Package com.google.cloud.aiplatform.v1beta1

Interface DeployedModelOrBuilder

  • All Superinterfaces:
    com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
    All Known Implementing Classes:
    DeployedModel, DeployedModel.Builder
    public interface DeployedModelOrBuilder
extends com.google.protobuf.MessageOrBuilder

    • Method Detail

      • hasDedicatedResources

        boolean hasDedicatedResources()
         A description of resources that are dedicated to the DeployedModel, and
 that need a higher degree of manual configuration.
        .google.cloud.aiplatform.v1beta1.DedicatedResources dedicated_resources = 7;
        Returns:
        Whether the dedicatedResources field is set.

      • getDedicatedResources

        DedicatedResources getDedicatedResources()
         A description of resources that are dedicated to the DeployedModel, and
 that need a higher degree of manual configuration.
        .google.cloud.aiplatform.v1beta1.DedicatedResources dedicated_resources = 7;
        Returns:
        The dedicatedResources.

      • getDedicatedResourcesOrBuilder

        DedicatedResourcesOrBuilder getDedicatedResourcesOrBuilder()
         A description of resources that are dedicated to the DeployedModel, and
 that need a higher degree of manual configuration.
        .google.cloud.aiplatform.v1beta1.DedicatedResources dedicated_resources = 7;

      • hasAutomaticResources

        boolean hasAutomaticResources()
         A description of resources that to large degree are decided by Vertex
 AI, and require only a modest additional configuration.
        .google.cloud.aiplatform.v1beta1.AutomaticResources automatic_resources = 8;
        Returns:
        Whether the automaticResources field is set.

      • getAutomaticResources

        AutomaticResources getAutomaticResources()
         A description of resources that to large degree are decided by Vertex
 AI, and require only a modest additional configuration.
        .google.cloud.aiplatform.v1beta1.AutomaticResources automatic_resources = 8;
        Returns:
        The automaticResources.

      • getAutomaticResourcesOrBuilder

        AutomaticResourcesOrBuilder getAutomaticResourcesOrBuilder()
         A description of resources that to large degree are decided by Vertex
 AI, and require only a modest additional configuration.
        .google.cloud.aiplatform.v1beta1.AutomaticResources automatic_resources = 8;

      • hasSharedResources

        boolean hasSharedResources()
         The resource name of the shared DeploymentResourcePool to deploy on.
 Format:
 `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
        string shared_resources = 17 [(.google.api.resource_reference) = { ... }
        Returns:
        Whether the sharedResources field is set.

      • getSharedResources

        String getSharedResources()
         The resource name of the shared DeploymentResourcePool to deploy on.
 Format:
 `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
        string shared_resources = 17 [(.google.api.resource_reference) = { ... }
        Returns:
        The sharedResources.

      • getSharedResourcesBytes

        com.google.protobuf.ByteString getSharedResourcesBytes()
         The resource name of the shared DeploymentResourcePool to deploy on.
 Format:
 `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
        string shared_resources = 17 [(.google.api.resource_reference) = { ... }
        Returns:
        The bytes for sharedResources.

      • getId

        String getId()
         Immutable. The ID of the DeployedModel. If not provided upon deployment,
 Vertex AI will generate a value for this ID.

 This value should be 1-10 characters, and valid characters are /[0-9]/.
        string id = 1 [(.google.api.field_behavior) = IMMUTABLE];
        Returns:
        The id.

      • getIdBytes

        com.google.protobuf.ByteString getIdBytes()
         Immutable. The ID of the DeployedModel. If not provided upon deployment,
 Vertex AI will generate a value for this ID.

 This value should be 1-10 characters, and valid characters are /[0-9]/.
        string id = 1 [(.google.api.field_behavior) = IMMUTABLE];
        Returns:
        The bytes for id.

      • getModel

        String getModel()
         Required. The resource name of the Model that this is the deployment of.
 Note that the Model may be in a different location than the DeployedModel's
 Endpoint.

 The resource name may contain version id or version alias to specify the
 version.
  Example: `projects/{project}/locations/{location}/models/{model}@2`
              or
            `projects/{project}/locations/{location}/models/{model}@golden`
 if no version is specified, the default version will be deployed.
        string model = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
        Returns:
        The model.

      • getModelBytes

        com.google.protobuf.ByteString getModelBytes()
         Required. The resource name of the Model that this is the deployment of.
 Note that the Model may be in a different location than the DeployedModel's
 Endpoint.

 The resource name may contain version id or version alias to specify the
 version.
  Example: `projects/{project}/locations/{location}/models/{model}@2`
              or
            `projects/{project}/locations/{location}/models/{model}@golden`
 if no version is specified, the default version will be deployed.
        string model = 2 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }
        Returns:
        The bytes for model.

      • getModelVersionId

        String getModelVersionId()
         Output only. The version ID of the model that is deployed.
        string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The modelVersionId.

      • getModelVersionIdBytes

        com.google.protobuf.ByteString getModelVersionIdBytes()
         Output only. The version ID of the model that is deployed.
        string model_version_id = 18 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The bytes for modelVersionId.

      • getDisplayName

        String getDisplayName()
         The display name of the DeployedModel. If not provided upon creation,
 the Model's display_name is used.
        string display_name = 3;
        Returns:
        The displayName.

      • getDisplayNameBytes

        com.google.protobuf.ByteString getDisplayNameBytes()
         The display name of the DeployedModel. If not provided upon creation,
 the Model's display_name is used.
        string display_name = 3;
        Returns:
        The bytes for displayName.

      • hasCreateTime

        boolean hasCreateTime()
         Output only. Timestamp when the DeployedModel was created.
        .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        Whether the createTime field is set.

      • getCreateTime

        com.google.protobuf.Timestamp getCreateTime()
         Output only. Timestamp when the DeployedModel was created.
        .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The createTime.

      • getCreateTimeOrBuilder

        com.google.protobuf.TimestampOrBuilder getCreateTimeOrBuilder()
         Output only. Timestamp when the DeployedModel was created.
        .google.protobuf.Timestamp create_time = 6 [(.google.api.field_behavior) = OUTPUT_ONLY];

      • hasExplanationSpec

        boolean hasExplanationSpec()
         Explanation configuration for this DeployedModel.

 When deploying a Model using
 [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel],
 this value overrides the value of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec].
 All fields of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]
 is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]
 is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 will be used for the explanation configuration.
        .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 9;
        Returns:
        Whether the explanationSpec field is set.

      • getExplanationSpec

        ExplanationSpec getExplanationSpec()
         Explanation configuration for this DeployedModel.

 When deploying a Model using
 [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel],
 this value overrides the value of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec].
 All fields of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]
 is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]
 is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 will be used for the explanation configuration.
        .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 9;
        Returns:
        The explanationSpec.

      • getExplanationSpecOrBuilder

        ExplanationSpecOrBuilder getExplanationSpecOrBuilder()
         Explanation configuration for this DeployedModel.

 When deploying a Model using
 [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel],
 this value overrides the value of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec].
 All fields of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]
 is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]
 is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec]
 will be used for the explanation configuration.
        .google.cloud.aiplatform.v1beta1.ExplanationSpec explanation_spec = 9;

      • getDisableExplanations

        boolean getDisableExplanations()
         If true, deploy the model without explainable feature, regardless the
 existence of
 [Model.explanation_spec][google.cloud.aiplatform.v1beta1.Model.explanation_spec]
 or
 [explanation_spec][google.cloud.aiplatform.v1beta1.DeployedModel.explanation_spec].
        bool disable_explanations = 19;
        Returns:
        The disableExplanations.

      • getServiceAccount

        String getServiceAccount()
         The service account that the DeployedModel's container runs as. Specify the
 email address of the service account. If this service account is not
 specified, the container runs as a service account that doesn't have access
 to the resource project.

 Users deploying the Model must have the `iam.serviceAccounts.actAs`
 permission on this service account.
        string service_account = 11;
        Returns:
        The serviceAccount.

      • getServiceAccountBytes

        com.google.protobuf.ByteString getServiceAccountBytes()
         The service account that the DeployedModel's container runs as. Specify the
 email address of the service account. If this service account is not
 specified, the container runs as a service account that doesn't have access
 to the resource project.

 Users deploying the Model must have the `iam.serviceAccounts.actAs`
 permission on this service account.
        string service_account = 11;
        Returns:
        The bytes for serviceAccount.

      • getEnableContainerLogging

        boolean getEnableContainerLogging()
         If true, the container of the DeployedModel instances will send `stderr`
 and `stdout` streams to Cloud Logging.

 Only supported for custom-trained Models and AutoML Tabular Models.
        bool enable_container_logging = 12;
        Returns:
        The enableContainerLogging.

      • getEnableAccessLogging

        boolean getEnableAccessLogging()
         If true, online prediction access logs are sent to Cloud
 Logging.
 These logs are like standard server access logs, containing
 information like timestamp and latency for each prediction request.

 Note that logs may incur a cost, especially if your project
 receives prediction requests at a high queries per second rate (QPS).
 Estimate your costs before enabling this option.
        bool enable_access_logging = 13;
        Returns:
        The enableAccessLogging.

      • hasPrivateEndpoints

        boolean hasPrivateEndpoints()
         Output only. Provide paths for users to send predict/explain/health
 requests directly to the deployed model services running on Cloud via
 private services access. This field is populated if
 [network][google.cloud.aiplatform.v1beta1.Endpoint.network] is configured.
        .google.cloud.aiplatform.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        Whether the privateEndpoints field is set.

      • getPrivateEndpoints

        PrivateEndpoints getPrivateEndpoints()
         Output only. Provide paths for users to send predict/explain/health
 requests directly to the deployed model services running on Cloud via
 private services access. This field is populated if
 [network][google.cloud.aiplatform.v1beta1.Endpoint.network] is configured.
        .google.cloud.aiplatform.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];
        Returns:
        The privateEndpoints.

      • getPrivateEndpointsOrBuilder

        PrivateEndpointsOrBuilder getPrivateEndpointsOrBuilder()
         Output only. Provide paths for users to send predict/explain/health
 requests directly to the deployed model services running on Cloud via
 private services access. This field is populated if
 [network][google.cloud.aiplatform.v1beta1.Endpoint.network] is configured.
        .google.cloud.aiplatform.v1beta1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];