeline,
:pipeline_execution,
:feature_group,
:project,
:feature_metadata,
:hyper_parameter_tuning_job,
:model,
:model_card)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] resource
# The name of the SageMaker resource to search for.
# @return [String]
#
# @!attribute [rw] search_expression
# A Boolean conditional statement. Resources must satisfy this
# condition to be included in search results. You must provide at
# least one subexpression, filter, or nested filter. The maximum
# number of recursive `SubExpressions`, `NestedFilters`, and `Filters`
# that can be included in a `SearchExpression` object is 50.
# @return [Types::SearchExpression]
#
# @!attribute [rw] sort_by
# The name of the resource property used to sort the `SearchResults`.
# The default is `LastModifiedTime`.
# @return [String]
#
# @!attribute [rw] sort_order
# How `SearchResults` are ordered. Valid values are `Ascending` or
# `Descending`. The default is `Descending`.
# @return [String]
#
# @!attribute [rw] next_token
# If more than `MaxResults` resources match the specified
# `SearchExpression`, the response includes a `NextToken`. The
# `NextToken` can be passed to the next `SearchRequest` to continue
# retrieving results.
# @return [String]
#
# @!attribute [rw] max_results
# The maximum number of results to return.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SearchRequest AWS API Documentation
#
class SearchRequest < Struct.new(
:resource,
:search_expression,
:sort_by,
:sort_order,
:next_token,
:max_results)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] results
# A list of `SearchRecord` objects.
# @return [Array<Types::SearchRecord>]
#
# @!attribute [rw] next_token
# If the result of the previous `Search` request was truncated, the
# response includes a NextToken. To retrieve the next set of results,
# use the token in the next request.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SearchResponse AWS API Documentation
#
class SearchResponse < Struct.new(
:results,
:next_token)
SENSITIVE = []
include Aws::Structure
end
# An array element of `SecondaryStatusTransitions` for
# [DescribeTrainingJob][1]. 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, SageMaker
# could be starting the training job or launching the ML instances.
# These transitional states are referred to as the job's secondary
# status.
#
#
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTrainingJob.html
#
# @!attribute [rw] status
# Contains a secondary status information from a training job.
#
# Status might be one of the following secondary statuses:
#
# InProgress
# : * `Starting` - Starting the training job.
#
# * `Downloading` - An optional stage for algorithms that support
# `File` training input mode. It indicates that data is being
# downloaded to the ML storage volumes.
#
# * `Training` - Training is in progress.
#
# * `Uploading` - Training is complete and the model artifacts are
# being uploaded to the S3 location.
#
# Completed
# : * `Completed` - The training job has completed.
#
# ^
#
# Failed
# : * `Failed` - The training job has failed. The reason for the
# failure is returned in the `FailureReason` field of
# `DescribeTrainingJobResponse`.
#
# ^
#
# Stopped
# : * `MaxRuntimeExceeded` - The job stopped because it exceeded the
# maximum allowed runtime.
#
# * `Stopped` - The training job has stopped.
#
# Stopping
# : * `Stopping` - Stopping the training job.
#
# ^
#
# We no longer support the following secondary statuses:
#
# * `LaunchingMLInstances`
#
# * `PreparingTrainingStack`
#
# * `DownloadingTrainingImage`
# @return [String]
#
# @!attribute [rw] start_time
# A timestamp that shows when the training job transitioned to the
# current secondary status state.
# @return [Time]
#
# @!attribute [rw] end_time
# A timestamp that shows when the training job transitioned out of
# this secondary status state into another secondary status state or
# when the training job has ended.
# @return [Time]
#
# @!attribute [rw] status_message
# A detailed description of the progress within a secondary status.
#
# SageMaker provides secondary statuses and status messages that apply
# to each of them:
#
# Starting
# : * Starting the training job.
#
# * Launching requested ML instances.
#
# * Insufficient capacity error from EC2 while launching instances,
# retrying!
#
# * Launched instance was unhealthy, replacing it!
#
# * Preparing the instances for training.
#
# Training
# : * Downloading the training image.
#
# * Training image download completed. Training in progress.
#
# Status messages are subject to change. Therefore, we recommend not
# including them in code that programmatically initiates actions. For
# examples, don't use status messages in if statements.
#
# To have an overview of your training job's progress, view
# `TrainingJobStatus` and `SecondaryStatus` in
# [DescribeTrainingJob][1], and `StatusMessage` together. For example,
# at the start of a training job, you might see the following:
#
# * `TrainingJobStatus` - InProgress
#
# * `SecondaryStatus` - Training
#
# * `StatusMessage` - Downloading the training image
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTrainingJob.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SecondaryStatusTransition AWS API Documentation
#
class SecondaryStatusTransition < Struct.new(
:status,
:start_time,
:end_time,
:status_message)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] callback_token
# The pipeline generated token from the Amazon SQS queue.
# @return [String]
#
# @!attribute [rw] failure_reason
# A message describing why the step failed.
# @return [String]
#
# @!attribute [rw] client_request_token
# A unique, case-sensitive identifier that you provide to ensure the
# idempotency of the operation. An idempotent operation completes no
# more than one time.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SendPipelineExecutionStepFailureRequest AWS API Documentation
#
class SendPipelineExecutionStepFailureRequest < Struct.new(
:callback_token,
:failure_reason,
:client_request_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SendPipelineExecutionStepFailureResponse AWS API Documentation
#
class SendPipelineExecutionStepFailureResponse < Struct.new(
:pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] callback_token
# The pipeline generated token from the Amazon SQS queue.
# @return [String]
#
# @!attribute [rw] output_parameters
# A list of the output parameters of the callback step.
# @return [Array<Types::OutputParameter>]
#
# @!attribute [rw] client_request_token
# A unique, case-sensitive identifier that you provide to ensure the
# idempotency of the operation. An idempotent operation completes no
# more than one time.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SendPipelineExecutionStepSuccessRequest AWS API Documentation
#
class SendPipelineExecutionStepSuccessRequest < Struct.new(
:callback_token,
:output_parameters,
:client_request_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SendPipelineExecutionStepSuccessResponse AWS API Documentation
#
class SendPipelineExecutionStepSuccessResponse < Struct.new(
:pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# Details of a provisioned service catalog product. For information
# about service catalog, see [What is Amazon Web Services Service
# Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
#
# @!attribute [rw] provisioned_product_id
# The ID of the provisioned product.
# @return [String]
#
# @!attribute [rw] provisioned_product_status_message
# The current status of the product.
#
# * `AVAILABLE` - Stable state, ready to perform any operation. The
# most recent operation succeeded and completed.
#
# * `UNDER_CHANGE` - Transitive state. Operations performed might not
# have valid results. Wait for an AVAILABLE status before performing
# operations.
#
# * `TAINTED` - Stable state, ready to perform any operation. The
# stack has completed the requested operation but is not exactly
# what was requested. For example, a request to update to a new
# version failed and the stack rolled back to the current version.
#
# * `ERROR` - An unexpected error occurred. The provisioned product
# exists but the stack is not running. For example, CloudFormation
# received a parameter value that was not valid and could not launch
# the stack.
#
# * `PLAN_IN_PROGRESS` - Transitive state. The plan operations were
# performed to provision a new product, but resources have not yet
# been created. After reviewing the list of resources to be created,
# execute the plan. Wait for an AVAILABLE status before performing
# operations.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ServiceCatalogProvisionedProductDetails AWS API Documentation
#
class ServiceCatalogProvisionedProductDetails < Struct.new(
:provisioned_product_id,
:provisioned_product_status_message)
SENSITIVE = []
include Aws::Structure
end
# Details that you specify to provision a service catalog product. For
# information about service catalog, see [What is Amazon Web Services
# Service Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
#
# @!attribute [rw] product_id
# The ID of the product to provision.
# @return [String]
#
# @!attribute [rw] provisioning_artifact_id
# The ID of the provisioning artifact.
# @return [String]
#
# @!attribute [rw] path_id
# The path identifier of the product. This value is optional if the
# product has a default path, and required if the product has more
# than one path.
# @return [String]
#
# @!attribute [rw] provisioning_parameters
# A list of key value pairs that you specify when you provision a
# product.
# @return [Array<Types::ProvisioningParameter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ServiceCatalogProvisioningDetails AWS API Documentation
#
class ServiceCatalogProvisioningDetails < Struct.new(
:product_id,
:provisioning_artifact_id,
:path_id,
:provisioning_parameters)
SENSITIVE = []
include Aws::Structure
end
# Details that you specify to provision a service catalog product. For
# information about service catalog, see [What is Amazon Web Services
# Service Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
#
# @!attribute [rw] provisioning_artifact_id
# The ID of the provisioning artifact.
# @return [String]
#
# @!attribute [rw] provisioning_parameters
# A list of key value pairs that you specify when you provision a
# product.
# @return [Array<Types::ProvisioningParameter>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ServiceCatalogProvisioningUpdateDetails AWS API Documentation
#
class ServiceCatalogProvisioningUpdateDetails < Struct.new(
:provisioning_artifact_id,
:provisioning_parameters)
SENSITIVE = []
include Aws::Structure
end
# The configuration of `ShadowMode` inference experiment type, which
# specifies a production variant to take all the inference requests, and
# a shadow variant to which Amazon SageMaker replicates a percentage of
# the inference requests. For the shadow variant it also specifies the
# percentage of requests that Amazon SageMaker replicates.
#
# @!attribute [rw] source_model_variant_name
# The name of the production variant, which takes all the inference
# requests.
# @return [String]
#
# @!attribute [rw] shadow_model_variants
# List of shadow variant configurations.
# @return [Array<Types::ShadowModelVariantConfig>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ShadowModeConfig AWS API Documentation
#
class ShadowModeConfig < Struct.new(
:source_model_variant_name,
:shadow_model_variants)
SENSITIVE = []
include Aws::Structure
end
# The name and sampling percentage of a shadow variant.
#
# @!attribute [rw] shadow_model_variant_name
# The name of the shadow variant.
# @return [String]
#
# @!attribute [rw] sampling_percentage
# The percentage of inference requests that Amazon SageMaker
# replicates from the production variant to the shadow variant.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ShadowModelVariantConfig AWS API Documentation
#
class ShadowModelVariantConfig < Struct.new(
:shadow_model_variant_name,
:sampling_percentage)
SENSITIVE = []
include Aws::Structure
end
# Specifies options for sharing SageMaker Studio notebooks. These
# settings are specified as part of `DefaultUserSettings` when the
# `CreateDomain` API is called, and as part of `UserSettings` when the
# `CreateUserProfile` API is called. When `SharingSettings` is not
# specified, notebook sharing isn't allowed.
#
# @!attribute [rw] notebook_output_option
# Whether to include the notebook cell output when sharing the
# notebook. The default is `Disabled`.
# @return [String]
#
# @!attribute [rw] s3_output_path
# When `NotebookOutputOption` is `Allowed`, the Amazon S3 bucket used
# to store the shared notebook snapshots.
# @return [String]
#
# @!attribute [rw] s3_kms_key_id
# When `NotebookOutputOption` is `Allowed`, the Amazon Web Services
# Key Management Service (KMS) encryption key ID used to encrypt the
# notebook cell output in the Amazon S3 bucket.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SharingSettings AWS API Documentation
#
class SharingSettings < Struct.new(
:notebook_output_option,
:s3_output_path,
:s3_kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# A configuration for a shuffle option for input data in a channel. If
# you use `S3Prefix` for `S3DataType`, the results of the S3 key prefix
# matches are shuffled. If you use `ManifestFile`, the order of the S3
# object references in the `ManifestFile` is shuffled. If you use
# `AugmentedManifestFile`, the order of the JSON lines in the
# `AugmentedManifestFile` is shuffled. The shuffling order is determined
# using the `Seed` value.
#
# For Pipe input mode, when `ShuffleConfig` is 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 when `ShuffleConfig` is combined with
# `S3DataDistributionType` of `ShardedByS3Key`, 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.
#
# @!attribute [rw] seed
# Determines the shuffling order in `ShuffleConfig` value.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ShuffleConfig AWS API Documentation
#
class ShuffleConfig < Struct.new(
:seed)
SENSITIVE = []
include Aws::Structure
end
# Specifies an algorithm that was used to create the model package. The
# algorithm must be either an algorithm resource in your SageMaker
# account or an algorithm in Amazon Web Services Marketplace that you
# are subscribed to.
#
# @!attribute [rw] model_data_url
# The Amazon S3 path where the model artifacts, which result from
# model training, are stored. This path must point to a single `gzip`
# compressed tar archive (`.tar.gz` suffix).
#
# <note markdown="1"> The model artifacts must be in an S3 bucket that is in the same
# region as the algorithm.
#
# </note>
# @return [String]
#
# @!attribute [rw] algorithm_name
# The name of an algorithm that was used to create the model package.
# The algorithm must be either an algorithm resource in your SageMaker
# account or an algorithm in Amazon Web Services Marketplace that you
# are subscribed to.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SourceAlgorithm AWS API Documentation
#
class SourceAlgorithm < Struct.new(
:model_data_url,
:algorithm_name)
SENSITIVE = []
include Aws::Structure
end
# A list of algorithms that were used to create a model package.
#
# @!attribute [rw] source_algorithms
# A list of the algorithms that were used to create a model package.
# @return [Array<Types::SourceAlgorithm>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SourceAlgorithmSpecification AWS API Documentation
#
class SourceAlgorithmSpecification < Struct.new(
:source_algorithms)
SENSITIVE = []
include Aws::Structure
end
# A list of IP address ranges ([CIDRs][1]). 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.
#
#
#
# [1]: https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html
#
# @!attribute [rw] cidrs
# A list of one to ten [Classless Inter-Domain Routing][1] (CIDR)
# values.
#
# Maximum: Ten CIDR values
#
# <note markdown="1"> The following Length Constraints apply to individual CIDR values in
# the CIDR value list.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SourceIpConfig AWS API Documentation
#
class SourceIpConfig < Struct.new(
:cidrs)
SENSITIVE = []
include Aws::Structure
end
# The space's details.
#
# @!attribute [rw] domain_id
# The ID of the associated Domain.
# @return [String]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @!attribute [rw] status
# The status.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last modified time.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SpaceDetails AWS API Documentation
#
class SpaceDetails < Struct.new(
:domain_id,
:space_name,
:status,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# A collection of space settings.
#
# @!attribute [rw] jupyter_server_app_settings
# The JupyterServer app settings.
# @return [Types::JupyterServerAppSettings]
#
# @!attribute [rw] kernel_gateway_app_settings
# The KernelGateway app settings.
# @return [Types::KernelGatewayAppSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SpaceSettings AWS API Documentation
#
class SpaceSettings < Struct.new(
:jupyter_server_app_settings,
:kernel_gateway_app_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan to start.
# @return [String]
#
# @!attribute [rw] stage_name
# The name of the stage to start.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartEdgeDeploymentStageRequest AWS API Documentation
#
class StartEdgeDeploymentStageRequest < Struct.new(
:edge_deployment_plan_name,
:stage_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name
# The name of the inference experiment to start.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartInferenceExperimentRequest AWS API Documentation
#
class StartInferenceExperimentRequest < Struct.new(
:name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] inference_experiment_arn
# The ARN of the started inference experiment to start.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartInferenceExperimentResponse AWS API Documentation
#
class StartInferenceExperimentResponse < Struct.new(
:inference_experiment_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# The name of the schedule to start.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartMonitoringScheduleRequest AWS API Documentation
#
class StartMonitoringScheduleRequest < Struct.new(
:monitoring_schedule_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_name
# The name of the notebook instance to start.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartNotebookInstanceInput AWS API Documentation
#
class StartNotebookInstanceInput < Struct.new(
:notebook_instance_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_name
# The name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_execution_display_name
# The display name of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_parameters
# Contains a list of pipeline parameters. This list can be empty.
# @return [Array<Types::Parameter>]
#
# @!attribute [rw] pipeline_execution_description
# The description of the pipeline execution.
# @return [String]
#
# @!attribute [rw] client_request_token
# A unique, case-sensitive identifier that you provide to ensure the
# idempotency of the operation. An idempotent operation completes no
# more than once.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @!attribute [rw] parallelism_configuration
# This configuration, if specified, overrides the parallelism
# configuration of the parent pipeline for this specific run.
# @return [Types::ParallelismConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartPipelineExecutionRequest AWS API Documentation
#
class StartPipelineExecutionRequest < Struct.new(
:pipeline_name,
:pipeline_execution_display_name,
:pipeline_parameters,
:pipeline_execution_description,
:client_request_token,
:parallelism_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StartPipelineExecutionResponse AWS API Documentation
#
class StartPipelineExecutionResponse < Struct.new(
:pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] auto_ml_job_name
# The name of the object you are requesting.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopAutoMLJobRequest AWS API Documentation
#
class StopAutoMLJobRequest < Struct.new(
:auto_ml_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] compilation_job_name
# The name of the model compilation job to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopCompilationJobRequest AWS API Documentation
#
class StopCompilationJobRequest < Struct.new(
:compilation_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_deployment_plan_name
# The name of the edge deployment plan to stop.
# @return [String]
#
# @!attribute [rw] stage_name
# The name of the stage to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopEdgeDeploymentStageRequest AWS API Documentation
#
class StopEdgeDeploymentStageRequest < Struct.new(
:edge_deployment_plan_name,
:stage_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] edge_packaging_job_name
# The name of the edge packaging job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopEdgePackagingJobRequest AWS API Documentation
#
class StopEdgePackagingJobRequest < Struct.new(
:edge_packaging_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hyper_parameter_tuning_job_name
# The name of the tuning job to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopHyperParameterTuningJobRequest AWS API Documentation
#
class StopHyperParameterTuningJobRequest < Struct.new(
:hyper_parameter_tuning_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name
# The name of the inference experiment to stop.
# @return [String]
#
# @!attribute [rw] model_variant_actions
# Array of key-value pairs, with names of variants mapped to actions.
# The possible actions are the following:
#
# * `Promote` - Promote the shadow variant to a production variant
#
# * `Remove` - Delete the variant
#
# * `Retain` - Keep the variant as it is
# @return [Hash<String,String>]
#
# @!attribute [rw] desired_model_variants
# An array of `ModelVariantConfig` objects. There is one for each
# variant that you want to deploy after the inference experiment
# stops. Each `ModelVariantConfig` describes the infrastructure
# configuration for deploying the corresponding variant.
# @return [Array<Types::ModelVariantConfig>]
#
# @!attribute [rw] desired_state
# The desired state of the experiment after stopping. The possible
# states are the following:
#
# * `Completed`: The experiment completed successfully
#
# * `Cancelled`: The experiment was canceled
# @return [String]
#
# @!attribute [rw] reason
# The reason for stopping the experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopInferenceExperimentRequest AWS API Documentation
#
class StopInferenceExperimentRequest < Struct.new(
:name,
:model_variant_actions,
:desired_model_variants,
:desired_state,
:reason)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] inference_experiment_arn
# The ARN of the stopped inference experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopInferenceExperimentResponse AWS API Documentation
#
class StopInferenceExperimentResponse < Struct.new(
:inference_experiment_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] job_name
# The name of the job you want to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopInferenceRecommendationsJobRequest AWS API Documentation
#
class StopInferenceRecommendationsJobRequest < Struct.new(
:job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] labeling_job_name
# The name of the labeling job to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopLabelingJobRequest AWS API Documentation
#
class StopLabelingJobRequest < Struct.new(
:labeling_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# The name of the schedule to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopMonitoringScheduleRequest AWS API Documentation
#
class StopMonitoringScheduleRequest < Struct.new(
:monitoring_schedule_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_name
# The name of the notebook instance to terminate.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopNotebookInstanceInput AWS API Documentation
#
class StopNotebookInstanceInput < Struct.new(
:notebook_instance_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @!attribute [rw] client_request_token
# A unique, case-sensitive identifier that you provide to ensure the
# idempotency of the operation. An idempotent operation completes no
# more than once.
#
# **A suitable default value is auto-generated.** You should normally
# not need to pass this option.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopPipelineExecutionRequest AWS API Documentation
#
class StopPipelineExecutionRequest < Struct.new(
:pipeline_execution_arn,
:client_request_token)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopPipelineExecutionResponse AWS API Documentation
#
class StopPipelineExecutionResponse < Struct.new(
:pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] processing_job_name
# The name of the processing job to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopProcessingJobRequest AWS API Documentation
#
class StopProcessingJobRequest < Struct.new(
:processing_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_name
# The name of the training job to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopTrainingJobRequest AWS API Documentation
#
class StopTrainingJobRequest < Struct.new(
:training_job_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] transform_job_name
# The name of the batch transform job to stop.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StopTransformJobRequest AWS API Documentation
#
class StopTransformJobRequest < Struct.new(
:transform_job_name)
SENSITIVE = []
include Aws::Structure
end
# Specifies a limit to how long a model training job or model
# compilation job can run. It also specifies how long a managed spot
# training job has to complete. When the job reaches the time limit,
# SageMaker ends the training or compilation job. Use this API to cap
# model training costs.
#
# To stop a training job, SageMaker sends the algorithm the `SIGTERM`
# signal, which delays job termination for 120 seconds. Algorithms can
# use this 120-second window to save the model artifacts, so the results
# of training are not lost.
#
# The training algorithms provided by 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`.
#
# <note markdown="1"> 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.
#
# </note>
#
# @!attribute [rw] max_runtime_in_seconds
# The maximum length of time, in seconds, that a training or
# compilation job can run before it is stopped.
#
# For compilation jobs, if the job does not complete during this time,
# a `TimeOut` error is generated. We recommend starting with 900
# seconds and increasing as necessary based on your model.
#
# For all other jobs, if the job does not complete during this time,
# SageMaker ends the job. When `RetryStrategy` is specified in the job
# request, `MaxRuntimeInSeconds` specifies the maximum time for all of
# the attempts in total, not each individual attempt. The default
# value is 1 day. The maximum value is 28 days.
#
# The maximum time that a `TrainingJob` can run in total, including
# any time spent publishing metrics or archiving and uploading models
# after it has been stopped, is 30 days.
# @return [Integer]
#
# @!attribute [rw] max_wait_time_in_seconds
# The maximum length of time, in seconds, that a managed Spot training
# job has to complete. It is the amount of time spent waiting for Spot
# capacity plus the amount of time the job can run. It must be equal
# to or greater than `MaxRuntimeInSeconds`. If the job does not
# complete during this time, SageMaker ends the job.
#
# When `RetryStrategy` is specified in the job request,
# `MaxWaitTimeInSeconds` specifies the maximum time for all of the
# attempts in total, not each individual attempt.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StoppingCondition AWS API Documentation
#
class StoppingCondition < Struct.new(
:max_runtime_in_seconds,
:max_wait_time_in_seconds)
SENSITIVE = []
include Aws::Structure
end
# Details of the Studio Lifecycle Configuration.
#
# @!attribute [rw] studio_lifecycle_config_arn
# The Amazon Resource Name (ARN) of the Lifecycle Configuration.
# @return [String]
#
# @!attribute [rw] studio_lifecycle_config_name
# The name of the Studio Lifecycle Configuration.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time of the Studio Lifecycle Configuration.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# This value is equivalent to CreationTime because Studio Lifecycle
# Configurations are immutable.
# @return [Time]
#
# @!attribute [rw] studio_lifecycle_config_app_type
# The App type to which the Lifecycle Configuration is attached.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StudioLifecycleConfigDetails AWS API Documentation
#
class StudioLifecycleConfigDetails < Struct.new(
:studio_lifecycle_config_arn,
:studio_lifecycle_config_name,
:creation_time,
:last_modified_time,
:studio_lifecycle_config_app_type)
SENSITIVE = []
include Aws::Structure
end
# Describes a work team of a vendor that does the a labelling job.
#
# @!attribute [rw] workteam_arn
# The Amazon Resource Name (ARN) of the vendor that you have
# subscribed.
# @return [String]
#
# @!attribute [rw] marketplace_title
# The title of the service provided by the vendor in the Amazon
# Marketplace.
# @return [String]
#
# @!attribute [rw] seller_name
# The name of the vendor in the Amazon Marketplace.
# @return [String]
#
# @!attribute [rw] marketplace_description
# The description of the vendor from the Amazon Marketplace.
# @return [String]
#
# @!attribute [rw] listing_id
# Marketplace product listing ID.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SubscribedWorkteam AWS API Documentation
#
class SubscribedWorkteam < Struct.new(
:workteam_arn,
:marketplace_title,
:seller_name,
:marketplace_description,
:listing_id)
SENSITIVE = []
include Aws::Structure
end
# Specified in the [GetSearchSuggestions][1] request. Limits the
# property names that are included in the response.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_GetSearchSuggestions.html
#
# @!attribute [rw] property_name_query
# Defines a property name hint. Only property names that begin with
# the specified hint are included in the response.
# @return [Types::PropertyNameQuery]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SuggestionQuery AWS API Documentation
#
class SuggestionQuery < Struct.new(
:property_name_query)
SENSITIVE = []
include Aws::Structure
end
# A tag object that consists of a key and an optional value, used to
# manage metadata for SageMaker Amazon Web Services 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 SageMaker resources, see [AddTags][1].
#
# For more information on adding metadata to your Amazon Web Services
# resources with tagging, see [Tagging Amazon Web Services
# resources][2]. For advice on best practices for managing Amazon Web
# Services resources with tagging, see [Tagging Best Practices:
# Implement an Effective Amazon Web Services Resource Tagging
# Strategy][3].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AddTags.html
# [2]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# [3]: https://d1.awsstatic.com/whitepapers/aws-tagging-best-practices.pdf
#
# @!attribute [rw] key
# The tag key. Tag keys must be unique per resource.
# @return [String]
#
# @!attribute [rw] value
# The tag value.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Tag AWS API Documentation
#
class Tag < Struct.new(
:key,
:value)
SENSITIVE = []
include Aws::Structure
end
# 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`.
#
# @!attribute [rw] os
# Specifies a target platform OS.
#
# * `LINUX`: Linux-based operating systems.
#
# * `ANDROID`: Android operating systems. Android API level can be
# specified using the `ANDROID_PLATFORM` compiler option. For
# example, `"CompilerOptions": \{'ANDROID_PLATFORM': 28\}`
# @return [String]
#
# @!attribute [rw] arch
# Specifies a target platform architecture.
#
# * `X86_64`: 64-bit version of the x86 instruction set.
#
# * `X86`: 32-bit version of the x86 instruction set.
#
# * `ARM64`: ARMv8 64-bit CPU.
#
# * `ARM_EABIHF`: ARMv7 32-bit, Hard Float.
#
# * `ARM_EABI`: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM
# platform.
# @return [String]
#
# @!attribute [rw] accelerator
# Specifies a target platform accelerator (optional).
#
# * `NVIDIA`: Nvidia graphics processing unit. It also requires
# `gpu-code`, `trt-ver`, `cuda-ver` compiler options
#
# * `MALI`: ARM Mali graphics processor
#
# * `INTEL_GRAPHICS`: Integrated Intel graphics
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TargetPlatform AWS API Documentation
#
class TargetPlatform < Struct.new(
:os,
:arch,
:accelerator)
SENSITIVE = []
include Aws::Structure
end
# The TensorBoard app settings.
#
# @!attribute [rw] default_resource_spec
# The default instance type and the Amazon Resource Name (ARN) of the
# SageMaker image created on the instance.
# @return [Types::ResourceSpec]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TensorBoardAppSettings AWS API Documentation
#
class TensorBoardAppSettings < Struct.new(
:default_resource_spec)
SENSITIVE = []
include Aws::Structure
end
# Configuration of storage locations for the Amazon SageMaker Debugger
# TensorBoard output data.
#
# @!attribute [rw] local_path
# Path to local storage location for tensorBoard output. Defaults to
# `/opt/ml/output/tensorboard`.
# @return [String]
#
# @!attribute [rw] s3_output_path
# Path to Amazon S3 storage location for TensorBoard output.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TensorBoardOutputConfig AWS API Documentation
#
class TensorBoardOutputConfig < Struct.new(
:local_path,
:s3_output_path)
SENSITIVE = []
include Aws::Structure
end
# Stores the configuration information for the text classification
# problem of an AutoML job using the V2 API.
#
# @!attribute [rw] completion_criteria
# How long a job is allowed to run, or how many candidates a job is
# allowed to generate.
# @return [Types::AutoMLJobCompletionCriteria]
#
# @!attribute [rw] content_column
# The name of the column used to provide the sentences to be
# classified. It should not be the same as the target column.
# @return [String]
#
# @!attribute [rw] target_label_column
# The name of the column used to provide the class labels. It should
# not be same as the content column.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TextClassificationJobConfig AWS API Documentation
#
class TextClassificationJobConfig < Struct.new(
:completion_criteria,
:content_column,
:target_label_column)
SENSITIVE = []
include Aws::Structure
end
# Time series forecast settings for the SageMaker Canvas application.
#
# @!attribute [rw] status
# Describes whether time series forecasting is enabled or disabled in
# the Canvas application.
# @return [String]
#
# @!attribute [rw] amazon_forecast_role_arn
# The IAM role that Canvas passes to Amazon Forecast for time series
# forecasting. By default, Canvas uses the execution role specified in
# the `UserProfile` that launches the Canvas application. If an
# execution role is not specified in the `UserProfile`, Canvas uses
# the execution role specified in the Domain that owns the
# `UserProfile`. To allow time series forecasting, this IAM role
# should have the [ AmazonSageMakerCanvasForecastAccess][1] policy
# attached and `forecast.amazonaws.com` added in the trust
# relationship as a service principal.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/security-iam-awsmanpol-canvas.html#security-iam-awsmanpol-AmazonSageMakerCanvasForecastAccess
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TimeSeriesForecastingSettings AWS API Documentation
#
class TimeSeriesForecastingSettings < Struct.new(
:status,
:amazon_forecast_role_arn)
SENSITIVE = []
include Aws::Structure
end
# Defines the traffic pattern of the load test.
#
# @!attribute [rw] traffic_type
# Defines the traffic patterns.
# @return [String]
#
# @!attribute [rw] phases
# Defines the phases traffic specification.
# @return [Array<Types::Phase>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrafficPattern AWS API Documentation
#
class TrafficPattern < Struct.new(
:traffic_type,
:phases)
SENSITIVE = []
include Aws::Structure
end
# Defines the traffic routing strategy during an endpoint deployment to
# shift traffic from the old fleet to the new fleet.
#
# @!attribute [rw] type
# Traffic routing strategy type.
#
# * `ALL_AT_ONCE`: Endpoint traffic shifts to the new fleet in a
# single step.
#
# * `CANARY`: Endpoint traffic shifts to the new fleet in two steps.
# The first step is the canary, which is a small portion of the
# traffic. The second step is the remainder of the traffic.
#
# * `LINEAR`: Endpoint traffic shifts to the new fleet in n steps of a
# configurable size.
# @return [String]
#
# @!attribute [rw] wait_interval_in_seconds
# The waiting time (in seconds) between incremental steps to turn on
# traffic on the new endpoint fleet.
# @return [Integer]
#
# @!attribute [rw] canary_size
# Batch size for the first step to turn on traffic on the new endpoint
# fleet. `Value` must be less than or equal to 50% of the variant's
# total instance count.
# @return [Types::CapacitySize]
#
# @!attribute [rw] linear_step_size
# Batch size for each step to turn on traffic on the new endpoint
# fleet. `Value` must be 10-50% of the variant's total instance
# count.
# @return [Types::CapacitySize]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrafficRoutingConfig AWS API Documentation
#
class TrafficRoutingConfig < Struct.new(
:type,
:wait_interval_in_seconds,
:canary_size,
:linear_step_size)
SENSITIVE = []
include Aws::Structure
end
# The configuration to use an image from a private Docker registry for a
# training job.
#
# @!attribute [rw] training_repository_access_mode
# The method that your training job will use to gain access to the
# images in your private Docker registry. For access to an image in a
# private Docker registry, set to `Vpc`.
# @return [String]
#
# @!attribute [rw] training_repository_auth_config
# An object containing authentication information for a private Docker
# registry containing your training images.
# @return [Types::TrainingRepositoryAuthConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingImageConfig AWS API Documentation
#
class TrainingImageConfig < Struct.new(
:training_repository_access_mode,
:training_repository_auth_config)
SENSITIVE = []
include Aws::Structure
end
# Contains information about a training job.
#
# @!attribute [rw] training_job_name
# The name of the training job.
# @return [String]
#
# @!attribute [rw] training_job_arn
# The Amazon Resource Name (ARN) of the training job.
# @return [String]
#
# @!attribute [rw] tuning_job_arn
# The Amazon Resource Name (ARN) of the associated hyperparameter
# tuning job if the training job was launched by a hyperparameter
# tuning job.
# @return [String]
#
# @!attribute [rw] labeling_job_arn
# The Amazon Resource Name (ARN) of the labeling job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# The Amazon Resource Name (ARN) of the job.
# @return [String]
#
# @!attribute [rw] model_artifacts
# Information about the Amazon S3 location that is configured for
# storing model artifacts.
# @return [Types::ModelArtifacts]
#
# @!attribute [rw] training_job_status
# The status of the training job.
#
# Training job statuses are:
#
# * `InProgress` - The training is in progress.
#
# * `Completed` - The training job has completed.
#
# * `Failed` - The training job has failed. To see the reason for the
# failure, see the `FailureReason` field in the response to a
# `DescribeTrainingJobResponse` call.
#
# * `Stopping` - The training job is stopping.
#
# * `Stopped` - The training job has stopped.
#
# For more detailed information, see `SecondaryStatus`.
# @return [String]
#
# @!attribute [rw] secondary_status
# Provides detailed information about the state of the training job.
# For detailed information about the secondary status of the training
# job, see `StatusMessage` under [SecondaryStatusTransition][1].
#
# SageMaker provides primary statuses and secondary statuses that
# apply to each of them:
#
# InProgress
# : * `Starting` - Starting the training job.
#
# * `Downloading` - An optional stage for algorithms that support
# `File` training input mode. It indicates that data is being
# downloaded to the ML storage volumes.
#
# * `Training` - Training is in progress.
#
# * `Uploading` - Training is complete and the model artifacts are
# being uploaded to the S3 location.
#
# Completed
# : * `Completed` - The training job has completed.
#
# ^
#
# Failed
# : * `Failed` - The training job has failed. The reason for the
# failure is returned in the `FailureReason` field of
# `DescribeTrainingJobResponse`.
#
# ^
#
# Stopped
# : * `MaxRuntimeExceeded` - The job stopped because it exceeded the
# maximum allowed runtime.
#
# * `Stopped` - The training job has stopped.
#
# Stopping
# : * `Stopping` - Stopping the training job.
#
# ^
#
# Valid values for `SecondaryStatus` are subject to change.
#
# We no longer support the following secondary statuses:
#
# * `LaunchingMLInstances`
#
# * `PreparingTrainingStack`
#
# * `DownloadingTrainingImage`
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_SecondaryStatusTransition.html
# @return [String]
#
# @!attribute [rw] failure_reason
# If the training job failed, the reason it failed.
# @return [String]
#
# @!attribute [rw] hyper_parameters
# Algorithm-specific parameters.
# @return [Hash<String,String>]
#
# @!attribute [rw] algorithm_specification
# Information about the algorithm used for training, and algorithm
# metadata.
# @return [Types::AlgorithmSpecification]
#
# @!attribute [rw] role_arn
# The Amazon Web Services Identity and Access Management (IAM) role
# configured for the training job.
# @return [String]
#
# @!attribute [rw] input_data_config
# An array of `Channel` objects that describes each data input
# channel.
# @return [Array<Types::Channel>]
#
# @!attribute [rw] output_data_config
# The S3 path where model artifacts that you configured when creating
# the job are stored. SageMaker creates subfolders for model
# artifacts.
# @return [Types::OutputDataConfig]
#
# @!attribute [rw] resource_config
# Resources, including ML compute instances and ML storage volumes,
# that are configured for model training.
# @return [Types::ResourceConfig]
#
# @!attribute [rw] vpc_config
# A [VpcConfig][1] object that specifies the VPC that this training
# job has access to. For more information, see [Protect Training Jobs
# by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
# @return [Types::VpcConfig]
#
# @!attribute [rw] stopping_condition
# Specifies a limit to how long a model training job can run. It also
# specifies how long a managed Spot training job has to complete. When
# the job reaches the time limit, SageMaker ends the training job. Use
# this API to cap model training costs.
#
# To stop a job, SageMaker sends the algorithm the `SIGTERM` signal,
# which delays job termination for 120 seconds. Algorithms can use
# this 120-second window to save the model artifacts, so the results
# of training are not lost.
# @return [Types::StoppingCondition]
#
# @!attribute [rw] creation_time
# A timestamp that indicates when the training job was created.
# @return [Time]
#
# @!attribute [rw] training_start_time
# Indicates the time when the training job starts on training
# instances. You are billed for the time interval between this time
# and the value of `TrainingEndTime`. The start time in CloudWatch
# Logs might be later than this time. The difference is due to the
# time it takes to download the training data and to the size of the
# training container.
# @return [Time]
#
# @!attribute [rw] training_end_time
# Indicates the time when the training job ends on training instances.
# You are billed for the time interval between the value of
# `TrainingStartTime` and this time. For successful jobs and stopped
# jobs, this is the time after model artifacts are uploaded. For
# failed jobs, this is the time when SageMaker detects a job failure.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# A timestamp that indicates when the status of the training job was
# last modified.
# @return [Time]
#
# @!attribute [rw] secondary_status_transitions
# A history of all of the secondary statuses that the training job has
# transitioned through.
# @return [Array<Types::SecondaryStatusTransition>]
#
# @!attribute [rw] final_metric_data_list
# A list of final metric values that are set when the training job
# completes. Used only if the training job was configured to use
# metrics.
# @return [Array<Types::MetricData>]
#
# @!attribute [rw] enable_network_isolation
# If the `TrainingJob` was created with network isolation, the value
# is set to `true`. If network isolation is enabled, nodes can't
# communicate beyond the VPC they run in.
# @return [Boolean]
#
# @!attribute [rw] enable_inter_container_traffic_encryption
# To encrypt all communications between ML compute instances in
# distributed training, choose `True`. Encryption provides greater
# security for distributed training, but training might take longer.
# How long it takes depends on the amount of communication between
# compute instances, especially if you use a deep learning algorithm
# in distributed training.
# @return [Boolean]
#
# @!attribute [rw] enable_managed_spot_training
# When true, enables managed spot training using Amazon EC2 Spot
# instances to run training jobs instead of on-demand instances. For
# more information, see [Managed Spot Training][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.html
# @return [Boolean]
#
# @!attribute [rw] checkpoint_config
# Contains information about the output location for managed spot
# training checkpoint data.
# @return [Types::CheckpointConfig]
#
# @!attribute [rw] training_time_in_seconds
# The training time in seconds.
# @return [Integer]
#
# @!attribute [rw] billable_time_in_seconds
# The billable time in seconds.
# @return [Integer]
#
# @!attribute [rw] debug_hook_config
# Configuration information for the Amazon SageMaker Debugger hook
# parameters, metric and tensor collections, and storage paths. To
# learn more about how to configure the `DebugHookConfig` parameter,
# see [Use the SageMaker and Debugger Configuration API Operations to
# Create, Update, and Debug Your Training Job][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/debugger-createtrainingjob-api.html
# @return [Types::DebugHookConfig]
#
# @!attribute [rw] experiment_config
# Associates a SageMaker job as a trial component with an experiment
# and trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
# @return [Types::ExperimentConfig]
#
# @!attribute [rw] debug_rule_configurations
# Information about the debug rule configuration.
# @return [Array<Types::DebugRuleConfiguration>]
#
# @!attribute [rw] tensor_board_output_config
# Configuration of storage locations for the Amazon SageMaker Debugger
# TensorBoard output data.
# @return [Types::TensorBoardOutputConfig]
#
# @!attribute [rw] debug_rule_evaluation_statuses
# Information about the evaluation status of the rules for the
# training job.
# @return [Array<Types::DebugRuleEvaluationStatus>]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container.
# @return [Hash<String,String>]
#
# @!attribute [rw] retry_strategy
# The number of times to retry the job when the job fails due to an
# `InternalServerError`.
# @return [Types::RetryStrategy]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingJob AWS API Documentation
#
class TrainingJob < Struct.new(
:training_job_name,
:training_job_arn,
:tuning_job_arn,
:labeling_job_arn,
:auto_ml_job_arn,
:model_artifacts,
:training_job_status,
:secondary_status,
:failure_reason,
:hyper_parameters,
:algorithm_specification,
:role_arn,
:input_data_config,
:output_data_config,
:resource_config,
:vpc_config,
:stopping_condition,
:creation_time,
:training_start_time,
:training_end_time,
:last_modified_time,
:secondary_status_transitions,
:final_metric_data_list,
:enable_network_isolation,
:enable_inter_container_traffic_encryption,
:enable_managed_spot_training,
:checkpoint_config,
:training_time_in_seconds,
:billable_time_in_seconds,
:debug_hook_config,
:experiment_config,
:debug_rule_configurations,
:tensor_board_output_config,
:debug_rule_evaluation_statuses,
:environment,
:retry_strategy,
:tags)
SENSITIVE = []
include Aws::Structure
end
# Defines the input needed to run a training job using the algorithm.
#
# @!attribute [rw] training_input_mode
# The training input mode that the algorithm supports. For more
# information about input modes, see [Algorithms][1].
#
# **Pipe mode**
#
# If an algorithm supports `Pipe` mode, Amazon SageMaker streams data
# directly from Amazon S3 to the container.
#
# **File mode**
#
# If an algorithm supports `File` mode, SageMaker downloads the
# training data from S3 to the provisioned ML storage volume, and
# mounts the directory to the Docker volume for the training
# container.
#
# You must provision the ML storage volume with sufficient capacity to
# accommodate the data downloaded from S3. In addition to the training
# data, the ML storage volume also stores the output model. The
# algorithm container uses the ML storage volume to also store
# intermediate information, if any.
#
# For distributed algorithms, training data is distributed uniformly.
# Your training duration is predictable if the input data objects
# sizes are approximately the same. SageMaker does not split the files
# any further for model training. If the object sizes are skewed,
# training won't be optimal as the data distribution is also skewed
# when one host in a training cluster is overloaded, thus becoming a
# bottleneck in training.
#
# **FastFile mode**
#
# If an algorithm supports `FastFile` mode, SageMaker streams data
# directly from S3 to the container with no code changes, and provides
# file system access to the data. Users can author their training
# script to interact with these files as if they were stored on disk.
#
# `FastFile` mode works best when the data is read sequentially.
# Augmented manifest files aren't supported. The startup time is
# lower when there are fewer files in the S3 bucket provided.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
# @return [String]
#
# @!attribute [rw] hyper_parameters
# The hyperparameters used for the training job.
# @return [Hash<String,String>]
#
# @!attribute [rw] input_data_config
# An array of `Channel` objects, each of which specifies an input
# source.
# @return [Array<Types::Channel>]
#
# @!attribute [rw] output_data_config
# the path to the S3 bucket where you want to store model artifacts.
# SageMaker creates subfolders for the artifacts.
# @return [Types::OutputDataConfig]
#
# @!attribute [rw] resource_config
# The resources, including the ML compute instances and ML storage
# volumes, to use for model training.
# @return [Types::ResourceConfig]
#
# @!attribute [rw] stopping_condition
# Specifies a limit to how long a model training job can run. It also
# specifies how long a managed Spot training job has to complete. When
# the job reaches the time limit, SageMaker ends the training job. Use
# this API to cap model training costs.
#
# To stop a job, SageMaker sends the algorithm the SIGTERM signal,
# which delays job termination for 120 seconds. Algorithms can use
# this 120-second window to save the model artifacts.
# @return [Types::StoppingCondition]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingJobDefinition AWS API Documentation
#
class TrainingJobDefinition < Struct.new(
:training_input_mode,
:hyper_parameters,
:input_data_config,
:output_data_config,
:resource_config,
:stopping_condition)
SENSITIVE = []
include Aws::Structure
end
# The numbers of training jobs launched by a hyperparameter tuning job,
# categorized by status.
#
# @!attribute [rw] completed
# The number of completed training jobs launched by the hyperparameter
# tuning job.
# @return [Integer]
#
# @!attribute [rw] in_progress
# The number of in-progress training jobs launched by a hyperparameter
# tuning job.
# @return [Integer]
#
# @!attribute [rw] retryable_error
# The number of training jobs that failed, but can be retried. A
# failed training job can be retried only if it failed because an
# internal service error occurred.
# @return [Integer]
#
# @!attribute [rw] non_retryable_error
# The number of training jobs that failed and can't be retried. A
# failed training job can't be retried if it failed because a client
# error occurred.
# @return [Integer]
#
# @!attribute [rw] stopped
# The number of training jobs launched by a hyperparameter tuning job
# that were manually stopped.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingJobStatusCounters AWS API Documentation
#
class TrainingJobStatusCounters < Struct.new(
:completed,
:in_progress,
:retryable_error,
:non_retryable_error,
:stopped)
SENSITIVE = []
include Aws::Structure
end
# Metadata for a training job step.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the training job that was run by
# this step execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingJobStepMetadata AWS API Documentation
#
class TrainingJobStepMetadata < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# Provides summary information about a training job.
#
# @!attribute [rw] training_job_name
# The name of the training job that you want a summary for.
# @return [String]
#
# @!attribute [rw] training_job_arn
# The Amazon Resource Name (ARN) of the training job.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the training job was created.
# @return [Time]
#
# @!attribute [rw] training_end_time
# A timestamp that shows when the training job ended. This field is
# set only if the training job has one of the terminal statuses
# (`Completed`, `Failed`, or `Stopped`).
# @return [Time]
#
# @!attribute [rw] last_modified_time
# Timestamp when the training job was last modified.
# @return [Time]
#
# @!attribute [rw] training_job_status
# The status of the training job.
# @return [String]
#
# @!attribute [rw] warm_pool_status
# The status of the warm pool associated with the training job.
# @return [Types::WarmPoolStatus]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingJobSummary AWS API Documentation
#
class TrainingJobSummary < Struct.new(
:training_job_name,
:training_job_arn,
:creation_time,
:training_end_time,
:last_modified_time,
:training_job_status,
:warm_pool_status)
SENSITIVE = []
include Aws::Structure
end
# An object containing authentication information for a private Docker
# registry.
#
# @!attribute [rw] training_repository_credentials_provider_arn
# The Amazon Resource Name (ARN) of an Amazon Web Services Lambda
# function used to give SageMaker access credentials to your private
# Docker registry.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingRepositoryAuthConfig AWS API Documentation
#
class TrainingRepositoryAuthConfig < Struct.new(
:training_repository_credentials_provider_arn)
SENSITIVE = []
include Aws::Structure
end
# Defines how the algorithm is used for a training job.
#
# @!attribute [rw] training_image
# The Amazon ECR registry path of the Docker image that contains the
# training algorithm.
# @return [String]
#
# @!attribute [rw] training_image_digest
# An MD5 hash of the training algorithm that identifies the Docker
# image used for training.
# @return [String]
#
# @!attribute [rw] supported_hyper_parameters
# A list of the `HyperParameterSpecification` objects, that define the
# supported hyperparameters. This is required if the algorithm
# supports automatic model tuning.>
# @return [Array<Types::HyperParameterSpecification>]
#
# @!attribute [rw] supported_training_instance_types
# A list of the instance types that this algorithm can use for
# training.
# @return [Array<String>]
#
# @!attribute [rw] supports_distributed_training
# Indicates whether the algorithm supports distributed training. If
# set to false, buyers can't request more than one instance during
# training.
# @return [Boolean]
#
# @!attribute [rw] metric_definitions
# A list of `MetricDefinition` objects, which are used for parsing
# metrics generated by the algorithm.
# @return [Array<Types::MetricDefinition>]
#
# @!attribute [rw] training_channels
# A list of `ChannelSpecification` objects, which specify the input
# sources to be used by the algorithm.
# @return [Array<Types::ChannelSpecification>]
#
# @!attribute [rw] supported_tuning_job_objective_metrics
# A list of the metrics that the algorithm emits that can be used as
# the objective metric in a hyperparameter tuning job.
# @return [Array<Types::HyperParameterTuningJobObjective>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingSpecification AWS API Documentation
#
class TrainingSpecification < Struct.new(
:training_image,
:training_image_digest,
:supported_hyper_parameters,
:supported_training_instance_types,
:supports_distributed_training,
:metric_definitions,
:training_channels,
:supported_tuning_job_objective_metrics)
SENSITIVE = []
include Aws::Structure
end
# Describes the location of the channel data.
#
# @!attribute [rw] s3_data_source
# The S3 location of the data source that is associated with a
# channel.
# @return [Types::TransformS3DataSource]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformDataSource AWS API Documentation
#
class TransformDataSource < Struct.new(
:s3_data_source)
SENSITIVE = []
include Aws::Structure
end
# Describes the input source of a transform job and the way the
# transform job consumes it.
#
# @!attribute [rw] data_source
# Describes the location of the channel data, which is, the S3
# location of the input data that the model can consume.
# @return [Types::TransformDataSource]
#
# @!attribute [rw] content_type
# The multipurpose internet mail extension (MIME) type of the data.
# Amazon SageMaker uses the MIME type with each http call to transfer
# data to the transform job.
# @return [String]
#
# @!attribute [rw] compression_type
# If your transform data is compressed, specify the compression type.
# Amazon SageMaker automatically decompresses the data for the
# transform job accordingly. The default value is `None`.
# @return [String]
#
# @!attribute [rw] split_type
# The method to use to split the transform job's data files into
# smaller batches. Splitting is necessary when the total size of each
# object is too large to fit in a single request. You can also use
# data splitting to improve performance by processing multiple
# concurrent mini-batches. The default value for `SplitType` is
# `None`, which indicates that input data files are not split, and
# request payloads contain the entire contents of an input object. Set
# the value of this parameter to `Line` to split records on a newline
# character boundary. `SplitType` also supports a number of
# record-oriented binary data formats. Currently, the supported record
# formats are:
#
# * RecordIO
#
# * TFRecord
#
# When splitting is enabled, the size of a mini-batch depends on the
# values of the `BatchStrategy` and `MaxPayloadInMB` parameters. When
# the value of `BatchStrategy` is `MultiRecord`, Amazon SageMaker
# sends the maximum number of records in each request, up to the
# `MaxPayloadInMB` limit. If the value of `BatchStrategy` is
# `SingleRecord`, Amazon SageMaker sends individual records in each
# request.
#
# <note markdown="1"> Some data formats represent a record as a binary payload wrapped
# with extra padding bytes. When splitting is applied to a binary data
# format, padding is removed if the value of `BatchStrategy` is set to
# `SingleRecord`. Padding is not removed if the value of
# `BatchStrategy` is set to `MultiRecord`.
#
# For more information about `RecordIO`, see [Create a Dataset Using
# RecordIO][1] in the MXNet documentation. For more information about
# `TFRecord`, see [Consuming TFRecord data][2] in the TensorFlow
# documentation.
#
# </note>
#
#
#
# [1]: https://mxnet.apache.org/api/faq/recordio
# [2]: https://www.tensorflow.org/guide/data#consuming_tfrecord_data
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformInput AWS API Documentation
#
class TransformInput < Struct.new(
:data_source,
:content_type,
:compression_type,
:split_type)
SENSITIVE = []
include Aws::Structure
end
# A batch transform job. For information about SageMaker batch
# transform, see [Use Batch Transform][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html
#
# @!attribute [rw] transform_job_name
# The name of the transform job.
# @return [String]
#
# @!attribute [rw] transform_job_arn
# The Amazon Resource Name (ARN) of the transform job.
# @return [String]
#
# @!attribute [rw] transform_job_status
# The status of the transform job.
#
# Transform job statuses are:
#
# * `InProgress` - The job is in progress.
#
# * `Completed` - The job has completed.
#
# * `Failed` - The transform job has failed. To see the reason for the
# failure, see the `FailureReason` field in the response to a
# `DescribeTransformJob` call.
#
# * `Stopping` - The transform job is stopping.
#
# * `Stopped` - The transform job has stopped.
# @return [String]
#
# @!attribute [rw] failure_reason
# If the transform job failed, the reason it failed.
# @return [String]
#
# @!attribute [rw] model_name
# The name of the model associated with the transform job.
# @return [String]
#
# @!attribute [rw] max_concurrent_transforms
# The maximum number of parallel requests that can be sent to each
# instance in a transform job. If `MaxConcurrentTransforms` is set to
# 0 or left unset, SageMaker checks the optional execution-parameters
# to determine the settings for your chosen algorithm. If the
# execution-parameters endpoint is not enabled, the default value is
# 1. For built-in algorithms, you don't need to set a value for
# `MaxConcurrentTransforms`.
# @return [Integer]
#
# @!attribute [rw] model_client_config
# Configures the timeout and maximum number of retries for processing
# a transform job invocation.
# @return [Types::ModelClientConfig]
#
# @!attribute [rw] max_payload_in_mb
# The maximum allowed size of the payload, in MB. A payload is the
# data portion of a record (without metadata). The value in
# `MaxPayloadInMB` must be greater than, or equal to, the size of a
# single record. To estimate the size of a record in MB, divide the
# size of your dataset by the number of records. To ensure that the
# records fit within the maximum payload size, we recommend using a
# slightly larger value. The default value is 6 MB. For cases where
# the payload might be arbitrarily large and is transmitted using HTTP
# chunked encoding, set the value to 0. This feature works only in
# supported algorithms. Currently, SageMaker built-in algorithms do
# not support HTTP chunked encoding.
# @return [Integer]
#
# @!attribute [rw] batch_strategy
# Specifies the number of records to include in a mini-batch for an
# HTTP inference request. A record is a single unit of input data that
# inference can be made on. For example, a single line in a CSV file
# is a record.
# @return [String]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container. We support
# up to 16 key and values entries in the map.
# @return [Hash<String,String>]
#
# @!attribute [rw] transform_input
# Describes the input source of a transform job and the way the
# transform job consumes it.
# @return [Types::TransformInput]
#
# @!attribute [rw] transform_output
# Describes the results of a transform job.
# @return [Types::TransformOutput]
#
# @!attribute [rw] transform_resources
# Describes the resources, including ML instance types and ML instance
# count, to use for transform job.
# @return [Types::TransformResources]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the transform Job was created.
# @return [Time]
#
# @!attribute [rw] transform_start_time
# Indicates when the transform job starts on ML instances. You are
# billed for the time interval between this time and the value of
# `TransformEndTime`.
# @return [Time]
#
# @!attribute [rw] transform_end_time
# Indicates when the transform job has been completed, or has stopped
# or failed. You are billed for the time interval between this time
# and the value of `TransformStartTime`.
# @return [Time]
#
# @!attribute [rw] labeling_job_arn
# The Amazon Resource Name (ARN) of the labeling job that created the
# transform job.
# @return [String]
#
# @!attribute [rw] auto_ml_job_arn
# The Amazon Resource Name (ARN) of the AutoML job that created the
# transform job.
# @return [String]
#
# @!attribute [rw] 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][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html
# @return [Types::DataProcessing]
#
# @!attribute [rw] experiment_config
# Associates a SageMaker job as a trial component with an experiment
# and trial. Specified when you call the following APIs:
#
# * [CreateProcessingJob][1]
#
# * [CreateTrainingJob][2]
#
# * [CreateTransformJob][3]
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
# [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
# @return [Types::ExperimentConfig]
#
# @!attribute [rw] tags
# A list of tags associated with the transform job.
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformJob AWS API Documentation
#
class TransformJob < Struct.new(
:transform_job_name,
:transform_job_arn,
:transform_job_status,
:failure_reason,
:model_name,
:max_concurrent_transforms,
:model_client_config,
:max_payload_in_mb,
:batch_strategy,
:environment,
:transform_input,
:transform_output,
:transform_resources,
:creation_time,
:transform_start_time,
:transform_end_time,
:labeling_job_arn,
:auto_ml_job_arn,
:data_processing,
:experiment_config,
:tags)
SENSITIVE = []
include Aws::Structure
end
# Defines the input needed to run a transform job using the inference
# specification specified in the algorithm.
#
# @!attribute [rw] max_concurrent_transforms
# The maximum number of parallel requests that can be sent to each
# instance in a transform job. The default value is 1.
# @return [Integer]
#
# @!attribute [rw] max_payload_in_mb
# The maximum payload size allowed, in MB. A payload is the data
# portion of a record (without metadata).
# @return [Integer]
#
# @!attribute [rw] batch_strategy
# A string that determines the number of records included in a single
# mini-batch.
#
# `SingleRecord` means only one record is used per mini-batch.
# `MultiRecord` means a mini-batch is set to contain as many records
# that can fit within the `MaxPayloadInMB` limit.
# @return [String]
#
# @!attribute [rw] environment
# The environment variables to set in the Docker container. We support
# up to 16 key and values entries in the map.
# @return [Hash<String,String>]
#
# @!attribute [rw] transform_input
# A description of the input source and the way the transform job
# consumes it.
# @return [Types::TransformInput]
#
# @!attribute [rw] transform_output
# Identifies the Amazon S3 location where you want Amazon SageMaker to
# save the results from the transform job.
# @return [Types::TransformOutput]
#
# @!attribute [rw] transform_resources
# Identifies the ML compute instances for the transform job.
# @return [Types::TransformResources]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformJobDefinition AWS API Documentation
#
class TransformJobDefinition < Struct.new(
:max_concurrent_transforms,
:max_payload_in_mb,
:batch_strategy,
:environment,
:transform_input,
:transform_output,
:transform_resources)
SENSITIVE = []
include Aws::Structure
end
# Metadata for a transform job step.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the transform job that was run by
# this step execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformJobStepMetadata AWS API Documentation
#
class TransformJobStepMetadata < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# Provides a summary of a transform job. Multiple `TransformJobSummary`
# objects are returned as a list after in response to a
# [ListTransformJobs][1] call.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListTransformJobs.html
#
# @!attribute [rw] transform_job_name
# The name of the transform job.
# @return [String]
#
# @!attribute [rw] transform_job_arn
# The Amazon Resource Name (ARN) of the transform job.
# @return [String]
#
# @!attribute [rw] creation_time
# A timestamp that shows when the transform Job was created.
# @return [Time]
#
# @!attribute [rw] transform_end_time
# Indicates when the transform job ends on compute instances. For
# successful jobs and stopped jobs, this is the exact time recorded
# after the results are uploaded. For failed jobs, this is when Amazon
# SageMaker detected that the job failed.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# Indicates when the transform job was last modified.
# @return [Time]
#
# @!attribute [rw] transform_job_status
# The status of the transform job.
# @return [String]
#
# @!attribute [rw] failure_reason
# If the transform job failed, the reason it failed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformJobSummary AWS API Documentation
#
class TransformJobSummary < Struct.new(
:transform_job_name,
:transform_job_arn,
:creation_time,
:transform_end_time,
:last_modified_time,
:transform_job_status,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# Describes the results of a transform job.
#
# @!attribute [rw] s3_output_path
# The Amazon S3 path where you want Amazon SageMaker to store the
# results of the transform job. For example,
# `s3://bucket-name/key-name-prefix`.
#
# For every S3 object used as input for the transform job, batch
# transform stores the transformed data with an .`out` suffix in a
# corresponding subfolder in the location in the output prefix. For
# example, for the input data stored at
# `s3://bucket-name/input-name-prefix/dataset01/data.csv`, batch
# transform stores the transformed data at
# `s3://bucket-name/output-name-prefix/input-name-prefix/data.csv.out`.
# Batch transform doesn't upload partially processed objects. For an
# input S3 object that contains multiple records, it creates an .`out`
# file only if the transform job succeeds on the entire file. When the
# input contains multiple S3 objects, the batch transform job
# processes the listed S3 objects and uploads only the output for
# successfully processed objects. If any object fails in the transform
# job batch transform marks the job as failed to prompt investigation.
# @return [String]
#
# @!attribute [rw] accept
# The MIME type used to specify the output data. Amazon SageMaker uses
# the MIME type with each http call to transfer data from the
# transform job.
# @return [String]
#
# @!attribute [rw] assemble_with
# Defines how to assemble the results of the transform job as a single
# S3 object. Choose a format that is most convenient to you. To
# concatenate the results in binary format, specify `None`. To add a
# newline character at the end of every transformed record, specify
# `Line`.
# @return [String]
#
# @!attribute [rw] kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt the model artifacts
# at rest using Amazon S3 server-side encryption. The `KmsKeyId` can
# be any of the following formats:
#
# * Key ID: `1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Key ARN:
# `arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Alias name: `alias/ExampleAlias`
#
# * Alias name ARN:
# `arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias`
#
# If you don't provide a KMS key ID, Amazon SageMaker uses the
# default KMS key for Amazon S3 for your role's account. For more
# information, see [KMS-Managed Encryption Keys][1] in the *Amazon
# Simple Storage Service Developer Guide.*
#
# The KMS key policy must grant permission to the IAM role that you
# specify in your [CreateModel][2] request. For more information, see
# [Using Key Policies in Amazon Web Services KMS][3] in the *Amazon
# Web Services Key Management Service Developer Guide*.
#
#
#
# [1]: https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html
# [3]: https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformOutput AWS API Documentation
#
class TransformOutput < Struct.new(
:s3_output_path,
:accept,
:assemble_with,
:kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# Describes the resources, including ML instance types and ML instance
# count, to use for transform job.
#
# @!attribute [rw] instance_type
# The ML compute instance type for the transform job. If you are using
# built-in algorithms to transform moderately sized datasets, we
# recommend using ml.m4.xlarge or `ml.m5.large`instance types.
# @return [String]
#
# @!attribute [rw] instance_count
# The number of ML compute instances to use in the transform job. The
# default value is `1`, and the maximum is `100`. For distributed
# transform jobs, specify a value greater than `1`.
# @return [Integer]
#
# @!attribute [rw] volume_kms_key_id
# The Amazon Web Services Key Management Service (Amazon Web Services
# KMS) key that Amazon SageMaker uses to encrypt model data on the
# storage volume attached to the ML compute instance(s) that run the
# batch transform job.
#
# <note markdown="1"> Certain Nitro-based instances include local storage, dependent on
# the instance type. Local storage volumes are encrypted using a
# hardware module on the instance. You can't request a
# `VolumeKmsKeyId` when using an instance type with local storage.
#
# For a list of instance types that support local instance storage,
# see [Instance Store Volumes][1].
#
# For more information about local instance storage encryption, see
# [SSD Instance Store Volumes][2].
#
# </note>
#
# The `VolumeKmsKeyId` can be any of the following formats:
#
# * Key ID: `1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Key ARN:
# `arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab`
#
# * Alias name: `alias/ExampleAlias`
#
# * Alias name ARN:
# `arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias`
#
#
#
# [1]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes
# [2]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ssd-instance-store.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformResources AWS API Documentation
#
class TransformResources < Struct.new(
:instance_type,
:instance_count,
:volume_kms_key_id)
SENSITIVE = []
include Aws::Structure
end
# Describes the S3 data source.
#
# @!attribute [rw] s3_data_type
# If you choose `S3Prefix`, `S3Uri` identifies a key name prefix.
# Amazon SageMaker uses all objects with the specified key name prefix
# for batch transform.
#
# If you choose `ManifestFile`, `S3Uri` identifies an object that is a
# manifest file containing a list of object keys that you want Amazon
# SageMaker to use for batch transform.
#
# The following values are compatible: `ManifestFile`, `S3Prefix`
#
# The following value is not compatible: `AugmentedManifestFile`
# @return [String]
#
# @!attribute [rw] s3_uri
# Depending on the value specified for the `S3DataType`, identifies
# either a key name prefix or a manifest. For example:
#
# * A key name prefix might look like this:
# `s3://bucketname/exampleprefix`.
#
# * A manifest might look like this:
# `s3://bucketname/example.manifest`
#
# The manifest is an S3 object which is a JSON file with the
# following format:
#
# `[ \{"prefix": "s3://customer_bucket/some/prefix/"\},`
#
# `"relative/path/to/custdata-1",`
#
# `"relative/path/custdata-2",`
#
# `...`
#
# `"relative/path/custdata-N"`
#
# `]`
#
# The preceding JSON matches the following `S3Uris`:
#
# `s3://customer_bucket/some/prefix/relative/path/to/custdata-1`
#
# `s3://customer_bucket/some/prefix/relative/path/custdata-2`
#
# `...`
#
# `s3://customer_bucket/some/prefix/relative/path/custdata-N`
#
# The complete set of `S3Uris` in this manifest constitutes the
# input data for the channel for this datasource. The object that
# each `S3Uris` points to must be readable by the IAM role that
# Amazon SageMaker uses to perform tasks on your behalf.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TransformS3DataSource AWS API Documentation
#
class TransformS3DataSource < Struct.new(
:s3_data_type,
:s3_uri)
SENSITIVE = []
include Aws::Structure
end
# The properties of a trial as returned by the [Search][1] API.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
#
# @!attribute [rw] trial_name
# The name of the trial.
# @return [String]
#
# @!attribute [rw] trial_arn
# The Amazon Resource Name (ARN) of the trial.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the trial as displayed. If `DisplayName` isn't
# specified, `TrialName` is displayed.
# @return [String]
#
# @!attribute [rw] experiment_name
# The name of the experiment the trial is part of.
# @return [String]
#
# @!attribute [rw] source
# The source of the trial.
# @return [Types::TrialSource]
#
# @!attribute [rw] creation_time
# When the trial was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Who created the trial.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# Who last modified the trial.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] tags
# The list of tags that are associated with the trial. You can use
# [Search][1] API to search on the tags.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] trial_component_summaries
# A list of the components associated with the trial. For each
# component, a summary of the component's properties is included.
# @return [Array<Types::TrialComponentSimpleSummary>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Trial AWS API Documentation
#
class Trial < Struct.new(
:trial_name,
:trial_arn,
:display_name,
:experiment_name,
:source,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:metadata_properties,
:tags,
:trial_component_summaries)
SENSITIVE = []
include Aws::Structure
end
# The properties of a trial component as returned by the [Search][1]
# API.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
#
# @!attribute [rw] trial_component_name
# The name of the trial component.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the component as displayed. If `DisplayName` isn't
# specified, `TrialComponentName` is displayed.
# @return [String]
#
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the trial component.
# @return [String]
#
# @!attribute [rw] source
# The Amazon Resource Name (ARN) and job type of the source of the
# component.
# @return [Types::TrialComponentSource]
#
# @!attribute [rw] status
# The status of the trial component.
# @return [Types::TrialComponentStatus]
#
# @!attribute [rw] start_time
# When the component started.
# @return [Time]
#
# @!attribute [rw] end_time
# When the component ended.
# @return [Time]
#
# @!attribute [rw] creation_time
# When the component was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Who created the trial component.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the component was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @!attribute [rw] parameters
# The hyperparameters of the component.
# @return [Hash<String,Types::TrialComponentParameterValue>]
#
# @!attribute [rw] input_artifacts
# The input artifacts of the component.
# @return [Hash<String,Types::TrialComponentArtifact>]
#
# @!attribute [rw] output_artifacts
# The output artifacts of the component.
# @return [Hash<String,Types::TrialComponentArtifact>]
#
# @!attribute [rw] metrics
# The metrics for the component.
# @return [Array<Types::TrialComponentMetricSummary>]
#
# @!attribute [rw] metadata_properties
# Metadata properties of the tracking entity, trial, or trial
# component.
# @return [Types::MetadataProperties]
#
# @!attribute [rw] source_detail
# Details of the source of the component.
# @return [Types::TrialComponentSourceDetail]
#
# @!attribute [rw] lineage_group_arn
# The Amazon Resource Name (ARN) of the lineage group resource.
# @return [String]
#
# @!attribute [rw] tags
# The list of tags that are associated with the component. You can use
# [Search][1] API to search on the tags.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_Search.html
# @return [Array<Types::Tag>]
#
# @!attribute [rw] parents
# An array of the parents of the component. A parent is a trial the
# component is associated with and the experiment the trial is part
# of. A component might not have any parents.
# @return [Array<Types::Parent>]
#
# @!attribute [rw] run_name
# The name of the experiment run.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponent AWS API Documentation
#
class TrialComponent < Struct.new(
:trial_component_name,
:display_name,
:trial_component_arn,
:source,
:status,
:start_time,
:end_time,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by,
:parameters,
:input_artifacts,
:output_artifacts,
:metrics,
:metadata_properties,
:source_detail,
:lineage_group_arn,
:tags,
:parents,
:run_name)
SENSITIVE = []
include Aws::Structure
end
# Represents an input or output artifact of a trial component. You
# specify `TrialComponentArtifact` as part of the `InputArtifacts` and
# `OutputArtifacts` parameters in the [CreateTrialComponent][1] request.
#
# Examples of input artifacts are datasets, algorithms, hyperparameters,
# source code, and instance types. Examples of output artifacts are
# metrics, snapshots, logs, and images.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrialComponent.html
#
# @!attribute [rw] media_type
# The media type of the artifact, which indicates the type of data in
# the artifact file. The media type consists of a *type* and a
# *subtype* concatenated with a slash (/) character, for example,
# text/csv, image/jpeg, and s3/uri. The type specifies the category of
# the media. The subtype specifies the kind of data.
# @return [String]
#
# @!attribute [rw] value
# The location of the artifact.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponentArtifact AWS API Documentation
#
class TrialComponentArtifact < Struct.new(
:media_type,
:value)
SENSITIVE = []
include Aws::Structure
end
# A summary of the metrics of a trial component.
#
# @!attribute [rw] metric_name
# The name of the metric.
# @return [String]
#
# @!attribute [rw] source_arn
# The Amazon Resource Name (ARN) of the source.
# @return [String]
#
# @!attribute [rw] time_stamp
# When the metric was last updated.
# @return [Time]
#
# @!attribute [rw] max
# The maximum value of the metric.
# @return [Float]
#
# @!attribute [rw] min
# The minimum value of the metric.
# @return [Float]
#
# @!attribute [rw] last
# The most recent value of the metric.
# @return [Float]
#
# @!attribute [rw] count
# The number of samples used to generate the metric.
# @return [Integer]
#
# @!attribute [rw] avg
# The average value of the metric.
# @return [Float]
#
# @!attribute [rw] std_dev
# The standard deviation of the metric.
# @return [Float]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponentMetricSummary AWS API Documentation
#
class TrialComponentMetricSummary < Struct.new(
:metric_name,
:source_arn,
:time_stamp,
:max,
:min,
:last,
:count,
:avg,
:std_dev)
SENSITIVE = []
include Aws::Structure
end
# The value of a hyperparameter. Only one of `NumberValue` or
# `StringValue` can be specified.
#
# This object is specified in the [CreateTrialComponent][1] request.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrialComponent.html
#
# @!attribute [rw] string_value
# The string value of a categorical hyperparameter. If you specify a
# value for this parameter, you can't specify the `NumberValue`
# parameter.
# @return [String]
#
# @!attribute [rw] number_value
# The numeric value of a numeric hyperparameter. If you specify a
# value for this parameter, you can't specify the `StringValue`
# parameter.
# @return [Float]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponentParameterValue AWS API Documentation
#
class TrialComponentParameterValue < Struct.new(
:string_value,
:number_value)
SENSITIVE = []
include Aws::Structure
end
# A short summary of a trial component.
#
# @!attribute [rw] trial_component_name
# The name of the trial component.
# @return [String]
#
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the trial component.
# @return [String]
#
# @!attribute [rw] trial_component_source
# The Amazon Resource Name (ARN) and job type of the source of a trial
# component.
# @return [Types::TrialComponentSource]
#
# @!attribute [rw] creation_time
# When the component was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
# @return [Types::UserContext]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponentSimpleSummary AWS API Documentation
#
class TrialComponentSimpleSummary < Struct.new(
:trial_component_name,
:trial_component_arn,
:trial_component_source,
:creation_time,
:created_by)
SENSITIVE = []
include Aws::Structure
end
# The Amazon Resource Name (ARN) and job type of the source of a trial
# component.
#
# @!attribute [rw] source_arn
# The source Amazon Resource Name (ARN).
# @return [String]
#
# @!attribute [rw] source_type
# The source job type.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponentSource AWS API Documentation
#
class TrialComponentSource < Struct.new(
:source_arn,
:source_type)
SENSITIVE = []
include Aws::Structure
end
# Detailed information about the source of a trial component. Either
# `ProcessingJob` or `TrainingJob` is returned.
#
# @!attribute [rw] source_arn
# The Amazon Resource Name (ARN) of the source.
# @return [String]
#
# @!attribute [rw] training_job
# Information about a training job that's the source of a trial
# component.
# @return [Types::TrainingJob]
#
# @!attribute [rw] processing_job
# Information about a processing job that's the source of a trial
# component.
# @return [Types::ProcessingJob]
#
# @!attribute [rw] transform_job
# Information about a transform job that's the source of a trial
# component.
# @return [Types::TransformJob]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponentSourceDetail AWS API Documentation
#
class TrialComponentSourceDetail < Struct.new(
:source_arn,
:training_job,
:processing_job,
:transform_job)
SENSITIVE = []
include Aws::Structure
end
# The status of the trial component.
#
# @!attribute [rw] primary_status
# The status of the trial component.
# @return [String]
#
# @!attribute [rw] message
# If the component failed, a message describing why.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponentStatus AWS API Documentation
#
class TrialComponentStatus < Struct.new(
:primary_status,
:message)
SENSITIVE = []
include Aws::Structure
end
# A summary of the properties of a trial component. To get all the
# properties, call the [DescribeTrialComponent][1] API and provide the
# `TrialComponentName`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTrialComponent.html
#
# @!attribute [rw] trial_component_name
# The name of the trial component.
# @return [String]
#
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the trial component.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the component as displayed. If `DisplayName` isn't
# specified, `TrialComponentName` is displayed.
# @return [String]
#
# @!attribute [rw] trial_component_source
# The Amazon Resource Name (ARN) and job type of the source of a trial
# component.
# @return [Types::TrialComponentSource]
#
# @!attribute [rw] status
# The status of the component. States include:
#
# * InProgress
#
# * Completed
#
# * Failed
# @return [Types::TrialComponentStatus]
#
# @!attribute [rw] start_time
# When the component started.
# @return [Time]
#
# @!attribute [rw] end_time
# When the component ended.
# @return [Time]
#
# @!attribute [rw] creation_time
# When the component was created.
# @return [Time]
#
# @!attribute [rw] created_by
# Who created the trial component.
# @return [Types::UserContext]
#
# @!attribute [rw] last_modified_time
# When the component was last modified.
# @return [Time]
#
# @!attribute [rw] last_modified_by
# Who last modified the component.
# @return [Types::UserContext]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialComponentSummary AWS API Documentation
#
class TrialComponentSummary < Struct.new(
:trial_component_name,
:trial_component_arn,
:display_name,
:trial_component_source,
:status,
:start_time,
:end_time,
:creation_time,
:created_by,
:last_modified_time,
:last_modified_by)
SENSITIVE = []
include Aws::Structure
end
# The source of the trial.
#
# @!attribute [rw] source_arn
# The Amazon Resource Name (ARN) of the source.
# @return [String]
#
# @!attribute [rw] source_type
# The source job type.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialSource AWS API Documentation
#
class TrialSource < Struct.new(
:source_arn,
:source_type)
SENSITIVE = []
include Aws::Structure
end
# A summary of the properties of a trial. To get the complete set of
# properties, call the [DescribeTrial][1] API and provide the
# `TrialName`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeTrial.html
#
# @!attribute [rw] trial_arn
# The Amazon Resource Name (ARN) of the trial.
# @return [String]
#
# @!attribute [rw] trial_name
# The name of the trial.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the trial as displayed. If `DisplayName` isn't
# specified, `TrialName` is displayed.
# @return [String]
#
# @!attribute [rw] trial_source
# The source of the trial.
# @return [Types::TrialSource]
#
# @!attribute [rw] creation_time
# When the trial was created.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# When the trial was last modified.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialSummary AWS API Documentation
#
class TrialSummary < Struct.new(
:trial_arn,
:trial_name,
:display_name,
:trial_source,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# The job completion criteria.
#
# @!attribute [rw] target_objective_metric_value
# The value of the objective metric.
# @return [Float]
#
# @!attribute [rw] best_objective_not_improving
# A flag to stop your hyperparameter tuning job if model performance
# fails to improve as evaluated against an objective function.
# @return [Types::BestObjectiveNotImproving]
#
# @!attribute [rw] convergence_detected
# A flag to top your hyperparameter tuning job if automatic model
# tuning (AMT) has detected that your model has converged as evaluated
# against your objective function.
# @return [Types::ConvergenceDetected]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TuningJobCompletionCriteria AWS API Documentation
#
class TuningJobCompletionCriteria < Struct.new(
:target_objective_metric_value,
:best_objective_not_improving,
:convergence_detected)
SENSITIVE = []
include Aws::Structure
end
# Metadata for a tuning step.
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the tuning job that was run by
# this step execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TuningJobStepMetaData AWS API Documentation
#
class TuningJobStepMetaData < Struct.new(
:arn)
SENSITIVE = []
include Aws::Structure
end
# Represents an amount of money in United States dollars.
#
# @!attribute [rw] dollars
# The whole number of dollars in the amount.
# @return [Integer]
#
# @!attribute [rw] cents
# The fractional portion, in cents, of the amount.
# @return [Integer]
#
# @!attribute [rw] tenth_fractions_of_a_cent
# Fractions of a cent, in tenths.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/USD AWS API Documentation
#
class USD < Struct.new(
:dollars,
:cents,
:tenth_fractions_of_a_cent)
SENSITIVE = []
include Aws::Structure
end
# Provided configuration information for the worker UI for a labeling
# job. Provide either `HumanTaskUiArn` or `UiTemplateS3Uri`.
#
# For named entity recognition, 3D point cloud and video frame labeling
# jobs, use `HumanTaskUiArn`.
#
# For all other Ground Truth built-in task types and custom task types,
# use `UiTemplateS3Uri` to specify the location of a worker task
# template in Amazon S3.
#
# @!attribute [rw] ui_template_s3_uri
# The Amazon S3 bucket location of the UI template, or worker task
# template. This is the template used to render the worker UI and
# tools for labeling job tasks. For more information about the
# contents of a UI template, see [ Creating Your Custom Labeling Task
# Template][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step2.html
# @return [String]
#
# @!attribute [rw] human_task_ui_arn
# The ARN of the worker task template used to render the worker UI and
# tools for labeling job tasks.
#
# Use this parameter when you are creating a labeling job for named
# entity recognition, 3D point cloud and video frame labeling jobs.
# Use your labeling job task type to select one of the following ARNs
# and use it with this parameter when you create a labeling job.
# Replace `aws-region` with the Amazon Web Services Region you are
# creating your labeling job in. For example, replace `aws-region`
# with `us-west-1` if you create a labeling job in US West (N.
# California).
#
# **Named Entity Recognition**
#
# Use the following `HumanTaskUiArn` for named entity recognition
# labeling jobs:
#
# `arn:aws:sagemaker:aws-region:394669845002:human-task-ui/NamedEntityRecognition`
#
# **3D Point Cloud HumanTaskUiArns**
#
# Use this `HumanTaskUiArn` for 3D point cloud object detection and 3D
# point cloud object detection adjustment labeling jobs.
#
# * `arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectDetection`
#
# ^
#
# Use this `HumanTaskUiArn` for 3D point cloud object tracking and 3D
# point cloud object tracking adjustment labeling jobs.
#
# * `arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudObjectTracking`
#
# ^
#
# Use this `HumanTaskUiArn` for 3D point cloud semantic segmentation
# and 3D point cloud semantic segmentation adjustment labeling jobs.
#
# * `arn:aws:sagemaker:aws-region:394669845002:human-task-ui/PointCloudSemanticSegmentation`
#
# ^
#
# **Video Frame HumanTaskUiArns**
#
# Use this `HumanTaskUiArn` for video frame object detection and video
# frame object detection adjustment labeling jobs.
#
# * `arn:aws:sagemaker:region:394669845002:human-task-ui/VideoObjectDetection`
#
# ^
#
# Use this `HumanTaskUiArn` for video frame object tracking and video
# frame object tracking adjustment labeling jobs.
#
# * `arn:aws:sagemaker:aws-region:394669845002:human-task-ui/VideoObjectTracking`
#
# ^
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UiConfig AWS API Documentation
#
class UiConfig < Struct.new(
:ui_template_s3_uri,
:human_task_ui_arn)
SENSITIVE = []
include Aws::Structure
end
# The Liquid template for the worker user interface.
#
# @!attribute [rw] content
# The content of the Liquid template for the worker user interface.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UiTemplate AWS API Documentation
#
class UiTemplate < Struct.new(
:content)
SENSITIVE = []
include Aws::Structure
end
# Container for user interface template information.
#
# @!attribute [rw] url
# The URL for the user interface template.
# @return [String]
#
# @!attribute [rw] content_sha_256
# The SHA-256 digest of the contents of the template.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UiTemplateInfo AWS API Documentation
#
class UiTemplateInfo < Struct.new(
:url,
:content_sha_256)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_name
# The name of the action to update.
# @return [String]
#
# @!attribute [rw] description
# The new description for the action.
# @return [String]
#
# @!attribute [rw] status
# The new status for the action.
# @return [String]
#
# @!attribute [rw] properties
# The new list of properties. Overwrites the current property list.
# @return [Hash<String,String>]
#
# @!attribute [rw] properties_to_remove
# A list of properties to remove.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateActionRequest AWS API Documentation
#
class UpdateActionRequest < Struct.new(
:action_name,
:description,
:status,
:properties,
:properties_to_remove)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] action_arn
# The Amazon Resource Name (ARN) of the action.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateActionResponse AWS API Documentation
#
class UpdateActionResponse < Struct.new(
:action_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_image_config_name
# The name of the AppImageConfig to update.
# @return [String]
#
# @!attribute [rw] kernel_gateway_image_config
# The new KernelGateway app to run on the image.
# @return [Types::KernelGatewayImageConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateAppImageConfigRequest AWS API Documentation
#
class UpdateAppImageConfigRequest < Struct.new(
:app_image_config_name,
:kernel_gateway_image_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] app_image_config_arn
# The Amazon Resource Name (ARN) for the AppImageConfig.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateAppImageConfigResponse AWS API Documentation
#
class UpdateAppImageConfigResponse < Struct.new(
:app_image_config_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_arn
# The Amazon Resource Name (ARN) of the artifact to update.
# @return [String]
#
# @!attribute [rw] artifact_name
# The new name for the artifact.
# @return [String]
#
# @!attribute [rw] properties
# The new list of properties. Overwrites the current property list.
# @return [Hash<String,String>]
#
# @!attribute [rw] properties_to_remove
# A list of properties to remove.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateArtifactRequest AWS API Documentation
#
class UpdateArtifactRequest < Struct.new(
:artifact_arn,
:artifact_name,
:properties,
:properties_to_remove)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] artifact_arn
# The Amazon Resource Name (ARN) of the artifact.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateArtifactResponse AWS API Documentation
#
class UpdateArtifactResponse < Struct.new(
:artifact_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] code_repository_name
# The name of the Git repository to update.
# @return [String]
#
# @!attribute [rw] git_config
# The configuration of the git repository, including the URL and the
# Amazon Resource Name (ARN) of the Amazon Web Services Secrets
# Manager secret that contains the credentials used to access the
# repository. The secret must have a staging label of `AWSCURRENT` and
# must be in the following format:
#
# `\{"username": UserName, "password": Password\}`
# @return [Types::GitConfigForUpdate]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateCodeRepositoryInput AWS API Documentation
#
class UpdateCodeRepositoryInput < Struct.new(
:code_repository_name,
:git_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] code_repository_arn
# The ARN of the Git repository.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateCodeRepositoryOutput AWS API Documentation
#
class UpdateCodeRepositoryOutput < Struct.new(
:code_repository_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_name
# The name of the context to update.
# @return [String]
#
# @!attribute [rw] description
# The new description for the context.
# @return [String]
#
# @!attribute [rw] properties
# The new list of properties. Overwrites the current property list.
# @return [Hash<String,String>]
#
# @!attribute [rw] properties_to_remove
# A list of properties to remove.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateContextRequest AWS API Documentation
#
class UpdateContextRequest < Struct.new(
:context_name,
:description,
:properties,
:properties_to_remove)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] context_arn
# The Amazon Resource Name (ARN) of the context.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateContextResponse AWS API Documentation
#
class UpdateContextResponse < Struct.new(
:context_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the device.
# @return [String]
#
# @!attribute [rw] description
# Description of the fleet.
# @return [String]
#
# @!attribute [rw] output_config
# Output configuration for storing sample data collected by the fleet.
# @return [Types::EdgeOutputConfig]
#
# @!attribute [rw] enable_iot_role_alias
# Whether to create an Amazon Web Services IoT Role Alias during
# device fleet creation. The name of the role alias generated will
# match this pattern: "SageMakerEdge-\\\{DeviceFleetName\\}".
#
# For example, if your device fleet is called "demo-fleet", the name
# of the role alias will be "SageMakerEdge-demo-fleet".
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateDeviceFleetRequest AWS API Documentation
#
class UpdateDeviceFleetRequest < Struct.new(
:device_fleet_name,
:role_arn,
:description,
:output_config,
:enable_iot_role_alias)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] device_fleet_name
# The name of the fleet the devices belong to.
# @return [String]
#
# @!attribute [rw] devices
# List of devices to register with Edge Manager agent.
# @return [Array<Types::Device>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateDevicesRequest AWS API Documentation
#
class UpdateDevicesRequest < Struct.new(
:device_fleet_name,
:devices)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The ID of the domain to be updated.
# @return [String]
#
# @!attribute [rw] default_user_settings
# A collection of settings.
# @return [Types::UserSettings]
#
# @!attribute [rw] domain_settings_for_update
# A collection of `DomainSettings` configuration values to update.
# @return [Types::DomainSettingsForUpdate]
#
# @!attribute [rw] default_space_settings
# The default settings used to create a space within the Domain.
# @return [Types::DefaultSpaceSettings]
#
# @!attribute [rw] app_security_group_management
# The entity that creates and manages the required security groups for
# inter-app communication in `VPCOnly` mode. Required when
# `CreateDomain.AppNetworkAccessType` is `VPCOnly` and
# `DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn`
# is provided.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateDomainRequest AWS API Documentation
#
class UpdateDomainRequest < Struct.new(
:domain_id,
:default_user_settings,
:domain_settings_for_update,
:default_space_settings,
:app_security_group_management)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_arn
# The Amazon Resource Name (ARN) of the domain.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateDomainResponse AWS API Documentation
#
class UpdateDomainResponse < Struct.new(
:domain_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# The name of the endpoint whose configuration you want to update.
# @return [String]
#
# @!attribute [rw] endpoint_config_name
# The name of the new endpoint configuration.
# @return [String]
#
# @!attribute [rw] retain_all_variant_properties
# When updating endpoint resources, enables or disables the retention
# of [variant properties][1], such as the instance count or the
# variant weight. To retain the variant properties of an endpoint when
# updating it, set `RetainAllVariantProperties` to `true`. To use the
# variant properties specified in a new `EndpointConfig` call when
# updating an endpoint, set `RetainAllVariantProperties` to `false`.
# The default is `false`.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VariantProperty.html
# @return [Boolean]
#
# @!attribute [rw] exclude_retained_variant_properties
# When you are updating endpoint resources with
# `RetainAllVariantProperties`, whose value is set to `true`,
# `ExcludeRetainedVariantProperties` specifies the list of type
# [VariantProperty][1] to override with the values provided by
# `EndpointConfig`. If you don't specify a value for
# `ExcludeRetainedVariantProperties`, no variant properties are
# overridden.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VariantProperty.html
# @return [Array<Types::VariantProperty>]
#
# @!attribute [rw] deployment_config
# The deployment configuration for an endpoint, which contains the
# desired deployment strategy and rollback configurations.
# @return [Types::DeploymentConfig]
#
# @!attribute [rw] retain_deployment_config
# Specifies whether to reuse the last deployment configuration. The
# default value is false (the configuration is not reused).
# @return [Boolean]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpointInput AWS API Documentation
#
class UpdateEndpointInput < Struct.new(
:endpoint_name,
:endpoint_config_name,
:retain_all_variant_properties,
:exclude_retained_variant_properties,
:deployment_config,
:retain_deployment_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_arn
# The Amazon Resource Name (ARN) of the endpoint.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpointOutput AWS API Documentation
#
class UpdateEndpointOutput < Struct.new(
:endpoint_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_name
# The name of an existing SageMaker endpoint.
# @return [String]
#
# @!attribute [rw] desired_weights_and_capacities
# An object that provides new capacity and weight values for a
# variant.
# @return [Array<Types::DesiredWeightAndCapacity>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpointWeightsAndCapacitiesInput AWS API Documentation
#
class UpdateEndpointWeightsAndCapacitiesInput < Struct.new(
:endpoint_name,
:desired_weights_and_capacities)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] endpoint_arn
# The Amazon Resource Name (ARN) of the updated endpoint.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateEndpointWeightsAndCapacitiesOutput AWS API Documentation
#
class UpdateEndpointWeightsAndCapacitiesOutput < Struct.new(
:endpoint_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_name
# The name of the experiment to update.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the experiment as displayed. The name doesn't need to
# be unique. If `DisplayName` isn't specified, `ExperimentName` is
# displayed.
# @return [String]
#
# @!attribute [rw] description
# The description of the experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateExperimentRequest AWS API Documentation
#
class UpdateExperimentRequest < Struct.new(
:experiment_name,
:display_name,
:description)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] experiment_arn
# The Amazon Resource Name (ARN) of the experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateExperimentResponse AWS API Documentation
#
class UpdateExperimentResponse < Struct.new(
:experiment_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_name
# The name of the feature group that you're updating.
# @return [String]
#
# @!attribute [rw] feature_additions
# Updates the feature group. Updating a feature group is an
# asynchronous operation. When you get an HTTP 200 response, you've
# made a valid request. It takes some time after you've made a valid
# request for Feature Store to update the feature group.
# @return [Array<Types::FeatureDefinition>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateFeatureGroupRequest AWS API Documentation
#
class UpdateFeatureGroupRequest < Struct.new(
:feature_group_name,
:feature_additions)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_arn
# The Amazon Resource Number (ARN) of the feature group that you're
# updating.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateFeatureGroupResponse AWS API Documentation
#
class UpdateFeatureGroupResponse < Struct.new(
:feature_group_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] feature_group_name
# The name of the feature group containing the feature that you're
# updating.
# @return [String]
#
# @!attribute [rw] feature_name
# The name of the feature that you're updating.
# @return [String]
#
# @!attribute [rw] description
# A description that you can write to better describe the feature.
# @return [String]
#
# @!attribute [rw] parameter_additions
# A list of key-value pairs that you can add to better describe the
# feature.
# @return [Array<Types::FeatureParameter>]
#
# @!attribute [rw] parameter_removals
# A list of parameter keys that you can specify to remove parameters
# that describe your feature.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateFeatureMetadataRequest AWS API Documentation
#
class UpdateFeatureMetadataRequest < Struct.new(
:feature_group_name,
:feature_name,
:description,
:parameter_additions,
:parameter_removals)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_name
# The name of the hub to update.
# @return [String]
#
# @!attribute [rw] hub_description
# A description of the updated hub.
# @return [String]
#
# @!attribute [rw] hub_display_name
# The display name of the hub.
# @return [String]
#
# @!attribute [rw] hub_search_keywords
# The searchable keywords for the hub.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateHubRequest AWS API Documentation
#
class UpdateHubRequest < Struct.new(
:hub_name,
:hub_description,
:hub_display_name,
:hub_search_keywords)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] hub_arn
# The Amazon Resource Name (ARN) of the updated hub.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateHubResponse AWS API Documentation
#
class UpdateHubResponse < Struct.new(
:hub_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] delete_properties
# A list of properties to delete. Only the `Description` and
# `DisplayName` properties can be deleted.
# @return [Array<String>]
#
# @!attribute [rw] description
# The new description for the image.
# @return [String]
#
# @!attribute [rw] display_name
# The new display name for the image.
# @return [String]
#
# @!attribute [rw] image_name
# The name of the image to update.
# @return [String]
#
# @!attribute [rw] role_arn
# The new ARN for the IAM role that enables Amazon SageMaker to
# perform tasks on your behalf.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateImageRequest AWS API Documentation
#
class UpdateImageRequest < Struct.new(
:delete_properties,
:description,
:display_name,
:image_name,
:role_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_arn
# The ARN of the image.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateImageResponse AWS API Documentation
#
class UpdateImageResponse < Struct.new(
:image_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_name
# The name of the image.
# @return [String]
#
# @!attribute [rw] alias
# The alias of the image version.
# @return [String]
#
# @!attribute [rw] version
# The version of the image.
# @return [Integer]
#
# @!attribute [rw] aliases_to_add
# A list of aliases to add.
# @return [Array<String>]
#
# @!attribute [rw] aliases_to_delete
# A list of aliases to delete.
# @return [Array<String>]
#
# @!attribute [rw] vendor_guidance
# The availability of the image version specified by the maintainer.
#
# * `NOT_PROVIDED`: The maintainers did not provide a status for image
# version stability.
#
# * `STABLE`: The image version is stable.
#
# * `TO_BE_ARCHIVED`: The image version is set to be archived. Custom
# image versions that are set to be archived are automatically
# archived after three months.
#
# * `ARCHIVED`: The image version is archived. Archived image versions
# are not searchable and are no longer actively supported.
# @return [String]
#
# @!attribute [rw] job_type
# Indicates SageMaker job type compatibility.
#
# * `TRAINING`: The image version is compatible with SageMaker
# training jobs.
#
# * `INFERENCE`: The image version is compatible with SageMaker
# inference jobs.
#
# * `NOTEBOOK_KERNEL`: The image version is compatible with SageMaker
# notebook kernels.
# @return [String]
#
# @!attribute [rw] ml_framework
# The machine learning framework vended in the image version.
# @return [String]
#
# @!attribute [rw] programming_lang
# The supported programming language and its version.
# @return [String]
#
# @!attribute [rw] processor
# Indicates CPU or GPU compatibility.
#
# * `CPU`: The image version is compatible with CPU.
#
# * `GPU`: The image version is compatible with GPU.
# @return [String]
#
# @!attribute [rw] horovod
# Indicates Horovod compatibility.
# @return [Boolean]
#
# @!attribute [rw] release_notes
# The maintainer description of the image version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateImageVersionRequest AWS API Documentation
#
class UpdateImageVersionRequest < Struct.new(
:image_name,
:alias,
:version,
:aliases_to_add,
:aliases_to_delete,
:vendor_guidance,
:job_type,
:ml_framework,
:programming_lang,
:processor,
:horovod,
:release_notes)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] image_version_arn
# The ARN of the image version.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateImageVersionResponse AWS API Documentation
#
class UpdateImageVersionResponse < Struct.new(
:image_version_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] name
# The name of the inference experiment to be updated.
# @return [String]
#
# @!attribute [rw] schedule
# The duration for which the inference experiment will run. If the
# status of the inference experiment is `Created`, then you can update
# both the start and end dates. If the status of the inference
# experiment is `Running`, then you can update only the end date.
# @return [Types::InferenceExperimentSchedule]
#
# @!attribute [rw] description
# The description of the inference experiment.
# @return [String]
#
# @!attribute [rw] model_variants
# An array of `ModelVariantConfig` objects. There is one for each
# variant, whose infrastructure configuration you want to update.
# @return [Array<Types::ModelVariantConfig>]
#
# @!attribute [rw] data_storage_config
# The Amazon S3 location and configuration for storing inference
# request and response data.
# @return [Types::InferenceExperimentDataStorageConfig]
#
# @!attribute [rw] shadow_mode_config
# The configuration of `ShadowMode` inference experiment type. Use
# this field to specify a production variant which takes all the
# inference requests, and a shadow variant to which Amazon SageMaker
# replicates a percentage of the inference requests. For the shadow
# variant also specify the percentage of requests that Amazon
# SageMaker replicates.
# @return [Types::ShadowModeConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateInferenceExperimentRequest AWS API Documentation
#
class UpdateInferenceExperimentRequest < Struct.new(
:name,
:schedule,
:description,
:model_variants,
:data_storage_config,
:shadow_mode_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] inference_experiment_arn
# The ARN of the updated inference experiment.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateInferenceExperimentResponse AWS API Documentation
#
class UpdateInferenceExperimentResponse < Struct.new(
:inference_experiment_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_card_name
# The name of the model card to update.
# @return [String]
#
# @!attribute [rw] content
# The updated model card content. Content must be in [model card JSON
# schema][1] and provided as a string.
#
# When updating model card content, be sure to include the full
# content and not just updated content.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-cards.html#model-cards-json-schema
# @return [String]
#
# @!attribute [rw] model_card_status
# The approval status of the model card within your organization.
# Different organizations might have different criteria for model card
# review and approval.
#
# * `Draft`: The model card is a work in progress.
#
# * `PendingReview`: The model card is pending review.
#
# * `Approved`: The model card is approved.
#
# * `Archived`: The model card is archived. No more updates should be
# made to the model card, but it can still be exported.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateModelCardRequest AWS API Documentation
#
class UpdateModelCardRequest < Struct.new(
:model_card_name,
:content,
:model_card_status)
SENSITIVE = [:content]
include Aws::Structure
end
# @!attribute [rw] model_card_arn
# The Amazon Resource Name (ARN) of the updated model card.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateModelCardResponse AWS API Documentation
#
class UpdateModelCardResponse < Struct.new(
:model_card_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_arn
# The Amazon Resource Name (ARN) of the model package.
# @return [String]
#
# @!attribute [rw] model_approval_status
# The approval status of the model.
# @return [String]
#
# @!attribute [rw] approval_description
# A description for the approval status of the model.
# @return [String]
#
# @!attribute [rw] customer_metadata_properties
# The metadata properties associated with the model package versions.
# @return [Hash<String,String>]
#
# @!attribute [rw] customer_metadata_properties_to_remove
# The metadata properties associated with the model package versions
# to remove.
# @return [Array<String>]
#
# @!attribute [rw] additional_inference_specifications_to_add
# An array of additional Inference Specification objects to be added
# to the existing array additional Inference Specification. Total
# number of additional Inference Specifications can not exceed 15.
# Each additional Inference Specification specifies artifacts based on
# this model package that can be used on inference endpoints.
# Generally used with SageMaker Neo to store the compiled artifacts.
# @return [Array<Types::AdditionalInferenceSpecificationDefinition>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateModelPackageInput AWS API Documentation
#
class UpdateModelPackageInput < Struct.new(
:model_package_arn,
:model_approval_status,
:approval_description,
:customer_metadata_properties,
:customer_metadata_properties_to_remove,
:additional_inference_specifications_to_add)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] model_package_arn
# The Amazon Resource Name (ARN) of the model.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateModelPackageOutput AWS API Documentation
#
class UpdateModelPackageOutput < Struct.new(
:model_package_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# The name of a monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_alert_name
# The name of a monitoring alert.
# @return [String]
#
# @!attribute [rw] datapoints_to_alert
# Within `EvaluationPeriod`, how many execution failures will raise an
# alert.
# @return [Integer]
#
# @!attribute [rw] evaluation_period
# The number of most recent monitoring executions to consider when
# evaluating alert status.
# @return [Integer]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateMonitoringAlertRequest AWS API Documentation
#
class UpdateMonitoringAlertRequest < Struct.new(
:monitoring_schedule_name,
:monitoring_alert_name,
:datapoints_to_alert,
:evaluation_period)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_arn
# The Amazon Resource Name (ARN) of the monitoring schedule.
# @return [String]
#
# @!attribute [rw] monitoring_alert_name
# The name of a monitoring alert.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateMonitoringAlertResponse AWS API Documentation
#
class UpdateMonitoringAlertResponse < Struct.new(
:monitoring_schedule_arn,
:monitoring_alert_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_name
# The name of the monitoring schedule. The name must be unique within
# an Amazon Web Services Region within an Amazon Web Services account.
# @return [String]
#
# @!attribute [rw] monitoring_schedule_config
# The configuration object that specifies the monitoring schedule and
# defines the monitoring job.
# @return [Types::MonitoringScheduleConfig]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateMonitoringScheduleRequest AWS API Documentation
#
class UpdateMonitoringScheduleRequest < Struct.new(
:monitoring_schedule_name,
:monitoring_schedule_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] monitoring_schedule_arn
# The Amazon Resource Name (ARN) of the monitoring schedule.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateMonitoringScheduleResponse AWS API Documentation
#
class UpdateMonitoringScheduleResponse < Struct.new(
:monitoring_schedule_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_name
# The name of the notebook instance to update.
# @return [String]
#
# @!attribute [rw] instance_type
# The Amazon ML compute instance type.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) of the IAM role that SageMaker can
# assume to access the notebook instance. For more information, see
# [SageMaker Roles][1].
#
# <note markdown="1"> To be able to pass this role to SageMaker, the caller of this API
# must have the `iam:PassRole` permission.
#
# </note>
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html
# @return [String]
#
# @!attribute [rw] lifecycle_config_name
# The name of a lifecycle configuration to associate with the notebook
# instance. For information about lifestyle configurations, see [Step
# 2.1: (Optional) Customize a Notebook Instance][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html
# @return [String]
#
# @!attribute [rw] disassociate_lifecycle_config
# Set to `true` to remove the notebook instance lifecycle
# configuration currently associated with the notebook instance. This
# operation is idempotent. If you specify a lifecycle configuration
# that is not associated with the notebook instance when you call this
# method, it does not throw an error.
# @return [Boolean]
#
# @!attribute [rw] volume_size_in_gb
# The size, in GB, of the ML storage volume to attach to the notebook
# instance. The default value is 5 GB. ML storage volumes are
# encrypted, so SageMaker can't determine the amount of available
# free space on the volume. Because of this, you can increase the
# volume size when you update a notebook instance, but you can't
# decrease the volume size. If you want to decrease the size of the ML
# storage volume in use, create a new notebook instance with the
# desired size.
# @return [Integer]
#
# @!attribute [rw] default_code_repository
# The Git repository to associate with the notebook instance as its
# default code repository. This can be either the name of a Git
# repository stored as a resource in your account, or the URL of a Git
# repository in [Amazon Web Services CodeCommit][1] or in any other
# Git repository. When you open a notebook instance, it opens in the
# directory that contains this repository. For more information, see
# [Associating Git Repositories with SageMaker Notebook Instances][2].
#
#
#
# [1]: https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html
# @return [String]
#
# @!attribute [rw] additional_code_repositories
# An array of up to three Git repositories to associate with the
# notebook instance. These can be either the names of Git repositories
# stored as resources in your account, or the URL of Git repositories
# in [Amazon Web Services CodeCommit][1] or in any other Git
# repository. These repositories are cloned at the same level as the
# default repository of your notebook instance. For more information,
# see [Associating Git Repositories with SageMaker Notebook
# Instances][2].
#
#
#
# [1]: https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html
# @return [Array<String>]
#
# @!attribute [rw] accelerator_types
# A list of the Elastic Inference (EI) instance types to associate
# with this notebook instance. Currently only one EI instance type can
# be associated with a notebook instance. For more information, see
# [Using Elastic Inference in Amazon SageMaker][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
# @return [Array<String>]
#
# @!attribute [rw] disassociate_accelerator_types
# A list of the Elastic Inference (EI) instance types to remove from
# this notebook instance. This operation is idempotent. If you specify
# an accelerator type that is not associated with the notebook
# instance when you call this method, it does not throw an error.
# @return [Boolean]
#
# @!attribute [rw] disassociate_default_code_repository
# The name or URL of the default Git repository to remove from this
# notebook instance. This operation is idempotent. If you specify a
# Git repository that is not associated with the notebook instance
# when you call this method, it does not throw an error.
# @return [Boolean]
#
# @!attribute [rw] disassociate_additional_code_repositories
# A list of names or URLs of the default Git repositories to remove
# from this notebook instance. This operation is idempotent. If you
# specify a Git repository that is not associated with the notebook
# instance when you call this method, it does not throw an error.
# @return [Boolean]
#
# @!attribute [rw] root_access
# Whether root access is enabled or disabled for users of the notebook
# instance. The default value is `Enabled`.
#
# <note markdown="1"> If you set this to `Disabled`, users don't have root access on the
# notebook instance, but lifecycle configuration scripts still run
# with root permissions.
#
# </note>
# @return [String]
#
# @!attribute [rw] instance_metadata_service_configuration
# Information on the IMDS configuration of the notebook instance
# @return [Types::InstanceMetadataServiceConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstanceInput AWS API Documentation
#
class UpdateNotebookInstanceInput < Struct.new(
:notebook_instance_name,
:instance_type,
:role_arn,
:lifecycle_config_name,
:disassociate_lifecycle_config,
:volume_size_in_gb,
:default_code_repository,
:additional_code_repositories,
:accelerator_types,
:disassociate_accelerator_types,
:disassociate_default_code_repository,
:disassociate_additional_code_repositories,
:root_access,
:instance_metadata_service_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] notebook_instance_lifecycle_config_name
# The name of the lifecycle configuration.
# @return [String]
#
# @!attribute [rw] on_create
# The shell script that runs only once, when you create a notebook
# instance. The shell script must be a base64-encoded string.
# @return [Array<Types::NotebookInstanceLifecycleHook>]
#
# @!attribute [rw] on_start
# The shell script that runs every time you start a notebook instance,
# including when you create the notebook instance. The shell script
# must be a base64-encoded string.
# @return [Array<Types::NotebookInstanceLifecycleHook>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstanceLifecycleConfigInput AWS API Documentation
#
class UpdateNotebookInstanceLifecycleConfigInput < Struct.new(
:notebook_instance_lifecycle_config_name,
:on_create,
:on_start)
SENSITIVE = []
include Aws::Structure
end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstanceLifecycleConfigOutput AWS API Documentation
#
class UpdateNotebookInstanceLifecycleConfigOutput < Aws::EmptyStructure; end
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateNotebookInstanceOutput AWS API Documentation
#
class UpdateNotebookInstanceOutput < Aws::EmptyStructure; end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_description
# The description of the pipeline execution.
# @return [String]
#
# @!attribute [rw] pipeline_execution_display_name
# The display name of the pipeline execution.
# @return [String]
#
# @!attribute [rw] parallelism_configuration
# This configuration, if specified, overrides the parallelism
# configuration of the parent pipeline for this specific run.
# @return [Types::ParallelismConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdatePipelineExecutionRequest AWS API Documentation
#
class UpdatePipelineExecutionRequest < Struct.new(
:pipeline_execution_arn,
:pipeline_execution_description,
:pipeline_execution_display_name,
:parallelism_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_execution_arn
# The Amazon Resource Name (ARN) of the updated pipeline execution.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdatePipelineExecutionResponse AWS API Documentation
#
class UpdatePipelineExecutionResponse < Struct.new(
:pipeline_execution_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_name
# The name of the pipeline to update.
# @return [String]
#
# @!attribute [rw] pipeline_display_name
# The display name of the pipeline.
# @return [String]
#
# @!attribute [rw] pipeline_definition
# The JSON pipeline definition.
# @return [String]
#
# @!attribute [rw] pipeline_definition_s3_location
# The location of the pipeline definition stored in Amazon S3. If
# specified, SageMaker will retrieve the pipeline definition from this
# location.
# @return [Types::PipelineDefinitionS3Location]
#
# @!attribute [rw] pipeline_description
# The description of the pipeline.
# @return [String]
#
# @!attribute [rw] role_arn
# The Amazon Resource Name (ARN) that the pipeline uses to execute.
# @return [String]
#
# @!attribute [rw] parallelism_configuration
# If specified, it applies to all executions of this pipeline by
# default.
# @return [Types::ParallelismConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdatePipelineRequest AWS API Documentation
#
class UpdatePipelineRequest < Struct.new(
:pipeline_name,
:pipeline_display_name,
:pipeline_definition,
:pipeline_definition_s3_location,
:pipeline_description,
:role_arn,
:parallelism_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] pipeline_arn
# The Amazon Resource Name (ARN) of the updated pipeline.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdatePipelineResponse AWS API Documentation
#
class UpdatePipelineResponse < Struct.new(
:pipeline_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_name
# The name of the project.
# @return [String]
#
# @!attribute [rw] project_description
# The description for the project.
# @return [String]
#
# @!attribute [rw] service_catalog_provisioning_update_details
# The product ID and provisioning artifact ID to provision a service
# catalog. The provisioning artifact ID will default to the latest
# provisioning artifact ID of the product, if you don't provide the
# provisioning artifact ID. For more information, see [What is Amazon
# Web Services Service Catalog][1].
#
#
#
# [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html
# @return [Types::ServiceCatalogProvisioningUpdateDetails]
#
# @!attribute [rw] tags
# An array of key-value pairs. You can use tags to categorize your
# Amazon Web Services resources in different ways, for example, by
# purpose, owner, or environment. For more information, see [Tagging
# Amazon Web Services Resources][1]. In addition, the project must
# have tag update constraints set in order to include this parameter
# in the request. For more information, see [Amazon Web Services
# Service Catalog Tag Update Constraints][2].
#
#
#
# [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html
# [2]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/constraints-resourceupdate.html
# @return [Array<Types::Tag>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateProjectInput AWS API Documentation
#
class UpdateProjectInput < Struct.new(
:project_name,
:project_description,
:service_catalog_provisioning_update_details,
:tags)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] project_arn
# The Amazon Resource Name (ARN) of the project.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateProjectOutput AWS API Documentation
#
class UpdateProjectOutput < Struct.new(
:project_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The ID of the associated Domain.
# @return [String]
#
# @!attribute [rw] space_name
# The name of the space.
# @return [String]
#
# @!attribute [rw] space_settings
# A collection of space settings.
# @return [Types::SpaceSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateSpaceRequest AWS API Documentation
#
class UpdateSpaceRequest < Struct.new(
:domain_id,
:space_name,
:space_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] space_arn
# The space's Amazon Resource Name (ARN).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateSpaceResponse AWS API Documentation
#
class UpdateSpaceResponse < Struct.new(
:space_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_name
# The name of a training job to update the Debugger profiling
# configuration.
# @return [String]
#
# @!attribute [rw] profiler_config
# Configuration information for Amazon SageMaker Debugger system
# monitoring, framework profiling, and storage paths.
# @return [Types::ProfilerConfigForUpdate]
#
# @!attribute [rw] profiler_rule_configurations
# Configuration information for Amazon SageMaker Debugger rules for
# profiling system and framework metrics.
# @return [Array<Types::ProfilerRuleConfiguration>]
#
# @!attribute [rw] resource_config
# The training job `ResourceConfig` to update warm pool retention
# length.
# @return [Types::ResourceConfigForUpdate]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrainingJobRequest AWS API Documentation
#
class UpdateTrainingJobRequest < Struct.new(
:training_job_name,
:profiler_config,
:profiler_rule_configurations,
:resource_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] training_job_arn
# The Amazon Resource Name (ARN) of the training job.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrainingJobResponse AWS API Documentation
#
class UpdateTrainingJobResponse < Struct.new(
:training_job_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_name
# The name of the component to update.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the component as displayed. The name doesn't need to be
# unique. If `DisplayName` isn't specified, `TrialComponentName` is
# displayed.
# @return [String]
#
# @!attribute [rw] status
# The new status of the component.
# @return [Types::TrialComponentStatus]
#
# @!attribute [rw] start_time
# When the component started.
# @return [Time]
#
# @!attribute [rw] end_time
# When the component ended.
# @return [Time]
#
# @!attribute [rw] parameters
# Replaces all of the component's hyperparameters with the specified
# hyperparameters or add new hyperparameters. Existing hyperparameters
# are replaced if the trial component is updated with an identical
# hyperparameter key.
# @return [Hash<String,Types::TrialComponentParameterValue>]
#
# @!attribute [rw] parameters_to_remove
# The hyperparameters to remove from the component.
# @return [Array<String>]
#
# @!attribute [rw] input_artifacts
# Replaces all of the component's input artifacts with the specified
# artifacts or adds new input artifacts. Existing input artifacts are
# replaced if the trial component is updated with an identical input
# artifact key.
# @return [Hash<String,Types::TrialComponentArtifact>]
#
# @!attribute [rw] input_artifacts_to_remove
# The input artifacts to remove from the component.
# @return [Array<String>]
#
# @!attribute [rw] output_artifacts
# Replaces all of the component's output artifacts with the specified
# artifacts or adds new output artifacts. Existing output artifacts
# are replaced if the trial component is updated with an identical
# output artifact key.
# @return [Hash<String,Types::TrialComponentArtifact>]
#
# @!attribute [rw] output_artifacts_to_remove
# The output artifacts to remove from the component.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrialComponentRequest AWS API Documentation
#
class UpdateTrialComponentRequest < Struct.new(
:trial_component_name,
:display_name,
:status,
:start_time,
:end_time,
:parameters,
:parameters_to_remove,
:input_artifacts,
:input_artifacts_to_remove,
:output_artifacts,
:output_artifacts_to_remove)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_component_arn
# The Amazon Resource Name (ARN) of the trial component.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrialComponentResponse AWS API Documentation
#
class UpdateTrialComponentResponse < Struct.new(
:trial_component_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_name
# The name of the trial to update.
# @return [String]
#
# @!attribute [rw] display_name
# The name of the trial as displayed. The name doesn't need to be
# unique. If `DisplayName` isn't specified, `TrialName` is displayed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrialRequest AWS API Documentation
#
class UpdateTrialRequest < Struct.new(
:trial_name,
:display_name)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] trial_arn
# The Amazon Resource Name (ARN) of the trial.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateTrialResponse AWS API Documentation
#
class UpdateTrialResponse < Struct.new(
:trial_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name.
# @return [String]
#
# @!attribute [rw] user_settings
# A collection of settings.
# @return [Types::UserSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateUserProfileRequest AWS API Documentation
#
class UpdateUserProfileRequest < Struct.new(
:domain_id,
:user_profile_name,
:user_settings)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] user_profile_arn
# The user profile Amazon Resource Name (ARN).
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateUserProfileResponse AWS API Documentation
#
class UpdateUserProfileResponse < Struct.new(
:user_profile_arn)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workforce_name
# The name of the private workforce that you want to update. You can
# find your workforce name by using the [ListWorkforces][1] operation.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ListWorkforces.html
# @return [String]
#
# @!attribute [rw] source_ip_config
# A list of one to ten worker IP address ranges ([CIDRs][1]) that can
# be used to access tasks assigned to this workforce.
#
# Maximum: Ten CIDR values
#
#
#
# [1]: https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html
# @return [Types::SourceIpConfig]
#
# @!attribute [rw] oidc_config
# Use this parameter to update your OIDC Identity Provider (IdP)
# configuration for a workforce made using your own IdP.
# @return [Types::OidcConfig]
#
# @!attribute [rw] workforce_vpc_config
# Use this parameter to update your VPC configuration for a workforce.
# @return [Types::WorkforceVpcConfigRequest]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkforceRequest AWS API Documentation
#
class UpdateWorkforceRequest < Struct.new(
:workforce_name,
:source_ip_config,
:oidc_config,
:workforce_vpc_config)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workforce
# A single private workforce. You can create one private work force in
# each Amazon Web Services 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][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html
# @return [Types::Workforce]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkforceResponse AWS API Documentation
#
class UpdateWorkforceResponse < Struct.new(
:workforce)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteam_name
# The name of the work team to update.
# @return [String]
#
# @!attribute [rw] member_definitions
# A list of `MemberDefinition` objects that contains objects that
# identify the workers that make up the work team.
#
# Workforces can be created using Amazon Cognito or your own OIDC
# Identity Provider (IdP). For private workforces created using Amazon
# Cognito use `CognitoMemberDefinition`. For workforces created using
# your own OIDC identity provider (IdP) use `OidcMemberDefinition`.
# You should not provide input for both of these parameters in a
# single request.
#
# For workforces created using Amazon Cognito, private work teams
# correspond to Amazon Cognito *user groups* within the user pool used
# to create a workforce. All of the `CognitoMemberDefinition` objects
# that make up the member definition must have the same `ClientId` and
# `UserPool` values. To add a Amazon Cognito user group to an existing
# worker pool, see [Adding groups to a User Pool](). For more
# information about user pools, see [Amazon Cognito User Pools][1].
#
# For workforces created using your own OIDC IdP, specify the user
# groups that you want to include in your private work team in
# `OidcMemberDefinition` by listing those groups in `Groups`. Be aware
# that user groups that are already in the work team must also be
# listed in `Groups` when you make this request to remain on the work
# team. If you do not include these user groups, they will no longer
# be associated with the work team you update.
#
#
#
# [1]: https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html
# @return [Array<Types::MemberDefinition>]
#
# @!attribute [rw] description
# An updated description for the work team.
# @return [String]
#
# @!attribute [rw] notification_configuration
# Configures SNS topic notifications for available or expiring work
# items
# @return [Types::NotificationConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkteamRequest AWS API Documentation
#
class UpdateWorkteamRequest < Struct.new(
:workteam_name,
:member_definitions,
:description,
:notification_configuration)
SENSITIVE = []
include Aws::Structure
end
# @!attribute [rw] workteam
# A `Workteam` object that describes the updated work team.
# @return [Types::Workteam]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateWorkteamResponse AWS API Documentation
#
class UpdateWorkteamResponse < Struct.new(
:workteam)
SENSITIVE = []
include Aws::Structure
end
# Information about the user who created or modified an experiment,
# trial, trial component, lineage group, project, or model card.
#
# @!attribute [rw] user_profile_arn
# The Amazon Resource Name (ARN) of the user's profile.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The name of the user's profile.
# @return [String]
#
# @!attribute [rw] domain_id
# The domain associated with the user.
# @return [String]
#
# @!attribute [rw] iam_identity
# The IAM Identity details associated with the user. These details are
# associated with model package groups, model packages, and project
# entities only.
# @return [Types::IamIdentity]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UserContext AWS API Documentation
#
class UserContext < Struct.new(
:user_profile_arn,
:user_profile_name,
:domain_id,
:iam_identity)
SENSITIVE = []
include Aws::Structure
end
# The user profile details.
#
# @!attribute [rw] domain_id
# The domain ID.
# @return [String]
#
# @!attribute [rw] user_profile_name
# The user profile name.
# @return [String]
#
# @!attribute [rw] status
# The status.
# @return [String]
#
# @!attribute [rw] creation_time
# The creation time.
# @return [Time]
#
# @!attribute [rw] last_modified_time
# The last modified time.
# @return [Time]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UserProfileDetails AWS API Documentation
#
class UserProfileDetails < Struct.new(
:domain_id,
:user_profile_name,
:status,
:creation_time,
:last_modified_time)
SENSITIVE = []
include Aws::Structure
end
# A collection of settings that apply to users of Amazon SageMaker
# Studio. These settings are specified when the `CreateUserProfile` API
# is called, and as `DefaultUserSettings` when the `CreateDomain` API is
# called.
#
# `SecurityGroups` is aggregated when specified in both calls. For all
# other settings in `UserSettings`, the values specified in
# `CreateUserProfile` take precedence over those specified in
# `CreateDomain`.
#
# @!attribute [rw] execution_role
# The execution role for the user.
# @return [String]
#
# @!attribute [rw] security_groups
# The security groups for the Amazon Virtual Private Cloud (VPC) that
# Studio uses for communication.
#
# Optional when the `CreateDomain.AppNetworkAccessType` parameter is
# set to `PublicInternetOnly`.
#
# Required when the `CreateDomain.AppNetworkAccessType` parameter is
# set to `VpcOnly`, unless specified as part of the
# `DefaultUserSettings` for the domain.
#
# Amazon SageMaker adds a security group to allow NFS traffic from
# SageMaker Studio. Therefore, the number of security groups that you
# can specify is one less than the maximum number shown.
# @return [Array<String>]
#
# @!attribute [rw] sharing_settings
# Specifies options for sharing SageMaker Studio notebooks.
# @return [Types::SharingSettings]
#
# @!attribute [rw] jupyter_server_app_settings
# The Jupyter server's app settings.
# @return [Types::JupyterServerAppSettings]
#
# @!attribute [rw] kernel_gateway_app_settings
# The kernel gateway app settings.
# @return [Types::KernelGatewayAppSettings]
#
# @!attribute [rw] tensor_board_app_settings
# The TensorBoard app settings.
# @return [Types::TensorBoardAppSettings]
#
# @!attribute [rw] r_studio_server_pro_app_settings
# A collection of settings that configure user interaction with the
# `RStudioServerPro` app.
# @return [Types::RStudioServerProAppSettings]
#
# @!attribute [rw] r_session_app_settings
# A collection of settings that configure the `RSessionGateway` app.
# @return [Types::RSessionAppSettings]
#
# @!attribute [rw] canvas_app_settings
# The Canvas app settings.
# @return [Types::CanvasAppSettings]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UserSettings AWS API Documentation
#
class UserSettings < Struct.new(
:execution_role,
:security_groups,
:sharing_settings,
:jupyter_server_app_settings,
:kernel_gateway_app_settings,
:tensor_board_app_settings,
:r_studio_server_pro_app_settings,
:r_session_app_settings,
:canvas_app_settings)
SENSITIVE = []
include Aws::Structure
end
# Specifies a production variant property type for an Endpoint.
#
# If you are updating an endpoint with the `RetainAllVariantProperties`
# option of [UpdateEndpointInput][1] set to `true`, the
# `VariantProperty` objects listed in the
# `ExcludeRetainedVariantProperties` parameter of
# [UpdateEndpointInput][1] override the existing variant properties of
# the endpoint.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateEndpoint.html
#
# @!attribute [rw] variant_property_type
# The type of variant property. The supported values are:
#
# * `DesiredInstanceCount`: Overrides the existing variant instance
# counts using the `InitialInstanceCount` values in the
# `ProductionVariants` of [CreateEndpointConfig][1].
#
# * `DesiredWeight`: Overrides the existing variant weights using the
# `InitialVariantWeight` values in the `ProductionVariants` of
# [CreateEndpointConfig][1].
#
# * `DataCaptureConfig`: (Not currently supported.)
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/VariantProperty AWS API Documentation
#
class VariantProperty < Struct.new(
:variant_property_type)
SENSITIVE = []
include Aws::Structure
end
# A lineage entity connected to the starting entity(ies).
#
# @!attribute [rw] arn
# The Amazon Resource Name (ARN) of the lineage entity resource.
# @return [String]
#
# @!attribute [rw] type
# The type of the lineage entity resource. For example: `DataSet`,
# `Model`, `Endpoint`, etc...
# @return [String]
#
# @!attribute [rw] lineage_type
# The type of resource of the lineage entity.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Vertex AWS API Documentation
#
class Vertex < Struct.new(
:arn,
:type,
:lineage_type)
SENSITIVE = []
include Aws::Structure
end
# 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][1] and [Protect Training Jobs
# by Using an Amazon Virtual Private Cloud][2].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html
# [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html
#
# @!attribute [rw] security_group_ids
# The VPC security group IDs, in the form sg-xxxxxxxx. Specify the
# security groups for the VPC that is specified in the `Subnets`
# field.
# @return [Array<String>]
#
# @!attribute [rw] subnets
# The ID of the subnets in the VPC to which you want to connect your
# training job or model. For information about the availability of
# specific instance types, see [Supported Instance Types and
# Availability Zones][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/instance-types-az.html
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/VpcConfig AWS API Documentation
#
class VpcConfig < Struct.new(
:security_group_ids,
:subnets)
SENSITIVE = []
include Aws::Structure
end
# Status and billing information about the warm pool.
#
# @!attribute [rw] status
# The status of the warm pool.
#
# * `InUse`: The warm pool is in use for the training job.
#
# * `Available`: The warm pool is available to reuse for a matching
# training job.
#
# * `Reused`: The warm pool moved to a matching training job for
# reuse.
#
# * `Terminated`: The warm pool is no longer available. Warm pools are
# unavailable if they are terminated by a user, terminated for a
# patch update, or terminated for exceeding the specified
# `KeepAlivePeriodInSeconds`.
# @return [String]
#
# @!attribute [rw] resource_retained_billable_time_in_seconds
# The billable time in seconds used by the warm pool. Billable time
# refers to the absolute wall-clock time.
#
# Multiply `ResourceRetainedBillableTimeInSeconds` by the number of
# instances (`InstanceCount`) in your training cluster to get the
# total compute time SageMaker bills you if you run warm pool
# training. The formula is as follows:
# `ResourceRetainedBillableTimeInSeconds * InstanceCount`.
# @return [Integer]
#
# @!attribute [rw] reused_by_job
# The name of the matching training job that reused the warm pool.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/WarmPoolStatus AWS API Documentation
#
class WarmPoolStatus < Struct.new(
:status,
:resource_retained_billable_time_in_seconds,
:reused_by_job)
SENSITIVE = []
include Aws::Structure
end
# 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 Amazon Web Services 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][1].
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-create-private.html
#
# @!attribute [rw] workforce_name
# The name of the private workforce.
# @return [String]
#
# @!attribute [rw] workforce_arn
# The Amazon Resource Name (ARN) of the private workforce.
# @return [String]
#
# @!attribute [rw] last_updated_date
# The most recent date that [UpdateWorkforce][1] was used to
# successfully add one or more IP address ranges ([CIDRs][2]) to a
# private workforce's allow list.
#
#
#
# [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateWorkforce.html
# [2]: https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html
# @return [Time]
#
# @!attribute [rw] source_ip_config
# A list of one to ten IP address ranges ([CIDRs][1]) to be added to
# the workforce allow list. By default, a workforce isn't restricted
# to specific IP addresses.
#
#
#
# [1]: https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html
# @return [Types::SourceIpConfig]
#
# @!attribute [rw] sub_domain
# The subdomain for your OIDC Identity Provider.
# @return [String]
#
# @!attribute [rw] cognito_config
# The configuration of an Amazon Cognito workforce. A single Cognito
# workforce is created using and corresponds to a single [ Amazon
# Cognito user pool][1].
#
#
#
# [1]: https://docs.aws.amazon.com/cognito/latest/developerguide/cognito-user-identity-pools.html
# @return [Types::CognitoConfig]
#
# @!attribute [rw] oidc_config
# The configuration of an OIDC Identity Provider (IdP) private
# workforce.
# @return [Types::OidcConfigForResponse]
#
# @!attribute [rw] create_date
# The date that the workforce is created.
# @return [Time]
#
# @!attribute [rw] workforce_vpc_config
# The configuration of a VPC workforce.
# @return [Types::WorkforceVpcConfigResponse]
#
# @!attribute [rw] status
# The status of your workforce.
# @return [String]
#
# @!attribute [rw] failure_reason
# The reason your workforce failed.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Workforce AWS API Documentation
#
class Workforce < Struct.new(
:workforce_name,
:workforce_arn,
:last_updated_date,
:source_ip_config,
:sub_domain,
:cognito_config,
:oidc_config,
:create_date,
:workforce_vpc_config,
:status,
:failure_reason)
SENSITIVE = []
include Aws::Structure
end
# The VPC object you use to create or update a workforce.
#
# @!attribute [rw] vpc_id
# The ID of the VPC that the workforce uses for communication.
# @return [String]
#
# @!attribute [rw] security_group_ids
# The VPC security group IDs, in the form sg-xxxxxxxx. The security
# groups must be for the same VPC as specified in the subnet.
# @return [Array<String>]
#
# @!attribute [rw] subnets
# The ID of the subnets in the VPC that you want to connect.
# @return [Array<String>]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/WorkforceVpcConfigRequest AWS API Documentation
#
class WorkforceVpcConfigRequest < Struct.new(
:vpc_id,
:security_group_ids,
:subnets)
SENSITIVE = []
include Aws::Structure
end
# A VpcConfig object that specifies the VPC that you want your workforce
# to connect to.
#
# @!attribute [rw] vpc_id
# The ID of the VPC that the workforce uses for communication.
# @return [String]
#
# @!attribute [rw] security_group_ids
# The VPC security group IDs, in the form sg-xxxxxxxx. The security
# groups must be for the same VPC as specified in the subnet.
# @return [Array<String>]
#
# @!attribute [rw] subnets
# The ID of the subnets in the VPC that you want to connect.
# @return [Array<String>]
#
# @!attribute [rw] vpc_endpoint_id
# The IDs for the VPC service endpoints of your VPC workforce when it
# is created and updated.
# @return [String]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/WorkforceVpcConfigResponse AWS API Documentation
#
class WorkforceVpcConfigResponse < Struct.new(
:vpc_id,
:security_group_ids,
:subnets,
:vpc_endpoint_id)
SENSITIVE = []
include Aws::Structure
end
# Provides details about a labeling work team.
#
# @!attribute [rw] workteam_name
# The name of the work team.
# @return [String]
#
# @!attribute [rw] member_definitions
# A list of `MemberDefinition` objects that contains objects that
# identify the workers that make up the work team.
#
# Workforces can be created using Amazon Cognito or your own OIDC
# Identity Provider (IdP). For private workforces created using Amazon
# Cognito use `CognitoMemberDefinition`. For workforces created using
# your own OIDC identity provider (IdP) use `OidcMemberDefinition`.
# @return [Array<Types::MemberDefinition>]
#
# @!attribute [rw] workteam_arn
# The Amazon Resource Name (ARN) that identifies the work team.
# @return [String]
#
# @!attribute [rw] workforce_arn
# The Amazon Resource Name (ARN) of the workforce.
# @return [String]
#
# @!attribute [rw] product_listing_ids
# The Amazon Marketplace identifier for a vendor's work team.
# @return [Array<String>]
#
# @!attribute [rw] description
# A description of the work team.
# @return [String]
#
# @!attribute [rw] sub_domain
# The URI of the labeling job's user interface. Workers open this URI
# to start labeling your data objects.
# @return [String]
#
# @!attribute [rw] create_date
# The date and time that the work team was created (timestamp).
# @return [Time]
#
# @!attribute [rw] last_updated_date
# The date and time that the work team was last updated (timestamp).
# @return [Time]
#
# @!attribute [rw] notification_configuration
# Configures SNS notifications of available or expiring work items for
# work teams.
# @return [Types::NotificationConfiguration]
#
# @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Workteam AWS API Documentation
#
class Workteam < Struct.new(
:workteam_name,
:member_definitions,
:workteam_arn,
:workforce_arn,
:product_listing_ids,
:description,
:sub_domain,
:create_date,
:last_updated_date,
:notification_configuration)
SENSITIVE = []
include Aws::Structure
end
end
end