Package com.google.cloud.aiplatform.v1

Interface DeployedModelOrBuilder

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

  • Method Details

    • 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.v1.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.v1.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.v1.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.v1.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.v1.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.v1.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()
       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.resource_reference) = { ... }
      Returns:
      The model.

    • getModelBytes

      com.google.protobuf.ByteString getModelBytes()
       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.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.v1.EndpointService.DeployModel],
 this value overrides the value of
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec].
 All fields of
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]
 is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]
 is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 will be used for the explanation configuration.
      .google.cloud.aiplatform.v1.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.v1.EndpointService.DeployModel],
 this value overrides the value of
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec].
 All fields of
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]
 is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]
 is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 will be used for the explanation configuration.
      .google.cloud.aiplatform.v1.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.v1.EndpointService.DeployModel],
 this value overrides the value of
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec].
 All fields of
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 are optional in the request. If a field of
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 is not populated, the value of the same field of
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]
 is inherited. If the corresponding
 [Model.explanation_spec][google.cloud.aiplatform.v1.Model.explanation_spec]
 is not populated, all fields of the
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec]
 will be used for the explanation configuration.
      .google.cloud.aiplatform.v1.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.v1.Model.explanation_spec]
 or
 [explanation_spec][google.cloud.aiplatform.v1.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.

    • getDisableContainerLogging

      boolean getDisableContainerLogging()
       For custom-trained Models and AutoML Tabular Models, the container of the
 DeployedModel instances will send `stderr` and `stdout` streams to
 Cloud Logging by default. Please note that the logs incur cost,
 which are subject to [Cloud Logging
 pricing](https://cloud.google.com/logging/pricing).

 User can disable container logging by setting this flag to true.
      bool disable_container_logging = 15;
      Returns:
      The disableContainerLogging.

    • 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.v1.Endpoint.network] is configured.
      .google.cloud.aiplatform.v1.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.v1.Endpoint.network] is configured.
      .google.cloud.aiplatform.v1.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.v1.Endpoint.network] is configured.
      .google.cloud.aiplatform.v1.PrivateEndpoints private_endpoints = 14 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • hasFasterDeploymentConfig

      boolean hasFasterDeploymentConfig()
       Configuration for faster model deployment.
      .google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23;
      Returns:
      Whether the fasterDeploymentConfig field is set.

    • getFasterDeploymentConfig

      FasterDeploymentConfig getFasterDeploymentConfig()
       Configuration for faster model deployment.
      .google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23;
      Returns:
      The fasterDeploymentConfig.

    • getFasterDeploymentConfigOrBuilder

      FasterDeploymentConfigOrBuilder getFasterDeploymentConfigOrBuilder()
       Configuration for faster model deployment.
      .google.cloud.aiplatform.v1.FasterDeploymentConfig faster_deployment_config = 23;

    • hasStatus

      boolean hasStatus()
       Output only. Runtime status of the deployed model.
      .google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      Whether the status field is set.

    • getStatus

      DeployedModel.Status getStatus()
       Output only. Runtime status of the deployed model.
      .google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];
      Returns:
      The status.

    • getStatusOrBuilder

      DeployedModel.StatusOrBuilder getStatusOrBuilder()
       Output only. Runtime status of the deployed model.
      .google.cloud.aiplatform.v1.DeployedModel.Status status = 26 [(.google.api.field_behavior) = OUTPUT_ONLY];

    • getSystemLabelsCount

      int getSystemLabelsCount()
       System labels to apply to Model Garden deployments.
 System labels are managed by Google for internal use only.
      map<string, string> system_labels = 28;

    • containsSystemLabels

      boolean containsSystemLabels(String key)
       System labels to apply to Model Garden deployments.
 System labels are managed by Google for internal use only.
      map<string, string> system_labels = 28;

    • getSystemLabels

      @Deprecated Map<String,String> getSystemLabels()
      Deprecated.
      Use getSystemLabelsMap() instead.

    • getSystemLabelsMap

      Map<String,String> getSystemLabelsMap()
       System labels to apply to Model Garden deployments.
 System labels are managed by Google for internal use only.
      map<string, string> system_labels = 28;

    • getSystemLabelsOrDefault

      String getSystemLabelsOrDefault(String key, String defaultValue)
       System labels to apply to Model Garden deployments.
 System labels are managed by Google for internal use only.
      map<string, string> system_labels = 28;

    • getSystemLabelsOrThrow

      String getSystemLabelsOrThrow(String key)
       System labels to apply to Model Garden deployments.
 System labels are managed by Google for internal use only.
      map<string, string> system_labels = 28;

    • getCheckpointId

      String getCheckpointId()
       The checkpoint id of the model.
      string checkpoint_id = 29;
      Returns:
      The checkpointId.

    • getCheckpointIdBytes

      com.google.protobuf.ByteString getCheckpointIdBytes()
       The checkpoint id of the model.
      string checkpoint_id = 29;
      Returns:
      The bytes for checkpointId.

    • hasSpeculativeDecodingSpec

      boolean hasSpeculativeDecodingSpec()
       Optional. Spec for configuring speculative decoding.
      .google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      Whether the speculativeDecodingSpec field is set.

    • getSpeculativeDecodingSpec

      SpeculativeDecodingSpec getSpeculativeDecodingSpec()
       Optional. Spec for configuring speculative decoding.
      .google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL];
      Returns:
      The speculativeDecodingSpec.

    • getSpeculativeDecodingSpecOrBuilder

      SpeculativeDecodingSpecOrBuilder getSpeculativeDecodingSpecOrBuilder()
       Optional. Spec for configuring speculative decoding.
      .google.cloud.aiplatform.v1.SpeculativeDecodingSpec speculative_decoding_spec = 30 [(.google.api.field_behavior) = OPTIONAL];

    • getPredictionResourcesCase

      DeployedModel.PredictionResourcesCase getPredictionResourcesCase()