Literals#
Index > CleanRoomsML > Literals
Auto-generated documentation for CleanRoomsML type annotations stubs module types-boto3-cleanroomsml.
AudienceExportJobStatusType#
# AudienceExportJobStatusType usage example
from types_boto3_cleanroomsml.literals import AudienceExportJobStatusType
def get_value() -> AudienceExportJobStatusType:
return "ACTIVE"
# AudienceExportJobStatusType definition
AudienceExportJobStatusType = Literal[
"ACTIVE",
"CREATE_FAILED",
"CREATE_IN_PROGRESS",
"CREATE_PENDING",
]
AudienceGenerationJobStatusType#
# AudienceGenerationJobStatusType usage example
from types_boto3_cleanroomsml.literals import AudienceGenerationJobStatusType
def get_value() -> AudienceGenerationJobStatusType:
return "ACTIVE"
# AudienceGenerationJobStatusType definition
AudienceGenerationJobStatusType = Literal[
"ACTIVE",
"CREATE_FAILED",
"CREATE_IN_PROGRESS",
"CREATE_PENDING",
"DELETE_FAILED",
"DELETE_IN_PROGRESS",
"DELETE_PENDING",
]
AudienceModelStatusType#
# AudienceModelStatusType usage example
from types_boto3_cleanroomsml.literals import AudienceModelStatusType
def get_value() -> AudienceModelStatusType:
return "ACTIVE"
# AudienceModelStatusType definition
AudienceModelStatusType = Literal[
"ACTIVE",
"CREATE_FAILED",
"CREATE_IN_PROGRESS",
"CREATE_PENDING",
"DELETE_FAILED",
"DELETE_IN_PROGRESS",
"DELETE_PENDING",
]
AudienceSizeTypeType#
# AudienceSizeTypeType usage example
from types_boto3_cleanroomsml.literals import AudienceSizeTypeType
def get_value() -> AudienceSizeTypeType:
return "ABSOLUTE"
# AudienceSizeTypeType definition
AudienceSizeTypeType = Literal[
"ABSOLUTE",
"PERCENTAGE",
]
ColumnTypeType#
# ColumnTypeType usage example
from types_boto3_cleanroomsml.literals import ColumnTypeType
def get_value() -> ColumnTypeType:
return "CATEGORICAL_FEATURE"
# ColumnTypeType definition
ColumnTypeType = Literal[
"CATEGORICAL_FEATURE",
"ITEM_ID",
"NUMERICAL_FEATURE",
"TIMESTAMP",
"USER_ID",
]
ConfiguredAudienceModelStatusType#
# ConfiguredAudienceModelStatusType usage example
from types_boto3_cleanroomsml.literals import ConfiguredAudienceModelStatusType
def get_value() -> ConfiguredAudienceModelStatusType:
return "ACTIVE"
# ConfiguredAudienceModelStatusType definition
ConfiguredAudienceModelStatusType = Literal[
"ACTIVE",
]
DatasetTypeType#
# DatasetTypeType usage example
from types_boto3_cleanroomsml.literals import DatasetTypeType
def get_value() -> DatasetTypeType:
return "INTERACTIONS"
# DatasetTypeType definition
DatasetTypeType = Literal[
"INTERACTIONS",
]
InferenceInstanceTypeType#
# InferenceInstanceTypeType usage example
from types_boto3_cleanroomsml.literals import InferenceInstanceTypeType
def get_value() -> InferenceInstanceTypeType:
return "ml.c4.2xlarge"
# InferenceInstanceTypeType definition
InferenceInstanceTypeType = Literal[
"ml.c4.2xlarge",
"ml.c4.4xlarge",
"ml.c4.8xlarge",
"ml.c4.xlarge",
"ml.c5.18xlarge",
"ml.c5.2xlarge",
"ml.c5.4xlarge",
"ml.c5.9xlarge",
"ml.c5.xlarge",
"ml.c6i.12xlarge",
"ml.c6i.16xlarge",
"ml.c6i.24xlarge",
"ml.c6i.2xlarge",
"ml.c6i.32xlarge",
"ml.c6i.4xlarge",
"ml.c6i.8xlarge",
"ml.c6i.large",
"ml.c6i.xlarge",
"ml.c7i.12xlarge",
"ml.c7i.16xlarge",
"ml.c7i.24xlarge",
"ml.c7i.2xlarge",
"ml.c7i.48xlarge",
"ml.c7i.4xlarge",
"ml.c7i.8xlarge",
"ml.c7i.large",
"ml.c7i.xlarge",
"ml.g4dn.12xlarge",
"ml.g4dn.16xlarge",
"ml.g4dn.2xlarge",
"ml.g4dn.4xlarge",
"ml.g4dn.8xlarge",
"ml.g4dn.xlarge",
"ml.g5.12xlarge",
"ml.g5.16xlarge",
"ml.g5.24xlarge",
"ml.g5.2xlarge",
"ml.g5.48xlarge",
"ml.g5.4xlarge",
"ml.g5.8xlarge",
"ml.g5.xlarge",
"ml.m4.10xlarge",
"ml.m4.16xlarge",
"ml.m4.2xlarge",
"ml.m4.4xlarge",
"ml.m4.xlarge",
"ml.m5.12xlarge",
"ml.m5.24xlarge",
"ml.m5.2xlarge",
"ml.m5.4xlarge",
"ml.m5.large",
"ml.m5.xlarge",
"ml.m6i.12xlarge",
"ml.m6i.16xlarge",
"ml.m6i.24xlarge",
"ml.m6i.2xlarge",
"ml.m6i.32xlarge",
"ml.m6i.4xlarge",
"ml.m6i.8xlarge",
"ml.m6i.large",
"ml.m6i.xlarge",
"ml.m7i.12xlarge",
"ml.m7i.16xlarge",
"ml.m7i.24xlarge",
"ml.m7i.2xlarge",
"ml.m7i.48xlarge",
"ml.m7i.4xlarge",
"ml.m7i.8xlarge",
"ml.m7i.large",
"ml.m7i.xlarge",
"ml.p2.16xlarge",
"ml.p2.8xlarge",
"ml.p2.xlarge",
"ml.p3.16xlarge",
"ml.p3.2xlarge",
"ml.p3.8xlarge",
"ml.r6i.12xlarge",
"ml.r6i.16xlarge",
"ml.r6i.24xlarge",
"ml.r6i.2xlarge",
"ml.r6i.32xlarge",
"ml.r6i.4xlarge",
"ml.r6i.8xlarge",
"ml.r6i.large",
"ml.r6i.xlarge",
"ml.r7i.12xlarge",
"ml.r7i.16xlarge",
"ml.r7i.24xlarge",
"ml.r7i.2xlarge",
"ml.r7i.48xlarge",
"ml.r7i.4xlarge",
"ml.r7i.8xlarge",
"ml.r7i.large",
"ml.r7i.xlarge",
]
InstanceTypeType#
# InstanceTypeType usage example
from types_boto3_cleanroomsml.literals import InstanceTypeType
def get_value() -> InstanceTypeType:
return "ml.c4.2xlarge"
# InstanceTypeType definition
InstanceTypeType = Literal[
"ml.c4.2xlarge",
"ml.c4.4xlarge",
"ml.c4.8xlarge",
"ml.c4.xlarge",
"ml.c5.18xlarge",
"ml.c5.2xlarge",
"ml.c5.4xlarge",
"ml.c5.9xlarge",
"ml.c5.xlarge",
"ml.c5n.18xlarge",
"ml.c5n.2xlarge",
"ml.c5n.4xlarge",
"ml.c5n.9xlarge",
"ml.c5n.xlarge",
"ml.c6i.12xlarge",
"ml.c6i.16xlarge",
"ml.c6i.24xlarge",
"ml.c6i.2xlarge",
"ml.c6i.32xlarge",
"ml.c6i.4xlarge",
"ml.c6i.8xlarge",
"ml.c6i.xlarge",
"ml.g4dn.12xlarge",
"ml.g4dn.16xlarge",
"ml.g4dn.2xlarge",
"ml.g4dn.4xlarge",
"ml.g4dn.8xlarge",
"ml.g4dn.xlarge",
"ml.g5.12xlarge",
"ml.g5.16xlarge",
"ml.g5.24xlarge",
"ml.g5.2xlarge",
"ml.g5.48xlarge",
"ml.g5.4xlarge",
"ml.g5.8xlarge",
"ml.g5.xlarge",
"ml.m4.10xlarge",
"ml.m4.16xlarge",
"ml.m4.2xlarge",
"ml.m4.4xlarge",
"ml.m4.xlarge",
"ml.m5.12xlarge",
"ml.m5.24xlarge",
"ml.m5.2xlarge",
"ml.m5.4xlarge",
"ml.m5.large",
"ml.m5.xlarge",
"ml.m6i.12xlarge",
"ml.m6i.16xlarge",
"ml.m6i.24xlarge",
"ml.m6i.2xlarge",
"ml.m6i.32xlarge",
"ml.m6i.4xlarge",
"ml.m6i.8xlarge",
"ml.m6i.large",
"ml.m6i.xlarge",
"ml.p2.16xlarge",
"ml.p2.8xlarge",
"ml.p2.xlarge",
"ml.p3.16xlarge",
"ml.p3.2xlarge",
"ml.p3.8xlarge",
"ml.p3dn.24xlarge",
"ml.p4d.24xlarge",
"ml.p4de.24xlarge",
"ml.p5.48xlarge",
"ml.r5.12xlarge",
"ml.r5.16xlarge",
"ml.r5.24xlarge",
"ml.r5.2xlarge",
"ml.r5.4xlarge",
"ml.r5.8xlarge",
"ml.r5.large",
"ml.r5.xlarge",
"ml.r5d.12xlarge",
"ml.r5d.16xlarge",
"ml.r5d.24xlarge",
"ml.r5d.2xlarge",
"ml.r5d.4xlarge",
"ml.r5d.8xlarge",
"ml.r5d.large",
"ml.r5d.xlarge",
"ml.t3.2xlarge",
"ml.t3.large",
"ml.t3.medium",
"ml.t3.xlarge",
"ml.trn1.2xlarge",
"ml.trn1.32xlarge",
"ml.trn1n.32xlarge",
]
ListAudienceExportJobsPaginatorName#
# ListAudienceExportJobsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListAudienceExportJobsPaginatorName
def get_value() -> ListAudienceExportJobsPaginatorName:
return "list_audience_export_jobs"
# ListAudienceExportJobsPaginatorName definition
ListAudienceExportJobsPaginatorName = Literal[
"list_audience_export_jobs",
]
ListAudienceGenerationJobsPaginatorName#
# ListAudienceGenerationJobsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListAudienceGenerationJobsPaginatorName
def get_value() -> ListAudienceGenerationJobsPaginatorName:
return "list_audience_generation_jobs"
# ListAudienceGenerationJobsPaginatorName definition
ListAudienceGenerationJobsPaginatorName = Literal[
"list_audience_generation_jobs",
]
ListAudienceModelsPaginatorName#
# ListAudienceModelsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListAudienceModelsPaginatorName
def get_value() -> ListAudienceModelsPaginatorName:
return "list_audience_models"
# ListAudienceModelsPaginatorName definition
ListAudienceModelsPaginatorName = Literal[
"list_audience_models",
]
ListCollaborationConfiguredModelAlgorithmAssociationsPaginatorName#
# ListCollaborationConfiguredModelAlgorithmAssociationsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListCollaborationConfiguredModelAlgorithmAssociationsPaginatorName
def get_value() -> ListCollaborationConfiguredModelAlgorithmAssociationsPaginatorName:
return "list_collaboration_configured_model_algorithm_associations"
# ListCollaborationConfiguredModelAlgorithmAssociationsPaginatorName definition
ListCollaborationConfiguredModelAlgorithmAssociationsPaginatorName = Literal[
"list_collaboration_configured_model_algorithm_associations",
]
ListCollaborationMLInputChannelsPaginatorName#
# ListCollaborationMLInputChannelsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListCollaborationMLInputChannelsPaginatorName
def get_value() -> ListCollaborationMLInputChannelsPaginatorName:
return "list_collaboration_ml_input_channels"
# ListCollaborationMLInputChannelsPaginatorName definition
ListCollaborationMLInputChannelsPaginatorName = Literal[
"list_collaboration_ml_input_channels",
]
ListCollaborationTrainedModelExportJobsPaginatorName#
# ListCollaborationTrainedModelExportJobsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListCollaborationTrainedModelExportJobsPaginatorName
def get_value() -> ListCollaborationTrainedModelExportJobsPaginatorName:
return "list_collaboration_trained_model_export_jobs"
# ListCollaborationTrainedModelExportJobsPaginatorName definition
ListCollaborationTrainedModelExportJobsPaginatorName = Literal[
"list_collaboration_trained_model_export_jobs",
]
ListCollaborationTrainedModelInferenceJobsPaginatorName#
# ListCollaborationTrainedModelInferenceJobsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListCollaborationTrainedModelInferenceJobsPaginatorName
def get_value() -> ListCollaborationTrainedModelInferenceJobsPaginatorName:
return "list_collaboration_trained_model_inference_jobs"
# ListCollaborationTrainedModelInferenceJobsPaginatorName definition
ListCollaborationTrainedModelInferenceJobsPaginatorName = Literal[
"list_collaboration_trained_model_inference_jobs",
]
ListCollaborationTrainedModelsPaginatorName#
# ListCollaborationTrainedModelsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListCollaborationTrainedModelsPaginatorName
def get_value() -> ListCollaborationTrainedModelsPaginatorName:
return "list_collaboration_trained_models"
# ListCollaborationTrainedModelsPaginatorName definition
ListCollaborationTrainedModelsPaginatorName = Literal[
"list_collaboration_trained_models",
]
ListConfiguredAudienceModelsPaginatorName#
# ListConfiguredAudienceModelsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListConfiguredAudienceModelsPaginatorName
def get_value() -> ListConfiguredAudienceModelsPaginatorName:
return "list_configured_audience_models"
# ListConfiguredAudienceModelsPaginatorName definition
ListConfiguredAudienceModelsPaginatorName = Literal[
"list_configured_audience_models",
]
ListConfiguredModelAlgorithmAssociationsPaginatorName#
# ListConfiguredModelAlgorithmAssociationsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListConfiguredModelAlgorithmAssociationsPaginatorName
def get_value() -> ListConfiguredModelAlgorithmAssociationsPaginatorName:
return "list_configured_model_algorithm_associations"
# ListConfiguredModelAlgorithmAssociationsPaginatorName definition
ListConfiguredModelAlgorithmAssociationsPaginatorName = Literal[
"list_configured_model_algorithm_associations",
]
ListConfiguredModelAlgorithmsPaginatorName#
# ListConfiguredModelAlgorithmsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListConfiguredModelAlgorithmsPaginatorName
def get_value() -> ListConfiguredModelAlgorithmsPaginatorName:
return "list_configured_model_algorithms"
# ListConfiguredModelAlgorithmsPaginatorName definition
ListConfiguredModelAlgorithmsPaginatorName = Literal[
"list_configured_model_algorithms",
]
ListMLInputChannelsPaginatorName#
# ListMLInputChannelsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListMLInputChannelsPaginatorName
def get_value() -> ListMLInputChannelsPaginatorName:
return "list_ml_input_channels"
# ListMLInputChannelsPaginatorName definition
ListMLInputChannelsPaginatorName = Literal[
"list_ml_input_channels",
]
ListTrainedModelInferenceJobsPaginatorName#
# ListTrainedModelInferenceJobsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListTrainedModelInferenceJobsPaginatorName
def get_value() -> ListTrainedModelInferenceJobsPaginatorName:
return "list_trained_model_inference_jobs"
# ListTrainedModelInferenceJobsPaginatorName definition
ListTrainedModelInferenceJobsPaginatorName = Literal[
"list_trained_model_inference_jobs",
]
ListTrainedModelsPaginatorName#
# ListTrainedModelsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListTrainedModelsPaginatorName
def get_value() -> ListTrainedModelsPaginatorName:
return "list_trained_models"
# ListTrainedModelsPaginatorName definition
ListTrainedModelsPaginatorName = Literal[
"list_trained_models",
]
ListTrainingDatasetsPaginatorName#
# ListTrainingDatasetsPaginatorName usage example
from types_boto3_cleanroomsml.literals import ListTrainingDatasetsPaginatorName
def get_value() -> ListTrainingDatasetsPaginatorName:
return "list_training_datasets"
# ListTrainingDatasetsPaginatorName definition
ListTrainingDatasetsPaginatorName = Literal[
"list_training_datasets",
]
LogsStatusType#
# LogsStatusType usage example
from types_boto3_cleanroomsml.literals import LogsStatusType
def get_value() -> LogsStatusType:
return "PUBLISH_FAILED"
# LogsStatusType definition
LogsStatusType = Literal[
"PUBLISH_FAILED",
"PUBLISH_SUCCEEDED",
]
MLInputChannelStatusType#
# MLInputChannelStatusType usage example
from types_boto3_cleanroomsml.literals import MLInputChannelStatusType
def get_value() -> MLInputChannelStatusType:
return "ACTIVE"
# MLInputChannelStatusType definition
MLInputChannelStatusType = Literal[
"ACTIVE",
"CREATE_FAILED",
"CREATE_IN_PROGRESS",
"CREATE_PENDING",
"DELETE_FAILED",
"DELETE_IN_PROGRESS",
"DELETE_PENDING",
"INACTIVE",
]
MetricsStatusType#
# MetricsStatusType usage example
from types_boto3_cleanroomsml.literals import MetricsStatusType
def get_value() -> MetricsStatusType:
return "PUBLISH_FAILED"
# MetricsStatusType definition
MetricsStatusType = Literal[
"PUBLISH_FAILED",
"PUBLISH_SUCCEEDED",
]
NoiseLevelTypeType#
# NoiseLevelTypeType usage example
from types_boto3_cleanroomsml.literals import NoiseLevelTypeType
def get_value() -> NoiseLevelTypeType:
return "HIGH"
# NoiseLevelTypeType definition
NoiseLevelTypeType = Literal[
"HIGH",
"LOW",
"MEDIUM",
"NONE",
]
PolicyExistenceConditionType#
# PolicyExistenceConditionType usage example
from types_boto3_cleanroomsml.literals import PolicyExistenceConditionType
def get_value() -> PolicyExistenceConditionType:
return "POLICY_MUST_EXIST"
# PolicyExistenceConditionType definition
PolicyExistenceConditionType = Literal[
"POLICY_MUST_EXIST",
"POLICY_MUST_NOT_EXIST",
]
SharedAudienceMetricsType#
# SharedAudienceMetricsType usage example
from types_boto3_cleanroomsml.literals import SharedAudienceMetricsType
def get_value() -> SharedAudienceMetricsType:
return "ALL"
# SharedAudienceMetricsType definition
SharedAudienceMetricsType = Literal[
"ALL",
"NONE",
]
TagOnCreatePolicyType#
# TagOnCreatePolicyType usage example
from types_boto3_cleanroomsml.literals import TagOnCreatePolicyType
def get_value() -> TagOnCreatePolicyType:
return "FROM_PARENT_RESOURCE"
# TagOnCreatePolicyType definition
TagOnCreatePolicyType = Literal[
"FROM_PARENT_RESOURCE",
"NONE",
]
TrainedModelExportFileTypeType#
# TrainedModelExportFileTypeType usage example
from types_boto3_cleanroomsml.literals import TrainedModelExportFileTypeType
def get_value() -> TrainedModelExportFileTypeType:
return "MODEL"
# TrainedModelExportFileTypeType definition
TrainedModelExportFileTypeType = Literal[
"MODEL",
"OUTPUT",
]
TrainedModelExportJobStatusType#
# TrainedModelExportJobStatusType usage example
from types_boto3_cleanroomsml.literals import TrainedModelExportJobStatusType
def get_value() -> TrainedModelExportJobStatusType:
return "ACTIVE"
# TrainedModelExportJobStatusType definition
TrainedModelExportJobStatusType = Literal[
"ACTIVE",
"CREATE_FAILED",
"CREATE_IN_PROGRESS",
"CREATE_PENDING",
]
TrainedModelExportsMaxSizeUnitTypeType#
# TrainedModelExportsMaxSizeUnitTypeType usage example
from types_boto3_cleanroomsml.literals import TrainedModelExportsMaxSizeUnitTypeType
def get_value() -> TrainedModelExportsMaxSizeUnitTypeType:
return "GB"
# TrainedModelExportsMaxSizeUnitTypeType definition
TrainedModelExportsMaxSizeUnitTypeType = Literal[
"GB",
]
TrainedModelInferenceJobStatusType#
# TrainedModelInferenceJobStatusType usage example
from types_boto3_cleanroomsml.literals import TrainedModelInferenceJobStatusType
def get_value() -> TrainedModelInferenceJobStatusType:
return "ACTIVE"
# TrainedModelInferenceJobStatusType definition
TrainedModelInferenceJobStatusType = Literal[
"ACTIVE",
"CANCEL_FAILED",
"CANCEL_IN_PROGRESS",
"CANCEL_PENDING",
"CREATE_FAILED",
"CREATE_IN_PROGRESS",
"CREATE_PENDING",
"INACTIVE",
]
TrainedModelInferenceMaxOutputSizeUnitTypeType#
# TrainedModelInferenceMaxOutputSizeUnitTypeType usage example
from types_boto3_cleanroomsml.literals import TrainedModelInferenceMaxOutputSizeUnitTypeType
def get_value() -> TrainedModelInferenceMaxOutputSizeUnitTypeType:
return "GB"
# TrainedModelInferenceMaxOutputSizeUnitTypeType definition
TrainedModelInferenceMaxOutputSizeUnitTypeType = Literal[
"GB",
]
TrainedModelStatusType#
# TrainedModelStatusType usage example
from types_boto3_cleanroomsml.literals import TrainedModelStatusType
def get_value() -> TrainedModelStatusType:
return "ACTIVE"
# TrainedModelStatusType definition
TrainedModelStatusType = Literal[
"ACTIVE",
"CANCEL_FAILED",
"CANCEL_IN_PROGRESS",
"CANCEL_PENDING",
"CREATE_FAILED",
"CREATE_IN_PROGRESS",
"CREATE_PENDING",
"DELETE_FAILED",
"DELETE_IN_PROGRESS",
"DELETE_PENDING",
"INACTIVE",
]
TrainingDatasetStatusType#
# TrainingDatasetStatusType usage example
from types_boto3_cleanroomsml.literals import TrainingDatasetStatusType
def get_value() -> TrainingDatasetStatusType:
return "ACTIVE"
# TrainingDatasetStatusType definition
TrainingDatasetStatusType = Literal[
"ACTIVE",
]
WorkerComputeTypeType#
# WorkerComputeTypeType usage example
from types_boto3_cleanroomsml.literals import WorkerComputeTypeType
def get_value() -> WorkerComputeTypeType:
return "CR.1X"
# WorkerComputeTypeType definition
WorkerComputeTypeType = Literal[
"CR.1X",
"CR.4X",
]
CleanRoomsMLServiceName#
# CleanRoomsMLServiceName usage example
from types_boto3_cleanroomsml.literals import CleanRoomsMLServiceName
def get_value() -> CleanRoomsMLServiceName:
return "cleanroomsml"
# CleanRoomsMLServiceName definition
CleanRoomsMLServiceName = Literal[
"cleanroomsml",
]
ServiceName#
# ServiceName usage example
from types_boto3_cleanroomsml.literals import ServiceName
def get_value() -> ServiceName:
return "accessanalyzer"
# ServiceName definition
ServiceName = Literal[
"accessanalyzer",
"account",
"acm",
"acm-pca",
"amp",
"amplify",
"amplifybackend",
"amplifyuibuilder",
"apigateway",
"apigatewaymanagementapi",
"apigatewayv2",
"appconfig",
"appconfigdata",
"appfabric",
"appflow",
"appintegrations",
"application-autoscaling",
"application-insights",
"application-signals",
"applicationcostprofiler",
"appmesh",
"apprunner",
"appstream",
"appsync",
"apptest",
"arc-zonal-shift",
"artifact",
"athena",
"auditmanager",
"autoscaling",
"autoscaling-plans",
"b2bi",
"backup",
"backup-gateway",
"backupsearch",
"batch",
"bcm-data-exports",
"bcm-pricing-calculator",
"bedrock",
"bedrock-agent",
"bedrock-agent-runtime",
"bedrock-data-automation",
"bedrock-data-automation-runtime",
"bedrock-runtime",
"billing",
"billingconductor",
"braket",
"budgets",
"ce",
"chatbot",
"chime",
"chime-sdk-identity",
"chime-sdk-media-pipelines",
"chime-sdk-meetings",
"chime-sdk-messaging",
"chime-sdk-voice",
"cleanrooms",
"cleanroomsml",
"cloud9",
"cloudcontrol",
"clouddirectory",
"cloudformation",
"cloudfront",
"cloudfront-keyvaluestore",
"cloudhsm",
"cloudhsmv2",
"cloudsearch",
"cloudsearchdomain",
"cloudtrail",
"cloudtrail-data",
"cloudwatch",
"codeartifact",
"codebuild",
"codecatalyst",
"codecommit",
"codeconnections",
"codedeploy",
"codeguru-reviewer",
"codeguru-security",
"codeguruprofiler",
"codepipeline",
"codestar-connections",
"codestar-notifications",
"cognito-identity",
"cognito-idp",
"cognito-sync",
"comprehend",
"comprehendmedical",
"compute-optimizer",
"config",
"connect",
"connect-contact-lens",
"connectcampaigns",
"connectcampaignsv2",
"connectcases",
"connectparticipant",
"controlcatalog",
"controltower",
"cost-optimization-hub",
"cur",
"customer-profiles",
"databrew",
"dataexchange",
"datapipeline",
"datasync",
"datazone",
"dax",
"deadline",
"detective",
"devicefarm",
"devops-guru",
"directconnect",
"discovery",
"dlm",
"dms",
"docdb",
"docdb-elastic",
"drs",
"ds",
"ds-data",
"dsql",
"dynamodb",
"dynamodbstreams",
"ebs",
"ec2",
"ec2-instance-connect",
"ecr",
"ecr-public",
"ecs",
"efs",
"eks",
"eks-auth",
"elastic-inference",
"elasticache",
"elasticbeanstalk",
"elastictranscoder",
"elb",
"elbv2",
"emr",
"emr-containers",
"emr-serverless",
"entityresolution",
"es",
"events",
"evidently",
"finspace",
"finspace-data",
"firehose",
"fis",
"fms",
"forecast",
"forecastquery",
"frauddetector",
"freetier",
"fsx",
"gamelift",
"geo-maps",
"geo-places",
"geo-routes",
"glacier",
"globalaccelerator",
"glue",
"grafana",
"greengrass",
"greengrassv2",
"groundstation",
"guardduty",
"health",
"healthlake",
"iam",
"identitystore",
"imagebuilder",
"importexport",
"inspector",
"inspector-scan",
"inspector2",
"internetmonitor",
"invoicing",
"iot",
"iot-data",
"iot-jobs-data",
"iot1click-devices",
"iot1click-projects",
"iotanalytics",
"iotdeviceadvisor",
"iotevents",
"iotevents-data",
"iotfleethub",
"iotfleetwise",
"iotsecuretunneling",
"iotsitewise",
"iotthingsgraph",
"iottwinmaker",
"iotwireless",
"ivs",
"ivs-realtime",
"ivschat",
"kafka",
"kafkaconnect",
"kendra",
"kendra-ranking",
"keyspaces",
"kinesis",
"kinesis-video-archived-media",
"kinesis-video-media",
"kinesis-video-signaling",
"kinesis-video-webrtc-storage",
"kinesisanalytics",
"kinesisanalyticsv2",
"kinesisvideo",
"kms",
"lakeformation",
"lambda",
"launch-wizard",
"lex-models",
"lex-runtime",
"lexv2-models",
"lexv2-runtime",
"license-manager",
"license-manager-linux-subscriptions",
"license-manager-user-subscriptions",
"lightsail",
"location",
"logs",
"lookoutequipment",
"lookoutmetrics",
"lookoutvision",
"m2",
"machinelearning",
"macie2",
"mailmanager",
"managedblockchain",
"managedblockchain-query",
"marketplace-agreement",
"marketplace-catalog",
"marketplace-deployment",
"marketplace-entitlement",
"marketplace-reporting",
"marketplacecommerceanalytics",
"mediaconnect",
"mediaconvert",
"medialive",
"mediapackage",
"mediapackage-vod",
"mediapackagev2",
"mediastore",
"mediastore-data",
"mediatailor",
"medical-imaging",
"memorydb",
"meteringmarketplace",
"mgh",
"mgn",
"migration-hub-refactor-spaces",
"migrationhub-config",
"migrationhuborchestrator",
"migrationhubstrategy",
"mq",
"mturk",
"mwaa",
"neptune",
"neptune-graph",
"neptunedata",
"network-firewall",
"networkflowmonitor",
"networkmanager",
"networkmonitor",
"notifications",
"notificationscontacts",
"oam",
"observabilityadmin",
"omics",
"opensearch",
"opensearchserverless",
"opsworks",
"opsworkscm",
"organizations",
"osis",
"outposts",
"panorama",
"partnercentral-selling",
"payment-cryptography",
"payment-cryptography-data",
"pca-connector-ad",
"pca-connector-scep",
"pcs",
"personalize",
"personalize-events",
"personalize-runtime",
"pi",
"pinpoint",
"pinpoint-email",
"pinpoint-sms-voice",
"pinpoint-sms-voice-v2",
"pipes",
"polly",
"pricing",
"privatenetworks",
"proton",
"qapps",
"qbusiness",
"qconnect",
"qldb",
"qldb-session",
"quicksight",
"ram",
"rbin",
"rds",
"rds-data",
"redshift",
"redshift-data",
"redshift-serverless",
"rekognition",
"repostspace",
"resiliencehub",
"resource-explorer-2",
"resource-groups",
"resourcegroupstaggingapi",
"robomaker",
"rolesanywhere",
"route53",
"route53-recovery-cluster",
"route53-recovery-control-config",
"route53-recovery-readiness",
"route53domains",
"route53profiles",
"route53resolver",
"rum",
"s3",
"s3control",
"s3outposts",
"s3tables",
"sagemaker",
"sagemaker-a2i-runtime",
"sagemaker-edge",
"sagemaker-featurestore-runtime",
"sagemaker-geospatial",
"sagemaker-metrics",
"sagemaker-runtime",
"savingsplans",
"scheduler",
"schemas",
"sdb",
"secretsmanager",
"security-ir",
"securityhub",
"securitylake",
"serverlessrepo",
"service-quotas",
"servicecatalog",
"servicecatalog-appregistry",
"servicediscovery",
"ses",
"sesv2",
"shield",
"signer",
"simspaceweaver",
"sms",
"sms-voice",
"snow-device-management",
"snowball",
"sns",
"socialmessaging",
"sqs",
"ssm",
"ssm-contacts",
"ssm-incidents",
"ssm-quicksetup",
"ssm-sap",
"sso",
"sso-admin",
"sso-oidc",
"stepfunctions",
"storagegateway",
"sts",
"supplychain",
"support",
"support-app",
"swf",
"synthetics",
"taxsettings",
"textract",
"timestream-influxdb",
"timestream-query",
"timestream-write",
"tnb",
"transcribe",
"transfer",
"translate",
"trustedadvisor",
"verifiedpermissions",
"voice-id",
"vpc-lattice",
"waf",
"waf-regional",
"wafv2",
"wellarchitected",
"wisdom",
"workdocs",
"workmail",
"workmailmessageflow",
"workspaces",
"workspaces-thin-client",
"workspaces-web",
"xray",
]
ResourceServiceName#
# ResourceServiceName usage example
from types_boto3_cleanroomsml.literals import ResourceServiceName
def get_value() -> ResourceServiceName:
return "cloudformation"
# ResourceServiceName definition
ResourceServiceName = Literal[
"cloudformation",
"cloudwatch",
"dynamodb",
"ec2",
"glacier",
"iam",
"opsworks",
"s3",
"sns",
"sqs",
]
PaginatorName#
# PaginatorName usage example
from types_boto3_cleanroomsml.literals import PaginatorName
def get_value() -> PaginatorName:
return "list_audience_export_jobs"
# PaginatorName definition
PaginatorName = Literal[
"list_audience_export_jobs",
"list_audience_generation_jobs",
"list_audience_models",
"list_collaboration_configured_model_algorithm_associations",
"list_collaboration_ml_input_channels",
"list_collaboration_trained_model_export_jobs",
"list_collaboration_trained_model_inference_jobs",
"list_collaboration_trained_models",
"list_configured_audience_models",
"list_configured_model_algorithm_associations",
"list_configured_model_algorithms",
"list_ml_input_channels",
"list_trained_model_inference_jobs",
"list_trained_models",
"list_training_datasets",
]