google-cloud-aiplatform overview (3.25.0)

com.google.cloud.aiplatform.util

com.google.cloud.aiplatform.v1

A client to Vertex AI API

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

DatasetServiceClient

Service Description: The service that manages Vertex AI Dataset and its child resources.

Sample for DatasetServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (EndpointServiceClient endpointServiceClient = EndpointServiceClient.create()) {  EndpointName name =  EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");  Endpoint response = endpointServiceClient.getEndpoint(name);  }

FeaturestoreOnlineServingServiceClient

Service Description: A service for serving online feature values.

Sample for FeaturestoreOnlineServingServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (JobServiceClient jobServiceClient = JobServiceClient.create()) {  LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");  CustomJob customJob = CustomJob.newBuilder().build();  CustomJob response = jobServiceClient.createCustomJob(parent, customJob);  }

MatchServiceClient

Service Description: MatchService is a Google managed service for efficient vector similarity search at scale.

Sample for MatchServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (MatchServiceClient matchServiceClient = MatchServiceClient.create()) {  FindNeighborsRequest request =  FindNeighborsRequest.newBuilder()  .setIndexEndpoint(  IndexEndpointName.of("[PROJECT]", "[LOCATION]", "[INDEX_ENDPOINT]").toString())  .setDeployedIndexId("deployedIndexId-1101212953")  .addAllQueries(new ArrayList<FindNeighborsRequest.Query>())  .setReturnFullDatapoint(true)  .build();  FindNeighborsResponse response = matchServiceClient.findNeighbors(request);  }

MetadataServiceClient

Service Description: Service for reading and writing metadata entries.

Sample for MetadataServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (MigrationServiceClient migrationServiceClient = MigrationServiceClient.create()) {  GetLocationRequest request = GetLocationRequest.newBuilder().setName("name3373707").build();  Location response = migrationServiceClient.getLocation(request);  }

ModelServiceClient

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

Sample for ModelServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (ModelServiceClient modelServiceClient = ModelServiceClient.create()) {  ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");  Model response = modelServiceClient.getModel(name);  }

ModelGardenServiceClient

Service Description: The interface of Model Garden Service.

Sample for ModelGardenServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (ModelGardenServiceClient modelGardenServiceClient = ModelGardenServiceClient.create()) {  PublisherModelName name = PublisherModelName.of("[PUBLISHER]", "[MODEL]");  PublisherModel response = modelGardenServiceClient.getPublisherModel(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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {  EndpointName endpoint =  EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");  List<Value> instances = new ArrayList<>();  Value parameters = Value.newBuilder().setBoolValue(true).build();  PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);  }

ScheduleServiceClient

Service Description: A service for creating and managing Vertex AI's Schedule resources to periodically launch shceudled runs to make API calls.

Sample for ScheduleServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (ScheduleServiceClient scheduleServiceClient = ScheduleServiceClient.create()) {  LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");  Schedule schedule = Schedule.newBuilder().build();  Schedule response = scheduleServiceClient.createSchedule(parent, schedule);  }

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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (VizierServiceClient vizierServiceClient = VizierServiceClient.create()) {  LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");  Study study = Study.newBuilder().build();  Study response = vizierServiceClient.createStudy(parent, study);  }

com.google.cloud.aiplatform.v1.schema.predict.instance

com.google.cloud.aiplatform.v1.schema.predict.params

com.google.cloud.aiplatform.v1.schema.predict.prediction

com.google.cloud.aiplatform.v1.schema.trainingjob.definition

com.google.cloud.aiplatform.v1.stub

com.google.cloud.aiplatform.v1beta1

A client to Vertex AI API

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

DatasetServiceClient

Service Description: The service that manages Vertex AI Dataset and its child resources.

Sample for DatasetServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (DatasetServiceClient datasetServiceClient = DatasetServiceClient.create()) {  DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");  Dataset response = datasetServiceClient.getDataset(name);  }

DeploymentResourcePoolServiceClient

Service Description: A service that manages the DeploymentResourcePool resource.

Sample for DeploymentResourcePoolServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (DeploymentResourcePoolServiceClient deploymentResourcePoolServiceClient =  DeploymentResourcePoolServiceClient.create()) {  DeploymentResourcePoolName name =  DeploymentResourcePoolName.of("[PROJECT]", "[LOCATION]", "[DEPLOYMENT_RESOURCE_POOL]");  DeploymentResourcePool response =  deploymentResourcePoolServiceClient.getDeploymentResourcePool(name);  }

EndpointServiceClient

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

Sample for EndpointServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (EndpointServiceClient endpointServiceClient = EndpointServiceClient.create()) {  EndpointName name =  EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");  Endpoint response = endpointServiceClient.getEndpoint(name);  }

FeaturestoreOnlineServingServiceClient

Service Description: A service for serving online feature values.

Sample for FeaturestoreOnlineServingServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (JobServiceClient jobServiceClient = JobServiceClient.create()) {  LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");  CustomJob customJob = CustomJob.newBuilder().build();  CustomJob response = jobServiceClient.createCustomJob(parent, customJob);  }

MatchServiceClient

Service Description: MatchService is a Google managed service for efficient vector similarity search at scale.

Sample for MatchServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (MatchServiceClient matchServiceClient = MatchServiceClient.create()) {  FindNeighborsRequest request =  FindNeighborsRequest.newBuilder()  .setIndexEndpoint(  IndexEndpointName.of("[PROJECT]", "[LOCATION]", "[INDEX_ENDPOINT]").toString())  .setDeployedIndexId("deployedIndexId-1101212953")  .addAllQueries(new ArrayList<FindNeighborsRequest.Query>())  .setReturnFullDatapoint(true)  .build();  FindNeighborsResponse response = matchServiceClient.findNeighbors(request);  }

MetadataServiceClient

Service Description: Service for reading and writing metadata entries.

Sample for MetadataServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (MigrationServiceClient migrationServiceClient = MigrationServiceClient.create()) {  GetLocationRequest request = GetLocationRequest.newBuilder().setName("name3373707").build();  Location response = migrationServiceClient.getLocation(request);  }

ModelGardenServiceClient

Service Description: The interface of Model Garden Service.

Sample for ModelGardenServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (ModelGardenServiceClient modelGardenServiceClient = ModelGardenServiceClient.create()) {  PublisherModelName name = PublisherModelName.of("[PUBLISHER]", "[MODEL]");  PublisherModel response = modelGardenServiceClient.getPublisherModel(name);  }

ModelServiceClient

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

Sample for ModelServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (ModelServiceClient modelServiceClient = ModelServiceClient.create()) {  ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");  Model response = modelServiceClient.getModel(name);  }

PersistentResourceServiceClient

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

Sample for PersistentResourceServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (PersistentResourceServiceClient persistentResourceServiceClient =  PersistentResourceServiceClient.create()) {  PersistentResourceName name =  PersistentResourceName.of("[PROJECT]", "[LOCATION]", "[PERSISTENT_RESOURCE]");  PersistentResource response = persistentResourceServiceClient.getPersistentResource(name);  }

PipelineServiceClient

Sample for PipelineServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {  EndpointName endpoint =  EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");  List<Value> instances = new ArrayList<>();  Value parameters = Value.newBuilder().setBoolValue(true).build();  PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);  }

ScheduleServiceClient

Service Description: A service for creating and managing Vertex AI's Schedule resources to periodically launch shceudled runs to make API calls.

Sample for ScheduleServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (ScheduleServiceClient scheduleServiceClient = ScheduleServiceClient.create()) {  LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");  Schedule schedule = Schedule.newBuilder().build();  Schedule response = scheduleServiceClient.createSchedule(parent, schedule);  }

SpecialistPoolServiceClient

Sample for SpecialistPoolServiceClient:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  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:

  // This snippet has been automatically generated and should be regarded as a code template only.  // It will require modifications to work:  // - It may require correct/in-range values for request initialization.  // - It may require specifying regional endpoints when creating the service client as shown in  // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library  try (VizierServiceClient vizierServiceClient = VizierServiceClient.create()) {  LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");  Study study = Study.newBuilder().build();  Study response = vizierServiceClient.createStudy(parent, study);  }

google-cloud-aiplatform overview (3.25.0) Stay organized with collections Save and categorize content based on your preferences.

DatasetServiceClient

EndpointServiceClient

FeaturestoreOnlineServingServiceClient

FeaturestoreServiceClient

IndexEndpointServiceClient

IndexServiceClient

JobServiceClient

MatchServiceClient

MetadataServiceClient

MigrationServiceClient

ModelServiceClient

ModelGardenServiceClient

PipelineServiceClient

PredictionServiceClient

ScheduleServiceClient

SpecialistPoolServiceClient

TensorboardServiceClient

VizierServiceClient

DatasetServiceClient

DeploymentResourcePoolServiceClient

EndpointServiceClient

FeaturestoreOnlineServingServiceClient

FeaturestoreServiceClient

IndexEndpointServiceClient

IndexServiceClient

JobServiceClient

MatchServiceClient

MetadataServiceClient

MigrationServiceClient

ModelGardenServiceClient

ModelServiceClient

PersistentResourceServiceClient

PipelineServiceClient

PredictionServiceClient

ScheduleServiceClient

SpecialistPoolServiceClient

TensorboardServiceClient

VizierServiceClient

google-cloud-aiplatform overview (3.25.0)