Package-level declarations

Types

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class AiDataset : KotlinCustomResource

A collection of DataItems and Annotations on them. To get more information about Dataset, see:

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data class AiDatasetArgs(val displayName: Output<String>? = null, val encryptionSpec: Output<AiDatasetEncryptionSpecArgs>? = null, val labels: Output<Map<String, String>>? = null, val metadataSchemaUri: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiDatasetArgs>

A collection of DataItems and Annotations on them. To get more information about Dataset, see:

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object AiDatasetMapper : ResourceMapper<AiDataset>
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class AiDeploymentResourcePool : KotlinCustomResource

'DeploymentResourcePool can be shared by multiple deployed models, whose underlying specification consists of dedicated resources.' To get more information about DeploymentResourcePool, see:

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data class AiDeploymentResourcePoolArgs(val dedicatedResources: Output<AiDeploymentResourcePoolDedicatedResourcesArgs>? = null, val name: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiDeploymentResourcePoolArgs>

'DeploymentResourcePool can be shared by multiple deployed models, whose underlying specification consists of dedicated resources.' To get more information about DeploymentResourcePool, see:

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class AiEndpoint : KotlinCustomResource

Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations. To get more information about Endpoint, see:

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data class AiEndpointArgs(val description: Output<String>? = null, val displayName: Output<String>? = null, val encryptionSpec: Output<AiEndpointEncryptionSpecArgs>? = null, val labels: Output<Map<String, String>>? = null, val location: Output<String>? = null, val name: Output<String>? = null, val network: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiEndpointArgs>

Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations. To get more information about Endpoint, see:

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class AiEndpointIamBinding : KotlinCustomResource
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data class AiEndpointIamBindingArgs(val condition: Output<AiEndpointIamBindingConditionArgs>? = null, val endpoint: Output<String>? = null, val location: Output<String>? = null, val members: Output<List<String>>? = null, val project: Output<String>? = null, val role: Output<String>? = null) : ConvertibleToJava<AiEndpointIamBindingArgs>
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class AiEndpointIamMember : KotlinCustomResource
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data class AiEndpointIamMemberArgs(val condition: Output<AiEndpointIamMemberConditionArgs>? = null, val endpoint: Output<String>? = null, val location: Output<String>? = null, val member: Output<String>? = null, val project: Output<String>? = null, val role: Output<String>? = null) : ConvertibleToJava<AiEndpointIamMemberArgs>
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class AiEndpointIamPolicy : KotlinCustomResource
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data class AiEndpointIamPolicyArgs(val endpoint: Output<String>? = null, val location: Output<String>? = null, val policyData: Output<String>? = null, val project: Output<String>? = null) : ConvertibleToJava<AiEndpointIamPolicyArgs>
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object AiEndpointMapper : ResourceMapper<AiEndpoint>
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class AiFeatureGroup : KotlinCustomResource

Vertex AI Feature Group. To get more information about FeatureGroup, see:

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data class AiFeatureGroupArgs(val bigQuery: Output<AiFeatureGroupBigQueryArgs>? = null, val description: Output<String>? = null, val labels: Output<Map<String, String>>? = null, val name: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiFeatureGroupArgs>

Vertex AI Feature Group. To get more information about FeatureGroup, see:

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class AiFeatureGroupFeature : KotlinCustomResource

Vertex AI Feature Group Feature is feature metadata information. To get more information about FeatureGroupFeature, see:

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data class AiFeatureGroupFeatureArgs(val description: Output<String>? = null, val featureGroup: Output<String>? = null, val labels: Output<Map<String, String>>? = null, val name: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null, val versionColumnName: Output<String>? = null) : ConvertibleToJava<AiFeatureGroupFeatureArgs>

Vertex AI Feature Group Feature is feature metadata information. To get more information about FeatureGroupFeature, see:

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object AiFeatureGroupMapper : ResourceMapper<AiFeatureGroup>
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class AiFeatureOnlineStore : KotlinCustomResource

Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container. To get more information about FeatureOnlineStore, see:

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data class AiFeatureOnlineStoreArgs(val bigtable: Output<AiFeatureOnlineStoreBigtableArgs>? = null, val dedicatedServingEndpoint: Output<AiFeatureOnlineStoreDedicatedServingEndpointArgs>? = null, val embeddingManagement: Output<AiFeatureOnlineStoreEmbeddingManagementArgs>? = null, val forceDestroy: Output<Boolean>? = null, val labels: Output<Map<String, String>>? = null, val name: Output<String>? = null, val optimized: Output<AiFeatureOnlineStoreOptimizedArgs>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiFeatureOnlineStoreArgs>

Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container. To get more information about FeatureOnlineStore, see:

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class AiFeatureOnlineStoreFeatureview : KotlinCustomResource

FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig. To get more information about FeatureOnlineStoreFeatureview, see:

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data class AiFeatureOnlineStoreFeatureviewArgs(val bigQuerySource: Output<AiFeatureOnlineStoreFeatureviewBigQuerySourceArgs>? = null, val featureOnlineStore: Output<String>? = null, val featureRegistrySource: Output<AiFeatureOnlineStoreFeatureviewFeatureRegistrySourceArgs>? = null, val labels: Output<Map<String, String>>? = null, val name: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null, val syncConfig: Output<AiFeatureOnlineStoreFeatureviewSyncConfigArgs>? = null, val vectorSearchConfig: Output<AiFeatureOnlineStoreFeatureviewVectorSearchConfigArgs>? = null) : ConvertibleToJava<AiFeatureOnlineStoreFeatureviewArgs>

FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig. To get more information about FeatureOnlineStoreFeatureview, see:

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class AiFeatureStore : KotlinCustomResource

A collection of DataItems and Annotations on them. To get more information about Featurestore, see:

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data class AiFeatureStoreArgs(val encryptionSpec: Output<AiFeatureStoreEncryptionSpecArgs>? = null, val forceDestroy: Output<Boolean>? = null, val labels: Output<Map<String, String>>? = null, val name: Output<String>? = null, val onlineServingConfig: Output<AiFeatureStoreOnlineServingConfigArgs>? = null, val onlineStorageTtlDays: Output<Int>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiFeatureStoreArgs>

A collection of DataItems and Annotations on them. To get more information about Featurestore, see:

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class AiFeatureStoreEntityType : KotlinCustomResource

An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver. To get more information about FeaturestoreEntitytype, see:

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data class AiFeatureStoreEntityTypeArgs(val description: Output<String>? = null, val featurestore: Output<String>? = null, val labels: Output<Map<String, String>>? = null, val monitoringConfig: Output<AiFeatureStoreEntityTypeMonitoringConfigArgs>? = null, val name: Output<String>? = null, val offlineStorageTtlDays: Output<Int>? = null) : ConvertibleToJava<AiFeatureStoreEntityTypeArgs>

An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver. To get more information about FeaturestoreEntitytype, see:

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class AiFeatureStoreEntityTypeFeature : KotlinCustomResource

Feature Metadata information that describes an attribute of an entity type. For example, apple is an entity type, and color is a feature that describes apple. To get more information about FeaturestoreEntitytypeFeature, see:

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data class AiFeatureStoreEntityTypeFeatureArgs(val description: Output<String>? = null, val entitytype: Output<String>? = null, val labels: Output<Map<String, String>>? = null, val name: Output<String>? = null, val valueType: Output<String>? = null) : ConvertibleToJava<AiFeatureStoreEntityTypeFeatureArgs>

Feature Metadata information that describes an attribute of an entity type. For example, apple is an entity type, and color is a feature that describes apple. To get more information about FeaturestoreEntitytypeFeature, see:

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class AiFeatureStoreEntityTypeIamBinding : KotlinCustomResource

For all import syntaxes, the "resource in question" can take any of the following forms:

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data class AiFeatureStoreEntityTypeIamBindingArgs(val condition: Output<AiFeatureStoreEntityTypeIamBindingConditionArgs>? = null, val entitytype: Output<String>? = null, val featurestore: Output<String>? = null, val members: Output<List<String>>? = null, val role: Output<String>? = null) : ConvertibleToJava<AiFeatureStoreEntityTypeIamBindingArgs>

For all import syntaxes, the "resource in question" can take any of the following forms:

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class AiFeatureStoreEntityTypeIamMember : KotlinCustomResource

For all import syntaxes, the "resource in question" can take any of the following forms:

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data class AiFeatureStoreEntityTypeIamMemberArgs(val condition: Output<AiFeatureStoreEntityTypeIamMemberConditionArgs>? = null, val entitytype: Output<String>? = null, val featurestore: Output<String>? = null, val member: Output<String>? = null, val role: Output<String>? = null) : ConvertibleToJava<AiFeatureStoreEntityTypeIamMemberArgs>

For all import syntaxes, the "resource in question" can take any of the following forms:

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class AiFeatureStoreEntityTypeIamPolicy : KotlinCustomResource

For all import syntaxes, the "resource in question" can take any of the following forms:

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data class AiFeatureStoreEntityTypeIamPolicyArgs(val entitytype: Output<String>? = null, val featurestore: Output<String>? = null, val policyData: Output<String>? = null) : ConvertibleToJava<AiFeatureStoreEntityTypeIamPolicyArgs>

For all import syntaxes, the "resource in question" can take any of the following forms:

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class AiFeatureStoreIamBinding : KotlinCustomResource

For all import syntaxes, the "resource in question" can take any of the following forms:

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data class AiFeatureStoreIamBindingArgs(val condition: Output<AiFeatureStoreIamBindingConditionArgs>? = null, val featurestore: Output<String>? = null, val members: Output<List<String>>? = null, val project: Output<String>? = null, val region: Output<String>? = null, val role: Output<String>? = null) : ConvertibleToJava<AiFeatureStoreIamBindingArgs>

For all import syntaxes, the "resource in question" can take any of the following forms:

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class AiFeatureStoreIamMember : KotlinCustomResource

For all import syntaxes, the "resource in question" can take any of the following forms:

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data class AiFeatureStoreIamMemberArgs(val condition: Output<AiFeatureStoreIamMemberConditionArgs>? = null, val featurestore: Output<String>? = null, val member: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null, val role: Output<String>? = null) : ConvertibleToJava<AiFeatureStoreIamMemberArgs>

For all import syntaxes, the "resource in question" can take any of the following forms:

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class AiFeatureStoreIamPolicy : KotlinCustomResource

For all import syntaxes, the "resource in question" can take any of the following forms:

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data class AiFeatureStoreIamPolicyArgs(val featurestore: Output<String>? = null, val policyData: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiFeatureStoreIamPolicyArgs>

For all import syntaxes, the "resource in question" can take any of the following forms:

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object AiFeatureStoreMapper : ResourceMapper<AiFeatureStore>
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class AiIndex : KotlinCustomResource

A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search. To get more information about Index, see:

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data class AiIndexArgs(val description: Output<String>? = null, val displayName: Output<String>? = null, val indexUpdateMethod: Output<String>? = null, val labels: Output<Map<String, String>>? = null, val metadata: Output<AiIndexMetadataArgs>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiIndexArgs>

A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search. To get more information about Index, see:

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class AiIndexEndpoint : KotlinCustomResource

An endpoint indexes are deployed into. An index endpoint can have multiple deployed indexes. To get more information about IndexEndpoint, see:

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data class AiIndexEndpointArgs(val description: Output<String>? = null, val displayName: Output<String>? = null, val labels: Output<Map<String, String>>? = null, val network: Output<String>? = null, val privateServiceConnectConfig: Output<AiIndexEndpointPrivateServiceConnectConfigArgs>? = null, val project: Output<String>? = null, val publicEndpointEnabled: Output<Boolean>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiIndexEndpointArgs>

An endpoint indexes are deployed into. An index endpoint can have multiple deployed indexes. To get more information about IndexEndpoint, see:

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class AiIndexEndpointDeployedIndex : KotlinCustomResource

An endpoint indexes are deployed into. An index endpoint can have multiple deployed indexes. To get more information about IndexEndpointDeployedIndex, see:

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data class AiIndexEndpointDeployedIndexArgs(val automaticResources: Output<AiIndexEndpointDeployedIndexAutomaticResourcesArgs>? = null, val dedicatedResources: Output<AiIndexEndpointDeployedIndexDedicatedResourcesArgs>? = null, val deployedIndexAuthConfig: Output<AiIndexEndpointDeployedIndexDeployedIndexAuthConfigArgs>? = null, val deployedIndexId: Output<String>? = null, val deploymentGroup: Output<String>? = null, val displayName: Output<String>? = null, val enableAccessLogging: Output<Boolean>? = null, val index: Output<String>? = null, val indexEndpoint: Output<String>? = null, val reservedIpRanges: Output<List<String>>? = null) : ConvertibleToJava<AiIndexEndpointDeployedIndexArgs>

An endpoint indexes are deployed into. An index endpoint can have multiple deployed indexes. To get more information about IndexEndpointDeployedIndex, see:

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object AiIndexEndpointMapper : ResourceMapper<AiIndexEndpoint>
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object AiIndexMapper : ResourceMapper<AiIndex>
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class AiMetadataStore : KotlinCustomResource
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data class AiMetadataStoreArgs(val description: Output<String>? = null, val encryptionSpec: Output<AiMetadataStoreEncryptionSpecArgs>? = null, val name: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiMetadataStoreArgs>
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object AiMetadataStoreMapper : ResourceMapper<AiMetadataStore>
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class AiTensorboard : KotlinCustomResource

Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a GCP project. If needed users can also create extra Tensorboards in their projects. To get more information about Tensorboard, see:

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data class AiTensorboardArgs(val description: Output<String>? = null, val displayName: Output<String>? = null, val encryptionSpec: Output<AiTensorboardEncryptionSpecArgs>? = null, val labels: Output<Map<String, String>>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiTensorboardArgs>

Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a GCP project. If needed users can also create extra Tensorboards in their projects. To get more information about Tensorboard, see:

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object AiTensorboardMapper : ResourceMapper<AiTensorboard>
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Functions

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suspend fun aiDataset(name: String, block: suspend AiDatasetResourceBuilder.() -> Unit): AiDataset
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suspend fun aiEndpoint(name: String, block: suspend AiEndpointResourceBuilder.() -> Unit): AiEndpoint
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fun aiIndex(name: String): AiIndex
suspend fun aiIndex(name: String, block: suspend AiIndexResourceBuilder.() -> Unit): AiIndex
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