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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);
}
Classes
AcceleratorTypeProto
ActiveLearningConfig
Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
Protobuf type google.cloud.aiplatform.v1.ActiveLearningConfig
ActiveLearningConfig.Builder
Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.
Protobuf type google.cloud.aiplatform.v1.ActiveLearningConfig
AddContextArtifactsAndExecutionsRequest
Request message for MetadataService.AddContextArtifactsAndExecutions.
Protobuf type google.cloud.aiplatform.v1.AddContextArtifactsAndExecutionsRequest
AddContextArtifactsAndExecutionsRequest.Builder
Request message for MetadataService.AddContextArtifactsAndExecutions.
Protobuf type google.cloud.aiplatform.v1.AddContextArtifactsAndExecutionsRequest
AddContextArtifactsAndExecutionsResponse
Response message for MetadataService.AddContextArtifactsAndExecutions.
Protobuf type google.cloud.aiplatform.v1.AddContextArtifactsAndExecutionsResponse
AddContextArtifactsAndExecutionsResponse.Builder
Response message for MetadataService.AddContextArtifactsAndExecutions.
Protobuf type google.cloud.aiplatform.v1.AddContextArtifactsAndExecutionsResponse
AddContextChildrenRequest
Request message for MetadataService.AddContextChildren.
Protobuf type google.cloud.aiplatform.v1.AddContextChildrenRequest
AddContextChildrenRequest.Builder
Request message for MetadataService.AddContextChildren.
Protobuf type google.cloud.aiplatform.v1.AddContextChildrenRequest
AddContextChildrenResponse
Response message for MetadataService.AddContextChildren.
Protobuf type google.cloud.aiplatform.v1.AddContextChildrenResponse
AddContextChildrenResponse.Builder
Response message for MetadataService.AddContextChildren.
Protobuf type google.cloud.aiplatform.v1.AddContextChildrenResponse
AddExecutionEventsRequest
Request message for MetadataService.AddExecutionEvents.
Protobuf type google.cloud.aiplatform.v1.AddExecutionEventsRequest
AddExecutionEventsRequest.Builder
Request message for MetadataService.AddExecutionEvents.
Protobuf type google.cloud.aiplatform.v1.AddExecutionEventsRequest
AddExecutionEventsResponse
Response message for MetadataService.AddExecutionEvents.
Protobuf type google.cloud.aiplatform.v1.AddExecutionEventsResponse
AddExecutionEventsResponse.Builder
Response message for MetadataService.AddExecutionEvents.
Protobuf type google.cloud.aiplatform.v1.AddExecutionEventsResponse
AddTrialMeasurementRequest
Request message for VizierService.AddTrialMeasurement.
Protobuf type google.cloud.aiplatform.v1.AddTrialMeasurementRequest
AddTrialMeasurementRequest.Builder
Request message for VizierService.AddTrialMeasurement.
Protobuf type google.cloud.aiplatform.v1.AddTrialMeasurementRequest
Annotation
Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.
Protobuf type google.cloud.aiplatform.v1.Annotation
Annotation.Builder
Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.
Protobuf type google.cloud.aiplatform.v1.Annotation
AnnotationProto
AnnotationSpec
Identifies a concept with which DataItems may be annotated with.
Protobuf type google.cloud.aiplatform.v1.AnnotationSpec
AnnotationSpec.Builder
Identifies a concept with which DataItems may be annotated with.
Protobuf type google.cloud.aiplatform.v1.AnnotationSpec
AnnotationSpecName
AnnotationSpecName.Builder
Builder for projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}.
AnnotationSpecProto
Artifact
Instance of a general artifact.
Protobuf type google.cloud.aiplatform.v1.Artifact
Artifact.Builder
Instance of a general artifact.
Protobuf type google.cloud.aiplatform.v1.Artifact
ArtifactName
ArtifactName.Builder
Builder for projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}.
ArtifactProto
Attribution
Attribution that explains a particular prediction output.
Protobuf type google.cloud.aiplatform.v1.Attribution
Attribution.Builder
Attribution that explains a particular prediction output.
Protobuf type google.cloud.aiplatform.v1.Attribution
AutomaticResources
A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.
Protobuf type google.cloud.aiplatform.v1.AutomaticResources
AutomaticResources.Builder
A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.
Protobuf type google.cloud.aiplatform.v1.AutomaticResources
AutoscalingMetricSpec
The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.
Protobuf type google.cloud.aiplatform.v1.AutoscalingMetricSpec
AutoscalingMetricSpec.Builder
The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.
Protobuf type google.cloud.aiplatform.v1.AutoscalingMetricSpec
AvroSource
The storage details for Avro input content.
Protobuf type google.cloud.aiplatform.v1.AvroSource
AvroSource.Builder
The storage details for Avro input content.
Protobuf type google.cloud.aiplatform.v1.AvroSource
BatchCreateFeaturesOperationMetadata
Details of operations that perform batch create Features.
Protobuf type google.cloud.aiplatform.v1.BatchCreateFeaturesOperationMetadata
BatchCreateFeaturesOperationMetadata.Builder
Details of operations that perform batch create Features.
Protobuf type google.cloud.aiplatform.v1.BatchCreateFeaturesOperationMetadata
BatchCreateFeaturesRequest
Request message for FeaturestoreService.BatchCreateFeatures.
Protobuf type google.cloud.aiplatform.v1.BatchCreateFeaturesRequest
BatchCreateFeaturesRequest.Builder
Request message for FeaturestoreService.BatchCreateFeatures.
Protobuf type google.cloud.aiplatform.v1.BatchCreateFeaturesRequest
BatchCreateFeaturesResponse
Response message for FeaturestoreService.BatchCreateFeatures.
Protobuf type google.cloud.aiplatform.v1.BatchCreateFeaturesResponse
BatchCreateFeaturesResponse.Builder
Response message for FeaturestoreService.BatchCreateFeatures.
Protobuf type google.cloud.aiplatform.v1.BatchCreateFeaturesResponse
BatchCreateTensorboardRunsRequest
Request message for TensorboardService.BatchCreateTensorboardRuns.
Protobuf type google.cloud.aiplatform.v1.BatchCreateTensorboardRunsRequest
BatchCreateTensorboardRunsRequest.Builder
Request message for TensorboardService.BatchCreateTensorboardRuns.
Protobuf type google.cloud.aiplatform.v1.BatchCreateTensorboardRunsRequest
BatchCreateTensorboardRunsResponse
Response message for TensorboardService.BatchCreateTensorboardRuns.
Protobuf type google.cloud.aiplatform.v1.BatchCreateTensorboardRunsResponse
BatchCreateTensorboardRunsResponse.Builder
Response message for TensorboardService.BatchCreateTensorboardRuns.
Protobuf type google.cloud.aiplatform.v1.BatchCreateTensorboardRunsResponse
BatchCreateTensorboardTimeSeriesRequest
Request message for TensorboardService.BatchCreateTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.BatchCreateTensorboardTimeSeriesRequest
BatchCreateTensorboardTimeSeriesRequest.Builder
Request message for TensorboardService.BatchCreateTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.BatchCreateTensorboardTimeSeriesRequest
BatchCreateTensorboardTimeSeriesResponse
Response message for TensorboardService.BatchCreateTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.BatchCreateTensorboardTimeSeriesResponse
BatchCreateTensorboardTimeSeriesResponse.Builder
Response message for TensorboardService.BatchCreateTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.BatchCreateTensorboardTimeSeriesResponse
BatchDedicatedResources
A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.
Protobuf type google.cloud.aiplatform.v1.BatchDedicatedResources
BatchDedicatedResources.Builder
A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.
Protobuf type google.cloud.aiplatform.v1.BatchDedicatedResources
BatchImportEvaluatedAnnotationsRequest
Request message for ModelService.BatchImportEvaluatedAnnotations
Protobuf type google.cloud.aiplatform.v1.BatchImportEvaluatedAnnotationsRequest
BatchImportEvaluatedAnnotationsRequest.Builder
Request message for ModelService.BatchImportEvaluatedAnnotations
Protobuf type google.cloud.aiplatform.v1.BatchImportEvaluatedAnnotationsRequest
BatchImportEvaluatedAnnotationsResponse
Response message for ModelService.BatchImportEvaluatedAnnotations
Protobuf type google.cloud.aiplatform.v1.BatchImportEvaluatedAnnotationsResponse
BatchImportEvaluatedAnnotationsResponse.Builder
Response message for ModelService.BatchImportEvaluatedAnnotations
Protobuf type google.cloud.aiplatform.v1.BatchImportEvaluatedAnnotationsResponse
BatchImportModelEvaluationSlicesRequest
Request message for ModelService.BatchImportModelEvaluationSlices
Protobuf type google.cloud.aiplatform.v1.BatchImportModelEvaluationSlicesRequest
BatchImportModelEvaluationSlicesRequest.Builder
Request message for ModelService.BatchImportModelEvaluationSlices
Protobuf type google.cloud.aiplatform.v1.BatchImportModelEvaluationSlicesRequest
BatchImportModelEvaluationSlicesResponse
Response message for ModelService.BatchImportModelEvaluationSlices
Protobuf type google.cloud.aiplatform.v1.BatchImportModelEvaluationSlicesResponse
BatchImportModelEvaluationSlicesResponse.Builder
Response message for ModelService.BatchImportModelEvaluationSlices
Protobuf type google.cloud.aiplatform.v1.BatchImportModelEvaluationSlicesResponse
BatchMigrateResourcesOperationMetadata
Runtime operation information for MigrationService.BatchMigrateResources.
Protobuf type google.cloud.aiplatform.v1.BatchMigrateResourcesOperationMetadata
BatchMigrateResourcesOperationMetadata.Builder
Runtime operation information for MigrationService.BatchMigrateResources.
Protobuf type google.cloud.aiplatform.v1.BatchMigrateResourcesOperationMetadata
BatchMigrateResourcesOperationMetadata.PartialResult
Represents a partial result in batch migration operation for one MigrateResourceRequest.
Protobuf type
google.cloud.aiplatform.v1.BatchMigrateResourcesOperationMetadata.PartialResult
BatchMigrateResourcesOperationMetadata.PartialResult.Builder
Represents a partial result in batch migration operation for one MigrateResourceRequest.
Protobuf type
google.cloud.aiplatform.v1.BatchMigrateResourcesOperationMetadata.PartialResult
BatchMigrateResourcesRequest
Request message for MigrationService.BatchMigrateResources.
Protobuf type google.cloud.aiplatform.v1.BatchMigrateResourcesRequest
BatchMigrateResourcesRequest.Builder
Request message for MigrationService.BatchMigrateResources.
Protobuf type google.cloud.aiplatform.v1.BatchMigrateResourcesRequest
BatchMigrateResourcesResponse
Response message for MigrationService.BatchMigrateResources.
Protobuf type google.cloud.aiplatform.v1.BatchMigrateResourcesResponse
BatchMigrateResourcesResponse.Builder
Response message for MigrationService.BatchMigrateResources.
Protobuf type google.cloud.aiplatform.v1.BatchMigrateResourcesResponse
BatchPredictionJob
A job that uses a Model to produce predictions on multiple input instances. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob
BatchPredictionJob.Builder
A job that uses a Model to produce predictions on multiple input instances. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob
BatchPredictionJob.InputConfig
Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig
BatchPredictionJob.InputConfig.Builder
Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.InputConfig
BatchPredictionJob.InstanceConfig
Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.InstanceConfig
BatchPredictionJob.InstanceConfig.Builder
Configuration defining how to transform batch prediction input instances to the instances that the Model accepts.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.InstanceConfig
BatchPredictionJob.OutputConfig
Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig
BatchPredictionJob.OutputConfig.Builder
Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.OutputConfig
BatchPredictionJob.OutputInfo
Further describes this job's output. Supplements output_config.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.OutputInfo
BatchPredictionJob.OutputInfo.Builder
Further describes this job's output. Supplements output_config.
Protobuf type google.cloud.aiplatform.v1.BatchPredictionJob.OutputInfo
BatchPredictionJobName
BatchPredictionJobName.Builder
Builder for projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}.
BatchPredictionJobProto
BatchReadFeatureValuesOperationMetadata
Details of operations that batch reads Feature values.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesOperationMetadata
BatchReadFeatureValuesOperationMetadata.Builder
Details of operations that batch reads Feature values.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesOperationMetadata
BatchReadFeatureValuesRequest
Request message for FeaturestoreService.BatchReadFeatureValues.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesRequest
BatchReadFeatureValuesRequest.Builder
Request message for FeaturestoreService.BatchReadFeatureValues.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesRequest
BatchReadFeatureValuesRequest.EntityTypeSpec
Selects Features of an EntityType to read values of and specifies read settings.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesRequest.EntityTypeSpec
BatchReadFeatureValuesRequest.EntityTypeSpec.Builder
Selects Features of an EntityType to read values of and specifies read settings.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesRequest.EntityTypeSpec
BatchReadFeatureValuesRequest.PassThroughField
Describe pass-through fields in read_instance source.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesRequest.PassThroughField
BatchReadFeatureValuesRequest.PassThroughField.Builder
Describe pass-through fields in read_instance source.
Protobuf type
google.cloud.aiplatform.v1.BatchReadFeatureValuesRequest.PassThroughField
BatchReadFeatureValuesResponse
Response message for FeaturestoreService.BatchReadFeatureValues.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesResponse
BatchReadFeatureValuesResponse.Builder
Response message for FeaturestoreService.BatchReadFeatureValues.
Protobuf type google.cloud.aiplatform.v1.BatchReadFeatureValuesResponse
BatchReadTensorboardTimeSeriesDataRequest
Request message for TensorboardService.BatchReadTensorboardTimeSeriesData.
Protobuf type google.cloud.aiplatform.v1.BatchReadTensorboardTimeSeriesDataRequest
BatchReadTensorboardTimeSeriesDataRequest.Builder
Request message for TensorboardService.BatchReadTensorboardTimeSeriesData.
Protobuf type google.cloud.aiplatform.v1.BatchReadTensorboardTimeSeriesDataRequest
BatchReadTensorboardTimeSeriesDataResponse
Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.
Protobuf type google.cloud.aiplatform.v1.BatchReadTensorboardTimeSeriesDataResponse
BatchReadTensorboardTimeSeriesDataResponse.Builder
Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.
Protobuf type google.cloud.aiplatform.v1.BatchReadTensorboardTimeSeriesDataResponse
BigQueryDestination
The BigQuery location for the output content.
Protobuf type google.cloud.aiplatform.v1.BigQueryDestination
BigQueryDestination.Builder
The BigQuery location for the output content.
Protobuf type google.cloud.aiplatform.v1.BigQueryDestination
BigQuerySource
The BigQuery location for the input content.
Protobuf type google.cloud.aiplatform.v1.BigQuerySource
BigQuerySource.Builder
The BigQuery location for the input content.
Protobuf type google.cloud.aiplatform.v1.BigQuerySource
BlurBaselineConfig
Config for blur baseline.
When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383
Protobuf type google.cloud.aiplatform.v1.BlurBaselineConfig
BlurBaselineConfig.Builder
Config for blur baseline.
When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383
Protobuf type google.cloud.aiplatform.v1.BlurBaselineConfig
BoolArray
A list of boolean values.
Protobuf type google.cloud.aiplatform.v1.BoolArray
BoolArray.Builder
A list of boolean values.
Protobuf type google.cloud.aiplatform.v1.BoolArray
CancelBatchPredictionJobRequest
Request message for JobService.CancelBatchPredictionJob.
Protobuf type google.cloud.aiplatform.v1.CancelBatchPredictionJobRequest
CancelBatchPredictionJobRequest.Builder
Request message for JobService.CancelBatchPredictionJob.
Protobuf type google.cloud.aiplatform.v1.CancelBatchPredictionJobRequest
CancelCustomJobRequest
Request message for JobService.CancelCustomJob.
Protobuf type google.cloud.aiplatform.v1.CancelCustomJobRequest
CancelCustomJobRequest.Builder
Request message for JobService.CancelCustomJob.
Protobuf type google.cloud.aiplatform.v1.CancelCustomJobRequest
CancelDataLabelingJobRequest
Request message for JobService.CancelDataLabelingJob.
Protobuf type google.cloud.aiplatform.v1.CancelDataLabelingJobRequest
CancelDataLabelingJobRequest.Builder
Request message for JobService.CancelDataLabelingJob.
Protobuf type google.cloud.aiplatform.v1.CancelDataLabelingJobRequest
CancelHyperparameterTuningJobRequest
Request message for JobService.CancelHyperparameterTuningJob.
Protobuf type google.cloud.aiplatform.v1.CancelHyperparameterTuningJobRequest
CancelHyperparameterTuningJobRequest.Builder
Request message for JobService.CancelHyperparameterTuningJob.
Protobuf type google.cloud.aiplatform.v1.CancelHyperparameterTuningJobRequest
CancelNasJobRequest
Request message for JobService.CancelNasJob.
Protobuf type google.cloud.aiplatform.v1.CancelNasJobRequest
CancelNasJobRequest.Builder
Request message for JobService.CancelNasJob.
Protobuf type google.cloud.aiplatform.v1.CancelNasJobRequest
CancelPipelineJobRequest
Request message for PipelineService.CancelPipelineJob.
Protobuf type google.cloud.aiplatform.v1.CancelPipelineJobRequest
CancelPipelineJobRequest.Builder
Request message for PipelineService.CancelPipelineJob.
Protobuf type google.cloud.aiplatform.v1.CancelPipelineJobRequest
CancelTrainingPipelineRequest
Request message for PipelineService.CancelTrainingPipeline.
Protobuf type google.cloud.aiplatform.v1.CancelTrainingPipelineRequest
CancelTrainingPipelineRequest.Builder
Request message for PipelineService.CancelTrainingPipeline.
Protobuf type google.cloud.aiplatform.v1.CancelTrainingPipelineRequest
CheckTrialEarlyStoppingStateMetatdata
This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
Protobuf type google.cloud.aiplatform.v1.CheckTrialEarlyStoppingStateMetatdata
CheckTrialEarlyStoppingStateMetatdata.Builder
This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
Protobuf type google.cloud.aiplatform.v1.CheckTrialEarlyStoppingStateMetatdata
CheckTrialEarlyStoppingStateRequest
Request message for VizierService.CheckTrialEarlyStoppingState.
Protobuf type google.cloud.aiplatform.v1.CheckTrialEarlyStoppingStateRequest
CheckTrialEarlyStoppingStateRequest.Builder
Request message for VizierService.CheckTrialEarlyStoppingState.
Protobuf type google.cloud.aiplatform.v1.CheckTrialEarlyStoppingStateRequest
CheckTrialEarlyStoppingStateResponse
Response message for VizierService.CheckTrialEarlyStoppingState.
Protobuf type google.cloud.aiplatform.v1.CheckTrialEarlyStoppingStateResponse
CheckTrialEarlyStoppingStateResponse.Builder
Response message for VizierService.CheckTrialEarlyStoppingState.
Protobuf type google.cloud.aiplatform.v1.CheckTrialEarlyStoppingStateResponse
CompleteTrialRequest
Request message for VizierService.CompleteTrial.
Protobuf type google.cloud.aiplatform.v1.CompleteTrialRequest
CompleteTrialRequest.Builder
Request message for VizierService.CompleteTrial.
Protobuf type google.cloud.aiplatform.v1.CompleteTrialRequest
CompletionStats
Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
Protobuf type google.cloud.aiplatform.v1.CompletionStats
CompletionStats.Builder
Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
Protobuf type google.cloud.aiplatform.v1.CompletionStats
CompletionStatsProto
ContainerRegistryDestination
The Container Registry location for the container image.
Protobuf type google.cloud.aiplatform.v1.ContainerRegistryDestination
ContainerRegistryDestination.Builder
The Container Registry location for the container image.
Protobuf type google.cloud.aiplatform.v1.ContainerRegistryDestination
ContainerSpec
The spec of a Container.
Protobuf type google.cloud.aiplatform.v1.ContainerSpec
ContainerSpec.Builder
The spec of a Container.
Protobuf type google.cloud.aiplatform.v1.ContainerSpec
Context
Instance of a general context.
Protobuf type google.cloud.aiplatform.v1.Context
Context.Builder
Instance of a general context.
Protobuf type google.cloud.aiplatform.v1.Context
ContextName
ContextName.Builder
Builder for projects/{project}/locations/{location}/metadataStores/{metadata_store}/contexts/{context}.
ContextProto
CopyModelOperationMetadata
Details of ModelService.CopyModel operation.
Protobuf type google.cloud.aiplatform.v1.CopyModelOperationMetadata
CopyModelOperationMetadata.Builder
Details of ModelService.CopyModel operation.
Protobuf type google.cloud.aiplatform.v1.CopyModelOperationMetadata
CopyModelRequest
Request message for ModelService.CopyModel.
Protobuf type google.cloud.aiplatform.v1.CopyModelRequest
CopyModelRequest.Builder
Request message for ModelService.CopyModel.
Protobuf type google.cloud.aiplatform.v1.CopyModelRequest
CopyModelResponse
Response message of ModelService.CopyModel operation.
Protobuf type google.cloud.aiplatform.v1.CopyModelResponse
CopyModelResponse.Builder
Response message of ModelService.CopyModel operation.
Protobuf type google.cloud.aiplatform.v1.CopyModelResponse
CreateArtifactRequest
Request message for MetadataService.CreateArtifact.
Protobuf type google.cloud.aiplatform.v1.CreateArtifactRequest
CreateArtifactRequest.Builder
Request message for MetadataService.CreateArtifact.
Protobuf type google.cloud.aiplatform.v1.CreateArtifactRequest
CreateBatchPredictionJobRequest
Request message for JobService.CreateBatchPredictionJob.
Protobuf type google.cloud.aiplatform.v1.CreateBatchPredictionJobRequest
CreateBatchPredictionJobRequest.Builder
Request message for JobService.CreateBatchPredictionJob.
Protobuf type google.cloud.aiplatform.v1.CreateBatchPredictionJobRequest
CreateContextRequest
Request message for MetadataService.CreateContext.
Protobuf type google.cloud.aiplatform.v1.CreateContextRequest
CreateContextRequest.Builder
Request message for MetadataService.CreateContext.
Protobuf type google.cloud.aiplatform.v1.CreateContextRequest
CreateCustomJobRequest
Request message for JobService.CreateCustomJob.
Protobuf type google.cloud.aiplatform.v1.CreateCustomJobRequest
CreateCustomJobRequest.Builder
Request message for JobService.CreateCustomJob.
Protobuf type google.cloud.aiplatform.v1.CreateCustomJobRequest
CreateDataLabelingJobRequest
Request message for JobService.CreateDataLabelingJob.
Protobuf type google.cloud.aiplatform.v1.CreateDataLabelingJobRequest
CreateDataLabelingJobRequest.Builder
Request message for JobService.CreateDataLabelingJob.
Protobuf type google.cloud.aiplatform.v1.CreateDataLabelingJobRequest
CreateDatasetOperationMetadata
Runtime operation information for DatasetService.CreateDataset.
Protobuf type google.cloud.aiplatform.v1.CreateDatasetOperationMetadata
CreateDatasetOperationMetadata.Builder
Runtime operation information for DatasetService.CreateDataset.
Protobuf type google.cloud.aiplatform.v1.CreateDatasetOperationMetadata
CreateDatasetRequest
Request message for DatasetService.CreateDataset.
Protobuf type google.cloud.aiplatform.v1.CreateDatasetRequest
CreateDatasetRequest.Builder
Request message for DatasetService.CreateDataset.
Protobuf type google.cloud.aiplatform.v1.CreateDatasetRequest
CreateDatasetVersionOperationMetadata
Runtime operation information for DatasetService.CreateDatasetVersion.
Protobuf type google.cloud.aiplatform.v1.CreateDatasetVersionOperationMetadata
CreateDatasetVersionOperationMetadata.Builder
Runtime operation information for DatasetService.CreateDatasetVersion.
Protobuf type google.cloud.aiplatform.v1.CreateDatasetVersionOperationMetadata
CreateEndpointOperationMetadata
Runtime operation information for EndpointService.CreateEndpoint.
Protobuf type google.cloud.aiplatform.v1.CreateEndpointOperationMetadata
CreateEndpointOperationMetadata.Builder
Runtime operation information for EndpointService.CreateEndpoint.
Protobuf type google.cloud.aiplatform.v1.CreateEndpointOperationMetadata
CreateEndpointRequest
Request message for EndpointService.CreateEndpoint.
Protobuf type google.cloud.aiplatform.v1.CreateEndpointRequest
CreateEndpointRequest.Builder
Request message for EndpointService.CreateEndpoint.
Protobuf type google.cloud.aiplatform.v1.CreateEndpointRequest
CreateEntityTypeOperationMetadata
Details of operations that perform create EntityType.
Protobuf type google.cloud.aiplatform.v1.CreateEntityTypeOperationMetadata
CreateEntityTypeOperationMetadata.Builder
Details of operations that perform create EntityType.
Protobuf type google.cloud.aiplatform.v1.CreateEntityTypeOperationMetadata
CreateEntityTypeRequest
Request message for FeaturestoreService.CreateEntityType.
Protobuf type google.cloud.aiplatform.v1.CreateEntityTypeRequest
CreateEntityTypeRequest.Builder
Request message for FeaturestoreService.CreateEntityType.
Protobuf type google.cloud.aiplatform.v1.CreateEntityTypeRequest
CreateExecutionRequest
Request message for MetadataService.CreateExecution.
Protobuf type google.cloud.aiplatform.v1.CreateExecutionRequest
CreateExecutionRequest.Builder
Request message for MetadataService.CreateExecution.
Protobuf type google.cloud.aiplatform.v1.CreateExecutionRequest
CreateFeatureOperationMetadata
Details of operations that perform create Feature.
Protobuf type google.cloud.aiplatform.v1.CreateFeatureOperationMetadata
CreateFeatureOperationMetadata.Builder
Details of operations that perform create Feature.
Protobuf type google.cloud.aiplatform.v1.CreateFeatureOperationMetadata
CreateFeatureRequest
Request message for FeaturestoreService.CreateFeature.
Protobuf type google.cloud.aiplatform.v1.CreateFeatureRequest
CreateFeatureRequest.Builder
Request message for FeaturestoreService.CreateFeature.
Protobuf type google.cloud.aiplatform.v1.CreateFeatureRequest
CreateFeaturestoreOperationMetadata
Details of operations that perform create Featurestore.
Protobuf type google.cloud.aiplatform.v1.CreateFeaturestoreOperationMetadata
CreateFeaturestoreOperationMetadata.Builder
Details of operations that perform create Featurestore.
Protobuf type google.cloud.aiplatform.v1.CreateFeaturestoreOperationMetadata
CreateFeaturestoreRequest
Request message for FeaturestoreService.CreateFeaturestore.
Protobuf type google.cloud.aiplatform.v1.CreateFeaturestoreRequest
CreateFeaturestoreRequest.Builder
Request message for FeaturestoreService.CreateFeaturestore.
Protobuf type google.cloud.aiplatform.v1.CreateFeaturestoreRequest
CreateHyperparameterTuningJobRequest
Request message for JobService.CreateHyperparameterTuningJob.
Protobuf type google.cloud.aiplatform.v1.CreateHyperparameterTuningJobRequest
CreateHyperparameterTuningJobRequest.Builder
Request message for JobService.CreateHyperparameterTuningJob.
Protobuf type google.cloud.aiplatform.v1.CreateHyperparameterTuningJobRequest
CreateIndexEndpointOperationMetadata
Runtime operation information for IndexEndpointService.CreateIndexEndpoint.
Protobuf type google.cloud.aiplatform.v1.CreateIndexEndpointOperationMetadata
CreateIndexEndpointOperationMetadata.Builder
Runtime operation information for IndexEndpointService.CreateIndexEndpoint.
Protobuf type google.cloud.aiplatform.v1.CreateIndexEndpointOperationMetadata
CreateIndexEndpointRequest
Request message for IndexEndpointService.CreateIndexEndpoint.
Protobuf type google.cloud.aiplatform.v1.CreateIndexEndpointRequest
CreateIndexEndpointRequest.Builder
Request message for IndexEndpointService.CreateIndexEndpoint.
Protobuf type google.cloud.aiplatform.v1.CreateIndexEndpointRequest
CreateIndexOperationMetadata
Runtime operation information for IndexService.CreateIndex.
Protobuf type google.cloud.aiplatform.v1.CreateIndexOperationMetadata
CreateIndexOperationMetadata.Builder
Runtime operation information for IndexService.CreateIndex.
Protobuf type google.cloud.aiplatform.v1.CreateIndexOperationMetadata
CreateIndexRequest
Request message for IndexService.CreateIndex.
Protobuf type google.cloud.aiplatform.v1.CreateIndexRequest
CreateIndexRequest.Builder
Request message for IndexService.CreateIndex.
Protobuf type google.cloud.aiplatform.v1.CreateIndexRequest
CreateMetadataSchemaRequest
Request message for MetadataService.CreateMetadataSchema.
Protobuf type google.cloud.aiplatform.v1.CreateMetadataSchemaRequest
CreateMetadataSchemaRequest.Builder
Request message for MetadataService.CreateMetadataSchema.
Protobuf type google.cloud.aiplatform.v1.CreateMetadataSchemaRequest
CreateMetadataStoreOperationMetadata
Details of operations that perform MetadataService.CreateMetadataStore.
Protobuf type google.cloud.aiplatform.v1.CreateMetadataStoreOperationMetadata
CreateMetadataStoreOperationMetadata.Builder
Details of operations that perform MetadataService.CreateMetadataStore.
Protobuf type google.cloud.aiplatform.v1.CreateMetadataStoreOperationMetadata
CreateMetadataStoreRequest
Request message for MetadataService.CreateMetadataStore.
Protobuf type google.cloud.aiplatform.v1.CreateMetadataStoreRequest
CreateMetadataStoreRequest.Builder
Request message for MetadataService.CreateMetadataStore.
Protobuf type google.cloud.aiplatform.v1.CreateMetadataStoreRequest
CreateModelDeploymentMonitoringJobRequest
Request message for JobService.CreateModelDeploymentMonitoringJob.
Protobuf type google.cloud.aiplatform.v1.CreateModelDeploymentMonitoringJobRequest
CreateModelDeploymentMonitoringJobRequest.Builder
Request message for JobService.CreateModelDeploymentMonitoringJob.
Protobuf type google.cloud.aiplatform.v1.CreateModelDeploymentMonitoringJobRequest
CreateNasJobRequest
Request message for JobService.CreateNasJob.
Protobuf type google.cloud.aiplatform.v1.CreateNasJobRequest
CreateNasJobRequest.Builder
Request message for JobService.CreateNasJob.
Protobuf type google.cloud.aiplatform.v1.CreateNasJobRequest
CreatePipelineJobRequest
Request message for PipelineService.CreatePipelineJob.
Protobuf type google.cloud.aiplatform.v1.CreatePipelineJobRequest
CreatePipelineJobRequest.Builder
Request message for PipelineService.CreatePipelineJob.
Protobuf type google.cloud.aiplatform.v1.CreatePipelineJobRequest
CreateScheduleRequest
Request message for ScheduleService.CreateSchedule.
Protobuf type google.cloud.aiplatform.v1.CreateScheduleRequest
CreateScheduleRequest.Builder
Request message for ScheduleService.CreateSchedule.
Protobuf type google.cloud.aiplatform.v1.CreateScheduleRequest
CreateSpecialistPoolOperationMetadata
Runtime operation information for SpecialistPoolService.CreateSpecialistPool.
Protobuf type google.cloud.aiplatform.v1.CreateSpecialistPoolOperationMetadata
CreateSpecialistPoolOperationMetadata.Builder
Runtime operation information for SpecialistPoolService.CreateSpecialistPool.
Protobuf type google.cloud.aiplatform.v1.CreateSpecialistPoolOperationMetadata
CreateSpecialistPoolRequest
Request message for SpecialistPoolService.CreateSpecialistPool.
Protobuf type google.cloud.aiplatform.v1.CreateSpecialistPoolRequest
CreateSpecialistPoolRequest.Builder
Request message for SpecialistPoolService.CreateSpecialistPool.
Protobuf type google.cloud.aiplatform.v1.CreateSpecialistPoolRequest
CreateStudyRequest
Request message for VizierService.CreateStudy.
Protobuf type google.cloud.aiplatform.v1.CreateStudyRequest
CreateStudyRequest.Builder
Request message for VizierService.CreateStudy.
Protobuf type google.cloud.aiplatform.v1.CreateStudyRequest
CreateTensorboardExperimentRequest
Request message for TensorboardService.CreateTensorboardExperiment.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardExperimentRequest
CreateTensorboardExperimentRequest.Builder
Request message for TensorboardService.CreateTensorboardExperiment.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardExperimentRequest
CreateTensorboardOperationMetadata
Details of operations that perform create Tensorboard.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardOperationMetadata
CreateTensorboardOperationMetadata.Builder
Details of operations that perform create Tensorboard.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardOperationMetadata
CreateTensorboardRequest
Request message for TensorboardService.CreateTensorboard.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardRequest
CreateTensorboardRequest.Builder
Request message for TensorboardService.CreateTensorboard.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardRequest
CreateTensorboardRunRequest
Request message for TensorboardService.CreateTensorboardRun.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardRunRequest
CreateTensorboardRunRequest.Builder
Request message for TensorboardService.CreateTensorboardRun.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardRunRequest
CreateTensorboardTimeSeriesRequest
Request message for TensorboardService.CreateTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardTimeSeriesRequest
CreateTensorboardTimeSeriesRequest.Builder
Request message for TensorboardService.CreateTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.CreateTensorboardTimeSeriesRequest
CreateTrainingPipelineRequest
Request message for PipelineService.CreateTrainingPipeline.
Protobuf type google.cloud.aiplatform.v1.CreateTrainingPipelineRequest
CreateTrainingPipelineRequest.Builder
Request message for PipelineService.CreateTrainingPipeline.
Protobuf type google.cloud.aiplatform.v1.CreateTrainingPipelineRequest
CreateTrialRequest
Request message for VizierService.CreateTrial.
Protobuf type google.cloud.aiplatform.v1.CreateTrialRequest
CreateTrialRequest.Builder
Request message for VizierService.CreateTrial.
Protobuf type google.cloud.aiplatform.v1.CreateTrialRequest
CsvDestination
The storage details for CSV output content.
Protobuf type google.cloud.aiplatform.v1.CsvDestination
CsvDestination.Builder
The storage details for CSV output content.
Protobuf type google.cloud.aiplatform.v1.CsvDestination
CsvSource
The storage details for CSV input content.
Protobuf type google.cloud.aiplatform.v1.CsvSource
CsvSource.Builder
The storage details for CSV input content.
Protobuf type google.cloud.aiplatform.v1.CsvSource
CustomJob
Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).
Protobuf type google.cloud.aiplatform.v1.CustomJob
CustomJob.Builder
Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).
Protobuf type google.cloud.aiplatform.v1.CustomJob
CustomJobName
CustomJobName.Builder
Builder for projects/{project}/locations/{location}/customJobs/{custom_job}.
CustomJobProto
CustomJobSpec
Represents the spec of a CustomJob.
Protobuf type google.cloud.aiplatform.v1.CustomJobSpec
CustomJobSpec.Builder
Represents the spec of a CustomJob.
Protobuf type google.cloud.aiplatform.v1.CustomJobSpec
DataItem
A piece of data in a Dataset. Could be an image, a video, a document or plain text.
Protobuf type google.cloud.aiplatform.v1.DataItem
DataItem.Builder
A piece of data in a Dataset. Could be an image, a video, a document or plain text.
Protobuf type google.cloud.aiplatform.v1.DataItem
DataItemName
DataItemName.Builder
Builder for projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}.
DataItemProto
DataItemView
A container for a single DataItem and Annotations on it.
Protobuf type google.cloud.aiplatform.v1.DataItemView
DataItemView.Builder
A container for a single DataItem and Annotations on it.
Protobuf type google.cloud.aiplatform.v1.DataItemView
DataLabelingJob
DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:
Protobuf type google.cloud.aiplatform.v1.DataLabelingJob
DataLabelingJob.Builder
DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:
Protobuf type google.cloud.aiplatform.v1.DataLabelingJob
DataLabelingJobName
DataLabelingJobName.Builder
Builder for projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}.
DataLabelingJobProto
Dataset
A collection of DataItems and Annotations on them.
Protobuf type google.cloud.aiplatform.v1.Dataset
Dataset.Builder
A collection of DataItems and Annotations on them.
Protobuf type google.cloud.aiplatform.v1.Dataset
DatasetName
DatasetName.Builder
Builder for projects/{project}/locations/{location}/datasets/{dataset}.
DatasetProto
DatasetServiceClient
Service Description: The service that manages Vertex AI Dataset and its child resources.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the DatasetServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of DatasetServiceSettings to create(). For example:
To customize credentials:
// 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
DatasetServiceSettings datasetServiceSettings =
DatasetServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
DatasetServiceClient datasetServiceClient = DatasetServiceClient.create(datasetServiceSettings);
To customize the endpoint:
// 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
DatasetServiceSettings datasetServiceSettings =
DatasetServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
DatasetServiceClient datasetServiceClient = DatasetServiceClient.create(datasetServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
DatasetServiceClient.ListAnnotationsFixedSizeCollection
DatasetServiceClient.ListAnnotationsPage
DatasetServiceClient.ListAnnotationsPagedResponse
DatasetServiceClient.ListDataItemsFixedSizeCollection
DatasetServiceClient.ListDataItemsPage
DatasetServiceClient.ListDataItemsPagedResponse
DatasetServiceClient.ListDatasetsFixedSizeCollection
DatasetServiceClient.ListDatasetsPage
DatasetServiceClient.ListDatasetsPagedResponse
DatasetServiceClient.ListLocationsFixedSizeCollection
DatasetServiceClient.ListLocationsPage
DatasetServiceClient.ListLocationsPagedResponse
DatasetServiceClient.ListSavedQueriesFixedSizeCollection
DatasetServiceClient.ListSavedQueriesPage
DatasetServiceClient.ListSavedQueriesPagedResponse
DatasetServiceClient.SearchDataItemsFixedSizeCollection
DatasetServiceClient.SearchDataItemsPage
DatasetServiceClient.SearchDataItemsPagedResponse
DatasetServiceGrpc
The service that manages Vertex AI Dataset and its child resources.
DatasetServiceGrpc.DatasetServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service DatasetService.
The service that manages Vertex AI Dataset and its child resources.
DatasetServiceGrpc.DatasetServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service DatasetService.
The service that manages Vertex AI Dataset and its child resources.
DatasetServiceGrpc.DatasetServiceImplBase
Base class for the server implementation of the service DatasetService.
The service that manages Vertex AI Dataset and its child resources.
DatasetServiceGrpc.DatasetServiceStub
A stub to allow clients to do asynchronous rpc calls to service DatasetService.
The service that manages Vertex AI Dataset and its child resources.
DatasetServiceProto
DatasetServiceSettings
Settings class to configure an instance of DatasetServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of getDataset to 30 seconds:
// 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
DatasetServiceSettings.Builder datasetServiceSettingsBuilder =
DatasetServiceSettings.newBuilder();
datasetServiceSettingsBuilder
.getDatasetSettings()
.setRetrySettings(
datasetServiceSettingsBuilder
.getDatasetSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
DatasetServiceSettings datasetServiceSettings = datasetServiceSettingsBuilder.build();
DatasetServiceSettings.Builder
Builder for DatasetServiceSettings.
DedicatedResources
A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.
Protobuf type google.cloud.aiplatform.v1.DedicatedResources
DedicatedResources.Builder
A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.
Protobuf type google.cloud.aiplatform.v1.DedicatedResources
DeleteArtifactRequest
Request message for MetadataService.DeleteArtifact.
Protobuf type google.cloud.aiplatform.v1.DeleteArtifactRequest
DeleteArtifactRequest.Builder
Request message for MetadataService.DeleteArtifact.
Protobuf type google.cloud.aiplatform.v1.DeleteArtifactRequest
DeleteBatchPredictionJobRequest
Request message for JobService.DeleteBatchPredictionJob.
Protobuf type google.cloud.aiplatform.v1.DeleteBatchPredictionJobRequest
DeleteBatchPredictionJobRequest.Builder
Request message for JobService.DeleteBatchPredictionJob.
Protobuf type google.cloud.aiplatform.v1.DeleteBatchPredictionJobRequest
DeleteContextRequest
Request message for MetadataService.DeleteContext.
Protobuf type google.cloud.aiplatform.v1.DeleteContextRequest
DeleteContextRequest.Builder
Request message for MetadataService.DeleteContext.
Protobuf type google.cloud.aiplatform.v1.DeleteContextRequest
DeleteCustomJobRequest
Request message for JobService.DeleteCustomJob.
Protobuf type google.cloud.aiplatform.v1.DeleteCustomJobRequest
DeleteCustomJobRequest.Builder
Request message for JobService.DeleteCustomJob.
Protobuf type google.cloud.aiplatform.v1.DeleteCustomJobRequest
DeleteDataLabelingJobRequest
Request message for JobService.DeleteDataLabelingJob.
Protobuf type google.cloud.aiplatform.v1.DeleteDataLabelingJobRequest
DeleteDataLabelingJobRequest.Builder
Request message for JobService.DeleteDataLabelingJob.
Protobuf type google.cloud.aiplatform.v1.DeleteDataLabelingJobRequest
DeleteDatasetRequest
Request message for DatasetService.DeleteDataset.
Protobuf type google.cloud.aiplatform.v1.DeleteDatasetRequest
DeleteDatasetRequest.Builder
Request message for DatasetService.DeleteDataset.
Protobuf type google.cloud.aiplatform.v1.DeleteDatasetRequest
DeleteEndpointRequest
Request message for EndpointService.DeleteEndpoint.
Protobuf type google.cloud.aiplatform.v1.DeleteEndpointRequest
DeleteEndpointRequest.Builder
Request message for EndpointService.DeleteEndpoint.
Protobuf type google.cloud.aiplatform.v1.DeleteEndpointRequest
DeleteEntityTypeRequest
Request message for [FeaturestoreService.DeleteEntityTypes][].
Protobuf type google.cloud.aiplatform.v1.DeleteEntityTypeRequest
DeleteEntityTypeRequest.Builder
Request message for [FeaturestoreService.DeleteEntityTypes][].
Protobuf type google.cloud.aiplatform.v1.DeleteEntityTypeRequest
DeleteExecutionRequest
Request message for MetadataService.DeleteExecution.
Protobuf type google.cloud.aiplatform.v1.DeleteExecutionRequest
DeleteExecutionRequest.Builder
Request message for MetadataService.DeleteExecution.
Protobuf type google.cloud.aiplatform.v1.DeleteExecutionRequest
DeleteFeatureRequest
Request message for FeaturestoreService.DeleteFeature.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureRequest
DeleteFeatureRequest.Builder
Request message for FeaturestoreService.DeleteFeature.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureRequest
DeleteFeatureValuesOperationMetadata
Details of operations that delete Feature values.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesOperationMetadata
DeleteFeatureValuesOperationMetadata.Builder
Details of operations that delete Feature values.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesOperationMetadata
DeleteFeatureValuesRequest
Request message for FeaturestoreService.DeleteFeatureValues.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesRequest
DeleteFeatureValuesRequest.Builder
Request message for FeaturestoreService.DeleteFeatureValues.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesRequest
DeleteFeatureValuesRequest.SelectEntity
Message to select entity. If an entity id is selected, all the feature values corresponding to the entity id will be deleted, including the entityId.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesRequest.SelectEntity
DeleteFeatureValuesRequest.SelectEntity.Builder
Message to select entity. If an entity id is selected, all the feature values corresponding to the entity id will be deleted, including the entityId.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesRequest.SelectEntity
DeleteFeatureValuesRequest.SelectTimeRangeAndFeature
Message to select time range and feature. Values of the selected feature generated within an inclusive time range will be deleted. Using this option permanently deletes the feature values from the specified feature IDs within the specified time range. This might include data from the online storage. If you want to retain any deleted historical data in the online storage, you must re-ingest it.
Protobuf type
google.cloud.aiplatform.v1.DeleteFeatureValuesRequest.SelectTimeRangeAndFeature
DeleteFeatureValuesRequest.SelectTimeRangeAndFeature.Builder
Message to select time range and feature. Values of the selected feature generated within an inclusive time range will be deleted. Using this option permanently deletes the feature values from the specified feature IDs within the specified time range. This might include data from the online storage. If you want to retain any deleted historical data in the online storage, you must re-ingest it.
Protobuf type
google.cloud.aiplatform.v1.DeleteFeatureValuesRequest.SelectTimeRangeAndFeature
DeleteFeatureValuesResponse
Response message for FeaturestoreService.DeleteFeatureValues.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesResponse
DeleteFeatureValuesResponse.Builder
Response message for FeaturestoreService.DeleteFeatureValues.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesResponse
DeleteFeatureValuesResponse.SelectEntity
Response message if the request uses the SelectEntity option.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesResponse.SelectEntity
DeleteFeatureValuesResponse.SelectEntity.Builder
Response message if the request uses the SelectEntity option.
Protobuf type google.cloud.aiplatform.v1.DeleteFeatureValuesResponse.SelectEntity
DeleteFeatureValuesResponse.SelectTimeRangeAndFeature
Response message if the request uses the SelectTimeRangeAndFeature option.
Protobuf type
google.cloud.aiplatform.v1.DeleteFeatureValuesResponse.SelectTimeRangeAndFeature
DeleteFeatureValuesResponse.SelectTimeRangeAndFeature.Builder
Response message if the request uses the SelectTimeRangeAndFeature option.
Protobuf type
google.cloud.aiplatform.v1.DeleteFeatureValuesResponse.SelectTimeRangeAndFeature
DeleteFeaturestoreRequest
Request message for FeaturestoreService.DeleteFeaturestore.
Protobuf type google.cloud.aiplatform.v1.DeleteFeaturestoreRequest
DeleteFeaturestoreRequest.Builder
Request message for FeaturestoreService.DeleteFeaturestore.
Protobuf type google.cloud.aiplatform.v1.DeleteFeaturestoreRequest
DeleteHyperparameterTuningJobRequest
Request message for JobService.DeleteHyperparameterTuningJob.
Protobuf type google.cloud.aiplatform.v1.DeleteHyperparameterTuningJobRequest
DeleteHyperparameterTuningJobRequest.Builder
Request message for JobService.DeleteHyperparameterTuningJob.
Protobuf type google.cloud.aiplatform.v1.DeleteHyperparameterTuningJobRequest
DeleteIndexEndpointRequest
Request message for IndexEndpointService.DeleteIndexEndpoint.
Protobuf type google.cloud.aiplatform.v1.DeleteIndexEndpointRequest
DeleteIndexEndpointRequest.Builder
Request message for IndexEndpointService.DeleteIndexEndpoint.
Protobuf type google.cloud.aiplatform.v1.DeleteIndexEndpointRequest
DeleteIndexRequest
Request message for IndexService.DeleteIndex.
Protobuf type google.cloud.aiplatform.v1.DeleteIndexRequest
DeleteIndexRequest.Builder
Request message for IndexService.DeleteIndex.
Protobuf type google.cloud.aiplatform.v1.DeleteIndexRequest
DeleteMetadataStoreOperationMetadata
Details of operations that perform MetadataService.DeleteMetadataStore.
Protobuf type google.cloud.aiplatform.v1.DeleteMetadataStoreOperationMetadata
DeleteMetadataStoreOperationMetadata.Builder
Details of operations that perform MetadataService.DeleteMetadataStore.
Protobuf type google.cloud.aiplatform.v1.DeleteMetadataStoreOperationMetadata
DeleteMetadataStoreRequest
Request message for MetadataService.DeleteMetadataStore.
Protobuf type google.cloud.aiplatform.v1.DeleteMetadataStoreRequest
DeleteMetadataStoreRequest.Builder
Request message for MetadataService.DeleteMetadataStore.
Protobuf type google.cloud.aiplatform.v1.DeleteMetadataStoreRequest
DeleteModelDeploymentMonitoringJobRequest
Request message for JobService.DeleteModelDeploymentMonitoringJob.
Protobuf type google.cloud.aiplatform.v1.DeleteModelDeploymentMonitoringJobRequest
DeleteModelDeploymentMonitoringJobRequest.Builder
Request message for JobService.DeleteModelDeploymentMonitoringJob.
Protobuf type google.cloud.aiplatform.v1.DeleteModelDeploymentMonitoringJobRequest
DeleteModelRequest
Request message for ModelService.DeleteModel.
Protobuf type google.cloud.aiplatform.v1.DeleteModelRequest
DeleteModelRequest.Builder
Request message for ModelService.DeleteModel.
Protobuf type google.cloud.aiplatform.v1.DeleteModelRequest
DeleteModelVersionRequest
Request message for ModelService.DeleteModelVersion.
Protobuf type google.cloud.aiplatform.v1.DeleteModelVersionRequest
DeleteModelVersionRequest.Builder
Request message for ModelService.DeleteModelVersion.
Protobuf type google.cloud.aiplatform.v1.DeleteModelVersionRequest
DeleteNasJobRequest
Request message for JobService.DeleteNasJob.
Protobuf type google.cloud.aiplatform.v1.DeleteNasJobRequest
DeleteNasJobRequest.Builder
Request message for JobService.DeleteNasJob.
Protobuf type google.cloud.aiplatform.v1.DeleteNasJobRequest
DeleteOperationMetadata
Details of operations that perform deletes of any entities.
Protobuf type google.cloud.aiplatform.v1.DeleteOperationMetadata
DeleteOperationMetadata.Builder
Details of operations that perform deletes of any entities.
Protobuf type google.cloud.aiplatform.v1.DeleteOperationMetadata
DeletePipelineJobRequest
Request message for PipelineService.DeletePipelineJob.
Protobuf type google.cloud.aiplatform.v1.DeletePipelineJobRequest
DeletePipelineJobRequest.Builder
Request message for PipelineService.DeletePipelineJob.
Protobuf type google.cloud.aiplatform.v1.DeletePipelineJobRequest
DeleteSavedQueryRequest
Request message for DatasetService.DeleteSavedQuery.
Protobuf type google.cloud.aiplatform.v1.DeleteSavedQueryRequest
DeleteSavedQueryRequest.Builder
Request message for DatasetService.DeleteSavedQuery.
Protobuf type google.cloud.aiplatform.v1.DeleteSavedQueryRequest
DeleteScheduleRequest
Request message for ScheduleService.DeleteSchedule.
Protobuf type google.cloud.aiplatform.v1.DeleteScheduleRequest
DeleteScheduleRequest.Builder
Request message for ScheduleService.DeleteSchedule.
Protobuf type google.cloud.aiplatform.v1.DeleteScheduleRequest
DeleteSpecialistPoolRequest
Request message for SpecialistPoolService.DeleteSpecialistPool.
Protobuf type google.cloud.aiplatform.v1.DeleteSpecialistPoolRequest
DeleteSpecialistPoolRequest.Builder
Request message for SpecialistPoolService.DeleteSpecialistPool.
Protobuf type google.cloud.aiplatform.v1.DeleteSpecialistPoolRequest
DeleteStudyRequest
Request message for VizierService.DeleteStudy.
Protobuf type google.cloud.aiplatform.v1.DeleteStudyRequest
DeleteStudyRequest.Builder
Request message for VizierService.DeleteStudy.
Protobuf type google.cloud.aiplatform.v1.DeleteStudyRequest
DeleteTensorboardExperimentRequest
Request message for TensorboardService.DeleteTensorboardExperiment.
Protobuf type google.cloud.aiplatform.v1.DeleteTensorboardExperimentRequest
DeleteTensorboardExperimentRequest.Builder
Request message for TensorboardService.DeleteTensorboardExperiment.
Protobuf type google.cloud.aiplatform.v1.DeleteTensorboardExperimentRequest
DeleteTensorboardRequest
Request message for TensorboardService.DeleteTensorboard.
Protobuf type google.cloud.aiplatform.v1.DeleteTensorboardRequest
DeleteTensorboardRequest.Builder
Request message for TensorboardService.DeleteTensorboard.
Protobuf type google.cloud.aiplatform.v1.DeleteTensorboardRequest
DeleteTensorboardRunRequest
Request message for TensorboardService.DeleteTensorboardRun.
Protobuf type google.cloud.aiplatform.v1.DeleteTensorboardRunRequest
DeleteTensorboardRunRequest.Builder
Request message for TensorboardService.DeleteTensorboardRun.
Protobuf type google.cloud.aiplatform.v1.DeleteTensorboardRunRequest
DeleteTensorboardTimeSeriesRequest
Request message for TensorboardService.DeleteTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.DeleteTensorboardTimeSeriesRequest
DeleteTensorboardTimeSeriesRequest.Builder
Request message for TensorboardService.DeleteTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.DeleteTensorboardTimeSeriesRequest
DeleteTrainingPipelineRequest
Request message for PipelineService.DeleteTrainingPipeline.
Protobuf type google.cloud.aiplatform.v1.DeleteTrainingPipelineRequest
DeleteTrainingPipelineRequest.Builder
Request message for PipelineService.DeleteTrainingPipeline.
Protobuf type google.cloud.aiplatform.v1.DeleteTrainingPipelineRequest
DeleteTrialRequest
Request message for VizierService.DeleteTrial.
Protobuf type google.cloud.aiplatform.v1.DeleteTrialRequest
DeleteTrialRequest.Builder
Request message for VizierService.DeleteTrial.
Protobuf type google.cloud.aiplatform.v1.DeleteTrialRequest
DeployIndexOperationMetadata
Runtime operation information for IndexEndpointService.DeployIndex.
Protobuf type google.cloud.aiplatform.v1.DeployIndexOperationMetadata
DeployIndexOperationMetadata.Builder
Runtime operation information for IndexEndpointService.DeployIndex.
Protobuf type google.cloud.aiplatform.v1.DeployIndexOperationMetadata
DeployIndexRequest
Request message for IndexEndpointService.DeployIndex.
Protobuf type google.cloud.aiplatform.v1.DeployIndexRequest
DeployIndexRequest.Builder
Request message for IndexEndpointService.DeployIndex.
Protobuf type google.cloud.aiplatform.v1.DeployIndexRequest
DeployIndexResponse
Response message for IndexEndpointService.DeployIndex.
Protobuf type google.cloud.aiplatform.v1.DeployIndexResponse
DeployIndexResponse.Builder
Response message for IndexEndpointService.DeployIndex.
Protobuf type google.cloud.aiplatform.v1.DeployIndexResponse
DeployModelOperationMetadata
Runtime operation information for EndpointService.DeployModel.
Protobuf type google.cloud.aiplatform.v1.DeployModelOperationMetadata
DeployModelOperationMetadata.Builder
Runtime operation information for EndpointService.DeployModel.
Protobuf type google.cloud.aiplatform.v1.DeployModelOperationMetadata
DeployModelRequest
Request message for EndpointService.DeployModel.
Protobuf type google.cloud.aiplatform.v1.DeployModelRequest
DeployModelRequest.Builder
Request message for EndpointService.DeployModel.
Protobuf type google.cloud.aiplatform.v1.DeployModelRequest
DeployModelResponse
Response message for EndpointService.DeployModel.
Protobuf type google.cloud.aiplatform.v1.DeployModelResponse
DeployModelResponse.Builder
Response message for EndpointService.DeployModel.
Protobuf type google.cloud.aiplatform.v1.DeployModelResponse
DeployedIndex
A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.
Protobuf type google.cloud.aiplatform.v1.DeployedIndex
DeployedIndex.Builder
A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.
Protobuf type google.cloud.aiplatform.v1.DeployedIndex
DeployedIndexAuthConfig
Used to set up the auth on the DeployedIndex's private endpoint.
Protobuf type google.cloud.aiplatform.v1.DeployedIndexAuthConfig
DeployedIndexAuthConfig.AuthProvider
Configuration for an authentication provider, including support for JSON Web Token (JWT).
Protobuf type google.cloud.aiplatform.v1.DeployedIndexAuthConfig.AuthProvider
DeployedIndexAuthConfig.AuthProvider.Builder
Configuration for an authentication provider, including support for JSON Web Token (JWT).
Protobuf type google.cloud.aiplatform.v1.DeployedIndexAuthConfig.AuthProvider
DeployedIndexAuthConfig.Builder
Used to set up the auth on the DeployedIndex's private endpoint.
Protobuf type google.cloud.aiplatform.v1.DeployedIndexAuthConfig
DeployedIndexRef
Points to a DeployedIndex.
Protobuf type google.cloud.aiplatform.v1.DeployedIndexRef
DeployedIndexRef.Builder
Points to a DeployedIndex.
Protobuf type google.cloud.aiplatform.v1.DeployedIndexRef
DeployedIndexRefProto
DeployedModel
A deployment of a Model. Endpoints contain one or more DeployedModels.
Protobuf type google.cloud.aiplatform.v1.DeployedModel
DeployedModel.Builder
A deployment of a Model. Endpoints contain one or more DeployedModels.
Protobuf type google.cloud.aiplatform.v1.DeployedModel
DeployedModelNameProto
DeployedModelRef
Points to a DeployedModel.
Protobuf type google.cloud.aiplatform.v1.DeployedModelRef
DeployedModelRef.Builder
Points to a DeployedModel.
Protobuf type google.cloud.aiplatform.v1.DeployedModelRef
DestinationFeatureSetting
Protobuf type google.cloud.aiplatform.v1.DestinationFeatureSetting
DestinationFeatureSetting.Builder
Protobuf type google.cloud.aiplatform.v1.DestinationFeatureSetting
DiskSpec
Represents the spec of disk options.
Protobuf type google.cloud.aiplatform.v1.DiskSpec
DiskSpec.Builder
Represents the spec of disk options.
Protobuf type google.cloud.aiplatform.v1.DiskSpec
DoubleArray
A list of double values.
Protobuf type google.cloud.aiplatform.v1.DoubleArray
DoubleArray.Builder
A list of double values.
Protobuf type google.cloud.aiplatform.v1.DoubleArray
EncryptionSpec
Represents a customer-managed encryption key spec that can be applied to a top-level resource.
Protobuf type google.cloud.aiplatform.v1.EncryptionSpec
EncryptionSpec.Builder
Represents a customer-managed encryption key spec that can be applied to a top-level resource.
Protobuf type google.cloud.aiplatform.v1.EncryptionSpec
EncryptionSpecProto
Endpoint
Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.
Protobuf type google.cloud.aiplatform.v1.Endpoint
Endpoint.Builder
Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.
Protobuf type google.cloud.aiplatform.v1.Endpoint
EndpointName
EndpointName.Builder
Builder for projects/{project}/locations/{location}/endpoints/{endpoint}.
EndpointName.ProjectLocationPublisherModelBuilder
Builder for projects/{project}/locations/{location}/publishers/{publisher}/models/{model}.
EndpointProto
EndpointServiceClient
Service Description: A service for managing Vertex AI's Endpoints.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the EndpointServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of EndpointServiceSettings to create(). For example:
To customize credentials:
// 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
EndpointServiceSettings endpointServiceSettings =
EndpointServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
EndpointServiceClient endpointServiceClient =
EndpointServiceClient.create(endpointServiceSettings);
To customize the endpoint:
// 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
EndpointServiceSettings endpointServiceSettings =
EndpointServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
EndpointServiceClient endpointServiceClient =
EndpointServiceClient.create(endpointServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
EndpointServiceClient.ListEndpointsFixedSizeCollection
EndpointServiceClient.ListEndpointsPage
EndpointServiceClient.ListEndpointsPagedResponse
EndpointServiceClient.ListLocationsFixedSizeCollection
EndpointServiceClient.ListLocationsPage
EndpointServiceClient.ListLocationsPagedResponse
EndpointServiceGrpc
A service for managing Vertex AI's Endpoints.
EndpointServiceGrpc.EndpointServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service EndpointService.
A service for managing Vertex AI's Endpoints.
EndpointServiceGrpc.EndpointServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service EndpointService.
A service for managing Vertex AI's Endpoints.
EndpointServiceGrpc.EndpointServiceImplBase
Base class for the server implementation of the service EndpointService.
A service for managing Vertex AI's Endpoints.
EndpointServiceGrpc.EndpointServiceStub
A stub to allow clients to do asynchronous rpc calls to service EndpointService.
A service for managing Vertex AI's Endpoints.
EndpointServiceProto
EndpointServiceSettings
Settings class to configure an instance of EndpointServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of getEndpoint to 30 seconds:
// 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
EndpointServiceSettings.Builder endpointServiceSettingsBuilder =
EndpointServiceSettings.newBuilder();
endpointServiceSettingsBuilder
.getEndpointSettings()
.setRetrySettings(
endpointServiceSettingsBuilder
.getEndpointSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
EndpointServiceSettings endpointServiceSettings = endpointServiceSettingsBuilder.build();
EndpointServiceSettings.Builder
Builder for EndpointServiceSettings.
EntityIdSelector
Selector for entityId. Getting ids from the given source.
Protobuf type google.cloud.aiplatform.v1.EntityIdSelector
EntityIdSelector.Builder
Selector for entityId. Getting ids from the given source.
Protobuf type google.cloud.aiplatform.v1.EntityIdSelector
EntityType
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.
Protobuf type google.cloud.aiplatform.v1.EntityType
EntityType.Builder
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.
Protobuf type google.cloud.aiplatform.v1.EntityType
EntityTypeName
EntityTypeName.Builder
Builder for projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}.
EntityTypeProto
EnvVar
Represents an environment variable present in a Container or Python Module.
Protobuf type google.cloud.aiplatform.v1.EnvVar
EnvVar.Builder
Represents an environment variable present in a Container or Python Module.
Protobuf type google.cloud.aiplatform.v1.EnvVar
EnvVarProto
ErrorAnalysisAnnotation
Model error analysis for each annotation.
Protobuf type google.cloud.aiplatform.v1.ErrorAnalysisAnnotation
ErrorAnalysisAnnotation.AttributedItem
Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.
Protobuf type google.cloud.aiplatform.v1.ErrorAnalysisAnnotation.AttributedItem
ErrorAnalysisAnnotation.AttributedItem.Builder
Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type.
Protobuf type google.cloud.aiplatform.v1.ErrorAnalysisAnnotation.AttributedItem
ErrorAnalysisAnnotation.Builder
Model error analysis for each annotation.
Protobuf type google.cloud.aiplatform.v1.ErrorAnalysisAnnotation
EvaluatedAnnotation
True positive, false positive, or false negative.
EvaluatedAnnotation is only available under ModelEvaluationSlice with slice
of annotationSpec dimension.
Protobuf type google.cloud.aiplatform.v1.EvaluatedAnnotation
EvaluatedAnnotation.Builder
True positive, false positive, or false negative.
EvaluatedAnnotation is only available under ModelEvaluationSlice with slice
of annotationSpec dimension.
Protobuf type google.cloud.aiplatform.v1.EvaluatedAnnotation
EvaluatedAnnotationExplanation
Explanation result of the prediction produced by the Model.
Protobuf type google.cloud.aiplatform.v1.EvaluatedAnnotationExplanation
EvaluatedAnnotationExplanation.Builder
Explanation result of the prediction produced by the Model.
Protobuf type google.cloud.aiplatform.v1.EvaluatedAnnotationExplanation
EvaluatedAnnotationProto
Event
An edge describing the relationship between an Artifact and an Execution in a lineage graph.
Protobuf type google.cloud.aiplatform.v1.Event
Event.Builder
An edge describing the relationship between an Artifact and an Execution in a lineage graph.
Protobuf type google.cloud.aiplatform.v1.Event
EventProto
Examples
Example-based explainability that returns the nearest neighbors from the provided dataset.
Protobuf type google.cloud.aiplatform.v1.Examples
Examples.Builder
Example-based explainability that returns the nearest neighbors from the provided dataset.
Protobuf type google.cloud.aiplatform.v1.Examples
Examples.ExampleGcsSource
The Cloud Storage input instances.
Protobuf type google.cloud.aiplatform.v1.Examples.ExampleGcsSource
Examples.ExampleGcsSource.Builder
The Cloud Storage input instances.
Protobuf type google.cloud.aiplatform.v1.Examples.ExampleGcsSource
ExamplesOverride
Overrides for example-based explanations.
Protobuf type google.cloud.aiplatform.v1.ExamplesOverride
ExamplesOverride.Builder
Overrides for example-based explanations.
Protobuf type google.cloud.aiplatform.v1.ExamplesOverride
ExamplesRestrictionsNamespace
Restrictions namespace for example-based explanations overrides.
Protobuf type google.cloud.aiplatform.v1.ExamplesRestrictionsNamespace
ExamplesRestrictionsNamespace.Builder
Restrictions namespace for example-based explanations overrides.
Protobuf type google.cloud.aiplatform.v1.ExamplesRestrictionsNamespace
Execution
Instance of a general execution.
Protobuf type google.cloud.aiplatform.v1.Execution
Execution.Builder
Instance of a general execution.
Protobuf type google.cloud.aiplatform.v1.Execution
ExecutionName
ExecutionName.Builder
Builder for projects/{project}/locations/{location}/metadataStores/{metadata_store}/executions/{execution}.
ExecutionProto
ExplainRequest
Request message for PredictionService.Explain.
Protobuf type google.cloud.aiplatform.v1.ExplainRequest
ExplainRequest.Builder
Request message for PredictionService.Explain.
Protobuf type google.cloud.aiplatform.v1.ExplainRequest
ExplainResponse
Response message for PredictionService.Explain.
Protobuf type google.cloud.aiplatform.v1.ExplainResponse
ExplainResponse.Builder
Response message for PredictionService.Explain.
Protobuf type google.cloud.aiplatform.v1.ExplainResponse
Explanation
Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.
Protobuf type google.cloud.aiplatform.v1.Explanation
Explanation.Builder
Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.
Protobuf type google.cloud.aiplatform.v1.Explanation
ExplanationMetadata
Metadata describing the Model's input and output for explanation.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata
ExplanationMetadata.Builder
Metadata describing the Model's input and output for explanation.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata
ExplanationMetadata.InputMetadata
Metadata of the input of a feature.
Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata
ExplanationMetadata.InputMetadata.Builder
Metadata of the input of a feature.
Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata
ExplanationMetadata.InputMetadata.FeatureValueDomain
Domain details of the input feature value. Provides numeric information about the feature, such as its range (min, max). If the feature has been pre-processed, for example with z-scoring, then it provides information about how to recover the original feature. For example, if the input feature is an image and it has been pre-processed to obtain 0-mean and stddev = 1 values, then original_mean, and original_stddev refer to the mean and stddev of the original feature (e.g. image tensor) from which input feature (with mean = 0 and stddev = 1) was obtained.
Protobuf type
google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain
ExplanationMetadata.InputMetadata.FeatureValueDomain.Builder
Domain details of the input feature value. Provides numeric information about the feature, such as its range (min, max). If the feature has been pre-processed, for example with z-scoring, then it provides information about how to recover the original feature. For example, if the input feature is an image and it has been pre-processed to obtain 0-mean and stddev = 1 values, then original_mean, and original_stddev refer to the mean and stddev of the original feature (e.g. image tensor) from which input feature (with mean = 0 and stddev = 1) was obtained.
Protobuf type
google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain
ExplanationMetadata.InputMetadata.Visualization
Visualization configurations for image explanation.
Protobuf type
google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization
ExplanationMetadata.InputMetadata.Visualization.Builder
Visualization configurations for image explanation.
Protobuf type
google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization
ExplanationMetadata.OutputMetadata
Metadata of the prediction output to be explained.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata
ExplanationMetadata.OutputMetadata.Builder
Metadata of the prediction output to be explained.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata
ExplanationMetadataOverride
The ExplanationMetadata entries that can be overridden at online explanation time.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadataOverride
ExplanationMetadataOverride.Builder
The ExplanationMetadata entries that can be overridden at online explanation time.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadataOverride
ExplanationMetadataOverride.InputMetadataOverride
The input metadata entries to be overridden.
Protobuf type
google.cloud.aiplatform.v1.ExplanationMetadataOverride.InputMetadataOverride
ExplanationMetadataOverride.InputMetadataOverride.Builder
The input metadata entries to be overridden.
Protobuf type
google.cloud.aiplatform.v1.ExplanationMetadataOverride.InputMetadataOverride
ExplanationMetadataProto
ExplanationParameters
Parameters to configure explaining for Model's predictions.
Protobuf type google.cloud.aiplatform.v1.ExplanationParameters
ExplanationParameters.Builder
Parameters to configure explaining for Model's predictions.
Protobuf type google.cloud.aiplatform.v1.ExplanationParameters
ExplanationProto
ExplanationSpec
Specification of Model explanation.
Protobuf type google.cloud.aiplatform.v1.ExplanationSpec
ExplanationSpec.Builder
Specification of Model explanation.
Protobuf type google.cloud.aiplatform.v1.ExplanationSpec
ExplanationSpecOverride
The ExplanationSpec entries that can be overridden at online explanation time.
Protobuf type google.cloud.aiplatform.v1.ExplanationSpecOverride
ExplanationSpecOverride.Builder
The ExplanationSpec entries that can be overridden at online explanation time.
Protobuf type google.cloud.aiplatform.v1.ExplanationSpecOverride
ExportDataConfig
Describes what part of the Dataset is to be exported, the destination of the export and how to export.
Protobuf type google.cloud.aiplatform.v1.ExportDataConfig
ExportDataConfig.Builder
Describes what part of the Dataset is to be exported, the destination of the export and how to export.
Protobuf type google.cloud.aiplatform.v1.ExportDataConfig
ExportDataOperationMetadata
Runtime operation information for DatasetService.ExportData.
Protobuf type google.cloud.aiplatform.v1.ExportDataOperationMetadata
ExportDataOperationMetadata.Builder
Runtime operation information for DatasetService.ExportData.
Protobuf type google.cloud.aiplatform.v1.ExportDataOperationMetadata
ExportDataRequest
Request message for DatasetService.ExportData.
Protobuf type google.cloud.aiplatform.v1.ExportDataRequest
ExportDataRequest.Builder
Request message for DatasetService.ExportData.
Protobuf type google.cloud.aiplatform.v1.ExportDataRequest
ExportDataResponse
Response message for DatasetService.ExportData.
Protobuf type google.cloud.aiplatform.v1.ExportDataResponse
ExportDataResponse.Builder
Response message for DatasetService.ExportData.
Protobuf type google.cloud.aiplatform.v1.ExportDataResponse
ExportFeatureValuesOperationMetadata
Details of operations that exports Features values.
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesOperationMetadata
ExportFeatureValuesOperationMetadata.Builder
Details of operations that exports Features values.
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesOperationMetadata
ExportFeatureValuesRequest
Request message for FeaturestoreService.ExportFeatureValues.
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesRequest
ExportFeatureValuesRequest.Builder
Request message for FeaturestoreService.ExportFeatureValues.
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesRequest
ExportFeatureValuesRequest.FullExport
Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time].
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesRequest.FullExport
ExportFeatureValuesRequest.FullExport.Builder
Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time].
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesRequest.FullExport
ExportFeatureValuesRequest.SnapshotExport
Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time].
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesRequest.SnapshotExport
ExportFeatureValuesRequest.SnapshotExport.Builder
Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time].
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesRequest.SnapshotExport
ExportFeatureValuesResponse
Response message for FeaturestoreService.ExportFeatureValues.
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesResponse
ExportFeatureValuesResponse.Builder
Response message for FeaturestoreService.ExportFeatureValues.
Protobuf type google.cloud.aiplatform.v1.ExportFeatureValuesResponse
ExportFractionSplit
Assigns the input data to training, validation, and test sets as per the
given fractions. Any of training_fraction, validation_fraction and
test_fraction may optionally be provided, they must sum to up to 1. If the
provided ones sum to less than 1, the remainder is assigned to sets as
decided by Vertex AI. If none of the fractions are set, by default roughly
80% of data is used for training, 10% for validation, and 10% for test.
Protobuf type google.cloud.aiplatform.v1.ExportFractionSplit
ExportFractionSplit.Builder
Assigns the input data to training, validation, and test sets as per the
given fractions. Any of training_fraction, validation_fraction and
test_fraction may optionally be provided, they must sum to up to 1. If the
provided ones sum to less than 1, the remainder is assigned to sets as
decided by Vertex AI. If none of the fractions are set, by default roughly
80% of data is used for training, 10% for validation, and 10% for test.
Protobuf type google.cloud.aiplatform.v1.ExportFractionSplit
ExportModelOperationMetadata
Details of ModelService.ExportModel operation.
Protobuf type google.cloud.aiplatform.v1.ExportModelOperationMetadata
ExportModelOperationMetadata.Builder
Details of ModelService.ExportModel operation.
Protobuf type google.cloud.aiplatform.v1.ExportModelOperationMetadata
ExportModelOperationMetadata.OutputInfo
Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig.
Protobuf type google.cloud.aiplatform.v1.ExportModelOperationMetadata.OutputInfo
ExportModelOperationMetadata.OutputInfo.Builder
Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig.
Protobuf type google.cloud.aiplatform.v1.ExportModelOperationMetadata.OutputInfo
ExportModelRequest
Request message for ModelService.ExportModel.
Protobuf type google.cloud.aiplatform.v1.ExportModelRequest
ExportModelRequest.Builder
Request message for ModelService.ExportModel.
Protobuf type google.cloud.aiplatform.v1.ExportModelRequest
ExportModelRequest.OutputConfig
Output configuration for the Model export.
Protobuf type google.cloud.aiplatform.v1.ExportModelRequest.OutputConfig
ExportModelRequest.OutputConfig.Builder
Output configuration for the Model export.
Protobuf type google.cloud.aiplatform.v1.ExportModelRequest.OutputConfig
ExportModelResponse
Response message of ModelService.ExportModel operation.
Protobuf type google.cloud.aiplatform.v1.ExportModelResponse
ExportModelResponse.Builder
Response message of ModelService.ExportModel operation.
Protobuf type google.cloud.aiplatform.v1.ExportModelResponse
ExportTensorboardTimeSeriesDataRequest
Request message for TensorboardService.ExportTensorboardTimeSeriesData.
Protobuf type google.cloud.aiplatform.v1.ExportTensorboardTimeSeriesDataRequest
ExportTensorboardTimeSeriesDataRequest.Builder
Request message for TensorboardService.ExportTensorboardTimeSeriesData.
Protobuf type google.cloud.aiplatform.v1.ExportTensorboardTimeSeriesDataRequest
ExportTensorboardTimeSeriesDataResponse
Response message for TensorboardService.ExportTensorboardTimeSeriesData.
Protobuf type google.cloud.aiplatform.v1.ExportTensorboardTimeSeriesDataResponse
ExportTensorboardTimeSeriesDataResponse.Builder
Response message for TensorboardService.ExportTensorboardTimeSeriesData.
Protobuf type google.cloud.aiplatform.v1.ExportTensorboardTimeSeriesDataResponse
Feature
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.
Protobuf type google.cloud.aiplatform.v1.Feature
Feature.Builder
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.
Protobuf type google.cloud.aiplatform.v1.Feature
Feature.MonitoringStatsAnomaly
A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.
Protobuf type google.cloud.aiplatform.v1.Feature.MonitoringStatsAnomaly
Feature.MonitoringStatsAnomaly.Builder
A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending.
Protobuf type google.cloud.aiplatform.v1.Feature.MonitoringStatsAnomaly
FeatureMonitoringStatsProto
FeatureName
FeatureName.Builder
Builder for projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}.
FeatureNoiseSigma
Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.
Protobuf type google.cloud.aiplatform.v1.FeatureNoiseSigma
FeatureNoiseSigma.Builder
Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.
Protobuf type google.cloud.aiplatform.v1.FeatureNoiseSigma
FeatureNoiseSigma.NoiseSigmaForFeature
Noise sigma for a single feature.
Protobuf type google.cloud.aiplatform.v1.FeatureNoiseSigma.NoiseSigmaForFeature
FeatureNoiseSigma.NoiseSigmaForFeature.Builder
Noise sigma for a single feature.
Protobuf type google.cloud.aiplatform.v1.FeatureNoiseSigma.NoiseSigmaForFeature
FeatureProto
FeatureSelector
Selector for Features of an EntityType.
Protobuf type google.cloud.aiplatform.v1.FeatureSelector
FeatureSelector.Builder
Selector for Features of an EntityType.
Protobuf type google.cloud.aiplatform.v1.FeatureSelector
FeatureSelectorProto
FeatureStatsAnomaly
Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.
Protobuf type google.cloud.aiplatform.v1.FeatureStatsAnomaly
FeatureStatsAnomaly.Builder
Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.
Protobuf type google.cloud.aiplatform.v1.FeatureStatsAnomaly
FeatureValue
Value for a feature.
Protobuf type google.cloud.aiplatform.v1.FeatureValue
FeatureValue.Builder
Value for a feature.
Protobuf type google.cloud.aiplatform.v1.FeatureValue
FeatureValue.Metadata
Metadata of feature value.
Protobuf type google.cloud.aiplatform.v1.FeatureValue.Metadata
FeatureValue.Metadata.Builder
Metadata of feature value.
Protobuf type google.cloud.aiplatform.v1.FeatureValue.Metadata
FeatureValueDestination
A destination location for Feature values and format.
Protobuf type google.cloud.aiplatform.v1.FeatureValueDestination
FeatureValueDestination.Builder
A destination location for Feature values and format.
Protobuf type google.cloud.aiplatform.v1.FeatureValueDestination
FeatureValueList
Container for list of values.
Protobuf type google.cloud.aiplatform.v1.FeatureValueList
FeatureValueList.Builder
Container for list of values.
Protobuf type google.cloud.aiplatform.v1.FeatureValueList
Featurestore
Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.
Protobuf type google.cloud.aiplatform.v1.Featurestore
Featurestore.Builder
Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.
Protobuf type google.cloud.aiplatform.v1.Featurestore
Featurestore.OnlineServingConfig
OnlineServingConfig specifies the details for provisioning online serving resources.
Protobuf type google.cloud.aiplatform.v1.Featurestore.OnlineServingConfig
Featurestore.OnlineServingConfig.Builder
OnlineServingConfig specifies the details for provisioning online serving resources.
Protobuf type google.cloud.aiplatform.v1.Featurestore.OnlineServingConfig
Featurestore.OnlineServingConfig.Scaling
Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).
Protobuf type google.cloud.aiplatform.v1.Featurestore.OnlineServingConfig.Scaling
Featurestore.OnlineServingConfig.Scaling.Builder
Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling).
Protobuf type google.cloud.aiplatform.v1.Featurestore.OnlineServingConfig.Scaling
FeaturestoreMonitoringConfig
Configuration of how features in Featurestore are monitored.
Protobuf type google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig
FeaturestoreMonitoringConfig.Builder
Configuration of how features in Featurestore are monitored.
Protobuf type google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig
FeaturestoreMonitoringConfig.ImportFeaturesAnalysis
Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.
Protobuf type
google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.ImportFeaturesAnalysis
FeaturestoreMonitoringConfig.ImportFeaturesAnalysis.Builder
Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation.
Protobuf type
google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.ImportFeaturesAnalysis
FeaturestoreMonitoringConfig.SnapshotAnalysis
Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.
Protobuf type google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.SnapshotAnalysis
FeaturestoreMonitoringConfig.SnapshotAnalysis.Builder
Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval.
Protobuf type
google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.SnapshotAnalysis
FeaturestoreMonitoringConfig.ThresholdConfig
The config for Featurestore Monitoring threshold.
Protobuf type google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.ThresholdConfig
FeaturestoreMonitoringConfig.ThresholdConfig.Builder
The config for Featurestore Monitoring threshold.
Protobuf type google.cloud.aiplatform.v1.FeaturestoreMonitoringConfig.ThresholdConfig
FeaturestoreMonitoringProto
FeaturestoreName
FeaturestoreName.Builder
Builder for projects/{project}/locations/{location}/featurestores/{featurestore}.
FeaturestoreOnlineServiceProto
FeaturestoreOnlineServingServiceClient
Service Description: A service for serving online feature values.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the FeaturestoreOnlineServingServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of FeaturestoreOnlineServingServiceSettings to create(). For example:
To customize credentials:
// 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
FeaturestoreOnlineServingServiceSettings featurestoreOnlineServingServiceSettings =
FeaturestoreOnlineServingServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
FeaturestoreOnlineServingServiceClient featurestoreOnlineServingServiceClient =
FeaturestoreOnlineServingServiceClient.create(featurestoreOnlineServingServiceSettings);
To customize the endpoint:
// 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
FeaturestoreOnlineServingServiceSettings featurestoreOnlineServingServiceSettings =
FeaturestoreOnlineServingServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
FeaturestoreOnlineServingServiceClient featurestoreOnlineServingServiceClient =
FeaturestoreOnlineServingServiceClient.create(featurestoreOnlineServingServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
FeaturestoreOnlineServingServiceClient.ListLocationsFixedSizeCollection
FeaturestoreOnlineServingServiceClient.ListLocationsPage
FeaturestoreOnlineServingServiceClient.ListLocationsPagedResponse
FeaturestoreOnlineServingServiceGrpc
A service for serving online feature values.
FeaturestoreOnlineServingServiceGrpc.FeaturestoreOnlineServingServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service FeaturestoreOnlineServingService.
A service for serving online feature values.
FeaturestoreOnlineServingServiceGrpc.FeaturestoreOnlineServingServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service FeaturestoreOnlineServingService.
A service for serving online feature values.
FeaturestoreOnlineServingServiceGrpc.FeaturestoreOnlineServingServiceImplBase
Base class for the server implementation of the service FeaturestoreOnlineServingService.
A service for serving online feature values.
FeaturestoreOnlineServingServiceGrpc.FeaturestoreOnlineServingServiceStub
A stub to allow clients to do asynchronous rpc calls to service FeaturestoreOnlineServingService.
A service for serving online feature values.
FeaturestoreOnlineServingServiceSettings
Settings class to configure an instance of FeaturestoreOnlineServingServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of readFeatureValues to 30 seconds:
// 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
FeaturestoreOnlineServingServiceSettings.Builder
featurestoreOnlineServingServiceSettingsBuilder =
FeaturestoreOnlineServingServiceSettings.newBuilder();
featurestoreOnlineServingServiceSettingsBuilder
.readFeatureValuesSettings()
.setRetrySettings(
featurestoreOnlineServingServiceSettingsBuilder
.readFeatureValuesSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
FeaturestoreOnlineServingServiceSettings featurestoreOnlineServingServiceSettings =
featurestoreOnlineServingServiceSettingsBuilder.build();
FeaturestoreOnlineServingServiceSettings.Builder
Builder for FeaturestoreOnlineServingServiceSettings.
FeaturestoreProto
FeaturestoreServiceClient
Service Description: The service that handles CRUD and List for resources for Featurestore.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the FeaturestoreServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of FeaturestoreServiceSettings to create(). For example:
To customize credentials:
// 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
FeaturestoreServiceSettings featurestoreServiceSettings =
FeaturestoreServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
FeaturestoreServiceClient featurestoreServiceClient =
FeaturestoreServiceClient.create(featurestoreServiceSettings);
To customize the endpoint:
// 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
FeaturestoreServiceSettings featurestoreServiceSettings =
FeaturestoreServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
FeaturestoreServiceClient featurestoreServiceClient =
FeaturestoreServiceClient.create(featurestoreServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
FeaturestoreServiceClient.ListEntityTypesFixedSizeCollection
FeaturestoreServiceClient.ListEntityTypesPage
FeaturestoreServiceClient.ListEntityTypesPagedResponse
FeaturestoreServiceClient.ListFeaturesFixedSizeCollection
FeaturestoreServiceClient.ListFeaturesPage
FeaturestoreServiceClient.ListFeaturesPagedResponse
FeaturestoreServiceClient.ListFeaturestoresFixedSizeCollection
FeaturestoreServiceClient.ListFeaturestoresPage
FeaturestoreServiceClient.ListFeaturestoresPagedResponse
FeaturestoreServiceClient.ListLocationsFixedSizeCollection
FeaturestoreServiceClient.ListLocationsPage
FeaturestoreServiceClient.ListLocationsPagedResponse
FeaturestoreServiceClient.SearchFeaturesFixedSizeCollection
FeaturestoreServiceClient.SearchFeaturesPage
FeaturestoreServiceClient.SearchFeaturesPagedResponse
FeaturestoreServiceGrpc
The service that handles CRUD and List for resources for Featurestore.
FeaturestoreServiceGrpc.FeaturestoreServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service FeaturestoreService.
The service that handles CRUD and List for resources for Featurestore.
FeaturestoreServiceGrpc.FeaturestoreServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service FeaturestoreService.
The service that handles CRUD and List for resources for Featurestore.
FeaturestoreServiceGrpc.FeaturestoreServiceImplBase
Base class for the server implementation of the service FeaturestoreService.
The service that handles CRUD and List for resources for Featurestore.
FeaturestoreServiceGrpc.FeaturestoreServiceStub
A stub to allow clients to do asynchronous rpc calls to service FeaturestoreService.
The service that handles CRUD and List for resources for Featurestore.
FeaturestoreServiceProto
FeaturestoreServiceSettings
Settings class to configure an instance of FeaturestoreServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of getFeaturestore to 30 seconds:
// 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
FeaturestoreServiceSettings.Builder featurestoreServiceSettingsBuilder =
FeaturestoreServiceSettings.newBuilder();
featurestoreServiceSettingsBuilder
.getFeaturestoreSettings()
.setRetrySettings(
featurestoreServiceSettingsBuilder
.getFeaturestoreSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
FeaturestoreServiceSettings featurestoreServiceSettings =
featurestoreServiceSettingsBuilder.build();
FeaturestoreServiceSettings.Builder
Builder for FeaturestoreServiceSettings.
FilterSplit
Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign).
Supported only for unstructured Datasets.
Protobuf type google.cloud.aiplatform.v1.FilterSplit
FilterSplit.Builder
Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign).
Supported only for unstructured Datasets.
Protobuf type google.cloud.aiplatform.v1.FilterSplit
FindNeighborsRequest
The request message for MatchService.FindNeighbors.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsRequest
FindNeighborsRequest.Builder
The request message for MatchService.FindNeighbors.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsRequest
FindNeighborsRequest.Query
A query to find a number of the nearest neighbors (most similar vectors) of a vector.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsRequest.Query
FindNeighborsRequest.Query.Builder
A query to find a number of the nearest neighbors (most similar vectors) of a vector.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsRequest.Query
FindNeighborsResponse
The response message for MatchService.FindNeighbors.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsResponse
FindNeighborsResponse.Builder
The response message for MatchService.FindNeighbors.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsResponse
FindNeighborsResponse.NearestNeighbors
Nearest neighbors for one query.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsResponse.NearestNeighbors
FindNeighborsResponse.NearestNeighbors.Builder
Nearest neighbors for one query.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsResponse.NearestNeighbors
FindNeighborsResponse.Neighbor
A neighbor of the query vector.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsResponse.Neighbor
FindNeighborsResponse.Neighbor.Builder
A neighbor of the query vector.
Protobuf type google.cloud.aiplatform.v1.FindNeighborsResponse.Neighbor
FractionSplit
Assigns the input data to training, validation, and test sets as per the
given fractions. Any of training_fraction, validation_fraction and
test_fraction may optionally be provided, they must sum to up to 1. If the
provided ones sum to less than 1, the remainder is assigned to sets as
decided by Vertex AI. If none of the fractions are set, by default roughly
80% of data is used for training, 10% for validation, and 10% for test.
Protobuf type google.cloud.aiplatform.v1.FractionSplit
FractionSplit.Builder
Assigns the input data to training, validation, and test sets as per the
given fractions. Any of training_fraction, validation_fraction and
test_fraction may optionally be provided, they must sum to up to 1. If the
provided ones sum to less than 1, the remainder is assigned to sets as
decided by Vertex AI. If none of the fractions are set, by default roughly
80% of data is used for training, 10% for validation, and 10% for test.
Protobuf type google.cloud.aiplatform.v1.FractionSplit
GcsDestination
The Google Cloud Storage location where the output is to be written to.
Protobuf type google.cloud.aiplatform.v1.GcsDestination
GcsDestination.Builder
The Google Cloud Storage location where the output is to be written to.
Protobuf type google.cloud.aiplatform.v1.GcsDestination
GcsSource
The Google Cloud Storage location for the input content.
Protobuf type google.cloud.aiplatform.v1.GcsSource
GcsSource.Builder
The Google Cloud Storage location for the input content.
Protobuf type google.cloud.aiplatform.v1.GcsSource
GenericOperationMetadata
Generic Metadata shared by all operations.
Protobuf type google.cloud.aiplatform.v1.GenericOperationMetadata
GenericOperationMetadata.Builder
Generic Metadata shared by all operations.
Protobuf type google.cloud.aiplatform.v1.GenericOperationMetadata
GetAnnotationSpecRequest
Request message for DatasetService.GetAnnotationSpec.
Protobuf type google.cloud.aiplatform.v1.GetAnnotationSpecRequest
GetAnnotationSpecRequest.Builder
Request message for DatasetService.GetAnnotationSpec.
Protobuf type google.cloud.aiplatform.v1.GetAnnotationSpecRequest
GetArtifactRequest
Request message for MetadataService.GetArtifact.
Protobuf type google.cloud.aiplatform.v1.GetArtifactRequest
GetArtifactRequest.Builder
Request message for MetadataService.GetArtifact.
Protobuf type google.cloud.aiplatform.v1.GetArtifactRequest
GetBatchPredictionJobRequest
Request message for JobService.GetBatchPredictionJob.
Protobuf type google.cloud.aiplatform.v1.GetBatchPredictionJobRequest
GetBatchPredictionJobRequest.Builder
Request message for JobService.GetBatchPredictionJob.
Protobuf type google.cloud.aiplatform.v1.GetBatchPredictionJobRequest
GetContextRequest
Request message for MetadataService.GetContext.
Protobuf type google.cloud.aiplatform.v1.GetContextRequest
GetContextRequest.Builder
Request message for MetadataService.GetContext.
Protobuf type google.cloud.aiplatform.v1.GetContextRequest
GetCustomJobRequest
Request message for JobService.GetCustomJob.
Protobuf type google.cloud.aiplatform.v1.GetCustomJobRequest
GetCustomJobRequest.Builder
Request message for JobService.GetCustomJob.
Protobuf type google.cloud.aiplatform.v1.GetCustomJobRequest
GetDataLabelingJobRequest
Request message for JobService.GetDataLabelingJob.
Protobuf type google.cloud.aiplatform.v1.GetDataLabelingJobRequest
GetDataLabelingJobRequest.Builder
Request message for JobService.GetDataLabelingJob.
Protobuf type google.cloud.aiplatform.v1.GetDataLabelingJobRequest
GetDatasetRequest
Request message for DatasetService.GetDataset.
Protobuf type google.cloud.aiplatform.v1.GetDatasetRequest
GetDatasetRequest.Builder
Request message for DatasetService.GetDataset.
Protobuf type google.cloud.aiplatform.v1.GetDatasetRequest
GetEndpointRequest
Request message for EndpointService.GetEndpoint
Protobuf type google.cloud.aiplatform.v1.GetEndpointRequest
GetEndpointRequest.Builder
Request message for EndpointService.GetEndpoint
Protobuf type google.cloud.aiplatform.v1.GetEndpointRequest
GetEntityTypeRequest
Request message for FeaturestoreService.GetEntityType.
Protobuf type google.cloud.aiplatform.v1.GetEntityTypeRequest
GetEntityTypeRequest.Builder
Request message for FeaturestoreService.GetEntityType.
Protobuf type google.cloud.aiplatform.v1.GetEntityTypeRequest
GetExecutionRequest
Request message for MetadataService.GetExecution.
Protobuf type google.cloud.aiplatform.v1.GetExecutionRequest
GetExecutionRequest.Builder
Request message for MetadataService.GetExecution.
Protobuf type google.cloud.aiplatform.v1.GetExecutionRequest
GetFeatureRequest
Request message for FeaturestoreService.GetFeature.
Protobuf type google.cloud.aiplatform.v1.GetFeatureRequest
GetFeatureRequest.Builder
Request message for FeaturestoreService.GetFeature.
Protobuf type google.cloud.aiplatform.v1.GetFeatureRequest
GetFeaturestoreRequest
Request message for FeaturestoreService.GetFeaturestore.
Protobuf type google.cloud.aiplatform.v1.GetFeaturestoreRequest
GetFeaturestoreRequest.Builder
Request message for FeaturestoreService.GetFeaturestore.
Protobuf type google.cloud.aiplatform.v1.GetFeaturestoreRequest
GetHyperparameterTuningJobRequest
Request message for JobService.GetHyperparameterTuningJob.
Protobuf type google.cloud.aiplatform.v1.GetHyperparameterTuningJobRequest
GetHyperparameterTuningJobRequest.Builder
Request message for JobService.GetHyperparameterTuningJob.
Protobuf type google.cloud.aiplatform.v1.GetHyperparameterTuningJobRequest
GetIndexEndpointRequest
Request message for IndexEndpointService.GetIndexEndpoint
Protobuf type google.cloud.aiplatform.v1.GetIndexEndpointRequest
GetIndexEndpointRequest.Builder
Request message for IndexEndpointService.GetIndexEndpoint
Protobuf type google.cloud.aiplatform.v1.GetIndexEndpointRequest
GetIndexRequest
Request message for IndexService.GetIndex
Protobuf type google.cloud.aiplatform.v1.GetIndexRequest
GetIndexRequest.Builder
Request message for IndexService.GetIndex
Protobuf type google.cloud.aiplatform.v1.GetIndexRequest
GetMetadataSchemaRequest
Request message for MetadataService.GetMetadataSchema.
Protobuf type google.cloud.aiplatform.v1.GetMetadataSchemaRequest
GetMetadataSchemaRequest.Builder
Request message for MetadataService.GetMetadataSchema.
Protobuf type google.cloud.aiplatform.v1.GetMetadataSchemaRequest
GetMetadataStoreRequest
Request message for MetadataService.GetMetadataStore.
Protobuf type google.cloud.aiplatform.v1.GetMetadataStoreRequest
GetMetadataStoreRequest.Builder
Request message for MetadataService.GetMetadataStore.
Protobuf type google.cloud.aiplatform.v1.GetMetadataStoreRequest
GetModelDeploymentMonitoringJobRequest
Request message for JobService.GetModelDeploymentMonitoringJob.
Protobuf type google.cloud.aiplatform.v1.GetModelDeploymentMonitoringJobRequest
GetModelDeploymentMonitoringJobRequest.Builder
Request message for JobService.GetModelDeploymentMonitoringJob.
Protobuf type google.cloud.aiplatform.v1.GetModelDeploymentMonitoringJobRequest
GetModelEvaluationRequest
Request message for ModelService.GetModelEvaluation.
Protobuf type google.cloud.aiplatform.v1.GetModelEvaluationRequest
GetModelEvaluationRequest.Builder
Request message for ModelService.GetModelEvaluation.
Protobuf type google.cloud.aiplatform.v1.GetModelEvaluationRequest
GetModelEvaluationSliceRequest
Request message for ModelService.GetModelEvaluationSlice.
Protobuf type google.cloud.aiplatform.v1.GetModelEvaluationSliceRequest
GetModelEvaluationSliceRequest.Builder
Request message for ModelService.GetModelEvaluationSlice.
Protobuf type google.cloud.aiplatform.v1.GetModelEvaluationSliceRequest
GetModelRequest
Request message for ModelService.GetModel.
Protobuf type google.cloud.aiplatform.v1.GetModelRequest
GetModelRequest.Builder
Request message for ModelService.GetModel.
Protobuf type google.cloud.aiplatform.v1.GetModelRequest
GetNasJobRequest
Request message for JobService.GetNasJob.
Protobuf type google.cloud.aiplatform.v1.GetNasJobRequest
GetNasJobRequest.Builder
Request message for JobService.GetNasJob.
Protobuf type google.cloud.aiplatform.v1.GetNasJobRequest
GetNasTrialDetailRequest
Request message for JobService.GetNasTrialDetail.
Protobuf type google.cloud.aiplatform.v1.GetNasTrialDetailRequest
GetNasTrialDetailRequest.Builder
Request message for JobService.GetNasTrialDetail.
Protobuf type google.cloud.aiplatform.v1.GetNasTrialDetailRequest
GetPipelineJobRequest
Request message for PipelineService.GetPipelineJob.
Protobuf type google.cloud.aiplatform.v1.GetPipelineJobRequest
GetPipelineJobRequest.Builder
Request message for PipelineService.GetPipelineJob.
Protobuf type google.cloud.aiplatform.v1.GetPipelineJobRequest
GetPublisherModelRequest
Request message for ModelGardenService.GetPublisherModel
Protobuf type google.cloud.aiplatform.v1.GetPublisherModelRequest
GetPublisherModelRequest.Builder
Request message for ModelGardenService.GetPublisherModel
Protobuf type google.cloud.aiplatform.v1.GetPublisherModelRequest
GetScheduleRequest
Request message for ScheduleService.GetSchedule.
Protobuf type google.cloud.aiplatform.v1.GetScheduleRequest
GetScheduleRequest.Builder
Request message for ScheduleService.GetSchedule.
Protobuf type google.cloud.aiplatform.v1.GetScheduleRequest
GetSpecialistPoolRequest
Request message for SpecialistPoolService.GetSpecialistPool.
Protobuf type google.cloud.aiplatform.v1.GetSpecialistPoolRequest
GetSpecialistPoolRequest.Builder
Request message for SpecialistPoolService.GetSpecialistPool.
Protobuf type google.cloud.aiplatform.v1.GetSpecialistPoolRequest
GetStudyRequest
Request message for VizierService.GetStudy.
Protobuf type google.cloud.aiplatform.v1.GetStudyRequest
GetStudyRequest.Builder
Request message for VizierService.GetStudy.
Protobuf type google.cloud.aiplatform.v1.GetStudyRequest
GetTensorboardExperimentRequest
Request message for TensorboardService.GetTensorboardExperiment.
Protobuf type google.cloud.aiplatform.v1.GetTensorboardExperimentRequest
GetTensorboardExperimentRequest.Builder
Request message for TensorboardService.GetTensorboardExperiment.
Protobuf type google.cloud.aiplatform.v1.GetTensorboardExperimentRequest
GetTensorboardRequest
Request message for TensorboardService.GetTensorboard.
Protobuf type google.cloud.aiplatform.v1.GetTensorboardRequest
GetTensorboardRequest.Builder
Request message for TensorboardService.GetTensorboard.
Protobuf type google.cloud.aiplatform.v1.GetTensorboardRequest
GetTensorboardRunRequest
Request message for TensorboardService.GetTensorboardRun.
Protobuf type google.cloud.aiplatform.v1.GetTensorboardRunRequest
GetTensorboardRunRequest.Builder
Request message for TensorboardService.GetTensorboardRun.
Protobuf type google.cloud.aiplatform.v1.GetTensorboardRunRequest
GetTensorboardTimeSeriesRequest
Request message for TensorboardService.GetTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.GetTensorboardTimeSeriesRequest
GetTensorboardTimeSeriesRequest.Builder
Request message for TensorboardService.GetTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.GetTensorboardTimeSeriesRequest
GetTrainingPipelineRequest
Request message for PipelineService.GetTrainingPipeline.
Protobuf type google.cloud.aiplatform.v1.GetTrainingPipelineRequest
GetTrainingPipelineRequest.Builder
Request message for PipelineService.GetTrainingPipeline.
Protobuf type google.cloud.aiplatform.v1.GetTrainingPipelineRequest
GetTrialRequest
Request message for VizierService.GetTrial.
Protobuf type google.cloud.aiplatform.v1.GetTrialRequest
GetTrialRequest.Builder
Request message for VizierService.GetTrial.
Protobuf type google.cloud.aiplatform.v1.GetTrialRequest
HyperparameterTuningJob
Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.
Protobuf type google.cloud.aiplatform.v1.HyperparameterTuningJob
HyperparameterTuningJob.Builder
Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.
Protobuf type google.cloud.aiplatform.v1.HyperparameterTuningJob
HyperparameterTuningJobName
HyperparameterTuningJobName.Builder
Builder for projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}.
HyperparameterTuningJobProto
IdMatcher
Matcher for Features of an EntityType by Feature ID.
Protobuf type google.cloud.aiplatform.v1.IdMatcher
IdMatcher.Builder
Matcher for Features of an EntityType by Feature ID.
Protobuf type google.cloud.aiplatform.v1.IdMatcher
ImportDataConfig
Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.
Protobuf type google.cloud.aiplatform.v1.ImportDataConfig
ImportDataConfig.Builder
Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.
Protobuf type google.cloud.aiplatform.v1.ImportDataConfig
ImportDataOperationMetadata
Runtime operation information for DatasetService.ImportData.
Protobuf type google.cloud.aiplatform.v1.ImportDataOperationMetadata
ImportDataOperationMetadata.Builder
Runtime operation information for DatasetService.ImportData.
Protobuf type google.cloud.aiplatform.v1.ImportDataOperationMetadata
ImportDataRequest
Request message for DatasetService.ImportData.
Protobuf type google.cloud.aiplatform.v1.ImportDataRequest
ImportDataRequest.Builder
Request message for DatasetService.ImportData.
Protobuf type google.cloud.aiplatform.v1.ImportDataRequest
ImportDataResponse
Response message for DatasetService.ImportData.
Protobuf type google.cloud.aiplatform.v1.ImportDataResponse
ImportDataResponse.Builder
Response message for DatasetService.ImportData.
Protobuf type google.cloud.aiplatform.v1.ImportDataResponse
ImportFeatureValuesOperationMetadata
Details of operations that perform import Feature values.
Protobuf type google.cloud.aiplatform.v1.ImportFeatureValuesOperationMetadata
ImportFeatureValuesOperationMetadata.Builder
Details of operations that perform import Feature values.
Protobuf type google.cloud.aiplatform.v1.ImportFeatureValuesOperationMetadata
ImportFeatureValuesRequest
Request message for FeaturestoreService.ImportFeatureValues.
Protobuf type google.cloud.aiplatform.v1.ImportFeatureValuesRequest
ImportFeatureValuesRequest.Builder
Request message for FeaturestoreService.ImportFeatureValues.
Protobuf type google.cloud.aiplatform.v1.ImportFeatureValuesRequest
ImportFeatureValuesRequest.FeatureSpec
Defines the Feature value(s) to import.
Protobuf type google.cloud.aiplatform.v1.ImportFeatureValuesRequest.FeatureSpec
ImportFeatureValuesRequest.FeatureSpec.Builder
Defines the Feature value(s) to import.
Protobuf type google.cloud.aiplatform.v1.ImportFeatureValuesRequest.FeatureSpec
ImportFeatureValuesResponse
Response message for FeaturestoreService.ImportFeatureValues.
Protobuf type google.cloud.aiplatform.v1.ImportFeatureValuesResponse
ImportFeatureValuesResponse.Builder
Response message for FeaturestoreService.ImportFeatureValues.
Protobuf type google.cloud.aiplatform.v1.ImportFeatureValuesResponse
ImportModelEvaluationRequest
Request message for ModelService.ImportModelEvaluation
Protobuf type google.cloud.aiplatform.v1.ImportModelEvaluationRequest
ImportModelEvaluationRequest.Builder
Request message for ModelService.ImportModelEvaluation
Protobuf type google.cloud.aiplatform.v1.ImportModelEvaluationRequest
Index
A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.
Protobuf type google.cloud.aiplatform.v1.Index
Index.Builder
A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.
Protobuf type google.cloud.aiplatform.v1.Index
IndexDatapoint
A datapoint of Index.
Protobuf type google.cloud.aiplatform.v1.IndexDatapoint
IndexDatapoint.Builder
A datapoint of Index.
Protobuf type google.cloud.aiplatform.v1.IndexDatapoint
IndexDatapoint.CrowdingTag
Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute.
Protobuf type google.cloud.aiplatform.v1.IndexDatapoint.CrowdingTag
IndexDatapoint.CrowdingTag.Builder
Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute.
Protobuf type google.cloud.aiplatform.v1.IndexDatapoint.CrowdingTag
IndexDatapoint.Restriction
Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces).
Protobuf type google.cloud.aiplatform.v1.IndexDatapoint.Restriction
IndexDatapoint.Restriction.Builder
Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces).
Protobuf type google.cloud.aiplatform.v1.IndexDatapoint.Restriction
IndexEndpoint
Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.
Protobuf type google.cloud.aiplatform.v1.IndexEndpoint
IndexEndpoint.Builder
Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.
Protobuf type google.cloud.aiplatform.v1.IndexEndpoint
IndexEndpointName
IndexEndpointName.Builder
Builder for projects/{project}/locations/{location}/indexEndpoints/{index_endpoint}.
IndexEndpointProto
IndexEndpointServiceClient
Service Description: A service for managing Vertex AI's IndexEndpoints.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the IndexEndpointServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of IndexEndpointServiceSettings to create(). For example:
To customize credentials:
// 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
IndexEndpointServiceSettings indexEndpointServiceSettings =
IndexEndpointServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
IndexEndpointServiceClient indexEndpointServiceClient =
IndexEndpointServiceClient.create(indexEndpointServiceSettings);
To customize the endpoint:
// 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
IndexEndpointServiceSettings indexEndpointServiceSettings =
IndexEndpointServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
IndexEndpointServiceClient indexEndpointServiceClient =
IndexEndpointServiceClient.create(indexEndpointServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
IndexEndpointServiceClient.ListIndexEndpointsFixedSizeCollection
IndexEndpointServiceClient.ListIndexEndpointsPage
IndexEndpointServiceClient.ListIndexEndpointsPagedResponse
IndexEndpointServiceClient.ListLocationsFixedSizeCollection
IndexEndpointServiceClient.ListLocationsPage
IndexEndpointServiceClient.ListLocationsPagedResponse
IndexEndpointServiceGrpc
A service for managing Vertex AI's IndexEndpoints.
IndexEndpointServiceGrpc.IndexEndpointServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service IndexEndpointService.
A service for managing Vertex AI's IndexEndpoints.
IndexEndpointServiceGrpc.IndexEndpointServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service IndexEndpointService.
A service for managing Vertex AI's IndexEndpoints.
IndexEndpointServiceGrpc.IndexEndpointServiceImplBase
Base class for the server implementation of the service IndexEndpointService.
A service for managing Vertex AI's IndexEndpoints.
IndexEndpointServiceGrpc.IndexEndpointServiceStub
A stub to allow clients to do asynchronous rpc calls to service IndexEndpointService.
A service for managing Vertex AI's IndexEndpoints.
IndexEndpointServiceProto
IndexEndpointServiceSettings
Settings class to configure an instance of IndexEndpointServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of getIndexEndpoint to 30 seconds:
// 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
IndexEndpointServiceSettings.Builder indexEndpointServiceSettingsBuilder =
IndexEndpointServiceSettings.newBuilder();
indexEndpointServiceSettingsBuilder
.getIndexEndpointSettings()
.setRetrySettings(
indexEndpointServiceSettingsBuilder
.getIndexEndpointSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
IndexEndpointServiceSettings indexEndpointServiceSettings =
indexEndpointServiceSettingsBuilder.build();
IndexEndpointServiceSettings.Builder
Builder for IndexEndpointServiceSettings.
IndexName
IndexName.Builder
Builder for projects/{project}/locations/{location}/indexes/{index}.
IndexPrivateEndpoints
IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.
Protobuf type google.cloud.aiplatform.v1.IndexPrivateEndpoints
IndexPrivateEndpoints.Builder
IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.
Protobuf type google.cloud.aiplatform.v1.IndexPrivateEndpoints
IndexProto
IndexServiceClient
Service Description: A service for creating and managing Vertex AI's Index resources.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the IndexServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of IndexServiceSettings to create(). For example:
To customize credentials:
// 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
IndexServiceSettings indexServiceSettings =
IndexServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
IndexServiceClient indexServiceClient = IndexServiceClient.create(indexServiceSettings);
To customize the endpoint:
// 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
IndexServiceSettings indexServiceSettings =
IndexServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
IndexServiceClient indexServiceClient = IndexServiceClient.create(indexServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
IndexServiceClient.ListIndexesFixedSizeCollection
IndexServiceClient.ListIndexesPage
IndexServiceClient.ListIndexesPagedResponse
IndexServiceClient.ListLocationsFixedSizeCollection
IndexServiceClient.ListLocationsPage
IndexServiceClient.ListLocationsPagedResponse
IndexServiceGrpc
A service for creating and managing Vertex AI's Index resources.
IndexServiceGrpc.IndexServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service IndexService.
A service for creating and managing Vertex AI's Index resources.
IndexServiceGrpc.IndexServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service IndexService.
A service for creating and managing Vertex AI's Index resources.
IndexServiceGrpc.IndexServiceImplBase
Base class for the server implementation of the service IndexService.
A service for creating and managing Vertex AI's Index resources.
IndexServiceGrpc.IndexServiceStub
A stub to allow clients to do asynchronous rpc calls to service IndexService.
A service for creating and managing Vertex AI's Index resources.
IndexServiceProto
IndexServiceSettings
Settings class to configure an instance of IndexServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of getIndex to 30 seconds:
// 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
IndexServiceSettings.Builder indexServiceSettingsBuilder = IndexServiceSettings.newBuilder();
indexServiceSettingsBuilder
.getIndexSettings()
.setRetrySettings(
indexServiceSettingsBuilder
.getIndexSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
IndexServiceSettings indexServiceSettings = indexServiceSettingsBuilder.build();
IndexServiceSettings.Builder
Builder for IndexServiceSettings.
IndexStats
Stats of the Index.
Protobuf type google.cloud.aiplatform.v1.IndexStats
IndexStats.Builder
Stats of the Index.
Protobuf type google.cloud.aiplatform.v1.IndexStats
InputDataConfig
Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.
Protobuf type google.cloud.aiplatform.v1.InputDataConfig
InputDataConfig.Builder
Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.
Protobuf type google.cloud.aiplatform.v1.InputDataConfig
Int64Array
A list of int64 values.
Protobuf type google.cloud.aiplatform.v1.Int64Array
Int64Array.Builder
A list of int64 values.
Protobuf type google.cloud.aiplatform.v1.Int64Array
IntegratedGradientsAttribution
An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
Protobuf type google.cloud.aiplatform.v1.IntegratedGradientsAttribution
IntegratedGradientsAttribution.Builder
An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
Protobuf type google.cloud.aiplatform.v1.IntegratedGradientsAttribution
IoProto
JobServiceClient
Service Description: A service for creating and managing Vertex AI's jobs.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the JobServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of JobServiceSettings to create(). For example:
To customize credentials:
// 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
JobServiceSettings jobServiceSettings =
JobServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
JobServiceClient jobServiceClient = JobServiceClient.create(jobServiceSettings);
To customize the endpoint:
// 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
JobServiceSettings jobServiceSettings =
JobServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
JobServiceClient jobServiceClient = JobServiceClient.create(jobServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
JobServiceClient.ListBatchPredictionJobsFixedSizeCollection
JobServiceClient.ListBatchPredictionJobsPage
JobServiceClient.ListBatchPredictionJobsPagedResponse
JobServiceClient.ListCustomJobsFixedSizeCollection
JobServiceClient.ListCustomJobsPage
JobServiceClient.ListCustomJobsPagedResponse
JobServiceClient.ListDataLabelingJobsFixedSizeCollection
JobServiceClient.ListDataLabelingJobsPage
JobServiceClient.ListDataLabelingJobsPagedResponse
JobServiceClient.ListHyperparameterTuningJobsFixedSizeCollection
JobServiceClient.ListHyperparameterTuningJobsPage
JobServiceClient.ListHyperparameterTuningJobsPagedResponse
JobServiceClient.ListLocationsFixedSizeCollection
JobServiceClient.ListLocationsPage
JobServiceClient.ListLocationsPagedResponse
JobServiceClient.ListModelDeploymentMonitoringJobsFixedSizeCollection
JobServiceClient.ListModelDeploymentMonitoringJobsPage
JobServiceClient.ListModelDeploymentMonitoringJobsPagedResponse
JobServiceClient.ListNasJobsFixedSizeCollection
JobServiceClient.ListNasJobsPage
JobServiceClient.ListNasJobsPagedResponse
JobServiceClient.ListNasTrialDetailsFixedSizeCollection
JobServiceClient.ListNasTrialDetailsPage
JobServiceClient.ListNasTrialDetailsPagedResponse
JobServiceClient.SearchModelDeploymentMonitoringStatsAnomaliesFixedSizeCollection
JobServiceClient.SearchModelDeploymentMonitoringStatsAnomaliesPage
JobServiceClient.SearchModelDeploymentMonitoringStatsAnomaliesPagedResponse
JobServiceGrpc
A service for creating and managing Vertex AI's jobs.
JobServiceGrpc.JobServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service JobService.
A service for creating and managing Vertex AI's jobs.
JobServiceGrpc.JobServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service JobService.
A service for creating and managing Vertex AI's jobs.
JobServiceGrpc.JobServiceImplBase
Base class for the server implementation of the service JobService.
A service for creating and managing Vertex AI's jobs.
JobServiceGrpc.JobServiceStub
A stub to allow clients to do asynchronous rpc calls to service JobService.
A service for creating and managing Vertex AI's jobs.
JobServiceProto
JobServiceSettings
Settings class to configure an instance of JobServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of createCustomJob to 30 seconds:
// 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
JobServiceSettings.Builder jobServiceSettingsBuilder = JobServiceSettings.newBuilder();
jobServiceSettingsBuilder
.createCustomJobSettings()
.setRetrySettings(
jobServiceSettingsBuilder
.createCustomJobSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
JobServiceSettings jobServiceSettings = jobServiceSettingsBuilder.build();
JobServiceSettings.Builder
Builder for JobServiceSettings.
JobStateProto
LargeModelReference
Contains information about the Large Model.
Protobuf type google.cloud.aiplatform.v1.LargeModelReference
LargeModelReference.Builder
Contains information about the Large Model.
Protobuf type google.cloud.aiplatform.v1.LargeModelReference
LineageSubgraph
A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.
Protobuf type google.cloud.aiplatform.v1.LineageSubgraph
LineageSubgraph.Builder
A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.
Protobuf type google.cloud.aiplatform.v1.LineageSubgraph
LineageSubgraphProto
ListAnnotationsRequest
Request message for DatasetService.ListAnnotations.
Protobuf type google.cloud.aiplatform.v1.ListAnnotationsRequest
ListAnnotationsRequest.Builder
Request message for DatasetService.ListAnnotations.
Protobuf type google.cloud.aiplatform.v1.ListAnnotationsRequest
ListAnnotationsResponse
Response message for DatasetService.ListAnnotations.
Protobuf type google.cloud.aiplatform.v1.ListAnnotationsResponse
ListAnnotationsResponse.Builder
Response message for DatasetService.ListAnnotations.
Protobuf type google.cloud.aiplatform.v1.ListAnnotationsResponse
ListArtifactsRequest
Request message for MetadataService.ListArtifacts.
Protobuf type google.cloud.aiplatform.v1.ListArtifactsRequest
ListArtifactsRequest.Builder
Request message for MetadataService.ListArtifacts.
Protobuf type google.cloud.aiplatform.v1.ListArtifactsRequest
ListArtifactsResponse
Response message for MetadataService.ListArtifacts.
Protobuf type google.cloud.aiplatform.v1.ListArtifactsResponse
ListArtifactsResponse.Builder
Response message for MetadataService.ListArtifacts.
Protobuf type google.cloud.aiplatform.v1.ListArtifactsResponse
ListBatchPredictionJobsRequest
Request message for JobService.ListBatchPredictionJobs.
Protobuf type google.cloud.aiplatform.v1.ListBatchPredictionJobsRequest
ListBatchPredictionJobsRequest.Builder
Request message for JobService.ListBatchPredictionJobs.
Protobuf type google.cloud.aiplatform.v1.ListBatchPredictionJobsRequest
ListBatchPredictionJobsResponse
Response message for JobService.ListBatchPredictionJobs
Protobuf type google.cloud.aiplatform.v1.ListBatchPredictionJobsResponse
ListBatchPredictionJobsResponse.Builder
Response message for JobService.ListBatchPredictionJobs
Protobuf type google.cloud.aiplatform.v1.ListBatchPredictionJobsResponse
ListContextsRequest
Request message for MetadataService.ListContexts
Protobuf type google.cloud.aiplatform.v1.ListContextsRequest
ListContextsRequest.Builder
Request message for MetadataService.ListContexts
Protobuf type google.cloud.aiplatform.v1.ListContextsRequest
ListContextsResponse
Response message for MetadataService.ListContexts.
Protobuf type google.cloud.aiplatform.v1.ListContextsResponse
ListContextsResponse.Builder
Response message for MetadataService.ListContexts.
Protobuf type google.cloud.aiplatform.v1.ListContextsResponse
ListCustomJobsRequest
Request message for JobService.ListCustomJobs.
Protobuf type google.cloud.aiplatform.v1.ListCustomJobsRequest
ListCustomJobsRequest.Builder
Request message for JobService.ListCustomJobs.
Protobuf type google.cloud.aiplatform.v1.ListCustomJobsRequest
ListCustomJobsResponse
Response message for JobService.ListCustomJobs
Protobuf type google.cloud.aiplatform.v1.ListCustomJobsResponse
ListCustomJobsResponse.Builder
Response message for JobService.ListCustomJobs
Protobuf type google.cloud.aiplatform.v1.ListCustomJobsResponse
ListDataItemsRequest
Request message for DatasetService.ListDataItems.
Protobuf type google.cloud.aiplatform.v1.ListDataItemsRequest
ListDataItemsRequest.Builder
Request message for DatasetService.ListDataItems.
Protobuf type google.cloud.aiplatform.v1.ListDataItemsRequest
ListDataItemsResponse
Response message for DatasetService.ListDataItems.
Protobuf type google.cloud.aiplatform.v1.ListDataItemsResponse
ListDataItemsResponse.Builder
Response message for DatasetService.ListDataItems.
Protobuf type google.cloud.aiplatform.v1.ListDataItemsResponse
ListDataLabelingJobsRequest
Request message for JobService.ListDataLabelingJobs.
Protobuf type google.cloud.aiplatform.v1.ListDataLabelingJobsRequest
ListDataLabelingJobsRequest.Builder
Request message for JobService.ListDataLabelingJobs.
Protobuf type google.cloud.aiplatform.v1.ListDataLabelingJobsRequest
ListDataLabelingJobsResponse
Response message for JobService.ListDataLabelingJobs.
Protobuf type google.cloud.aiplatform.v1.ListDataLabelingJobsResponse
ListDataLabelingJobsResponse.Builder
Response message for JobService.ListDataLabelingJobs.
Protobuf type google.cloud.aiplatform.v1.ListDataLabelingJobsResponse
ListDatasetsRequest
Request message for DatasetService.ListDatasets.
Protobuf type google.cloud.aiplatform.v1.ListDatasetsRequest
ListDatasetsRequest.Builder
Request message for DatasetService.ListDatasets.
Protobuf type google.cloud.aiplatform.v1.ListDatasetsRequest
ListDatasetsResponse
Response message for DatasetService.ListDatasets.
Protobuf type google.cloud.aiplatform.v1.ListDatasetsResponse
ListDatasetsResponse.Builder
Response message for DatasetService.ListDatasets.
Protobuf type google.cloud.aiplatform.v1.ListDatasetsResponse
ListEndpointsRequest
Request message for EndpointService.ListEndpoints.
Protobuf type google.cloud.aiplatform.v1.ListEndpointsRequest
ListEndpointsRequest.Builder
Request message for EndpointService.ListEndpoints.
Protobuf type google.cloud.aiplatform.v1.ListEndpointsRequest
ListEndpointsResponse
Response message for EndpointService.ListEndpoints.
Protobuf type google.cloud.aiplatform.v1.ListEndpointsResponse
ListEndpointsResponse.Builder
Response message for EndpointService.ListEndpoints.
Protobuf type google.cloud.aiplatform.v1.ListEndpointsResponse
ListEntityTypesRequest
Request message for FeaturestoreService.ListEntityTypes.
Protobuf type google.cloud.aiplatform.v1.ListEntityTypesRequest
ListEntityTypesRequest.Builder
Request message for FeaturestoreService.ListEntityTypes.
Protobuf type google.cloud.aiplatform.v1.ListEntityTypesRequest
ListEntityTypesResponse
Response message for FeaturestoreService.ListEntityTypes.
Protobuf type google.cloud.aiplatform.v1.ListEntityTypesResponse
ListEntityTypesResponse.Builder
Response message for FeaturestoreService.ListEntityTypes.
Protobuf type google.cloud.aiplatform.v1.ListEntityTypesResponse
ListExecutionsRequest
Request message for MetadataService.ListExecutions.
Protobuf type google.cloud.aiplatform.v1.ListExecutionsRequest
ListExecutionsRequest.Builder
Request message for MetadataService.ListExecutions.
Protobuf type google.cloud.aiplatform.v1.ListExecutionsRequest
ListExecutionsResponse
Response message for MetadataService.ListExecutions.
Protobuf type google.cloud.aiplatform.v1.ListExecutionsResponse
ListExecutionsResponse.Builder
Response message for MetadataService.ListExecutions.
Protobuf type google.cloud.aiplatform.v1.ListExecutionsResponse
ListFeaturesRequest
Request message for FeaturestoreService.ListFeatures.
Protobuf type google.cloud.aiplatform.v1.ListFeaturesRequest
ListFeaturesRequest.Builder
Request message for FeaturestoreService.ListFeatures.
Protobuf type google.cloud.aiplatform.v1.ListFeaturesRequest
ListFeaturesResponse
Response message for FeaturestoreService.ListFeatures.
Protobuf type google.cloud.aiplatform.v1.ListFeaturesResponse
ListFeaturesResponse.Builder
Response message for FeaturestoreService.ListFeatures.
Protobuf type google.cloud.aiplatform.v1.ListFeaturesResponse
ListFeaturestoresRequest
Request message for FeaturestoreService.ListFeaturestores.
Protobuf type google.cloud.aiplatform.v1.ListFeaturestoresRequest
ListFeaturestoresRequest.Builder
Request message for FeaturestoreService.ListFeaturestores.
Protobuf type google.cloud.aiplatform.v1.ListFeaturestoresRequest
ListFeaturestoresResponse
Response message for FeaturestoreService.ListFeaturestores.
Protobuf type google.cloud.aiplatform.v1.ListFeaturestoresResponse
ListFeaturestoresResponse.Builder
Response message for FeaturestoreService.ListFeaturestores.
Protobuf type google.cloud.aiplatform.v1.ListFeaturestoresResponse
ListHyperparameterTuningJobsRequest
Request message for JobService.ListHyperparameterTuningJobs.
Protobuf type google.cloud.aiplatform.v1.ListHyperparameterTuningJobsRequest
ListHyperparameterTuningJobsRequest.Builder
Request message for JobService.ListHyperparameterTuningJobs.
Protobuf type google.cloud.aiplatform.v1.ListHyperparameterTuningJobsRequest
ListHyperparameterTuningJobsResponse
Response message for JobService.ListHyperparameterTuningJobs
Protobuf type google.cloud.aiplatform.v1.ListHyperparameterTuningJobsResponse
ListHyperparameterTuningJobsResponse.Builder
Response message for JobService.ListHyperparameterTuningJobs
Protobuf type google.cloud.aiplatform.v1.ListHyperparameterTuningJobsResponse
ListIndexEndpointsRequest
Request message for IndexEndpointService.ListIndexEndpoints.
Protobuf type google.cloud.aiplatform.v1.ListIndexEndpointsRequest
ListIndexEndpointsRequest.Builder
Request message for IndexEndpointService.ListIndexEndpoints.
Protobuf type google.cloud.aiplatform.v1.ListIndexEndpointsRequest
ListIndexEndpointsResponse
Response message for IndexEndpointService.ListIndexEndpoints.
Protobuf type google.cloud.aiplatform.v1.ListIndexEndpointsResponse
ListIndexEndpointsResponse.Builder
Response message for IndexEndpointService.ListIndexEndpoints.
Protobuf type google.cloud.aiplatform.v1.ListIndexEndpointsResponse
ListIndexesRequest
Request message for IndexService.ListIndexes.
Protobuf type google.cloud.aiplatform.v1.ListIndexesRequest
ListIndexesRequest.Builder
Request message for IndexService.ListIndexes.
Protobuf type google.cloud.aiplatform.v1.ListIndexesRequest
ListIndexesResponse
Response message for IndexService.ListIndexes.
Protobuf type google.cloud.aiplatform.v1.ListIndexesResponse
ListIndexesResponse.Builder
Response message for IndexService.ListIndexes.
Protobuf type google.cloud.aiplatform.v1.ListIndexesResponse
ListMetadataSchemasRequest
Request message for MetadataService.ListMetadataSchemas.
Protobuf type google.cloud.aiplatform.v1.ListMetadataSchemasRequest
ListMetadataSchemasRequest.Builder
Request message for MetadataService.ListMetadataSchemas.
Protobuf type google.cloud.aiplatform.v1.ListMetadataSchemasRequest
ListMetadataSchemasResponse
Response message for MetadataService.ListMetadataSchemas.
Protobuf type google.cloud.aiplatform.v1.ListMetadataSchemasResponse
ListMetadataSchemasResponse.Builder
Response message for MetadataService.ListMetadataSchemas.
Protobuf type google.cloud.aiplatform.v1.ListMetadataSchemasResponse
ListMetadataStoresRequest
Request message for MetadataService.ListMetadataStores.
Protobuf type google.cloud.aiplatform.v1.ListMetadataStoresRequest
ListMetadataStoresRequest.Builder
Request message for MetadataService.ListMetadataStores.
Protobuf type google.cloud.aiplatform.v1.ListMetadataStoresRequest
ListMetadataStoresResponse
Response message for MetadataService.ListMetadataStores.
Protobuf type google.cloud.aiplatform.v1.ListMetadataStoresResponse
ListMetadataStoresResponse.Builder
Response message for MetadataService.ListMetadataStores.
Protobuf type google.cloud.aiplatform.v1.ListMetadataStoresResponse
ListModelDeploymentMonitoringJobsRequest
Request message for JobService.ListModelDeploymentMonitoringJobs.
Protobuf type google.cloud.aiplatform.v1.ListModelDeploymentMonitoringJobsRequest
ListModelDeploymentMonitoringJobsRequest.Builder
Request message for JobService.ListModelDeploymentMonitoringJobs.
Protobuf type google.cloud.aiplatform.v1.ListModelDeploymentMonitoringJobsRequest
ListModelDeploymentMonitoringJobsResponse
Response message for JobService.ListModelDeploymentMonitoringJobs.
Protobuf type google.cloud.aiplatform.v1.ListModelDeploymentMonitoringJobsResponse
ListModelDeploymentMonitoringJobsResponse.Builder
Response message for JobService.ListModelDeploymentMonitoringJobs.
Protobuf type google.cloud.aiplatform.v1.ListModelDeploymentMonitoringJobsResponse
ListModelEvaluationSlicesRequest
Request message for ModelService.ListModelEvaluationSlices.
Protobuf type google.cloud.aiplatform.v1.ListModelEvaluationSlicesRequest
ListModelEvaluationSlicesRequest.Builder
Request message for ModelService.ListModelEvaluationSlices.
Protobuf type google.cloud.aiplatform.v1.ListModelEvaluationSlicesRequest
ListModelEvaluationSlicesResponse
Response message for ModelService.ListModelEvaluationSlices.
Protobuf type google.cloud.aiplatform.v1.ListModelEvaluationSlicesResponse
ListModelEvaluationSlicesResponse.Builder
Response message for ModelService.ListModelEvaluationSlices.
Protobuf type google.cloud.aiplatform.v1.ListModelEvaluationSlicesResponse
ListModelEvaluationsRequest
Request message for ModelService.ListModelEvaluations.
Protobuf type google.cloud.aiplatform.v1.ListModelEvaluationsRequest
ListModelEvaluationsRequest.Builder
Request message for ModelService.ListModelEvaluations.
Protobuf type google.cloud.aiplatform.v1.ListModelEvaluationsRequest
ListModelEvaluationsResponse
Response message for ModelService.ListModelEvaluations.
Protobuf type google.cloud.aiplatform.v1.ListModelEvaluationsResponse
ListModelEvaluationsResponse.Builder
Response message for ModelService.ListModelEvaluations.
Protobuf type google.cloud.aiplatform.v1.ListModelEvaluationsResponse
ListModelVersionsRequest
Request message for ModelService.ListModelVersions.
Protobuf type google.cloud.aiplatform.v1.ListModelVersionsRequest
ListModelVersionsRequest.Builder
Request message for ModelService.ListModelVersions.
Protobuf type google.cloud.aiplatform.v1.ListModelVersionsRequest
ListModelVersionsResponse
Response message for ModelService.ListModelVersions
Protobuf type google.cloud.aiplatform.v1.ListModelVersionsResponse
ListModelVersionsResponse.Builder
Response message for ModelService.ListModelVersions
Protobuf type google.cloud.aiplatform.v1.ListModelVersionsResponse
ListModelsRequest
Request message for ModelService.ListModels.
Protobuf type google.cloud.aiplatform.v1.ListModelsRequest
ListModelsRequest.Builder
Request message for ModelService.ListModels.
Protobuf type google.cloud.aiplatform.v1.ListModelsRequest
ListModelsResponse
Response message for ModelService.ListModels
Protobuf type google.cloud.aiplatform.v1.ListModelsResponse
ListModelsResponse.Builder
Response message for ModelService.ListModels
Protobuf type google.cloud.aiplatform.v1.ListModelsResponse
ListNasJobsRequest
Request message for JobService.ListNasJobs.
Protobuf type google.cloud.aiplatform.v1.ListNasJobsRequest
ListNasJobsRequest.Builder
Request message for JobService.ListNasJobs.
Protobuf type google.cloud.aiplatform.v1.ListNasJobsRequest
ListNasJobsResponse
Response message for JobService.ListNasJobs
Protobuf type google.cloud.aiplatform.v1.ListNasJobsResponse
ListNasJobsResponse.Builder
Response message for JobService.ListNasJobs
Protobuf type google.cloud.aiplatform.v1.ListNasJobsResponse
ListNasTrialDetailsRequest
Request message for JobService.ListNasTrialDetails.
Protobuf type google.cloud.aiplatform.v1.ListNasTrialDetailsRequest
ListNasTrialDetailsRequest.Builder
Request message for JobService.ListNasTrialDetails.
Protobuf type google.cloud.aiplatform.v1.ListNasTrialDetailsRequest
ListNasTrialDetailsResponse
Response message for JobService.ListNasTrialDetails
Protobuf type google.cloud.aiplatform.v1.ListNasTrialDetailsResponse
ListNasTrialDetailsResponse.Builder
Response message for JobService.ListNasTrialDetails
Protobuf type google.cloud.aiplatform.v1.ListNasTrialDetailsResponse
ListOptimalTrialsRequest
Request message for VizierService.ListOptimalTrials.
Protobuf type google.cloud.aiplatform.v1.ListOptimalTrialsRequest
ListOptimalTrialsRequest.Builder
Request message for VizierService.ListOptimalTrials.
Protobuf type google.cloud.aiplatform.v1.ListOptimalTrialsRequest
ListOptimalTrialsResponse
Response message for VizierService.ListOptimalTrials.
Protobuf type google.cloud.aiplatform.v1.ListOptimalTrialsResponse
ListOptimalTrialsResponse.Builder
Response message for VizierService.ListOptimalTrials.
Protobuf type google.cloud.aiplatform.v1.ListOptimalTrialsResponse
ListPipelineJobsRequest
Request message for PipelineService.ListPipelineJobs.
Protobuf type google.cloud.aiplatform.v1.ListPipelineJobsRequest
ListPipelineJobsRequest.Builder
Request message for PipelineService.ListPipelineJobs.
Protobuf type google.cloud.aiplatform.v1.ListPipelineJobsRequest
ListPipelineJobsResponse
Response message for PipelineService.ListPipelineJobs
Protobuf type google.cloud.aiplatform.v1.ListPipelineJobsResponse
ListPipelineJobsResponse.Builder
Response message for PipelineService.ListPipelineJobs
Protobuf type google.cloud.aiplatform.v1.ListPipelineJobsResponse
ListSavedQueriesRequest
Request message for DatasetService.ListSavedQueries.
Protobuf type google.cloud.aiplatform.v1.ListSavedQueriesRequest
ListSavedQueriesRequest.Builder
Request message for DatasetService.ListSavedQueries.
Protobuf type google.cloud.aiplatform.v1.ListSavedQueriesRequest
ListSavedQueriesResponse
Response message for DatasetService.ListSavedQueries.
Protobuf type google.cloud.aiplatform.v1.ListSavedQueriesResponse
ListSavedQueriesResponse.Builder
Response message for DatasetService.ListSavedQueries.
Protobuf type google.cloud.aiplatform.v1.ListSavedQueriesResponse
ListSchedulesRequest
Request message for ScheduleService.ListSchedules.
Protobuf type google.cloud.aiplatform.v1.ListSchedulesRequest
ListSchedulesRequest.Builder
Request message for ScheduleService.ListSchedules.
Protobuf type google.cloud.aiplatform.v1.ListSchedulesRequest
ListSchedulesResponse
Response message for ScheduleService.ListSchedules
Protobuf type google.cloud.aiplatform.v1.ListSchedulesResponse
ListSchedulesResponse.Builder
Response message for ScheduleService.ListSchedules
Protobuf type google.cloud.aiplatform.v1.ListSchedulesResponse
ListSpecialistPoolsRequest
Request message for SpecialistPoolService.ListSpecialistPools.
Protobuf type google.cloud.aiplatform.v1.ListSpecialistPoolsRequest
ListSpecialistPoolsRequest.Builder
Request message for SpecialistPoolService.ListSpecialistPools.
Protobuf type google.cloud.aiplatform.v1.ListSpecialistPoolsRequest
ListSpecialistPoolsResponse
Response message for SpecialistPoolService.ListSpecialistPools.
Protobuf type google.cloud.aiplatform.v1.ListSpecialistPoolsResponse
ListSpecialistPoolsResponse.Builder
Response message for SpecialistPoolService.ListSpecialistPools.
Protobuf type google.cloud.aiplatform.v1.ListSpecialistPoolsResponse
ListStudiesRequest
Request message for VizierService.ListStudies.
Protobuf type google.cloud.aiplatform.v1.ListStudiesRequest
ListStudiesRequest.Builder
Request message for VizierService.ListStudies.
Protobuf type google.cloud.aiplatform.v1.ListStudiesRequest
ListStudiesResponse
Response message for VizierService.ListStudies.
Protobuf type google.cloud.aiplatform.v1.ListStudiesResponse
ListStudiesResponse.Builder
Response message for VizierService.ListStudies.
Protobuf type google.cloud.aiplatform.v1.ListStudiesResponse
ListTensorboardExperimentsRequest
Request message for TensorboardService.ListTensorboardExperiments.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardExperimentsRequest
ListTensorboardExperimentsRequest.Builder
Request message for TensorboardService.ListTensorboardExperiments.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardExperimentsRequest
ListTensorboardExperimentsResponse
Response message for TensorboardService.ListTensorboardExperiments.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardExperimentsResponse
ListTensorboardExperimentsResponse.Builder
Response message for TensorboardService.ListTensorboardExperiments.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardExperimentsResponse
ListTensorboardRunsRequest
Request message for TensorboardService.ListTensorboardRuns.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardRunsRequest
ListTensorboardRunsRequest.Builder
Request message for TensorboardService.ListTensorboardRuns.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardRunsRequest
ListTensorboardRunsResponse
Response message for TensorboardService.ListTensorboardRuns.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardRunsResponse
ListTensorboardRunsResponse.Builder
Response message for TensorboardService.ListTensorboardRuns.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardRunsResponse
ListTensorboardTimeSeriesRequest
Request message for TensorboardService.ListTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardTimeSeriesRequest
ListTensorboardTimeSeriesRequest.Builder
Request message for TensorboardService.ListTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardTimeSeriesRequest
ListTensorboardTimeSeriesResponse
Response message for TensorboardService.ListTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardTimeSeriesResponse
ListTensorboardTimeSeriesResponse.Builder
Response message for TensorboardService.ListTensorboardTimeSeries.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardTimeSeriesResponse
ListTensorboardsRequest
Request message for TensorboardService.ListTensorboards.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardsRequest
ListTensorboardsRequest.Builder
Request message for TensorboardService.ListTensorboards.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardsRequest
ListTensorboardsResponse
Response message for TensorboardService.ListTensorboards.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardsResponse
ListTensorboardsResponse.Builder
Response message for TensorboardService.ListTensorboards.
Protobuf type google.cloud.aiplatform.v1.ListTensorboardsResponse
ListTrainingPipelinesRequest
Request message for PipelineService.ListTrainingPipelines.
Protobuf type google.cloud.aiplatform.v1.ListTrainingPipelinesRequest
ListTrainingPipelinesRequest.Builder
Request message for PipelineService.ListTrainingPipelines.
Protobuf type google.cloud.aiplatform.v1.ListTrainingPipelinesRequest
ListTrainingPipelinesResponse
Response message for PipelineService.ListTrainingPipelines
Protobuf type google.cloud.aiplatform.v1.ListTrainingPipelinesResponse
ListTrainingPipelinesResponse.Builder
Response message for PipelineService.ListTrainingPipelines
Protobuf type google.cloud.aiplatform.v1.ListTrainingPipelinesResponse
ListTrialsRequest
Request message for VizierService.ListTrials.
Protobuf type google.cloud.aiplatform.v1.ListTrialsRequest
ListTrialsRequest.Builder
Request message for VizierService.ListTrials.
Protobuf type google.cloud.aiplatform.v1.ListTrialsRequest
ListTrialsResponse
Response message for VizierService.ListTrials.
Protobuf type google.cloud.aiplatform.v1.ListTrialsResponse
ListTrialsResponse.Builder
Response message for VizierService.ListTrials.
Protobuf type google.cloud.aiplatform.v1.ListTrialsResponse
LocationName
LocationName.Builder
Builder for projects/{project}/locations/{location}.
LookupStudyRequest
Request message for VizierService.LookupStudy.
Protobuf type google.cloud.aiplatform.v1.LookupStudyRequest
LookupStudyRequest.Builder
Request message for VizierService.LookupStudy.
Protobuf type google.cloud.aiplatform.v1.LookupStudyRequest
MachineResourcesProto
MachineSpec
Specification of a single machine.
Protobuf type google.cloud.aiplatform.v1.MachineSpec
MachineSpec.Builder
Specification of a single machine.
Protobuf type google.cloud.aiplatform.v1.MachineSpec
ManualBatchTuningParameters
Manual batch tuning parameters.
Protobuf type google.cloud.aiplatform.v1.ManualBatchTuningParameters
ManualBatchTuningParameters.Builder
Manual batch tuning parameters.
Protobuf type google.cloud.aiplatform.v1.ManualBatchTuningParameters
ManualBatchTuningParametersProto
MatchServiceClient
Service Description: MatchService is a Google managed service for efficient vector similarity search at scale.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the MatchServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of MatchServiceSettings to create(). For example:
To customize credentials:
// 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
MatchServiceSettings matchServiceSettings =
MatchServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
MatchServiceClient matchServiceClient = MatchServiceClient.create(matchServiceSettings);
To customize the endpoint:
// 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
MatchServiceSettings matchServiceSettings =
MatchServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
MatchServiceClient matchServiceClient = MatchServiceClient.create(matchServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
MatchServiceClient.ListLocationsFixedSizeCollection
MatchServiceClient.ListLocationsPage
MatchServiceClient.ListLocationsPagedResponse
MatchServiceGrpc
MatchService is a Google managed service for efficient vector similarity search at scale.
MatchServiceGrpc.MatchServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service MatchService.
MatchService is a Google managed service for efficient vector similarity search at scale.
MatchServiceGrpc.MatchServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service MatchService.
MatchService is a Google managed service for efficient vector similarity search at scale.
MatchServiceGrpc.MatchServiceImplBase
Base class for the server implementation of the service MatchService.
MatchService is a Google managed service for efficient vector similarity search at scale.
MatchServiceGrpc.MatchServiceStub
A stub to allow clients to do asynchronous rpc calls to service MatchService.
MatchService is a Google managed service for efficient vector similarity search at scale.
MatchServiceProto
MatchServiceSettings
Settings class to configure an instance of MatchServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of findNeighbors to 30 seconds:
// 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
MatchServiceSettings.Builder matchServiceSettingsBuilder = MatchServiceSettings.newBuilder();
matchServiceSettingsBuilder
.findNeighborsSettings()
.setRetrySettings(
matchServiceSettingsBuilder
.findNeighborsSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
MatchServiceSettings matchServiceSettings = matchServiceSettingsBuilder.build();
MatchServiceSettings.Builder
Builder for MatchServiceSettings.
Measurement
A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.
Protobuf type google.cloud.aiplatform.v1.Measurement
Measurement.Builder
A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.
Protobuf type google.cloud.aiplatform.v1.Measurement
Measurement.Metric
A message representing a metric in the measurement.
Protobuf type google.cloud.aiplatform.v1.Measurement.Metric
Measurement.Metric.Builder
A message representing a metric in the measurement.
Protobuf type google.cloud.aiplatform.v1.Measurement.Metric
MergeVersionAliasesRequest
Request message for ModelService.MergeVersionAliases.
Protobuf type google.cloud.aiplatform.v1.MergeVersionAliasesRequest
MergeVersionAliasesRequest.Builder
Request message for ModelService.MergeVersionAliases.
Protobuf type google.cloud.aiplatform.v1.MergeVersionAliasesRequest
MetadataProto
MetadataSchema
Instance of a general MetadataSchema.
Protobuf type google.cloud.aiplatform.v1.MetadataSchema
MetadataSchema.Builder
Instance of a general MetadataSchema.
Protobuf type google.cloud.aiplatform.v1.MetadataSchema
MetadataSchemaName
MetadataSchemaName.Builder
Builder for projects/{project}/locations/{location}/metadataStores/{metadata_store}/metadataSchemas/{metadata_schema}.
MetadataSchemaProto
MetadataServiceClient
Service Description: Service for reading and writing metadata entries.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the MetadataServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of MetadataServiceSettings to create(). For example:
To customize credentials:
// 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
MetadataServiceSettings metadataServiceSettings =
MetadataServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
MetadataServiceClient metadataServiceClient =
MetadataServiceClient.create(metadataServiceSettings);
To customize the endpoint:
// 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
MetadataServiceSettings metadataServiceSettings =
MetadataServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
MetadataServiceClient metadataServiceClient =
MetadataServiceClient.create(metadataServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
MetadataServiceClient.ListArtifactsFixedSizeCollection
MetadataServiceClient.ListArtifactsPage
MetadataServiceClient.ListArtifactsPagedResponse
MetadataServiceClient.ListContextsFixedSizeCollection
MetadataServiceClient.ListContextsPage
MetadataServiceClient.ListContextsPagedResponse
MetadataServiceClient.ListExecutionsFixedSizeCollection
MetadataServiceClient.ListExecutionsPage
MetadataServiceClient.ListExecutionsPagedResponse
MetadataServiceClient.ListLocationsFixedSizeCollection
MetadataServiceClient.ListLocationsPage
MetadataServiceClient.ListLocationsPagedResponse
MetadataServiceClient.ListMetadataSchemasFixedSizeCollection
MetadataServiceClient.ListMetadataSchemasPage
MetadataServiceClient.ListMetadataSchemasPagedResponse
MetadataServiceClient.ListMetadataStoresFixedSizeCollection
MetadataServiceClient.ListMetadataStoresPage
MetadataServiceClient.ListMetadataStoresPagedResponse
MetadataServiceGrpc
Service for reading and writing metadata entries.
MetadataServiceGrpc.MetadataServiceBlockingStub
A stub to allow clients to do synchronous rpc calls to service MetadataService.
Service for reading and writing metadata entries.
MetadataServiceGrpc.MetadataServiceFutureStub
A stub to allow clients to do ListenableFuture-style rpc calls to service MetadataService.
Service for reading and writing metadata entries.
MetadataServiceGrpc.MetadataServiceImplBase
Base class for the server implementation of the service MetadataService.
Service for reading and writing metadata entries.
MetadataServiceGrpc.MetadataServiceStub
A stub to allow clients to do asynchronous rpc calls to service MetadataService.
Service for reading and writing metadata entries.
MetadataServiceProto
MetadataServiceSettings
Settings class to configure an instance of MetadataServiceClient.
The default instance has everything set to sensible defaults:
- The default service address (aiplatform.googleapis.com) and default port (443) are used.
- Credentials are acquired automatically through Application Default Credentials.
- Retries are configured for idempotent methods but not for non-idempotent methods.
The builder of this class is recursive, so contained classes are themselves builders. When build() is called, the tree of builders is called to create the complete settings object.
For example, to set the total timeout of getMetadataStore to 30 seconds:
// 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
MetadataServiceSettings.Builder metadataServiceSettingsBuilder =
MetadataServiceSettings.newBuilder();
metadataServiceSettingsBuilder
.getMetadataStoreSettings()
.setRetrySettings(
metadataServiceSettingsBuilder
.getMetadataStoreSettings()
.getRetrySettings()
.toBuilder()
.setTotalTimeout(Duration.ofSeconds(30))
.build());
MetadataServiceSettings metadataServiceSettings = metadataServiceSettingsBuilder.build();
MetadataServiceSettings.Builder
Builder for MetadataServiceSettings.
MetadataStore
Instance of a metadata store. Contains a set of metadata that can be queried.
Protobuf type google.cloud.aiplatform.v1.MetadataStore
MetadataStore.Builder
Instance of a metadata store. Contains a set of metadata that can be queried.
Protobuf type google.cloud.aiplatform.v1.MetadataStore
MetadataStore.MetadataStoreState
Represents state information for a MetadataStore.
Protobuf type google.cloud.aiplatform.v1.MetadataStore.MetadataStoreState
MetadataStore.MetadataStoreState.Builder
Represents state information for a MetadataStore.
Protobuf type google.cloud.aiplatform.v1.MetadataStore.MetadataStoreState
MetadataStoreName
MetadataStoreName.Builder
Builder for projects/{project}/locations/{location}/metadataStores/{metadata_store}.
MigratableResource
Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource
MigratableResource.AutomlDataset
Represents one Dataset in automl.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource.AutomlDataset
MigratableResource.AutomlDataset.Builder
Represents one Dataset in automl.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource.AutomlDataset
MigratableResource.AutomlModel
Represents one Model in automl.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource.AutomlModel
MigratableResource.AutomlModel.Builder
Represents one Model in automl.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource.AutomlModel
MigratableResource.Builder
Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource
MigratableResource.DataLabelingDataset
Represents one Dataset in datalabeling.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource.DataLabelingDataset
MigratableResource.DataLabelingDataset.Builder
Represents one Dataset in datalabeling.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource.DataLabelingDataset
MigratableResource.DataLabelingDataset.DataLabelingAnnotatedDataset
Represents one AnnotatedDataset in datalabeling.googleapis.com.
Protobuf type
google.cloud.aiplatform.v1.MigratableResource.DataLabelingDataset.DataLabelingAnnotatedDataset
MigratableResource.DataLabelingDataset.DataLabelingAnnotatedDataset.Builder
Represents one AnnotatedDataset in datalabeling.googleapis.com.
Protobuf type
google.cloud.aiplatform.v1.MigratableResource.DataLabelingDataset.DataLabelingAnnotatedDataset
MigratableResource.MlEngineModelVersion
Represents one model Version in ml.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource.MlEngineModelVersion
MigratableResource.MlEngineModelVersion.Builder
Represents one model Version in ml.googleapis.com.
Protobuf type google.cloud.aiplatform.v1.MigratableResource.MlEngineModelVersion
MigratableResourceProto
MigrateResourceRequest
Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
Protobuf type google.cloud.aiplatform.v1.MigrateResourceRequest
MigrateResourceRequest.Builder
Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
Protobuf type google.cloud.aiplatform.v1.MigrateResourceRequest
MigrateResourceRequest.MigrateAutomlDatasetConfig
Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateAutomlDatasetConfig
MigrateResourceRequest.MigrateAutomlDatasetConfig.Builder
Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateAutomlDatasetConfig
MigrateResourceRequest.MigrateAutomlModelConfig
Config for migrating Model in automl.googleapis.com to Vertex AI's Model.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateAutomlModelConfig
MigrateResourceRequest.MigrateAutomlModelConfig.Builder
Config for migrating Model in automl.googleapis.com to Vertex AI's Model.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateAutomlModelConfig
MigrateResourceRequest.MigrateDataLabelingDatasetConfig
Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateDataLabelingDatasetConfig
MigrateResourceRequest.MigrateDataLabelingDatasetConfig.Builder
Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateDataLabelingDatasetConfig
MigrateResourceRequest.MigrateDataLabelingDatasetConfig.MigrateDataLabelingAnnotatedDatasetConfig
Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateDataLabelingDatasetConfig.MigrateDataLabelingAnnotatedDatasetConfig
MigrateResourceRequest.MigrateDataLabelingDatasetConfig.MigrateDataLabelingAnnotatedDatasetConfig.Builder
Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateDataLabelingDatasetConfig.MigrateDataLabelingAnnotatedDatasetConfig
MigrateResourceRequest.MigrateMlEngineModelVersionConfig
Config for migrating version in ml.googleapis.com to Vertex AI's Model.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateMlEngineModelVersionConfig
MigrateResourceRequest.MigrateMlEngineModelVersionConfig.Builder
Config for migrating version in ml.googleapis.com to Vertex AI's Model.
Protobuf type
google.cloud.aiplatform.v1.MigrateResourceRequest.MigrateMlEngineModelVersionConfig
MigrateResourceResponse
Describes a successfully migrated resource.
Protobuf type google.cloud.aiplatform.v1.MigrateResourceResponse
MigrateResourceResponse.Builder
Describes a successfully migrated resource.
Protobuf type google.cloud.aiplatform.v1.MigrateResourceResponse
MigrationServiceClient
Service Description: A service that migrates resources from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// 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);
}
Note: close() needs to be called on the MigrationServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
The surface of this class includes several types of Java methods for each of the API's methods:
- A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
- A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
- A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of MigrationServiceSettings to create(). For example:
To customize credentials:
// 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
MigrationServiceSettings migrationServiceSettings =
MigrationServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
MigrationServiceClient migrationServiceClient =
MigrationServiceClient.create(migrationServiceSettings);
To custom