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@Generated(value="by gapic-generator-java")

Package com.google.cloud.aiplatform.v1beta1

The interfaces provided are listed below, along with usage samples.

See: Description

Package com.google.cloud.aiplatform.v1beta1 Description

The interfaces provided are listed below, along with usage samples.

======================= DatasetServiceClient =======================

Service Description: The service that handles the CRUD of Vertex AI Dataset and its child resources.

Sample for DatasetServiceClient: 


 try (DatasetServiceClient datasetServiceClient = DatasetServiceClient.create()) {
   DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
   Dataset response = datasetServiceClient.getDataset(name);
 }

======================= EndpointServiceClient =======================

Service Description: A service for managing Vertex AI's Endpoints.

Sample for EndpointServiceClient: 


 try (EndpointServiceClient endpointServiceClient = EndpointServiceClient.create()) {
   EndpointName name = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
   Endpoint response = endpointServiceClient.getEndpoint(name);
 }

======================= FeaturestoreOnlineServingServiceClient =======================

Service Description: A service for serving online feature values.

Sample for FeaturestoreOnlineServingServiceClient: 


 try (FeaturestoreOnlineServingServiceClient featurestoreOnlineServingServiceClient =
     FeaturestoreOnlineServingServiceClient.create()) {
   EntityTypeName entityType =
       EntityTypeName.of("[PROJECT]", "[LOCATION]", "[FEATURESTORE]", "[ENTITY_TYPE]");
   ReadFeatureValuesResponse response =
       featurestoreOnlineServingServiceClient.readFeatureValues(entityType);
 }

======================= FeaturestoreServiceClient =======================

Service Description: The service that handles CRUD and List for resources for Featurestore.

Sample for FeaturestoreServiceClient: 


 try (FeaturestoreServiceClient featurestoreServiceClient = FeaturestoreServiceClient.create()) {
   FeaturestoreName name = FeaturestoreName.of("[PROJECT]", "[LOCATION]", "[FEATURESTORE]");
   Featurestore response = featurestoreServiceClient.getFeaturestore(name);
 }

======================= IndexEndpointServiceClient =======================

Service Description: A service for managing Vertex AI's IndexEndpoints.

Sample for IndexEndpointServiceClient: 


 try (IndexEndpointServiceClient indexEndpointServiceClient =
     IndexEndpointServiceClient.create()) {
   IndexEndpointName name = IndexEndpointName.of("[PROJECT]", "[LOCATION]", "[INDEX_ENDPOINT]");
   IndexEndpoint response = indexEndpointServiceClient.getIndexEndpoint(name);
 }

======================= IndexServiceClient =======================

Service Description: A service for creating and managing Vertex AI's Index resources.

Sample for IndexServiceClient: 


 try (IndexServiceClient indexServiceClient = IndexServiceClient.create()) {
   IndexName name = IndexName.of("[PROJECT]", "[LOCATION]", "[INDEX]");
   Index response = indexServiceClient.getIndex(name);
 }

======================= JobServiceClient =======================

Service Description: A service for creating and managing Vertex AI's jobs.

Sample for JobServiceClient: 


 try (JobServiceClient jobServiceClient = JobServiceClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   CustomJob customJob = CustomJob.newBuilder().build();
   CustomJob response = jobServiceClient.createCustomJob(parent, customJob);
 }

======================= MetadataServiceClient =======================

Service Description: Service for reading and writing metadata entries.

Sample for MetadataServiceClient: 


 try (MetadataServiceClient metadataServiceClient = MetadataServiceClient.create()) {
   MetadataStoreName name = MetadataStoreName.of("[PROJECT]", "[LOCATION]", "[METADATA_STORE]");
   MetadataStore response = metadataServiceClient.getMetadataStore(name);
 }

======================= MigrationServiceClient =======================

Service Description: A service that migrates resources from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.

Sample for MigrationServiceClient: 


 try (MigrationServiceClient migrationServiceClient = MigrationServiceClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   for (MigratableResource element :
       migrationServiceClient.searchMigratableResources(parent).iterateAll()) {
     // doThingsWith(element);
   }
 }

======================= ModelServiceClient =======================

Service Description: A service for managing Vertex AI's machine learning Models.

Sample for ModelServiceClient: 


 try (ModelServiceClient modelServiceClient = ModelServiceClient.create()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   Model response = modelServiceClient.getModel(name);
 }

======================= PipelineServiceClient =======================

Service Description: A service for creating and managing Vertex AI's pipelines. This includes both `TrainingPipeline` resources (used for AutoML and custom training) and `PipelineJob` resources (used for Vertex AI Pipelines).

Sample for PipelineServiceClient: 


 try (PipelineServiceClient pipelineServiceClient = PipelineServiceClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().build();
   TrainingPipeline response =
       pipelineServiceClient.createTrainingPipeline(parent, trainingPipeline);
 }

======================= PredictionServiceClient =======================

Service Description: A service for online predictions and explanations.

Sample for PredictionServiceClient: 


 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   EndpointName endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
   List<Value> instances = new ArrayList<>();
   Value parameters = Value.newBuilder().build();
   PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);
 }

======================= SpecialistPoolServiceClient =======================

Service Description: A service for creating and managing Customer SpecialistPools. When customers start Data Labeling jobs, they can reuse/create Specialist Pools to bring their own Specialists to label the data. Customers can add/remove Managers for the Specialist Pool on Cloud console, then Managers will get email notifications to manage Specialists and tasks on CrowdCompute console.

Sample for SpecialistPoolServiceClient: 


 try (SpecialistPoolServiceClient specialistPoolServiceClient =
     SpecialistPoolServiceClient.create()) {
   SpecialistPoolName name =
       SpecialistPoolName.of("[PROJECT]", "[LOCATION]", "[SPECIALIST_POOL]");
   SpecialistPool response = specialistPoolServiceClient.getSpecialistPool(name);
 }

======================= TensorboardServiceClient =======================

Service Description: TensorboardService

Sample for TensorboardServiceClient: 


 try (TensorboardServiceClient tensorboardServiceClient = TensorboardServiceClient.create()) {
   TensorboardName name = TensorboardName.of("[PROJECT]", "[LOCATION]", "[TENSORBOARD]");
   Tensorboard response = tensorboardServiceClient.getTensorboard(name);
 }

======================= VizierServiceClient =======================

Service Description: Vertex AI Vizier API.

Vertex AI Vizier is a service to solve blackbox optimization problems, such as tuning machine learning hyperparameters and searching over deep learning architectures.

Sample for VizierServiceClient: 


 try (VizierServiceClient vizierServiceClient = VizierServiceClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   Study study = Study.newBuilder().build();
   Study response = vizierServiceClient.createStudy(parent, study);
 }
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