# 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] # # @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] # # @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] # # @!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] # # @!attribute [rw] supported_realtime_inference_instance_types # A list of the instance types that are used to generate inferences in # real-time. # @return [Array] # # @!attribute [rw] supported_content_types # The supported MIME types for the input data. # @return [Array] # # @!attribute [rw] supported_response_mime_types # The supported MIME types for the output data. # @return [Array] # # @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 # A data source used for training or inference that is in addition to # the input dataset or model data. # # @!attribute [rw] s3_data_type # The data type of the additional data source that you specify for use # in inference or training. # @return [String] # # @!attribute [rw] s3_uri # The uniform resource identifier (URI) used to identify an additional # data source used in inference or training. # @return [String] # # @!attribute [rw] compression_type # The type of compression used for an additional data source used in # inference or training. Specify `None` if your additional data source # is not compressed. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AdditionalS3DataSource AWS API Documentation # class AdditionalS3DataSource < Struct.new( :s3_data_type, :s3_uri, :compression_type) 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]. # # 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. # # # # # # [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. # # 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. # # # @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] # # @!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] # # @!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] # # @!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] # # @!attribute [rw] image_scan_statuses # The status of the scan of the algorithm's Docker image container. # @return [Array] # # @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] # # @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] space_name # The name of the space. # @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] 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/AppDetails AWS API Documentation # class AppDetails < Struct.new( :domain_id, :user_profile_name, :space_name, :app_type, :app_name, :status, :creation_time, :resource_spec) SENSITIVE = [] include Aws::Structure end # The configuration for running a SageMaker image as a KernelGateway # app. # # @!attribute [rw] app_image_config_arn # The 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] # # @!attribute [rw] jupyter_lab_app_image_config # The configuration for the file system and the runtime, such as the # environment variables and entry point. # @return [Types::JupyterLabAppImageConfig] # # @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, :jupyter_lab_app_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] # # @!attribute [rw] container_arguments # The arguments for a container used to run a processing job. # @return [Array] # # @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] # # @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. # # The inference response is included only if the response size is less # than or equal to 128 KB. # # # @return [Array] # # @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. # # 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. # # # # * 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] # # @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] # # @!attribute [rw] candidate_status # The candidate's status. # @return [String] # # @!attribute [rw] inference_containers # Information about the recommended inference container definitions. # @return [Array] # # @!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 AutoML jobs V2 (for example, for jobs created by # calling `CreateAutoMLJobV2`) related to image or text classification # problem types only. # @return [Hash>] # # @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" ... # \} \}` # # These column keys may not include the target column. # # # # 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] # # @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]. # # A validation dataset must contain the same headers as the training # dataset. # # # # # # # # [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] # # @!attribute [rw] sample_weight_attribute_name # If specified, this column name indicates which column of the dataset # should be treated as sample weights for use by the objective metric # during the training, evaluation, and the selection of the best # model. This column is not considered as a predictive feature. For # more information on Autopilot metrics, see [Metrics and # validation][1]. # # Sample weights should be numeric, non-negative, with larger values # indicating which rows are more important than others. Data points # that have invalid or no weight value are excluded. # # Support for sample weights is available in [Ensembling][2] mode # only. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html # @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, :sample_weight_attribute_name) 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] # # @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. # # The validation and training datasets must contain the same headers. # For jobs created by calling `CreateAutoMLJob`, 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 AutoML jobs V2 (jobs created by # calling [CreateAutoMLJobV2][1]). # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.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` # # The type of channel defaults to `training` for the time-series # forecasting problem type. # # # @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: # # * For tabular problem types: `text/csv;header=present` or # `x-application/vnd.amazon+parquet`. The default value is # `text/csv;header=present`. # # * For image classification: `image/png`, `image/jpeg`, or `image/*`. # The default value is `image/*`. # # * For text classification: `text/csv;header=present` or # `x-application/vnd.amazon+parquet`. The default value is # `text/csv;header=present`. # # * For time-series forecasting: `text/csv;header=present` or # `x-application/vnd.amazon+parquet`. The default value is # `text/csv;header=present`. # # * For text generation (LLMs fine-tuning): `text/csv;header=present` # or `x-application/vnd.amazon+parquet`. The default value is # `text/csv;header=present`. # @return [String] # # @!attribute [rw] compression_type # The allowed compression types depend on the input format and problem # type. We allow the compression type `Gzip` for `S3Prefix` inputs on # tabular data 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 (Required). # @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 text and image classification, time-series forecasting, as well # as text generation (LLMs fine-tuning) problem types, the supported # value is 1. For tabular problem types, the maximum value is 750. # @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 job V2s (jobs created by calling `CreateAutoMLJobV2`), this # field controls the runtime of the job candidate. # # For [TextGenerationJobConfig][3] problem types, the maximum time # defaults to 72 hours (259200 seconds). # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_StoppingCondition.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateHyperParameterTuningJob.html # [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TextClassificationJobConfig.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] candidate_generation_config # The configuration for generating a candidate for an AutoML job # (optional). # @return [Types::AutoMLCandidateGenerationConfig] # # @!attribute [rw] data_split_config # The configuration for splitting the input training dataset. # # Type: AutoMLDataSplitConfig # @return [Types::AutoMLDataSplitConfig] # # @!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-support # @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, :candidate_generation_config, :data_split_config, :mode) SENSITIVE = [] include Aws::Structure end # Specifies a metric to minimize or maximize as the objective of an # AutoML job. # # @!attribute [rw] metric_name # The name of the objective metric used to measure the predictive # quality of a machine learning system. During training, the model's # parameters are updated iteratively to optimize its performance based # on the feedback provided by the objective metric when evaluating the # model on the validation dataset. # # The list of available metrics supported by Autopilot and the default # metric applied when you do not specify a metric name explicitly # depend on the problem type. # # * For tabular problem types: # # * List of available metrics: # # * Regression: `MAE`, `MSE`, `R2`, `RMSE` # # * Binary classification: `Accuracy`, `AUC`, `BalancedAccuracy`, # `F1`, `Precision`, `Recall` # # * Multiclass classification: `Accuracy`, `BalancedAccuracy`, # `F1macro`, `PrecisionMacro`, `RecallMacro` # # For a description of each metric, see [Autopilot metrics for # classification and regression][1]. # # * Default objective metrics: # # * Regression: `MSE`. # # * Binary classification: `F1`. # # * Multiclass classification: `Accuracy`. # # * For image or text classification problem types: # # * List of available metrics: `Accuracy` # # For a description of each metric, see [Autopilot metrics for # text and image classification][2]. # # * Default objective metrics: `Accuracy` # # * For time-series forecasting problem types: # # * List of available metrics: `RMSE`, `wQL`, `Average wQL`, `MASE`, # `MAPE`, `WAPE` # # For a description of each metric, see [Autopilot metrics for # time-series forecasting][3]. # # * Default objective metrics: `AverageWeightedQuantileLoss` # # * For text generation problem types (LLMs fine-tuning): Fine-tuning # language models in Autopilot does not require setting the # `AutoMLJobObjective` field. Autopilot fine-tunes LLMs without # requiring multiple candidates to be trained and evaluated. # Instead, using your dataset, Autopilot directly fine-tunes your # target model to enhance a default objective metric, the # cross-entropy loss. After fine-tuning a language model, you can # evaluate the quality of its generated text using different # metrics. For a list of the available metrics, see [Metrics for # fine-tuning LLMs in Autopilot][4]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.html#autopilot-metrics # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/text-classification-data-format-and-metric.html # [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/timeseries-objective-metric.html # [4]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-llms-finetuning-metrics.html # @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] # # @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 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 V2. 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 V2 for the image # classification problem type. # @return [Types::ImageClassificationJobConfig] # # @!attribute [rw] text_classification_job_config # Settings used to configure an AutoML job V2 for the text # classification problem type. # @return [Types::TextClassificationJobConfig] # # @!attribute [rw] time_series_forecasting_job_config # Settings used to configure an AutoML job V2 for the time-series # forecasting problem type. # @return [Types::TimeSeriesForecastingJobConfig] # # @!attribute [rw] tabular_job_config # Settings used to configure an AutoML job V2 for the tabular problem # type (regression, classification). # @return [Types::TabularJobConfig] # # @!attribute [rw] text_generation_job_config # Settings used to configure an AutoML job V2 for the text generation # (LLMs fine-tuning) problem type. # # The text generation models that support fine-tuning in Autopilot are # currently accessible exclusively in regions supported by Canvas. # Refer to the documentation of Canvas for the [full list of its # supported Regions][1]. # # # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/canvas.html # @return [Types::TextGenerationJobConfig] # # @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, :time_series_forecasting_job_config, :tabular_job_config, :text_generation_job_config, :unknown) SENSITIVE = [] include Aws::Structure include Aws::Structure::Union class ImageClassificationJobConfig < AutoMLProblemTypeConfig; end class TextClassificationJobConfig < AutoMLProblemTypeConfig; end class TimeSeriesForecastingJobConfig < AutoMLProblemTypeConfig; end class TabularJobConfig < AutoMLProblemTypeConfig; end class TextGenerationJobConfig < AutoMLProblemTypeConfig; end class Unknown < AutoMLProblemTypeConfig; end end # Stores resolved attributes specific to the problem type of an AutoML # job V2. # # @note AutoMLProblemTypeResolvedAttributes is a union - when returned from an API call exactly one value will be set and the returned type will be a subclass of AutoMLProblemTypeResolvedAttributes corresponding to the set member. # # @!attribute [rw] tabular_resolved_attributes # The resolved attributes for the tabular problem type. # @return [Types::TabularResolvedAttributes] # # @!attribute [rw] text_generation_resolved_attributes # The resolved attributes for the text generation problem type. # @return [Types::TextGenerationResolvedAttributes] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLProblemTypeResolvedAttributes AWS API Documentation # class AutoMLProblemTypeResolvedAttributes < Struct.new( :tabular_resolved_attributes, :text_generation_resolved_attributes, :unknown) SENSITIVE = [] include Aws::Structure include Aws::Structure::Union class TabularResolvedAttributes < AutoMLProblemTypeResolvedAttributes; end class TextGenerationResolvedAttributes < AutoMLProblemTypeResolvedAttributes; end class Unknown < AutoMLProblemTypeResolvedAttributes; end end # The resolved attributes used to configure an AutoML job V2. # # @!attribute [rw] auto_ml_job_objective # Specifies a metric to minimize or maximize as the objective of an # AutoML job. # @return [Types::AutoMLJobObjective] # # @!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] auto_ml_problem_type_resolved_attributes # Defines the resolved attributes specific to a problem type. # @return [Types::AutoMLProblemTypeResolvedAttributes] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLResolvedAttributes AWS API Documentation # class AutoMLResolvedAttributes < Struct.new( :auto_ml_job_objective, :completion_criteria, :auto_ml_problem_type_resolved_attributes) SENSITIVE = [] include Aws::Structure 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 # The name and an example value of the hyperparameter that you want to # use in Autotune. If Automatic model tuning (AMT) determines that your # hyperparameter is eligible for Autotune, an optimal hyperparameter # range is selected for you. # # @!attribute [rw] name # The name of the hyperparameter to optimize using Autotune. # @return [String] # # @!attribute [rw] value_hint # An example value of the hyperparameter to optimize using Autotune. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoParameter AWS API Documentation # class AutoParameter < Struct.new( :name, :value_hint) 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] # # @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 # A flag to indicate if you want to use Autotune to automatically find # optimal values for the following fields: # # * [ParameterRanges][1]: The names and ranges of parameters that a # hyperparameter tuning job can optimize. # # * [ResourceLimits][2]: The maximum resources that can be used for a # training job. These resources include the maximum number of training # jobs, the maximum runtime of a tuning job, and the maximum number of # training jobs to run at the same time. # # * [TrainingJobEarlyStoppingType][3]: A flag that specifies whether or # not to use early stopping for training jobs launched by a # hyperparameter tuning job. # # * [RetryStrategy][4]: The number of times to retry a training job. # # * [Strategy][5]: Specifies how hyperparameter tuning chooses the # combinations of hyperparameter values to use for the training jobs # that it launches. # # * [ConvergenceDetected][6]: A flag to indicate that Automatic model # tuning (AMT) has detected model convergence. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html#sagemaker-Type-HyperParameterTuningJobConfig-ParameterRanges # [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ResourceLimits.html # [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html#sagemaker-Type-HyperParameterTuningJobConfig-TrainingJobEarlyStoppingType # [4]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html#sagemaker-Type-HyperParameterTrainingJobDefinition-RetryStrategy # [5]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html # [6]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ConvergenceDetected.html # # @!attribute [rw] mode # Set `Mode` to `Enabled` if you want to use Autotune. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Autotune AWS API Documentation # class Autotune < Struct.new( :mode) 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] # # @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] # # @!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] # # @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 subtract 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] # # @!attribute [rw] exclude_features_attribute # The attributes of the input data to exclude from the analysis. # @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, :exclude_features_attribute) 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] # # @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] # # @!attribute [rw] backtest_results # The Amazon S3 prefix to the accuracy metrics and the inference # results observed over the testing window. Available only for the # time-series forecasting problem type. # @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, :backtest_results) SENSITIVE = [] include Aws::Structure end # Stores the configuration information for how model candidates are # generated using an AutoML job V2. # # @!attribute [rw] algorithms_config # Stores the configuration information for the selection of algorithms # used to train model candidates on tabular data. # # The list of available algorithms to choose from depends on the # training mode set in [ `TabularJobConfig.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, `CandidateGenerationConfig` uses the # full set of algorithms for the given training mode. # # * When `AlgorithmsConfig` is not provided, # `CandidateGenerationConfig` uses the full set of algorithms for # the given training mode. # # For the list of all algorithms per problem type and 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_TabularJobConfig.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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CandidateGenerationConfig AWS API Documentation # class CandidateGenerationConfig < Struct.new( :algorithms_config) 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] # # @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 SageMaker Canvas application. # @return [Types::TimeSeriesForecastingSettings] # # @!attribute [rw] model_register_settings # The model registry settings for the SageMaker Canvas application. # @return [Types::ModelRegisterSettings] # # @!attribute [rw] workspace_settings # The workspace settings for the SageMaker Canvas application. # @return [Types::WorkspaceSettings] # # @!attribute [rw] identity_provider_o_auth_settings # The settings for connecting to an external data source with OAuth. # @return [Array] # # @!attribute [rw] direct_deploy_settings # The model deployment settings for the SageMaker Canvas application. # @return [Types::DirectDeploySettings] # # @!attribute [rw] kendra_settings # The settings for document querying. # @return [Types::KendraSettings] # # @!attribute [rw] generative_ai_settings # The generative AI settings for the SageMaker Canvas application. # @return [Types::GenerativeAiSettings] # # @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, :workspace_settings, :identity_provider_o_auth_settings, :direct_deploy_settings, :kendra_settings, :generative_ai_settings) SENSITIVE = [] include Aws::Structure end # Specifies the type and size of the endpoint capacity to activate for a # blue/green deployment, a rolling deployment, or a rollback strategy. # You can specify your batches as either instance count or the overall # percentage or your fleet. # # For a rollback strategy, if you don't specify the fields in this # object, or if you set the `Value` to 100%, then SageMaker uses a # blue/green rollback strategy and rolls all traffic back to the blue # fleet. # # @!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 Amazon SageMaker will by default base64 encode when # capturing the data. # # @!attribute [rw] csv_content_types # The list of all content type headers that Amazon SageMaker will # treat as CSV and capture accordingly. # @return [Array] # # @!attribute [rw] json_content_types # The list of all content type headers that SageMaker will treat as # JSON and capture accordingly. # @return [Array] # # @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] # # @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] # # @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] # # @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] # # @!attribute [rw] supported_compression_types # The allowed compression types, if data compression is used. # @return [Array] # # @!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] # # @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] # # @!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] # # @!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] # # @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. # # * 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. # # # # # # [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. # # 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]. # # # # # # [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. # # For a mix of multiple languages, use code `'xx'`. # # # # # # [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 # Details of an instance group in a SageMaker HyperPod cluster. # # @!attribute [rw] current_count # The number of instances that are currently in the instance group of # a SageMaker HyperPod cluster. # @return [Integer] # # @!attribute [rw] target_count # The number of instances you specified to add to the instance group # of a SageMaker HyperPod cluster. # @return [Integer] # # @!attribute [rw] instance_group_name # The name of the instance group of a SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] instance_type # The instance type of the instance group of a SageMaker HyperPod # cluster. # @return [String] # # @!attribute [rw] life_cycle_config # Details of LifeCycle configuration for the instance group. # @return [Types::ClusterLifeCycleConfig] # # @!attribute [rw] execution_role # The execution role for the instance group to assume. # @return [String] # # @!attribute [rw] threads_per_core # The number you specified to `TreadsPerCore` in `CreateCluster` for # enabling or disabling multithreading. For instance types that # support multithreading, you can specify 1 for disabling # multithreading and 2 for enabling multithreading. For more # information, see the reference table of [CPU cores and threads per # CPU core per instance type][1] in the *Amazon Elastic Compute Cloud # User Guide*. # # # # [1]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/cpu-options-supported-instances-values.html # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClusterInstanceGroupDetails AWS API Documentation # class ClusterInstanceGroupDetails < Struct.new( :current_count, :target_count, :instance_group_name, :instance_type, :life_cycle_config, :execution_role, :threads_per_core) SENSITIVE = [] include Aws::Structure end # The specifications of an instance group that you need to define. # # @!attribute [rw] instance_count # Specifies the number of instances to add to the instance group of a # SageMaker HyperPod cluster. # @return [Integer] # # @!attribute [rw] instance_group_name # Specifies the name of the instance group. # @return [String] # # @!attribute [rw] instance_type # Specifies the instance type of the instance group. # @return [String] # # @!attribute [rw] life_cycle_config # Specifies the LifeCycle configuration for the instance group. # @return [Types::ClusterLifeCycleConfig] # # @!attribute [rw] execution_role # Specifies an IAM execution role to be assumed by the instance group. # @return [String] # # @!attribute [rw] threads_per_core # Specifies the value for **Threads per core**. For instance types # that support multithreading, you can specify `1` for disabling # multithreading and `2` for enabling multithreading. For instance # types that doesn't support multithreading, specify `1`. For more # information, see the reference table of [CPU cores and threads per # CPU core per instance type][1] in the *Amazon Elastic Compute Cloud # User Guide*. # # # # [1]: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/cpu-options-supported-instances-values.html # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClusterInstanceGroupSpecification AWS API Documentation # class ClusterInstanceGroupSpecification < Struct.new( :instance_count, :instance_group_name, :instance_type, :life_cycle_config, :execution_role, :threads_per_core) SENSITIVE = [] include Aws::Structure end # Details of an instance in a SageMaker HyperPod cluster. # # @!attribute [rw] status # The status of an instance in a SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] message # The message from an instance in a SageMaker HyperPod cluster. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClusterInstanceStatusDetails AWS API Documentation # class ClusterInstanceStatusDetails < Struct.new( :status, :message) SENSITIVE = [] include Aws::Structure end # The LifeCycle configuration for a SageMaker HyperPod cluster. # # @!attribute [rw] source_s3_uri # An Amazon S3 bucket path where your LifeCycle scripts are stored. # @return [String] # # @!attribute [rw] on_create # The directory of the LifeCycle script under `SourceS3Uri`. This # LifeCycle script runs during cluster creation. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClusterLifeCycleConfig AWS API Documentation # class ClusterLifeCycleConfig < Struct.new( :source_s3_uri, :on_create) SENSITIVE = [] include Aws::Structure end # Details of an instance (also called a *node* interchangeably) in a # SageMaker HyperPod cluster. # # @!attribute [rw] instance_group_name # The instance group name in which the instance is. # @return [String] # # @!attribute [rw] instance_id # The ID of the instance. # @return [String] # # @!attribute [rw] instance_status # The status of the instance. # @return [Types::ClusterInstanceStatusDetails] # # @!attribute [rw] instance_type # The type of the instance. # @return [String] # # @!attribute [rw] launch_time # The time when the instance is launched. # @return [Time] # # @!attribute [rw] life_cycle_config # The LifeCycle configuration applied to the instance. # @return [Types::ClusterLifeCycleConfig] # # @!attribute [rw] threads_per_core # The number of threads per CPU core you specified under # `CreateCluster`. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClusterNodeDetails AWS API Documentation # class ClusterNodeDetails < Struct.new( :instance_group_name, :instance_id, :instance_status, :instance_type, :launch_time, :life_cycle_config, :threads_per_core) SENSITIVE = [] include Aws::Structure end # Lists a summary of the properties of an instance (also called a *node* # interchangeably) of a SageMaker HyperPod cluster. # # @!attribute [rw] instance_group_name # The name of the instance group in which the instance is. # @return [String] # # @!attribute [rw] instance_id # The ID of the instance. # @return [String] # # @!attribute [rw] instance_type # The type of the instance. # @return [String] # # @!attribute [rw] launch_time # The time when the instance is launched. # @return [Time] # # @!attribute [rw] instance_status # The status of the instance. # @return [Types::ClusterInstanceStatusDetails] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClusterNodeSummary AWS API Documentation # class ClusterNodeSummary < Struct.new( :instance_group_name, :instance_id, :instance_type, :launch_time, :instance_status) SENSITIVE = [] include Aws::Structure end # Lists a summary of the properties of a SageMaker HyperPod cluster. # # @!attribute [rw] cluster_arn # The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] cluster_name # The name of the SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] creation_time # The time when the SageMaker HyperPod cluster is created. # @return [Time] # # @!attribute [rw] cluster_status # The status of the SageMaker HyperPod cluster. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ClusterSummary AWS API Documentation # class ClusterSummary < Struct.new( :cluster_arn, :cluster_name, :creation_time, :cluster_status) SENSITIVE = [] include Aws::Structure end # The Code Editor application settings. # # For more information about Code Editor, see [Get started with Code # Editor in Amazon SageMaker][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/code-editor.html # # @!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] lifecycle_config_arns # The Amazon Resource Name (ARN) of the Code Editor application # lifecycle configuration. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CodeEditorAppSettings AWS API Documentation # class CodeEditorAppSettings < Struct.new( :default_resource_spec, :lifecycle_config_arns) 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 for your collection. # # @note CollectionConfig is a union - when making an API calls you must set exactly one of the members. # # @note CollectionConfig is a union - when returned from an API call exactly one value will be set and the returned type will be a subclass of CollectionConfig corresponding to the set member. # # @!attribute [rw] vector_config # Configuration for your vector collection type. # # * `Dimension`: The number of elements in your vector. # # ^ # @return [Types::VectorConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CollectionConfig AWS API Documentation # class CollectionConfig < Struct.new( :vector_config, :unknown) SENSITIVE = [] include Aws::Structure include Aws::Structure::Union class VectorConfig < CollectionConfig; end class Unknown < CollectionConfig; end 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] # # @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 # The configuration used to run the application image container. # # @!attribute [rw] container_arguments # The arguments for the container when you're running the # application. # @return [Array] # # @!attribute [rw] container_entrypoint # The entrypoint used to run the application in the container. # @return [Array] # # @!attribute [rw] container_environment_variables # The environment variables to set in the container # @return [Hash] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ContainerConfig AWS API Documentation # class ContainerConfig < Struct.new( :container_arguments, :container_entrypoint, :container_environment_variables) 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]. # # 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. # # # # # # [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]. # # 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. # # # # # # [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]. # # The model artifacts must be in an S3 bucket that is in the same # region as the model or endpoint you are creating. # # # # 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] model_data_source # Specifies the location of ML model data to deploy. # # Currently you cannot use `ModelDataSource` in conjunction with # SageMaker batch transform, SageMaker serverless endpoints, SageMaker # multi-model endpoints, and SageMaker Marketplace. # # # @return [Types::ModelDataSource] # # @!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] # # @!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, :model_data_source, :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] # # @!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] # # @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] # # @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] # # @!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] # # @!attribute [rw] jupyter_lab_app_image_config # The `JupyterLabAppImageConfig`. You can only specify one image # kernel in the `AppImageConfig` API. This kernel is shown to users # before the image starts. After the image runs, all kernels are # visible in JupyterLab. # @return [Types::JupyterLabAppImageConfig] # # @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, :jupyter_lab_app_image_config) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] app_image_config_arn # The 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] space_name # The name of the space. If this value is not set, then # `UserProfileName` 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] # # @!attribute [rw] resource_spec # The instance type and the Amazon Resource Name (ARN) of the # SageMaker image created on the instance. # # 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. # # # @return [Types::ResourceSpec] # # @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, :space_name, :app_type, :app_name, :tags, :resource_spec) 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] # # @!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] # # @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] # # @!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 [ 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 # Specifies a metric to minimize or maximize as the objective of a # job. If not specified, the default objective metric depends on the # problem type. See [AutoMLJobObjective][1] for the default values. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobObjective.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] # # @!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 the # [InputDataConfig][1] attribute in the `CreateAutoMLJob` input # parameters. The supported formats depend on the problem type: # # * For tabular problem types: `S3Prefix`, `ManifestFile`. # # * For image classification: `S3Prefix`, `ManifestFile`, # `AugmentedManifestFile`. # # * For text classification: `S3Prefix`. # # * For time-series forecasting: `S3Prefix`. # # * For text generation (LLMs fine-tuning): `S3Prefix`. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJob.html#sagemaker-CreateAutoMLJob-request-InputDataConfig # @return [Array] # # @!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] # # @!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. If not specified, the default objective metric depends on the # problem type. For the list of default values per problem type, see # [AutoMLJobObjective][1]. # # * For tabular problem types: You must either provide both the # `AutoMLJobObjective` and indicate the type of supervised learning # problem in `AutoMLProblemTypeConfig` # (`TabularJobConfig.ProblemType`), or none at all. # # * For text generation problem types (LLMs fine-tuning): Fine-tuning # language models in Autopilot does not require setting the # `AutoMLJobObjective` field. Autopilot fine-tunes LLMs without # requiring multiple candidates to be trained and evaluated. # Instead, using your dataset, Autopilot directly fine-tunes your # target model to enhance a default objective metric, the # cross-entropy loss. After fine-tuning a language model, you can # evaluate the quality of its generated text using different # metrics. For a list of the available metrics, see [Metrics for # fine-tuning LLMs in Autopilot][2]. # # # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLJobObjective.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-llms-finetuning-metrics.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. # # The validation and training datasets must contain the same headers. # For jobs created by calling `CreateAutoMLJob`, the validation # dataset must be less than 2 GB in size. # # This attribute must not be set for the time-series forecasting # problem type, as Autopilot automatically splits the input dataset # into training and validation sets. # # # @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] cluster_name # The name for the new SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] instance_groups # The instance groups to be created in the SageMaker HyperPod cluster. # @return [Array] # # @!attribute [rw] vpc_config # Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.html # @return [Types::VpcConfig] # # @!attribute [rw] tags # Custom tags for managing the SageMaker HyperPod cluster as an Amazon # Web Services resource. You can add tags to your cluster in the same # way you add them in other Amazon Web Services services that support # tagging. To learn more about tagging Amazon Web Services resources # in general, see [Tagging Amazon Web Services Resources User # Guide][1]. # # # # [1]: https://docs.aws.amazon.com/tag-editor/latest/userguide/tagging.html # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateClusterRequest AWS API Documentation # class CreateClusterRequest < Struct.new( :cluster_name, :instance_groups, :vpc_config, :tags) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] cluster_arn # The Amazon Resource Name (ARN) of the cluster. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateClusterResponse AWS API Documentation # class CreateClusterResponse < Struct.new( :cluster_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] # # @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] # # @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] # # @!attribute [rw] tags # A list of tags to apply to the context. # @return [Array] # # @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] # # @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] # # @!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] domain_settings # A collection of `Domain` settings. # @return [Types::DomainSettings] # # @!attribute [rw] subnet_ids # The VPC subnets that the domain uses for communication. # @return [Array] # # @!attribute [rw] vpc_id # The ID of the Amazon Virtual Private Cloud (VPC) that the domain # 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] # # @!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 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. If setting up the domain for use with RStudio, this # value must be set to `Service`. # @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/CreateDomainRequest AWS API Documentation # class CreateDomainRequest < Struct.new( :domain_name, :auth_mode, :default_user_settings, :domain_settings, :subnet_ids, :vpc_id, :tags, :app_network_access_type, :home_efs_file_system_kms_key_id, :kms_key_id, :app_security_group_management, :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] # # @!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] # # @!attribute [rw] tags # List of tags with which to tag the edge deployment plan. # @return [Array] # # @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] # # @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] # # @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] # # @!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] # # @!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] # # 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]. # # # # # # [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] # # @!attribute [rw] execution_role_arn # The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker # can assume to perform actions on your behalf. For more information, # see [SageMaker Roles][1]. # # To be able to pass this role to Amazon SageMaker, the caller of this # action must have the `iam:PassRole` permission. # # # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html # @return [String] # # @!attribute [rw] vpc_config # Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.html # @return [Types::VpcConfig] # # @!attribute [rw] enable_network_isolation # Sets whether all model containers deployed to the endpoint are # isolated. If they are, no inbound or outbound network calls can be # made to or from the model containers. # @return [Boolean] # # @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, :execution_role_arn, :vpc_config, :enable_network_isolation) 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] # # @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] # # @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] # # @!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] throughput_config # Used to set feature group throughput configuration. There are two # modes: `ON_DEMAND` and `PROVISIONED`. With on-demand mode, you are # charged for data reads and writes that your application performs on # your feature group. You do not need to specify read and write # throughput because Feature Store accommodates your workloads as they # ramp up and down. You can switch a feature group to on-demand only # once in a 24 hour period. With provisioned throughput mode, you # specify the read and write capacity per second that you expect your # application to require, and you are billed based on those limits. # Exceeding provisioned throughput will result in your requests being # throttled. # # Note: `PROVISIONED` throughput mode is supported only for feature # groups that are offline-only, or use the [ `Standard` ][1] tier # online store. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OnlineStoreConfig.html#sagemaker-Type-OnlineStoreConfig-StorageType # @return [Types::ThroughputConfig] # # @!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] # # @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, :throughput_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] # # @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] # # @!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] # # @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] # # @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] # # @!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. # # 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. # # # @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] # # @!attribute [rw] autotune # Configures SageMaker Automatic model tuning (AMT) to automatically # find optimal parameters for the following fields: # # * [ParameterRanges][1]: The names and ranges of parameters that a # hyperparameter tuning job can optimize. # # * [ResourceLimits][2]: The maximum resources that can be used for a # training job. These resources include the maximum number of # training jobs, the maximum runtime of a tuning job, and the # maximum number of training jobs to run at the same time. # # * [TrainingJobEarlyStoppingType][3]: A flag that specifies whether # or not to use early stopping for training jobs launched by a # hyperparameter tuning job. # # * [RetryStrategy][4]: The number of times to retry a training job. # # * [Strategy][5]: Specifies how hyperparameter tuning chooses the # combinations of hyperparameter values to use for the training jobs # that it launches. # # * [ConvergenceDetected][6]: A flag to indicate that Automatic model # tuning (AMT) has detected model convergence. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html#sagemaker-Type-HyperParameterTuningJobConfig-ParameterRanges # [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ResourceLimits.html # [3]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html#sagemaker-Type-HyperParameterTuningJobConfig-TrainingJobEarlyStoppingType # [4]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTrainingJobDefinition.html#sagemaker-Type-HyperParameterTrainingJobDefinition-RetryStrategy # [5]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_HyperParameterTuningJobConfig.html # [6]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ConvergenceDetected.html # @return [Types::Autotune] # # @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, :autotune) 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] # # @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 ECR URI in the # following format: # # `.dkr.ecr..amazonaws.com/` # @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] # # @!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] inference_component_name # A unique name to assign to the inference component. # @return [String] # # @!attribute [rw] endpoint_name # The name of an existing endpoint where you host the inference # component. # @return [String] # # @!attribute [rw] variant_name # The name of an existing production variant where you host the # inference component. # @return [String] # # @!attribute [rw] specification # Details about the resources to deploy with this inference component, # including the model, container, and compute resources. # @return [Types::InferenceComponentSpecification] # # @!attribute [rw] runtime_config # Runtime settings for a model that is deployed with an inference # component. # @return [Types::InferenceComponentRuntimeConfig] # # @!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*. # # # # [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateInferenceComponentInput AWS API Documentation # class CreateInferenceComponentInput < Struct.new( :inference_component_name, :endpoint_name, :variant_name, :specification, :runtime_config, :tags) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] inference_component_arn # The Amazon Resource Name (ARN) of the inference component. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateInferenceComponentOutput AWS API Documentation # class CreateInferenceComponentOutput < Struct.new( :inference_component_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] # # @!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] # # @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] # # @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":"

Add header

Add Instructions

", # "fullInstruction":"

Add additional instructions.

"\}`. 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] # # @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] # # @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 or Amazon Resource Name (ARN) 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] # # @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] # # @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] # # @!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]. # # To be able to pass this role to SageMaker, the caller of this API # must have the `iam:PassRole` permission. # # # # # # [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] # # @!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] # # @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 you can run with models # based on this model package, including the following information: # # * 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*. # # If you supply `ModelPackageGroupName`, your model package belongs to # the model group you specify and uses the tags associated with the # model group. In this case, you cannot supply a `tag` argument. # # # # [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html # @return [Array] # # @!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] 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] customer_metadata_properties # The metadata properties associated with the model package versions. # @return [Hash] # # @!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] 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] # # @!attribute [rw] skip_model_validation # Indicates if you want to skip model validation. # @return [String] # # @!attribute [rw] source_uri # The URI of the source for the model package. If you want to clone a # model package, set it to the model package Amazon Resource Name # (ARN). If you want to register a model, set it to the model ARN. # @return [String] # # @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, :domain, :task, :sample_payload_url, :customer_metadata_properties, :drift_check_baselines, :additional_inference_specifications, :skip_model_validation, :source_uri) 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] # # @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] # # @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] # # @!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]. # # To be able to pass this role to SageMaker, the caller of this API # must have the `iam:PassRole` permission. # # # # # # [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] # # @!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] # # @!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] # # @!attribute [rw] root_access # Whether root access is enabled or disabled for users of the notebook # instance. The default value is `Enabled`. # # 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. # # # @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] # # @!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] # # @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][1] of the pipeline. # # # # [1]: https://aws-sagemaker-mlops.github.io/sagemaker-model-building-pipeline-definition-JSON-schema/ # @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] # # @!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] # # @!attribute [rw] landing_uri # The landing page that the user is directed to when accessing the # presigned URL. Using this value, users can access Studio or Studio # Classic, even if it is not the default experience for the domain. # The supported values are: # # * `studio::relative/path`: Directs users to the relative path in # Studio. # # * `app:JupyterServer:relative/path`: Directs users to the relative # path in the Studio Classic application. # # * `app:JupyterLab:relative/path`: Directs users to the relative path # in the JupyterLab application. # # * `app:RStudioServerPro:relative/path`: Directs users to the # relative path in the RStudio application. # # * `app:CodeEditor:relative/path`: Directs users to the relative path # in the Code Editor, based on Code-OSS, Visual Studio Code - Open # Source application. # # * `app:Canvas:relative/path`: Directs users to the relative path in # the Canvas application. # @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, :landing_uri) 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] # # @!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] # # @!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] # # @!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] # # @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] # # @!attribute [rw] space_settings # A collection of space settings. # @return [Types::SpaceSettings] # # @!attribute [rw] ownership_settings # A collection of ownership settings. # @return [Types::OwnershipSettings] # # @!attribute [rw] space_sharing_settings # A collection of space sharing settings. # @return [Types::SpaceSharingSettings] # # @!attribute [rw] space_display_name # The name of the space that appears in the SageMaker Studio UI. # @return [String] # # @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, :ownership_settings, :space_sharing_settings, :space_display_name) 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 Amazon SageMaker Studio Lifecycle Configuration to # create. # @return [String] # # @!attribute [rw] studio_lifecycle_config_content # The content of your Amazon SageMaker 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] # # @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] # # @!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]. # # To be able to pass this role to SageMaker, the caller of this API # must have the `iam:PassRole` permission. # # # # # # [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. # # Your input must be in the same Amazon Web Services region as your # training job. # @return [Array] # # @!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] # # @!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] # # @!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] # # @!attribute [rw] environment # The environment variables to set in the Docker container. # @return [Hash] # # @!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] remote_debug_config # Configuration for remote debugging. To learn more about the remote # debugging functionality of SageMaker, see [Access a training # container through Amazon Web Services Systems Manager (SSM) for # remote debugging][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-remote-debugging.html # @return [Types::RemoteDebugConfig] # # @!attribute [rw] infra_check_config # Contains information about the infrastructure health check # configuration for the training job. # @return [Types::InfraCheckConfig] # # @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, :remote_debug_config, :infra_check_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/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] # # @!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] # # @!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] # # @!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] # # @!attribute [rw] output_artifacts # The output artifacts for the component. Examples of output artifacts # are metrics, snapshots, logs, and images. # @return [Hash] # # @!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] # # @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] # # @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] # # @!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] # # @!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] # # @!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 Amazon Web Services Billing and Cost # Management User Guide. # # # # [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] # # @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 file system, created by you, that you assign to a user profile or # space for an Amazon SageMaker Domain. Permitted users can access this # file system in Amazon SageMaker Studio. # # @note CustomFileSystem is a union - when making an API calls you must set exactly one of the members. # # @note CustomFileSystem is a union - when returned from an API call exactly one value will be set and the returned type will be a subclass of CustomFileSystem corresponding to the set member. # # @!attribute [rw] efs_file_system # A custom file system in Amazon EFS. # @return [Types::EFSFileSystem] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CustomFileSystem AWS API Documentation # class CustomFileSystem < Struct.new( :efs_file_system, :unknown) SENSITIVE = [] include Aws::Structure include Aws::Structure::Union class EfsFileSystem < CustomFileSystem; end class Unknown < CustomFileSystem; end end # The settings for assigning a custom file system to a user profile or # space for an Amazon SageMaker Domain. Permitted users can access this # file system in Amazon SageMaker Studio. # # @note CustomFileSystemConfig is a union - when making an API calls you must set exactly one of the members. # # @note CustomFileSystemConfig is a union - when returned from an API call exactly one value will be set and the returned type will be a subclass of CustomFileSystemConfig corresponding to the set member. # # @!attribute [rw] efs_file_system_config # The settings for a custom Amazon EFS file system. # @return [Types::EFSFileSystemConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CustomFileSystemConfig AWS API Documentation # class CustomFileSystemConfig < Struct.new( :efs_file_system_config, :unknown) SENSITIVE = [] include Aws::Structure include Aws::Structure::Union class EfsFileSystemConfig < CustomFileSystemConfig; end class Unknown < CustomFileSystemConfig; end 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 # Details about the POSIX identity that is used for file system # operations. # # @!attribute [rw] uid # The POSIX user ID. # @return [Integer] # # @!attribute [rw] gid # The POSIX group ID. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CustomPosixUserConfig AWS API Documentation # class CustomPosixUserConfig < Struct.new( :uid, :gid) SENSITIVE = [] include Aws::Structure end # A customized metric. # # @!attribute [rw] metric_name # The name of the customized metric. # @return [String] # # @!attribute [rw] namespace # The namespace of the customized metric. # @return [String] # # @!attribute [rw] statistic # The statistic of the customized metric. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CustomizedMetricSpecification AWS API Documentation # class CustomizedMetricSpecification < Struct.new( :metric_name, :namespace, :statistic) 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 an 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] # # @!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] # # @!attribute [rw] container_arguments # The arguments to send to the container that the monitoring job runs. # @return [Array] # # @!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 # flattened 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] # # @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] # # @!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] # # @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] # # @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 default EBS storage settings that applies to private # spaces created within a domain or user profile. # # @!attribute [rw] default_ebs_volume_size_in_gb # The default size of the EBS storage volume for a private space. # @return [Integer] # # @!attribute [rw] maximum_ebs_volume_size_in_gb # The maximum size of the EBS storage volume for a private space. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DefaultEbsStorageSettings AWS API Documentation # class DefaultEbsStorageSettings < Struct.new( :default_ebs_volume_size_in_gb, :maximum_ebs_volume_size_in_gb) 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 VPC that the space uses for # communication. # @return [Array] # # @!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 # The default storage settings for a private space. # # @!attribute [rw] default_ebs_storage_settings # The default EBS storage settings for a private space. # @return [Types::DefaultEbsStorageSettings] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DefaultSpaceStorageSettings AWS API Documentation # class DefaultSpaceStorageSettings < Struct.new( :default_ebs_storage_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] space_name # The name of the space. If this value is not set, then # `UserProfileName` 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] # # @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, :space_name, :app_type, :app_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] cluster_name # The string name or the Amazon Resource Name (ARN) of the SageMaker # HyperPod cluster to delete. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteClusterRequest AWS API Documentation # class DeleteClusterRequest < Struct.new( :cluster_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] cluster_arn # The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster to # delete. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteClusterResponse AWS API Documentation # class DeleteClusterResponse < Struct.new( :cluster_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] compilation_job_name # The name of the compilation job to delete. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteCompilationJobRequest AWS API Documentation # class DeleteCompilationJobRequest < Struct.new( :compilation_job_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] hyper_parameter_tuning_job_name # The name of the hyperparameter tuning job that you want to delete. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteHyperParameterTuningJobRequest AWS API Documentation # class DeleteHyperParameterTuningJobRequest < Struct.new( :hyper_parameter_tuning_job_name) SENSITIVE = [] include Aws::Structure 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] inference_component_name # The name of the inference component to delete. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteInferenceComponentInput AWS API Documentation # class DeleteInferenceComponentInput < Struct.new( :inference_component_name) SENSITIVE = [] include Aws::Structure 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 Amazon SageMaker 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] # # @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] rolling_update_policy # Specifies a rolling deployment strategy for updating a SageMaker # endpoint. # @return [Types::RollingUpdatePolicy] # # @!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, :rolling_update_policy, :auto_rollback_configuration) SENSITIVE = [] include Aws::Structure end # A set of recommended deployment configurations for the model. To get # more advanced recommendations, see # [CreateInferenceRecommendationsJob][1] to create an inference # recommendation job. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceRecommendationsJob.html # # @!attribute [rw] recommendation_status # Status of the deployment recommendation. The status `NOT_APPLICABLE` # means that SageMaker is unable to provide a default recommendation # for the model using the information provided. If the deployment # status is `IN_PROGRESS`, retry your API call after a few seconds to # get a `COMPLETED` deployment recommendation. # @return [String] # # @!attribute [rw] real_time_inference_recommendations # A list of [RealTimeInferenceRecommendation][1] items. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_RealTimeInferenceRecommendation.html # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeploymentRecommendation AWS API Documentation # class DeploymentRecommendation < Struct.new( :recommendation_status, :real_time_inference_recommendations) 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] # # @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 # Information that SageMaker Neo automatically derived about the model. # # @!attribute [rw] derived_data_input_config # The data input configuration that SageMaker Neo automatically # derived for the model. When SageMaker Neo derives this information, # you don't need to specify the data input configuration when you # create a compilation job. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DerivedInformation AWS API Documentation # class DerivedInformation < Struct.new( :derived_data_input_config) 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] # # @!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 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] # # @!attribute [rw] jupyter_lab_app_image_config # The configuration of the JupyterLab app. # @return [Types::JupyterLabAppImageConfig] # # @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, :jupyter_lab_app_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] space_name # The name of the space. # @return [String] # # @!attribute [rw] app_type # The type of app. # @return [String] # # @!attribute [rw] app_name # The name of the app. # @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, :space_name, :app_type, :app_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] space_name # The name of the space. If this value is not set, then # `UserProfileName` must be set. # @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 of the application. # # After an application has been shut down for 24 hours, SageMaker # deletes all metadata for the application. To be considered an update # and retain application metadata, applications must be restarted # within 24 hours after the previous application has been shut down. # After this time window, creation of an application is considered a # new application rather than an update of the previous application. # # # @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] # # @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, :space_name, :status, :last_health_check_timestamp, :last_user_activity_timestamp, :creation_time, :failure_reason, :resource_spec) 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] # # @!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] # # @!attribute [rw] output_data_config # Returns the job's output data config. # @return [Types::AutoMLOutputDataConfig] # # @!attribute [rw] role_arn # The ARN of the 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] # # @!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 # inferred. # @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 job V2 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 job V2. # @return [String] # # @!attribute [rw] auto_ml_job_arn # Returns the Amazon Resource Name (ARN) of the AutoML job V2. # @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] # # @!attribute [rw] output_data_config # Returns the job's output data config. # @return [Types::AutoMLOutputDataConfig] # # @!attribute [rw] role_arn # The ARN of the 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] auto_ml_problem_type_config # Returns the configuration settings of the problem type set for the # AutoML job V2. # @return [Types::AutoMLProblemTypeConfig] # # @!attribute [rw] auto_ml_problem_type_config_name # Returns the name of the problem type configuration set for the # AutoML job V2. # @return [String] # # @!attribute [rw] creation_time # Returns the creation time of the AutoML job V2. # @return [Time] # # @!attribute [rw] end_time # Returns the end time of the AutoML job V2. # @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 job V2, when # applicable. # @return [String] # # @!attribute [rw] partial_failure_reasons # Returns a list of reasons for partial failures within an AutoML job # V2. # @return [Array] # # @!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 job V2. # @return [String] # # @!attribute [rw] auto_ml_job_secondary_status # Returns the secondary status of the AutoML job V2. # @return [String] # # @!attribute [rw] auto_ml_job_artifacts # The artifacts that are generated during an AutoML job. # @return [Types::AutoMLJobArtifacts] # # @!attribute [rw] resolved_attributes # Returns the resolved attributes used by the AutoML job V2. # @return [Types::AutoMLResolvedAttributes] # # @!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, :auto_ml_problem_type_config_name, :creation_time, :end_time, :last_modified_time, :failure_reason, :partial_failure_reasons, :best_candidate, :auto_ml_job_status, :auto_ml_job_secondary_status, :auto_ml_job_artifacts, :resolved_attributes, :model_deploy_config, :model_deploy_result, :data_split_config, :security_config) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] cluster_name # The string name or the Amazon Resource Name (ARN) of the SageMaker # HyperPod cluster in which the instance is. # @return [String] # # @!attribute [rw] node_id # The ID of the instance. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeClusterNodeRequest AWS API Documentation # class DescribeClusterNodeRequest < Struct.new( :cluster_name, :node_id) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] node_details # The details of the instance. # @return [Types::ClusterNodeDetails] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeClusterNodeResponse AWS API Documentation # class DescribeClusterNodeResponse < Struct.new( :node_details) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] cluster_name # The string name or the Amazon Resource Name (ARN) of the SageMaker # HyperPod cluster. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeClusterRequest AWS API Documentation # class DescribeClusterRequest < Struct.new( :cluster_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] cluster_arn # The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] cluster_name # The name of the SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] cluster_status # The status of the SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] creation_time # The time when the SageMaker Cluster is created. # @return [Time] # # @!attribute [rw] failure_message # The failure message of the SageMaker HyperPod cluster. # @return [String] # # @!attribute [rw] instance_groups # The instance groups of the SageMaker HyperPod cluster. # @return [Array] # # @!attribute [rw] vpc_config # Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.html # @return [Types::VpcConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeClusterResponse AWS API Documentation # class DescribeClusterResponse < Struct.new( :cluster_arn, :cluster_name, :cluster_status, :creation_time, :failure_message, :instance_groups, :vpc_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] # # @!attribute [rw] derived_information # Information that SageMaker Neo automatically derived about the # model. # @return [Types::DerivedInformation] # # @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, :derived_information) 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] # # @!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] # # @!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 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] single_sign_on_application_arn # The ARN of the application managed by SageMaker in IAM Identity # Center. This value is only returned for domains created after # October 1, 2023. # @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] 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] 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] domain_settings # A collection of `Domain` settings. # @return [Types::DomainSettings] # # @!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 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 the domain uses for communication. # @return [Array] # # @!attribute [rw] url # The domain's URL. # @return [String] # # @!attribute [rw] vpc_id # The ID of the Amazon Virtual Private Cloud (VPC) that the domain # 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] 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] 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, :single_sign_on_application_arn, :status, :creation_time, :last_modified_time, :failure_reason, :security_group_id_for_domain_boundary, :auth_mode, :default_user_settings, :domain_settings, :app_network_access_type, :home_efs_file_system_kms_key_id, :subnet_ids, :url, :vpc_id, :kms_key_id, :app_security_group_management, :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] # # @!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] # # @!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] # # @!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] # # @!attribute [rw] execution_role_arn # The Amazon Resource Name (ARN) of the IAM role that you assigned to # the endpoint configuration. # @return [String] # # @!attribute [rw] vpc_config # Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.html # @return [Types::VpcConfig] # # @!attribute [rw] enable_network_isolation # Indicates whether all model containers deployed to the endpoint are # isolated. If they are, no inbound or outbound network calls can be # made to or from the model containers. # @return [Boolean] # # @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, :execution_role_arn, :vpc_config, :enable_network_isolation) 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] # # @!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. # # * `UpdateRollbackFailed`: Both the rolling deployment and # auto-rollback failed. Your endpoint is in service with a mix of # the old and new endpoint configurations. For information about how # to remedy this issue and restore the endpoint's status to # `InService`, see [Rolling Deployments][6]. # # # # [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 # [6]: https://docs.aws.amazon.com/sagemaker/latest/dg/deployment-guardrails-rolling.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] # # @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 or Amazon Resource Name (ARN) 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] # # @!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] throughput_config # Active throughput configuration of the feature group. There are two # modes: `ON_DEMAND` and `PROVISIONED`. With on-demand mode, you are # charged for data reads and writes that your application performs on # your feature group. You do not need to specify read and write # throughput because Feature Store accommodates your workloads as they # ramp up and down. You can switch a feature group to on-demand only # once in a 24 hour period. With provisioned throughput mode, you # specify the read and write capacity per second that you expect your # application to require, and you are billed based on those limits. # Exceeding provisioned throughput will result in your requests being # throttled. # # Note: `PROVISIONED` throughput mode is supported only for feature # groups that are offline-only, or use the [ `Standard` ][1] tier # online store. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OnlineStoreConfig.html#sagemaker-Type-OnlineStoreConfig-StorageType # @return [Types::ThroughputConfigDescription] # # @!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, :throughput_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 or Amazon Resource Name (ARN) 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] # # @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] # # @!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] # # @!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] # # @!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 hyperparameter 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] # # @!attribute [rw] hyper_parameter_tuning_job_status # The status of the tuning job. # @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] autotune # A flag to indicate if autotune is enabled for the hyperparameter # tuning job. # @return [Types::Autotune] # # @!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, :autotune, :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] inference_component_name # The name of the inference component. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeInferenceComponentInput AWS API Documentation # class DescribeInferenceComponentInput < Struct.new( :inference_component_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] inference_component_name # The name of the inference component. # @return [String] # # @!attribute [rw] inference_component_arn # The Amazon Resource Name (ARN) of the inference component. # @return [String] # # @!attribute [rw] endpoint_name # The name of the endpoint that hosts the inference component. # @return [String] # # @!attribute [rw] endpoint_arn # The Amazon Resource Name (ARN) of the endpoint that hosts the # inference component. # @return [String] # # @!attribute [rw] variant_name # The name of the production variant that hosts the inference # component. # @return [String] # # @!attribute [rw] failure_reason # If the inference component status is `Failed`, the reason for the # failure. # @return [String] # # @!attribute [rw] specification # Details about the resources that are deployed with this inference # component. # @return [Types::InferenceComponentSpecificationSummary] # # @!attribute [rw] runtime_config # Details about the runtime settings for the model that is deployed # with the inference component. # @return [Types::InferenceComponentRuntimeConfigSummary] # # @!attribute [rw] creation_time # The time when the inference component was created. # @return [Time] # # @!attribute [rw] last_modified_time # The time when the inference component was last updated. # @return [Time] # # @!attribute [rw] inference_component_status # The status of the inference component. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeInferenceComponentOutput AWS API Documentation # class DescribeInferenceComponentOutput < Struct.new( :inference_component_name, :inference_component_arn, :endpoint_name, :endpoint_arn, :variant_name, :failure_reason, :specification, :runtime_config, :creation_time, :last_modified_time, :inference_component_status) 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] # # @!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] # # @!attribute [rw] endpoint_performances # The performance results from running an Inference Recommender job on # an existing endpoint. # @return [Array] # # @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] # # @!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 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 or Amazon Resource Name (ARN) 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 or Amazon Resource Name (ARN) 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 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] # # @!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] # # @!attribute [rw] deployment_recommendation # A set of recommended deployment configurations for the model. # @return [Types::DeploymentRecommendation] # # @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, :deployment_recommendation) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] model_package_group_name # The name of the 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 you can 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] 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] customer_metadata_properties # The metadata properties associated with the model package versions. # @return [Hash] # # @!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] 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] # # @!attribute [rw] skip_model_validation # Indicates if you want to skip model validation. # @return [String] # # @!attribute [rw] source_uri # The URI of the source for the model package. # @return [String] # # @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, :domain, :task, :sample_payload_url, :customer_metadata_properties, :drift_check_baselines, :additional_inference_specifications, :skip_model_validation, :source_uri) 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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!attribute [rw] root_access # Whether root access is enabled or disabled for users of the notebook # instance. # # 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. # # # @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] # # @!attribute [rw] selective_execution_config # The selective execution configuration applied to the pipeline run. # @return [Types::SelectiveExecutionConfig] # # @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, :selective_execution_config) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] pipeline_name # The name or Amazon Resource Name (ARN) 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] # # @!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] # # @!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 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] space_settings # A collection of space settings. # @return [Types::SpaceSettings] # # @!attribute [rw] ownership_settings # The collection of ownership settings for a space. # @return [Types::OwnershipSettings] # # @!attribute [rw] space_sharing_settings # The collection of space sharing settings for a space. # @return [Types::SpaceSharingSettings] # # @!attribute [rw] space_display_name # The name of the space that appears in the Amazon SageMaker Studio # UI. # @return [String] # # @!attribute [rw] url # Returns the URL of the space. If the space is created with Amazon # Web Services IAM Identity Center (Successor to Amazon Web Services # Single Sign-On) authentication, users can navigate to the URL after # appending the respective redirect parameter for the application type # to be federated through Amazon Web Services IAM Identity Center. # # The following application types are supported: # # * Studio Classic: `&redirect=JupyterServer` # # * JupyterLab: `&redirect=JupyterLab` # # * Code Editor, based on Code-OSS, Visual Studio Code - Open Source: # `&redirect=CodeEditor` # @return [String] # # @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, :ownership_settings, :space_sharing_settings, :space_display_name, :url) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] studio_lifecycle_config_name # The name of the Amazon SageMaker 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 Amazon SageMaker Studio Lifecycle Configuration that # is described. # @return [String] # # @!attribute [rw] creation_time # The creation time of the Amazon SageMaker Studio Lifecycle # Configuration. # @return [Time] # # @!attribute [rw] last_modified_time # This value is equivalent to CreationTime because Amazon SageMaker # Studio Lifecycle Configurations are immutable. # @return [Time] # # @!attribute [rw] studio_lifecycle_config_content # The content of your Amazon SageMaker 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] # # @!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] # # @!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] warm_pool_status # The status of the warm pool associated with the training job. # @return [Types::WarmPoolStatus] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!attribute [rw] profiler_rule_evaluation_statuses # Evaluation status of Amazon SageMaker Debugger rules for profiling # on a training job. # @return [Array] # # @!attribute [rw] profiling_status # Profiling status of a training job. # @return [String] # # @!attribute [rw] environment # The environment variables to set in the Docker container. # @return [Hash] # # @!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] remote_debug_config # Configuration for remote debugging. To learn more about the remote # debugging functionality of SageMaker, see [Access a training # container through Amazon Web Services Systems Manager (SSM) for # remote debugging][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-remote-debugging.html # @return [Types::RemoteDebugConfig] # # @!attribute [rw] infra_check_config # Contains information about the infrastructure health check # configuration for the training job. # @return [Types::InfraCheckConfig] # # @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, :warm_pool_status, :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, :environment, :retry_strategy, :remote_debug_config, :infra_check_config) 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] # # @!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] # # @!attribute [rw] input_artifacts # The input artifacts of the component. # @return [Hash] # # @!attribute [rw] output_artifacts # The output artifacts of the component. # @return [Hash] # # @!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] # # @!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] # # @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 # 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] # # @!attribute [rw] serverless_update_config # Specifies the serverless update concurrency configuration for an # endpoint variant. # @return [Types::ProductionVariantServerlessUpdateConfig] # # @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, :serverless_update_config) 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] # # @!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] # # @!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 # The model deployment settings for the SageMaker Canvas application. # # In order to enable model deployment for Canvas, the SageMaker # Domain's or user profile's Amazon Web Services IAM execution role # must have the `AmazonSageMakerCanvasDirectDeployAccess` policy # attached. You can also turn on model deployment permissions through # the SageMaker Domain's or user profile's settings in the SageMaker # console. # # # # @!attribute [rw] status # Describes whether model deployment permissions are enabled or # disabled in the Canvas application. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DirectDeploySettings AWS API Documentation # class DirectDeploySettings < Struct.new( :status) 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 # A collection of settings that configure the domain's Docker # interaction. # # @!attribute [rw] enable_docker_access # Indicates whether the domain can access Docker. # @return [String] # # @!attribute [rw] vpc_only_trusted_accounts # The list of Amazon Web Services accounts that are trusted when the # domain is created in VPC-only mode. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DockerSettings AWS API Documentation # class DockerSettings < Struct.new( :enable_docker_access, :vpc_only_trusted_accounts) 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] # # @!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] # # @!attribute [rw] docker_settings # A collection of settings that configure the domain's Docker # interaction. # @return [Types::DockerSettings] # # @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, :docker_settings) 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. A single `RStudioServerPro` application is created for a # domain. # @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] # # @!attribute [rw] docker_settings # A collection of settings that configure the domain's Docker # interaction. # @return [Types::DockerSettings] # # @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, :docker_settings) 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 # An object with the recommended values for you to specify when creating # an autoscaling policy. # # @!attribute [rw] min_capacity # The recommended minimum capacity to specify for your autoscaling # policy. # @return [Integer] # # @!attribute [rw] max_capacity # The recommended maximum capacity to specify for your autoscaling # policy. # @return [Integer] # # @!attribute [rw] scale_in_cooldown # The recommended scale in cooldown time for your autoscaling policy. # @return [Integer] # # @!attribute [rw] scale_out_cooldown # The recommended scale out cooldown time for your autoscaling policy. # @return [Integer] # # @!attribute [rw] scaling_policies # An object of the scaling policies for each metric. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DynamicScalingConfiguration AWS API Documentation # class DynamicScalingConfiguration < Struct.new( :min_capacity, :max_capacity, :scale_in_cooldown, :scale_out_cooldown, :scaling_policies) SENSITIVE = [] include Aws::Structure end # A file system, created by you in Amazon EFS, that you assign to a user # profile or space for an Amazon SageMaker Domain. Permitted users can # access this file system in Amazon SageMaker Studio. # # @!attribute [rw] file_system_id # The ID of your Amazon EFS file system. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EFSFileSystem AWS API Documentation # class EFSFileSystem < Struct.new( :file_system_id) SENSITIVE = [] include Aws::Structure end # The settings for assigning a custom Amazon EFS file system to a user # profile or space for an Amazon SageMaker Domain. # # @!attribute [rw] file_system_id # The ID of your Amazon EFS file system. # @return [String] # # @!attribute [rw] file_system_path # The path to the file system directory that is accessible in Amazon # SageMaker Studio. Permitted users can access only this directory and # below. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EFSFileSystemConfig AWS API Documentation # class EFSFileSystemConfig < Struct.new( :file_system_id, :file_system_path) 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 collection of EBS storage settings that applies to private spaces. # # @!attribute [rw] ebs_volume_size_in_gb # The size of an EBS storage volume for a private space. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EbsStorageSettings AWS API Documentation # class EbsStorageSettings < Struct.new( :ebs_volume_size_in_gb) 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. # # Amazon Web Services IoT Greengrass uses semantic versions for # components. Semantic versions follow a major.minor.patch # 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]. # # # # * `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] # # @!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] # # @!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] # # @!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] # # @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 Amazon 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] # # @!attribute [rw] exclude_features_attribute # The attributes of the input data to exclude from the analysis. # @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, :exclude_features_attribute) 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] serverless_config # Specifies the serverless configuration for an endpoint variant. # @return [Types::ProductionVariantServerlessConfig] # # @!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, :serverless_config, :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] # # @!attribute [rw] serverless_config # Specifies the serverless configuration for an endpoint variant. # @return [Types::ProductionVariantServerlessConfig] # # @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, :serverless_config) 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] # # @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] # # @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] # # @!attribute [rw] collection_type # A grouping of elements where each element within the collection must # have the same feature type (`String`, `Integral`, or `Fractional`). # # * `List`: An ordered collection of elements. # # * `Set`: An unordered collection of unique elements. # # * `Vector`: A specialized list that represents a fixed-size array of # elements. The vector dimension is determined by you. Must have # elements with fractional feature types. # @return [String] # # @!attribute [rw] collection_config # Configuration for your collection. # @return [Types::CollectionConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FeatureDefinition AWS API Documentation # class FeatureDefinition < Struct.new( :feature_name, :feature_type, :collection_type, :collection_config) 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] # # @!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] # # @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] # # @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 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."`, where `` 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."`. 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.`. # # # # [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 # The generative AI settings for the SageMaker Canvas application. # # Configure these settings for Canvas users starting chats with # generative AI foundation models. For more information, see [ Use # generative AI with foundation models][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/canvas-fm-chat.html # # @!attribute [rw] amazon_bedrock_role_arn # The ARN of an Amazon Web Services IAM role that allows fine-tuning # of large language models (LLMs) in Amazon Bedrock. The IAM role # should have Amazon S3 read and write permissions, as well as a trust # relationship that establishes `bedrock.amazonaws.com` as a service # principal. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GenerativeAiSettings AWS API Documentation # class GenerativeAiSettings < Struct.new( :amazon_bedrock_role_arn) 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] # # @!attribute [rw] model_stats # Status of model on device. # @return [Array] # # @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] inference_recommendations_job_name # The name of a previously completed Inference Recommender job. # @return [String] # # @!attribute [rw] recommendation_id # The recommendation ID of a previously completed inference # recommendation. This ID should come from one of the recommendations # returned by the job specified in the # `InferenceRecommendationsJobName` field. # # Specify either this field or the `EndpointName` field. # @return [String] # # @!attribute [rw] endpoint_name # The name of an endpoint benchmarked during a previously completed # inference recommendation job. This name should come from one of the # recommendations returned by the job specified in the # `InferenceRecommendationsJobName` field. # # Specify either this field or the `RecommendationId` field. # @return [String] # # @!attribute [rw] target_cpu_utilization_per_core # The percentage of how much utilization you want an instance to use # before autoscaling. The default value is 50%. # @return [Integer] # # @!attribute [rw] scaling_policy_objective # An object where you specify the anticipated traffic pattern for an # endpoint. # @return [Types::ScalingPolicyObjective] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetScalingConfigurationRecommendationRequest AWS API Documentation # class GetScalingConfigurationRecommendationRequest < Struct.new( :inference_recommendations_job_name, :recommendation_id, :endpoint_name, :target_cpu_utilization_per_core, :scaling_policy_objective) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] inference_recommendations_job_name # The name of a previously completed Inference Recommender job. # @return [String] # # @!attribute [rw] recommendation_id # The recommendation ID of a previously completed inference # recommendation. # @return [String] # # @!attribute [rw] endpoint_name # The name of an endpoint benchmarked during a previously completed # Inference Recommender job. # @return [String] # # @!attribute [rw] target_cpu_utilization_per_core # The percentage of how much utilization you want an instance to use # before autoscaling, which you specified in the request. The default # value is 50%. # @return [Integer] # # @!attribute [rw] scaling_policy_objective # An object representing the anticipated traffic pattern for an # endpoint that you specified in the request. # @return [Types::ScalingPolicyObjective] # # @!attribute [rw] metric # An object with a list of metrics that were benchmarked during the # previously completed Inference Recommender job. # @return [Types::ScalingPolicyMetric] # # @!attribute [rw] dynamic_scaling_configuration # An object with the recommended values for you to specify when # creating an autoscaling policy. # @return [Types::DynamicScalingConfiguration] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/GetScalingConfigurationRecommendationResponse AWS API Documentation # class GetScalingConfigurationRecommendationResponse < Struct.new( :inference_recommendations_job_name, :recommendation_id, :endpoint_name, :target_cpu_utilization_per_core, :scaling_policy_objective, :metric, :dynamic_scaling_configuration) 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] # # @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 # Stores the holiday featurization attributes applicable to each item of # time-series datasets during the training of a forecasting model. This # allows the model to identify patterns associated with specific # holidays. # # @!attribute [rw] country_code # The country code for the holiday calendar. # # For the list of public holiday calendars supported by AutoML job V2, # see [Country Codes][1]. Use the country code corresponding to the # country of your choice. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-timeseries-forecasting-holiday-calendars.html#holiday-country-codes # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HolidayConfigAttributes AWS API Documentation # class HolidayConfigAttributes < Struct.new( :country_code) 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] # # @!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] # # @!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] # # @!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] # # @!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] # # @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. If you want to # define a custom objective metric, see [Define metrics and # environment variables][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics-variables.html # @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. # # 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. # # # @return [Types::ParameterRanges] # # @!attribute [rw] static_hyper_parameters # Specifies the values of hyperparameters that do not change for the # tuning job. # @return [Hash] # # @!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] # # @!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. # # If you want to use hyperparameter optimization with instance type # flexibility, use `HyperParameterTuningResourceConfig` instead. # # # @return [Types::ResourceConfig] # # @!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] 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] 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. # # 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. # # # # # # [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] # # @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, :hyper_parameter_tuning_resource_config, :stopping_condition, :enable_network_isolation, :enable_inter_container_traffic_encryption, :enable_managed_spot_training, :checkpoint_config, :retry_strategy, :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] # # @!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 [Step 2: Launch a SageMaker Distributed Training Job # Using the SageMaker Python SDK][1] for more information. # # # # [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 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. If you want to define # a custom objective metric, see [Define metrics and environment # variables][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics-variables.html # # @!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] # # @!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. # # 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. # # # @return [Types::HyperParameterTuningJobWarmStartConfig] # # @!attribute [rw] failure_reason # The error that was created when a hyperparameter tuning job failed. # @return [String] # # @!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] # # @!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] # # @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, :tuning_job_completion_details, :consumed_resources, :tags) 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. # # 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. # # # # @!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] # # @!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. # # `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. # # # # @!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/sagemaker/latest/dg/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]. # # SageMaker supports only the [General Purpose SSD (gp2)][2] storage # volume type. # # # # # # [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. # # 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`. # # # @return [Array] # # @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, `HyperbandTraining` 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 # [distributed][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 # The Amazon SageMaker Canvas application setting where you configure # OAuth for connecting to an external data source, such as Snowflake. # # @!attribute [rw] data_source_name # The name of the data source that you're connecting to. Canvas # currently supports OAuth for Snowflake and Salesforce Data Cloud. # @return [String] # # @!attribute [rw] status # Describes whether OAuth for a data source is enabled or disabled in # the Canvas application. # @return [String] # # @!attribute [rw] secret_arn # The ARN of an Amazon Web Services Secrets Manager secret that stores # the credentials from your identity provider, such as the client ID # and secret, authorization URL, and token URL. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/IdentityProviderOAuthSetting AWS API Documentation # class IdentityProviderOAuthSetting < Struct.new( :data_source_name, :status, :secret_arn) 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 # The collection of settings used by an AutoML job V2 for the image # classification problem type. # # @!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] # # @!attribute [rw] tags # Any tags associated with the hub content. # @return [Array] # # @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 # Defines the compute resources to allocate to run a model that you # assign to an inference component. These resources include CPU cores, # accelerators, and memory. # # @!attribute [rw] number_of_cpu_cores_required # The number of CPU cores to allocate to run a model that you assign # to an inference component. # @return [Float] # # @!attribute [rw] number_of_accelerator_devices_required # The number of accelerators to allocate to run a model that you # assign to an inference component. Accelerators include GPUs and # Amazon Web Services Inferentia. # @return [Float] # # @!attribute [rw] min_memory_required_in_mb # The minimum MB of memory to allocate to run a model that you assign # to an inference component. # @return [Integer] # # @!attribute [rw] max_memory_required_in_mb # The maximum MB of memory to allocate to run a model that you assign # to an inference component. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentComputeResourceRequirements AWS API Documentation # class InferenceComponentComputeResourceRequirements < Struct.new( :number_of_cpu_cores_required, :number_of_accelerator_devices_required, :min_memory_required_in_mb, :max_memory_required_in_mb) SENSITIVE = [] include Aws::Structure end # Defines a container that provides the runtime environment for a model # that you deploy with an inference component. # # @!attribute [rw] image # The Amazon Elastic Container Registry (Amazon ECR) path where the # Docker image for the model is stored. # @return [String] # # @!attribute [rw] artifact_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). # @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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentContainerSpecification AWS API Documentation # class InferenceComponentContainerSpecification < Struct.new( :image, :artifact_url, :environment) SENSITIVE = [] include Aws::Structure end # Details about the resources that are deployed with this inference # component. # # @!attribute [rw] deployed_image # 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 # @return [Types::DeployedImage] # # @!attribute [rw] artifact_url # The Amazon S3 path where the model artifacts are stored. # @return [String] # # @!attribute [rw] environment # The environment variables to set in the Docker container. # @return [Hash] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentContainerSpecificationSummary AWS API Documentation # class InferenceComponentContainerSpecificationSummary < Struct.new( :deployed_image, :artifact_url, :environment) SENSITIVE = [] include Aws::Structure end # Runtime settings for a model that is deployed with an inference # component. # # @!attribute [rw] copy_count # The number of runtime copies of the model container to deploy with # the inference component. Each copy can serve inference requests. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentRuntimeConfig AWS API Documentation # class InferenceComponentRuntimeConfig < Struct.new( :copy_count) SENSITIVE = [] include Aws::Structure end # Details about the runtime settings for the model that is deployed with # the inference component. # # @!attribute [rw] desired_copy_count # The number of runtime copies of the model container that you # requested to deploy with the inference component. # @return [Integer] # # @!attribute [rw] current_copy_count # The number of runtime copies of the model container that are # currently deployed. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentRuntimeConfigSummary AWS API Documentation # class InferenceComponentRuntimeConfigSummary < Struct.new( :desired_copy_count, :current_copy_count) SENSITIVE = [] include Aws::Structure end # Details about the resources to deploy with this inference component, # including the model, container, and compute resources. # # @!attribute [rw] model_name # The name of an existing SageMaker model object in your account that # you want to deploy with the inference component. # @return [String] # # @!attribute [rw] container # Defines a container that provides the runtime environment for a # model that you deploy with an inference component. # @return [Types::InferenceComponentContainerSpecification] # # @!attribute [rw] startup_parameters # Settings that take effect while the model container starts up. # @return [Types::InferenceComponentStartupParameters] # # @!attribute [rw] compute_resource_requirements # The compute resources allocated to run the model assigned to the # inference component. # @return [Types::InferenceComponentComputeResourceRequirements] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentSpecification AWS API Documentation # class InferenceComponentSpecification < Struct.new( :model_name, :container, :startup_parameters, :compute_resource_requirements) SENSITIVE = [] include Aws::Structure end # Details about the resources that are deployed with this inference # component. # # @!attribute [rw] model_name # The name of the SageMaker model object that is deployed with the # inference component. # @return [String] # # @!attribute [rw] container # Details about the container that provides the runtime environment # for the model that is deployed with the inference component. # @return [Types::InferenceComponentContainerSpecificationSummary] # # @!attribute [rw] startup_parameters # Settings that take effect while the model container starts up. # @return [Types::InferenceComponentStartupParameters] # # @!attribute [rw] compute_resource_requirements # The compute resources allocated to run the model assigned to the # inference component. # @return [Types::InferenceComponentComputeResourceRequirements] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentSpecificationSummary AWS API Documentation # class InferenceComponentSpecificationSummary < Struct.new( :model_name, :container, :startup_parameters, :compute_resource_requirements) SENSITIVE = [] include Aws::Structure end # Settings that take effect while the model container starts up. # # @!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 inference component. # @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 Amazon S3 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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentStartupParameters AWS API Documentation # class InferenceComponentStartupParameters < Struct.new( :model_data_download_timeout_in_seconds, :container_startup_health_check_timeout_in_seconds) SENSITIVE = [] include Aws::Structure end # A summary of the properties of an inference component. # # @!attribute [rw] creation_time # The time when the inference component was created. # @return [Time] # # @!attribute [rw] inference_component_arn # The Amazon Resource Name (ARN) of the inference component. # @return [String] # # @!attribute [rw] inference_component_name # The name of the inference component. # @return [String] # # @!attribute [rw] endpoint_arn # The Amazon Resource Name (ARN) of the endpoint that hosts the # inference component. # @return [String] # # @!attribute [rw] endpoint_name # The name of the endpoint that hosts the inference component. # @return [String] # # @!attribute [rw] variant_name # The name of the production variant that hosts the inference # component. # @return [String] # # @!attribute [rw] inference_component_status # The status of the inference component. # @return [String] # # @!attribute [rw] last_modified_time # The time when the inference component was last updated. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceComponentSummary AWS API Documentation # class InferenceComponentSummary < Struct.new( :creation_time, :inference_component_arn, :inference_component_name, :endpoint_arn, :endpoint_name, :variant_name, :inference_component_status, :last_modified_time) 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 Amazon 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] recommendation_id # The recommendation ID which uniquely identifies each recommendation. # @return [String] # # @!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] invocation_end_time # A timestamp that shows when the benchmark completed. # @return [Time] # # @!attribute [rw] invocation_start_time # A timestamp that shows when the benchmark started. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InferenceRecommendation AWS API Documentation # class InferenceRecommendation < Struct.new( :recommendation_id, :metrics, :endpoint_configuration, :model_configuration, :invocation_end_time, :invocation_start_time) 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] # # @!attribute [rw] model_name # The name of the created model. # @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). # @return [String] # # @!attribute [rw] model_package_version_arn # The Amazon Resource Name (ARN) of a versioned model package. # @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, :model_name, :sample_payload_url, :model_package_version_arn) 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] # # @!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] # # @!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] # # @!attribute [rw] supported_content_types # The supported MIME types for the input data. # @return [Array] # # @!attribute [rw] supported_response_mime_types # The supported MIME types for the output data. # @return [Array] # # @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 # Configuration information for the infrastructure health check of a # training job. A SageMaker-provided health check tests the health of # instance hardware and cluster network connectivity. # # @!attribute [rw] enable_infra_check # Enables an infrastructure health check. # @return [Boolean] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/InfraCheckConfig AWS API Documentation # class InfraCheckConfig < Struct.new( :enable_infra_check) 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 configuration for the file system and kernels in a SageMaker image # running as a JupyterLab app. The `FileSystemConfig` object is not # supported. # # @!attribute [rw] file_system_config # The Amazon Elastic File System storage configuration for a SageMaker # image. # @return [Types::FileSystemConfig] # # @!attribute [rw] container_config # The configuration used to run the application image container. # @return [Types::ContainerConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/JupyterLabAppImageConfig AWS API Documentation # class JupyterLabAppImageConfig < Struct.new( :file_system_config, :container_config) SENSITIVE = [] include Aws::Structure end # The settings for the JupyterLab application. # # @!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 # JupyterLab app. # @return [Array] # # @!attribute [rw] lifecycle_config_arns # The Amazon Resource Name (ARN) of the lifecycle configurations # attached to the user profile or domain. To remove a lifecycle # config, you must set `LifecycleConfigArns` to an empty list. # @return [Array] # # @!attribute [rw] code_repositories # A list of Git repositories that SageMaker automatically displays to # users for cloning in the JupyterLab application. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/JupyterLabAppSettings AWS API Documentation # class JupyterLabAppSettings < Struct.new( :default_resource_spec, :custom_images, :lifecycle_config_arns, :code_repositories) 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. # # To remove a Lifecycle Config, you must set `LifecycleConfigArns` to # an empty list. # # # @return [Array] # # @!attribute [rw] code_repositories # A list of Git repositories that SageMaker automatically displays to # users for cloning in the JupyterServer application. # @return [Array] # # @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 Amazon SageMaker Canvas application setting where you configure # document querying. # # @!attribute [rw] status # Describes whether the document querying feature is enabled or # disabled in the Canvas application. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/KendraSettings AWS API Documentation # class KendraSettings < Struct.new( :status) 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. # # 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 CLI or CloudFormation and the instance # type parameter value is not passed. # # # @return [Types::ResourceSpec] # # @!attribute [rw] custom_images # A list of custom SageMaker images that are configured to run as a # KernelGateway app. # @return [Array] # # @!attribute [rw] lifecycle_config_arns # The Amazon Resource Name (ARN) of the Lifecycle Configurations # attached to the the user profile or domain. # # To remove a Lifecycle Config, you must set `LifecycleConfigArns` to # an empty list. # # # @return [Array] # # @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] # # @!attribute [rw] file_system_config # The Amazon Elastic File System 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] # # @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 an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.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. # # Labeling jobs fail after 30 days with an appropriate client error # message. # # # # @!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] # # @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] # # @!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] # # @!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] # # @!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 total number of items to return in the response. If the total # number of items available is more than the value specified, a # `NextToken` is provided in the response. To resume pagination, # provide the `NextToken` value in the as part of a subsequent call. # 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] # # @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 # The total number of items to return in the response. If the total # number of items available is more than the value specified, a # `NextToken` is provided in the response. To resume pagination, # provide the `NextToken` value in the as part of a subsequent call. # The default value is 10. # @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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] cluster_name # The string name or the Amazon Resource Name (ARN) of the SageMaker # HyperPod cluster in which you want to retrieve the list of nodes. # @return [String] # # @!attribute [rw] creation_time_after # A filter that returns nodes in a SageMaker HyperPod cluster created # after the specified time. Timestamps are formatted according to the # ISO 8601 standard. # # Acceptable formats include: # # * `YYYY-MM-DDThh:mm:ss.sssTZD` (UTC), for example, # `2014-10-01T20:30:00.000Z` # # * `YYYY-MM-DDThh:mm:ss.sssTZD` (with offset), for example, # `2014-10-01T12:30:00.000-08:00` # # * `YYYY-MM-DD`, for example, `2014-10-01` # # * Unix time in seconds, for example, `1412195400`. This is also # referred to as Unix Epoch time and represents the number of # seconds since midnight, January 1, 1970 UTC. # # For more information about the timestamp format, see [Timestamp][1] # in the *Amazon Web Services Command Line Interface User Guide*. # # # # [1]: https://docs.aws.amazon.com/cli/latest/userguide/cli-usage-parameters-types.html#parameter-type-timestamp # @return [Time] # # @!attribute [rw] creation_time_before # A filter that returns nodes in a SageMaker HyperPod cluster created # before the specified time. The acceptable formats are the same as # the timestamp formats for `CreationTimeAfter`. For more information # about the timestamp format, see [Timestamp][1] in the *Amazon Web # Services Command Line Interface User Guide*. # # # # [1]: https://docs.aws.amazon.com/cli/latest/userguide/cli-usage-parameters-types.html#parameter-type-timestamp # @return [Time] # # @!attribute [rw] instance_group_name_contains # A filter that returns the instance groups whose name contain a # specified string. # @return [String] # # @!attribute [rw] max_results # The maximum number of nodes to return in the response. # @return [Integer] # # @!attribute [rw] next_token # If the result of the previous `ListClusterNodes` request was # truncated, the response includes a `NextToken`. To retrieve the next # set of cluster nodes, use the token in the next request. # @return [String] # # @!attribute [rw] sort_by # The field by which to sort results. The default value is # `CREATION_TIME`. # @return [String] # # @!attribute [rw] sort_order # The sort order for results. The default value is `Ascending`. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListClusterNodesRequest AWS API Documentation # class ListClusterNodesRequest < Struct.new( :cluster_name, :creation_time_after, :creation_time_before, :instance_group_name_contains, :max_results, :next_token, :sort_by, :sort_order) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] next_token # The next token specified for listing instances in a SageMaker # HyperPod cluster. # @return [String] # # @!attribute [rw] cluster_node_summaries # The summaries of listed instances in a SageMaker HyperPod cluster # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListClusterNodesResponse AWS API Documentation # class ListClusterNodesResponse < Struct.new( :next_token, :cluster_node_summaries) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] creation_time_after # Set a start time for the time range during which you want to list # SageMaker HyperPod clusters. Timestamps are formatted according to # the ISO 8601 standard. # # Acceptable formats include: # # * `YYYY-MM-DDThh:mm:ss.sssTZD` (UTC), for example, # `2014-10-01T20:30:00.000Z` # # * `YYYY-MM-DDThh:mm:ss.sssTZD` (with offset), for example, # `2014-10-01T12:30:00.000-08:00` # # * `YYYY-MM-DD`, for example, `2014-10-01` # # * Unix time in seconds, for example, `1412195400`. This is also # referred to as Unix Epoch time and represents the number of # seconds since midnight, January 1, 1970 UTC. # # For more information about the timestamp format, see [Timestamp][1] # in the *Amazon Web Services Command Line Interface User Guide*. # # # # [1]: https://docs.aws.amazon.com/cli/latest/userguide/cli-usage-parameters-types.html#parameter-type-timestamp # @return [Time] # # @!attribute [rw] creation_time_before # Set an end time for the time range during which you want to list # SageMaker HyperPod clusters. A filter that returns nodes in a # SageMaker HyperPod cluster created before the specified time. The # acceptable formats are the same as the timestamp formats for # `CreationTimeAfter`. For more information about the timestamp # format, see [Timestamp][1] in the *Amazon Web Services Command Line # Interface User Guide*. # # # # [1]: https://docs.aws.amazon.com/cli/latest/userguide/cli-usage-parameters-types.html#parameter-type-timestamp # @return [Time] # # @!attribute [rw] max_results # Set the maximum number of SageMaker HyperPod clusters to list. # @return [Integer] # # @!attribute [rw] name_contains # Set the maximum number of instances to print in the list. # @return [String] # # @!attribute [rw] next_token # Set the next token to retrieve the list of SageMaker HyperPod # clusters. # @return [String] # # @!attribute [rw] sort_by # The field by which to sort results. The default value is # `CREATION_TIME`. # @return [String] # # @!attribute [rw] sort_order # The sort order for results. The default value is `Ascending`. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListClustersRequest AWS API Documentation # class ListClustersRequest < 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] next_token # If the result of the previous `ListClusters` request was truncated, # the response includes a `NextToken`. To retrieve the next set of # clusters, use the token in the next request. # @return [String] # # @!attribute [rw] cluster_summaries # The summaries of listed SageMaker HyperPod clusters. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListClustersResponse AWS API Documentation # class ListClustersResponse < Struct.new( :next_token, :cluster_summaries) 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] # # @!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] # # @!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] # # @!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 # Whether to sort the results in `Ascending` or `Descending` order. # 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] # # @!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] # # @!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] # # @!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 # The total number of items to return in the response. If the total # number of items available is more than the value specified, a # `NextToken` is provided in the response. To resume pagination, # provide the `NextToken` value in the as part of a subsequent call. # The default value is 10. # @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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] sort_by # The field by which to sort the inference components in the response. # 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 # A token that you use to get the next set of results following a # truncated response. If the response to the previous request was # truncated, that response provides the value for this token. # @return [String] # # @!attribute [rw] max_results # The maximum number of inference components to return in the # response. This value defaults to 10. # @return [Integer] # # @!attribute [rw] name_contains # Filters the results to only those inference components with a name # that contains the specified string. # @return [String] # # @!attribute [rw] creation_time_before # Filters the results to only those inference components that were # created before the specified time. # @return [Time] # # @!attribute [rw] creation_time_after # Filters the results to only those inference components that were # created after the specified time. # @return [Time] # # @!attribute [rw] last_modified_time_before # Filters the results to only those inference components that were # updated before the specified time. # @return [Time] # # @!attribute [rw] last_modified_time_after # Filters the results to only those inference components that were # updated after the specified time. # @return [Time] # # @!attribute [rw] status_equals # Filters the results to only those inference components with the # specified status. # @return [String] # # @!attribute [rw] endpoint_name_equals # An endpoint name to filter the listed inference components. The # response includes only those inference components that are hosted at # the specified endpoint. # @return [String] # # @!attribute [rw] variant_name_equals # A production variant name to filter the listed inference components. # The response includes only those inference components that are # hosted at the specified variant. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListInferenceComponentsInput AWS API Documentation # class ListInferenceComponentsInput < 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, :endpoint_name_equals, :variant_name_equals) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] inference_components # A list of inference components and their properties that matches any # of the filters you specified in the request. # @return [Array] # # @!attribute [rw] next_token # The token to use in a subsequent request to get the next set of # results following a truncated response. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListInferenceComponentsOutput AWS API Documentation # class ListInferenceComponentsOutput < Struct.new( :inference_components, :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] # # @!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] # # @!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] # # @!attribute [rw] model_name_equals # A filter that returns only jobs that were created for this model. # @return [String] # # @!attribute [rw] model_package_version_arn_equals # A filter that returns only jobs that were created for this versioned # model package. # @return [String] # # @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, :model_name_equals, :model_package_version_arn_equals) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] inference_recommendations_jobs # The recommendations created from the Amazon SageMaker Inference # Recommender job. # @return [Array] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @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] # # @!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 # or Amazon Resource Name (ARN). # @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] # # @!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] # # @!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] # # @!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] # # @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] # # @!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] # # @!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] # # @!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 # Whether to sort the results in `Ascending` or `Descending` order. # 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] # # @!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] # # @!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] # # @!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] # # @!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 the results by the `Status`, `CreationTime`, or # `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] # # @!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] # # @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 the results by the `Status`, `CreationTime`, or # `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] # # @!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] # # @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] # # @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. # # 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. # # # @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] # # @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] # # @!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 or Amazon Resource Name (ARN) 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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] name_contains # A string that partially matches one or more `ResourceCatalog`s # names. Filters `ResourceCatalog` by name. # @return [String] # # @!attribute [rw] creation_time_after # Use this parameter to search for `ResourceCatalog`s created after a # specific date and time. # @return [Time] # # @!attribute [rw] creation_time_before # Use this parameter to search for `ResourceCatalog`s created before a # specific date and time. # @return [Time] # # @!attribute [rw] sort_order # The order in which the resource catalogs are listed. # @return [String] # # @!attribute [rw] sort_by # The value on which the resource catalog list is sorted. # @return [String] # # @!attribute [rw] max_results # The maximum number of results returned by `ListResourceCatalogs`. # @return [Integer] # # @!attribute [rw] next_token # A token to resume pagination of `ListResourceCatalogs` results. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListResourceCatalogsRequest AWS API Documentation # class ListResourceCatalogsRequest < Struct.new( :name_contains, :creation_time_after, :creation_time_before, :sort_order, :sort_by, :max_results, :next_token) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] resource_catalogs # A list of the requested `ResourceCatalog`s. # @return [Array] # # @!attribute [rw] next_token # A token to resume pagination of `ListResourceCatalogs` results. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListResourceCatalogsResponse AWS API Documentation # class ListResourceCatalogsResponse < Struct.new( :resource_catalogs, :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 # The total number of items to return in the response. If the total # number of items available is more than the value specified, a # `NextToken` is provided in the response. To resume pagination, # provide the `NextToken` value in the as part of a subsequent call. # The default value is 10. # @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] # # @!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] # # @!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 total number of items to return in the response. If the total # number of items available is more than the value specified, a # `NextToken` is provided in the response. To resume pagination, # provide the `NextToken` value in the as part of a subsequent call. # 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 # 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] studio_lifecycle_configs # A list of Lifecycle Configurations and their properties. # @return [Array] # # @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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!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 # The total number of items to return in the response. If the total # number of items available is more than the value specified, a # `NextToken` is provided in the response. To resume pagination, # provide the `NextToken` value in the as part of a subsequent call. # The default value is 10. # @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] # # @!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] # # @!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] # # @!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. # # For definitions of the standard metrics, see [ `Autopilot candidate # metrics` ][1]. # # # # # # [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 # An object containing information about a metric. # # @note MetricSpecification is a union - when returned from an API call exactly one value will be set and the returned type will be a subclass of MetricSpecification corresponding to the set member. # # @!attribute [rw] predefined # Information about a predefined metric. # @return [Types::PredefinedMetricSpecification] # # @!attribute [rw] customized # Information about a customized metric. # @return [Types::CustomizedMetricSpecification] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MetricSpecification AWS API Documentation # class MetricSpecification < Struct.new( :predefined, :customized, :unknown) SENSITIVE = [] include Aws::Structure include Aws::Structure::Union class Predefined < MetricSpecification; end class Customized < MetricSpecification; end class Unknown < MetricSpecification; end 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] # # @!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 an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.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] # # @!attribute [rw] deployment_recommendation # A set of recommended deployment configurations for the model. # @return [Types::DeploymentRecommendation] # # @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, :deployment_recommendation) SENSITIVE = [] include Aws::Structure end # The access configuration file to control access to the ML model. You # can explicitly accept the model end-user license agreement (EULA) # within the `ModelAccessConfig`. # # * If you are a Jumpstart user, see the [End-user license # agreements][1] section for more details on accepting the EULA. # # * If you are an AutoML user, see the *Optional Parameters* section of # *Create an AutoML job to fine-tune text generation models using the # API* for details on [How to set the EULA acceptance when fine-tuning # a model using the AutoML API][2]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/jumpstart-foundation-models-choose.html#jumpstart-foundation-models-choose-eula # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-create-experiment-finetune-llms.html#autopilot-llms-finetuning-api-optional-params # # @!attribute [rw] accept_eula # Specifies agreement to the model end-user license agreement (EULA). # The `AcceptEula` value must be explicitly defined as `True` in order # to accept the EULA that this model requires. You are responsible for # reviewing and complying with any applicable license terms and making # sure they are acceptable for your use case before downloading or # using a model. # @return [Boolean] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelAccessConfig AWS API Documentation # class ModelAccessConfig < Struct.new( :accept_eula) SENSITIVE = [] include Aws::Structure end # Provides information about the location that is configured for storing # model artifacts. # # Model artifacts are outputs that result from training a model. They # typically consist of trained parameters, a model definition that # describes how to compute inferences, and other metadata. A SageMaker # container stores your trained model artifacts in the `/opt/ml/model` # directory. After training has completed, by default, these artifacts # are uploaded to your Amazon S3 bucket as compressed files. # # @!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] # # @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] # # @!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] # # @!attribute [rw] model_package_group_name # The model package group that contains the model package. Only # relevant for model cards created for model packages in the Amazon # SageMaker Model Registry. # @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, :model_package_group_name) 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] # # @!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] # # @!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] # # @!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] # # @!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] # # @!attribute [rw] last_monitoring_execution_summary # Summary of information about the last monitoring job to run. # @return [Types::MonitoringExecutionSummary] # # @!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/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, :batch_transform_input) 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 the location of ML model data to deploy. If specified, you # must specify one and only one of the available data sources. # # @!attribute [rw] s3_data_source # Specifies the S3 location of ML model data to deploy. # @return [Types::S3ModelDataSource] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDataSource AWS API Documentation # class ModelDataSource < Struct.new( :s3_data_source) 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`. # # If you set `AutoGenerateEndpointName` to `True`, do not specify the # `EndpointName`; otherwise a 400 error is thrown. # # # @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. # # Specify the `EndpointName` if and only if you set # `AutoGenerateEndpointName` to `False`; otherwise a 400 error is # thrown. # # # @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. # # If model deployment fails, this field is omitted from the response. # # # @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 Amazon 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] # # @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. Acceptable values are `P95` # and `P99`. For custom load tests, specify the value as `P95`. # @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] # # @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 bias 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] # # @!attribute [rw] source_uri # The URI of the source for the model package. # @return [String] # # @!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] # # @!attribute [rw] customer_metadata_properties # The metadata properties for the model package. # @return [Hash] # # @!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] # # @!attribute [rw] skip_model_validation # Indicates if you want to skip model validation. # @return [String] # # @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, :source_uri, :tags, :customer_metadata_properties, :drift_check_baselines, :skip_model_validation) 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). # # The model artifacts must be in an S3 bucket that is in the same # region as the model package. # # # @return [String] # # @!attribute [rw] model_data_source # Specifies the location of ML model data to deploy during endpoint # creation. # @return [Types::ModelDataSource] # # @!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] # # @!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] # # @!attribute [rw] additional_s3_data_source # The additional data source that is used during inference in the # Docker container for your model package. # @return [Types::AdditionalS3DataSource] # # @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, :model_data_source, :product_id, :environment, :model_input, :framework, :framework_version, :nearest_model_name, :additional_s3_data_source) 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] # # @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] # # @!attribute [rw] image_scan_statuses # The status of the scan of the Docker image container for the model # package. # @return [Array] # # @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] # # @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] # # @!attribute [rw] container_arguments # An array of arguments for the container used to run the monitoring # job. # @return [Array] # # @!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 # flattened 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] # # @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 endpoints # 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 Amazon Web Services account than the # Amazon Web Services 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] # # @!attribute [rw] container_arguments # An array of arguments for the container used to run the monitoring # job. # @return [Array] # # @!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 # flattened 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 Key Management Service (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] # # @!attribute [rw] monitoring_output_config # The array of outputs from the monitoring job to be uploaded to # 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] # # @!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 an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.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] # # @!attribute [rw] kms_key_id # The Key Management Service (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] # # @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. # # 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. # # # @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] # # @!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] # # @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] # # @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 an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.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 Amazon 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] # # @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] # # @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] # # @!attribute [rw] ttl_duration # Time to live duration, where the record is hard deleted after the # expiration time is reached; `ExpiresAt` = `EventTime` + # `TtlDuration`. For information on HardDelete, see the # [DeleteRecord][1] API in the Amazon SageMaker API Reference guide. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_feature_store_DeleteRecord.html # @return [Types::TtlDuration] # # @!attribute [rw] storage_type # Option for different tiers of low latency storage for real-time data # retrieval. # # * `Standard`: A managed low latency data store for feature groups. # # * `InMemory`: A managed data store for feature groups that supports # very low latency retrieval. # @return [String] # # @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, :ttl_duration, :storage_type) SENSITIVE = [] include Aws::Structure end # Updates the feature group online store configuration. # # @!attribute [rw] ttl_duration # Time to live duration, where the record is hard deleted after the # expiration time is reached; `ExpiresAt` = `EventTime` + # `TtlDuration`. For information on HardDelete, see the # [DeleteRecord][1] API in the Amazon SageMaker API Reference guide. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_feature_store_DeleteRecord.html # @return [Types::TtlDuration] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OnlineStoreConfigUpdate AWS API Documentation # class OnlineStoreConfigUpdate < Struct.new( :ttl_duration) 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`. # # Currently `ml_trn1` is available only in US East (N. Virginia) # Region, and `ml_inf2` is available only in US East (Ohio) Region. # # # # # # [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 Reference Guide][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://awsdocs-neuron.readthedocs-hosted.com/en/latest/compiler/neuronx-cc/api-reference-guide/neuron-compiler-cli-reference-guide.html # [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. For more information, see # [KMS-Managed Encryption Keys][1] in the *Amazon Simple Storage # Service Developer Guide*. If the output data is stored in Amazon S3 # Express One Zone, it is encrypted with server-side encryption with # Amazon S3 managed keys (SSE-S3). KMS key is not supported for Amazon # S3 Express One Zone # # 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] # # @!attribute [rw] compression_type # The model output compression type. Select `None` to output an # uncompressed model, recommended for large model outputs. Defaults to # gzip. # @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, :compression_type) 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 # The collection of ownership settings for a space. # # @!attribute [rw] owner_user_profile_name # The user profile who is the owner of the private space. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OwnershipSettings AWS API Documentation # class OwnershipSettings < Struct.new( :owner_user_profile_name) SENSITIVE = [] include Aws::Structure end # Specifies summary information about the ownership settings. # # @!attribute [rw] owner_user_profile_name # The user profile who is the owner of the private space. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OwnershipSettingsSummary AWS API Documentation # class OwnershipSettingsSummary < Struct.new( :owner_user_profile_name) 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. # # 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. # # # # @!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] # # @!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] # # @!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] # # @!attribute [rw] auto_parameters # A list containing hyperparameter names and example values to be used # by Autotune to determine optimal ranges for your tuning job. # @return [Array] # # @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, :auto_parameters) 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] # # @!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] # # @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] # # @!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] # # @!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] # # @!attribute [rw] managed_instance_scaling # Settings that control the range in the number of instances that the # endpoint provisions as it scales up or down to accommodate traffic. # @return [Types::ProductionVariantManagedInstanceScaling] # # @!attribute [rw] routing_config # Settings that control how the endpoint routes incoming traffic to # the instances that the endpoint hosts. # @return [Types::ProductionVariantRoutingConfig] # # @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, :managed_instance_scaling, :routing_config) SENSITIVE = [] include Aws::Structure end # Defines the traffic pattern. # # @!attribute [rw] initial_number_of_users # Specifies how many concurrent users to start with. The value should # be between 1 and 3. # @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 a traffic phase should be. For custom load tests, # the value should be between 120 and 3600. This value should not # exceed `JobDurationInSeconds`. # @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] # # @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] selective_execution_config # The selective execution configuration applied to the pipeline run. # @return [Types::SelectiveExecutionConfig] # # @!attribute [rw] pipeline_parameters # Contains a list of pipeline parameters. This list can be empty. # @return [Array] # # @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, :selective_execution_config, :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] 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] # # @!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] selective_execution_result # The ARN from an execution of the current pipeline from which results # are reused for this step. # @return [Types::SelectiveExecutionResult] # # @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, :failure_reason, :metadata, :attempt_count, :selective_execution_result) 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] emr # The configurations and outcomes of an Amazon EMR step execution. # @return [Types::EMRStepMetadata] # # @!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] 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, :emr, :quality_check, :clarify_check, :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 # A specification for a predefined metric. # # @!attribute [rw] predefined_metric_type # The metric type. You can only apply SageMaker metric types to # SageMaker endpoints. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PredefinedMetricSpecification AWS API Documentation # class PredefinedMetricSpecification < Struct.new( :predefined_metric_type) 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. # # 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]. # # # # # # [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. # # 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]. # # # # # # [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] # # @!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] # # @!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] # # @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] # # @!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] # # @!attribute [rw] managed_instance_scaling # Settings that control the range in the number of instances that the # endpoint provisions as it scales up or down to accommodate traffic. # @return [Types::ProductionVariantManagedInstanceScaling] # # @!attribute [rw] routing_config # Settings that control how the endpoint routes incoming traffic to # the instances that the endpoint hosts. # @return [Types::ProductionVariantRoutingConfig] # # @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, :managed_instance_scaling, :routing_config) 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 # Settings that control the range in the number of instances that the # endpoint provisions as it scales up or down to accommodate traffic. # # @!attribute [rw] status # Indicates whether managed instance scaling is enabled. # @return [String] # # @!attribute [rw] min_instance_count # The minimum number of instances that the endpoint must retain when # it scales down to accommodate a decrease in traffic. # @return [Integer] # # @!attribute [rw] max_instance_count # The maximum number of instances that the endpoint can provision when # it scales up to accommodate an increase in traffic. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProductionVariantManagedInstanceScaling AWS API Documentation # class ProductionVariantManagedInstanceScaling < Struct.new( :status, :min_instance_count, :max_instance_count) SENSITIVE = [] include Aws::Structure end # Settings that control how the endpoint routes incoming traffic to the # instances that the endpoint hosts. # # @!attribute [rw] routing_strategy # Sets how the endpoint routes incoming traffic: # # * `LEAST_OUTSTANDING_REQUESTS`: The endpoint routes requests to the # specific instances that have more capacity to process them. # # * `RANDOM`: The endpoint routes each request to a randomly chosen # instance. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProductionVariantRoutingConfig AWS API Documentation # class ProductionVariantRoutingConfig < Struct.new( :routing_strategy) 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] # # @!attribute [rw] provisioned_concurrency # The amount of provisioned concurrency to allocate for the serverless # endpoint. Should be less than or equal to `MaxConcurrency`. # # This field is not supported for serverless endpoint recommendations # for Inference Recommender jobs. For more information about creating # an Inference Recommender job, see # [CreateInferenceRecommendationsJobs][1]. # # # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceRecommendationsJob.html # @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, :provisioned_concurrency) SENSITIVE = [] include Aws::Structure end # Specifies the serverless update concurrency configuration for an # endpoint variant. # # @!attribute [rw] max_concurrency # The updated maximum number of concurrent invocations your serverless # endpoint can process. # @return [Integer] # # @!attribute [rw] provisioned_concurrency # The updated amount of provisioned concurrency to allocate for the # serverless endpoint. Should be less than or equal to # `MaxConcurrency`. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ProductionVariantServerlessUpdateConfig AWS API Documentation # class ProductionVariantServerlessUpdateConfig < Struct.new( :max_concurrency, :provisioned_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] # # @!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] # # @!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] # # @!attribute [rw] managed_instance_scaling # Settings that control the range in the number of instances that the # endpoint provisions as it scales up or down to accommodate traffic. # @return [Types::ProductionVariantManagedInstanceScaling] # # @!attribute [rw] routing_config # Settings that control how the endpoint routes incoming traffic to # the instances that the endpoint hosts. # @return [Types::ProductionVariantRoutingConfig] # # @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, :managed_instance_scaling, :routing_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] # # @!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] # # @!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] # # @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] # # @!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] # # @!attribute [rw] lineage_types # Filter the lineage entities connected to the `StartArn`(s) by the # type of the lineage entity. # @return [Array] # # @!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] # # @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] # # @!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] # # @!attribute [rw] edges # A list of edges that connect vertices in the response. # @return [Array] # # @!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] # # @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. # # @!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 # The recommended configuration to use for Real-Time Inference. # # @!attribute [rw] recommendation_id # The recommendation ID which uniquely identifies each recommendation. # @return [String] # # @!attribute [rw] instance_type # The recommended instance type for Real-Time Inference. # @return [String] # # @!attribute [rw] environment # The recommended environment variables to set in the model container # for Real-Time Inference. # @return [Hash] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RealTimeInferenceRecommendation AWS API Documentation # class RealTimeInferenceRecommendation < Struct.new( :recommendation_id, :instance_type, :environment) 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] # # @!attribute [rw] supported_endpoint_type # The endpoint type to receive recommendations for. By default this is # null, and the results of the inference recommendation job return a # combined list of both real-time and serverless benchmarks. By # specifying a value for this field, you can receive a longer list of # benchmarks for the desired endpoint type. # @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. 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] # # @!attribute [rw] supported_response_mime_types # The supported MIME types for the output data. # @return [Array] # # @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, :supported_endpoint_type, :data_input_config, :supported_response_mime_types) 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_metrics # The metrics for an existing endpoint compared in an Inference # Recommender job. # @return [Types::InferenceMetrics] # # @!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] invocation_end_time # A timestamp that shows when the benchmark completed. # @return [Time] # # @!attribute [rw] invocation_start_time # A timestamp that shows when the benchmark started. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobInferenceBenchmark AWS API Documentation # class RecommendationJobInferenceBenchmark < Struct.new( :metrics, :endpoint_metrics, :endpoint_configuration, :model_configuration, :failure_reason, :invocation_end_time, :invocation_start_time) 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] model_name # The name of the created model. # @return [String] # # @!attribute [rw] job_duration_in_seconds # Specifies the maximum duration of the job, in seconds. The maximum # value is 18,000 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] # # @!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:::key/"` # # * // KMS Key Alias # # `"alias/ExampleAlias"` # # * // Amazon Resource Name (ARN) of a KMS Key Alias # # `"arn:aws:kms:::alias/"` # # 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] # # @!attribute [rw] vpc_config # Inference Recommender provisions SageMaker endpoints with access to # VPC in the inference recommendation job. # @return [Types::RecommendationJobVpcConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RecommendationJobInputConfig AWS API Documentation # class RecommendationJobInputConfig < Struct.new( :model_package_version_arn, :model_name, :job_duration_in_seconds, :traffic_pattern, :resource_limit, :endpoint_configurations, :volume_kms_key_id, :container_config, :endpoints, :vpc_config) 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:::key/"` # # * // KMS Key Alias # # `"alias/ExampleAlias"` # # * // Amazon Resource Name (ARN) of a KMS Key Alias # # `"arn:aws:kms:::alias/"` # # 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] # # @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] # # @!attribute [rw] flat_invocations # Stops a load test when the number of invocations (TPS) peaks and # flattens, which means that the instance has reached capacity. The # default value is `Stop`. If you want the load test to continue after # invocations have flattened, set the value to `Continue`. # @return [String] # # @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, :flat_invocations) 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] # # @!attribute [rw] subnets # The ID of the subnets in the VPC to which you want to connect your # model. # @return [Array] # # @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] # # @!attribute [rw] model_setup_time # The time it takes to launch new compute resources for a serverless # endpoint. The time can vary depending on the model size, how long it # takes to download the model, and the start-up time of the container. # # `NaN` indicates that the value is not available. # @return [Integer] # # @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, :model_setup_time) 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] # # @!attribute [rw] tags # The tags associated with devices. # @return [Array] # # @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 # Configuration for remote debugging for the [CreateTrainingJob][1] API. # To learn more about the remote debugging functionality of SageMaker, # see [Access a training container through Amazon Web Services Systems # Manager (SSM) for remote debugging][2]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-remote-debugging.html # # @!attribute [rw] enable_remote_debug # If set to True, enables remote debugging. # @return [Boolean] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RemoteDebugConfig AWS API Documentation # class RemoteDebugConfig < Struct.new( :enable_remote_debug) SENSITIVE = [] include Aws::Structure end # Configuration for remote debugging for the [UpdateTrainingJob][1] API. # To learn more about the remote debugging functionality of SageMaker, # see [Access a training container through Amazon Web Services Systems # Manager (SSM) for remote debugging][2]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateTrainingJob.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-remote-debugging.html # # @!attribute [rw] enable_remote_debug # If set to True, enables remote debugging. # @return [Boolean] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RemoteDebugConfigForUpdate AWS API Documentation # class RemoteDebugConfigForUpdate < Struct.new( :enable_remote_debug) 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] # # @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 an # AutoML job. # @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 # A resource catalog containing all of the resources of a specific # resource type within a resource owner account. For an example on # sharing the Amazon SageMaker Feature Store # `DefaultFeatureGroupCatalog`, see [Share Amazon SageMaker Catalog # resource type][1] in the Amazon SageMaker Developer Guide. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/feature-store-cross-account-discoverability-share-sagemaker-catalog.html # # @!attribute [rw] resource_catalog_arn # The Amazon Resource Name (ARN) of the `ResourceCatalog`. # @return [String] # # @!attribute [rw] resource_catalog_name # The name of the `ResourceCatalog`. # @return [String] # # @!attribute [rw] description # A free form description of the `ResourceCatalog`. # @return [String] # # @!attribute [rw] creation_time # The time the `ResourceCatalog` was created. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceCatalog AWS API Documentation # class ResourceCatalog < Struct.new( :resource_catalog_arn, :resource_catalog_name, :description, :creation_time) 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. # # 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. # # # # # # [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. # # 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]. # # # # 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] 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] # # @!attribute [rw] instance_groups # The configuration of a heterogeneous cluster in JSON format. # @return [Array] # # @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, :keep_alive_period_in_seconds, :instance_groups) 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] sage_maker_image_version_alias # The SageMakerImageVersionAlias of the image to launch with. This # value is in SemVer 2.0.0 versioning format. # @return [String] # # @!attribute [rw] instance_type # The instance type that the image version runs on. # # **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. # # # @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, :sage_maker_image_version_alias, :instance_type, :lifecycle_config_arn) SENSITIVE = [] include Aws::Structure end # The retention policy for data stored on an Amazon Elastic File System # volume. # # @!attribute [rw] home_efs_file_system # The default is `Retain`, which specifies to keep the data stored on # the Amazon EFS volume. # # Specify `Delete` to delete the data stored on the Amazon 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 # Specifies a rolling deployment strategy for updating a SageMaker # endpoint. # # @!attribute [rw] maximum_batch_size # Batch size for each rolling step to provision capacity and turn on # traffic on the new endpoint fleet, and terminate capacity on the old # endpoint fleet. Value must be between 5% to 50% of the variant's # total instance count. # @return [Types::CapacitySize] # # @!attribute [rw] wait_interval_in_seconds # The length of the baking period, during which SageMaker monitors # alarms for each batch on the new fleet. # @return [Integer] # # @!attribute [rw] maximum_execution_timeout_in_seconds # The time limit for the total deployment. Exceeding this limit causes # a timeout. # @return [Integer] # # @!attribute [rw] rollback_maximum_batch_size # Batch size for rollback to the old endpoint fleet. Each rolling step # to provision capacity and turn on traffic on the old endpoint fleet, # and terminate capacity on the new endpoint fleet. If this field is # absent, the default value will be set to 100% of total capacity # which means to bring up the whole capacity of the old fleet at once # during rollback. # @return [Types::CapacitySize] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RollingUpdatePolicy AWS API Documentation # class RollingUpdatePolicy < Struct.new( :maximum_batch_size, :wait_interval_in_seconds, :maximum_execution_timeout_in_seconds, :rollback_maximum_batch_size) SENSITIVE = [] include Aws::Structure end # Describes the S3 data source. # # Your input bucket must be in the same Amazon Web Services region as # your training job. # # @!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. # # Your input bucket must be located in same Amazon Web Services region # as your training job. # @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] # # @!attribute [rw] instance_group_names # A list of names of instance groups that get data from the S3 data # source. # @return [Array] # # @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 # Specifies the S3 location of ML model data to deploy. # # @!attribute [rw] s3_uri # Specifies the S3 path of ML model data to deploy. # @return [String] # # @!attribute [rw] s3_data_type # Specifies the type of ML model data to deploy. # # If you choose `S3Prefix`, `S3Uri` identifies a key name prefix. # SageMaker uses all objects that match the specified key name prefix # as part of the ML model data to deploy. A valid key name prefix # identified by `S3Uri` always ends with a forward slash (/). # # If you choose `S3Object`, `S3Uri` identifies an object that is the # ML model data to deploy. # @return [String] # # @!attribute [rw] compression_type # Specifies how the ML model data is prepared. # # If you choose `Gzip` and choose `S3Object` as the value of # `S3DataType`, `S3Uri` identifies an object that is a gzip-compressed # TAR archive. SageMaker will attempt to decompress and untar the # object during model deployment. # # If you choose `None` and chooose `S3Object` as the value of # `S3DataType`, `S3Uri` identifies an object that represents an # uncompressed ML model to deploy. # # If you choose None and choose `S3Prefix` as the value of # `S3DataType`, `S3Uri` identifies a key name prefix, under which all # objects represents the uncompressed ML model to deploy. # # If you choose None, then SageMaker will follow rules below when # creating model data files under /opt/ml/model directory for use by # your inference code: # # * If you choose `S3Object` as the value of `S3DataType`, then # SageMaker will split the key of the S3 object referenced by # `S3Uri` by slash (/), and use the last part as the filename of the # file holding the content of the S3 object. # # * If you choose `S3Prefix` as the value of `S3DataType`, then for # each S3 object under the key name pefix referenced by `S3Uri`, # SageMaker will trim its key by the prefix, and use the remainder # as the path (relative to `/opt/ml/model`) of the file holding the # content of the S3 object. SageMaker will split the remainder by # slash (/), using intermediate parts as directory names and the # last part as filename of the file holding the content of the S3 # object. # # * Do not use any of the following as file names or directory names: # # * An empty or blank string # # * A string which contains null bytes # # * A string longer than 255 bytes # # * A single dot (`.`) # # * A double dot (`..`) # # * Ambiguous file names will result in model deployment failure. For # example, if your uncompressed ML model consists of two S3 objects # `s3://mybucket/model/weights` and # `s3://mybucket/model/weights/part1` and you specify # `s3://mybucket/model/` as the value of `S3Uri` and `S3Prefix` as # the value of `S3DataType`, then it will result in name clash # between `/opt/ml/model/weights` (a regular file) and # `/opt/ml/model/weights/` (a directory). # # * Do not organize the model artifacts in [S3 console using # folders][1]. When you create a folder in S3 console, S3 creates a # 0-byte object with a key set to the folder name you provide. They # key of the 0-byte object ends with a slash (/) which violates # SageMaker restrictions on model artifact file names, leading to # model deployment failure. # # # # [1]: https://docs.aws.amazon.com/AmazonS3/latest/userguide/using-folders.html # @return [String] # # @!attribute [rw] model_access_config # Specifies the access configuration file for the ML model. You can # explicitly accept the model end-user license agreement (EULA) within # the `ModelAccessConfig`. You are responsible for reviewing and # complying with any applicable license terms and making sure they are # acceptable for your use case before downloading or using a model. # @return [Types::ModelAccessConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/S3ModelDataSource AWS API Documentation # class S3ModelDataSource < Struct.new( :s3_uri, :s3_data_type, :compression_type, :model_access_config) 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 # An object containing a recommended scaling policy. # # @note ScalingPolicy is a union - when returned from an API call exactly one value will be set and the returned type will be a subclass of ScalingPolicy corresponding to the set member. # # @!attribute [rw] target_tracking # A target tracking scaling policy. Includes support for predefined or # customized metrics. # @return [Types::TargetTrackingScalingPolicyConfiguration] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ScalingPolicy AWS API Documentation # class ScalingPolicy < Struct.new( :target_tracking, :unknown) SENSITIVE = [] include Aws::Structure include Aws::Structure::Union class TargetTracking < ScalingPolicy; end class Unknown < ScalingPolicy; end end # The metric for a scaling policy. # # @!attribute [rw] invocations_per_instance # The number of invocations sent to a model, normalized by # `InstanceCount` in each ProductionVariant. `1/numberOfInstances` is # sent as the value on each request, where `numberOfInstances` is the # number of active instances for the ProductionVariant behind the # endpoint at the time of the request. # @return [Integer] # # @!attribute [rw] model_latency # The interval of time taken by a model to respond as viewed from # SageMaker. This interval includes the local communication times # 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 [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ScalingPolicyMetric AWS API Documentation # class ScalingPolicyMetric < Struct.new( :invocations_per_instance, :model_latency) SENSITIVE = [] include Aws::Structure end # An object where you specify the anticipated traffic pattern for an # endpoint. # # @!attribute [rw] min_invocations_per_minute # The minimum number of expected requests to your endpoint per minute. # @return [Integer] # # @!attribute [rw] max_invocations_per_minute # The maximum number of expected requests to your endpoint per minute. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ScalingPolicyObjective AWS API Documentation # class ScalingPolicyObjective < Struct.new( :min_invocations_per_minute, :max_invocations_per_minute) 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. # # The supported cron expressions are: # # * If you want to set the job to start every hour, use the following: # # `Hourly: cron(0 * ? * * *)` # # * If you want to start the job daily: # # `cron(0 [00-23] ? * * *)` # # * If you want to run the job one time, immediately, use the # following keyword: # # `NOW` # # 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 ? * * *)` # # * 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. # # # # You can also specify the keyword `NOW` to run the monitoring job # immediately, one time, without recurring. # @return [String] # # @!attribute [rw] data_analysis_start_time # Sets the start time for a monitoring job window. Express this time # as an offset to the times that you schedule your monitoring jobs to # run. You schedule monitoring jobs with the `ScheduleExpression` # parameter. Specify this offset in ISO 8601 duration format. For # example, if you want to monitor the five hours of data in your # dataset that precede the start of each monitoring job, you would # specify: `"-PT5H"`. # # The start time that you specify must not precede the end time that # you specify by more than 24 hours. You specify the end time with the # `DataAnalysisEndTime` parameter. # # If you set `ScheduleExpression` to `NOW`, this parameter is # required. # @return [String] # # @!attribute [rw] data_analysis_end_time # Sets the end time for a monitoring job window. Express this time as # an offset to the times that you schedule your monitoring jobs to # run. You schedule monitoring jobs with the `ScheduleExpression` # parameter. Specify this offset in ISO 8601 duration format. For # example, if you want to end the window one hour before the start of # each monitoring job, you would specify: `"-PT1H"`. # # The end time that you specify must not follow the start time that # you specify by more than 24 hours. You specify the start time with # the `DataAnalysisStartTime` parameter. # # If you set `ScheduleExpression` to `NOW`, this parameter is # required. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ScheduleConfig AWS API Documentation # class ScheduleConfig < Struct.new( :schedule_expression, :data_analysis_start_time, :data_analysis_end_time) 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] # # @!attribute [rw] nested_filters # A list of nested filter objects. # @return [Array] # # @!attribute [rw] sub_expressions # A list of search expression objects. # @return [Array] # # @!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] feature_metadata # The feature metadata used to search through the features. # @return [Types::FeatureMetadata] # # @!attribute [rw] project # The properties of a project. # @return [Types::Project] # # @!attribute [rw] hyper_parameter_tuning_job # The properties of a hyperparameter tuning job. # @return [Types::HyperParameterTuningJobSearchEntity] # # @!attribute [rw] model_card # An Amazon SageMaker Model Card that documents details about a # machine learning model. # @return [Types::ModelCard] # # @!attribute [rw] model # A model displayed in the Amazon SageMaker Model Dashboard. # @return [Types::ModelDashboardModel] # # @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, :feature_metadata, :project, :hyper_parameter_tuning_job, :model_card, :model) 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] # # @!attribute [rw] cross_account_filter_option # A cross account filter option. When the value is `"CrossAccount"` # the search results will only include resources made discoverable to # you from other accounts. When the value is `"SameAccount"` or `null` # the search results will only include resources from your account. # Default is `null`. For more information on searching for resources # made discoverable to your account, see [ Search discoverable # resources][1] in the SageMaker Developer Guide. The maximum number # of `ResourceCatalog`s viewable is 1000. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/feature-store-cross-account-discoverability-use.html # @return [String] # # @!attribute [rw] visibility_conditions # Limits the results of your search request to the resources that you # can access. # @return [Array] # # @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, :cross_account_filter_option, :visibility_conditions) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] results # A list of `SearchRecord` objects. # @return [Array] # # @!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 # : * 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 # A step selected to run in selective execution mode. # # @!attribute [rw] step_name # The name of the pipeline step. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SelectedStep AWS API Documentation # class SelectedStep < Struct.new( :step_name) SENSITIVE = [] include Aws::Structure end # The selective execution configuration applied to the pipeline run. # # @!attribute [rw] source_pipeline_execution_arn # The ARN from a reference execution of the current pipeline. Used to # copy input collaterals needed for the selected steps to run. The # execution status of the pipeline can be either `Failed` or # `Success`. # # This field is required if the steps you specify for `SelectedSteps` # depend on output collaterals from any non-specified pipeline steps. # For more information, see [Selective Execution for Pipeline # Steps][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/pipelines-selective-ex.html # @return [String] # # @!attribute [rw] selected_steps # A list of pipeline steps to run. All step(s) in all path(s) between # two selected steps should be included. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SelectiveExecutionConfig AWS API Documentation # class SelectiveExecutionConfig < Struct.new( :source_pipeline_execution_arn, :selected_steps) SENSITIVE = [] include Aws::Structure end # The ARN from an execution of the current pipeline. # # @!attribute [rw] source_pipeline_execution_arn # The ARN from an execution of the current pipeline. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SelectiveExecutionResult AWS API Documentation # class SelectiveExecutionResult < Struct.new( :source_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] 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] # # @!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] # # @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] # # @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] # # @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 Amazon 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). # # The model artifacts must be in an S3 bucket that is in the same # Amazon Web Services region as the algorithm. # # # @return [String] # # @!attribute [rw] model_data_source # Specifies the location of ML model data to deploy during endpoint # creation. # @return [Types::ModelDataSource] # # @!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, :model_data_source, :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] # # @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 # # The following Length Constraints apply to individual CIDR values in # the CIDR value list. # # # # # # [1]: https://docs.aws.amazon.com/vpc/latest/userguide/VPC_Subnets.html # @return [Array] # # @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 application settings for a Code Editor space. # # @!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/SpaceCodeEditorAppSettings AWS API Documentation # class SpaceCodeEditorAppSettings < Struct.new( :default_resource_spec) 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] # # @!attribute [rw] space_settings_summary # Specifies summary information about the space settings. # @return [Types::SpaceSettingsSummary] # # @!attribute [rw] space_sharing_settings_summary # Specifies summary information about the space sharing settings. # @return [Types::SpaceSharingSettingsSummary] # # @!attribute [rw] ownership_settings_summary # Specifies summary information about the ownership settings. # @return [Types::OwnershipSettingsSummary] # # @!attribute [rw] space_display_name # The name of the space that appears in the Studio UI. # @return [String] # # @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, :space_settings_summary, :space_sharing_settings_summary, :ownership_settings_summary, :space_display_name) SENSITIVE = [] include Aws::Structure end # The settings for the JupyterLab application within a space. # # @!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] code_repositories # A list of Git repositories that SageMaker automatically displays to # users for cloning in the JupyterLab application. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SpaceJupyterLabAppSettings AWS API Documentation # class SpaceJupyterLabAppSettings < Struct.new( :default_resource_spec, :code_repositories) 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] # # @!attribute [rw] code_editor_app_settings # The Code Editor application settings. # @return [Types::SpaceCodeEditorAppSettings] # # @!attribute [rw] jupyter_lab_app_settings # The settings for the JupyterLab application. # @return [Types::SpaceJupyterLabAppSettings] # # @!attribute [rw] app_type # The type of app created within the space. # @return [String] # # @!attribute [rw] space_storage_settings # The storage settings for a private space. # @return [Types::SpaceStorageSettings] # # @!attribute [rw] custom_file_systems # A file system, created by you, that you assign to a space for an # Amazon SageMaker Domain. Permitted users can access this file system # in Amazon SageMaker Studio. # @return [Array] # # @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, :code_editor_app_settings, :jupyter_lab_app_settings, :app_type, :space_storage_settings, :custom_file_systems) SENSITIVE = [] include Aws::Structure end # Specifies summary information about the space settings. # # @!attribute [rw] app_type # The type of app created within the space. # @return [String] # # @!attribute [rw] space_storage_settings # The storage settings for a private space. # @return [Types::SpaceStorageSettings] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SpaceSettingsSummary AWS API Documentation # class SpaceSettingsSummary < Struct.new( :app_type, :space_storage_settings) SENSITIVE = [] include Aws::Structure end # A collection of space sharing settings. # # @!attribute [rw] sharing_type # Specifies the sharing type of the space. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SpaceSharingSettings AWS API Documentation # class SpaceSharingSettings < Struct.new( :sharing_type) SENSITIVE = [] include Aws::Structure end # Specifies summary information about the space sharing settings. # # @!attribute [rw] sharing_type # Specifies the sharing type of the space. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SpaceSharingSettingsSummary AWS API Documentation # class SpaceSharingSettingsSummary < Struct.new( :sharing_type) SENSITIVE = [] include Aws::Structure end # The storage settings for a private space. # # @!attribute [rw] ebs_storage_settings # A collection of EBS storage settings for a private space. # @return [Types::EbsStorageSettings] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SpaceStorageSettings AWS API Documentation # class SpaceStorageSettings < Struct.new( :ebs_storage_settings) SENSITIVE = [] include Aws::Structure end # Defines the stairs traffic pattern for an Inference Recommender load # test. This pattern type consists of multiple steps where the number of # users increases at each step. # # Specify either the stairs or phases traffic pattern. # # @!attribute [rw] duration_in_seconds # Defines how long each traffic step should be. # @return [Integer] # # @!attribute [rw] number_of_steps # Specifies how many steps to perform during traffic. # @return [Integer] # # @!attribute [rw] users_per_step # Specifies how many new users to spawn in each step. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/Stairs AWS API Documentation # class Stairs < Struct.new( :duration_in_seconds, :number_of_steps, :users_per_step) 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 or Amazon Resource Name (ARN) 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] # # @!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] # # @!attribute [rw] selective_execution_config # The selective execution configuration applied to the pipeline run. # @return [Types::SelectiveExecutionConfig] # # @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, :selective_execution_config) 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] # # @!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] # # @!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`. # # 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. # # # # @!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] # # @!attribute [rw] max_pending_time_in_seconds # The maximum length of time, in seconds, that a training or # compilation job can be pending before it is stopped. # @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, :max_pending_time_in_seconds) SENSITIVE = [] include Aws::Structure end # Details of the Amazon SageMaker 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 Amazon SageMaker Studio Lifecycle Configuration. # @return [String] # # @!attribute [rw] creation_time # The creation time of the Amazon SageMaker Studio Lifecycle # Configuration. # @return [Time] # # @!attribute [rw] last_modified_time # This value is equivalent to CreationTime because Amazon SageMaker # 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 # The collection of settings used by an AutoML job V2 for the tabular # problem type. # # @!attribute [rw] candidate_generation_config # The configuration information of how model candidates are generated. # @return [Types::CandidateGenerationConfig] # # @!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] 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 V2. 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" ... # \} \}` # # These column keys may not include the target column. # # # # 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] 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-support # @return [String] # # @!attribute [rw] generate_candidate_definitions_only # Generates possible candidates without training the models. A model # candidate is a combination of data preprocessors, algorithms, and # algorithm parameter settings. # @return [Boolean] # # @!attribute [rw] problem_type # The type of supervised learning problem available for the model # candidates of the AutoML job V2. For more information, see [ # SageMaker Autopilot problem types][1]. # # You must either specify the type of supervised learning problem in # `ProblemType` and provide the [AutoMLJobObjective][2] metric, or # none at all. # # # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-problem-types # [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateAutoMLJobV2.html#sagemaker-CreateAutoMLJobV2-request-AutoMLJobObjective # @return [String] # # @!attribute [rw] target_attribute_name # The name of the target variable in supervised learning, usually # represented by 'y'. # @return [String] # # @!attribute [rw] sample_weight_attribute_name # If specified, this column name indicates which column of the dataset # should be treated as sample weights for use by the objective metric # during the training, evaluation, and the selection of the best # model. This column is not considered as a predictive feature. For # more information on Autopilot metrics, see [Metrics and # validation][1]. # # Sample weights should be numeric, non-negative, with larger values # indicating which rows are more important than others. Data points # that have invalid or no weight value are excluded. # # Support for sample weights is available in [Ensembling][2] mode # only. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-metrics-validation.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_AutoMLAlgorithmConfig.html # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TabularJobConfig AWS API Documentation # class TabularJobConfig < Struct.new( :candidate_generation_config, :completion_criteria, :feature_specification_s3_uri, :mode, :generate_candidate_definitions_only, :problem_type, :target_attribute_name, :sample_weight_attribute_name) SENSITIVE = [] include Aws::Structure end # The resolved attributes specific to the tabular problem type. # # @!attribute [rw] problem_type # The type of supervised learning problem available for the model # candidates of the AutoML job V2 (Binary Classification, Multiclass # Classification, Regression). For more information, see [ SageMaker # Autopilot problem types][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-datasets-problem-types.html#autopilot-problem-types # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TabularResolvedAttributes AWS API Documentation # class TabularResolvedAttributes < Struct.new( :problem_type) 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 # A target tracking scaling policy. Includes support for predefined or # customized metrics. # # When using the [PutScalingPolicy][1] API, this parameter is required # when you are creating a policy with the policy type # `TargetTrackingScaling`. # # # # [1]: https://docs.aws.amazon.com/autoscaling/application/APIReference/API_PutScalingPolicy.html # # @!attribute [rw] metric_specification # An object containing information about a metric. # @return [Types::MetricSpecification] # # @!attribute [rw] target_value # The recommended target value to specify for the metric when creating # a scaling policy. # @return [Float] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TargetTrackingScalingPolicyConfiguration AWS API Documentation # class TargetTrackingScalingPolicyConfiguration < Struct.new( :metric_specification, :target_value) 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 # The collection of settings used by an AutoML job V2 for the text # classification problem type. # # @!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 # The collection of settings used by an AutoML job V2 for the text # generation problem type. # # The text generation models that support fine-tuning in Autopilot are # currently accessible exclusively in regions supported by Canvas. Refer # to the documentation of Canvas for the [full list of its supported # Regions][1]. # # # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/canvas.html # # @!attribute [rw] completion_criteria # How long a fine-tuning job is allowed to run. For # `TextGenerationJobConfig` problem types, the # `MaxRuntimePerTrainingJobInSeconds` attribute of # `AutoMLJobCompletionCriteria` defaults to 72h (259200s). # @return [Types::AutoMLJobCompletionCriteria] # # @!attribute [rw] base_model_name # The name of the base model to fine-tune. Autopilot supports # fine-tuning a variety of large language models. For information on # the list of supported models, see [Text generation models supporting # fine-tuning in Autopilot][1]. If no `BaseModelName` is provided, the # default model used is **Falcon7BInstruct**. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-llms-finetuning-models.html#autopilot-llms-finetuning-supported-llms # @return [String] # # @!attribute [rw] text_generation_hyper_parameters # The hyperparameters used to configure and optimize the learning # process of the base model. You can set any combination of the # following hyperparameters for all base models. For more information # on each supported hyperparameter, see [Optimize the learning process # of your text generation models with hyperparameters][1]. # # * `"epochCount"`: The number of times the model goes through the # entire training dataset. Its value should be a string containing # an integer value within the range of "1" to "10". # # * `"batchSize"`: The number of data samples used in each iteration # of training. Its value should be a string containing an integer # value within the range of "1" to "64". # # * `"learningRate"`: The step size at which a model's parameters are # updated during training. Its value should be a string containing a # floating-point value within the range of "0" to "1". # # * `"learningRateWarmupSteps"`: The number of training steps during # which the learning rate gradually increases before reaching its # target or maximum value. Its value should be a string containing # an integer value within the range of "0" to "250". # # Here is an example where all four hyperparameters are configured. # # `\{ "epochCount":"5", "learningRate":"0.5", "batchSize": "32", # "learningRateWarmupSteps": "10" \}` # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-llms-finetuning-set-hyperparameters.html # @return [Hash] # # @!attribute [rw] model_access_config # The access configuration file to control access to the ML model. You # can explicitly accept the model end-user license agreement (EULA) # within the `ModelAccessConfig`. # # * If you are a Jumpstart user, see the [End-user license # agreements][1] section for more details on accepting the EULA. # # * If you are an AutoML user, see the *Optional Parameters* section # of *Create an AutoML job to fine-tune text generation models using # the API* for details on [How to set the EULA acceptance when # fine-tuning a model using the AutoML API][2]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/jumpstart-foundation-models-choose.html#jumpstart-foundation-models-choose-eula # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-create-experiment-finetune-llms.html#autopilot-llms-finetuning-api-optional-params # @return [Types::ModelAccessConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TextGenerationJobConfig AWS API Documentation # class TextGenerationJobConfig < Struct.new( :completion_criteria, :base_model_name, :text_generation_hyper_parameters, :model_access_config) SENSITIVE = [] include Aws::Structure end # The resolved attributes specific to the text generation problem type. # # @!attribute [rw] base_model_name # The name of the base model to fine-tune. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TextGenerationResolvedAttributes AWS API Documentation # class TextGenerationResolvedAttributes < Struct.new( :base_model_name) SENSITIVE = [] include Aws::Structure end # Used to set feature group throughput configuration. There are two # modes: `ON_DEMAND` and `PROVISIONED`. With on-demand mode, you are # charged for data reads and writes that your application performs on # your feature group. You do not need to specify read and write # throughput because Feature Store accommodates your workloads as they # ramp up and down. You can switch a feature group to on-demand only # once in a 24 hour period. With provisioned throughput mode, you # specify the read and write capacity per second that you expect your # application to require, and you are billed based on those limits. # Exceeding provisioned throughput will result in your requests being # throttled. # # Note: `PROVISIONED` throughput mode is supported only for feature # groups that are offline-only, or use the [ `Standard` ][1] tier online # store. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OnlineStoreConfig.html#sagemaker-Type-OnlineStoreConfig-StorageType # # @!attribute [rw] throughput_mode # The mode used for your feature group throughput: `ON_DEMAND` or # `PROVISIONED`. # @return [String] # # @!attribute [rw] provisioned_read_capacity_units # For provisioned feature groups with online store enabled, this # indicates the read throughput you are billed for and can consume # without throttling. # # This field is not applicable for on-demand feature groups. # @return [Integer] # # @!attribute [rw] provisioned_write_capacity_units # For provisioned feature groups, this indicates the write throughput # you are billed for and can consume without throttling. # # This field is not applicable for on-demand feature groups. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ThroughputConfig AWS API Documentation # class ThroughputConfig < Struct.new( :throughput_mode, :provisioned_read_capacity_units, :provisioned_write_capacity_units) SENSITIVE = [] include Aws::Structure end # Active throughput configuration of the feature group. There are two # modes: `ON_DEMAND` and `PROVISIONED`. With on-demand mode, you are # charged for data reads and writes that your application performs on # your feature group. You do not need to specify read and write # throughput because Feature Store accommodates your workloads as they # ramp up and down. You can switch a feature group to on-demand only # once in a 24 hour period. With provisioned throughput mode, you # specify the read and write capacity per second that you expect your # application to require, and you are billed based on those limits. # Exceeding provisioned throughput will result in your requests being # throttled. # # Note: `PROVISIONED` throughput mode is supported only for feature # groups that are offline-only, or use the [ `Standard` ][1] tier online # store. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_OnlineStoreConfig.html#sagemaker-Type-OnlineStoreConfig-StorageType # # @!attribute [rw] throughput_mode # The mode used for your feature group throughput: `ON_DEMAND` or # `PROVISIONED`. # @return [String] # # @!attribute [rw] provisioned_read_capacity_units # For provisioned feature groups with online store enabled, this # indicates the read throughput you are billed for and can consume # without throttling. # # This field is not applicable for on-demand feature groups. # @return [Integer] # # @!attribute [rw] provisioned_write_capacity_units # For provisioned feature groups, this indicates the write throughput # you are billed for and can consume without throttling. # # This field is not applicable for on-demand feature groups. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ThroughputConfigDescription AWS API Documentation # class ThroughputConfigDescription < Struct.new( :throughput_mode, :provisioned_read_capacity_units, :provisioned_write_capacity_units) SENSITIVE = [] include Aws::Structure end # The new throughput configuration for the feature group. You can switch # between on-demand and provisioned modes or update the read / write # capacity of provisioned feature groups. You can switch a feature group # to on-demand only once in a 24 hour period. # # @!attribute [rw] throughput_mode # Target throughput mode of the feature group. Throughput update is an # asynchronous operation, and the outcome should be monitored by # polling `LastUpdateStatus` field in `DescribeFeatureGroup` response. # You cannot update a feature group's throughput while another update # is in progress. # @return [String] # # @!attribute [rw] provisioned_read_capacity_units # For provisioned feature groups with online store enabled, this # indicates the read throughput you are billed for and can consume # without throttling. # @return [Integer] # # @!attribute [rw] provisioned_write_capacity_units # For provisioned feature groups, this indicates the write throughput # you are billed for and can consume without throttling. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ThroughputConfigUpdate AWS API Documentation # class ThroughputConfigUpdate < Struct.new( :throughput_mode, :provisioned_read_capacity_units, :provisioned_write_capacity_units) SENSITIVE = [] include Aws::Structure end # The collection of components that defines the time-series. # # @!attribute [rw] target_attribute_name # The name of the column representing the target variable that you # want to predict for each item in your dataset. The data type of the # target variable must be numerical. # @return [String] # # @!attribute [rw] timestamp_attribute_name # The name of the column indicating a point in time at which the # target value of a given item is recorded. # @return [String] # # @!attribute [rw] item_identifier_attribute_name # The name of the column that represents the set of item identifiers # for which you want to predict the target value. # @return [String] # # @!attribute [rw] grouping_attribute_names # A set of columns names that can be grouped with the item identifier # column to create a composite key for which a target value is # predicted. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TimeSeriesConfig AWS API Documentation # class TimeSeriesConfig < Struct.new( :target_attribute_name, :timestamp_attribute_name, :item_identifier_attribute_name, :grouping_attribute_names) SENSITIVE = [] include Aws::Structure end # The collection of settings used by an AutoML job V2 for the # time-series forecasting problem type. # # @!attribute [rw] feature_specification_s3_uri # A URL to the Amazon S3 data source containing additional selected # features that complement the target, itemID, timestamp, and grouped # columns set in `TimeSeriesConfig`. When not provided, the AutoML job # V2 includes all the columns from the original dataset that are not # already declared in `TimeSeriesConfig`. If provided, the AutoML job # V2 only considers these additional columns as a complement to the # ones declared in `TimeSeriesConfig`. # # 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" ... # \} \}` # # Autopilot supports the following data types: `numeric`, # `categorical`, `text`, and `datetime`. # # These column keys must not include any column set in # `TimeSeriesConfig`. # # # @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] # # @!attribute [rw] forecast_frequency # The frequency of predictions in a forecast. # # Valid intervals are an integer followed by Y (Year), M (Month), W # (Week), D (Day), H (Hour), and min (Minute). For example, `1D` # indicates every day and `15min` indicates every 15 minutes. The # value of a frequency must not overlap with the next larger # frequency. For example, you must use a frequency of `1H` instead of # `60min`. # # The valid values for each frequency are the following: # # * Minute - 1-59 # # * Hour - 1-23 # # * Day - 1-6 # # * Week - 1-4 # # * Month - 1-11 # # * Year - 1 # @return [String] # # @!attribute [rw] forecast_horizon # The number of time-steps that the model predicts. The forecast # horizon is also called the prediction length. The maximum forecast # horizon is the lesser of 500 time-steps or 1/4 of the time-steps in # the dataset. # @return [Integer] # # @!attribute [rw] forecast_quantiles # The quantiles used to train the model for forecasts at a specified # quantile. You can specify quantiles from `0.01` (p1) to `0.99` # (p99), by increments of 0.01 or higher. Up to five forecast # quantiles can be specified. When `ForecastQuantiles` is not # provided, the AutoML job uses the quantiles p10, p50, and p90 as # default. # @return [Array] # # @!attribute [rw] transformations # The transformations modifying specific attributes of the # time-series, such as filling strategies for missing values. # @return [Types::TimeSeriesTransformations] # # @!attribute [rw] time_series_config # The collection of components that defines the time-series. # @return [Types::TimeSeriesConfig] # # @!attribute [rw] holiday_config # The collection of holiday featurization attributes used to # incorporate national holiday information into your forecasting # model. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TimeSeriesForecastingJobConfig AWS API Documentation # class TimeSeriesForecastingJobConfig < Struct.new( :feature_specification_s3_uri, :completion_criteria, :forecast_frequency, :forecast_horizon, :forecast_quantiles, :transformations, :time_series_config, :holiday_config) 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 # Transformations allowed on the dataset. Supported transformations are # `Filling` and `Aggregation`. `Filling` specifies how to add values to # missing values in the dataset. `Aggregation` defines how to aggregate # data that does not align with forecast frequency. # # @!attribute [rw] filling # A key value pair defining the filling method for a column, where the # key is the column name and the value is an object which defines the # filling logic. You can specify multiple filling methods for a single # column. # # The supported filling methods and their corresponding options are: # # * `frontfill`: `none` (Supported only for target column) # # * `middlefill`: `zero`, `value`, `median`, `mean`, `min`, `max` # # * `backfill`: `zero`, `value`, `median`, `mean`, `min`, `max` # # * `futurefill`: `zero`, `value`, `median`, `mean`, `min`, `max` # # To set a filling method to a specific value, set the fill parameter # to the chosen filling method value (for example `"backfill" : # "value"`), and define the filling value in an additional parameter # prefixed with "\_value". For example, to set `backfill` to a value # of `2`, you must include two parameters: `"backfill": "value"` and # `"backfill_value":"2"`. # @return [Hash>] # # @!attribute [rw] aggregation # A key value pair defining the aggregation method for a column, where # the key is the column name and the value is the aggregation method. # # The supported aggregation methods are `sum` (default), `avg`, # `first`, `min`, `max`. # # Aggregation is only supported for the target column. # # # @return [Hash] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TimeSeriesTransformations AWS API Documentation # class TimeSeriesTransformations < Struct.new( :filling, :aggregation) SENSITIVE = [] include Aws::Structure end # Defines the traffic pattern of the load test. # # @!attribute [rw] traffic_type # Defines the traffic patterns. Choose either `PHASES` or `STAIRS`. # @return [String] # # @!attribute [rw] phases # Defines the phases traffic specification. # @return [Array] # # @!attribute [rw] stairs # Defines the stairs traffic pattern. # @return [Types::Stairs] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrafficPattern AWS API Documentation # class TrafficPattern < Struct.new( :traffic_type, :phases, :stairs) 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] # # @!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. # # Your input must be in the same Amazon Web Services region as your # training job. # @return [Array] # # @!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] # # @!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] # # @!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] # # @!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] # # @!attribute [rw] profiler_config # Configuration information for Amazon SageMaker Debugger system # monitoring, framework profiling, and storage paths. # @return [Types::ProfilerConfig] # # @!attribute [rw] environment # The environment variables to set in the Docker container. # @return [Hash] # # @!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] # # @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, :profiler_config, :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] # # @!attribute [rw] input_data_config # An array of `Channel` objects, each of which specifies an input # source. # @return [Array] # # @!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] # # @!attribute [rw] supported_training_instance_types # A list of the instance types that this algorithm can use for # training. # @return [Array] # # @!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] # # @!attribute [rw] training_channels # A list of `ChannelSpecification` objects, which specify the input # sources to be used by the algorithm. # @return [Array] # # @!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] # # @!attribute [rw] additional_s3_data_source # The additional data source used during the training job. # @return [Types::AdditionalS3DataSource] # # @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, :additional_s3_data_source) 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. # # 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. # # # # # # [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] # # @!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] data_capture_config # Configuration to control how SageMaker captures inference data for # batch transform jobs. # @return [Types::BatchDataCaptureConfig] # # @!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] # # @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, :data_capture_config, :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] # # @!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. # # 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]. # # # # 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] # # @!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] # # @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] # # @!attribute [rw] input_artifacts # The input artifacts of the component. # @return [Hash] # # @!attribute [rw] output_artifacts # The output artifacts of the component. # @return [Hash] # # @!attribute [rw] metrics # The metrics for the component. # @return [Array] # # @!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] # # @!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] # # @!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 # Time to live duration, where the record is hard deleted after the # expiration time is reached; `ExpiresAt` = `EventTime` + `TtlDuration`. # For information on HardDelete, see the [DeleteRecord][1] API in the # Amazon SageMaker API Reference guide. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_feature_store_DeleteRecord.html # # @!attribute [rw] unit # `TtlDuration` time unit. # @return [String] # # @!attribute [rw] value # `TtlDuration` time value. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TtlDuration AWS API Documentation # class TtlDuration < Struct.new( :unit, :value) 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] # # @!attribute [rw] properties_to_remove # A list of properties to remove. # @return [Array] # # @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] # # @!attribute [rw] jupyter_lab_app_image_config # The JupyterLab app running on the image. # @return [Types::JupyterLabAppImageConfig] # # @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, :jupyter_lab_app_image_config) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] app_image_config_arn # The 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] # # @!attribute [rw] properties_to_remove # A list of properties to remove. # @return [Array] # # @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] cluster_name # Specify the name of the SageMaker HyperPod cluster you want to # update. # @return [String] # # @!attribute [rw] instance_groups # Specify the instance groups to update. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateClusterRequest AWS API Documentation # class UpdateClusterRequest < Struct.new( :cluster_name, :instance_groups) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] cluster_arn # The Amazon Resource Name (ARN) of the updated SageMaker HyperPod # cluster. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateClusterResponse AWS API Documentation # class UpdateClusterResponse < Struct.new( :cluster_arn) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] cluster_name # Specify the name or the Amazon Resource Name (ARN) of the SageMaker # HyperPod cluster you want to update for security patching. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateClusterSoftwareRequest AWS API Documentation # class UpdateClusterSoftwareRequest < Struct.new( :cluster_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] cluster_arn # The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster # being updated for security patching. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateClusterSoftwareResponse AWS API Documentation # class UpdateClusterSoftwareResponse < Struct.new( :cluster_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] # # @!attribute [rw] properties_to_remove # A list of properties to remove. # @return [Array] # # @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] # # @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] 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. If setting up the domain for use with RStudio, this # value must be set to `Service`. # @return [String] # # @!attribute [rw] default_space_settings # The default settings used to create a space within the domain. # @return [Types::DefaultSpaceSettings] # # @!attribute [rw] subnet_ids # The VPC subnets that Studio uses for communication. # # If removing subnets, ensure there are no apps in the `InService`, # `Pending`, or `Deleting` state. # @return [Array] # # @!attribute [rw] app_network_access_type # Specifies the VPC used for non-EFS traffic. # # * `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. # # This configuration can only be modified if there are no apps in the # `InService`, `Pending`, or `Deleting` state. The configuration # cannot be updated if # `DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn` # is already set or # `DomainSettings.RStudioServerProDomainSettings.DomainExecutionRoleArn` # is provided as part of the same request. # @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, :app_security_group_management, :default_space_settings, :subnet_ids, :app_network_access_type) 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] # # @!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] # # @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 or Amazon Resource Name (ARN) 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] # # @!attribute [rw] online_store_config # Updates the feature group online store configuration. # @return [Types::OnlineStoreConfigUpdate] # # @!attribute [rw] throughput_config # The new throughput configuration for the feature group. You can # switch between on-demand and provisioned modes or update the read / # write capacity of provisioned feature groups. You can switch a # feature group to on-demand only once in a 24 hour period. # @return [Types::ThroughputConfigUpdate] # # @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, :online_store_config, :throughput_config) 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 or Amazon Resource Name (ARN) 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] # # @!attribute [rw] parameter_removals # A list of parameter keys that you can specify to remove parameters # that describe your feature. # @return [Array] # # @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] # # @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] # # @!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] # # @!attribute [rw] aliases_to_delete # A list of aliases to delete. # @return [Array] # # @!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] inference_component_name # The name of the inference component. # @return [String] # # @!attribute [rw] specification # Details about the resources to deploy with this inference component, # including the model, container, and compute resources. # @return [Types::InferenceComponentSpecification] # # @!attribute [rw] runtime_config # Runtime settings for a model that is deployed with an inference # component. # @return [Types::InferenceComponentRuntimeConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateInferenceComponentInput AWS API Documentation # class UpdateInferenceComponentInput < Struct.new( :inference_component_name, :specification, :runtime_config) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] inference_component_arn # The Amazon Resource Name (ARN) of the inference component. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateInferenceComponentOutput AWS API Documentation # class UpdateInferenceComponentOutput < Struct.new( :inference_component_arn) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] inference_component_name # The name of the inference component to update. # @return [String] # # @!attribute [rw] desired_runtime_config # Runtime settings for a model that is deployed with an inference # component. # @return [Types::InferenceComponentRuntimeConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateInferenceComponentRuntimeConfigInput AWS API Documentation # class UpdateInferenceComponentRuntimeConfigInput < Struct.new( :inference_component_name, :desired_runtime_config) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] inference_component_arn # The Amazon Resource Name (ARN) of the inference component. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateInferenceComponentRuntimeConfigOutput AWS API Documentation # class UpdateInferenceComponentRuntimeConfigOutput < Struct.new( :inference_component_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] # # @!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 or Amazon Resource Name (ARN) 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] # # @!attribute [rw] customer_metadata_properties_to_remove # The metadata properties associated with the model package versions # to remove. # @return [Array] # # @!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] # # @!attribute [rw] inference_specification # Specifies details about inference jobs that you can run with models # based on this model package, including the following information: # # * 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] source_uri # The URI of the source for the model package. # @return [String] # # @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, :inference_specification, :source_uri) 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]. # # To be able to pass this role to SageMaker, the caller of this API # must have the `iam:PassRole` permission. # # # # # # [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] # # @!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] # # @!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`. # # 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. # # # @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] # # @!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] # # @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] # # @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] # # @!attribute [rw] space_display_name # The name of the space that appears in the Amazon SageMaker Studio # UI. # @return [String] # # @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, :space_display_name) 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] # # @!attribute [rw] resource_config # The training job `ResourceConfig` to update warm pool retention # length. # @return [Types::ResourceConfigForUpdate] # # @!attribute [rw] remote_debug_config # Configuration for remote debugging while the training job is # running. You can update the remote debugging configuration when the # `SecondaryStatus` of the job is `Downloading` or `Training`.To learn # more about the remote debugging functionality of SageMaker, see # [Access a training container through Amazon Web Services Systems # Manager (SSM) for remote debugging][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-remote-debugging.html # @return [Types::RemoteDebugConfigForUpdate] # # @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, :remote_debug_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] # # @!attribute [rw] parameters_to_remove # The hyperparameters to remove from the component. # @return [Array] # # @!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] # # @!attribute [rw] input_artifacts_to_remove # The input artifacts to remove from the component. # @return [Array] # # @!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] # # @!attribute [rw] output_artifacts_to_remove # The output artifacts to remove from the component. # @return [Array] # # @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] # # @!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 in a domain. 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 # the domain 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 # Amazon SageMaker Studio. Therefore, the number of security groups # that you can specify is one less than the maximum number shown. # @return [Array] # # @!attribute [rw] sharing_settings # Specifies options for sharing Amazon 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] # # @!attribute [rw] code_editor_app_settings # The Code Editor application settings. # @return [Types::CodeEditorAppSettings] # # @!attribute [rw] jupyter_lab_app_settings # The settings for the JupyterLab application. # @return [Types::JupyterLabAppSettings] # # @!attribute [rw] space_storage_settings # The storage settings for a private space. # @return [Types::DefaultSpaceStorageSettings] # # @!attribute [rw] default_landing_uri # The default experience that the user is directed to when accessing # the domain. The supported values are: # # * `studio::`: Indicates that Studio is the default experience. This # value can only be passed if `StudioWebPortal` is set to `ENABLED`. # # * `app:JupyterServer:`: Indicates that Studio Classic is the default # experience. # @return [String] # # @!attribute [rw] studio_web_portal # Whether the user can access Studio. If this value is set to # `DISABLED`, the user cannot access Studio, even if that is the # default experience for the domain. # @return [String] # # @!attribute [rw] custom_posix_user_config # Details about the POSIX identity that is used for file system # operations. # @return [Types::CustomPosixUserConfig] # # @!attribute [rw] custom_file_system_configs # The settings for assigning a custom file system to a user profile. # Permitted users can access this file system in Amazon SageMaker # Studio. # @return [Array] # # @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, :code_editor_app_settings, :jupyter_lab_app_settings, :space_storage_settings, :default_landing_uri, :studio_web_portal, :custom_posix_user_config, :custom_file_system_configs) 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 # Configuration for your vector collection type. # # @!attribute [rw] dimension # The number of elements in your vector. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/VectorConfig AWS API Documentation # class VectorConfig < Struct.new( :dimension) 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 # The list of key-value pairs used to filter your search results. If a # search result contains a key from your list, it is included in the # final search response if the value associated with the key in the # result matches the value you specified. If the value doesn't match, # the result is excluded from the search response. Any resources that # don't have a key from the list that you've provided will also be # included in the search response. # # @!attribute [rw] key # The key that specifies the tag that you're using to filter the # search results. It must be in the following format: `Tags.`. # @return [String] # # @!attribute [rw] value # The value for the tag that you're using to filter the search # results. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/VisibilityConditions AWS API Documentation # class VisibilityConditions < Struct.new( :key, :value) SENSITIVE = [] include Aws::Structure end # Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker # jobs, hosted models, and compute resources have access to. You can # control access to and from your resources by configuring a VPC. For # more information, see [Give SageMaker Access to Resources in your # Amazon VPC][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.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] # # @!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] # # @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] # # @!attribute [rw] subnets # The ID of the subnets in the VPC that you want to connect. # @return [Array] # # @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] # # @!attribute [rw] subnets # The ID of the subnets in the VPC that you want to connect. # @return [Array] # # @!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 # The workspace settings for the SageMaker Canvas application. # # @!attribute [rw] s3_artifact_path # The Amazon S3 bucket used to store artifacts generated by Canvas. # Updating the Amazon S3 location impacts existing configuration # settings, and Canvas users no longer have access to their artifacts. # Canvas users must log out and log back in to apply the new location. # @return [String] # # @!attribute [rw] s3_kms_key_id # The Amazon Web Services Key Management Service (KMS) encryption key # ID that is used to encrypt artifacts generated by Canvas in the # Amazon S3 bucket. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/WorkspaceSettings AWS API Documentation # class WorkspaceSettings < Struct.new( :s3_artifact_path, :s3_kms_key_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] # # @!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] # # @!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