# 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. # # @note When making an API call, you may pass ActionSource # data as a hash: # # { # source_uri: "String2048", # required # source_type: "String256", # source_id: "String256", # } # # @!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 # @note When making an API call, you may pass AddAssociationRequest # data as a hash: # # { # source_arn: "AssociationEntityArn", # required # destination_arn: "AssociationEntityArn", # required # association_type: "ContributedTo", # accepts ContributedTo, AssociatedWith, DerivedFrom, Produced # } # # @!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 # @note When making an API call, you may pass AddTagsInput # data as a hash: # # { # resource_arn: "ResourceArn", # required # tags: [ # required # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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 Amazon 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 # 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 # This API is not supported. # # @note When making an API call, you may pass Alarm # data as a hash: # # { # alarm_name: "AlarmName", # } # # @!attribute [rw] alarm_name # @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 # request. # # For more information about algorithms provided by Amazon SageMaker, # see [Algorithms][1]. For information about using 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 # # @note When making an API call, you may pass AlgorithmSpecification # data as a hash: # # { # training_image: "AlgorithmImage", # algorithm_name: "ArnOrName", # training_input_mode: "Pipe", # required, accepts Pipe, File # metric_definitions: [ # { # name: "MetricName", # required # regex: "MetricRegex", # required # }, # ], # enable_sage_maker_metrics_time_series: false, # } # # @!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]. Amazon 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] 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 # AWS Marketplace. If you specify a value for this parameter, you # can't specify a value for `TrainingImage`. # @return [String] # # @!attribute [rw] training_input_mode # The input mode that the algorithm supports. For the input modes that # Amazon SageMaker algorithms support, see [Algorithms][1]. If an # algorithm supports the `File` input mode, Amazon SageMaker downloads # the training data from S3 to the provisioned ML storage Volume, and # mounts the directory to docker volume for training container. If an # algorithm supports the `Pipe` input mode, Amazon SageMaker streams # data directly from S3 to the container. # # In File mode, make sure you provision ML storage volume with # sufficient capacity to accommodate the data download from S3. In # addition to the training data, the ML storage volume also stores the # output model. The algorithm container use ML storage volume to also # store intermediate information, if any. # # For distributed algorithms using File mode, training data is # distributed uniformly, and your training duration is predictable if # the input data objects size is approximately same. Amazon 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 where one host in a training cluster is # overloaded, thus becoming bottleneck in training. # # # # [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. # Amazon 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 Amazon SageMaker built-in algorithms # # * You use one of the following [Prebuilt Amazon SageMaker Docker # Images][1]\: # # * Tensorflow (version >= 1.15) # # * MXNet (version >= 1.6) # # * PyTorch (version >= 1.3) # # * You specify at least one MetricDefinition # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/pre-built-containers-frameworks-deep-learning.html # @return [Boolean] # # @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) 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 Amazon SageMaker # runs to validate your algorithm. # # The data provided in the validation profile is made available to your # buyers on AWS Marketplace. # # @note When making an API call, you may pass AlgorithmValidationProfile # data as a hash: # # { # profile_name: "EntityName", # required # training_job_definition: { # required # training_input_mode: "Pipe", # required, accepts Pipe, File # hyper_parameters: { # "HyperParameterKey" => "HyperParameterValue", # }, # input_data_config: [ # required # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # }, # ], # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # resource_config: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # }, # transform_job_definition: { # max_concurrent_transforms: 1, # max_payload_in_mb: 1, # batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord # environment: { # "TransformEnvironmentKey" => "TransformEnvironmentValue", # }, # transform_input: { # required # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # }, # transform_output: { # required # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # }, # transform_resources: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # } # # @!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 Amazon SageMaker runs to validate your algorithm. # @return [Types::TrainingJobDefinition] # # @!attribute [rw] transform_job_definition # The `TransformJobDefinition` object that describes the transform job # that Amazon 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 Amazon # SageMaker runs to test the algorithm. # # @note When making an API call, you may pass AlgorithmValidationSpecification # data as a hash: # # { # validation_role: "RoleArn", # required # validation_profiles: [ # required # { # profile_name: "EntityName", # required # training_job_definition: { # required # training_input_mode: "Pipe", # required, accepts Pipe, File # hyper_parameters: { # "HyperParameterKey" => "HyperParameterValue", # }, # input_data_config: [ # required # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # }, # ], # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # resource_config: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # }, # transform_job_definition: { # max_concurrent_transforms: 1, # max_payload_in_mb: 1, # batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord # environment: { # "TransformEnvironmentKey" => "TransformEnvironmentValue", # }, # transform_input: { # required # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # }, # transform_output: { # required # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # }, # transform_resources: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # }, # ], # } # # @!attribute [rw] validation_role # The IAM roles that Amazon 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 Amazon # 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. # # @note When making an API call, you may pass AnnotationConsolidationConfig # data as a hash: # # { # annotation_consolidation_lambda_arn: "LambdaFunctionArn", # required # } # # @!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. # # * `rn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClass` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClass` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClass` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClass` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClass` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClass` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClass` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClass` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClass` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClass` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClass` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClass` # # **Multi-label text classification** - Uses a variant of the # Expectation Maximization approach to estimate the true classes of # text based on annotations from individual workers. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-TextMultiClassMultiLabel` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-TextMultiClassMultiLabel` # # **Named entity recognition** - Groups similar selections and # calculates aggregate boundaries, resolving to most-assigned label. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-NamedEntityRecognition` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-NamedEntityRecognition` # # **Video Classification** - Use this task type when you need workers # to classify videos using predefined labels that you specify. Workers # are shown videos and are asked to choose one label for each video. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoMultiClass` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoMultiClass` # # **Video Frame Object Detection** - Use this task type to have # workers identify and locate objects in a sequence of video frames # (images extracted from a video) using bounding boxes. For example, # you can use this task to ask workers to identify and localize # various objects in a series of video frames, such as cars, bikes, # and pedestrians. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectDetection` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectDetection` # # **Video Frame Object Tracking** - Use this task type to have workers # track the movement of objects in a sequence of video frames (images # extracted from a video) using bounding boxes. For example, you can # use this task to ask workers to track the movement of objects, such # as cars, bikes, and pedestrians. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VideoObjectTracking` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VideoObjectTracking` # # **3D Point Cloud Object Detection** - Use this task type when you # want workers to classify objects in a 3D point cloud by drawing 3D # cuboids around objects. For example, you can use this task type to # ask workers to identify different types of objects in a point cloud, # such as cars, bikes, and pedestrians. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectDetection` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectDetection` # # **3D Point Cloud Object Tracking** - Use this task type when you # want workers to draw 3D cuboids around objects that appear in a # sequence of 3D point cloud frames. For example, you can use this # task type to ask workers to track the movement of vehicles across # multiple point cloud frames. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudObjectTracking` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudObjectTracking` # # **3D Point Cloud Semantic Segmentation** - Use this task type when # you want workers to create a point-level semantic segmentation masks # by painting objects in a 3D point cloud using different colors where # each color is assigned to one of the classes you specify. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-3DPointCloudSemanticSegmentation` # # **Use the following ARNs for Label Verification and Adjustment # Jobs** # # Use label verification and adjustment jobs to review and adjust # labels. To learn more, see [Verify and Adjust Labels ][4]. # # **Semantic Segmentation Adjustment** - Treats each pixel in an image # as a multi-class classification and treats pixel adjusted # annotations from workers as "votes" for the correct label. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentSemanticSegmentation` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentSemanticSegmentation` # # **Semantic Segmentation Verification** - Uses a variant of the # Expectation Maximization approach to estimate the true class of # verification judgment for semantic segmentation labels based on # annotations from individual workers. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationSemanticSegmentation` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationSemanticSegmentation` # # **Bounding Box Adjustment** - Finds the most similar boxes from # different workers based on the Jaccard index of the adjusted # annotations. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentBoundingBox` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentBoundingBox` # # **Bounding Box Verification** - Uses a variant of the Expectation # Maximization approach to estimate the true class of verification # judgement for bounding box labels based on annotations from # individual workers. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-VerificationBoundingBox` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-VerificationBoundingBox` # # **Video Frame Object Detection Adjustment** - Use this task type # when you want workers to adjust bounding boxes that workers have # added to video frames to classify and localize objects in a sequence # of video frames. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectDetection` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectDetection` # # **Video Frame Object Tracking Adjustment** - Use this task type when # you want workers to adjust bounding boxes that workers have added to # video frames to track object movement across a sequence of video # frames. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-AdjustmentVideoObjectTracking` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-AdjustmentVideoObjectTracking` # # **3D Point Cloud Object Detection Adjustment** - Use this task type # when you want workers to adjust 3D cuboids around objects in a 3D # point cloud. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectDetection` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectDetection` # # **3D Point Cloud Object Tracking Adjustment** - Use this task type # when you want workers to adjust 3D cuboids around objects that # appear in a sequence of 3D point cloud frames. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudObjectTracking` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudObjectTracking` # # **3D Point Cloud Semantic Segmentation Adjustment** - Use this task # type when you want workers to adjust a point-level semantic # segmentation masks using a paint tool. # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:us-east-1:432418664414:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:us-east-2:266458841044:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:us-west-2:081040173940:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:eu-west-1:568282634449:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-northeast-1:477331159723:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-southeast-2:454466003867:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-south-1:565803892007:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:eu-central-1:203001061592:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-northeast-2:845288260483:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:eu-west-2:487402164563:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ap-southeast-1:377565633583:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # * `arn:aws:lambda:ca-central-1:918755190332:function:ACS-Adjustment3DPointCloudSemanticSegmentation` # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-annotation-consolidation.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-task-types.html # [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates-step3.html#sms-custom-templates-step3-postlambda # [4]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-verification-data.html # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AnnotationConsolidationConfig AWS API Documentation # class AnnotationConsolidationConfig < Struct.new( :annotation_consolidation_lambda_arn) SENSITIVE = [] include Aws::Structure end # Details about an Amazon SageMaker app. # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] user_profile_name # The user profile name. # @return [String] # # @!attribute [rw] app_type # The type of app. # @return [String] # # @!attribute [rw] app_name # The name of the app. # @return [String] # # @!attribute [rw] status # The status. # @return [String] # # @!attribute [rw] creation_time # The creation time. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AppDetails AWS API Documentation # class AppDetails < Struct.new( :domain_id, :user_profile_name, :app_type, :app_name, :status, :creation_time) SENSITIVE = [] include Aws::Structure end # The configuration for running a SageMaker image as a KernelGateway # app. # # @!attribute [rw] app_image_config_arn # The Amazon Resource Name (ARN) of the AppImageConfig. # @return [String] # # @!attribute [rw] app_image_config_name # The name of the AppImageConfig. Must be unique to your account. # @return [String] # # @!attribute [rw] creation_time # When the AppImageConfig was created. # @return [Time] # # @!attribute [rw] last_modified_time # When the AppImageConfig was last modified. # @return [Time] # # @!attribute [rw] kernel_gateway_image_config # The configuration for the file system and kernels in the SageMaker # image. # @return [Types::KernelGatewayImageConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AppImageConfigDetails AWS API Documentation # class AppImageConfigDetails < Struct.new( :app_image_config_arn, :app_image_config_name, :creation_time, :last_modified_time, :kernel_gateway_image_config) SENSITIVE = [] include Aws::Structure end # Configuration to run a processing job in a specified container image. # # @note When making an API call, you may pass AppSpecification # data as a hash: # # { # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # } # # @!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. # # @note When making an API call, you may pass ArtifactSource # data as a hash: # # { # source_uri: "String2048", # required # source_types: [ # { # source_id_type: "MD5Hash", # required, accepts MD5Hash, S3ETag, S3Version, Custom # value: "String256", # required # }, # ], # } # # @!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. # # @note When making an API call, you may pass ArtifactSourceType # data as a hash: # # { # source_id_type: "MD5Hash", # required, accepts MD5Hash, S3ETag, S3Version, Custom # value: "String256", # required # } # # @!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 # @note When making an API call, you may pass AssociateTrialComponentRequest # data as a hash: # # { # trial_component_name: "ExperimentEntityName", # required # trial_name: "ExperimentEntityName", # required # } # # @!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 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, or trial component. # @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 # Configuration for Athena Dataset Definition input. # # @note When making an API call, you may pass AthenaDatasetDefinition # data as a hash: # # { # catalog: "AthenaCatalog", # required # database: "AthenaDatabase", # required # query_string: "AthenaQueryString", # required # work_group: "AthenaWorkGroup", # output_s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # output_format: "PARQUET", # required, accepts PARQUET, ORC, AVRO, JSON, TEXTFILE # output_compression: "GZIP", # accepts GZIP, SNAPPY, ZLIB # } # # @!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 AWS Key Management Service (AWS 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 # An Autopilot job returns recommendations, or candidates. Each # candidate has futher details about the steps involved and the status. # # @!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 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 AutoML candidate's properties. # @return [Types::CandidateProperties] # # @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) 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. For more information, see . # # @note When making an API call, you may pass AutoMLChannel # data as a hash: # # { # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix # s3_uri: "S3Uri", # required # }, # }, # compression_type: "None", # accepts None, Gzip # target_attribute_name: "TargetAttributeName", # required # } # # @!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] # # @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) 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 . # # @!attribute [rw] image # The ECR path of the container. For more information, see . # @return [String] # # @!attribute [rw] model_data_url # The location of the model artifacts. For more information, see . # @return [String] # # @!attribute [rw] environment # The environment variables to set in the container. For more # information, see . # @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. # # @note When making an API call, you may pass AutoMLDataSource # data as a hash: # # { # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix # s3_uri: "S3Uri", # required # }, # } # # @!attribute [rw] s3_data_source # The Amazon S3 location of the input data. # # The input data must be in CSV format and contain at least 500 rows. # # # @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 # 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 # How long a job is allowed to run, or how many candidates a job is # allowed to generate. # # @note When making an API call, you may pass AutoMLJobCompletionCriteria # data as a hash: # # { # max_candidates: 1, # max_runtime_per_training_job_in_seconds: 1, # max_auto_ml_job_runtime_in_seconds: 1, # } # # @!attribute [rw] max_candidates # The maximum number of times a training job is allowed to run. # @return [Integer] # # @!attribute [rw] max_runtime_per_training_job_in_seconds # The maximum time, in seconds, a training job is allowed to run as # part of an AutoML job. # @return [Integer] # # @!attribute [rw] max_auto_ml_job_runtime_in_seconds # The maximum runtime, in seconds, an AutoML job has to complete. # @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. # # @note When making an API call, you may pass AutoMLJobConfig # data as a hash: # # { # completion_criteria: { # max_candidates: 1, # max_runtime_per_training_job_in_seconds: 1, # max_auto_ml_job_runtime_in_seconds: 1, # }, # security_config: { # volume_kms_key_id: "KmsKeyId", # enable_inter_container_traffic_encryption: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # } # # @!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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobConfig AWS API Documentation # class AutoMLJobConfig < Struct.new( :completion_criteria, :security_config) SENSITIVE = [] include Aws::Structure end # Specifies a metric to minimize or maximize as the objective of a job. # # @note When making an API call, you may pass AutoMLJobObjective # data as a hash: # # { # metric_name: "Accuracy", # required, accepts Accuracy, MSE, F1, F1macro, AUC # } # # @!attribute [rw] metric_name # The name of the objective metric used to measure the predictive # quality of a machine learning system. This metric is optimized # during training to provide the best estimate for model parameter # values from data. # # Here are the options: # # * `MSE`\: The mean squared error (MSE) is the average of the squared # differences between the predicted and actual values. It is used # for regression. MSE values are always positive: the better a model # is at predicting the actual values, the smaller the MSE value. # When the data contains outliers, they tend to dominate the MSE, # which might cause subpar prediction performance. # # * `Accuracy`\: The ratio of the number of correctly classified items # to the total number of (correctly and incorrectly) classified # items. It is used for binary and multiclass classification. It # measures how close the predicted class values are to the actual # values. Accuracy values vary between zero and one: one indicates # perfect accuracy and zero indicates perfect inaccuracy. # # * `F1`\: The F1 score is the harmonic mean of the precision and # recall. It is used for binary classification into classes # traditionally referred to as positive and negative. Predictions # are said to be true when they match their actual (correct) class # and false when they do not. Precision is the ratio of the true # positive predictions to all positive predictions (including the # false positives) in a data set and measures the quality of the # prediction when it predicts the positive class. Recall (or # sensitivity) is the ratio of the true positive predictions to all # actual positive instances and measures how completely a model # predicts the actual class members in a data set. The standard F1 # score weighs precision and recall equally. But which metric is # paramount typically depends on specific aspects of a problem. F1 # scores vary between zero and one: one indicates the best possible # performance and zero the worst. # # * `AUC`\: The area under the curve (AUC) metric is used to compare # and evaluate binary classification by algorithms such as logistic # regression that return probabilities. A threshold is needed to map # the probabilities into classifications. The relevant curve is the # receiver operating characteristic curve that plots the true # positive rate (TPR) of predictions (or recall) against the false # positive rate (FPR) as a function of the threshold value, above # which a prediction is considered positive. Increasing the # threshold results in fewer false positives but more false # negatives. AUC is the area under this receiver operating # characteristic curve and so provides an aggregated measure of the # model performance across all possible classification thresholds. # The AUC score can also be interpreted as the probability that a # randomly selected positive data point is more likely to be # predicted positive than a randomly selected negative example. AUC # scores vary between zero and one: a score of one indicates perfect # accuracy and a score of one half indicates that the prediction is # not better than a random classifier. Values under one half predict # less accurately than a random predictor. But such consistently bad # predictors can simply be inverted to obtain better than random # predictors. # # * `F1macro`\: The F1macro score applies F1 scoring to multiclass # classification. In this context, you have multiple classes to # predict. You just calculate the precision and recall for each # class as you did for the positive class in binary classification. # Then, use these values to calculate the F1 score for each class # and average them to obtain the F1macro score. F1macro scores vary # between zero and one: one indicates the best possible performance # and zero the worst. # # If you do not specify a metric explicitly, the default behavior is # to automatically use: # # * `MSE`\: for regression. # # * `F1`\: for binary classification # # * `Accuracy`\: for multiclass classification. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLJobObjective AWS API Documentation # class AutoMLJobObjective < Struct.new( :metric_name) SENSITIVE = [] include Aws::Structure end # Provides a summary about an AutoML job. # # @!attribute [rw] auto_ml_job_name # The name of the AutoML 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. # # @note When making an API call, you may pass AutoMLOutputDataConfig # data as a hash: # # { # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # } # # @!attribute [rw] kms_key_id # The AWS KMS encryption key ID. # @return [String] # # @!attribute [rw] s3_output_path # The Amazon S3 output path. Must be 128 characters or less. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLOutputDataConfig AWS API Documentation # class AutoMLOutputDataConfig < Struct.new( :kms_key_id, :s3_output_path) SENSITIVE = [] include Aws::Structure end # The reason for a partial failure of an AutoML job. # # @!attribute [rw] partial_failure_message # The message containing the reason for a partial failure of an AutoML # job. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/AutoMLPartialFailureReason AWS API Documentation # class AutoMLPartialFailureReason < Struct.new( :partial_failure_message) SENSITIVE = [] include Aws::Structure end # The Amazon S3 data source. # # @note When making an API call, you may pass AutoMLS3DataSource # data as a hash: # # { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix # s3_uri: "S3Uri", # required # } # # @!attribute [rw] s3_data_type # The data type. # @return [String] # # @!attribute [rw] s3_uri # The URL to the Amazon S3 data source. # @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. # # @note When making an API call, you may pass AutoMLSecurityConfig # data as a hash: # # { # volume_kms_key_id: "KmsKeyId", # enable_inter_container_traffic_encryption: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # } # # @!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 # Currently, the `AutoRollbackConfig` API is not supported. # # @note When making an API call, you may pass AutoRollbackConfig # data as a hash: # # { # alarms: [ # { # alarm_name: "AlarmName", # }, # ], # } # # @!attribute [rw] alarms # @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 # Contains bias metrics for a model. # # @note When making an API call, you may pass Bias # data as a hash: # # { # report: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # } # # @!attribute [rw] report # The 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) SENSITIVE = [] include Aws::Structure end # Currently, the `BlueGreenUpdatePolicy` API is not supported. # # @note When making an API call, you may pass BlueGreenUpdatePolicy # data as a hash: # # { # traffic_routing_configuration: { # required # type: "ALL_AT_ONCE", # required, accepts ALL_AT_ONCE, CANARY # wait_interval_in_seconds: 1, # required # canary_size: { # type: "INSTANCE_COUNT", # required, accepts INSTANCE_COUNT, CAPACITY_PERCENT # value: 1, # required # }, # }, # termination_wait_in_seconds: 1, # maximum_execution_timeout_in_seconds: 1, # } # # @!attribute [rw] traffic_routing_configuration # @return [Types::TrafficRoutingConfig] # # @!attribute [rw] termination_wait_in_seconds # @return [Integer] # # @!attribute [rw] maximum_execution_timeout_in_seconds # @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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CandidateArtifactLocations AWS API Documentation # class CandidateArtifactLocations < Struct.new( :explainability) 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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CandidateProperties AWS API Documentation # class CandidateProperties < Struct.new( :candidate_artifact_locations) SENSITIVE = [] include Aws::Structure end # Currently, the `CapacitySize` API is not supported. # # @note When making an API call, you may pass CapacitySize # data as a hash: # # { # type: "INSTANCE_COUNT", # required, accepts INSTANCE_COUNT, CAPACITY_PERCENT # value: 1, # required # } # # @!attribute [rw] type # This API is not supported. # @return [String] # # @!attribute [rw] value # @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 # @note When making an API call, you may pass CaptureContentTypeHeader # data as a hash: # # { # csv_content_types: ["CsvContentType"], # json_content_types: ["JsonContentType"], # } # # @!attribute [rw] csv_content_types # @return [Array] # # @!attribute [rw] json_content_types # @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 # @note When making an API call, you may pass CaptureOption # data as a hash: # # { # capture_mode: "Input", # required, accepts Input, Output # } # # @!attribute [rw] capture_mode # @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 # A list of categorical hyperparameters to tune. # # @note When making an API call, you may pass CategoricalParameterRange # data as a hash: # # { # name: "ParameterKey", # required # values: ["ParameterValue"], # required # } # # @!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. # # @note When making an API call, you may pass CategoricalParameterRangeSpecification # data as a hash: # # { # values: ["ParameterValue"], # required # } # # @!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. # # @note When making an API call, you may pass Channel # data as a hash: # # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # } # # @!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, # Amazon 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`, Amazon SageMaker # uses the value set for `TrainingInputMode`. Use this parameter to # override the `TrainingInputMode` setting in a AlgorithmSpecification # 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. # @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. # # @note When making an API call, you may pass ChannelSpecification # data as a hash: # # { # name: "ChannelName", # required # description: "EntityDescription", # is_required: false, # supported_content_types: ["ContentType"], # required # supported_compression_types: ["None"], # accepts None, Gzip # supported_input_modes: ["Pipe"], # required, accepts Pipe, File # } # # @!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. # # @note When making an API call, you may pass CheckpointConfig # data as a hash: # # { # s3_uri: "S3Uri", # required # local_path: "DirectoryPath", # } # # @!attribute [rw] s3_uri # Identifies the S3 path where you want Amazon 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 # 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 AWS 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 # # @note When making an API call, you may pass CognitoConfig # data as a hash: # # { # user_pool: "CognitoUserPool", # required # client_id: "ClientId", # required # } # # @!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. # # @note When making an API call, you may pass CognitoMemberDefinition # data as a hash: # # { # user_pool: "CognitoUserPool", # required # user_group: "CognitoUserGroup", # required # client_id: "ClientId", # required # } # # @!attribute [rw] user_pool # An identifier for a user pool. The user pool must be in the same # region as the service that you are calling. # @return [String] # # @!attribute [rw] user_group # An identifier for a user group. # @return [String] # # @!attribute [rw] client_id # An identifier for an application client. You must create the app # client ID using Amazon Cognito. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CognitoMemberDefinition AWS API Documentation # class CognitoMemberDefinition < Struct.new( :user_pool, :user_group, :client_id) SENSITIVE = [] include Aws::Structure end # Configuration information for the Debugger output tensor collections. # # @note When making an API call, you may pass CollectionConfiguration # data as a hash: # # { # collection_name: "CollectionName", # collection_parameters: { # "ConfigKey" => "ConfigValue", # }, # } # # @!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 # Describes the container, as part of model definition. # # @note When making an API call, you may pass ContainerDefinition # data as a hash: # # { # container_hostname: "ContainerHostname", # image: "ContainerImage", # image_config: { # repository_access_mode: "Platform", # required, accepts Platform, Vpc # repository_auth_config: { # repository_credentials_provider_arn: "RepositoryCredentialsProviderArn", # required # }, # }, # mode: "SingleModel", # accepts SingleModel, MultiModel # model_data_url: "Url", # environment: { # "EnvironmentKey" => "EnvironmentValue", # }, # model_package_name: "VersionedArnOrName", # multi_model_config: { # model_cache_setting: "Enabled", # accepts Enabled, Disabled # }, # } # # @!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 Amazon SageMaker, the inference code must meet Amazon # SageMaker requirements. Amazon 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_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] # # # # [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 # Amazon 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, Amazon SageMaker uses AWS # Security Token Service to download model artifacts from the S3 path # you provide. AWS STS is activated in your IAM user account by # default. If you previously deactivated AWS STS for a region, you # need to reactivate AWS STS for that region. For more information, # see [Activating and Deactivating AWS STS in an AWS Region][2] in the # *AWS Identity and Access Management User Guide*. # # If you use a built-in algorithm to create a model, Amazon SageMaker # requires that you provide a S3 path to the model artifacts in # `ModelDataUrl`. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-algo-docker-registry-paths.html # [2]: https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html # @return [String] # # @!attribute [rw] environment # The environment variables to set in the Docker container. Each key # and value in the `Environment` string to string map can have length # of up to 1024. We support up to 16 entries in the map. # @return [Hash] # # @!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] multi_model_config # Specifies additional configuration for multi-model endpoints. # @return [Types::MultiModelConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ContainerDefinition AWS API Documentation # class ContainerDefinition < Struct.new( :container_hostname, :image, :image_config, :mode, :model_data_url, :environment, :model_package_name, :multi_model_config) SENSITIVE = [] include Aws::Structure end # A structure describing the source of a context. # # @note When making an API call, you may pass ContextSource # data as a hash: # # { # source_uri: "String2048", # required # source_type: "String256", # source_id: "String256", # } # # @!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. # # @note When making an API call, you may pass ContinuousParameterRange # data as a hash: # # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # } # # @!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 # # : Amazon 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. # # @note When making an API call, you may pass ContinuousParameterRangeSpecification # data as a hash: # # { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # } # # @!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 # @note When making an API call, you may pass CreateActionRequest # data as a hash: # # { # action_name: "ExperimentEntityName", # required # source: { # required # source_uri: "String2048", # required # source_type: "String256", # source_id: "String256", # }, # action_type: "String256", # required # description: "ExperimentDescription", # status: "Unknown", # accepts Unknown, InProgress, Completed, Failed, Stopping, Stopped # properties: { # "StringParameterValue" => "StringParameterValue", # }, # metadata_properties: { # commit_id: "MetadataPropertyValue", # repository: "MetadataPropertyValue", # generated_by: "MetadataPropertyValue", # project_id: "MetadataPropertyValue", # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] action_name # The name of the action. Must be unique to your account in an AWS # 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 # @note When making an API call, you may pass CreateAlgorithmInput # data as a hash: # # { # algorithm_name: "EntityName", # required # algorithm_description: "EntityDescription", # training_specification: { # required # training_image: "ContainerImage", # required # training_image_digest: "ImageDigest", # supported_hyper_parameters: [ # { # name: "ParameterName", # required # description: "EntityDescription", # type: "Integer", # required, accepts Integer, Continuous, Categorical, FreeText # range: { # integer_parameter_range_specification: { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # }, # continuous_parameter_range_specification: { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # }, # categorical_parameter_range_specification: { # values: ["ParameterValue"], # required # }, # }, # is_tunable: false, # is_required: false, # default_value: "HyperParameterValue", # }, # ], # supported_training_instance_types: ["ml.m4.xlarge"], # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # supports_distributed_training: false, # metric_definitions: [ # { # name: "MetricName", # required # regex: "MetricRegex", # required # }, # ], # training_channels: [ # required # { # name: "ChannelName", # required # description: "EntityDescription", # is_required: false, # supported_content_types: ["ContentType"], # required # supported_compression_types: ["None"], # accepts None, Gzip # supported_input_modes: ["Pipe"], # required, accepts Pipe, File # }, # ], # supported_tuning_job_objective_metrics: [ # { # type: "Maximize", # required, accepts Maximize, Minimize # metric_name: "MetricName", # required # }, # ], # }, # inference_specification: { # containers: [ # required # { # container_hostname: "ContainerHostname", # image: "ContainerImage", # required # image_digest: "ImageDigest", # model_data_url: "Url", # product_id: "ProductId", # }, # ], # supported_transform_instance_types: ["ml.m4.xlarge"], # accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # supported_realtime_inference_instance_types: ["ml.t2.medium"], # accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.m5d.large, ml.m5d.xlarge, ml.m5d.2xlarge, ml.m5d.4xlarge, ml.m5d.12xlarge, ml.m5d.24xlarge, ml.c4.large, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.large, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.12xlarge, ml.r5.24xlarge, ml.r5d.large, ml.r5d.xlarge, ml.r5d.2xlarge, ml.r5d.4xlarge, ml.r5d.12xlarge, ml.r5d.24xlarge, ml.inf1.xlarge, ml.inf1.2xlarge, ml.inf1.6xlarge, ml.inf1.24xlarge # supported_content_types: ["ContentType"], # required # supported_response_mime_types: ["ResponseMIMEType"], # required # }, # validation_specification: { # validation_role: "RoleArn", # required # validation_profiles: [ # required # { # profile_name: "EntityName", # required # training_job_definition: { # required # training_input_mode: "Pipe", # required, accepts Pipe, File # hyper_parameters: { # "HyperParameterKey" => "HyperParameterValue", # }, # input_data_config: [ # required # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # }, # ], # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # resource_config: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # }, # transform_job_definition: { # max_concurrent_transforms: 1, # max_payload_in_mb: 1, # batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord # environment: { # "TransformEnvironmentKey" => "TransformEnvironmentValue", # }, # transform_input: { # required # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # }, # transform_output: { # required # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # }, # transform_resources: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # }, # ], # }, # certify_for_marketplace: false, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 # Amazon SageMaker runs to test the algorithm's training code and, # optionally, one or more batch transform jobs that Amazon 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 AWS # Marketplace. # @return [Boolean] # # @!attribute [rw] tags # An array of key-value pairs. You can use tags to categorize your AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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 # @note When making an API call, you may pass CreateAppImageConfigRequest # data as a hash: # # { # app_image_config_name: "AppImageConfigName", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # kernel_gateway_image_config: { # kernel_specs: [ # required # { # name: "KernelName", # required # display_name: "KernelDisplayName", # }, # ], # file_system_config: { # mount_path: "MountPath", # default_uid: 1, # default_gid: 1, # }, # }, # } # # @!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. # @return [Types::KernelGatewayImageConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAppImageConfigRequest AWS API Documentation # class CreateAppImageConfigRequest < Struct.new( :app_image_config_name, :tags, :kernel_gateway_image_config) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] app_image_config_arn # The Amazon Resource Name (ARN) of the AppImageConfig. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateAppImageConfigResponse AWS API Documentation # class CreateAppImageConfigResponse < Struct.new( :app_image_config_arn) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass CreateAppRequest # data as a hash: # # { # domain_id: "DomainId", # required # user_profile_name: "UserProfileName", # required # app_type: "JupyterServer", # required, accepts JupyterServer, KernelGateway, TensorBoard # app_name: "AppName", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # } # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] user_profile_name # The user profile name. # @return [String] # # @!attribute [rw] app_type # The type of app. Supported apps are `JupyterServer` and # `KernelGateway`. `TensorBoard` is not supported. # @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. # @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, :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 # @note When making an API call, you may pass CreateArtifactRequest # data as a hash: # # { # artifact_name: "ExperimentEntityName", # source: { # required # source_uri: "String2048", # required # source_types: [ # { # source_id_type: "MD5Hash", # required, accepts MD5Hash, S3ETag, S3Version, Custom # value: "String256", # required # }, # ], # }, # artifact_type: "String256", # required # properties: { # "StringParameterValue" => "StringParameterValue", # }, # metadata_properties: { # commit_id: "MetadataPropertyValue", # repository: "MetadataPropertyValue", # generated_by: "MetadataPropertyValue", # project_id: "MetadataPropertyValue", # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] artifact_name # The name of the artifact. Must be unique to your account in an AWS # 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 # @note When making an API call, you may pass CreateAutoMLJobRequest # data as a hash: # # { # auto_ml_job_name: "AutoMLJobName", # required # input_data_config: [ # required # { # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix # s3_uri: "S3Uri", # required # }, # }, # compression_type: "None", # accepts None, Gzip # target_attribute_name: "TargetAttributeName", # required # }, # ], # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # problem_type: "BinaryClassification", # accepts BinaryClassification, MulticlassClassification, Regression # auto_ml_job_objective: { # metric_name: "Accuracy", # required, accepts Accuracy, MSE, F1, F1macro, AUC # }, # auto_ml_job_config: { # completion_criteria: { # max_candidates: 1, # max_runtime_per_training_job_in_seconds: 1, # max_auto_ml_job_runtime_in_seconds: 1, # }, # security_config: { # volume_kms_key_id: "KmsKeyId", # enable_inter_container_traffic_encryption: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # }, # role_arn: "RoleArn", # required # generate_candidate_definitions_only: false, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # model_deploy_config: { # auto_generate_endpoint_name: false, # endpoint_name: "EndpointName", # }, # } # # @!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 . Format(s) supported: CSV. Minimum # of 500 rows. # @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 available for the # candidates. Options include: `BinaryClassification`, # `MulticlassClassification`, and `Regression`. For more information, # see [ Amazon SageMaker Autopilot problem types and algorithm # support][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/autopilot-automate-model-development-problem-types.html # @return [String] # # @!attribute [rw] auto_ml_job_objective # Defines the objective metric used to measure the predictive quality # of an AutoML job. You provide an AutoMLJobObjective$MetricName and # Autopilot infers whether to minimize or maximize it. # @return [Types::AutoMLJobObjective] # # @!attribute [rw] auto_ml_job_config # Contains `CompletionCriteria` and `SecurityConfig` settings for the # 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 # Each tag consists of a key and an optional value. Tag keys must be # unique per resource. # @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 that is 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 # @note When making an API call, you may pass CreateCodeRepositoryInput # data as a hash: # # { # code_repository_name: "EntityName", # required # git_config: { # required # repository_url: "GitConfigUrl", # required # branch: "Branch", # secret_arn: "SecretArn", # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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 # @note When making an API call, you may pass CreateCompilationJobRequest # data as a hash: # # { # compilation_job_name: "EntityName", # required # role_arn: "RoleArn", # required # input_config: { # required # s3_uri: "S3Uri", # required # data_input_config: "DataInputConfig", # required # framework: "TENSORFLOW", # required, accepts TENSORFLOW, KERAS, MXNET, ONNX, PYTORCH, XGBOOST, TFLITE, DARKNET, SKLEARN # framework_version: "FrameworkVersion", # }, # output_config: { # required # s3_output_location: "S3Uri", # required # target_device: "lambda", # accepts lambda, ml_m4, ml_m5, ml_c4, ml_c5, ml_p2, ml_p3, ml_g4dn, ml_inf1, ml_eia2, jetson_tx1, jetson_tx2, jetson_nano, jetson_xavier, rasp3b, imx8qm, deeplens, rk3399, rk3288, aisage, sbe_c, qcs605, qcs603, sitara_am57x, amba_cv22, x86_win32, x86_win64, coreml, jacinto_tda4vm # target_platform: { # os: "ANDROID", # required, accepts ANDROID, LINUX # arch: "X86_64", # required, accepts X86_64, X86, ARM64, ARM_EABI, ARM_EABIHF # accelerator: "INTEL_GRAPHICS", # accepts INTEL_GRAPHICS, MALI, NVIDIA # }, # compiler_options: "CompilerOptions", # kms_key_id: "KmsKeyId", # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] compilation_job_name # A name for the model compilation job. The name must be unique within # the AWS Region and within your AWS 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] 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] 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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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, :input_config, :output_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 # @note When making an API call, you may pass CreateContextRequest # data as a hash: # # { # context_name: "ExperimentEntityName", # required # source: { # required # source_uri: "String2048", # required # source_type: "String256", # source_id: "String256", # }, # context_type: "String256", # required # description: "ExperimentDescription", # properties: { # "StringParameterValue" => "StringParameterValue", # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] context_name # The name of the context. Must be unique to your account in an AWS # 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 # @note When making an API call, you may pass CreateDataQualityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # data_quality_baseline_config: { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # statistics_resource: { # s3_uri: "S3Uri", # }, # }, # data_quality_app_specification: { # required # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # }, # data_quality_job_input: { # required # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # }, # data_quality_job_output_config: { # required # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # }, # job_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 *AWS 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 # @note When making an API call, you may pass CreateDeviceFleetRequest # data as a hash: # # { # device_fleet_name: "EntityName", # required # role_arn: "RoleArn", # description: "DeviceFleetDescription", # output_config: { # required # s3_output_location: "S3Uri", # required # kms_key_id: "KmsKeyId", # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 AWS 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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass CreateDomainRequest # data as a hash: # # { # domain_name: "DomainName", # required # auth_mode: "SSO", # required, accepts SSO, IAM # default_user_settings: { # required # execution_role: "RoleArn", # security_groups: ["SecurityGroupId"], # sharing_settings: { # notebook_output_option: "Allowed", # accepts Allowed, Disabled # s3_output_path: "S3Uri", # s3_kms_key_id: "KmsKeyId", # }, # jupyter_server_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # kernel_gateway_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # custom_images: [ # { # image_name: "ImageName", # required # image_version_number: 1, # app_image_config_name: "AppImageConfigName", # required # }, # ], # }, # tensor_board_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # }, # subnet_ids: ["SubnetId"], # required # vpc_id: "VpcId", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # app_network_access_type: "PublicInternetOnly", # accepts PublicInternetOnly, VpcOnly # home_efs_file_system_kms_key_id: "KmsKeyId", # kms_key_id: "KmsKeyId", # } # # @!attribute [rw] domain_name # A name for the domain. # @return [String] # # @!attribute [rw] auth_mode # The mode of authentication that members use to access the domain. # @return [String] # # @!attribute [rw] default_user_settings # The default settings to use to create a user profile when # `UserSettings` isn't specified in the call to the # `CreateUserProfile` API. # # `SecurityGroups` is aggregated when specified in both calls. For all # other settings in `UserSettings`, the values specified in # `CreateUserProfile` take precedence over those specified in # `CreateDomain`. # @return [Types::UserSettings] # # @!attribute [rw] subnet_ids # The VPC subnets that Studio uses for communication. # @return [Array] # # @!attribute [rw] vpc_id # The ID of the Amazon Virtual Private Cloud (VPC) that Studio uses # for communication. # @return [String] # # @!attribute [rw] tags # Tags to associated with the Domain. Each tag consists of a key and # an optional value. Tag keys must be unique per resource. Tags are # searchable using the `Search` API. # # Tags that you specify for the Domain are also added to all Apps that # the Domain launches. # @return [Array] # # @!attribute [rw] app_network_access_type # Specifies the VPC used for non-EFS traffic. The default value is # `PublicInternetOnly`. # # * `PublicInternetOnly` - Non-EFS traffic is through a VPC managed by # Amazon SageMaker, which allows direct internet access # # * `VpcOnly` - All Studio traffic is through the specified VPC and # subnets # @return [String] # # @!attribute [rw] home_efs_file_system_kms_key_id # This member is deprecated and replaced with `KmsKeyId`. # @return [String] # # @!attribute [rw] kms_key_id # SageMaker uses AWS KMS to encrypt the EFS volume attached to the # domain with an AWS managed customer master key (CMK) by default. For # more control, specify a customer managed CMK. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateDomainRequest AWS API Documentation # class CreateDomainRequest < Struct.new( :domain_name, :auth_mode, :default_user_settings, :subnet_ids, :vpc_id, :tags, :app_network_access_type, :home_efs_file_system_kms_key_id, :kms_key_id) 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 # @note When making an API call, you may pass CreateEdgePackagingJobRequest # data as a hash: # # { # edge_packaging_job_name: "EntityName", # required # compilation_job_name: "EntityName", # required # model_name: "EntityName", # required # model_version: "EdgeVersion", # required # role_arn: "RoleArn", # required # output_config: { # required # s3_output_location: "S3Uri", # required # kms_key_id: "KmsKeyId", # }, # resource_key: "KmsKeyId", # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 CMK 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 # @note When making an API call, you may pass CreateEndpointConfigInput # data as a hash: # # { # endpoint_config_name: "EndpointConfigName", # required # production_variants: [ # required # { # variant_name: "VariantName", # required # model_name: "ModelName", # required # initial_instance_count: 1, # required # instance_type: "ml.t2.medium", # required, accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.m5d.large, ml.m5d.xlarge, ml.m5d.2xlarge, ml.m5d.4xlarge, ml.m5d.12xlarge, ml.m5d.24xlarge, ml.c4.large, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.large, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.12xlarge, ml.r5.24xlarge, ml.r5d.large, ml.r5d.xlarge, ml.r5d.2xlarge, ml.r5d.4xlarge, ml.r5d.12xlarge, ml.r5d.24xlarge, ml.inf1.xlarge, ml.inf1.2xlarge, ml.inf1.6xlarge, ml.inf1.24xlarge # initial_variant_weight: 1.0, # accelerator_type: "ml.eia1.medium", # accepts ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge # core_dump_config: { # destination_s3_uri: "DestinationS3Uri", # required # kms_key_id: "KmsKeyId", # }, # }, # ], # data_capture_config: { # enable_capture: false, # initial_sampling_percentage: 1, # required # destination_s3_uri: "DestinationS3Uri", # required # kms_key_id: "KmsKeyId", # capture_options: [ # required # { # capture_mode: "Input", # required, accepts Input, Output # }, # ], # capture_content_type_header: { # csv_content_types: ["CsvContentType"], # json_content_types: ["JsonContentType"], # }, # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # kms_key_id: "KmsKeyId", # } # # @!attribute [rw] endpoint_config_name # The name of the endpoint configuration. You specify this name in a # CreateEndpoint request. # @return [String] # # @!attribute [rw] production_variants # An list of `ProductionVariant` objects, one for each model that you # want to host at this endpoint. # @return [Array] # # @!attribute [rw] data_capture_config # @return [Types::DataCaptureConfig] # # @!attribute [rw] tags # An array of key-value pairs. You can use tags to categorize your AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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 AWS Key Management Service key # that Amazon 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 AWS Key Management Service section[ # Using Key Policies in AWS 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] # # @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) 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 # @note When making an API call, you may pass CreateEndpointInput # data as a hash: # # { # endpoint_name: "EndpointName", # required # endpoint_config_name: "EndpointConfigName", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] endpoint_name # The name of the endpoint.The name must be unique within an AWS # Region in your AWS account. The name is case-insensitive in # `CreateEndpoint`, but the case is preserved and must be matched in . # @return [String] # # @!attribute [rw] endpoint_config_name # The name of an endpoint configuration. For more information, see # CreateEndpointConfig. # @return [String] # # @!attribute [rw] tags # An array of key-value pairs. You can use tags to categorize your AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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, :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 # @note When making an API call, you may pass CreateExperimentRequest # data as a hash: # # { # experiment_name: "ExperimentEntityName", # required # display_name: "ExperimentEntityName", # description: "ExperimentDescription", # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] experiment_name # The name of the experiment. The name must be unique in your AWS # 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 # API to search on the tags. # @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 # @note When making an API call, you may pass CreateFeatureGroupRequest # data as a hash: # # { # feature_group_name: "FeatureGroupName", # required # record_identifier_feature_name: "FeatureName", # required # event_time_feature_name: "FeatureName", # required # feature_definitions: [ # required # { # feature_name: "FeatureName", # feature_type: "Integral", # accepts Integral, Fractional, String # }, # ], # online_store_config: { # security_config: { # kms_key_id: "KmsKeyId", # }, # enable_online_store: false, # }, # offline_store_config: { # s3_storage_config: { # required # s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # resolved_output_s3_uri: "S3Uri", # }, # disable_glue_table_creation: false, # data_catalog_config: { # table_name: "TableName", # required # catalog: "Catalog", # required # database: "Database", # required # }, # }, # role_arn: "RoleArn", # description: "Description", # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] feature_group_name # The name of the `FeatureGroup`. The name must be unique within an # AWS Region in an AWS 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`; the default # value is `False`. # # You can also include an AWS KMS key ID (`KMSKeyId`) for at-rest # encryption of the `OnlineStore`. # @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 AWS Glue or AWS Hive data cataolgue. # # * An KMS encryption key to encrypt the Amazon S3 location used for # `OfflineStore`. # # To learn more about this parameter, see OfflineStoreConfig. # @return [Types::OfflineStoreConfig] # # @!attribute [rw] role_arn # The Amazon Resource Name (ARN) of the IAM execution role used to # persist data into the `OfflineStore` if an `OfflineStoreConfig` is # provided. # @return [String] # # @!attribute [rw] description # A free-form description of a `FeatureGroup`. # @return [String] # # @!attribute [rw] tags # Tags used to identify `Features` in each `FeatureGroup`. # @return [Array] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFeatureGroupRequest AWS API Documentation # class CreateFeatureGroupRequest < Struct.new( :feature_group_name, :record_identifier_feature_name, :event_time_feature_name, :feature_definitions, :online_store_config, :offline_store_config, :role_arn, :description, :tags) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] feature_group_arn # The Amazon Resource Name (ARN) of the `FeatureGroup`. This is a # unique identifier for the feature group. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateFeatureGroupResponse AWS API Documentation # class CreateFeatureGroupResponse < Struct.new( :feature_group_arn) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass CreateFlowDefinitionRequest # data as a hash: # # { # flow_definition_name: "FlowDefinitionName", # required # human_loop_request_source: { # aws_managed_human_loop_request_source: "AWS/Rekognition/DetectModerationLabels/Image/V3", # required, accepts AWS/Rekognition/DetectModerationLabels/Image/V3, AWS/Textract/AnalyzeDocument/Forms/V1 # }, # human_loop_activation_config: { # human_loop_activation_conditions_config: { # required # human_loop_activation_conditions: "HumanLoopActivationConditions", # required # }, # }, # human_loop_config: { # required # workteam_arn: "WorkteamArn", # required # human_task_ui_arn: "HumanTaskUiArn", # required # task_title: "FlowDefinitionTaskTitle", # required # task_description: "FlowDefinitionTaskDescription", # required # task_count: 1, # required # task_availability_lifetime_in_seconds: 1, # task_time_limit_in_seconds: 1, # task_keywords: ["FlowDefinitionTaskKeyword"], # public_workforce_task_price: { # amount_in_usd: { # dollars: 1, # cents: 1, # tenth_fractions_of_a_cent: 1, # }, # }, # }, # output_config: { # required # s3_output_path: "S3Uri", # required # kms_key_id: "KmsKeyId", # }, # role_arn: "RoleArn", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 # @note When making an API call, you may pass CreateHumanTaskUiRequest # data as a hash: # # { # human_task_ui_name: "HumanTaskUiName", # required # ui_template: { # required # content: "TemplateContent", # required # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 # @note When making an API call, you may pass CreateHyperParameterTuningJobRequest # data as a hash: # # { # hyper_parameter_tuning_job_name: "HyperParameterTuningJobName", # required # hyper_parameter_tuning_job_config: { # required # strategy: "Bayesian", # required, accepts Bayesian, Random # hyper_parameter_tuning_job_objective: { # type: "Maximize", # required, accepts Maximize, Minimize # metric_name: "MetricName", # required # }, # resource_limits: { # required # max_number_of_training_jobs: 1, # required # max_parallel_training_jobs: 1, # required # }, # parameter_ranges: { # integer_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # continuous_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # categorical_parameter_ranges: [ # { # name: "ParameterKey", # required # values: ["ParameterValue"], # required # }, # ], # }, # training_job_early_stopping_type: "Off", # accepts Off, Auto # tuning_job_completion_criteria: { # target_objective_metric_value: 1.0, # required # }, # }, # training_job_definition: { # definition_name: "HyperParameterTrainingJobDefinitionName", # tuning_objective: { # type: "Maximize", # required, accepts Maximize, Minimize # metric_name: "MetricName", # required # }, # hyper_parameter_ranges: { # integer_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # continuous_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # categorical_parameter_ranges: [ # { # name: "ParameterKey", # required # values: ["ParameterValue"], # required # }, # ], # }, # static_hyper_parameters: { # "HyperParameterKey" => "HyperParameterValue", # }, # algorithm_specification: { # required # training_image: "AlgorithmImage", # training_input_mode: "Pipe", # required, accepts Pipe, File # algorithm_name: "ArnOrName", # metric_definitions: [ # { # name: "MetricName", # required # regex: "MetricRegex", # required # }, # ], # }, # role_arn: "RoleArn", # required # input_data_config: [ # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # }, # ], # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # resource_config: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # enable_network_isolation: false, # enable_inter_container_traffic_encryption: false, # enable_managed_spot_training: false, # checkpoint_config: { # s3_uri: "S3Uri", # required # local_path: "DirectoryPath", # }, # retry_strategy: { # maximum_retry_attempts: 1, # required # }, # }, # training_job_definitions: [ # { # definition_name: "HyperParameterTrainingJobDefinitionName", # tuning_objective: { # type: "Maximize", # required, accepts Maximize, Minimize # metric_name: "MetricName", # required # }, # hyper_parameter_ranges: { # integer_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # continuous_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # categorical_parameter_ranges: [ # { # name: "ParameterKey", # required # values: ["ParameterValue"], # required # }, # ], # }, # static_hyper_parameters: { # "HyperParameterKey" => "HyperParameterValue", # }, # algorithm_specification: { # required # training_image: "AlgorithmImage", # training_input_mode: "Pipe", # required, accepts Pipe, File # algorithm_name: "ArnOrName", # metric_definitions: [ # { # name: "MetricName", # required # regex: "MetricRegex", # required # }, # ], # }, # role_arn: "RoleArn", # required # input_data_config: [ # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # }, # ], # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # resource_config: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # enable_network_isolation: false, # enable_inter_container_traffic_encryption: false, # enable_managed_spot_training: false, # checkpoint_config: { # s3_uri: "S3Uri", # required # local_path: "DirectoryPath", # }, # retry_strategy: { # maximum_retry_attempts: 1, # required # }, # }, # ], # warm_start_config: { # parent_hyper_parameter_tuning_jobs: [ # required # { # hyper_parameter_tuning_job_name: "HyperParameterTuningJobName", # }, # ], # warm_start_type: "IdenticalDataAndAlgorithm", # required, accepts IdenticalDataAndAlgorithm, TransferLearning # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 AWS account and AWS 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 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][1]. # # # # [1]: 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 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. # @return [Types::HyperParameterTrainingJobDefinition] # # @!attribute [rw] training_job_definitions # A list of the HyperParameterTrainingJobDefinition objects launched # for this tuning job. # @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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateHyperParameterTuningJobRequest AWS API Documentation # class CreateHyperParameterTuningJobRequest < Struct.new( :hyper_parameter_tuning_job_name, :hyper_parameter_tuning_job_config, :training_job_definition, :training_job_definitions, :warm_start_config, :tags) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] hyper_parameter_tuning_job_arn # The Amazon Resource Name (ARN) of the tuning job. Amazon 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 # @note When making an API call, you may pass CreateImageRequest # data as a hash: # # { # description: "ImageDescription", # display_name: "ImageDisplayName", # image_name: "ImageName", # required # role_arn: "RoleArn", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 Amazon Resource Name (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 Amazon Resource Name (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 # @note When making an API call, you may pass CreateImageVersionRequest # data as a hash: # # { # base_image: "ImageBaseImage", # required # client_token: "ClientToken", # required # image_name: "ImageName", # required # } # # @!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 Container Registry # (ECR) URI in the following format: # # `.dkr.ecr..amazonaws.com/` # @return [String] # # @!attribute [rw] client_token # A unique ID. If not specified, the AWS CLI and AWS 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] # # @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) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] image_version_arn # The Amazon Resource Name (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 # @note When making an API call, you may pass CreateLabelingJobRequest # data as a hash: # # { # labeling_job_name: "LabelingJobName", # required # label_attribute_name: "LabelAttributeName", # required # input_config: { # required # data_source: { # required # s3_data_source: { # manifest_s3_uri: "S3Uri", # required # }, # sns_data_source: { # sns_topic_arn: "SnsTopicArn", # required # }, # }, # data_attributes: { # content_classifiers: ["FreeOfPersonallyIdentifiableInformation"], # accepts FreeOfPersonallyIdentifiableInformation, FreeOfAdultContent # }, # }, # output_config: { # required # s3_output_path: "S3Uri", # required # kms_key_id: "KmsKeyId", # sns_topic_arn: "SnsTopicArn", # }, # role_arn: "RoleArn", # required # label_category_config_s3_uri: "S3Uri", # stopping_conditions: { # max_human_labeled_object_count: 1, # max_percentage_of_input_dataset_labeled: 1, # }, # labeling_job_algorithms_config: { # labeling_job_algorithm_specification_arn: "LabelingJobAlgorithmSpecificationArn", # required # initial_active_learning_model_arn: "ModelArn", # labeling_job_resource_config: { # volume_kms_key_id: "KmsKeyId", # }, # }, # human_task_config: { # required # workteam_arn: "WorkteamArn", # required # ui_config: { # required # ui_template_s3_uri: "S3Uri", # human_task_ui_arn: "HumanTaskUiArn", # }, # pre_human_task_lambda_arn: "LambdaFunctionArn", # required # task_keywords: ["TaskKeyword"], # task_title: "TaskTitle", # required # task_description: "TaskDescription", # required # number_of_human_workers_per_data_object: 1, # required # task_time_limit_in_seconds: 1, # required # task_availability_lifetime_in_seconds: 1, # max_concurrent_task_count: 1, # annotation_consolidation_config: { # required # annotation_consolidation_lambda_arn: "LambdaFunctionArn", # required # }, # public_workforce_task_price: { # amount_in_usd: { # dollars: 1, # cents: 1, # tenth_fractions_of_a_cent: 1, # }, # }, # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 AWS 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 AWS 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 all other [built-in task types][2] and [custom tasks][3], 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` ][4] 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-task-types.html # [3]: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-custom-templates.html # [4]: 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 *AWS 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 # @note When making an API call, you may pass CreateModelBiasJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # model_bias_baseline_config: { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # }, # model_bias_app_specification: { # required # image_uri: "ImageUri", # required # config_uri: "S3Uri", # required # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # }, # model_bias_job_input: { # required # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # ground_truth_s3_input: { # required # s3_uri: "MonitoringS3Uri", # }, # }, # model_bias_job_output_config: { # required # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # }, # job_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] job_definition_name # The name of the bias job definition. The name must be unique within # an AWS Region in the AWS 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 *AWS 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 # @note When making an API call, you may pass CreateModelExplainabilityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # model_explainability_baseline_config: { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # }, # model_explainability_app_specification: { # required # image_uri: "ImageUri", # required # config_uri: "S3Uri", # required # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # }, # model_explainability_job_input: { # required # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # }, # model_explainability_job_output_config: { # required # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # }, # job_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] job_definition_name # The name of the model explainability job definition. The name must # be unique within an AWS Region in the AWS 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 *AWS 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 # @note When making an API call, you may pass CreateModelInput # data as a hash: # # { # model_name: "ModelName", # required # primary_container: { # container_hostname: "ContainerHostname", # image: "ContainerImage", # image_config: { # repository_access_mode: "Platform", # required, accepts Platform, Vpc # repository_auth_config: { # repository_credentials_provider_arn: "RepositoryCredentialsProviderArn", # required # }, # }, # mode: "SingleModel", # accepts SingleModel, MultiModel # model_data_url: "Url", # environment: { # "EnvironmentKey" => "EnvironmentValue", # }, # model_package_name: "VersionedArnOrName", # multi_model_config: { # model_cache_setting: "Enabled", # accepts Enabled, Disabled # }, # }, # containers: [ # { # container_hostname: "ContainerHostname", # image: "ContainerImage", # image_config: { # repository_access_mode: "Platform", # required, accepts Platform, Vpc # repository_auth_config: { # repository_credentials_provider_arn: "RepositoryCredentialsProviderArn", # required # }, # }, # mode: "SingleModel", # accepts SingleModel, MultiModel # model_data_url: "Url", # environment: { # "EnvironmentKey" => "EnvironmentValue", # }, # model_package_name: "VersionedArnOrName", # multi_model_config: { # model_cache_setting: "Enabled", # accepts Enabled, Disabled # }, # }, # ], # inference_execution_config: { # mode: "Serial", # required, accepts Serial, Direct # }, # execution_role_arn: "RoleArn", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # enable_network_isolation: false, # } # # @!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 Amazon 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 [Amazon SageMaker Roles][1]. # # To be able to pass this role to Amazon 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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS Resources][1]. # # # # [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html # @return [Array] # # @!attribute [rw] vpc_config # A VpcConfig 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][1] and [Protect Data in Batch # Transform Jobs by Using an Amazon Virtual Private Cloud][2]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/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 Amazon 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 # @note When making an API call, you may pass CreateModelPackageGroupInput # data as a hash: # # { # model_package_group_name: "EntityName", # required # model_package_group_description: "EntityDescription", # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 AWS resources][1] in the *AWS 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 # @note When making an API call, you may pass CreateModelPackageInput # data as a hash: # # { # model_package_name: "EntityName", # model_package_group_name: "EntityName", # model_package_description: "EntityDescription", # inference_specification: { # containers: [ # required # { # container_hostname: "ContainerHostname", # image: "ContainerImage", # required # image_digest: "ImageDigest", # model_data_url: "Url", # product_id: "ProductId", # }, # ], # supported_transform_instance_types: ["ml.m4.xlarge"], # accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # supported_realtime_inference_instance_types: ["ml.t2.medium"], # accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.m5d.large, ml.m5d.xlarge, ml.m5d.2xlarge, ml.m5d.4xlarge, ml.m5d.12xlarge, ml.m5d.24xlarge, ml.c4.large, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.large, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.12xlarge, ml.r5.24xlarge, ml.r5d.large, ml.r5d.xlarge, ml.r5d.2xlarge, ml.r5d.4xlarge, ml.r5d.12xlarge, ml.r5d.24xlarge, ml.inf1.xlarge, ml.inf1.2xlarge, ml.inf1.6xlarge, ml.inf1.24xlarge # supported_content_types: ["ContentType"], # required # supported_response_mime_types: ["ResponseMIMEType"], # required # }, # validation_specification: { # validation_role: "RoleArn", # required # validation_profiles: [ # required # { # profile_name: "EntityName", # required # transform_job_definition: { # required # max_concurrent_transforms: 1, # max_payload_in_mb: 1, # batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord # environment: { # "TransformEnvironmentKey" => "TransformEnvironmentValue", # }, # transform_input: { # required # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # }, # transform_output: { # required # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # }, # transform_resources: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # }, # ], # }, # source_algorithm_specification: { # source_algorithms: [ # required # { # model_data_url: "Url", # algorithm_name: "ArnOrName", # required # }, # ], # }, # certify_for_marketplace: false, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # model_approval_status: "Approved", # accepts Approved, Rejected, PendingManualApproval # metadata_properties: { # commit_id: "MetadataPropertyValue", # repository: "MetadataPropertyValue", # generated_by: "MetadataPropertyValue", # project_id: "MetadataPropertyValue", # }, # model_metrics: { # model_quality: { # statistics: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # constraints: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # }, # model_data_quality: { # statistics: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # constraints: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # }, # bias: { # report: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # }, # explainability: { # report: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # }, # }, # client_token: "ClientToken", # } # # @!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 of the model group that this model version belongs to. # # This parameter is required for versioned models, and does not apply # to unversioned models. # @return [String] # # @!attribute [rw] model_package_description # A description of the model package. # @return [String] # # @!attribute [rw] inference_specification # Specifies details about inference jobs that can be run with models # based on this model package, including the following: # # * The Amazon ECR paths of containers that contain the inference code # and model artifacts. # # * The instance types that the model package supports for transform # jobs and real-time endpoints used for inference. # # * The input and output content formats that the model package # supports for inference. # @return [Types::InferenceSpecification] # # @!attribute [rw] validation_specification # Specifies configurations for one or more transform jobs that Amazon # 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 AWS 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 AWS resources][1] in the *AWS General # Reference Guide*. # # # # [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] # # @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) 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 # @note When making an API call, you may pass CreateModelQualityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # model_quality_baseline_config: { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # }, # model_quality_app_specification: { # required # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # problem_type: "BinaryClassification", # accepts BinaryClassification, MulticlassClassification, Regression # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # }, # model_quality_job_input: { # required # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # ground_truth_s3_input: { # required # s3_uri: "MonitoringS3Uri", # }, # }, # model_quality_job_output_config: { # required # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # }, # job_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 *AWS 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 # @note When making an API call, you may pass CreateMonitoringScheduleRequest # data as a hash: # # { # monitoring_schedule_name: "MonitoringScheduleName", # required # monitoring_schedule_config: { # required # schedule_config: { # schedule_expression: "ScheduleExpression", # required # }, # monitoring_job_definition: { # baseline_config: { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # statistics_resource: { # s3_uri: "S3Uri", # }, # }, # monitoring_inputs: [ # required # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # }, # ], # monitoring_output_config: { # required # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # }, # monitoring_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # monitoring_app_specification: { # required # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # }, # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # }, # monitoring_job_definition_name: "MonitoringJobDefinitionName", # monitoring_type: "DataQuality", # accepts DataQuality, ModelQuality, ModelBias, ModelExplainability # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] monitoring_schedule_name # The name of the monitoring schedule. The name must be unique within # an AWS Region within an AWS 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 *AWS 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 # @note When making an API call, you may pass CreateNotebookInstanceInput # data as a hash: # # { # notebook_instance_name: "NotebookInstanceName", # required # instance_type: "ml.t2.medium", # required, accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge # subnet_id: "SubnetId", # security_group_ids: ["SecurityGroupId"], # role_arn: "RoleArn", # required # kms_key_id: "KmsKeyId", # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # lifecycle_config_name: "NotebookInstanceLifecycleConfigName", # direct_internet_access: "Enabled", # accepts Enabled, Disabled # volume_size_in_gb: 1, # accelerator_types: ["ml.eia1.medium"], # accepts ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge # default_code_repository: "CodeRepositoryNameOrUrl", # additional_code_repositories: ["CodeRepositoryNameOrUrl"], # root_access: "Enabled", # accepts Enabled, Disabled # } # # @!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 AWS resources from the notebook # instance, Amazon SageMaker assumes this role to perform tasks on # your behalf. You must grant this role necessary permissions so # Amazon SageMaker can perform these tasks. The policy must allow the # Amazon SageMaker service principal (sagemaker.amazonaws.com) # permissions to assume this role. For more information, see [Amazon # SageMaker Roles][1]. # # To be able to pass this role to Amazon 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 AWS Key Management Service key # that Amazon 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 *AWS 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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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 Amazon 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 Amazon 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 [AWS 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 Amazon 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 [AWS 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 Amazon 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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass CreateNotebookInstanceLifecycleConfigInput # data as a hash: # # { # notebook_instance_lifecycle_config_name: "NotebookInstanceLifecycleConfigName", # required # on_create: [ # { # content: "NotebookInstanceLifecycleConfigContent", # }, # ], # on_start: [ # { # content: "NotebookInstanceLifecycleConfigContent", # }, # ], # } # # @!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 # @note When making an API call, you may pass CreatePipelineRequest # data as a hash: # # { # pipeline_name: "PipelineName", # required # pipeline_display_name: "PipelineName", # pipeline_definition: "PipelineDefinition", # required # pipeline_description: "PipelineDescription", # client_request_token: "IdempotencyToken", # required # role_arn: "RoleArn", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] pipeline_name # The name of the pipeline. # @return [String] # # @!attribute [rw] pipeline_display_name # The display name of the pipeline. # @return [String] # # @!attribute [rw] pipeline_definition # The JSON pipeline definition of the pipeline. # @return [String] # # @!attribute [rw] pipeline_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] # # @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_description, :client_request_token, :role_arn, :tags) 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 # @note When making an API call, you may pass CreatePresignedDomainUrlRequest # data as a hash: # # { # domain_id: "DomainId", # required # user_profile_name: "UserProfileName", # required # session_expiration_duration_in_seconds: 1, # expires_in_seconds: 1, # } # # @!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] # # @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) 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 # @note When making an API call, you may pass CreatePresignedNotebookInstanceUrlInput # data as a hash: # # { # notebook_instance_name: "NotebookInstanceName", # required # session_expiration_duration_in_seconds: 1, # } # # @!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 # @note When making an API call, you may pass CreateProcessingJobRequest # data as a hash: # # { # processing_inputs: [ # { # input_name: "String", # required # app_managed: false, # s3_input: { # s3_uri: "S3Uri", # required # local_path: "ProcessingLocalPath", # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # s3_compression_type: "None", # accepts None, Gzip # }, # dataset_definition: { # athena_dataset_definition: { # catalog: "AthenaCatalog", # required # database: "AthenaDatabase", # required # query_string: "AthenaQueryString", # required # work_group: "AthenaWorkGroup", # output_s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # output_format: "PARQUET", # required, accepts PARQUET, ORC, AVRO, JSON, TEXTFILE # output_compression: "GZIP", # accepts GZIP, SNAPPY, ZLIB # }, # redshift_dataset_definition: { # cluster_id: "RedshiftClusterId", # required # database: "RedshiftDatabase", # required # db_user: "RedshiftUserName", # required # query_string: "RedshiftQueryString", # required # cluster_role_arn: "RoleArn", # required # output_s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # output_format: "PARQUET", # required, accepts PARQUET, CSV # output_compression: "None", # accepts None, GZIP, BZIP2, ZSTD, SNAPPY # }, # local_path: "ProcessingLocalPath", # data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # input_mode: "Pipe", # accepts Pipe, File # }, # }, # ], # processing_output_config: { # outputs: [ # required # { # output_name: "String", # required # s3_output: { # s3_uri: "S3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # required, accepts Continuous, EndOfJob # }, # feature_store_output: { # feature_group_name: "FeatureGroupName", # required # }, # app_managed: false, # }, # ], # kms_key_id: "KmsKeyId", # }, # processing_job_name: "ProcessingJobName", # required # processing_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # app_specification: { # required # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # }, # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # experiment_config: { # experiment_name: "ExperimentEntityName", # trial_name: "ExperimentEntityName", # trial_component_display_name: "ExperimentEntityName", # }, # } # # @!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 # AWS Region in the AWS 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 *AWS 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 # # * CreateTrainingJob # # * CreateTransformJob # @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 # @note When making an API call, you may pass CreateProjectInput # data as a hash: # # { # project_name: "ProjectEntityName", # required # project_description: "EntityDescription", # service_catalog_provisioning_details: { # required # product_id: "ServiceCatalogEntityId", # required # provisioning_artifact_id: "ServiceCatalogEntityId", # required # path_id: "ServiceCatalogEntityId", # provisioning_parameters: [ # { # key: "ProvisioningParameterKey", # value: "ProvisioningParameterValue", # }, # ], # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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. For information, see [What is AWS 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 AWS resource costs. For more information, see [Tagging # AWS resources][1] in the *AWS 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 # @note When making an API call, you may pass CreateTrainingJobRequest # data as a hash: # # { # training_job_name: "TrainingJobName", # required # hyper_parameters: { # "HyperParameterKey" => "HyperParameterValue", # }, # algorithm_specification: { # required # training_image: "AlgorithmImage", # algorithm_name: "ArnOrName", # training_input_mode: "Pipe", # required, accepts Pipe, File # metric_definitions: [ # { # name: "MetricName", # required # regex: "MetricRegex", # required # }, # ], # enable_sage_maker_metrics_time_series: false, # }, # role_arn: "RoleArn", # required # input_data_config: [ # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # }, # ], # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # resource_config: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # enable_network_isolation: false, # enable_inter_container_traffic_encryption: false, # enable_managed_spot_training: false, # checkpoint_config: { # s3_uri: "S3Uri", # required # local_path: "DirectoryPath", # }, # debug_hook_config: { # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # required # hook_parameters: { # "ConfigKey" => "ConfigValue", # }, # collection_configurations: [ # { # collection_name: "CollectionName", # collection_parameters: { # "ConfigKey" => "ConfigValue", # }, # }, # ], # }, # debug_rule_configurations: [ # { # rule_configuration_name: "RuleConfigurationName", # required # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # rule_evaluator_image: "AlgorithmImage", # required # instance_type: "ml.t3.medium", # accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # rule_parameters: { # "ConfigKey" => "ConfigValue", # }, # }, # ], # tensor_board_output_config: { # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # required # }, # experiment_config: { # experiment_name: "ExperimentEntityName", # trial_name: "ExperimentEntityName", # trial_component_display_name: "ExperimentEntityName", # }, # profiler_config: { # s3_output_path: "S3Uri", # required # profiling_interval_in_milliseconds: 1, # profiling_parameters: { # "ConfigKey" => "ConfigValue", # }, # }, # profiler_rule_configurations: [ # { # rule_configuration_name: "RuleConfigurationName", # required # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # rule_evaluator_image: "AlgorithmImage", # required # instance_type: "ml.t3.medium", # accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # rule_parameters: { # "ConfigKey" => "ConfigValue", # }, # }, # ], # environment: { # "TrainingEnvironmentKey" => "TrainingEnvironmentValue", # }, # retry_strategy: { # maximum_retry_attempts: 1, # required # }, # } # # @!attribute [rw] training_job_name # The name of the training job. The name must be unique within an AWS # Region in an AWS 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 Amazon 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`. # # # # [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 Amazon 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 Amazon SageMaker # can assume to perform tasks on your behalf. # # During model training, Amazon 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 [Amazon SageMaker Roles][1]. # # To be able to pass this role to Amazon 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, Amazon # 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 will be made available as input streams. They do not need # to be downloaded. # @return [Array] # # @!attribute [rw] output_data_config # Specifies the path to the S3 location where you want to store model # artifacts. Amazon 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 Amazon 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 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][1]. # # # # [1]: 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, Amazon SageMaker ends the training # job. Use this API to cap model training costs. # # To stop a job, Amazon 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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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, Amazon 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 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 Debugger rules for debugging output # tensors. # @return [Array] # # @!attribute [rw] tensor_board_output_config # Configuration of storage locations for the 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 # # * CreateTrainingJob # # * CreateTransformJob # @return [Types::ExperimentConfig] # # @!attribute [rw] profiler_config # Configuration information for Debugger system monitoring, framework # profiling, and storage paths. # @return [Types::ProfilerConfig] # # @!attribute [rw] profiler_rule_configurations # Configuration information for 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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrainingJobRequest AWS API Documentation # class CreateTrainingJobRequest < Struct.new( :training_job_name, :hyper_parameters, :algorithm_specification, :role_arn, :input_data_config, :output_data_config, :resource_config, :vpc_config, :stopping_condition, :tags, :enable_network_isolation, :enable_inter_container_traffic_encryption, :enable_managed_spot_training, :checkpoint_config, :debug_hook_config, :debug_rule_configurations, :tensor_board_output_config, :experiment_config, :profiler_config, :profiler_rule_configurations, :environment, :retry_strategy) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] training_job_arn # The Amazon Resource Name (ARN) of the training job. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/CreateTrainingJobResponse AWS API Documentation # class CreateTrainingJobResponse < Struct.new( :training_job_arn) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass CreateTransformJobRequest # data as a hash: # # { # transform_job_name: "TransformJobName", # required # model_name: "ModelName", # required # max_concurrent_transforms: 1, # model_client_config: { # invocations_timeout_in_seconds: 1, # invocations_max_retries: 1, # }, # max_payload_in_mb: 1, # batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord # environment: { # "TransformEnvironmentKey" => "TransformEnvironmentValue", # }, # transform_input: { # required # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # }, # transform_output: { # required # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # }, # transform_resources: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # data_processing: { # input_filter: "JsonPath", # output_filter: "JsonPath", # join_source: "Input", # accepts Input, None # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # experiment_config: { # experiment_name: "ExperimentEntityName", # trial_name: "ExperimentEntityName", # trial_component_display_name: "ExperimentEntityName", # }, # } # # @!attribute [rw] transform_job_name # The name of the transform job. The name must be unique within an AWS # Region in an AWS 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 AWS Region in an AWS 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. # # 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] 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 *AWS 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 # # * CreateTrainingJob # # * CreateTransformJob # @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, :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 # @note When making an API call, you may pass CreateTrialComponentRequest # data as a hash: # # { # trial_component_name: "ExperimentEntityName", # required # display_name: "ExperimentEntityName", # status: { # primary_status: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped # message: "TrialComponentStatusMessage", # }, # start_time: Time.now, # end_time: Time.now, # parameters: { # "TrialComponentKey256" => { # string_value: "StringParameterValue", # number_value: 1.0, # }, # }, # input_artifacts: { # "TrialComponentKey64" => { # media_type: "MediaType", # value: "TrialComponentArtifactValue", # required # }, # }, # output_artifacts: { # "TrialComponentKey64" => { # media_type: "MediaType", # value: "TrialComponentArtifactValue", # required # }, # }, # metadata_properties: { # commit_id: "MetadataPropertyValue", # repository: "MetadataPropertyValue", # generated_by: "MetadataPropertyValue", # project_id: "MetadataPropertyValue", # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] trial_component_name # The name of the component. The name must be unique in your AWS # 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 # API to search on the tags. # @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 # @note When making an API call, you may pass CreateTrialRequest # data as a hash: # # { # trial_name: "ExperimentEntityName", # required # display_name: "ExperimentEntityName", # experiment_name: "ExperimentEntityName", # required # metadata_properties: { # commit_id: "MetadataPropertyValue", # repository: "MetadataPropertyValue", # generated_by: "MetadataPropertyValue", # project_id: "MetadataPropertyValue", # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!attribute [rw] trial_name # The name of the trial. The name must be unique in your AWS 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 API # to search on the tags. # @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 # @note When making an API call, you may pass CreateUserProfileRequest # data as a hash: # # { # domain_id: "DomainId", # required # user_profile_name: "UserProfileName", # required # single_sign_on_user_identifier: "SingleSignOnUserIdentifier", # single_sign_on_user_value: "String256", # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # user_settings: { # execution_role: "RoleArn", # security_groups: ["SecurityGroupId"], # sharing_settings: { # notebook_output_option: "Allowed", # accepts Allowed, Disabled # s3_output_path: "S3Uri", # s3_kms_key_id: "KmsKeyId", # }, # jupyter_server_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # kernel_gateway_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # custom_images: [ # { # image_name: "ImageName", # required # image_version_number: 1, # app_image_config_name: "AppImageConfigName", # required # }, # ], # }, # tensor_board_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # }, # } # # @!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 SSO, this field is # required. If the Domain's AuthMode is not SSO, this field cannot be # specified. # @return [String] # # @!attribute [rw] single_sign_on_user_value # The username of the associated AWS Single Sign-On User for this # UserProfile. If the Domain's AuthMode is SSO, this field is # required, and must match a valid username of a user in your # directory. If the Domain's AuthMode is not SSO, 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 # @note When making an API call, you may pass CreateWorkforceRequest # data as a hash: # # { # cognito_config: { # user_pool: "CognitoUserPool", # required # client_id: "ClientId", # required # }, # oidc_config: { # client_id: "ClientId", # required # client_secret: "ClientSecret", # required # issuer: "OidcEndpoint", # required # authorization_endpoint: "OidcEndpoint", # required # token_endpoint: "OidcEndpoint", # required # user_info_endpoint: "OidcEndpoint", # required # logout_endpoint: "OidcEndpoint", # required # jwks_uri: "OidcEndpoint", # required # }, # source_ip_config: { # cidrs: ["Cidr"], # required # }, # workforce_name: "WorkforceName", # required # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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] # # @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) 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 # @note When making an API call, you may pass CreateWorkteamRequest # data as a hash: # # { # workteam_name: "WorkteamName", # required # workforce_name: "WorkforceName", # member_definitions: [ # required # { # cognito_member_definition: { # user_pool: "CognitoUserPool", # required # user_group: "CognitoUserGroup", # required # client_id: "ClientId", # required # }, # oidc_member_definition: { # groups: ["Group"], # required # }, # }, # ], # description: "String200", # required # notification_configuration: { # notification_topic_arn: "NotificationTopicArn", # }, # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 AWS 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 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 # # @note When making an API call, you may pass CustomImage # data as a hash: # # { # image_name: "ImageName", # required # image_version_number: 1, # app_image_config_name: "AppImageConfigName", # required # } # # @!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 # @note When making an API call, you may pass DataCaptureConfig # data as a hash: # # { # enable_capture: false, # initial_sampling_percentage: 1, # required # destination_s3_uri: "DestinationS3Uri", # required # kms_key_id: "KmsKeyId", # capture_options: [ # required # { # capture_mode: "Input", # required, accepts Input, Output # }, # ], # capture_content_type_header: { # csv_content_types: ["CsvContentType"], # json_content_types: ["JsonContentType"], # }, # } # # @!attribute [rw] enable_capture # @return [Boolean] # # @!attribute [rw] initial_sampling_percentage # @return [Integer] # # @!attribute [rw] destination_s3_uri # @return [String] # # @!attribute [rw] kms_key_id # @return [String] # # @!attribute [rw] capture_options # @return [Array] # # @!attribute [rw] capture_content_type_header # @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 # @!attribute [rw] enable_capture # @return [Boolean] # # @!attribute [rw] capture_status # @return [String] # # @!attribute [rw] current_sampling_percentage # @return [Integer] # # @!attribute [rw] destination_s3_uri # @return [String] # # @!attribute [rw] kms_key_id # @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`. # # @note When making an API call, you may pass DataCatalogConfig # data as a hash: # # { # table_name: "TableName", # required # catalog: "Catalog", # required # database: "Database", # required # } # # @!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 # # @note When making an API call, you may pass DataProcessing # data as a hash: # # { # input_filter: "JsonPath", # output_filter: "JsonPath", # join_source: "Input", # accepts Input, None # } # # @!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 # Amazon SageMaker to pass the entire input dataset to the algorithm, # accept the default value `$`. # # Examples: `"$"`, `"$[1:]"`, `"$.features"` # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html#data-processing-operators # @return [String] # # @!attribute [rw] output_filter # A [JSONPath][1] expression used to select a portion of the joined # dataset to save in the output file for a batch transform job. If you # want Amazon SageMaker to store the entire input dataset in the # output file, leave the default value, `$`. 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, Amazon # 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, Amazon 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, Amazon 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. # # @note When making an API call, you may pass DataQualityAppSpecification # data as a hash: # # { # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # } # # @!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 # flatted json so that the built-in container can use the converted # data. Applicable only for the built-in (first party) containers. # @return [String] # # @!attribute [rw] post_analytics_processor_source_uri # An Amazon S3 URI to a script that is called after analysis has been # performed. Applicable only for the built-in (first party) # containers. # @return [String] # # @!attribute [rw] environment # Sets the environment variables in the container that the monitoring # job runs. # @return [Hash] # # @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. # # @note When making an API call, you may pass DataQualityBaselineConfig # data as a hash: # # { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # statistics_resource: { # s3_uri: "S3Uri", # }, # } # # @!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. # # @note When making an API call, you may pass DataQualityJobInput # data as a hash: # # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # } # # @!attribute [rw] endpoint_input # Input object for the endpoint # @return [Types::EndpointInput] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DataQualityJobInput AWS API Documentation # class DataQualityJobInput < Struct.new( :endpoint_input) SENSITIVE = [] include Aws::Structure end # Describes the location of the channel data. # # @note When making an API call, you may pass DataSource # data as a hash: # # { # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # } # # @!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. # # @note When making an API call, you may pass DatasetDefinition # data as a hash: # # { # athena_dataset_definition: { # catalog: "AthenaCatalog", # required # database: "AthenaDatabase", # required # query_string: "AthenaQueryString", # required # work_group: "AthenaWorkGroup", # output_s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # output_format: "PARQUET", # required, accepts PARQUET, ORC, AVRO, JSON, TEXTFILE # output_compression: "GZIP", # accepts GZIP, SNAPPY, ZLIB # }, # redshift_dataset_definition: { # cluster_id: "RedshiftClusterId", # required # database: "RedshiftDatabase", # required # db_user: "RedshiftUserName", # required # query_string: "RedshiftQueryString", # required # cluster_role_arn: "RoleArn", # required # output_s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # output_format: "PARQUET", # required, accepts PARQUET, CSV # output_compression: "None", # accepts None, GZIP, BZIP2, ZSTD, SNAPPY # }, # local_path: "ProcessingLocalPath", # data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # input_mode: "Pipe", # accepts Pipe, File # } # # @!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 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 # # @note When making an API call, you may pass DebugHookConfig # data as a hash: # # { # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # required # hook_parameters: { # "ConfigKey" => "ConfigValue", # }, # collection_configurations: [ # { # collection_name: "CollectionName", # collection_parameters: { # "ConfigKey" => "ConfigValue", # }, # }, # ], # } # # @!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 Debugger hook parameters. # @return [Hash] # # @!attribute [rw] collection_configurations # Configuration information for 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 # # @note When making an API call, you may pass DebugRuleConfiguration # data as a hash: # # { # rule_configuration_name: "RuleConfigurationName", # required # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # rule_evaluator_image: "AlgorithmImage", # required # instance_type: "ml.t3.medium", # accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # rule_parameters: { # "ConfigKey" => "ConfigValue", # }, # } # # @!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 Debugger 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 # @note When making an API call, you may pass DeleteActionRequest # data as a hash: # # { # action_name: "ExperimentEntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteAlgorithmInput # data as a hash: # # { # algorithm_name: "EntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteAppImageConfigRequest # data as a hash: # # { # app_image_config_name: "AppImageConfigName", # required # } # # @!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 # @note When making an API call, you may pass DeleteAppRequest # data as a hash: # # { # domain_id: "DomainId", # required # user_profile_name: "UserProfileName", # required # app_type: "JupyterServer", # required, accepts JupyterServer, KernelGateway, TensorBoard # app_name: "AppName", # required # } # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] user_profile_name # The user profile name. # @return [String] # # @!attribute [rw] app_type # The type of app. # @return [String] # # @!attribute [rw] app_name # The name of the app. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteAppRequest AWS API Documentation # class DeleteAppRequest < Struct.new( :domain_id, :user_profile_name, :app_type, :app_name) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DeleteArtifactRequest # data as a hash: # # { # artifact_arn: "ArtifactArn", # source: { # source_uri: "String2048", # required # source_types: [ # { # source_id_type: "MD5Hash", # required, accepts MD5Hash, S3ETag, S3Version, Custom # value: "String256", # required # }, # ], # }, # } # # @!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 # @note When making an API call, you may pass DeleteAssociationRequest # data as a hash: # # { # source_arn: "AssociationEntityArn", # required # destination_arn: "AssociationEntityArn", # required # } # # @!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 # @note When making an API call, you may pass DeleteCodeRepositoryInput # data as a hash: # # { # code_repository_name: "EntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteContextRequest # data as a hash: # # { # context_name: "ExperimentEntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteDataQualityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # } # # @!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 # @note When making an API call, you may pass DeleteDeviceFleetRequest # data as a hash: # # { # device_fleet_name: "EntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteDomainRequest # data as a hash: # # { # domain_id: "DomainId", # required # retention_policy: { # home_efs_file_system: "Retain", # accepts Retain, Delete # }, # } # # @!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 # @note When making an API call, you may pass DeleteEndpointConfigInput # data as a hash: # # { # endpoint_config_name: "EndpointConfigName", # required # } # # @!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 # @note When making an API call, you may pass DeleteEndpointInput # data as a hash: # # { # endpoint_name: "EndpointName", # required # } # # @!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 # @note When making an API call, you may pass DeleteExperimentRequest # data as a hash: # # { # experiment_name: "ExperimentEntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteFeatureGroupRequest # data as a hash: # # { # feature_group_name: "FeatureGroupName", # required # } # # @!attribute [rw] feature_group_name # The name of the `FeatureGroup` you want to delete. The name must be # unique within an AWS Region in an AWS 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 # @note When making an API call, you may pass DeleteFlowDefinitionRequest # data as a hash: # # { # flow_definition_name: "FlowDefinitionName", # required # } # # @!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 # @note When making an API call, you may pass DeleteHumanTaskUiRequest # data as a hash: # # { # human_task_ui_name: "HumanTaskUiName", # required # } # # @!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 # @note When making an API call, you may pass DeleteImageRequest # data as a hash: # # { # image_name: "ImageName", # required # } # # @!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 # @note When making an API call, you may pass DeleteImageVersionRequest # data as a hash: # # { # image_name: "ImageName", # required # version: 1, # required # } # # @!attribute [rw] image_name # The name of the image. # @return [String] # # @!attribute [rw] version # The version to delete. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeleteImageVersionRequest AWS API Documentation # class DeleteImageVersionRequest < Struct.new( :image_name, :version) 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 # @note When making an API call, you may pass DeleteModelBiasJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # } # # @!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 # @note When making an API call, you may pass DeleteModelExplainabilityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # } # # @!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 # @note When making an API call, you may pass DeleteModelInput # data as a hash: # # { # model_name: "ModelName", # required # } # # @!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 # @note When making an API call, you may pass DeleteModelPackageGroupInput # data as a hash: # # { # model_package_group_name: "ArnOrName", # required # } # # @!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 # @note When making an API call, you may pass DeleteModelPackageGroupPolicyInput # data as a hash: # # { # model_package_group_name: "EntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteModelPackageInput # data as a hash: # # { # model_package_name: "VersionedArnOrName", # required # } # # @!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 # @note When making an API call, you may pass DeleteModelQualityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # } # # @!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 # @note When making an API call, you may pass DeleteMonitoringScheduleRequest # data as a hash: # # { # monitoring_schedule_name: "MonitoringScheduleName", # required # } # # @!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 # @note When making an API call, you may pass DeleteNotebookInstanceInput # data as a hash: # # { # notebook_instance_name: "NotebookInstanceName", # required # } # # @!attribute [rw] notebook_instance_name # The name of the Amazon 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 # @note When making an API call, you may pass DeleteNotebookInstanceLifecycleConfigInput # data as a hash: # # { # notebook_instance_lifecycle_config_name: "NotebookInstanceLifecycleConfigName", # required # } # # @!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 # @note When making an API call, you may pass DeletePipelineRequest # data as a hash: # # { # pipeline_name: "PipelineName", # required # client_request_token: "IdempotencyToken", # required # } # # @!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 # @note When making an API call, you may pass DeleteProjectInput # data as a hash: # # { # project_name: "ProjectEntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteTagsInput # data as a hash: # # { # resource_arn: "ResourceArn", # required # tag_keys: ["TagKey"], # required # } # # @!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 # @note When making an API call, you may pass DeleteTrialComponentRequest # data as a hash: # # { # trial_component_name: "ExperimentEntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteTrialRequest # data as a hash: # # { # trial_name: "ExperimentEntityName", # required # } # # @!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 # @note When making an API call, you may pass DeleteUserProfileRequest # data as a hash: # # { # domain_id: "DomainId", # required # user_profile_name: "UserProfileName", # required # } # # @!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 # @note When making an API call, you may pass DeleteWorkforceRequest # data as a hash: # # { # workforce_name: "WorkforceName", # required # } # # @!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 # @note When making an API call, you may pass DeleteWorkteamRequest # data as a hash: # # { # workteam_name: "WorkteamName", # required # } # # @!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. # # 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][1] in the *Amazon ECR User # Guide*. # # # # [1]: 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 # Currently, the `DeploymentConfig` API is not supported. # # @note When making an API call, you may pass DeploymentConfig # data as a hash: # # { # blue_green_update_policy: { # required # traffic_routing_configuration: { # required # type: "ALL_AT_ONCE", # required, accepts ALL_AT_ONCE, CANARY # wait_interval_in_seconds: 1, # required # canary_size: { # type: "INSTANCE_COUNT", # required, accepts INSTANCE_COUNT, CAPACITY_PERCENT # value: 1, # required # }, # }, # termination_wait_in_seconds: 1, # maximum_execution_timeout_in_seconds: 1, # }, # auto_rollback_configuration: { # alarms: [ # { # alarm_name: "AlarmName", # }, # ], # }, # } # # @!attribute [rw] blue_green_update_policy # @return [Types::BlueGreenUpdatePolicy] # # @!attribute [rw] auto_rollback_configuration # @return [Types::AutoRollbackConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DeploymentConfig AWS API Documentation # class DeploymentConfig < Struct.new( :blue_green_update_policy, :auto_rollback_configuration) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DeregisterDevicesRequest # data as a hash: # # { # device_fleet_name: "EntityName", # required # device_names: ["DeviceName"], # required # } # # @!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 # @note When making an API call, you may pass DescribeActionRequest # data as a hash: # # { # action_name: "ExperimentEntityName", # required # } # # @!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, or trial component. # @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, or trial component. # @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/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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeAlgorithmInput # data as a hash: # # { # algorithm_name: "ArnOrName", # required # } # # @!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 # Amazon 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 AWS 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 # @note When making an API call, you may pass DescribeAppImageConfigRequest # data as a hash: # # { # app_image_config_name: "AppImageConfigName", # required # } # # @!attribute [rw] app_image_config_name # The name of the AppImageConfig to describe. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAppImageConfigRequest AWS API Documentation # class DescribeAppImageConfigRequest < Struct.new( :app_image_config_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] app_image_config_arn # The Amazon Resource Name (ARN) of the AppImageConfig. # @return [String] # # @!attribute [rw] app_image_config_name # The name of the AppImageConfig. # @return [String] # # @!attribute [rw] creation_time # When the AppImageConfig was created. # @return [Time] # # @!attribute [rw] last_modified_time # When the AppImageConfig was last modified. # @return [Time] # # @!attribute [rw] kernel_gateway_image_config # The configuration of a KernelGateway app. # @return [Types::KernelGatewayImageConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAppImageConfigResponse AWS API Documentation # class DescribeAppImageConfigResponse < Struct.new( :app_image_config_arn, :app_image_config_name, :creation_time, :last_modified_time, :kernel_gateway_image_config) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeAppRequest # data as a hash: # # { # domain_id: "DomainId", # required # user_profile_name: "UserProfileName", # required # app_type: "JupyterServer", # required, accepts JupyterServer, KernelGateway, TensorBoard # app_name: "AppName", # required # } # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] user_profile_name # The user profile name. # @return [String] # # @!attribute [rw] app_type # The type of app. # @return [String] # # @!attribute [rw] app_name # The name of the app. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAppRequest AWS API Documentation # class DescribeAppRequest < Struct.new( :domain_id, :user_profile_name, :app_type, :app_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] app_arn # The Amazon Resource Name (ARN) of the app. # @return [String] # # @!attribute [rw] app_type # The type of app. # @return [String] # # @!attribute [rw] app_name # The name of the app. # @return [String] # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] user_profile_name # The user profile name. # @return [String] # # @!attribute [rw] status # The status. # @return [String] # # @!attribute [rw] last_health_check_timestamp # The timestamp of the last health check. # @return [Time] # # @!attribute [rw] last_user_activity_timestamp # The timestamp of the last user's activity. # @return [Time] # # @!attribute [rw] creation_time # The creation time. # @return [Time] # # @!attribute [rw] failure_reason # The failure reason. # @return [String] # # @!attribute [rw] resource_spec # The instance type and the Amazon Resource Name (ARN) of the # SageMaker image created on the instance. # @return [Types::ResourceSpec] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAppResponse AWS API Documentation # class DescribeAppResponse < Struct.new( :app_arn, :app_type, :app_name, :domain_id, :user_profile_name, :status, :last_health_check_timestamp, :last_user_activity_timestamp, :creation_time, :failure_reason, :resource_spec) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeArtifactRequest # data as a hash: # # { # artifact_arn: "ArtifactArn", # required # } # # @!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, or trial component. # @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, or trial component. # @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/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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeAutoMLJobRequest # data as a hash: # # { # auto_ml_job_name: "AutoMLJobName", # required # } # # @!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 Amazon Resource Name (ARN) of the AWS Identity and Access # Management (IAM) role that has read permission to the input data # location and write permission to the output data location in Amazon # S3. # @return [String] # # @!attribute [rw] auto_ml_job_objective # Returns the job's objective. # @return [Types::AutoMLJobObjective] # # @!attribute [rw] problem_type # Returns the job's problem type. # @return [String] # # @!attribute [rw] auto_ml_job_config # Returns the configuration for the AutoML job. # @return [Types::AutoMLJobConfig] # # @!attribute [rw] creation_time # Returns the creation time of the AutoML job. # @return [Time] # # @!attribute [rw] end_time # Returns the end time of the AutoML job. # @return [Time] # # @!attribute [rw] last_modified_time # Returns the job's last modified time. # @return [Time] # # @!attribute [rw] failure_reason # Returns the failure reason for an AutoML job, when applicable. # @return [String] # # @!attribute [rw] partial_failure_reasons # Returns a list of reasons for partial failures within an AutoML job. # @return [Array] # # @!attribute [rw] best_candidate # Returns the job's best `AutoMLCandidate`. # @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 # This contains `ProblemType`, `AutoMLJobObjective` and # `CompletionCriteria`. If you do not provide these values, they are # auto-inferred. If you do provide them, the values used are the ones # you provide. # @return [Types::ResolvedAttributes] # # @!attribute [rw] model_deploy_config # Indicates whether the model was deployed automatically to an # endpoint and the name of that endpoint if deployed automatically. # @return [Types::ModelDeployConfig] # # @!attribute [rw] model_deploy_result # Provides information about endpoint for the model deployment. # @return [Types::ModelDeployResult] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeAutoMLJobResponse AWS API Documentation # class DescribeAutoMLJobResponse < Struct.new( :auto_ml_job_name, :auto_ml_job_arn, :input_data_config, :output_data_config, :role_arn, :auto_ml_job_objective, :problem_type, :auto_ml_job_config, :creation_time, :end_time, :last_modified_time, :failure_reason, :partial_failure_reasons, :best_candidate, :auto_ml_job_status, :auto_ml_job_secondary_status, :generate_candidate_definitions_only, :auto_ml_job_artifacts, :resolved_attributes, :model_deploy_config, :model_deploy_result) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeCodeRepositoryInput # data as a hash: # # { # code_repository_name: "EntityName", # required # } # # @!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 AWS 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 # @note When making an API call, you may pass DescribeCompilationJobRequest # data as a hash: # # { # compilation_job_name: "EntityName", # required # } # # @!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 DescribeCompilationJobResponse$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] 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] # # @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, :creation_time, :last_modified_time, :failure_reason, :model_artifacts, :model_digests, :role_arn, :input_config, :output_config) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeContextRequest # data as a hash: # # { # context_name: "ExperimentEntityName", # required # } # # @!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, or trial component. # @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, or trial component. # @return [Types::UserContext] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeDataQualityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # } # # @!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 # @note When making an API call, you may pass DescribeDeviceFleetRequest # data as a hash: # # { # device_fleet_name: "EntityName", # required # } # # @!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 AWS Internet of # Things (IoT). # @return [String] # # @!attribute [rw] iot_role_alias # The Amazon Resource Name (ARN) alias created in AWS 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 # @note When making an API call, you may pass DescribeDeviceRequest # data as a hash: # # { # next_token: "NextToken", # device_name: "EntityName", # required # device_fleet_name: "EntityName", # required # } # # @!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 AWS 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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeDomainRequest # data as a hash: # # { # domain_id: "DomainId", # required # } # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDomainRequest AWS API Documentation # class DescribeDomainRequest < Struct.new( :domain_id) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] domain_arn # The domain's Amazon Resource Name (ARN). # @return [String] # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] domain_name # The domain name. # @return [String] # # @!attribute [rw] home_efs_file_system_id # The ID of the Amazon Elastic File System (EFS) managed by this # Domain. # @return [String] # # @!attribute [rw] single_sign_on_managed_application_instance_id # The SSO managed application instance ID. # @return [String] # # @!attribute [rw] status # The status. # @return [String] # # @!attribute [rw] creation_time # The creation time. # @return [Time] # # @!attribute [rw] last_modified_time # The last modified time. # @return [Time] # # @!attribute [rw] failure_reason # The failure reason. # @return [String] # # @!attribute [rw] auth_mode # The domain's authentication mode. # @return [String] # # @!attribute [rw] default_user_settings # Settings which are applied to UserProfiles in this domain if # settings are not explicitly specified in a given UserProfile. # @return [Types::UserSettings] # # @!attribute [rw] app_network_access_type # Specifies the VPC used for non-EFS traffic. The default value is # `PublicInternetOnly`. # # * `PublicInternetOnly` - Non-EFS traffic is through a VPC managed by # Amazon SageMaker, which allows direct internet access # # * `VpcOnly` - All Studio traffic is through the specified VPC and # subnets # @return [String] # # @!attribute [rw] home_efs_file_system_kms_key_id # This member is deprecated and replaced with `KmsKeyId`. # @return [String] # # @!attribute [rw] subnet_ids # The VPC subnets that Studio 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 Studio uses # for communication. # @return [String] # # @!attribute [rw] kms_key_id # The AWS KMS customer managed CMK used to encrypt the EFS volume # attached to the domain. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeDomainResponse AWS API Documentation # class DescribeDomainResponse < Struct.new( :domain_arn, :domain_id, :domain_name, :home_efs_file_system_id, :single_sign_on_managed_application_instance_id, :status, :creation_time, :last_modified_time, :failure_reason, :auth_mode, :default_user_settings, :app_network_access_type, :home_efs_file_system_kms_key_id, :subnet_ids, :url, :vpc_id, :kms_key_id) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeEdgePackagingJobRequest # data as a hash: # # { # edge_packaging_job_name: "EntityName", # required # } # # @!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 CMK 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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeEndpointConfigInput # data as a hash: # # { # endpoint_config_name: "EndpointConfigName", # required # } # # @!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 Amazon 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 # @return [Types::DataCaptureConfig] # # @!attribute [rw] kms_key_id # AWS 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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeEndpointInput # data as a hash: # # { # endpoint_name: "EndpointName", # required # } # # @!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 objects, one for each model # hosted behind this endpoint. # @return [Array] # # @!attribute [rw] data_capture_config # @return [Types::DataCaptureConfigSummary] # # @!attribute [rw] endpoint_status # The status of the endpoint. # # * `OutOfService`\: Endpoint is not available to take incoming # requests. # # * `Creating`\: CreateEndpoint is executing. # # * `Updating`\: UpdateEndpoint or UpdateEndpointWeightsAndCapacities # 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 call or when the # UpdateEndpointWeightsAndCapacities operation is called explicitly. # # * `InService`\: Endpoint is available to process incoming requests. # # * `Deleting`\: DeleteEndpoint is executing. # # * `Failed`\: Endpoint could not be created, updated, or re-scaled. # Use DescribeEndpointOutput$FailureReason for information about the # failure. DeleteEndpoint is the only operation that can be # performed on a failed endpoint. # @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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeExperimentRequest # data as a hash: # # { # experiment_name: "ExperimentEntityName", # required # } # # @!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 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 # @note When making an API call, you may pass DescribeFeatureGroupRequest # data as a hash: # # { # feature_group_name: "FeatureGroupName", # required # next_token: "NextToken", # } # # @!attribute [rw] feature_group_name # The name of the `FeatureGroup` you want described. # @return [String] # # @!attribute [rw] next_token # A token to resume pagination of the list of `Features` # (`FeatureDefinitions`). 2,500 `Features` are returned by default. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeFeatureGroupRequest AWS API Documentation # class DescribeFeatureGroupRequest < Struct.new( :feature_group_name, :next_token) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] feature_group_arn # The Amazon Resource Name (ARN) of the `FeatureGroup`. # @return [String] # # @!attribute [rw] feature_group_name # he name of the `FeatureGroup`. # @return [String] # # @!attribute [rw] record_identifier_feature_name # The name of the `Feature` used for `RecordIdentifier`, whose value # uniquely identifies a record stored in the feature store. # @return [String] # # @!attribute [rw] event_time_feature_name # The name of the feature that stores the `EventTime` of a Record in a # `FeatureGroup`. # # An `EventTime` is a point in time when a new event occurs that # corresponds to the creation or update of a `Record` in a # `FeatureGroup`. All `Records` in the `FeatureGroup` have a # corresponding `EventTime`. # @return [String] # # @!attribute [rw] feature_definitions # A list of the `Features` in the `FeatureGroup`. Each feature is # defined by a `FeatureName` and `FeatureType`. # @return [Array] # # @!attribute [rw] creation_time # A timestamp indicating when SageMaker created the `FeatureGroup`. # @return [Time] # # @!attribute [rw] online_store_config # The configuration for the `OnlineStore`. # @return [Types::OnlineStoreConfig] # # @!attribute [rw] offline_store_config # The configuration of the `OfflineStore`, inducing the S3 location of # the `OfflineStore`, AWS Glue or AWS Hive data catalogue # configurations, and the security configuration. # @return [Types::OfflineStoreConfig] # # @!attribute [rw] role_arn # The Amazon Resource Name (ARN) of the IAM execution role used to # persist data into the `OfflineStore` if an `OfflineStoreConfig` is # provided. # @return [String] # # @!attribute [rw] feature_group_status # The status of the feature group. # @return [String] # # @!attribute [rw] offline_store_status # The status of the `OfflineStore`. Notifies you if replicating data # into the `OfflineStore` has failed. Returns either: `Active` or # `Blocked` # @return [Types::OfflineStoreStatus] # # @!attribute [rw] 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] # # @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, :online_store_config, :offline_store_config, :role_arn, :feature_group_status, :offline_store_status, :failure_reason, :description, :next_token) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeFlowDefinitionRequest # data as a hash: # # { # flow_definition_name: "FlowDefinitionName", # required # } # # @!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 AWS 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 # @note When making an API call, you may pass DescribeHumanTaskUiRequest # data as a hash: # # { # human_task_ui_name: "HumanTaskUiName", # required # } # # @!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 # @note When making an API call, you may pass DescribeHyperParameterTuningJobRequest # data as a hash: # # { # hyper_parameter_tuning_job_name: "HyperParameterTuningJobName", # required # } # # @!attribute [rw] hyper_parameter_tuning_job_name # The name of the tuning job. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHyperParameterTuningJobRequest AWS API Documentation # class DescribeHyperParameterTuningJobRequest < Struct.new( :hyper_parameter_tuning_job_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] hyper_parameter_tuning_job_name # The name of the tuning job. # @return [String] # # @!attribute [rw] hyper_parameter_tuning_job_arn # The Amazon Resource Name (ARN) of the tuning job. # @return [String] # # @!attribute [rw] hyper_parameter_tuning_job_config # The HyperParameterTuningJobConfig object that specifies the # configuration of the tuning job. # @return [Types::HyperParameterTuningJobConfig] # # @!attribute [rw] training_job_definition # The HyperParameterTrainingJobDefinition object that specifies the # definition of the training jobs that this tuning job launches. # @return [Types::HyperParameterTrainingJobDefinition] # # @!attribute [rw] training_job_definitions # A list of the HyperParameterTrainingJobDefinition objects launched # for this tuning job. # @return [Array] # # @!attribute [rw] hyper_parameter_tuning_job_status # The status of the tuning job: InProgress, Completed, Failed, # Stopping, or Stopped. # @return [String] # # @!attribute [rw] creation_time # The date and time that the tuning job started. # @return [Time] # # @!attribute [rw] hyper_parameter_tuning_end_time # The date and time that the tuning job ended. # @return [Time] # # @!attribute [rw] last_modified_time # The date and time that the status of the tuning job was modified. # @return [Time] # # @!attribute [rw] training_job_status_counters # The TrainingJobStatusCounters object that specifies the number of # training jobs, categorized by status, that this tuning job launched. # @return [Types::TrainingJobStatusCounters] # # @!attribute [rw] objective_status_counters # The ObjectiveStatusCounters object that specifies the number of # training jobs, categorized by the status of their final objective # metric, that this tuning job launched. # @return [Types::ObjectiveStatusCounters] # # @!attribute [rw] best_training_job # A TrainingJobSummary object that describes the training job that # completed with the best current HyperParameterTuningJobObjective. # @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 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. # @return [Types::HyperParameterTrainingJobSummary] # # @!attribute [rw] warm_start_config # The configuration for starting the hyperparameter parameter tuning # job using one or more previous tuning jobs as a starting point. The # results of previous tuning jobs are used to inform which # combinations of hyperparameters to search over in the new tuning # job. # @return [Types::HyperParameterTuningJobWarmStartConfig] # # @!attribute [rw] failure_reason # If the tuning job failed, the reason it failed. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeHyperParameterTuningJobResponse AWS API Documentation # class DescribeHyperParameterTuningJobResponse < Struct.new( :hyper_parameter_tuning_job_name, :hyper_parameter_tuning_job_arn, :hyper_parameter_tuning_job_config, :training_job_definition, :training_job_definitions, :hyper_parameter_tuning_job_status, :creation_time, :hyper_parameter_tuning_end_time, :last_modified_time, :training_job_status_counters, :objective_status_counters, :best_training_job, :overall_best_training_job, :warm_start_config, :failure_reason) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeImageRequest # data as a hash: # # { # image_name: "ImageName", # required # } # # @!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 Amazon Resource Name (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 Amazon Resource Name (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 # @note When making an API call, you may pass DescribeImageVersionRequest # data as a hash: # # { # image_name: "ImageName", # required # version: 1, # } # # @!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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeImageVersionRequest AWS API Documentation # class DescribeImageVersionRequest < Struct.new( :image_name, :version) 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 Amazon Resource Name (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/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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeLabelingJobRequest # data as a hash: # # { # labeling_job_name: "LabelingJobName", # required # } # # @!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 AWS 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 Amazon 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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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 # @note When making an API call, you may pass DescribeModelBiasJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # } # # @!attribute [rw] job_definition_name # The name of the model bias job definition. The name must be unique # within an AWS Region in the AWS 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 AWS Region in the AWS 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 AWS Identity and Access # Management (IAM) role that has read permission to the input data # location and write permission to the output data location in Amazon # S3. # @return [String] # # @!attribute [rw] stopping_condition # A time limit for how long the monitoring job is allowed to run # before stopping. # @return [Types::MonitoringStoppingCondition] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelBiasJobDefinitionResponse AWS API Documentation # class DescribeModelBiasJobDefinitionResponse < Struct.new( :job_definition_arn, :job_definition_name, :creation_time, :model_bias_baseline_config, :model_bias_app_specification, :model_bias_job_input, :model_bias_job_output_config, :job_resources, :network_config, :role_arn, :stopping_condition) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeModelExplainabilityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # } # # @!attribute [rw] job_definition_name # The name of the model explainability job definition. The name must # be unique within an AWS Region in the AWS 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 AWS Region in the AWS 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 AWS Identity and Access # Management (IAM) role that has read permission to the input data # location and write permission to the output data location in Amazon # S3. # @return [String] # # @!attribute [rw] stopping_condition # A time limit for how long the monitoring job is allowed to run # before stopping. # @return [Types::MonitoringStoppingCondition] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelExplainabilityJobDefinitionResponse AWS API Documentation # class DescribeModelExplainabilityJobDefinitionResponse < Struct.new( :job_definition_arn, :job_definition_name, :creation_time, :model_explainability_baseline_config, :model_explainability_app_specification, :model_explainability_job_input, :model_explainability_job_output_config, :job_resources, :network_config, :role_arn, :stopping_condition) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeModelInput # data as a hash: # # { # model_name: "ModelName", # required # } # # @!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 Amazon 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 object that specifies the VPC that this model has access # to. For more information, see [Protect Endpoints by Using an Amazon # Virtual Private Cloud][1] # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html # @return [Types::VpcConfig] # # @!attribute [rw] creation_time # A timestamp that shows when the model was created. # @return [Time] # # @!attribute [rw] model_arn # The Amazon Resource Name (ARN) of the model. # @return [String] # # @!attribute [rw] enable_network_isolation # If `True`, no inbound or outbound network calls can be made to or # from the model container. # @return [Boolean] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelOutput AWS API Documentation # class DescribeModelOutput < Struct.new( :model_name, :primary_container, :containers, :inference_execution_config, :execution_role_arn, :vpc_config, :creation_time, :model_arn, :enable_network_isolation) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeModelPackageGroupInput # data as a hash: # # { # model_package_group_name: "ArnOrName", # required # } # # @!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, or trial component. # @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 # @note When making an API call, you may pass DescribeModelPackageInput # data as a hash: # # { # model_package_name: "VersionedArnOrName", # required # } # # @!attribute [rw] model_package_name # The name or Amazon Resource Name (ARN) of the model package to # describe. # # When you specify a name, the name must have 1 to 63 characters. # Valid characters are a-z, A-Z, 0-9, and - (hyphen). # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeModelPackageInput AWS API Documentation # class DescribeModelPackageInput < Struct.new( :model_package_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] model_package_name # The name of the model package being described. # @return [String] # # @!attribute [rw] model_package_group_name # If the model is a versioned model, the name of the model group that # the versioned model belongs to. # @return [String] # # @!attribute [rw] model_package_version # The version of the model package. # @return [Integer] # # @!attribute [rw] model_package_arn # The Amazon Resource Name (ARN) of the model package. # @return [String] # # @!attribute [rw] model_package_description # A brief summary of the model package. # @return [String] # # @!attribute [rw] creation_time # A timestamp specifying when the model package was created. # @return [Time] # # @!attribute [rw] inference_specification # Details about inference jobs that can be run with models based on # this model package. # @return [Types::InferenceSpecification] # # @!attribute [rw] source_algorithm_specification # Details about the algorithm that was used to create the model # package. # @return [Types::SourceAlgorithmSpecification] # # @!attribute [rw] validation_specification # Configurations for one or more transform jobs that Amazon 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 AWS # 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, or trial component. # @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, or trial component. # @return [Types::UserContext] # # @!attribute [rw] approval_description # A description provided for the model approval. # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeModelQualityJobDefinitionRequest # data as a hash: # # { # job_definition_name: "MonitoringJobDefinitionName", # required # } # # @!attribute [rw] job_definition_name # The name of the model quality job. The name must be unique within an # AWS Region in the AWS 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 AWS Region in the AWS 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 # @note When making an API call, you may pass DescribeMonitoringScheduleRequest # data as a hash: # # { # monitoring_schedule_name: "MonitoringScheduleName", # required # } # # @!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 # @note When making an API call, you may pass DescribeNotebookInstanceInput # data as a hash: # # { # notebook_instance_name: "NotebookInstanceName", # required # } # # @!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 # @note When making an API call, you may pass DescribeNotebookInstanceLifecycleConfigInput # data as a hash: # # { # notebook_instance_lifecycle_config_name: "NotebookInstanceLifecycleConfigName", # required # } # # @!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 Amazon 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 AWS 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] network_interface_id # The network interface IDs that Amazon 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 Amazon 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 Amazon # 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 [AWS 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 Amazon 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 [AWS 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 Amazon 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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribePipelineDefinitionForExecutionRequest # data as a hash: # # { # pipeline_execution_arn: "PipelineExecutionArn", # required # } # # @!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 # @note When making an API call, you may pass DescribePipelineExecutionRequest # data as a hash: # # { # pipeline_execution_arn: "PipelineExecutionArn", # required # } # # @!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, or trial component. # @return [Types::UserContext] # # @!attribute [rw] last_modified_by # Information about the user who created or modified an experiment, # trial, or trial component. # @return [Types::UserContext] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribePipelineRequest # data as a hash: # # { # pipeline_name: "PipelineName", # required # } # # @!attribute [rw] pipeline_name # The name of the pipeline to describe. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribePipelineRequest AWS API Documentation # class DescribePipelineRequest < Struct.new( :pipeline_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] pipeline_arn # The Amazon Resource Name (ARN) of the pipeline. # @return [String] # # @!attribute [rw] pipeline_name # The name of the pipeline. # @return [String] # # @!attribute [rw] pipeline_display_name # The display name of the pipeline. # @return [String] # # @!attribute [rw] pipeline_definition # The JSON pipeline definition. # @return [String] # # @!attribute [rw] pipeline_description # The description of the pipeline. # @return [String] # # @!attribute [rw] role_arn # The Amazon Resource Name (ARN) that the pipeline uses to execute. # @return [String] # # @!attribute [rw] pipeline_status # The status of the pipeline execution. # @return [String] # # @!attribute [rw] creation_time # The time when the pipeline was created. # @return [Time] # # @!attribute [rw] last_modified_time # The time when the pipeline was last modified. # @return [Time] # # @!attribute [rw] last_run_time # The time when the pipeline was last run. # @return [Time] # # @!attribute [rw] created_by # Information about the user who created or modified an experiment, # trial, or trial component. # @return [Types::UserContext] # # @!attribute [rw] last_modified_by # Information about the user who created or modified an experiment, # trial, or trial component. # @return [Types::UserContext] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeProcessingJobRequest # data as a hash: # # { # processing_job_name: "ProcessingJobName", # required # } # # @!attribute [rw] processing_job_name # The name of the processing job. The name must be unique within an # AWS Region in the AWS 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 # AWS Region in the AWS 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 # @note When making an API call, you may pass DescribeProjectInput # data as a hash: # # { # project_name: "ProjectEntityName", # required # } # # @!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 AWS 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, or trial component. # @return [Types::UserContext] # # @!attribute [rw] creation_time # The time when the project was created. # @return [Time] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeSubscribedWorkteamRequest # data as a hash: # # { # workteam_arn: "WorkteamArn", # required # } # # @!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 # @note When making an API call, you may pass DescribeTrainingJobRequest # data as a hash: # # { # training_job_name: "TrainingJobName", # required # } # # @!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 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 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. # # Amazon 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. # # Amazon 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` # @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 AWS 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. Amazon 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 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][1]. # # # # [1]: 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, Amazon SageMaker ends the training # job. Use this API to cap model training costs. # # To stop a job, Amazon 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 Amazon 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, Amazon 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 Amazon SageMaker will bill 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 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 # # * CreateTrainingJob # # * CreateTransformJob # @return [Types::ExperimentConfig] # # @!attribute [rw] debug_rule_configurations # Configuration information for Debugger rules for debugging output # tensors. # @return [Array] # # @!attribute [rw] tensor_board_output_config # Configuration of storage locations for the Debugger TensorBoard # output data. # @return [Types::TensorBoardOutputConfig] # # @!attribute [rw] debug_rule_evaluation_statuses # Evaluation status of Debugger rules for debugging on a training job. # @return [Array] # # @!attribute [rw] profiler_config # Configuration information for Debugger system monitoring, framework # profiling, and storage paths. # @return [Types::ProfilerConfig] # # @!attribute [rw] profiler_rule_configurations # Configuration information for Debugger rules for profiling system # and framework metrics. # @return [Array] # # @!attribute [rw] profiler_rule_evaluation_statuses # Evaluation status of Debugger rules for profiling on a training job. # @return [Array] # # @!attribute [rw] profiling_status # Profiling status of a training job. # @return [String] # # @!attribute [rw] retry_strategy # The number of times to retry the job when the job fails due to an # `InternalServerError`. # @return [Types::RetryStrategy] # # @!attribute [rw] environment # The environment variables to set in the Docker container. # @return [Hash] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeTrainingJobResponse AWS API Documentation # class DescribeTrainingJobResponse < Struct.new( :training_job_name, :training_job_arn, :tuning_job_arn, :labeling_job_arn, :auto_ml_job_arn, :model_artifacts, :training_job_status, :secondary_status, :failure_reason, :hyper_parameters, :algorithm_specification, :role_arn, :input_data_config, :output_data_config, :resource_config, :vpc_config, :stopping_condition, :creation_time, :training_start_time, :training_end_time, :last_modified_time, :secondary_status_transitions, :final_metric_data_list, :enable_network_isolation, :enable_inter_container_traffic_encryption, :enable_managed_spot_training, :checkpoint_config, :training_time_in_seconds, :billable_time_in_seconds, :debug_hook_config, :experiment_config, :debug_rule_configurations, :tensor_board_output_config, :debug_rule_evaluation_statuses, :profiler_config, :profiler_rule_configurations, :profiler_rule_evaluation_statuses, :profiling_status, :retry_strategy, :environment) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeTransformJobRequest # data as a hash: # # { # transform_job_name: "TransformJobName", # required # } # # @!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] 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 # # * CreateTrainingJob # # * CreateTransformJob # @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, :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 # @note When making an API call, you may pass DescribeTrialComponentRequest # data as a hash: # # { # trial_component_name: "ExperimentEntityName", # required # } # # @!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 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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass DescribeTrialRequest # data as a hash: # # { # trial_name: "ExperimentEntityName", # required # } # # @!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 # @note When making an API call, you may pass DescribeUserProfileRequest # data as a hash: # # { # domain_id: "DomainId", # required # user_profile_name: "UserProfileName", # required # } # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] user_profile_name # The user profile name. This value is not case sensitive. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DescribeUserProfileRequest AWS API Documentation # class DescribeUserProfileRequest < Struct.new( :domain_id, :user_profile_name) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] domain_id # The ID of the domain that contains the profile. # @return [String] # # @!attribute [rw] user_profile_arn # The user profile Amazon Resource Name (ARN). # @return [String] # # @!attribute [rw] user_profile_name # The user profile name. # @return [String] # # @!attribute [rw] home_efs_file_system_uid # The ID of the user's profile in the Amazon Elastic File System # (EFS) volume. # @return [String] # # @!attribute [rw] status # The status. # @return [String] # # @!attribute [rw] last_modified_time # The last modified time. # @return [Time] # # @!attribute [rw] creation_time # The creation time. # @return [Time] # # @!attribute [rw] failure_reason # The failure reason. # @return [String] # # @!attribute [rw] single_sign_on_user_identifier # The SSO user identifier. # @return [String] # # @!attribute [rw] single_sign_on_user_value # The SSO 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 # @note When making an API call, you may pass DescribeWorkforceRequest # data as a hash: # # { # workforce_name: "WorkforceName", # required # } # # @!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 AWS Region. By default, any workforce-related API # operation used in a specific region will apply to the workforce # created in that region. To learn how to create a private workforce, # see [Create a Private Workforce][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 # @note When making an API call, you may pass DescribeWorkteamRequest # data as a hash: # # { # workteam_name: "WorkteamName", # required # } # # @!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. # # @note When making an API call, you may pass DesiredWeightAndCapacity # data as a hash: # # { # variant_name: "VariantName", # required # desired_weight: 1.0, # desired_instance_count: 1, # } # # @!attribute [rw] variant_name # The name of the variant to update. # @return [String] # # @!attribute [rw] desired_weight # The variant's weight. # @return [Float] # # @!attribute [rw] desired_instance_count # The variant's capacity. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DesiredWeightAndCapacity AWS API Documentation # class DesiredWeightAndCapacity < Struct.new( :variant_name, :desired_weight, :desired_instance_count) SENSITIVE = [] include Aws::Structure end # Information of a particular device. # # @note When making an API call, you may pass Device # data as a hash: # # { # device_name: "DeviceName", # required # description: "DeviceDescription", # iot_thing_name: "ThingName", # } # # @!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 # AWS 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 # 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 # 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 AWS 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] # # @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) 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 # @note When making an API call, you may pass DisassociateTrialComponentRequest # data as a hash: # # { # trial_component_name: "ExperimentEntityName", # required # trial_name: "ExperimentEntityName", # required # } # # @!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 ARN of the trial component. # @return [String] # # @!attribute [rw] trial_arn # The Amazon Resource Name (ARN) of the trial. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DisassociateTrialComponentResponse AWS API Documentation # class DisassociateTrialComponentResponse < Struct.new( :trial_component_arn, :trial_arn) SENSITIVE = [] include Aws::Structure end # The domain's details. # # @!attribute [rw] domain_arn # The domain's Amazon Resource Name (ARN). # @return [String] # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] domain_name # The domain name. # @return [String] # # @!attribute [rw] status # The status. # @return [String] # # @!attribute [rw] creation_time # The creation time. # @return [Time] # # @!attribute [rw] last_modified_time # The last modified time. # @return [Time] # # @!attribute [rw] url # The domain's URL. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/DomainDetails AWS API Documentation # class DomainDetails < Struct.new( :domain_arn, :domain_id, :domain_name, :status, :creation_time, :last_modified_time, :url) SENSITIVE = [] include Aws::Structure end # 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. # # @note When making an API call, you may pass EdgeOutputConfig # data as a hash: # # { # s3_output_location: "S3Uri", # required # kms_key_id: "KmsKeyId", # } # # @!attribute [rw] s3_output_location # The Amazon Simple Storage (S3) bucker URI. # @return [String] # # @!attribute [rw] kms_key_id # The AWS Key Management Service (AWS 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] # # @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) 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 # @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 # @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 AWS resources][1] in the *AWS 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/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) 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 # Input object for the endpoint # # @note When making an API call, you may pass EndpointInput # data as a hash: # # { # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # } # # @!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 # transfering data for the monitoring job. `Pipe` mode is recommended # for large datasets. `File` mode is useful for small files that fit # in memory. Defaults to `File`. # @return [String] # # @!attribute [rw] s3_data_distribution_type # Whether input data distributed in Amazon S3 is fully replicated or # sharded by an S3 key. Defaults to `FullyReplicated` # @return [String] # # @!attribute [rw] features_attribute # The attributes of the input data that are the input features. # @return [String] # # @!attribute [rw] inference_attribute # The attribute of the input data that represents the ground truth # label. # @return [String] # # @!attribute [rw] probability_attribute # In a classification problem, the attribute that represents the class # probability. # @return [String] # # @!attribute [rw] probability_threshold_attribute # The threshold for the class probability to be evaluated as a # positive result. # @return [Float] # # @!attribute [rw] start_time_offset # If specified, monitoring jobs substract this time from the start # time. For information about using offsets for scheduling monitoring # jobs, see [Schedule Model Quality Monitoring Jobs][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html # @return [String] # # @!attribute [rw] end_time_offset # If specified, monitoring jobs substract this time from the end time. # For information about using offsets for scheduling monitoring jobs, # see [Schedule Model Quality Monitoring Jobs][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-model-quality-schedule.html # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/EndpointInput AWS API Documentation # class EndpointInput < Struct.new( :endpoint_name, :local_path, :s3_input_mode, :s3_data_distribution_type, :features_attribute, :inference_attribute, :probability_attribute, :probability_threshold_attribute, :start_time_offset, :end_time_offset) SENSITIVE = [] include Aws::Structure end # 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 is executing. # # * `Updating`\: UpdateEndpoint or UpdateEndpointWeightsAndCapacities # 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 call or when the # UpdateEndpointWeightsAndCapacities operation is called explicitly. # # * `InService`\: Endpoint is available to process incoming requests. # # * `Deleting`\: DeleteEndpoint is executing. # # * `Failed`\: Endpoint could not be created, updated, or re-scaled. # Use DescribeEndpointOutput$FailureReason for information about the # failure. DeleteEndpoint is the only operation that can be # performed on a failed endpoint. # # To get a list of endpoints with a specified status, use the # ListEndpointsInput$StatusEquals filter. # @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 # The properties of an experiment as returned by the Search API. # # @!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 # Information about the user who created or modified an experiment, # trial, or trial component. # @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, or trial component. # @return [Types::UserContext] # # @!attribute [rw] tags # The list of tags that are associated with the experiment. You can # use Search API to search on the tags. # @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 # # * CreateTrainingJob # # * CreateTransformJob # # @note When making an API call, you may pass ExperimentConfig # data as a hash: # # { # experiment_name: "ExperimentEntityName", # trial_name: "ExperimentEntityName", # trial_component_display_name: "ExperimentEntityName", # } # # @!attribute [rw] experiment_name # The name of an existing experiment to associate the trial component # with. # @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] # # @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) 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 API and provide the # `ExperimentName`. # # @!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. # # @note When making an API call, you may pass Explainability # data as a hash: # # { # report: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # } # # @!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 list of features. You must include `FeatureName` and `FeatureType`. # Valid feature `FeatureType`s are `Integral`, `Fractional` and # `String`. # # @note When making an API call, you may pass FeatureDefinition # data as a hash: # # { # feature_name: "FeatureName", # feature_type: "Integral", # accepts Integral, Fractional, String # } # # @!attribute [rw] feature_name # The name of a feature. The type must be a string. `FeatureName` # cannot be any of the following: `is_deleted`, `write_time`, # `api_invocation_time`. # @return [String] # # @!attribute [rw] feature_type # The value type of a feature. Valid values are Integral, Fractional, # or String. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FeatureDefinition AWS API Documentation # class FeatureDefinition < Struct.new( :feature_name, :feature_type) SENSITIVE = [] include Aws::Structure end # Amazon SageMaker Feature Store stores features in a collection called # Feature Group. A Feature Group can be visualized as a table which has # rows, with a unique identifier for each row where each column in the # table is a feature. In principle, a Feature Group is composed of # features and values per features. # # @!attribute [rw] feature_group_arn # The Amazon Resource Name (ARN) of a `FeatureGroup`. # @return [String] # # @!attribute [rw] feature_group_name # The name of the `FeatureGroup`. # @return [String] # # @!attribute [rw] record_identifier_feature_name # The name of the `Feature` whose value uniquely identifies a `Record` # defined in the `FeatureGroup` `FeatureDefinitions`. # @return [String] # # @!attribute [rw] event_time_feature_name # The name of the feature that stores the `EventTime` of a Record in a # `FeatureGroup`. # # A `EventTime` is point in time when a new event occurs that # corresponds to the creation or update of a `Record` in # `FeatureGroup`. All `Records` in the `FeatureGroup` must have a # corresponding `EventTime`. # @return [String] # # @!attribute [rw] feature_definitions # A list of `Feature`s. Each `Feature` must include a `FeatureName` # and a `FeatureType`. # # Valid `FeatureType`s are `Integral`, `Fractional` and `String`. # # `FeatureName`s cannot be any of the following: `is_deleted`, # `write_time`, `api_invocation_time`. # # You can create up to 2,500 `FeatureDefinition`s per `FeatureGroup`. # @return [Array] # # @!attribute [rw] creation_time # The time a `FeatureGroup` was created. # @return [Time] # # @!attribute [rw] online_store_config # Use this to specify the AWS 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 # AWS 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] 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, :online_store_config, :offline_store_config, :role_arn, :feature_group_status, :offline_store_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 Amazon Elastic File System (EFS) storage configuration for a # SageMaker image. # # @note When making an API call, you may pass FileSystemConfig # data as a hash: # # { # mount_path: "MountPath", # default_uid: 1, # default_gid: 1, # } # # @!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. # # @note When making an API call, you may pass FileSystemDataSource # data as a hash: # # { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # } # # @!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 API. # # If you specify a `Value`, but not an `Operator`, Amazon SageMaker uses # the equals operator. # # In search, there are several property types: # # Metrics # # : To define a metric filter, enter a value using the form # `"Metrics."`, 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.`. # # @note When making an API call, you may pass Filter # data as a hash: # # { # name: "ResourcePropertyName", # required # operator: "Equals", # accepts Equals, NotEquals, GreaterThan, GreaterThanOrEqualTo, LessThan, LessThanOrEqualTo, Contains, Exists, NotExists, In # value: "FilterValue", # } # # @!attribute [rw] name # A resource property name. For example, `TrainingJobName`. For valid # property names, see SearchRecord. You must specify a valid property # for the resource. # @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. # @return [String] # # @!attribute [rw] value # The value of the metric with the best result. # @return [Float] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/FinalAutoMLJobObjectiveMetric AWS API Documentation # class FinalAutoMLJobObjectiveMetric < Struct.new( :type, :metric_name, :value) SENSITIVE = [] include Aws::Structure end # Shows the final value for the objective metric for a training job that # was launched by a hyperparameter tuning job. You define the objective # metric in the `HyperParameterTuningJobObjective` parameter of # HyperParameterTuningJobConfig. # # @!attribute [rw] type # Whether to minimize or maximize the objective metric. Valid values # are Minimize and Maximize. # @return [String] # # @!attribute [rw] metric_name # The name of the objective metric. # @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. # # @note When making an API call, you may pass FlowDefinitionOutputConfig # data as a hash: # # { # s3_output_path: "S3Uri", # required # kms_key_id: "KmsKeyId", # } # # @!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 # @note When making an API call, you may pass GetDeviceFleetReportRequest # data as a hash: # # { # device_fleet_name: "EntityName", # required # } # # @!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 # @note When making an API call, you may pass GetModelPackageGroupPolicyInput # data as a hash: # # { # model_package_group_name: "EntityName", # required # } # # @!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 # @note When making an API call, you may pass GetSearchSuggestionsRequest # data as a hash: # # { # resource: "TrainingJob", # required, accepts TrainingJob, Experiment, ExperimentTrial, ExperimentTrialComponent, Endpoint, ModelPackage, ModelPackageGroup, Pipeline, PipelineExecution, FeatureGroup # suggestion_query: { # property_name_query: { # property_name_hint: "PropertyNameHint", # required # }, # }, # } # # @!attribute [rw] resource # The name of the Amazon 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 AWS # account. # # @note When making an API call, you may pass GitConfig # data as a hash: # # { # repository_url: "GitConfigUrl", # required # branch: "Branch", # secret_arn: "SecretArn", # } # # @!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 AWS 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. # # @note When making an API call, you may pass GitConfigForUpdate # data as a hash: # # { # secret_arn: "SecretArn", # } # # @!attribute [rw] secret_arn # The Amazon Resource Name (ARN) of the AWS 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 # Defines under what conditions SageMaker creates a human loop. Used # within . See for the required format of activation conditions. # # @note When making an API call, you may pass HumanLoopActivationConditionsConfig # data as a hash: # # { # human_loop_activation_conditions: "HumanLoopActivationConditions", # required # } # # @!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. # # @note When making an API call, you may pass HumanLoopActivationConfig # data as a hash: # # { # human_loop_activation_conditions_config: { # required # human_loop_activation_conditions: "HumanLoopActivationConditions", # required # }, # } # # @!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. # # @note When making an API call, you may pass HumanLoopConfig # data as a hash: # # { # workteam_arn: "WorkteamArn", # required # human_task_ui_arn: "HumanTaskUiArn", # required # task_title: "FlowDefinitionTaskTitle", # required # task_description: "FlowDefinitionTaskDescription", # required # task_count: 1, # required # task_availability_lifetime_in_seconds: 1, # task_time_limit_in_seconds: 1, # task_keywords: ["FlowDefinitionTaskKeyword"], # public_workforce_task_price: { # amount_in_usd: { # dollars: 1, # cents: 1, # tenth_fractions_of_a_cent: 1, # }, # }, # } # # @!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. # # @note When making an API call, you may pass HumanLoopRequestSource # data as a hash: # # { # aws_managed_human_loop_request_source: "AWS/Rekognition/DetectModerationLabels/Image/V3", # required, accepts AWS/Rekognition/DetectModerationLabels/Image/V3, AWS/Textract/AnalyzeDocument/Forms/V1 # } # # @!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. # # @note When making an API call, you may pass HumanTaskConfig # data as a hash: # # { # workteam_arn: "WorkteamArn", # required # ui_config: { # required # ui_template_s3_uri: "S3Uri", # human_task_ui_arn: "HumanTaskUiArn", # }, # pre_human_task_lambda_arn: "LambdaFunctionArn", # required # task_keywords: ["TaskKeyword"], # task_title: "TaskTitle", # required # task_description: "TaskDescription", # required # number_of_human_workers_per_data_object: 1, # required # task_time_limit_in_seconds: 1, # required # task_availability_lifetime_in_seconds: 1, # max_concurrent_task_count: 1, # annotation_consolidation_config: { # required # annotation_consolidation_lambda_arn: "LambdaFunctionArn", # required # }, # public_workforce_task_price: { # amount_in_usd: { # dollars: 1, # cents: 1, # tenth_fractions_of_a_cent: 1, # }, # }, # } # # @!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 7 days (604,800 seconds). If you want to change these # limits, contact AWS Support. # # # # [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 # 10 days (864,000 seconds). For most users, the maximum is also 10 # days. If you want to change this limit, contact AWS Support. # @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. # @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. # # @note When making an API call, you may pass HyperParameterAlgorithmSpecification # data as a hash: # # { # training_image: "AlgorithmImage", # training_input_mode: "Pipe", # required, accepts Pipe, File # algorithm_name: "ArnOrName", # metric_definitions: [ # { # name: "MetricName", # required # regex: "MetricRegex", # required # }, # ], # } # # @!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]. Amazon 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 input mode that the algorithm supports: File or Pipe. In File # input mode, Amazon SageMaker downloads the training data from Amazon # S3 to the storage volume that is attached to the training instance # and mounts the directory to the Docker volume for the training # container. In Pipe input mode, Amazon SageMaker streams data # directly from Amazon S3 to the container. # # If you specify File mode, make sure that you provision the storage # volume that is attached to the training instance with enough # capacity to accommodate the training data downloaded from Amazon S3, # the model artifacts, and intermediate information. # # # # For more information about input modes, see [Algorithms][1]. # # # # [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 objects that specify the metrics that # the algorithm emits. # @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. # # @note When making an API call, you may pass HyperParameterSpecification # data as a hash: # # { # name: "ParameterName", # required # description: "EntityDescription", # type: "Integer", # required, accepts Integer, Continuous, Categorical, FreeText # range: { # integer_parameter_range_specification: { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # }, # continuous_parameter_range_specification: { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # }, # categorical_parameter_range_specification: { # values: ["ParameterValue"], # required # }, # }, # is_tunable: false, # is_required: false, # default_value: "HyperParameterValue", # } # # @!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. # # @note When making an API call, you may pass HyperParameterTrainingJobDefinition # data as a hash: # # { # definition_name: "HyperParameterTrainingJobDefinitionName", # tuning_objective: { # type: "Maximize", # required, accepts Maximize, Minimize # metric_name: "MetricName", # required # }, # hyper_parameter_ranges: { # integer_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # continuous_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # categorical_parameter_ranges: [ # { # name: "ParameterKey", # required # values: ["ParameterValue"], # required # }, # ], # }, # static_hyper_parameters: { # "HyperParameterKey" => "HyperParameterValue", # }, # algorithm_specification: { # required # training_image: "AlgorithmImage", # training_input_mode: "Pipe", # required, accepts Pipe, File # algorithm_name: "ArnOrName", # metric_definitions: [ # { # name: "MetricName", # required # regex: "MetricRegex", # required # }, # ], # }, # role_arn: "RoleArn", # required # input_data_config: [ # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # }, # ], # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # resource_config: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # enable_network_isolation: false, # enable_inter_container_traffic_encryption: false, # enable_managed_spot_training: false, # checkpoint_config: { # s3_uri: "S3Uri", # required # local_path: "DirectoryPath", # }, # retry_strategy: { # maximum_retry_attempts: 1, # required # }, # } # # @!attribute [rw] definition_name # The job definition name. # @return [String] # # @!attribute [rw] tuning_objective # Defines the objective metric for a hyperparameter tuning job. # Hyperparameter tuning uses the value of this metric to evaluate the # training jobs it launches, and returns the training job that results # in either the highest or lowest value for this metric, depending on # the value you specify for the `Type` parameter. # @return [Types::HyperParameterTuningJobObjective] # # @!attribute [rw] hyper_parameter_ranges # Specifies ranges of integer, continuous, and categorical # hyperparameters that a hyperparameter tuning job searches. The # hyperparameter tuning job launches training jobs with hyperparameter # values within these ranges to find the combination of values that # result in the training job with the best performance as measured by # the objective metric of the hyperparameter tuning job. # # You can specify a maximum of 20 hyperparameters that a # hyperparameter tuning job can search over. Every possible value of a # categorical parameter range counts against this limit. # # # @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 object that specifies the # resource algorithm to use for the training jobs that the tuning job # launches. # @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 objects that specify the input for the training # jobs that the tuning job launches. # @return [Array] # # @!attribute [rw] vpc_config # The VpcConfig 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][1]. # # # # [1]: 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 Amazon 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. # @return [Types::ResourceConfig] # # @!attribute [rw] stopping_condition # Specifies a limit to how long a model hyperparameter training job # can run. It also specifies how long a managed spot training job has # to complete. When the job reaches the time limit, Amazon 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, Amazon 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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTrainingJobDefinition AWS API Documentation # class HyperParameterTrainingJobDefinition < Struct.new( :definition_name, :tuning_objective, :hyper_parameter_ranges, :static_hyper_parameters, :algorithm_specification, :role_arn, :input_data_config, :vpc_config, :output_data_config, :resource_config, :stopping_condition, :enable_network_isolation, :enable_inter_container_traffic_encryption, :enable_managed_spot_training, :checkpoint_config, :retry_strategy) SENSITIVE = [] include Aws::Structure end # Specifies 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 Amazon 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 object that # specifies the value of the objective metric of the tuning job that # launched this training job. # @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 # Configures a hyperparameter tuning job. # # @note When making an API call, you may pass HyperParameterTuningJobConfig # data as a hash: # # { # strategy: "Bayesian", # required, accepts Bayesian, Random # hyper_parameter_tuning_job_objective: { # type: "Maximize", # required, accepts Maximize, Minimize # metric_name: "MetricName", # required # }, # resource_limits: { # required # max_number_of_training_jobs: 1, # required # max_parallel_training_jobs: 1, # required # }, # parameter_ranges: { # integer_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # continuous_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # categorical_parameter_ranges: [ # { # name: "ParameterKey", # required # values: ["ParameterValue"], # required # }, # ], # }, # training_job_early_stopping_type: "Off", # accepts Off, Auto # tuning_job_completion_criteria: { # target_objective_metric_value: 1.0, # required # }, # } # # @!attribute [rw] strategy # Specifies how hyperparameter tuning chooses the combinations of # hyperparameter values to use for the training job it launches. To # use the Bayesian search strategy, set this to `Bayesian`. To # randomly search, set it to `Random`. 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] hyper_parameter_tuning_job_objective # The HyperParameterTuningJobObjective object that specifies the # objective metric for this tuning job. # @return [Types::HyperParameterTuningJobObjective] # # @!attribute [rw] resource_limits # The ResourceLimits object that specifies the maximum number of # training jobs and parallel training jobs for this tuning job. # @return [Types::ResourceLimits] # # @!attribute [rw] parameter_ranges # The ParameterRanges object that specifies the ranges of # hyperparameters that this tuning job searches. # @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. This can be 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 # # : Amazon 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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/HyperParameterTuningJobConfig AWS API Documentation # class HyperParameterTuningJobConfig < Struct.new( :strategy, :hyper_parameter_tuning_job_objective, :resource_limits, :parameter_ranges, :training_job_early_stopping_type, :tuning_job_completion_criteria) 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. # # @note When making an API call, you may pass HyperParameterTuningJobObjective # data as a hash: # # { # type: "Maximize", # required, accepts Maximize, Minimize # metric_name: "MetricName", # required # } # # @!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 # 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 use for each iteration. Currently, the only # valid value is Bayesian. # @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 object that specifies the numbers of # training jobs, categorized by status, that this tuning job launched. # @return [Types::TrainingJobStatusCounters] # # @!attribute [rw] objective_status_counters # The ObjectiveStatusCounters object that specifies the numbers of # training jobs, categorized by objective metric status, that this # tuning job launched. # @return [Types::ObjectiveStatusCounters] # # @!attribute [rw] resource_limits # The ResourceLimits object that specifies the maximum number of # training jobs and parallel training jobs allowed for this tuning # job. # @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. # # # # @note When making an API call, you may pass HyperParameterTuningJobWarmStartConfig # data as a hash: # # { # parent_hyper_parameter_tuning_jobs: [ # required # { # hyper_parameter_tuning_job_name: "HyperParameterTuningJobName", # }, # ], # warm_start_type: "IdenticalDataAndAlgorithm", # required, accepts IdenticalDataAndAlgorithm, TransferLearning # } # # @!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 # 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 Amazon Resource Name (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 # Specifies whether the model container is in Amazon ECR or a private # Docker registry accessible from your Amazon Virtual Private Cloud # (VPC). # # @note When making an API call, you may pass ImageConfig # data as a hash: # # { # repository_access_mode: "Platform", # required, accepts Platform, Vpc # repository_auth_config: { # repository_credentials_provider_arn: "RepositoryCredentialsProviderArn", # required # }, # } # # @!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 Amazon Resource Name (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 # Specifies details about how containers in a multi-container endpoint # are run. # # @note When making an API call, you may pass InferenceExecutionConfig # data as a hash: # # { # mode: "Serial", # required, accepts Serial, Direct # } # # @!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 # Defines how to perform inference generation after a training job is # run. # # @note When making an API call, you may pass InferenceSpecification # data as a hash: # # { # containers: [ # required # { # container_hostname: "ContainerHostname", # image: "ContainerImage", # required # image_digest: "ImageDigest", # model_data_url: "Url", # product_id: "ProductId", # }, # ], # supported_transform_instance_types: ["ml.m4.xlarge"], # accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # supported_realtime_inference_instance_types: ["ml.t2.medium"], # accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.m5d.large, ml.m5d.xlarge, ml.m5d.2xlarge, ml.m5d.4xlarge, ml.m5d.12xlarge, ml.m5d.24xlarge, ml.c4.large, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.large, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.12xlarge, ml.r5.24xlarge, ml.r5d.large, ml.r5d.xlarge, ml.r5d.2xlarge, ml.r5d.4xlarge, ml.r5d.12xlarge, ml.r5d.24xlarge, ml.inf1.xlarge, ml.inf1.2xlarge, ml.inf1.6xlarge, ml.inf1.24xlarge # supported_content_types: ["ContentType"], # required # supported_response_mime_types: ["ResponseMIMEType"], # required # } # # @!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 # 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. # # @note When making an API call, you may pass InputConfig # data as a hash: # # { # s3_uri: "S3Uri", # required # data_input_config: "DataInputConfig", # required # framework: "TENSORFLOW", # required, accepts TENSORFLOW, KERAS, MXNET, ONNX, PYTORCH, XGBOOST, TFLITE, DARKNET, SKLEARN # framework_version: "FrameworkVersion", # } # # @!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 # InputConfig$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` # OutputConfig$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$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][1]. # # * 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` ][2] 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` ][2]. # 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#sagemaker-Type-OutputConfig-TargetDevice # [2]: 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 PyTorch framework versions # `1.4`, `1.5`, and `1.6` for cloud instance target devices: `ml_c4`, # `ml_c5`, `ml_m4`, `ml_m5`, `ml_p2`, `ml_p3`, and `ml_g4dn`. # @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 # For a hyperparameter of the integer type, specifies the range that a # hyperparameter tuning job searches. # # @note When making an API call, you may pass IntegerParameterRange # data as a hash: # # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # } # # @!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 # # : Amazon 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. # # @note When making an API call, you may pass IntegerParameterRangeSpecification # data as a hash: # # { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # } # # @!attribute [rw] min_value # The minimum integer value allowed. # @return [String] # # @!attribute [rw] max_value # The maximum integer value allowed. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/IntegerParameterRangeSpecification AWS API Documentation # class IntegerParameterRangeSpecification < Struct.new( :min_value, :max_value) SENSITIVE = [] include Aws::Structure end # The JupyterServer app settings. # # @note When making an API call, you may pass JupyterServerAppSettings # data as a hash: # # { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # } # # @!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. # @return [Types::ResourceSpec] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/JupyterServerAppSettings AWS API Documentation # class JupyterServerAppSettings < Struct.new( :default_resource_spec) SENSITIVE = [] include Aws::Structure end # The KernelGateway app settings. # # @note When making an API call, you may pass KernelGatewayAppSettings # data as a hash: # # { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # custom_images: [ # { # image_name: "ImageName", # required # image_version_number: 1, # app_image_config_name: "AppImageConfigName", # required # }, # ], # } # # @!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. # @return [Types::ResourceSpec] # # @!attribute [rw] custom_images # A list of custom SageMaker images that are configured to run as a # KernelGateway app. # @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) SENSITIVE = [] include Aws::Structure end # The configuration for the file system and kernels in a SageMaker image # running as a KernelGateway app. # # @note When making an API call, you may pass KernelGatewayImageConfig # data as a hash: # # { # kernel_specs: [ # required # { # name: "KernelName", # required # display_name: "KernelDisplayName", # }, # ], # file_system_config: { # mount_path: "MountPath", # default_uid: 1, # default_gid: 1, # }, # } # # @!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 (EFS) storage configuration for a # SageMaker image. # @return [Types::FileSystemConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/KernelGatewayImageConfig AWS API Documentation # class KernelGatewayImageConfig < Struct.new( :kernel_specs, :file_system_config) SENSITIVE = [] include Aws::Structure end # The specification of a Jupyter kernel. # # @note When making an API call, you may pass KernelSpec # data as a hash: # # { # name: "KernelName", # required # display_name: "KernelDisplayName", # } # # @!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. # # @note When making an API call, you may pass LabelingJobAlgorithmsConfig # data as a hash: # # { # labeling_job_algorithm_specification_arn: "LabelingJobAlgorithmSpecificationArn", # required # initial_active_learning_model_arn: "ModelArn", # labeling_job_resource_config: { # volume_kms_key_id: "KmsKeyId", # }, # } # # @!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. # # @note When making an API call, you may pass LabelingJobDataAttributes # data as a hash: # # { # content_classifiers: ["FreeOfPersonallyIdentifiableInformation"], # accepts FreeOfPersonallyIdentifiableInformation, FreeOfAdultContent # } # # @!attribute [rw] content_classifiers # Declares that your content is free of personally identifiable # information or adult content. Amazon 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. # # @note When making an API call, you may pass LabelingJobDataSource # data as a hash: # # { # s3_data_source: { # manifest_s3_uri: "S3Uri", # required # }, # sns_data_source: { # sns_topic_arn: "SnsTopicArn", # required # }, # } # # @!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 AWS 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. # # @note When making an API call, you may pass LabelingJobInputConfig # data as a hash: # # { # data_source: { # required # s3_data_source: { # manifest_s3_uri: "S3Uri", # required # }, # sns_data_source: { # sns_topic_arn: "SnsTopicArn", # required # }, # }, # data_attributes: { # content_classifiers: ["FreeOfPersonallyIdentifiableInformation"], # accepts FreeOfPersonallyIdentifiableInformation, FreeOfAdultContent # }, # } # # @!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 Amazon 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. # # @note When making an API call, you may pass LabelingJobOutputConfig # data as a hash: # # { # s3_output_path: "S3Uri", # required # kms_key_id: "KmsKeyId", # sns_topic_arn: "SnsTopicArn", # } # # @!attribute [rw] s3_output_path # The Amazon S3 location to write output data. # @return [String] # # @!attribute [rw] kms_key_id # The AWS 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 AWS KMS][1]. # # If you don't provide a KMS key ID, Amazon SageMaker uses the # default AWS 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. # # @note When making an API call, you may pass LabelingJobResourceConfig # data as a hash: # # { # volume_kms_key_id: "KmsKeyId", # } # # @!attribute [rw] volume_kms_key_id # The AWS Key Management Service (AWS 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 AWS KMS customer managed # CMK 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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/LabelingJobResourceConfig AWS API Documentation # class LabelingJobResourceConfig < Struct.new( :volume_kms_key_id) SENSITIVE = [] include Aws::Structure end # The Amazon S3 location of the input data objects. # # @note When making an API call, you may pass LabelingJobS3DataSource # data as a hash: # # { # manifest_s3_uri: "S3Uri", # required # } # # @!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. # # @note When making an API call, you may pass LabelingJobSnsDataSource # data as a hash: # # { # sns_topic_arn: "SnsTopicArn", # required # } # # @!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. # # # # @note When making an API call, you may pass LabelingJobStoppingConditions # data as a hash: # # { # max_human_labeled_object_count: 1, # max_percentage_of_input_dataset_labeled: 1, # } # # @!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 # @note When making an API call, you may pass ListActionsRequest # data as a hash: # # { # source_uri: "SourceUri", # action_type: "String256", # created_after: Time.now, # created_before: Time.now, # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListAlgorithmsInput # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # max_results: 1, # name_contains: "NameContains", # next_token: "NextToken", # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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, Amazon 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 # @note When making an API call, you may pass ListAppImageConfigsRequest # data as a hash: # # { # max_results: 1, # next_token: "NextToken", # name_contains: "AppImageConfigName", # creation_time_before: Time.now, # creation_time_after: Time.now, # modified_time_before: Time.now, # modified_time_after: Time.now, # sort_by: "CreationTime", # accepts CreationTime, LastModifiedTime, Name # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!attribute [rw] max_results # The maximum number of AppImageConfigs to return in the response. The # default value is 10. # @return [Integer] # # @!attribute [rw] next_token # If the previous call to `ListImages` didn't return the full set of # AppImageConfigs, the call returns a token for getting the next set # of AppImageConfigs. # @return [String] # # @!attribute [rw] name_contains # A filter that returns only AppImageConfigs whose name contains the # specified string. # @return [String] # # @!attribute [rw] creation_time_before # A filter that returns only AppImageConfigs created on or before the # specified time. # @return [Time] # # @!attribute [rw] creation_time_after # A filter that returns only AppImageConfigs created on or after the # specified time. # @return [Time] # # @!attribute [rw] modified_time_before # A filter that returns only AppImageConfigs modified on or before the # specified time. # @return [Time] # # @!attribute [rw] modified_time_after # A filter that returns only AppImageConfigs modified on or after the # specified time. # @return [Time] # # @!attribute [rw] sort_by # The property used to sort results. The default value is # `CreationTime`. # @return [String] # # @!attribute [rw] sort_order # The sort order. The default value is `Descending`. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListAppImageConfigsRequest AWS API Documentation # class ListAppImageConfigsRequest < Struct.new( :max_results, :next_token, :name_contains, :creation_time_before, :creation_time_after, :modified_time_before, :modified_time_after, :sort_by, :sort_order) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] next_token # A token for getting the next set of AppImageConfigs, if there are # any. # @return [String] # # @!attribute [rw] app_image_configs # A list of AppImageConfigs and their properties. # @return [Array] # # @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 # @note When making an API call, you may pass ListAppsRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # sort_order: "Ascending", # accepts Ascending, Descending # sort_by: "CreationTime", # accepts CreationTime # domain_id_equals: "DomainId", # user_profile_name_equals: "UserProfileName", # } # # @!attribute [rw] next_token # If the previous response was truncated, you will receive this token. # Use it in your next request to receive the next set of results. # @return [String] # # @!attribute [rw] max_results # Returns a list up to a specified limit. # @return [Integer] # # @!attribute [rw] sort_order # The sort order for the results. The default is Ascending. # @return [String] # # @!attribute [rw] sort_by # The parameter by which to sort the results. The default is # CreationTime. # @return [String] # # @!attribute [rw] domain_id_equals # A parameter to search for the domain ID. # @return [String] # # @!attribute [rw] user_profile_name_equals # A parameter to search by user profile name. # @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) 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 # @note When making an API call, you may pass ListArtifactsRequest # data as a hash: # # { # source_uri: "SourceUri", # artifact_type: "String256", # created_after: Time.now, # created_before: Time.now, # sort_by: "CreationTime", # accepts CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListAssociationsRequest # data as a hash: # # { # source_arn: "AssociationEntityArn", # destination_arn: "AssociationEntityArn", # source_type: "String256", # destination_type: "String256", # association_type: "ContributedTo", # accepts ContributedTo, AssociatedWith, DerivedFrom, Produced # created_after: Time.now, # created_before: Time.now, # sort_by: "SourceArn", # accepts SourceArn, DestinationArn, SourceType, DestinationType, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListAutoMLJobsRequest # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # name_contains: "AutoMLNameContains", # status_equals: "Completed", # accepts Completed, InProgress, Failed, Stopped, Stopping # sort_order: "Ascending", # accepts Ascending, Descending # sort_by: "Name", # accepts Name, CreationTime, Status # max_results: 1, # next_token: "NextToken", # } # # @!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 # @note When making an API call, you may pass ListCandidatesForAutoMLJobRequest # data as a hash: # # { # auto_ml_job_name: "AutoMLJobName", # required # status_equals: "Completed", # accepts Completed, InProgress, Failed, Stopped, Stopping # candidate_name_equals: "CandidateName", # sort_order: "Ascending", # accepts Ascending, Descending # sort_by: "CreationTime", # accepts CreationTime, Status, FinalObjectiveMetricValue # max_results: 1, # next_token: "NextToken", # } # # @!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 # @note When making an API call, you may pass ListCodeRepositoriesInput # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # max_results: 1, # name_contains: "CodeRepositoryNameContains", # next_token: "NextToken", # sort_by: "Name", # accepts Name, CreationTime, LastModifiedTime # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 AWS 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 # @note When making an API call, you may pass ListCompilationJobsRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # name_contains: "NameContains", # status_equals: "INPROGRESS", # accepts INPROGRESS, COMPLETED, FAILED, STARTING, STOPPING, STOPPED # sort_by: "Name", # accepts Name, CreationTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 # DescribeCompilationJobResponse$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 objects, each describing a model # compilation job. # @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 # @note When making an API call, you may pass ListContextsRequest # data as a hash: # # { # source_uri: "SourceUri", # context_type: "String256", # created_after: Time.now, # created_before: Time.now, # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListDataQualityJobDefinitionsRequest # data as a hash: # # { # endpoint_name: "EndpointName", # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # name_contains: "NameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # } # # @!attribute [rw] endpoint_name # A filter that lists the data quality job definitions associated with # the specified endpoint. # @return [String] # # @!attribute [rw] sort_by # The field to sort results by. The default is `CreationTime`. # @return [String] # # @!attribute [rw] sort_order # The sort order for results. The default is `Descending`. # @return [String] # # @!attribute [rw] next_token # If the result of the previous `ListDataQualityJobDefinitions` # request was truncated, the response includes a `NextToken`. To # retrieve the next set of transform jobs, use the token in the next # request.> # @return [String] # # @!attribute [rw] max_results # The maximum number of data quality monitoring job definitions to # return in the response. # @return [Integer] # # @!attribute [rw] name_contains # A string in the data quality monitoring job definition name. This # filter returns only data quality monitoring job definitions whose # name contains the specified string. # @return [String] # # @!attribute [rw] creation_time_before # A filter that returns only data quality monitoring job definitions # created before the specified time. # @return [Time] # # @!attribute [rw] creation_time_after # A filter that returns only data quality monitoring job definitions # created after the specified time. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDataQualityJobDefinitionsRequest AWS API Documentation # class ListDataQualityJobDefinitionsRequest < Struct.new( :endpoint_name, :sort_by, :sort_order, :next_token, :max_results, :name_contains, :creation_time_before, :creation_time_after) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] job_definition_summaries # A list of data quality monitoring job definitions. # @return [Array] # # @!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 # @note When making an API call, you may pass ListDeviceFleetsRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # name_contains: "NameContains", # sort_by: "NAME", # accepts NAME, CREATION_TIME, LAST_MODIFIED_TIME # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 # @note When making an API call, you may pass ListDevicesRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # latest_heartbeat_after: Time.now, # model_name: "EntityName", # device_fleet_name: "EntityName", # } # # @!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 # @note When making an API call, you may pass ListDomainsRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # } # # @!attribute [rw] next_token # If the previous response was truncated, you will receive this token. # Use it in your next request to receive the next set of results. # @return [String] # # @!attribute [rw] max_results # Returns a list up to a specified limit. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListDomainsRequest AWS API Documentation # class ListDomainsRequest < Struct.new( :next_token, :max_results) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] domains # The list of domains. # @return [Array] # # @!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 # @note When making an API call, you may pass ListEdgePackagingJobsRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # name_contains: "NameContains", # model_name_contains: "NameContains", # status_equals: "STARTING", # accepts STARTING, INPROGRESS, COMPLETED, FAILED, STOPPING, STOPPED # sort_by: "NAME", # accepts NAME, MODEL_NAME, CREATION_TIME, LAST_MODIFIED_TIME, STATUS # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 # @note When making an API call, you may pass ListEndpointConfigsInput # data as a hash: # # { # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "PaginationToken", # max_results: 1, # name_contains: "EndpointConfigNameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # } # # @!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, Amazon 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 # @note When making an API call, you may pass ListEndpointsInput # data as a hash: # # { # sort_by: "Name", # accepts Name, CreationTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "PaginationToken", # max_results: 1, # name_contains: "EndpointNameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # last_modified_time_before: Time.now, # last_modified_time_after: Time.now, # status_equals: "OutOfService", # accepts OutOfService, Creating, Updating, SystemUpdating, RollingBack, InService, Deleting, Failed # } # # @!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, Amazon 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 # @note When making an API call, you may pass ListExperimentsRequest # data as a hash: # # { # created_after: Time.now, # created_before: Time.now, # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListFeatureGroupsRequest # data as a hash: # # { # name_contains: "FeatureGroupNameContains", # feature_group_status_equals: "Creating", # accepts Creating, Created, CreateFailed, Deleting, DeleteFailed # offline_store_status_equals: "Active", # accepts Active, Blocked, Disabled # creation_time_after: Time.now, # creation_time_before: Time.now, # sort_order: "Ascending", # accepts Ascending, Descending # sort_by: "Name", # accepts Name, FeatureGroupStatus, OfflineStoreStatus, CreationTime # max_results: 1, # next_token: "NextToken", # } # # @!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 # @note When making an API call, you may pass ListFlowDefinitionsRequest # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListHumanTaskUisRequest # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListHyperParameterTuningJobsRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # sort_by: "Name", # accepts Name, Status, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # name_contains: "NameContains", # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # status_equals: "Completed", # accepts Completed, InProgress, Failed, Stopped, Stopping # } # # @!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 objects that describe the # tuning jobs that the `ListHyperParameterTuningJobs` request # returned. # @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 # @note When making an API call, you may pass ListImageVersionsRequest # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # image_name: "ImageName", # required # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # max_results: 1, # next_token: "NextToken", # sort_by: "CREATION_TIME", # accepts CREATION_TIME, LAST_MODIFIED_TIME, VERSION # sort_order: "ASCENDING", # accepts ASCENDING, DESCENDING # } # # @!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 # @note When making an API call, you may pass ListImagesRequest # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # max_results: 1, # name_contains: "ImageNameContains", # next_token: "NextToken", # sort_by: "CREATION_TIME", # accepts CREATION_TIME, LAST_MODIFIED_TIME, IMAGE_NAME # sort_order: "ASCENDING", # accepts ASCENDING, DESCENDING # } # # @!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 # @note When making an API call, you may pass ListLabelingJobsForWorkteamRequest # data as a hash: # # { # workteam_arn: "WorkteamArn", # required # max_results: 1, # next_token: "NextToken", # creation_time_after: Time.now, # creation_time_before: Time.now, # job_reference_code_contains: "JobReferenceCodeContains", # sort_by: "CreationTime", # accepts CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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, Amazon 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 # @note When making an API call, you may pass ListLabelingJobsRequest # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # max_results: 1, # next_token: "NextToken", # name_contains: "NameContains", # sort_by: "Name", # accepts Name, CreationTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # status_equals: "Initializing", # accepts Initializing, InProgress, Completed, Failed, Stopping, Stopped # } # # @!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, Amazon 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 # @note When making an API call, you may pass ListModelBiasJobDefinitionsRequest # data as a hash: # # { # endpoint_name: "EndpointName", # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # name_contains: "NameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # } # # @!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 # If the response is truncated, Amazon SageMaker returns this token. # To retrieve the next set of jobs, use it in the subsequent request. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelBiasJobDefinitionsResponse AWS API Documentation # class ListModelBiasJobDefinitionsResponse < Struct.new( :job_definition_summaries, :next_token) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass ListModelExplainabilityJobDefinitionsRequest # data as a hash: # # { # endpoint_name: "EndpointName", # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # name_contains: "NameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # } # # @!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 # If the response is truncated, Amazon SageMaker returns this token. # To retrieve the next set of jobs, use it in the subsequent request. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelExplainabilityJobDefinitionsResponse AWS API Documentation # class ListModelExplainabilityJobDefinitionsResponse < Struct.new( :job_definition_summaries, :next_token) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass ListModelPackageGroupsInput # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # max_results: 1, # name_contains: "NameContains", # next_token: "NextToken", # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 AWS 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 # @note When making an API call, you may pass ListModelPackagesInput # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # max_results: 1, # name_contains: "NameContains", # model_approval_status: "Approved", # accepts Approved, Rejected, PendingManualApproval # model_package_group_name: "ArnOrName", # model_package_type: "Versioned", # accepts Versioned, Unversioned, Both # next_token: "NextToken", # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 onlyl the model packages of the specified # type. This can be one of the following values. # # * `VERSIONED` - List only versioned models. # # * `UNVERSIONED` - List only unversioined 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, Amazon 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 # @note When making an API call, you may pass ListModelQualityJobDefinitionsRequest # data as a hash: # # { # endpoint_name: "EndpointName", # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # name_contains: "NameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # } # # @!attribute [rw] endpoint_name # A filter that returns only model quality monitoring job definitions # that are associated with the specified endpoint. # @return [String] # # @!attribute [rw] sort_by # The field to sort results by. The default is `CreationTime`. # @return [String] # # @!attribute [rw] sort_order # The sort order for results. The default is `Descending`. # @return [String] # # @!attribute [rw] next_token # If the result of the previous `ListModelQualityJobDefinitions` # request was truncated, the response includes a `NextToken`. To # retrieve the next set of model quality monitoring job definitions, # use the token in the next request. # @return [String] # # @!attribute [rw] max_results # The maximum number of results to return in a call to # `ListModelQualityJobDefinitions`. # @return [Integer] # # @!attribute [rw] name_contains # A string in the transform job name. This filter returns only model # quality monitoring job definitions whose name contains the specified # string. # @return [String] # # @!attribute [rw] creation_time_before # A filter that returns only model quality monitoring job definitions # created before the specified time. # @return [Time] # # @!attribute [rw] creation_time_after # A filter that returns only model quality monitoring job definitions # created after the specified time. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListModelQualityJobDefinitionsRequest AWS API Documentation # class ListModelQualityJobDefinitionsRequest < Struct.new( :endpoint_name, :sort_by, :sort_order, :next_token, :max_results, :name_contains, :creation_time_before, :creation_time_after) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] job_definition_summaries # A list of summaries of model quality monitoring job definitions. # @return [Array] # # @!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 # @note When making an API call, you may pass ListModelsInput # data as a hash: # # { # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "PaginationToken", # max_results: 1, # name_contains: "ModelNameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # } # # @!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 training job name. This filter returns only models # in the training job 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, Amazon 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 # @note When making an API call, you may pass ListMonitoringExecutionsRequest # data as a hash: # # { # monitoring_schedule_name: "MonitoringScheduleName", # endpoint_name: "EndpointName", # sort_by: "CreationTime", # accepts CreationTime, ScheduledTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # scheduled_time_before: Time.now, # scheduled_time_after: Time.now, # creation_time_before: Time.now, # creation_time_after: Time.now, # last_modified_time_before: Time.now, # last_modified_time_after: Time.now, # status_equals: "Pending", # accepts Pending, Completed, CompletedWithViolations, InProgress, Failed, Stopping, Stopped # monitoring_job_definition_name: "MonitoringJobDefinitionName", # monitoring_type_equals: "DataQuality", # accepts DataQuality, ModelQuality, ModelBias, ModelExplainability # } # # @!attribute [rw] monitoring_schedule_name # Name of a specific schedule to fetch jobs for. # @return [String] # # @!attribute [rw] endpoint_name # Name of a specific endpoint to fetch jobs for. # @return [String] # # @!attribute [rw] sort_by # Whether to sort results by `Status`, `CreationTime`, `ScheduledTime` # field. The default is `CreationTime`. # @return [String] # # @!attribute [rw] sort_order # Whether to sort the results in `Ascending` or `Descending` order. # The default is `Descending`. # @return [String] # # @!attribute [rw] next_token # The token returned if the response is truncated. To retrieve the # next set of job executions, use it in the next request. # @return [String] # # @!attribute [rw] max_results # The maximum number of jobs to return in the response. The default # value is 10. # @return [Integer] # # @!attribute [rw] scheduled_time_before # Filter for jobs scheduled before a specified time. # @return [Time] # # @!attribute [rw] scheduled_time_after # Filter for jobs scheduled after a specified time. # @return [Time] # # @!attribute [rw] creation_time_before # A filter that returns only jobs created before a specified time. # @return [Time] # # @!attribute [rw] creation_time_after # A filter that returns only jobs created after a specified time. # @return [Time] # # @!attribute [rw] last_modified_time_before # A filter that returns only jobs modified after a specified time. # @return [Time] # # @!attribute [rw] last_modified_time_after # A filter that returns only jobs modified before a specified time. # @return [Time] # # @!attribute [rw] status_equals # A filter that retrieves only jobs with a specific status. # @return [String] # # @!attribute [rw] monitoring_job_definition_name # Gets a list of the monitoring job runs of the specified monitoring # job definitions. # @return [String] # # @!attribute [rw] monitoring_type_equals # A filter that returns only the monitoring job runs of the specified # monitoring type. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringExecutionsRequest AWS API Documentation # class ListMonitoringExecutionsRequest < Struct.new( :monitoring_schedule_name, :endpoint_name, :sort_by, :sort_order, :next_token, :max_results, :scheduled_time_before, :scheduled_time_after, :creation_time_before, :creation_time_after, :last_modified_time_before, :last_modified_time_after, :status_equals, :monitoring_job_definition_name, :monitoring_type_equals) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] monitoring_execution_summaries # A JSON array in which each element is a summary for a monitoring # execution. # @return [Array] # # @!attribute [rw] next_token # If the response is truncated, Amazon SageMaker returns this token. # To retrieve the next set of jobs, use it in the subsequent reques # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringExecutionsResponse AWS API Documentation # class ListMonitoringExecutionsResponse < Struct.new( :monitoring_execution_summaries, :next_token) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass ListMonitoringSchedulesRequest # data as a hash: # # { # endpoint_name: "EndpointName", # sort_by: "Name", # accepts Name, CreationTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # name_contains: "NameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # last_modified_time_before: Time.now, # last_modified_time_after: Time.now, # status_equals: "Pending", # accepts Pending, Failed, Scheduled, Stopped # monitoring_job_definition_name: "MonitoringJobDefinitionName", # monitoring_type_equals: "DataQuality", # accepts DataQuality, ModelQuality, ModelBias, ModelExplainability # } # # @!attribute [rw] endpoint_name # Name of a specific endpoint to fetch schedules for. # @return [String] # # @!attribute [rw] sort_by # Whether to sort results by `Status`, `CreationTime`, `ScheduledTime` # field. The default is `CreationTime`. # @return [String] # # @!attribute [rw] sort_order # Whether to sort the results in `Ascending` or `Descending` order. # The default is `Descending`. # @return [String] # # @!attribute [rw] next_token # The token returned if the response is truncated. To retrieve the # next set of job executions, use it in the next request. # @return [String] # # @!attribute [rw] max_results # The maximum number of jobs to return in the response. The default # value is 10. # @return [Integer] # # @!attribute [rw] name_contains # Filter for monitoring schedules whose name contains a specified # string. # @return [String] # # @!attribute [rw] creation_time_before # A filter that returns only monitoring schedules created before a # specified time. # @return [Time] # # @!attribute [rw] creation_time_after # A filter that returns only monitoring schedules created after a # specified time. # @return [Time] # # @!attribute [rw] last_modified_time_before # A filter that returns only monitoring schedules modified before a # specified time. # @return [Time] # # @!attribute [rw] last_modified_time_after # A filter that returns only monitoring schedules modified after a # specified time. # @return [Time] # # @!attribute [rw] status_equals # A filter that returns only monitoring schedules modified before a # specified time. # @return [String] # # @!attribute [rw] monitoring_job_definition_name # Gets a list of the monitoring schedules for the specified monitoring # job definition. # @return [String] # # @!attribute [rw] monitoring_type_equals # A filter that returns only the monitoring schedules for the # specified monitoring type. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringSchedulesRequest AWS API Documentation # class ListMonitoringSchedulesRequest < Struct.new( :endpoint_name, :sort_by, :sort_order, :next_token, :max_results, :name_contains, :creation_time_before, :creation_time_after, :last_modified_time_before, :last_modified_time_after, :status_equals, :monitoring_job_definition_name, :monitoring_type_equals) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] monitoring_schedule_summaries # A JSON array in which each element is a summary for a monitoring # schedule. # @return [Array] # # @!attribute [rw] next_token # If the response is truncated, Amazon SageMaker returns this token. # To retrieve the next set of jobs, use it in the subsequent request. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListMonitoringSchedulesResponse AWS API Documentation # class ListMonitoringSchedulesResponse < Struct.new( :monitoring_schedule_summaries, :next_token) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass ListNotebookInstanceLifecycleConfigsInput # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # sort_by: "Name", # accepts Name, CreationTime, LastModifiedTime # sort_order: "Ascending", # accepts Ascending, Descending # name_contains: "NotebookInstanceLifecycleConfigNameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # last_modified_time_before: Time.now, # last_modified_time_after: Time.now, # } # # @!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, Amazon 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 # @note When making an API call, you may pass ListNotebookInstancesInput # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # sort_by: "Name", # accepts Name, CreationTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # name_contains: "NotebookInstanceNameContains", # creation_time_before: Time.now, # creation_time_after: Time.now, # last_modified_time_before: Time.now, # last_modified_time_after: Time.now, # status_equals: "Pending", # accepts Pending, InService, Stopping, Stopped, Failed, Deleting, Updating # notebook_instance_lifecycle_config_name_contains: "NotebookInstanceLifecycleConfigName", # default_code_repository_contains: "CodeRepositoryContains", # additional_code_repository_equals: "CodeRepositoryNameOrUrl", # } # # @!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, Amazon 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 # @note When making an API call, you may pass ListPipelineExecutionStepsRequest # data as a hash: # # { # pipeline_execution_arn: "PipelineExecutionArn", # next_token: "NextToken", # max_results: 1, # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 # @note When making an API call, you may pass ListPipelineExecutionsRequest # data as a hash: # # { # pipeline_name: "PipelineName", # required # created_after: Time.now, # created_before: Time.now, # sort_by: "CreationTime", # accepts CreationTime, PipelineExecutionArn # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!attribute [rw] pipeline_name # The name of the pipeline. # @return [String] # # @!attribute [rw] created_after # A filter that returns the pipeline executions that were created # after a specified time. # @return [Time] # # @!attribute [rw] created_before # A filter that returns the pipeline executions that were created # before a specified time. # @return [Time] # # @!attribute [rw] sort_by # The field by which to sort results. The default is `CreatedTime`. # @return [String] # # @!attribute [rw] sort_order # The sort order for results. # @return [String] # # @!attribute [rw] next_token # If the result of the previous `ListPipelineExecutions` request was # truncated, the response includes a `NextToken`. To retrieve the next # set of pipeline executions, use the token in the next request. # @return [String] # # @!attribute [rw] max_results # The maximum number of pipeline executions to return in the response. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListPipelineExecutionsRequest AWS API Documentation # class ListPipelineExecutionsRequest < Struct.new( :pipeline_name, :created_after, :created_before, :sort_by, :sort_order, :next_token, :max_results) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] pipeline_execution_summaries # Contains a sorted list of pipeline execution summary objects # matching the specified filters. Each run summary includes the Amazon # Resource Name (ARN) of the pipeline execution, the run date, and the # status. This list can be empty. # @return [Array] # # @!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 # @note When making an API call, you may pass ListPipelineParametersForExecutionRequest # data as a hash: # # { # pipeline_execution_arn: "PipelineExecutionArn", # required # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListPipelinesRequest # data as a hash: # # { # pipeline_name_prefix: "PipelineName", # created_after: Time.now, # created_before: Time.now, # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListProcessingJobsRequest # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # name_contains: "String", # status_equals: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped # sort_by: "Name", # accepts Name, CreationTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListProjectsInput # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # max_results: 1, # name_contains: "ProjectEntityName", # next_token: "NextToken", # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 # @note When making an API call, you may pass ListSubscribedWorkteamsRequest # data as a hash: # # { # name_contains: "WorkteamName", # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListTagsInput # data as a hash: # # { # resource_arn: "ResourceArn", # required # next_token: "NextToken", # max_results: 1, # } # # @!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, # Amazon 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, Amazon 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 # @note When making an API call, you may pass ListTrainingJobsForHyperParameterTuningJobRequest # data as a hash: # # { # hyper_parameter_tuning_job_name: "HyperParameterTuningJobName", # required # next_token: "NextToken", # max_results: 1, # status_equals: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped # sort_by: "Name", # accepts Name, CreationTime, Status, FinalObjectiveMetricValue # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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 objects that describe the training jobs # that the `ListTrainingJobsForHyperParameterTuningJob` request # returned. # @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 # @note When making an API call, you may pass ListTrainingJobsRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # name_contains: "NameContains", # status_equals: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped # sort_by: "Name", # accepts Name, CreationTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # } # # @!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] # # @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) 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, Amazon 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 # @note When making an API call, you may pass ListTransformJobsRequest # data as a hash: # # { # creation_time_after: Time.now, # creation_time_before: Time.now, # last_modified_time_after: Time.now, # last_modified_time_before: Time.now, # name_contains: "NameContains", # status_equals: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped # sort_by: "Name", # accepts Name, CreationTime, Status # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListTrialComponentsRequest # data as a hash: # # { # experiment_name: "ExperimentEntityName", # trial_name: "ExperimentEntityName", # source_arn: "String256", # created_after: Time.now, # created_before: Time.now, # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # max_results: 1, # next_token: "NextToken", # } # # @!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 # @note When making an API call, you may pass ListTrialsRequest # data as a hash: # # { # experiment_name: "ExperimentEntityName", # trial_component_name: "ExperimentEntityName", # created_after: Time.now, # created_before: Time.now, # sort_by: "Name", # accepts Name, CreationTime # sort_order: "Ascending", # accepts Ascending, Descending # max_results: 1, # next_token: "NextToken", # } # # @!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 # @note When making an API call, you may pass ListUserProfilesRequest # data as a hash: # # { # next_token: "NextToken", # max_results: 1, # sort_order: "Ascending", # accepts Ascending, Descending # sort_by: "CreationTime", # accepts CreationTime, LastModifiedTime # domain_id_equals: "DomainId", # user_profile_name_contains: "UserProfileName", # } # # @!attribute [rw] next_token # If the previous response was truncated, you will receive this token. # Use it in your next request to receive the next set of results. # @return [String] # # @!attribute [rw] max_results # Returns a list up to a specified limit. # @return [Integer] # # @!attribute [rw] sort_order # The sort order for the results. The default is Ascending. # @return [String] # # @!attribute [rw] sort_by # The parameter by which to sort the results. The default is # CreationTime. # @return [String] # # @!attribute [rw] domain_id_equals # A parameter by which to filter the results. # @return [String] # # @!attribute [rw] user_profile_name_contains # A parameter by which to filter the results. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListUserProfilesRequest AWS API Documentation # class ListUserProfilesRequest < Struct.new( :next_token, :max_results, :sort_order, :sort_by, :domain_id_equals, :user_profile_name_contains) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] user_profiles # The list of user profiles. # @return [Array] # # @!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 # @note When making an API call, you may pass ListWorkforcesRequest # data as a hash: # # { # sort_by: "Name", # accepts Name, CreateDate # sort_order: "Ascending", # accepts Ascending, Descending # name_contains: "WorkforceName", # next_token: "NextToken", # max_results: 1, # } # # @!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 # @note When making an API call, you may pass ListWorkteamsRequest # data as a hash: # # { # sort_by: "Name", # accepts Name, CreateDate # sort_order: "Ascending", # accepts Ascending, Descending # name_contains: "WorkteamName", # next_token: "NextToken", # max_results: 1, # } # # @!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. # # @note When making an API call, you may pass MemberDefinition # data as a hash: # # { # cognito_member_definition: { # user_pool: "CognitoUserPool", # required # user_group: "CognitoUserGroup", # required # client_id: "ClientId", # required # }, # oidc_member_definition: { # groups: ["Group"], # required # }, # } # # @!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. # # @note When making an API call, you may pass MetadataProperties # data as a hash: # # { # commit_id: "MetadataPropertyValue", # repository: "MetadataPropertyValue", # generated_by: "MetadataPropertyValue", # project_id: "MetadataPropertyValue", # } # # @!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 # Specifies a metric that the training algorithm writes to `stderr` or # `stdout` . Amazon SageMakerhyperparameter tuning captures all defined # metrics. You specify one metric that a hyperparameter tuning job uses # as its objective metric to choose the best training job. # # @note When making an API call, you may pass MetricDefinition # data as a hash: # # { # name: "MetricName", # required # regex: "MetricRegex", # required # } # # @!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 Objective # Metrics][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics.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 # @note When making an API call, you may pass MetricsSource # data as a hash: # # { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # } # # @!attribute [rw] content_type # @return [String] # # @!attribute [rw] content_digest # @return [String] # # @!attribute [rw] s3_uri # @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 # Provides information about the location that is configured for storing # model artifacts. # # Model artifacts are the output that results from training a model, and # typically consist of trained parameters, a model defintion that # describes how to compute inferences, and other metadata. # # @!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. # # @note When making an API call, you may pass ModelBiasAppSpecification # data as a hash: # # { # image_uri: "ImageUri", # required # config_uri: "S3Uri", # required # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # } # # @!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/json-bias-parameter-config.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. # # @note When making an API call, you may pass ModelBiasBaselineConfig # data as a hash: # # { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # } # # @!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. # # @note When making an API call, you may pass ModelBiasJobInput # data as a hash: # # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # ground_truth_s3_input: { # required # s3_uri: "MonitoringS3Uri", # }, # } # # @!attribute [rw] endpoint_input # Input object for the endpoint # @return [Types::EndpointInput] # # @!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, :ground_truth_s3_input) SENSITIVE = [] include Aws::Structure end # Configures the timeout and maximum number of retries for processing a # transform job invocation. # # @note When making an API call, you may pass ModelClientConfig # data as a hash: # # { # invocations_timeout_in_seconds: 1, # invocations_max_retries: 1, # } # # @!attribute [rw] invocations_timeout_in_seconds # The timeout value in seconds for an invocation request. # @return [Integer] # # @!attribute [rw] invocations_max_retries # The maximum number of retries when invocation requests are failing. # @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 # Data quality constraints and statistics for a model. # # @note When making an API call, you may pass ModelDataQuality # data as a hash: # # { # statistics: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # constraints: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # } # # @!attribute [rw] statistics # Data quality statistics for a model. # @return [Types::MetricsSource] # # @!attribute [rw] constraints # Data quality constraints for a model. # @return [Types::MetricsSource] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelDataQuality AWS API Documentation # class ModelDataQuality < Struct.new( :statistics, :constraints) SENSITIVE = [] include Aws::Structure end # Specifies how to generate the endpoint name for an automatic one-click # Autopilot model deployment. # # @note When making an API call, you may pass ModelDeployConfig # data as a hash: # # { # auto_generate_endpoint_name: false, # endpoint_name: "EndpointName", # } # # @!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. # # @note When making an API call, you may pass ModelExplainabilityAppSpecification # data as a hash: # # { # image_uri: "ImageUri", # required # config_uri: "S3Uri", # required # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # } # # @!attribute [rw] image_uri # The container image to be run by the model explainability job. # @return [String] # # @!attribute [rw] config_uri # JSON formatted S3 file that defines explainability parameters. For # more information on this JSON configuration file, see [Configure # model explainability parameters][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/json-model-explainability-parameter-config.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. # # @note When making an API call, you may pass ModelExplainabilityBaselineConfig # data as a hash: # # { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # } # # @!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. # # @note When making an API call, you may pass ModelExplainabilityJobInput # data as a hash: # # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # } # # @!attribute [rw] endpoint_input # Input object for the endpoint # @return [Types::EndpointInput] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelExplainabilityJobInput AWS API Documentation # class ModelExplainabilityJobInput < Struct.new( :endpoint_input) SENSITIVE = [] include Aws::Structure end # Contains metrics captured from a model. # # @note When making an API call, you may pass ModelMetrics # data as a hash: # # { # model_quality: { # statistics: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # constraints: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # }, # model_data_quality: { # statistics: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # constraints: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # }, # bias: { # report: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # }, # explainability: { # report: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # }, # } # # @!attribute [rw] model_quality # Metrics that measure the quality of a model. # @return [Types::ModelQuality] # # @!attribute [rw] model_data_quality # Metrics that measure the quality of the input data for a model. # @return [Types::ModelDataQuality] # # @!attribute [rw] bias # Metrics that measure bais in a model. # @return [Types::Bias] # # @!attribute [rw] explainability # Metrics that help explain a model. # @return [Types::Explainability] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelMetrics AWS API Documentation # class ModelMetrics < Struct.new( :model_quality, :model_data_quality, :bias, :explainability) SENSITIVE = [] include Aws::Structure end # A versioned model that can be deployed for SageMaker inference. # # @!attribute [rw] model_package_name # The name of the model. # @return [String] # # @!attribute [rw] model_package_group_name # The model group to which the model belongs. # @return [String] # # @!attribute [rw] model_package_version # The version number of a versioned model. # @return [Integer] # # @!attribute [rw] model_package_arn # The Amazon Resource Name (ARN) of the model package. # @return [String] # # @!attribute [rw] model_package_description # The description of the model package. # @return [String] # # @!attribute [rw] creation_time # The time that the model package was created. # @return [Time] # # @!attribute [rw] inference_specification # Defines how to perform inference generation after a training job is # run. # @return [Types::InferenceSpecification] # # @!attribute [rw] source_algorithm_specification # A list of algorithms that were used to create a model package. # @return [Types::SourceAlgorithmSpecification] # # @!attribute [rw] validation_specification # Specifies batch transform jobs that Amazon 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 AWS # Marketplace. For information about listing model packages on AWS # Marketplace, see [List Your Algorithm or Model Package on AWS # 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, or trial component. # @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, or trial component. # @return [Types::UserContext] # # @!attribute [rw] approval_description # A description provided when the model approval is set. # @return [String] # # @!attribute [rw] tags # A list of the tags associated with the model package. For more # information, see [Tagging AWS resources][1] in the *AWS 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/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, :tags) SENSITIVE = [] include Aws::Structure end # Describes the Docker container for the model package. # # @note When making an API call, you may pass ModelPackageContainerDefinition # data as a hash: # # { # container_hostname: "ContainerHostname", # image: "ContainerImage", # required # image_digest: "ImageDigest", # model_data_url: "Url", # product_id: "ProductId", # } # # @!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 Amazon SageMaker, the inference code must meet Amazon # SageMaker requirements. Amazon 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] product_id # The AWS Marketplace product ID of the model package. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelPackageContainerDefinition AWS API Documentation # class ModelPackageContainerDefinition < Struct.new( :container_hostname, :image, :image_digest, :model_data_url, :product_id) 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, or trial component. # @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 AWS resources][1] in the *AWS 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 AWS Marketplace. # # @note When making an API call, you may pass ModelPackageValidationProfile # data as a hash: # # { # profile_name: "EntityName", # required # transform_job_definition: { # required # max_concurrent_transforms: 1, # max_payload_in_mb: 1, # batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord # environment: { # "TransformEnvironmentKey" => "TransformEnvironmentValue", # }, # transform_input: { # required # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # }, # transform_output: { # required # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # }, # transform_resources: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # } # # @!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 Amazon SageMaker runs to validate # your model package. # # @note When making an API call, you may pass ModelPackageValidationSpecification # data as a hash: # # { # validation_role: "RoleArn", # required # validation_profiles: [ # required # { # profile_name: "EntityName", # required # transform_job_definition: { # required # max_concurrent_transforms: 1, # max_payload_in_mb: 1, # batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord # environment: { # "TransformEnvironmentKey" => "TransformEnvironmentValue", # }, # transform_input: { # required # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # }, # transform_output: { # required # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # }, # transform_resources: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # }, # ], # } # # @!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 Amazon 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. # # @note When making an API call, you may pass ModelQuality # data as a hash: # # { # statistics: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # constraints: { # content_type: "ContentType", # required # content_digest: "ContentDigest", # s3_uri: "S3Uri", # required # }, # } # # @!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. # # @note When making an API call, you may pass ModelQualityAppSpecification # data as a hash: # # { # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # problem_type: "BinaryClassification", # accepts BinaryClassification, MulticlassClassification, Regression # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # } # # @!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 # flatted json so that the built-in container can use the converted # data. Applicable only for the built-in (first party) containers. # @return [String] # # @!attribute [rw] post_analytics_processor_source_uri # An Amazon S3 URI to a script that is called after analysis has been # performed. Applicable only for the built-in (first party) # containers. # @return [String] # # @!attribute [rw] problem_type # The machine learning problem type of the model that the monitoring # job monitors. # @return [String] # # @!attribute [rw] environment # Sets the environment variables in the container that the monitoring # job runs. # @return [Hash] # # @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. # # @note When making an API call, you may pass ModelQualityBaselineConfig # data as a hash: # # { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # } # # @!attribute [rw] baselining_job_name # The name of the job that performs baselining for the monitoring job. # @return [String] # # @!attribute [rw] constraints_resource # The constraints resource for a monitoring job. # @return [Types::MonitoringConstraintsResource] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ModelQualityBaselineConfig AWS API Documentation # class ModelQualityBaselineConfig < Struct.new( :baselining_job_name, :constraints_resource) SENSITIVE = [] include Aws::Structure end # The input for the model quality monitoring job. Currently endponts are # supported for input for model quality monitoring jobs. # # @note When making an API call, you may pass ModelQualityJobInput # data as a hash: # # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # ground_truth_s3_input: { # required # s3_uri: "MonitoringS3Uri", # }, # } # # @!attribute [rw] endpoint_input # Input object for the endpoint # @return [Types::EndpointInput] # # @!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, :ground_truth_s3_input) 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 # Container image configuration object for the monitoring job. # # @note When making an API call, you may pass MonitoringAppSpecification # data as a hash: # # { # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # } # # @!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 # flatted json so that the built-in container can use the converted # data. Applicable only for the built-in (first party) containers. # @return [String] # # @!attribute [rw] post_analytics_processor_source_uri # An Amazon S3 URI to a script that is called after analysis has been # performed. Applicable only for the built-in (first party) # containers. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringAppSpecification AWS API Documentation # class MonitoringAppSpecification < Struct.new( :image_uri, :container_entrypoint, :container_arguments, :record_preprocessor_source_uri, :post_analytics_processor_source_uri) SENSITIVE = [] include Aws::Structure end # Configuration for monitoring constraints and monitoring statistics. # These baseline resources are compared against the results of the # current job from the series of jobs scheduled to collect data # periodically. # # @note When making an API call, you may pass MonitoringBaselineConfig # data as a hash: # # { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # statistics_resource: { # s3_uri: "S3Uri", # }, # } # # @!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. # # @note When making an API call, you may pass MonitoringClusterConfig # data as a hash: # # { # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # } # # @!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 AWS Key Management Service (AWS 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. # # @note When making an API call, you may pass MonitoringConstraintsResource # data as a hash: # # { # s3_uri: "S3Uri", # } # # @!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 # 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. # # @note When making an API call, you may pass MonitoringGroundTruthS3Input # data as a hash: # # { # s3_uri: "MonitoringS3Uri", # } # # @!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. # # @note When making an API call, you may pass MonitoringInput # data as a hash: # # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # } # # @!attribute [rw] endpoint_input # The endpoint for a monitoring job. # @return [Types::EndpointInput] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringInput AWS API Documentation # class MonitoringInput < Struct.new( :endpoint_input) SENSITIVE = [] include Aws::Structure end # Defines the monitoring job. # # @note When making an API call, you may pass MonitoringJobDefinition # data as a hash: # # { # baseline_config: { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # statistics_resource: { # s3_uri: "S3Uri", # }, # }, # monitoring_inputs: [ # required # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # }, # ], # monitoring_output_config: { # required # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # }, # monitoring_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # monitoring_app_specification: { # required # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # }, # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # } # # @!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 Simple Storage Service (Amazon S3). # @return [Types::MonitoringOutputConfig] # # @!attribute [rw] monitoring_resources # Identifies the resources, ML compute instances, and ML storage # volumes to deploy for a monitoring job. In distributed processing, # you specify more than one instance. # @return [Types::MonitoringResources] # # @!attribute [rw] monitoring_app_specification # Configures the monitoring job to run a specified Docker container # image. # @return [Types::MonitoringAppSpecification] # # @!attribute [rw] stopping_condition # Specifies a time limit for how long the monitoring job is allowed to # run. # @return [Types::MonitoringStoppingCondition] # # @!attribute [rw] environment # Sets the environment variables in the Docker container. # @return [Hash] # # @!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 # The networking configuration for the monitoring job. # # @note When making an API call, you may pass MonitoringNetworkConfig # data as a hash: # # { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # } # # @!attribute [rw] enable_inter_container_traffic_encryption # Whether to encrypt all communications between the instances used for # the monitoring jobs. Choose `True` to encrypt communications. # Encryption provides greater security for distributed jobs, but the # processing might take longer. # @return [Boolean] # # @!attribute [rw] enable_network_isolation # Whether to allow inbound and outbound network calls to and from the # containers used for the monitoring job. # @return [Boolean] # # @!attribute [rw] vpc_config # Specifies a VPC that your training jobs and hosted models have # access to. Control access to and from your training and model # containers by configuring the VPC. For more information, see # [Protect Endpoints by Using an Amazon Virtual Private Cloud][1] and # [Protect Training Jobs by Using an Amazon Virtual Private Cloud][2]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html # @return [Types::VpcConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/MonitoringNetworkConfig AWS API Documentation # class MonitoringNetworkConfig < Struct.new( :enable_inter_container_traffic_encryption, :enable_network_isolation, :vpc_config) SENSITIVE = [] include Aws::Structure end # The output object for a monitoring job. # # @note When making an API call, you may pass MonitoringOutput # data as a hash: # # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # } # # @!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. # # @note When making an API call, you may pass MonitoringOutputConfig # data as a hash: # # { # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # } # # @!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 AWS Key Management Service (AWS 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 # Identifies the resources to deploy for a monitoring job. # # @note When making an API call, you may pass MonitoringResources # data as a hash: # # { # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # } # # @!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. # # @note When making an API call, you may pass MonitoringS3Output # data as a hash: # # { # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # } # # @!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 AWS resources][1] in the *AWS 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. # # @note When making an API call, you may pass MonitoringScheduleConfig # data as a hash: # # { # schedule_config: { # schedule_expression: "ScheduleExpression", # required # }, # monitoring_job_definition: { # baseline_config: { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # statistics_resource: { # s3_uri: "S3Uri", # }, # }, # monitoring_inputs: [ # required # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # }, # ], # monitoring_output_config: { # required # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # }, # monitoring_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # monitoring_app_specification: { # required # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # }, # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # }, # monitoring_job_definition_name: "MonitoringJobDefinitionName", # monitoring_type: "DataQuality", # accepts DataQuality, ModelQuality, ModelBias, ModelExplainability # } # # @!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. # # @note When making an API call, you may pass MonitoringStatisticsResource # data as a hash: # # { # s3_uri: "S3Uri", # } # # @!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. # # @note When making an API call, you may pass MonitoringStoppingCondition # data as a hash: # # { # max_runtime_in_seconds: 1, # required # } # # @!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. # # @note When making an API call, you may pass MultiModelConfig # data as a hash: # # { # model_cache_setting: "Enabled", # accepts Enabled, Disabled # } # # @!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 # A list of nested Filter objects. A resource must satisfy the # conditions of all filters to be included in the results returned from # the Search API. # # For example, to filter on a training job's `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"\}'` # # @note When making an API call, you may pass NestedFilters # data as a hash: # # { # nested_property_name: "ResourcePropertyName", # required # filters: [ # required # { # name: "ResourcePropertyName", # required # operator: "Equals", # accepts Equals, NotEquals, GreaterThan, GreaterThanOrEqualTo, LessThan, LessThanOrEqualTo, Contains, Exists, NotExists, In # value: "FilterValue", # }, # ], # } # # @!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. # # @note When making an API call, you may pass NetworkConfig # data as a hash: # # { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # } # # @!attribute [rw] enable_inter_container_traffic_encryption # Whether to encrypt all communications between distributed processing # jobs. Choose `True` to encrypt communications. Encryption provides # greater security for distributed processing jobs, but the processing # might take longer. # @return [Boolean] # # @!attribute [rw] enable_network_isolation # Whether to allow inbound and outbound network calls to and from the # containers used for the processing job. # @return [Boolean] # # @!attribute [rw] vpc_config # Specifies a VPC that your training jobs and hosted models have # access to. Control access to and from your training and model # containers by configuring the VPC. For more information, see # [Protect Endpoints by Using an Amazon Virtual Private Cloud][1] and # [Protect Training Jobs by Using an Amazon Virtual Private Cloud][2]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html # @return [Types::VpcConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NetworkConfig AWS API Documentation # class NetworkConfig < Struct.new( :enable_inter_container_traffic_encryption, :enable_network_isolation, :vpc_config) SENSITIVE = [] include Aws::Structure end # Provides a summary of a notebook instance lifecycle configuration. # # @!attribute [rw] notebook_instance_lifecycle_config_name # The name of the lifecycle configuration. # @return [String] # # @!attribute [rw] notebook_instance_lifecycle_config_arn # The Amazon Resource Name (ARN) of the lifecycle configuration. # @return [String] # # @!attribute [rw] creation_time # A timestamp that tells when the lifecycle configuration was created. # @return [Time] # # @!attribute [rw] last_modified_time # A timestamp that tells when the lifecycle configuration was last # modified. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/NotebookInstanceLifecycleConfigSummary AWS API Documentation # class NotebookInstanceLifecycleConfigSummary < Struct.new( :notebook_instance_lifecycle_config_name, :notebook_instance_lifecycle_config_arn, :creation_time, :last_modified_time) SENSITIVE = [] include Aws::Structure end # Contains the notebook instance lifecycle configuration script. # # Each lifecycle configuration script has a limit of 16384 characters. # # The value of the `$PATH` environment variable that is available to # both scripts is `/sbin:bin:/usr/sbin:/usr/bin`. # # View CloudWatch Logs for notebook instance lifecycle configurations in # log group `/aws/sagemaker/NotebookInstances` in log stream # `[notebook-instance-name]/[LifecycleConfigHook]`. # # Lifecycle configuration scripts cannot run for longer than 5 minutes. # If a script runs for longer than 5 minutes, it fails and the notebook # instance is not created or started. # # For information about notebook instance lifestyle configurations, see # [Step 2.1: (Optional) Customize a Notebook Instance][1]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html # # @note When making an API call, you may pass NotebookInstanceLifecycleHook # data as a hash: # # { # content: "NotebookInstanceLifecycleConfigContent", # } # # @!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 Amazon 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 instance 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 [AWS 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 Amazon 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 [AWS 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 Amazon 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 SNS notifications of available or expiring work items for # work teams. # # @note When making an API call, you may pass NotificationConfiguration # data as a hash: # # { # notification_topic_arn: "NotificationTopicArn", # } # # @!attribute [rw] notification_topic_arn # The ARN for the 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 # AWS Key Management Service (KMS) key ID, or `KMSKeyId`, in # `S3StorageConfig`. # # @note When making an API call, you may pass OfflineStoreConfig # data as a hash: # # { # s3_storage_config: { # required # s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # resolved_output_s3_uri: "S3Uri", # }, # disable_glue_table_creation: false, # data_catalog_config: { # table_name: "TableName", # required # catalog: "Catalog", # required # database: "Database", # required # }, # } # # @!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 AWS Glue table # when configuring an `OfflineStore`. # @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] # # @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) 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). # # @note When making an API call, you may pass OidcConfig # data as a hash: # # { # client_id: "ClientId", # required # client_secret: "ClientSecret", # required # issuer: "OidcEndpoint", # required # authorization_endpoint: "OidcEndpoint", # required # token_endpoint: "OidcEndpoint", # required # user_info_endpoint: "OidcEndpoint", # required # logout_endpoint: "OidcEndpoint", # required # jwks_uri: "OidcEndpoint", # required # } # # @!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. # # @note When making an API call, you may pass OidcMemberDefinition # data as a hash: # # { # groups: ["Group"], # required # } # # @!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 AWS 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`. # # @note When making an API call, you may pass OnlineStoreConfig # data as a hash: # # { # security_config: { # kms_key_id: "KmsKeyId", # }, # enable_online_store: false, # } # # @!attribute [rw] security_config # Use to specify KMS Key ID (`KMSKeyId`) for at-rest encryption of # your `OnlineStore`. # @return [Types::OnlineStoreSecurityConfig] # # @!attribute [rw] enable_online_store # Turn `OnlineStore` off by specifying `False` for the # `EnableOnlineStore` flag. Turn `OnlineStore` on by specifying `True` # for the `EnableOnlineStore` flag. # # The default value is `False`. # @return [Boolean] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OnlineStoreConfig AWS API Documentation # class OnlineStoreConfig < Struct.new( :security_config, :enable_online_store) SENSITIVE = [] include Aws::Structure end # The security configuration for `OnlineStore`. # # @note When making an API call, you may pass OnlineStoreSecurityConfig # data as a hash: # # { # kms_key_id: "KmsKeyId", # } # # @!attribute [rw] kms_key_id # The ID of the AWS Key Management Service (AWS KMS) key that # SageMaker Feature Store uses to encrypt the Amazon S3 objects at # rest using Amazon S3 server-side encryption. # # The caller (either IAM 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 IAM 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. # # @note When making an API call, you may pass OutputConfig # data as a hash: # # { # s3_output_location: "S3Uri", # required # target_device: "lambda", # accepts lambda, ml_m4, ml_m5, ml_c4, ml_c5, ml_p2, ml_p3, ml_g4dn, ml_inf1, ml_eia2, jetson_tx1, jetson_tx2, jetson_nano, jetson_xavier, rasp3b, imx8qm, deeplens, rk3399, rk3288, aisage, sbe_c, qcs605, qcs603, sitara_am57x, amba_cv22, x86_win32, x86_win64, coreml, jacinto_tda4vm # target_platform: { # os: "ANDROID", # required, accepts ANDROID, LINUX # arch: "X86_64", # required, accepts X86_64, X86, ARM64, ARM_EABI, ARM_EABIHF # accelerator: "INTEL_GRAPHICS", # accepts INTEL_GRAPHICS, MALI, NVIDIA # }, # compiler_options: "CompilerOptions", # kms_key_id: "KmsKeyId", # } # # @!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 fields. It can be used instead of # `TargetPlatform`. # @return [String] # # @!attribute [rw] target_platform # Contains information about a target platform that you want your # model to run on, such as OS, architecture, and accelerators. It is # an alternative of `TargetDevice`. # # The following examples show how to configure the `TargetPlatform` # and `CompilerOptions` JSON strings for popular target platforms: # # * Raspberry Pi 3 Model B+ # # `"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM_EABIHF"\},` # # ` "CompilerOptions": \{'mattr': ['+neon']\}` # # * Jetson TX2 # # `"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM64", # "Accelerator": "NVIDIA"\},` # # ` "CompilerOptions": \{'gpu-code': 'sm_62', 'trt-ver': '6.0.1', # 'cuda-ver': '10.0'\}` # # * EC2 m5.2xlarge instance OS # # `"TargetPlatform": \{"Os": "LINUX", "Arch": "X86_64", # "Accelerator": "NVIDIA"\},` # # ` "CompilerOptions": \{'mcpu': 'skylake-avx512'\}` # # * RK3399 # # `"TargetPlatform": \{"Os": "LINUX", "Arch": "ARM64", # "Accelerator": "MALI"\}` # # * ARMv7 phone (CPU) # # `"TargetPlatform": \{"Os": "ANDROID", "Arch": "ARM_EABI"\},` # # ` "CompilerOptions": \{'ANDROID_PLATFORM': 25, 'mattr': # ['+neon']\}` # # * ARMv8 phone (CPU) # # `"TargetPlatform": \{"Os": "ANDROID", "Arch": "ARM64"\},` # # ` "CompilerOptions": \{'ANDROID_PLATFORM': 29\}` # @return [Types::TargetPlatform] # # @!attribute [rw] compiler_options # Specifies additional parameters for compiler options in JSON format. # The compiler options are `TargetPlatform` specific. It is required # for NVIDIA accelerators and highly recommended for CPU compilations. # For any other cases, it is optional to specify `CompilerOptions.` # # * `DTYPE`\: Specifies the data type for the input. When compiling # for `ml_*` (except for `ml_inf`) instances using PyTorch # framework, provide the data type (dtype) of the model's input. # `"float32"` is used if `"DTYPE"` is not specified. Options for # data type are: # # * float32: Use either `"float"` or `"float32"`. # # * int64: Use either `"int64"` or `"long"`. # # For example, `\{"dtype" : "float32"\}`. # # * `CPU`\: Compilation for CPU supports the following compiler # options. # # * `mcpu`\: CPU micro-architecture. For example, `\{'mcpu': # 'skylake-avx512'\}` # # * `mattr`\: CPU flags. For example, `\{'mattr': ['+neon', # '+vfpv4']\}` # # * `ARM`\: Details of ARM CPU compilations. # # * `NEON`\: NEON is an implementation of the Advanced SIMD # extension used in ARMv7 processors. # # For example, add `\{'mattr': ['+neon']\}` to the compiler # options if compiling for ARM 32-bit platform with the NEON # support. # # * `NVIDIA`\: Compilation for NVIDIA GPU supports the following # compiler options. # # * `gpu_code`\: Specifies the targeted architecture. # # * `trt-ver`\: Specifies the TensorRT versions in x.y.z. format. # # * `cuda-ver`\: Specifies the CUDA version in x.y format. # # For example, `\{'gpu-code': 'sm_72', 'trt-ver': '6.0.1', # 'cuda-ver': '10.1'\}` # # * `ANDROID`\: Compilation for the Android OS supports the following # compiler options: # # * `ANDROID_PLATFORM`\: Specifies the Android API levels. Available # levels range from 21 to 29. For example, `\{'ANDROID_PLATFORM': # 28\}`. # # * `mattr`\: Add `\{'mattr': ['+neon']\}` to compiler options if # compiling for ARM 32-bit platform with NEON support. # # * `INFERENTIA`\: Compilation for target ml\_inf1 uses compiler # options passed in as a JSON string. For example, # `"CompilerOptions": ""--verbose 1 --num-neuroncores 2 -O2""`. # # For information about supported compiler options, see [ Neuron # Compiler CLI][1]. # # * `CoreML`\: Compilation for the CoreML OutputConfig$TargetDevice # supports the following compiler options: # # * `class_labels`\: Specifies the classification labels file name # inside input tar.gz file. For example, `\{"class_labels": # "imagenet_labels_1000.txt"\}`. Labels inside the txt file should # be separated by newlines. # # ^ # # * `EIA`\: Compilation for the Elastic Inference Accelerator supports # the following compiler options: # # * `precision_mode`\: Specifies the precision of compiled # artifacts. Supported values are `"FP16"` and `"FP32"`. Default # is `"FP32"`. # # * `signature_def_key`\: Specifies the signature to use for models # in SavedModel format. Defaults is TensorFlow's default # signature def key. # # * `output_names`\: Specifies a list of output tensor names for # models in FrozenGraph format. Set at most one API field, either: # `signature_def_key` or `output_names`. # # For example: `\{"precision_mode": "FP32", "output_names": # ["output:0"]\}` # # # # [1]: https://github.com/aws/aws-neuron-sdk/blob/master/docs/neuron-cc/command-line-reference.md # @return [String] # # @!attribute [rw] kms_key_id # The AWS Key Management Service (AWS 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 # # 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] # # @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). # # @note When making an API call, you may pass OutputDataConfig # data as a hash: # # { # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # } # # @!attribute [rw] kms_key_id # The AWS Key Management Service (AWS 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: # # * // 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 master 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 `CreateTrainingJob`, `CreateTransformJob`, or # `CreateHyperParameterTuningJob` requests. For more information, see # [Using Key Policies in AWS KMS][2] in the *AWS 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 Amazon SageMaker to store the # model artifacts. For example, `s3://bucket-name/key-name-prefix`. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/OutputDataConfig AWS API Documentation # class OutputDataConfig < Struct.new( :kms_key_id, :s3_output_path) SENSITIVE = [] include Aws::Structure end # An output parameter of a pipeline step. # # @note When making an API call, you may pass OutputParameter # data as a hash: # # { # name: "String256", # required # value: "String1024", # required # } # # @!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 # Assigns a value to a named Pipeline parameter. # # @note When making an API call, you may pass Parameter # data as a hash: # # { # name: "PipelineParameterName", # required # value: "String1024", # required # } # # @!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. # # @note When making an API call, you may pass ParameterRange # data as a hash: # # { # integer_parameter_range_specification: { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # }, # continuous_parameter_range_specification: { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # }, # categorical_parameter_range_specification: { # values: ["ParameterValue"], # required # }, # } # # @!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. # # You can specify a maximum of 20 hyperparameters that a hyperparameter # tuning job can search over. Every possible value of a categorical # parameter range counts against this limit. # # # # @note When making an API call, you may pass ParameterRanges # data as a hash: # # { # integer_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # continuous_parameter_ranges: [ # { # name: "ParameterKey", # required # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # scaling_type: "Auto", # accepts Auto, Linear, Logarithmic, ReverseLogarithmic # }, # ], # categorical_parameter_ranges: [ # { # name: "ParameterKey", # required # values: ["ParameterValue"], # required # }, # ], # } # # @!attribute [rw] integer_parameter_ranges # The array of IntegerParameterRange objects that specify ranges of # integer hyperparameters that a hyperparameter tuning job searches. # @return [Array] # # @!attribute [rw] continuous_parameter_ranges # The array of ContinuousParameterRange objects that specify ranges of # continuous hyperparameters that a hyperparameter tuning job # searches. # @return [Array] # # @!attribute [rw] categorical_parameter_ranges # The array of CategoricalParameterRange objects that specify ranges # of categorical hyperparameters that a hyperparameter tuning job # searches. # @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) 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. # # @note When making an API call, you may pass ParentHyperParameterTuningJob # data as a hash: # # { # hyper_parameter_tuning_job_name: "HyperParameterTuningJobName", # } # # @!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 # 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, or trial component. # @return [Types::UserContext] # # @!attribute [rw] last_modified_by # Information about the user who created or modified an experiment, # trial, or trial component. # @return [Types::UserContext] # # @!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, :tags) 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, or trial component. # @return [Types::UserContext] # # @!attribute [rw] last_modified_by # Information about the user who created or modified an experiment, # trial, or trial component. # @return [Types::UserContext] # # @!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, :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] 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 for the step execution. # @return [Types::PipelineExecutionStepMetadata] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineExecutionStep AWS API Documentation # class PipelineExecutionStep < Struct.new( :step_name, :start_time, :end_time, :step_status, :cache_hit_result, :failure_reason, :metadata) SENSITIVE = [] include Aws::Structure end # Metadata for a step execution. # # @!attribute [rw] training_job # The Amazon Resource Name (ARN) of the training job that was run by # this step execution. # @return [Types::TrainingJobStepMetadata] # # @!attribute [rw] processing_job # The Amazon Resource Name (ARN) of the processing job that was run by # this step execution. # @return [Types::ProcessingJobStepMetadata] # # @!attribute [rw] transform_job # The Amazon Resource Name (ARN) of the transform job that was run by # this step execution. # @return [Types::TransformJobStepMetadata] # # @!attribute [rw] model # Metadata for the Model step. # @return [Types::ModelStepMetadata] # # @!attribute [rw] register_model # Metadata for the RegisterModel step. # @return [Types::RegisterModelStepMetadata] # # @!attribute [rw] condition # If this is a Condition step metadata object, details on the # condition. # @return [Types::ConditionStepMetadata] # # @!attribute [rw] callback # Metadata about a callback step. # @return [Types::CallbackStepMetadata] # # @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, :model, :register_model, :condition, :callback) 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] # # @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) SENSITIVE = [] include Aws::Structure end # Specifies the names of the experiment and trial created by a pipeline. # # @!attribute [rw] experiment_name # The name of the experiment. # @return [String] # # @!attribute [rw] trial_name # The name of the trial. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineExperimentConfig AWS API Documentation # class PipelineExperimentConfig < Struct.new( :experiment_name, :trial_name) SENSITIVE = [] include Aws::Structure end # A summary of a pipeline. # # @!attribute [rw] pipeline_arn # The Amazon Resource Name (ARN) of the pipeline. # @return [String] # # @!attribute [rw] pipeline_name # The name of the pipeline. # @return [String] # # @!attribute [rw] pipeline_display_name # The display name of the pipeline. # @return [String] # # @!attribute [rw] pipeline_description # The description of the pipeline. # @return [String] # # @!attribute [rw] role_arn # The Amazon Resource Name (ARN) that the pipeline used to execute. # @return [String] # # @!attribute [rw] creation_time # The creation time of the pipeline. # @return [Time] # # @!attribute [rw] last_modified_time # The time that the pipeline was last modified. # @return [Time] # # @!attribute [rw] last_execution_time # The last time that a pipeline execution began. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/PipelineSummary AWS API Documentation # class PipelineSummary < Struct.new( :pipeline_arn, :pipeline_name, :pipeline_display_name, :pipeline_description, :role_arn, :creation_time, :last_modified_time, :last_execution_time) SENSITIVE = [] include Aws::Structure end # Configuration for the cluster used to run a processing job. # # @note When making an API call, you may pass ProcessingClusterConfig # data as a hash: # # { # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # } # # @!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. # @return [Integer] # # @!attribute [rw] volume_kms_key_id # The AWS Key Management Service (AWS 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. # @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. # # @note When making an API call, you may pass ProcessingFeatureStoreOutput # data as a hash: # # { # feature_group_name: "FeatureGroupName", # required # } # # @!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. # # @note When making an API call, you may pass ProcessingInput # data as a hash: # # { # input_name: "String", # required # app_managed: false, # s3_input: { # s3_uri: "S3Uri", # required # local_path: "ProcessingLocalPath", # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # s3_compression_type: "None", # accepts None, Gzip # }, # dataset_definition: { # athena_dataset_definition: { # catalog: "AthenaCatalog", # required # database: "AthenaDatabase", # required # query_string: "AthenaQueryString", # required # work_group: "AthenaWorkGroup", # output_s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # output_format: "PARQUET", # required, accepts PARQUET, ORC, AVRO, JSON, TEXTFILE # output_compression: "GZIP", # accepts GZIP, SNAPPY, ZLIB # }, # redshift_dataset_definition: { # cluster_id: "RedshiftClusterId", # required # database: "RedshiftDatabase", # required # db_user: "RedshiftUserName", # required # query_string: "RedshiftQueryString", # required # cluster_role_arn: "RoleArn", # required # output_s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # output_format: "PARQUET", # required, accepts PARQUET, CSV # output_compression: "None", # accepts None, GZIP, BZIP2, ZSTD, SNAPPY # }, # local_path: "ProcessingLocalPath", # data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # input_mode: "Pipe", # accepts Pipe, File # }, # } # # @!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 # # * CreateTrainingJob # # * CreateTransformJob # @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 *AWS 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. # # @note When making an API call, you may pass ProcessingOutput # data as a hash: # # { # output_name: "String", # required # s3_output: { # s3_uri: "S3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # required, accepts Continuous, EndOfJob # }, # feature_store_output: { # feature_group_name: "FeatureGroupName", # required # }, # app_managed: false, # } # # @!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. # # @note When making an API call, you may pass ProcessingOutputConfig # data as a hash: # # { # outputs: [ # required # { # output_name: "String", # required # s3_output: { # s3_uri: "S3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # required, accepts Continuous, EndOfJob # }, # feature_store_output: { # feature_group_name: "FeatureGroupName", # required # }, # app_managed: false, # }, # ], # kms_key_id: "KmsKeyId", # } # # @!attribute [rw] outputs # An array of outputs configuring the data to upload from the # processing container. # @return [Array] # # @!attribute [rw] kms_key_id # The AWS Key Management Service (AWS 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. # # @note When making an API call, you may pass ProcessingResources # data as a hash: # # { # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # } # # @!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. # # @note When making an API call, you may pass ProcessingS3Input # data as a hash: # # { # s3_uri: "S3Uri", # required # local_path: "ProcessingLocalPath", # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # s3_compression_type: "None", # accepts None, Gzip # } # # @!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. # # @note When making an API call, you may pass ProcessingS3Output # data as a hash: # # { # s3_uri: "S3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # required, accepts Continuous, EndOfJob # } # # @!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. # # @note When making an API call, you may pass ProcessingStoppingCondition # data as a hash: # # { # max_runtime_in_seconds: 1, # required # } # # @!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 # Amazon SageMaker how to distribute traffic among the models by # specifying variant weights. # # @note When making an API call, you may pass ProductionVariant # data as a hash: # # { # variant_name: "VariantName", # required # model_name: "ModelName", # required # initial_instance_count: 1, # required # instance_type: "ml.t2.medium", # required, accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.m5d.large, ml.m5d.xlarge, ml.m5d.2xlarge, ml.m5d.4xlarge, ml.m5d.12xlarge, ml.m5d.24xlarge, ml.c4.large, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.large, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.12xlarge, ml.r5.24xlarge, ml.r5d.large, ml.r5d.xlarge, ml.r5d.2xlarge, ml.r5d.4xlarge, ml.r5d.12xlarge, ml.r5d.24xlarge, ml.inf1.xlarge, ml.inf1.2xlarge, ml.inf1.6xlarge, ml.inf1.24xlarge # initial_variant_weight: 1.0, # accelerator_type: "ml.eia1.medium", # accepts ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge # core_dump_config: { # destination_s3_uri: "DestinationS3Uri", # required # kms_key_id: "KmsKeyId", # }, # } # # @!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] # # @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) SENSITIVE = [] include Aws::Structure end # Specifies configuration for a core dump from the model container when # the process crashes. # # @note When making an API call, you may pass ProductionVariantCoreDumpConfig # data as a hash: # # { # destination_s3_uri: "DestinationS3Uri", # required # kms_key_id: "KmsKeyId", # } # # @!attribute [rw] destination_s3_uri # The Amazon S3 bucket to send the core dump to. # @return [String] # # @!attribute [rw] kms_key_id # The AWS Key Management Service (AWS KMS) key that Amazon 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 master 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 AWS KMS][2] in the *AWS # 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 # 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] # # @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) SENSITIVE = [] include Aws::Structure end # Configuration information for Debugger system monitoring, framework # profiling, and storage paths. # # @note When making an API call, you may pass ProfilerConfig # data as a hash: # # { # s3_output_path: "S3Uri", # required # profiling_interval_in_milliseconds: 1, # profiling_parameters: { # "ConfigKey" => "ConfigValue", # }, # } # # @!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] # # @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) SENSITIVE = [] include Aws::Structure end # Configuration information for updating the Debugger profile # parameters, system and framework metrics configurations, and storage # paths. # # @note When making an API call, you may pass ProfilerConfigForUpdate # data as a hash: # # { # s3_output_path: "S3Uri", # profiling_interval_in_milliseconds: 1, # profiling_parameters: { # "ConfigKey" => "ConfigValue", # }, # disable_profiler: false, # } # # @!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 disable Debugger monitoring and profiling, 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. # # @note When making an API call, you may pass ProfilerRuleConfiguration # data as a hash: # # { # rule_configuration_name: "RuleConfigurationName", # required # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # rule_evaluator_image: "AlgorithmImage", # required # instance_type: "ml.t3.medium", # accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # rule_parameters: { # "ConfigKey" => "ConfigValue", # }, # } # # @!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 Debugger 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 # 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. # # @note When making an API call, you may pass PropertyNameQuery # data as a hash: # # { # property_name_hint: "PropertyNameHint", # required # } # # @!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 Amazon 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 AWS Service # Catalog][1]. # # # # [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html # # @note When making an API call, you may pass ProvisioningParameter # data as a hash: # # { # key: "ProvisioningParameterKey", # value: "ProvisioningParameterValue", # } # # @!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 # # @note When making an API call, you may pass PublicWorkforceTaskPrice # data as a hash: # # { # amount_in_usd: { # dollars: 1, # cents: 1, # tenth_fractions_of_a_cent: 1, # }, # } # # @!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 # @note When making an API call, you may pass PutModelPackageGroupPolicyInput # data as a hash: # # { # model_package_group_name: "EntityName", # required # resource_policy: "PolicyString", # required # } # # @!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 # Configuration for Redshift Dataset Definition input. # # @note When making an API call, you may pass RedshiftDatasetDefinition # data as a hash: # # { # cluster_id: "RedshiftClusterId", # required # database: "RedshiftDatabase", # required # db_user: "RedshiftUserName", # required # query_string: "RedshiftQueryString", # required # cluster_role_arn: "RoleArn", # required # output_s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # output_format: "PARQUET", # required, accepts PARQUET, CSV # output_compression: "None", # accepts None, GZIP, BZIP2, ZSTD, SNAPPY # } # # @!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 AWS Key Management Service (AWS 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 # @note When making an API call, you may pass RegisterDevicesRequest # data as a hash: # # { # device_fleet_name: "EntityName", # required # devices: [ # required # { # device_name: "DeviceName", # required # description: "DeviceDescription", # iot_thing_name: "ThingName", # }, # ], # tags: [ # { # key: "TagKey", # required # value: "TagValue", # required # }, # ], # } # # @!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 # @note When making an API call, you may pass RenderUiTemplateRequest # data as a hash: # # { # ui_template: { # content: "TemplateContent", # required # }, # task: { # required # input: "TaskInput", # required # }, # role_arn: "RoleArn", # required # human_task_ui_arn: "HumanTaskUiArn", # } # # @!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. # @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. # # @note When making an API call, you may pass RenderableTask # data as a hash: # # { # input: "TaskInput", # required # } # # @!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. # # @note When making an API call, you may pass RepositoryAuthConfig # data as a hash: # # { # repository_credentials_provider_arn: "RepositoryCredentialsProviderArn", # required # } # # @!attribute [rw] repository_credentials_provider_arn # The Amazon Resource Name (ARN) of an AWS 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 AWS Lambda function, see [Create a Lambda function with # the console][1] in the *AWS Lambda Developer Guide*. # # # # [1]: https://docs.aws.amazon.com/lambda/latest/dg/getting-started-create-function.html # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RepositoryAuthConfig AWS API Documentation # class RepositoryAuthConfig < Struct.new( :repository_credentials_provider_arn) SENSITIVE = [] include Aws::Structure end # The resolved attributes. # # @!attribute [rw] auto_ml_job_objective # Specifies a metric to minimize or maximize as the objective of a # job. # @return [Types::AutoMLJobObjective] # # @!attribute [rw] problem_type # The problem type. # @return [String] # # @!attribute [rw] completion_criteria # How long a job is allowed to run, or how many candidates a job is # allowed to generate. # @return [Types::AutoMLJobCompletionCriteria] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResolvedAttributes AWS API Documentation # class ResolvedAttributes < Struct.new( :auto_ml_job_objective, :problem_type, :completion_criteria) SENSITIVE = [] include Aws::Structure end # Describes the resources, including ML compute instances and ML storage # volumes, to use for model training. # # @note When making an API call, you may pass ResourceConfig # data as a hash: # # { # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # } # # @!attribute [rw] instance_type # The ML compute instance type. # @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. # # You must specify sufficient ML storage for your scenario. # # Amazon SageMaker supports only the General Purpose SSD (gp2) ML # storage volume type. # # # # Certain Nitro-based instances include local storage with a fixed # total size, dependent on the instance type. When using these # instances for training, 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 AWS KMS key that Amazon 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] # # @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) 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 Amazon 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. # # @note When making an API call, you may pass ResourceLimits # data as a hash: # # { # max_number_of_training_jobs: 1, # required # max_parallel_training_jobs: 1, # required # } # # @!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] # # @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) 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. # # @note When making an API call, you may pass ResourceSpec # data as a hash: # # { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # } # # @!attribute [rw] sage_maker_image_arn # The ARN of the SageMaker image that the image version belongs to. # @return [String] # # @!attribute [rw] sage_maker_image_version_arn # The ARN of the image version created on the instance. # @return [String] # # @!attribute [rw] instance_type # The instance type that the image version runs on. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ResourceSpec AWS API Documentation # class ResourceSpec < Struct.new( :sage_maker_image_arn, :sage_maker_image_version_arn, :instance_type) SENSITIVE = [] include Aws::Structure end # The retention policy for data stored on an Amazon Elastic File System # (EFS) volume. # # @note When making an API call, you may pass RetentionPolicy # data as a hash: # # { # home_efs_file_system: "Retain", # accepts Retain, Delete # } # # @!attribute [rw] home_efs_file_system # The default is `Retain`, which specifies to keep the data stored on # the EFS volume. # # Specify `Delete` to delete the data stored on the EFS volume. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RetentionPolicy AWS API Documentation # class RetentionPolicy < Struct.new( :home_efs_file_system) SENSITIVE = [] include Aws::Structure end # 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. # # @note When making an API call, you may pass RetryStrategy # data as a hash: # # { # maximum_retry_attempts: 1, # required # } # # @!attribute [rw] maximum_retry_attempts # The number of times to retry the job. When the job is retried, it's # `SecondaryStatus` is changed to `STARTING`. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/RetryStrategy AWS API Documentation # class RetryStrategy < Struct.new( :maximum_retry_attempts) SENSITIVE = [] include Aws::Structure end # Describes the S3 data source. # # @note When making an API call, you may pass S3DataSource # data as a hash: # # { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # } # # @!attribute [rw] s3_data_type # If you choose `S3Prefix`, `S3Uri` identifies a key name prefix. # Amazon 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 Amazon # 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 Amazon SageMaker # uses to perform tasks on your behalf. # @return [String] # # @!attribute [rw] s3_data_distribution_type # If you want Amazon SageMaker to replicate the entire dataset on each # ML compute instance that is launched for model training, specify # `FullyReplicated`. # # If you want Amazon 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] # # @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) SENSITIVE = [] include Aws::Structure end # The Amazon Simple Storage (Amazon S3) location and and security # configuration for `OfflineStore`. # # @note When making an API call, you may pass S3StorageConfig # data as a hash: # # { # s3_uri: "S3Uri", # required # kms_key_id: "KmsKeyId", # resolved_output_s3_uri: "S3Uri", # } # # @!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 AWS Key Management Service (KMS) key ID of the key used to # encrypt any objects written into the `OfflineStore` S3 location. # # The IAM `roleARN` that is passed as a parameter to # `CreateFeatureGroup` must have below permissions to the `KmsKeyId`\: # # * `"kms:GenerateDataKey"` # # ^ # @return [String] # # @!attribute [rw] resolved_output_s3_uri # The S3 path where offline records are written. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/S3StorageConfig AWS API Documentation # class S3StorageConfig < Struct.new( :s3_uri, :kms_key_id, :resolved_output_s3_uri) SENSITIVE = [] include Aws::Structure end # Configuration details about the monitoring schedule. # # @note When making an API call, you may pass ScheduleConfig # data as a hash: # # { # schedule_expression: "ScheduleExpression", # required # } # # @!attribute [rw] schedule_expression # A cron expression that describes details about the monitoring # schedule. # # Currently the only supported cron expressions are: # # * If you want to set the job to start every hour, please use the # following: # # `Hourly: cron(0 * ? * * *)` # # * If you want to start the job daily: # # `cron(0 [00-23] ? * * *)` # # For example, the following are valid cron expressions: # # * Daily at noon UTC: `cron(0 12 ? * * *)` # # * Daily at midnight UTC: `cron(0 0 ? * * *)` # # To support running every 6, 12 hours, the following are also # supported: # # `cron(0 [00-23]/[01-24] ? * * *)` # # For example, the following are valid cron expressions: # # * Every 12 hours, starting at 5pm UTC: `cron(0 17/12 ? * * *)` # # * Every two hours starting at midnight: `cron(0 0/2 ? * * *)` # # * 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. # # # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ScheduleConfig AWS API Documentation # class ScheduleConfig < Struct.new( :schedule_expression) SENSITIVE = [] include Aws::Structure end # A multi-expression that searches for the specified resource or # resources in a search. All resource objects that satisfy the # expression's condition are included in the search results. You must # specify at least one subexpression, filter, or nested filter. A # `SearchExpression` can contain up to twenty elements. # # A `SearchExpression` contains the following components: # # * A list of `Filter` objects. Each filter defines a simple Boolean # expression comprised of a resource property name, Boolean operator, # and value. # # * A list of `NestedFilter` objects. Each nested filter defines a list # of Boolean expressions using a list of resource properties. A nested # filter is satisfied if a single object in the list satisfies all # Boolean expressions. # # * A list of `SearchExpression` objects. A search expression object can # be nested in a list of search expression objects. # # * A Boolean operator: `And` or `Or`. # # @note When making an API call, you may pass SearchExpression # data as a hash: # # { # filters: [ # { # name: "ResourcePropertyName", # required # operator: "Equals", # accepts Equals, NotEquals, GreaterThan, GreaterThanOrEqualTo, LessThan, LessThanOrEqualTo, Contains, Exists, NotExists, In # value: "FilterValue", # }, # ], # nested_filters: [ # { # nested_property_name: "ResourcePropertyName", # required # filters: [ # required # { # name: "ResourcePropertyName", # required # operator: "Equals", # accepts Equals, NotEquals, GreaterThan, GreaterThanOrEqualTo, LessThan, LessThanOrEqualTo, Contains, Exists, NotExists, In # value: "FilterValue", # }, # ], # }, # ], # sub_expressions: [ # { # filters: [ # { # name: "ResourcePropertyName", # required # operator: "Equals", # accepts Equals, NotEquals, GreaterThan, GreaterThanOrEqualTo, LessThan, LessThanOrEqualTo, Contains, Exists, NotExists, In # value: "FilterValue", # }, # ], # nested_filters: [ # { # nested_property_name: "ResourcePropertyName", # required # filters: [ # required # { # name: "ResourcePropertyName", # required # operator: "Equals", # accepts Equals, NotEquals, GreaterThan, GreaterThanOrEqualTo, LessThan, LessThanOrEqualTo, Contains, Exists, NotExists, In # value: "FilterValue", # }, # ], # }, # ], # sub_expressions: { # # recursive SearchExpressionList # }, # operator: "And", # accepts And, Or # }, # ], # operator: "And", # accepts And, 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 API response. # # @!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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass SearchRequest # data as a hash: # # { # resource: "TrainingJob", # required, accepts TrainingJob, Experiment, ExperimentTrial, ExperimentTrialComponent, Endpoint, ModelPackage, ModelPackageGroup, Pipeline, PipelineExecution, FeatureGroup # search_expression: { # filters: [ # { # name: "ResourcePropertyName", # required # operator: "Equals", # accepts Equals, NotEquals, GreaterThan, GreaterThanOrEqualTo, LessThan, LessThanOrEqualTo, Contains, Exists, NotExists, In # value: "FilterValue", # }, # ], # nested_filters: [ # { # nested_property_name: "ResourcePropertyName", # required # filters: [ # required # { # name: "ResourcePropertyName", # required # operator: "Equals", # accepts Equals, NotEquals, GreaterThan, GreaterThanOrEqualTo, LessThan, LessThanOrEqualTo, Contains, Exists, NotExists, In # value: "FilterValue", # }, # ], # }, # ], # sub_expressions: [ # { # # recursive SearchExpression # }, # ], # operator: "And", # accepts And, Or # }, # sort_by: "ResourcePropertyName", # sort_order: "Ascending", # accepts Ascending, Descending # next_token: "NextToken", # max_results: 1, # } # # @!attribute [rw] resource # The name of the Amazon SageMaker resource to search for. # @return [String] # # @!attribute [rw] search_expression # A Boolean conditional statement. Resources must satisfy this # condition to be included in search results. You must provide at # least one subexpression, filter, or nested filter. The maximum # number of recursive `SubExpressions`, `NestedFilters`, and `Filters` # that can be included in a `SearchExpression` object is 50. # @return [Types::SearchExpression] # # @!attribute [rw] sort_by # The name of the resource property used to sort the `SearchResults`. # The default is `LastModifiedTime`. # @return [String] # # @!attribute [rw] sort_order # How `SearchResults` are ordered. Valid values are `Ascending` or # `Descending`. The default is `Descending`. # @return [String] # # @!attribute [rw] next_token # If more than `MaxResults` resources match the specified # `SearchExpression`, the response includes a `NextToken`. The # `NextToken` can be passed to the next `SearchRequest` to continue # retrieving results. # @return [String] # # @!attribute [rw] max_results # The maximum number of results to return. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SearchRequest AWS API Documentation # class SearchRequest < Struct.new( :resource, :search_expression, :sort_by, :sort_order, :next_token, :max_results) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] results # A list of `SearchRecord` objects. # @return [Array] # # @!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 # DescribeTrainingJobResponse$SecondaryStatusTransitions. It provides # additional details about a status that the training job has # transitioned through. A training job can be in one of several states, # for example, starting, downloading, training, or uploading. Within # each state, there are a number of intermediate states. For example, # within the starting state, Amazon SageMaker could be starting the # training job or launching the ML instances. These transitional states # are referred to as the job's secondary status. # # @!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. # # Amazon SageMaker provides secondary statuses and status messages # that apply to each of them: # # Starting # : * Starting the training job. # # * Launching requested ML instances. # # * Insufficient capacity error from EC2 while launching instances, # retrying! # # * Launched instance was unhealthy, replacing it! # # * Preparing the instances for training. # # Training # : * Downloading the training image. # # * Training image download completed. Training in progress. # # Status messages are subject to change. Therefore, we recommend not # including them in code that programmatically initiates actions. For # examples, don't use status messages in if statements. # # To have an overview of your training job's progress, view # `TrainingJobStatus` and `SecondaryStatus` in DescribeTrainingJob, # 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 # @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 # @note When making an API call, you may pass SendPipelineExecutionStepFailureRequest # data as a hash: # # { # callback_token: "CallbackToken", # required # failure_reason: "String256", # client_request_token: "IdempotencyToken", # } # # @!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 # @note When making an API call, you may pass SendPipelineExecutionStepSuccessRequest # data as a hash: # # { # callback_token: "CallbackToken", # required # output_parameters: [ # { # name: "String256", # required # value: "String1024", # required # }, # ], # client_request_token: "IdempotencyToken", # } # # @!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 AWS 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 AWS Service # Catalog][1]. # # # # [1]: https://docs.aws.amazon.com/servicecatalog/latest/adminguide/introduction.html # # @note When making an API call, you may pass ServiceCatalogProvisioningDetails # data as a hash: # # { # product_id: "ServiceCatalogEntityId", # required # provisioning_artifact_id: "ServiceCatalogEntityId", # required # path_id: "ServiceCatalogEntityId", # provisioning_parameters: [ # { # key: "ProvisioningParameterKey", # value: "ProvisioningParameterValue", # }, # ], # } # # @!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 # Specifies options for sharing SageMaker Studio notebooks. These # settings are specified as part of `DefaultUserSettings` when the # `CreateDomain` API is called, and as part of `UserSettings` when the # `CreateUserProfile` API is called. When `SharingSettings` is not # specified, notebook sharing isn't allowed. # # @note When making an API call, you may pass SharingSettings # data as a hash: # # { # notebook_output_option: "Allowed", # accepts Allowed, Disabled # s3_output_path: "S3Uri", # s3_kms_key_id: "KmsKeyId", # } # # @!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 AWS 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. # # @note When making an API call, you may pass ShuffleConfig # data as a hash: # # { # seed: 1, # required # } # # @!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 Amazon # SageMaker account or an algorithm in AWS Marketplace that you are # subscribed to. # # @note When making an API call, you may pass SourceAlgorithm # data as a hash: # # { # model_data_url: "Url", # algorithm_name: "ArnOrName", # required # } # # @!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 algorithm. # # # @return [String] # # @!attribute [rw] algorithm_name # The name of an algorithm that was used to create the model package. # The algorithm must be either an algorithm resource in your Amazon # SageMaker account or an algorithm in AWS Marketplace that you are # subscribed to. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SourceAlgorithm AWS API Documentation # class SourceAlgorithm < Struct.new( :model_data_url, :algorithm_name) SENSITIVE = [] include Aws::Structure end # A list of algorithms that were used to create a model package. # # @note When making an API call, you may pass SourceAlgorithmSpecification # data as a hash: # # { # source_algorithms: [ # required # { # model_data_url: "Url", # algorithm_name: "ArnOrName", # required # }, # ], # } # # @!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 # # @note When making an API call, you may pass SourceIpConfig # data as a hash: # # { # cidrs: ["Cidr"], # required # } # # @!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 # @note When making an API call, you may pass StartMonitoringScheduleRequest # data as a hash: # # { # monitoring_schedule_name: "MonitoringScheduleName", # required # } # # @!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 # @note When making an API call, you may pass StartNotebookInstanceInput # data as a hash: # # { # notebook_instance_name: "NotebookInstanceName", # required # } # # @!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 # @note When making an API call, you may pass StartPipelineExecutionRequest # data as a hash: # # { # pipeline_name: "PipelineName", # required # pipeline_execution_display_name: "PipelineExecutionName", # pipeline_parameters: [ # { # name: "PipelineParameterName", # required # value: "String1024", # required # }, # ], # pipeline_execution_description: "PipelineExecutionDescription", # client_request_token: "IdempotencyToken", # required # } # # @!attribute [rw] pipeline_name # The name of the pipeline. # @return [String] # # @!attribute [rw] pipeline_execution_display_name # The display name of the pipeline execution. # @return [String] # # @!attribute [rw] pipeline_parameters # Contains a list of pipeline parameters. This list can be empty. # @return [Array] # # @!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 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/StartPipelineExecutionRequest AWS API Documentation # class StartPipelineExecutionRequest < Struct.new( :pipeline_name, :pipeline_execution_display_name, :pipeline_parameters, :pipeline_execution_description, :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/StartPipelineExecutionResponse AWS API Documentation # class StartPipelineExecutionResponse < Struct.new( :pipeline_execution_arn) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass StopAutoMLJobRequest # data as a hash: # # { # auto_ml_job_name: "AutoMLJobName", # required # } # # @!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 # @note When making an API call, you may pass StopCompilationJobRequest # data as a hash: # # { # compilation_job_name: "EntityName", # required # } # # @!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 # @note When making an API call, you may pass StopEdgePackagingJobRequest # data as a hash: # # { # edge_packaging_job_name: "EntityName", # required # } # # @!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 # @note When making an API call, you may pass StopHyperParameterTuningJobRequest # data as a hash: # # { # hyper_parameter_tuning_job_name: "HyperParameterTuningJobName", # required # } # # @!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 # @note When making an API call, you may pass StopLabelingJobRequest # data as a hash: # # { # labeling_job_name: "LabelingJobName", # required # } # # @!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 # @note When making an API call, you may pass StopMonitoringScheduleRequest # data as a hash: # # { # monitoring_schedule_name: "MonitoringScheduleName", # required # } # # @!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 # @note When making an API call, you may pass StopNotebookInstanceInput # data as a hash: # # { # notebook_instance_name: "NotebookInstanceName", # required # } # # @!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 # @note When making an API call, you may pass StopPipelineExecutionRequest # data as a hash: # # { # pipeline_execution_arn: "PipelineExecutionArn", # required # client_request_token: "IdempotencyToken", # required # } # # @!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 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/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 # @note When making an API call, you may pass StopProcessingJobRequest # data as a hash: # # { # processing_job_name: "ProcessingJobName", # required # } # # @!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 # @note When making an API call, you may pass StopTrainingJobRequest # data as a hash: # # { # training_job_name: "TrainingJobName", # required # } # # @!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 # @note When making an API call, you may pass StopTransformJobRequest # data as a hash: # # { # transform_job_name: "TransformJobName", # required # } # # @!attribute [rw] transform_job_name # The name of the 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, model compilation # job, or hyperparameter tuning job can run. It also specifies how long # a managed Spot training job has to complete. When the job reaches the # time limit, Amazon SageMaker ends the training or compilation job. Use # this API to cap model training costs. # # To stop a job, Amazon SageMaker sends the algorithm the `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 Amazon SageMaker automatically # save the intermediate results of a model training job when possible. # This attempt to save artifacts is only a best effort case as model # might not be in a state from which it can be saved. For example, if # training has just started, the model might not be ready to save. When # saved, this intermediate data is a valid model artifact. You can use # it to create a model with `CreateModel`. # # The Neural Topic Model (NTM) currently does not support saving # intermediate model artifacts. When training NTMs, make sure that the # maximum runtime is sufficient for the training job to complete. # # # # @note When making an API call, you may pass StoppingCondition # data as a hash: # # { # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # } # # @!attribute [rw] max_runtime_in_seconds # The maximum length of time, in seconds, that a training or # compilation job can run. If the job does not complete during this # time, Amazon 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. # @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, Amazon SageMaker ends the job. # # When `RetryStrategy` is specified in the job request, # `MaxWaitTimeInSeconds` specifies the maximum time for all of the # attempts in total, not each individual attempt. # @return [Integer] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StoppingCondition AWS API Documentation # class StoppingCondition < Struct.new( :max_runtime_in_seconds, :max_wait_time_in_seconds) SENSITIVE = [] include Aws::Structure end # 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 request. Limits the property # names that are included in the response. # # @note When making an API call, you may pass SuggestionQuery # data as a hash: # # { # property_name_query: { # property_name_hint: "PropertyNameHint", # required # }, # } # # @!attribute [rw] property_name_query # Defines a property name hint. Only property names that begin with # the specified hint are included in the response. # @return [Types::PropertyNameQuery] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/SuggestionQuery AWS API Documentation # class SuggestionQuery < Struct.new( :property_name_query) SENSITIVE = [] include Aws::Structure end # A tag object that consists of a key and an optional value, used to # manage metadata for Amazon SageMaker AWS resources. # # You can add tags to notebook instances, training jobs, hyperparameter # tuning jobs, batch transform jobs, models, labeling jobs, work teams, # endpoint configurations, and endpoints. For more information on adding # tags to Amazon SageMaker resources, see AddTags. # # For more information on adding metadata to your AWS resources with # tagging, see [Tagging AWS resources][1]. For advice on best practices # for managing AWS resources with tagging, see [Tagging Best Practices: # Implement an Effective AWS Resource Tagging Strategy][2]. # # # # [1]: https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html # [2]: https://d1.awsstatic.com/whitepapers/aws-tagging-best-practices.pdf # # @note When making an API call, you may pass Tag # data as a hash: # # { # key: "TagKey", # required # value: "TagValue", # required # } # # @!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`. # # @note When making an API call, you may pass TargetPlatform # data as a hash: # # { # os: "ANDROID", # required, accepts ANDROID, LINUX # arch: "X86_64", # required, accepts X86_64, X86, ARM64, ARM_EABI, ARM_EABIHF # accelerator: "INTEL_GRAPHICS", # accepts INTEL_GRAPHICS, MALI, NVIDIA # } # # @!attribute [rw] os # Specifies a target platform OS. # # * `LINUX`\: Linux-based operating systems. # # * `ANDROID`\: Android operating systems. Android API level can be # specified using the `ANDROID_PLATFORM` compiler option. For # example, `"CompilerOptions": \{'ANDROID_PLATFORM': 28\}` # @return [String] # # @!attribute [rw] arch # Specifies a target platform architecture. # # * `X86_64`\: 64-bit version of the x86 instruction set. # # * `X86`\: 32-bit version of the x86 instruction set. # # * `ARM64`\: ARMv8 64-bit CPU. # # * `ARM_EABIHF`\: ARMv7 32-bit, Hard Float. # # * `ARM_EABI`\: ARMv7 32-bit, Soft Float. Used by Android 32-bit ARM # platform. # @return [String] # # @!attribute [rw] accelerator # Specifies a target platform accelerator (optional). # # * `NVIDIA`\: Nvidia graphics processing unit. It also requires # `gpu-code`, `trt-ver`, `cuda-ver` compiler options # # * `MALI`\: ARM Mali graphics processor # # * `INTEL_GRAPHICS`\: Integrated Intel graphics # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TargetPlatform AWS API Documentation # class TargetPlatform < Struct.new( :os, :arch, :accelerator) SENSITIVE = [] include Aws::Structure end # The TensorBoard app settings. # # @note When making an API call, you may pass TensorBoardAppSettings # data as a hash: # # { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # } # # @!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 Debugger TensorBoard output # data. # # @note When making an API call, you may pass TensorBoardOutputConfig # data as a hash: # # { # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # required # } # # @!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 # Currently, the `TrafficRoutingConfig` API is not supported. # # @note When making an API call, you may pass TrafficRoutingConfig # data as a hash: # # { # type: "ALL_AT_ONCE", # required, accepts ALL_AT_ONCE, CANARY # wait_interval_in_seconds: 1, # required # canary_size: { # type: "INSTANCE_COUNT", # required, accepts INSTANCE_COUNT, CAPACITY_PERCENT # value: 1, # required # }, # } # # @!attribute [rw] type # @return [String] # # @!attribute [rw] wait_interval_in_seconds # @return [Integer] # # @!attribute [rw] canary_size # @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) 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. # # Amazon 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` # @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 AWS 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. Amazon 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 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][1]. # # # # [1]: 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, Amazon SageMaker ends the training # job. Use this API to cap model training costs. # # To stop a job, Amazon 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 Amazon 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 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 # # * CreateTrainingJob # # * CreateTransformJob # @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 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] 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 AWS # resources in different ways, for example, by purpose, owner, or # environment. For more information, see [Tagging AWS 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, :environment, :retry_strategy, :tags) SENSITIVE = [] include Aws::Structure end # Defines the input needed to run a training job using the algorithm. # # @note When making an API call, you may pass TrainingJobDefinition # data as a hash: # # { # training_input_mode: "Pipe", # required, accepts Pipe, File # hyper_parameters: { # "HyperParameterKey" => "HyperParameterValue", # }, # input_data_config: [ # required # { # channel_name: "ChannelName", # required # data_source: { # required # s3_data_source: { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # attribute_names: ["AttributeName"], # }, # file_system_data_source: { # file_system_id: "FileSystemId", # required # file_system_access_mode: "rw", # required, accepts rw, ro # file_system_type: "EFS", # required, accepts EFS, FSxLustre # directory_path: "DirectoryPath", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # record_wrapper_type: "None", # accepts None, RecordIO # input_mode: "Pipe", # accepts Pipe, File # shuffle_config: { # seed: 1, # required # }, # }, # ], # output_data_config: { # required # kms_key_id: "KmsKeyId", # s3_output_path: "S3Uri", # required # }, # resource_config: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # instance_count: 1, # required # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # stopping_condition: { # required # max_runtime_in_seconds: 1, # max_wait_time_in_seconds: 1, # }, # } # # @!attribute [rw] training_input_mode # The input mode used by the algorithm for the training job. For the # input modes that Amazon SageMaker algorithms support, see # [Algorithms][1]. # # If an algorithm supports the `File` input mode, Amazon SageMaker # downloads the training data from S3 to the provisioned ML storage # Volume, and mounts the directory to docker volume for training # container. If an algorithm supports the `Pipe` input mode, Amazon # SageMaker streams data directly from S3 to the container. # # # # [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. # Amazon 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, Amazon SageMaker ends the training # job. Use this API to cap model training costs. # # To stop a job, Amazon 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] # # @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) SENSITIVE = [] include Aws::Structure end # Defines how the algorithm is used for a training job. # # @note When making an API call, you may pass TrainingSpecification # data as a hash: # # { # training_image: "ContainerImage", # required # training_image_digest: "ImageDigest", # supported_hyper_parameters: [ # { # name: "ParameterName", # required # description: "EntityDescription", # type: "Integer", # required, accepts Integer, Continuous, Categorical, FreeText # range: { # integer_parameter_range_specification: { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # }, # continuous_parameter_range_specification: { # min_value: "ParameterValue", # required # max_value: "ParameterValue", # required # }, # categorical_parameter_range_specification: { # values: ["ParameterValue"], # required # }, # }, # is_tunable: false, # is_required: false, # default_value: "HyperParameterValue", # }, # ], # supported_training_instance_types: ["ml.m4.xlarge"], # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.p3dn.24xlarge, ml.p4d.24xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5n.xlarge, ml.c5n.2xlarge, ml.c5n.4xlarge, ml.c5n.9xlarge, ml.c5n.18xlarge # supports_distributed_training: false, # metric_definitions: [ # { # name: "MetricName", # required # regex: "MetricRegex", # required # }, # ], # training_channels: [ # required # { # name: "ChannelName", # required # description: "EntityDescription", # is_required: false, # supported_content_types: ["ContentType"], # required # supported_compression_types: ["None"], # accepts None, Gzip # supported_input_modes: ["Pipe"], # required, accepts Pipe, File # }, # ], # supported_tuning_job_objective_metrics: [ # { # type: "Maximize", # required, accepts Maximize, Minimize # metric_name: "MetricName", # required # }, # ], # } # # @!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] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrainingSpecification AWS API Documentation # class TrainingSpecification < Struct.new( :training_image, :training_image_digest, :supported_hyper_parameters, :supported_training_instance_types, :supports_distributed_training, :metric_definitions, :training_channels, :supported_tuning_job_objective_metrics) SENSITIVE = [] include Aws::Structure end # Describes the location of the channel data. # # @note When making an API call, you may pass TransformDataSource # data as a hash: # # { # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # } # # @!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. # # @note When making an API call, you may pass TransformInput # data as a hash: # # { # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # } # # @!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] 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 # # * CreateTrainingJob # # * CreateTransformJob # @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, :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. # # @note When making an API call, you may pass TransformJobDefinition # data as a hash: # # { # max_concurrent_transforms: 1, # max_payload_in_mb: 1, # batch_strategy: "MultiRecord", # accepts MultiRecord, SingleRecord # environment: { # "TransformEnvironmentKey" => "TransformEnvironmentValue", # }, # transform_input: { # required # data_source: { # required # s3_data_source: { # required # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # }, # }, # content_type: "ContentType", # compression_type: "None", # accepts None, Gzip # split_type: "None", # accepts None, Line, RecordIO, TFRecord # }, # transform_output: { # required # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # }, # transform_resources: { # required # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # } # # @!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 call. # # @!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. # # @note When making an API call, you may pass TransformOutput # data as a hash: # # { # s3_output_path: "S3Uri", # required # accept: "Accept", # assemble_with: "None", # accepts None, Line # kms_key_id: "KmsKeyId", # } # # @!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 AWS Key Management Service (AWS 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 request. For more information, see # [Using Key Policies in AWS KMS][2] in the *AWS Key Management # Service Developer Guide*. # # # # [1]: https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html # [2]: http://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. # # @note When making an API call, you may pass TransformResources # data as a hash: # # { # instance_type: "ml.m4.xlarge", # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge # instance_count: 1, # required # volume_kms_key_id: "KmsKeyId", # } # # @!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. For # distributed transform jobs, specify a value greater than 1. The # default value is `1`. # @return [Integer] # # @!attribute [rw] volume_kms_key_id # The AWS Key Management Service (AWS 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. 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` # @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. # # @note When making an API call, you may pass TransformS3DataSource # data as a hash: # # { # s3_data_type: "ManifestFile", # required, accepts ManifestFile, S3Prefix, AugmentedManifestFile # s3_uri: "S3Uri", # required # } # # @!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 API. # # @!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 # Information about the user who created or modified an experiment, # trial, or trial component. # @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, or trial component. # @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 API to search on the tags. # @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 API. # # @!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 # Information about the user who created or modified an experiment, # trial, or 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, or trial 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] 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] tags # The list of tags that are associated with the component. You can use # Search API to search on the tags. # @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] # # @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, :tags, :parents) 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 request. # # Examples of input artifacts are datasets, algorithms, hyperparameters, # source code, and instance types. Examples of output artifacts are # metrics, snapshots, logs, and images. # # @note When making an API call, you may pass TrialComponentArtifact # data as a hash: # # { # media_type: "MediaType", # value: "TrialComponentArtifactValue", # required # } # # @!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 request. # # @note When making an API call, you may pass TrialComponentParameterValue # data as a hash: # # { # string_value: "StringParameterValue", # number_value: 1.0, # } # # @!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, or trial component. # @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 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. # # @note When making an API call, you may pass TrialComponentStatus # data as a hash: # # { # primary_status: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped # message: "TrialComponentStatusMessage", # } # # @!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 API and provide the # `TrialComponentName`. # # @!attribute [rw] trial_component_name # The name of the trial component. # @return [String] # # @!attribute [rw] trial_component_arn # The 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 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 API and provide the `TrialName`. # # @!attribute [rw] trial_arn # The Amazon Resource Name (ARN) of the trial. # @return [String] # # @!attribute [rw] trial_name # The name of the trial. # @return [String] # # @!attribute [rw] display_name # The name of the trial as displayed. If `DisplayName` isn't # specified, `TrialName` is displayed. # @return [String] # # @!attribute [rw] trial_source # The source of the trial. # @return [Types::TrialSource] # # @!attribute [rw] creation_time # When the trial was created. # @return [Time] # # @!attribute [rw] last_modified_time # When the trial was last modified. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TrialSummary AWS API Documentation # class TrialSummary < Struct.new( :trial_arn, :trial_name, :display_name, :trial_source, :creation_time, :last_modified_time) SENSITIVE = [] include Aws::Structure end # The job completion criteria. # # @note When making an API call, you may pass TuningJobCompletionCriteria # data as a hash: # # { # target_objective_metric_value: 1.0, # required # } # # @!attribute [rw] target_objective_metric_value # The value of the objective metric. # @return [Float] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/TuningJobCompletionCriteria AWS API Documentation # class TuningJobCompletionCriteria < Struct.new( :target_objective_metric_value) SENSITIVE = [] include Aws::Structure end # Represents an amount of money in United States dollars. # # @note When making an API call, you may pass USD # data as a hash: # # { # dollars: 1, # cents: 1, # tenth_fractions_of_a_cent: 1, # } # # @!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. # # @note When making an API call, you may pass UiConfig # data as a hash: # # { # ui_template_s3_uri: "S3Uri", # human_task_ui_arn: "HumanTaskUiArn", # } # # @!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 3D point # cloud and video fram 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 AWS # region you are creating your labeling job in. # # **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. # # @note When making an API call, you may pass UiTemplate # data as a hash: # # { # content: "TemplateContent", # required # } # # @!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 # @note When making an API call, you may pass UpdateActionRequest # data as a hash: # # { # action_name: "ExperimentEntityName", # required # description: "ExperimentDescription", # status: "Unknown", # accepts Unknown, InProgress, Completed, Failed, Stopping, Stopped # properties: { # "StringParameterValue" => "StringParameterValue", # }, # properties_to_remove: ["StringParameterValue"], # } # # @!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 # @note When making an API call, you may pass UpdateAppImageConfigRequest # data as a hash: # # { # app_image_config_name: "AppImageConfigName", # required # kernel_gateway_image_config: { # kernel_specs: [ # required # { # name: "KernelName", # required # display_name: "KernelDisplayName", # }, # ], # file_system_config: { # mount_path: "MountPath", # default_uid: 1, # default_gid: 1, # }, # }, # } # # @!attribute [rw] app_image_config_name # The name of the AppImageConfig to update. # @return [String] # # @!attribute [rw] kernel_gateway_image_config # The new KernelGateway app to run on the image. # @return [Types::KernelGatewayImageConfig] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateAppImageConfigRequest AWS API Documentation # class UpdateAppImageConfigRequest < Struct.new( :app_image_config_name, :kernel_gateway_image_config) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] app_image_config_arn # The Amazon Resource Name (ARN) for the AppImageConfig. # @return [String] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UpdateAppImageConfigResponse AWS API Documentation # class UpdateAppImageConfigResponse < Struct.new( :app_image_config_arn) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass UpdateArtifactRequest # data as a hash: # # { # artifact_arn: "ArtifactArn", # required # artifact_name: "ExperimentEntityName", # properties: { # "StringParameterValue" => "StringParameterValue", # }, # properties_to_remove: ["StringParameterValue"], # } # # @!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 # @note When making an API call, you may pass UpdateCodeRepositoryInput # data as a hash: # # { # code_repository_name: "EntityName", # required # git_config: { # secret_arn: "SecretArn", # }, # } # # @!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 AWS 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 # @note When making an API call, you may pass UpdateContextRequest # data as a hash: # # { # context_name: "ExperimentEntityName", # required # description: "ExperimentDescription", # properties: { # "StringParameterValue" => "StringParameterValue", # }, # properties_to_remove: ["StringParameterValue"], # } # # @!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 # @note When making an API call, you may pass UpdateDeviceFleetRequest # data as a hash: # # { # device_fleet_name: "EntityName", # required # role_arn: "RoleArn", # description: "DeviceFleetDescription", # output_config: { # required # s3_output_location: "S3Uri", # required # kms_key_id: "KmsKeyId", # }, # } # # @!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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass UpdateDevicesRequest # data as a hash: # # { # device_fleet_name: "EntityName", # required # devices: [ # required # { # device_name: "DeviceName", # required # description: "DeviceDescription", # iot_thing_name: "ThingName", # }, # ], # } # # @!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 # @note When making an API call, you may pass UpdateDomainRequest # data as a hash: # # { # domain_id: "DomainId", # required # default_user_settings: { # execution_role: "RoleArn", # security_groups: ["SecurityGroupId"], # sharing_settings: { # notebook_output_option: "Allowed", # accepts Allowed, Disabled # s3_output_path: "S3Uri", # s3_kms_key_id: "KmsKeyId", # }, # jupyter_server_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # kernel_gateway_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # custom_images: [ # { # image_name: "ImageName", # required # image_version_number: 1, # app_image_config_name: "AppImageConfigName", # required # }, # ], # }, # tensor_board_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # }, # } # # @!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] # # @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) 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 # @note When making an API call, you may pass UpdateEndpointInput # data as a hash: # # { # endpoint_name: "EndpointName", # required # endpoint_config_name: "EndpointConfigName", # required # retain_all_variant_properties: false, # exclude_retained_variant_properties: [ # { # variant_property_type: "DesiredInstanceCount", # required, accepts DesiredInstanceCount, DesiredWeight, DataCaptureConfig # }, # ], # deployment_config: { # blue_green_update_policy: { # required # traffic_routing_configuration: { # required # type: "ALL_AT_ONCE", # required, accepts ALL_AT_ONCE, CANARY # wait_interval_in_seconds: 1, # required # canary_size: { # type: "INSTANCE_COUNT", # required, accepts INSTANCE_COUNT, CAPACITY_PERCENT # value: 1, # required # }, # }, # termination_wait_in_seconds: 1, # maximum_execution_timeout_in_seconds: 1, # }, # auto_rollback_configuration: { # alarms: [ # { # alarm_name: "AlarmName", # }, # ], # }, # }, # } # # @!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 # UpdateEndpointInput$RetainAllVariantProperties, whose value is set # to `true`, `ExcludeRetainedVariantProperties` specifies the list of # type VariantProperty to override with the values provided by # `EndpointConfig`. If you don't specify a value for # `ExcludeAllVariantProperties`, no variant properties are overridden. # @return [Array] # # @!attribute [rw] deployment_config # The deployment configuration for the endpoint to be updated. # @return [Types::DeploymentConfig] # # @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) 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 # @note When making an API call, you may pass UpdateEndpointWeightsAndCapacitiesInput # data as a hash: # # { # endpoint_name: "EndpointName", # required # desired_weights_and_capacities: [ # required # { # variant_name: "VariantName", # required # desired_weight: 1.0, # desired_instance_count: 1, # }, # ], # } # # @!attribute [rw] endpoint_name # The name of an existing Amazon 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 # @note When making an API call, you may pass UpdateExperimentRequest # data as a hash: # # { # experiment_name: "ExperimentEntityName", # required # display_name: "ExperimentEntityName", # description: "ExperimentDescription", # } # # @!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 # @note When making an API call, you may pass UpdateImageRequest # data as a hash: # # { # delete_properties: ["ImageDeleteProperty"], # description: "ImageDescription", # display_name: "ImageDisplayName", # image_name: "ImageName", # required # role_arn: "RoleArn", # } # # @!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 Amazon Resource Name (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 Amazon Resource Name (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 # @note When making an API call, you may pass UpdateModelPackageInput # data as a hash: # # { # model_package_arn: "ModelPackageArn", # required # model_approval_status: "Approved", # required, accepts Approved, Rejected, PendingManualApproval # approval_description: "ApprovalDescription", # } # # @!attribute [rw] model_package_arn # The Amazon Resource Name (ARN) of the model. # @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] # # @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) 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 # @note When making an API call, you may pass UpdateMonitoringScheduleRequest # data as a hash: # # { # monitoring_schedule_name: "MonitoringScheduleName", # required # monitoring_schedule_config: { # required # schedule_config: { # schedule_expression: "ScheduleExpression", # required # }, # monitoring_job_definition: { # baseline_config: { # baselining_job_name: "ProcessingJobName", # constraints_resource: { # s3_uri: "S3Uri", # }, # statistics_resource: { # s3_uri: "S3Uri", # }, # }, # monitoring_inputs: [ # required # { # endpoint_input: { # required # endpoint_name: "EndpointName", # required # local_path: "ProcessingLocalPath", # required # s3_input_mode: "Pipe", # accepts Pipe, File # s3_data_distribution_type: "FullyReplicated", # accepts FullyReplicated, ShardedByS3Key # features_attribute: "String", # inference_attribute: "String", # probability_attribute: "String", # probability_threshold_attribute: 1.0, # start_time_offset: "MonitoringTimeOffsetString", # end_time_offset: "MonitoringTimeOffsetString", # }, # }, # ], # monitoring_output_config: { # required # monitoring_outputs: [ # required # { # s3_output: { # required # s3_uri: "MonitoringS3Uri", # required # local_path: "ProcessingLocalPath", # required # s3_upload_mode: "Continuous", # accepts Continuous, EndOfJob # }, # }, # ], # kms_key_id: "KmsKeyId", # }, # monitoring_resources: { # required # cluster_config: { # required # instance_count: 1, # required # instance_type: "ml.t3.medium", # required, accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # required # volume_kms_key_id: "KmsKeyId", # }, # }, # monitoring_app_specification: { # required # image_uri: "ImageUri", # required # container_entrypoint: ["ContainerEntrypointString"], # container_arguments: ["ContainerArgument"], # record_preprocessor_source_uri: "S3Uri", # post_analytics_processor_source_uri: "S3Uri", # }, # stopping_condition: { # max_runtime_in_seconds: 1, # required # }, # environment: { # "ProcessingEnvironmentKey" => "ProcessingEnvironmentValue", # }, # network_config: { # enable_inter_container_traffic_encryption: false, # enable_network_isolation: false, # vpc_config: { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # }, # }, # role_arn: "RoleArn", # required # }, # monitoring_job_definition_name: "MonitoringJobDefinitionName", # monitoring_type: "DataQuality", # accepts DataQuality, ModelQuality, ModelBias, ModelExplainability # }, # } # # @!attribute [rw] monitoring_schedule_name # The name of the monitoring schedule. The name must be unique within # an AWS Region within an AWS 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 # @note When making an API call, you may pass UpdateNotebookInstanceInput # data as a hash: # # { # notebook_instance_name: "NotebookInstanceName", # required # instance_type: "ml.t2.medium", # accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge # role_arn: "RoleArn", # lifecycle_config_name: "NotebookInstanceLifecycleConfigName", # disassociate_lifecycle_config: false, # volume_size_in_gb: 1, # default_code_repository: "CodeRepositoryNameOrUrl", # additional_code_repositories: ["CodeRepositoryNameOrUrl"], # accelerator_types: ["ml.eia1.medium"], # accepts ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge # disassociate_accelerator_types: false, # disassociate_default_code_repository: false, # disassociate_additional_code_repositories: false, # root_access: "Enabled", # accepts Enabled, Disabled # } # # @!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 Amazon SageMaker # can assume to access the notebook instance. For more information, # see [Amazon SageMaker Roles][1]. # # To be able to pass this role to Amazon 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 Amazon 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 [AWS 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 Amazon 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 [AWS 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 Amazon 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] # # @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) SENSITIVE = [] include Aws::Structure end # @note When making an API call, you may pass UpdateNotebookInstanceLifecycleConfigInput # data as a hash: # # { # notebook_instance_lifecycle_config_name: "NotebookInstanceLifecycleConfigName", # required # on_create: [ # { # content: "NotebookInstanceLifecycleConfigContent", # }, # ], # on_start: [ # { # content: "NotebookInstanceLifecycleConfigContent", # }, # ], # } # # @!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 # @note When making an API call, you may pass UpdatePipelineExecutionRequest # data as a hash: # # { # pipeline_execution_arn: "PipelineExecutionArn", # required # pipeline_execution_description: "PipelineExecutionDescription", # pipeline_execution_display_name: "PipelineExecutionName", # } # # @!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] # # @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) 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 # @note When making an API call, you may pass UpdatePipelineRequest # data as a hash: # # { # pipeline_name: "PipelineName", # required # pipeline_display_name: "PipelineName", # pipeline_definition: "PipelineDefinition", # pipeline_description: "PipelineDescription", # role_arn: "RoleArn", # } # # @!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_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] # # @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_description, :role_arn) 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 # @note When making an API call, you may pass UpdateTrainingJobRequest # data as a hash: # # { # training_job_name: "TrainingJobName", # required # profiler_config: { # s3_output_path: "S3Uri", # profiling_interval_in_milliseconds: 1, # profiling_parameters: { # "ConfigKey" => "ConfigValue", # }, # disable_profiler: false, # }, # profiler_rule_configurations: [ # { # rule_configuration_name: "RuleConfigurationName", # required # local_path: "DirectoryPath", # s3_output_path: "S3Uri", # rule_evaluator_image: "AlgorithmImage", # required # instance_type: "ml.t3.medium", # accepts ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.8xlarge, ml.r5.12xlarge, ml.r5.16xlarge, ml.r5.24xlarge # volume_size_in_gb: 1, # rule_parameters: { # "ConfigKey" => "ConfigValue", # }, # }, # ], # } # # @!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 Debugger system monitoring, framework # profiling, and storage paths. # @return [Types::ProfilerConfigForUpdate] # # @!attribute [rw] profiler_rule_configurations # Configuration information for Debugger rules for profiling system # and framework metrics. # @return [Array] # # @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) 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 # @note When making an API call, you may pass UpdateTrialComponentRequest # data as a hash: # # { # trial_component_name: "ExperimentEntityName", # required # display_name: "ExperimentEntityName", # status: { # primary_status: "InProgress", # accepts InProgress, Completed, Failed, Stopping, Stopped # message: "TrialComponentStatusMessage", # }, # start_time: Time.now, # end_time: Time.now, # parameters: { # "TrialComponentKey256" => { # string_value: "StringParameterValue", # number_value: 1.0, # }, # }, # parameters_to_remove: ["TrialComponentKey256"], # input_artifacts: { # "TrialComponentKey64" => { # media_type: "MediaType", # value: "TrialComponentArtifactValue", # required # }, # }, # input_artifacts_to_remove: ["TrialComponentKey256"], # output_artifacts: { # "TrialComponentKey64" => { # media_type: "MediaType", # value: "TrialComponentArtifactValue", # required # }, # }, # output_artifacts_to_remove: ["TrialComponentKey256"], # } # # @!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. # @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. # @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. # @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 # @note When making an API call, you may pass UpdateTrialRequest # data as a hash: # # { # trial_name: "ExperimentEntityName", # required # display_name: "ExperimentEntityName", # } # # @!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 # @note When making an API call, you may pass UpdateUserProfileRequest # data as a hash: # # { # domain_id: "DomainId", # required # user_profile_name: "UserProfileName", # required # user_settings: { # execution_role: "RoleArn", # security_groups: ["SecurityGroupId"], # sharing_settings: { # notebook_output_option: "Allowed", # accepts Allowed, Disabled # s3_output_path: "S3Uri", # s3_kms_key_id: "KmsKeyId", # }, # jupyter_server_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # kernel_gateway_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # custom_images: [ # { # image_name: "ImageName", # required # image_version_number: 1, # app_image_config_name: "AppImageConfigName", # required # }, # ], # }, # tensor_board_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # }, # } # # @!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 # @note When making an API call, you may pass UpdateWorkforceRequest # data as a hash: # # { # workforce_name: "WorkforceName", # required # source_ip_config: { # cidrs: ["Cidr"], # required # }, # oidc_config: { # client_id: "ClientId", # required # client_secret: "ClientSecret", # required # issuer: "OidcEndpoint", # required # authorization_endpoint: "OidcEndpoint", # required # token_endpoint: "OidcEndpoint", # required # user_info_endpoint: "OidcEndpoint", # required # logout_endpoint: "OidcEndpoint", # required # jwks_uri: "OidcEndpoint", # required # }, # } # # @!attribute [rw] workforce_name # The name of the private workforce that you want to update. You can # find your workforce name by using the operation. # @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] # # @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) SENSITIVE = [] include Aws::Structure end # @!attribute [rw] workforce # A single private workforce. You can create one private work force in # each AWS Region. By default, any workforce-related API operation # used in a specific region will apply to the workforce created in # that region. To learn how to create a private workforce, see [Create # a Private Workforce][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 # @note When making an API call, you may pass UpdateWorkteamRequest # data as a hash: # # { # workteam_name: "WorkteamName", # required # member_definitions: [ # { # cognito_member_definition: { # user_pool: "CognitoUserPool", # required # user_group: "CognitoUserGroup", # required # client_id: "ClientId", # required # }, # oidc_member_definition: { # groups: ["Group"], # required # }, # }, # ], # description: "String200", # notification_configuration: { # notification_topic_arn: "NotificationTopicArn", # }, # } # # @!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, or trial component. # # @!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] # # @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) SENSITIVE = [] include Aws::Structure end # The user profile details. # # @!attribute [rw] domain_id # The domain ID. # @return [String] # # @!attribute [rw] user_profile_name # The user profile name. # @return [String] # # @!attribute [rw] status # The status. # @return [String] # # @!attribute [rw] creation_time # The creation time. # @return [Time] # # @!attribute [rw] last_modified_time # The last modified time. # @return [Time] # # @see http://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/UserProfileDetails AWS API Documentation # class UserProfileDetails < Struct.new( :domain_id, :user_profile_name, :status, :creation_time, :last_modified_time) SENSITIVE = [] include Aws::Structure end # A collection of settings that apply to users of Amazon SageMaker # Studio. These settings are specified when the `CreateUserProfile` API # is called, and as `DefaultUserSettings` when the `CreateDomain` API is # called. # # `SecurityGroups` is aggregated when specified in both calls. For all # other settings in `UserSettings`, the values specified in # `CreateUserProfile` take precedence over those specified in # `CreateDomain`. # # @note When making an API call, you may pass UserSettings # data as a hash: # # { # execution_role: "RoleArn", # security_groups: ["SecurityGroupId"], # sharing_settings: { # notebook_output_option: "Allowed", # accepts Allowed, Disabled # s3_output_path: "S3Uri", # s3_kms_key_id: "KmsKeyId", # }, # jupyter_server_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # kernel_gateway_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # custom_images: [ # { # image_name: "ImageName", # required # image_version_number: 1, # app_image_config_name: "AppImageConfigName", # required # }, # ], # }, # tensor_board_app_settings: { # default_resource_spec: { # sage_maker_image_arn: "ImageArn", # sage_maker_image_version_arn: "ImageVersionArn", # instance_type: "system", # accepts system, ml.t3.micro, ml.t3.small, ml.t3.medium, ml.t3.large, ml.t3.xlarge, ml.t3.2xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.8xlarge, ml.m5.12xlarge, ml.m5.16xlarge, ml.m5.24xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.12xlarge, ml.c5.18xlarge, ml.c5.24xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge # }, # }, # } # # @!attribute [rw] execution_role # The execution role for the user. # @return [String] # # @!attribute [rw] security_groups # The security groups for the Amazon Virtual Private Cloud (VPC) that # Studio uses for communication. # # Optional when the `CreateDomain.AppNetworkAccessType` parameter is # set to `PublicInternetOnly`. # # Required when the `CreateDomain.AppNetworkAccessType` parameter is # set to `VpcOnly`. # # Amazon SageMaker adds a security group to allow NFS traffic from # SageMaker Studio. Therefore, the number of security groups that you # can specify is one less than the maximum number shown. # @return [Array] # # @!attribute [rw] sharing_settings # Specifies options for sharing SageMaker Studio notebooks. # @return [Types::SharingSettings] # # @!attribute [rw] jupyter_server_app_settings # The Jupyter server's app settings. # @return [Types::JupyterServerAppSettings] # # @!attribute [rw] kernel_gateway_app_settings # The kernel gateway app settings. # @return [Types::KernelGatewayAppSettings] # # @!attribute [rw] tensor_board_app_settings # The TensorBoard app settings. # @return [Types::TensorBoardAppSettings] # # @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) SENSITIVE = [] include Aws::Structure end # Specifies a production variant property type for an Endpoint. # # If you are updating an endpoint with the # UpdateEndpointInput$RetainAllVariantProperties option set to `true`, # the `VariantProperty` objects listed in # UpdateEndpointInput$ExcludeRetainedVariantProperties override the # existing variant properties of the endpoint. # # @note When making an API call, you may pass VariantProperty # data as a hash: # # { # variant_property_type: "DesiredInstanceCount", # required, accepts DesiredInstanceCount, DesiredWeight, DataCaptureConfig # } # # @!attribute [rw] variant_property_type # The type of variant property. The supported values are: # # * `DesiredInstanceCount`\: Overrides the existing variant instance # counts using the ProductionVariant$InitialInstanceCount values in # the CreateEndpointConfigInput$ProductionVariants. # # * `DesiredWeight`\: Overrides the existing variant weights using the # ProductionVariant$InitialVariantWeight values in the # CreateEndpointConfigInput$ProductionVariants. # # * `DataCaptureConfig`\: (Not currently supported.) # @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 # Specifies a VPC that your training jobs and hosted models have access # to. Control access to and from your training and model containers by # configuring the VPC. For more information, see [Protect Endpoints by # Using an Amazon Virtual Private Cloud][1] and [Protect Training Jobs # by Using an Amazon Virtual Private Cloud][2]. # # # # [1]: https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html # [2]: https://docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html # # @note When making an API call, you may pass VpcConfig # data as a hash: # # { # security_group_ids: ["SecurityGroupId"], # required # subnets: ["SubnetId"], # required # } # # @!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 # A single private workforce, which is automatically created when you # create your first private work team. You can create one private work # force in each AWS Region. By default, any workforce-related API # operation used in a specific region will apply to the workforce # created in that region. To learn how to create a private workforce, # see [Create a Private Workforce][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 was used to successfully add one or more # IP address ranges ([CIDRs][1]) to a private workforce's allow list. # # # # [1]: 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] # # @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) 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