Module google_api_proto::google::cloud::aiplatform::v1

Modules

• active_learning_config
  Nested message and enum types in ActiveLearningConfig.
• artifact
  Nested message and enum types in Artifact.
• batch_migrate_resources_operation_metadata
  Nested message and enum types in BatchMigrateResourcesOperationMetadata.
• batch_prediction_job
  Nested message and enum types in BatchPredictionJob.
• batch_read_feature_values_request
  Nested message and enum types in BatchReadFeatureValuesRequest.
• candidate
  Nested message and enum types in Candidate.
• copy_model_request
  Nested message and enum types in CopyModelRequest.
• dataset_service_client
  Generated client implementations.
• delete_feature_values_request
  Nested message and enum types in DeleteFeatureValuesRequest.
• delete_feature_values_response
  Nested message and enum types in DeleteFeatureValuesResponse.
• deployed_index_auth_config
  Nested message and enum types in DeployedIndexAuthConfig.
• deployed_model
  Nested message and enum types in DeployedModel.
• deployment_resource_pool_service_client
  Generated client implementations.
• endpoint_service_client
  Generated client implementations.
• entity_id_selector
  Nested message and enum types in EntityIdSelector.
• error_analysis_annotation
  Nested message and enum types in ErrorAnalysisAnnotation.
• evaluate_instances_request
  Nested message and enum types in EvaluateInstancesRequest.
• evaluate_instances_response
  Nested message and enum types in EvaluateInstancesResponse.
• evaluated_annotation
  Nested message and enum types in EvaluatedAnnotation.
• evaluation_service_client
  Generated client implementations.
• event
  Nested message and enum types in Event.
• examples
  Nested message and enum types in Examples.
• examples_override
  Nested message and enum types in ExamplesOverride.
• execution
  Nested message and enum types in Execution.
• explanation_metadata
  Nested message and enum types in ExplanationMetadata.
• explanation_metadata_override
  Nested message and enum types in ExplanationMetadataOverride.
• explanation_parameters
  Nested message and enum types in ExplanationParameters.
• export_data_config
  Nested message and enum types in ExportDataConfig.
• export_feature_values_request
  Nested message and enum types in ExportFeatureValuesRequest.
• export_model_operation_metadata
  Nested message and enum types in ExportModelOperationMetadata.
• export_model_request
  Nested message and enum types in ExportModelRequest.
• feature
  Nested message and enum types in Feature.
• feature_group
  Nested message and enum types in FeatureGroup.
• feature_noise_sigma
  Nested message and enum types in FeatureNoiseSigma.
• feature_online_store
  Nested message and enum types in FeatureOnlineStore.
• feature_online_store_admin_service_client
  Generated client implementations.
• feature_online_store_service_client
  Generated client implementations.
• feature_registry_service_client
  Generated client implementations.
• feature_value
  Nested message and enum types in FeatureValue.
• feature_value_destination
  Nested message and enum types in FeatureValueDestination.
• feature_view
  Nested message and enum types in FeatureView.
• feature_view_data_key
  Nested message and enum types in FeatureViewDataKey.
• feature_view_sync
  Nested message and enum types in FeatureViewSync.
• featurestore
  Nested message and enum types in Featurestore.
• featurestore_monitoring_config
  Nested message and enum types in FeaturestoreMonitoringConfig.
• featurestore_online_serving_service_client
  Generated client implementations.
• featurestore_service_client
  Generated client implementations.
• fetch_feature_values_response
  Nested message and enum types in FetchFeatureValuesResponse.
• find_neighbors_request
  Nested message and enum types in FindNeighborsRequest.
• find_neighbors_response
  Nested message and enum types in FindNeighborsResponse.
• function_calling_config
  Nested message and enum types in FunctionCallingConfig.
• gen_ai_tuning_service_client
  Generated client implementations.
• generate_content_response
  Nested message and enum types in GenerateContentResponse.
• generation_config
  Nested message and enum types in GenerationConfig.
• grounding_chunk
  Nested message and enum types in GroundingChunk.
• import_data_config
  Nested message and enum types in ImportDataConfig.
• import_feature_values_request
  Nested message and enum types in ImportFeatureValuesRequest.
• index
  Nested message and enum types in Index.
• index_datapoint
  Nested message and enum types in IndexDatapoint.
• index_endpoint_service_client
  Generated client implementations.
• index_service_client
  Generated client implementations.
• input_data_config
  Nested message and enum types in InputDataConfig.
• job_service_client
  Generated client implementations.
• llm_utility_service_client
  Generated client implementations.
• match_service_client
  Generated client implementations.
• measurement
  Nested message and enum types in Measurement.
• metadata_schema
  Nested message and enum types in MetadataSchema.
• metadata_service_client
  Generated client implementations.
• metadata_store
  Nested message and enum types in MetadataStore.
• migratable_resource
  Nested message and enum types in MigratableResource.
• migrate_resource_request
  Nested message and enum types in MigrateResourceRequest.
• migrate_resource_response
  Nested message and enum types in MigrateResourceResponse.
• migration_service_client
  Generated client implementations.
• model
  Nested message and enum types in Model.
• model_deployment_monitoring_big_query_table
  Nested message and enum types in ModelDeploymentMonitoringBigQueryTable.
• model_deployment_monitoring_job
  Nested message and enum types in ModelDeploymentMonitoringJob.
• model_evaluation
  Nested message and enum types in ModelEvaluation.
• model_evaluation_slice
  Nested message and enum types in ModelEvaluationSlice.
• model_garden_service_client
  Generated client implementations.
• model_monitoring_alert_config
  Nested message and enum types in ModelMonitoringAlertConfig.
• model_monitoring_objective_config
  Nested message and enum types in ModelMonitoringObjectiveConfig.
• model_monitoring_stats_anomalies
  Nested message and enum types in ModelMonitoringStatsAnomalies.
• model_service_client
  Generated client implementations.
• model_source_info
  Nested message and enum types in ModelSourceInfo.
• nas_job_output
  Nested message and enum types in NasJobOutput.
• nas_job_spec
  Nested message and enum types in NasJobSpec.
• nas_trial
  Nested message and enum types in NasTrial.
• nearest_neighbor_query
  Nested message and enum types in NearestNeighborQuery.
• nearest_neighbor_search_operation_metadata
  Nested message and enum types in NearestNeighborSearchOperationMetadata.
• nearest_neighbors
  Nested message and enum types in NearestNeighbors.
• notebook_execution_job
  Nested message and enum types in NotebookExecutionJob.
• notebook_runtime
  Nested message and enum types in NotebookRuntime.
• notebook_service_client
  Generated client implementations.
• pairwise_metric_instance
  Nested message and enum types in PairwiseMetricInstance.
• part
  Nested message and enum types in Part.
• persistent_resource
  Nested message and enum types in PersistentResource.
• persistent_resource_service_client
  Generated client implementations.
• pipeline_job
  Nested message and enum types in PipelineJob.
• pipeline_service_client
  Generated client implementations.
• pipeline_task_detail
  Nested message and enum types in PipelineTaskDetail.
• pipeline_task_executor_detail
  Nested message and enum types in PipelineTaskExecutorDetail.
• pointwise_metric_instance
  Nested message and enum types in PointwiseMetricInstance.
• prediction_service_client
  Generated client implementations.
• presets
  Nested message and enum types in Presets.
• probe
  Nested message and enum types in Probe.
• publisher_model
  Nested message and enum types in PublisherModel.
• read_feature_values_response
  Nested message and enum types in ReadFeatureValuesResponse.
• read_tensorboard_usage_response
  Nested message and enum types in ReadTensorboardUsageResponse.
• reservation_affinity
  Nested message and enum types in ReservationAffinity.
• resource_pool
  Nested message and enum types in ResourcePool.
• retrieval
  Nested message and enum types in Retrieval.
• safety_rating
  Nested message and enum types in SafetyRating.
• safety_setting
  Nested message and enum types in SafetySetting.
• sample_config
  Nested message and enum types in SampleConfig.
• sampling_strategy
  Nested message and enum types in SamplingStrategy.
• schedule
  Nested message and enum types in Schedule.
• schedule_service_client
  Generated client implementations.
• scheduling
  Nested message and enum types in Scheduling.
• schema
• search_data_items_request
  Nested message and enum types in SearchDataItemsRequest.
• search_model_deployment_monitoring_stats_anomalies_request
  Nested message and enum types in SearchModelDeploymentMonitoringStatsAnomaliesRequest.
• smooth_grad_config
  Nested message and enum types in SmoothGradConfig.
• specialist_pool_service_client
  Generated client implementations.
• study
  Nested message and enum types in Study.
• study_spec
  Nested message and enum types in StudySpec.
• study_time_constraint
  Nested message and enum types in StudyTimeConstraint.
• supervised_hyper_parameters
  Nested message and enum types in SupervisedHyperParameters.
• supervised_tuning_dataset_distribution
  Nested message and enum types in SupervisedTuningDatasetDistribution.
• tensor
  Nested message and enum types in Tensor.
• tensorboard_service_client
  Generated client implementations.
• tensorboard_time_series
  Nested message and enum types in TensorboardTimeSeries.
• threshold_config
  Nested message and enum types in ThresholdConfig.
• time_series_data_point
  Nested message and enum types in TimeSeriesDataPoint.
• trial
  Nested message and enum types in Trial.
• tuning_data_stats
  Nested message and enum types in TuningDataStats.
• tuning_job
  Nested message and enum types in TuningJob.
• user_action_reference
  Nested message and enum types in UserActionReference.
• value
  Nested message and enum types in Value.
• vizier_service_client
  Generated client implementations.
• worker_pool_spec
  Nested message and enum types in WorkerPoolSpec.

Structs

• 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.
• AddContextArtifactsAndExecutionsRequest
  Request message for [MetadataService.AddContextArtifactsAndExecutions][google.cloud.aiplatform.v1.MetadataService.AddContextArtifactsAndExecutions].
• AddContextArtifactsAndExecutionsResponse
  Response message for [MetadataService.AddContextArtifactsAndExecutions][google.cloud.aiplatform.v1.MetadataService.AddContextArtifactsAndExecutions].
• AddContextChildrenRequest
  Request message for [MetadataService.AddContextChildren][google.cloud.aiplatform.v1.MetadataService.AddContextChildren].
• AddContextChildrenResponse
  Response message for [MetadataService.AddContextChildren][google.cloud.aiplatform.v1.MetadataService.AddContextChildren].
• AddExecutionEventsRequest
  Request message for [MetadataService.AddExecutionEvents][google.cloud.aiplatform.v1.MetadataService.AddExecutionEvents].
• AddExecutionEventsResponse
  Response message for [MetadataService.AddExecutionEvents][google.cloud.aiplatform.v1.MetadataService.AddExecutionEvents].
• AddTrialMeasurementRequest
  Request message for [VizierService.AddTrialMeasurement][google.cloud.aiplatform.v1.VizierService.AddTrialMeasurement].
• Annotation
  Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.
• AnnotationSpec
  Identifies a concept with which DataItems may be annotated with.
• Artifact
  Instance of a general artifact.
• AssignNotebookRuntimeOperationMetadata
  Metadata information for [NotebookService.AssignNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.AssignNotebookRuntime].
• AssignNotebookRuntimeRequest
  Request message for [NotebookService.AssignNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.AssignNotebookRuntime].
• Attribution
  Attribution that explains a particular prediction output.
• 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.
• 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.
• AvroSource
  The storage details for Avro input content.
• BatchCancelPipelineJobsOperationMetadata
  Runtime operation information for [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].
• BatchCancelPipelineJobsRequest
  Request message for [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].
• BatchCancelPipelineJobsResponse
  Response message for [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].
• BatchCreateFeaturesOperationMetadata
  Details of operations that perform batch create Features.
• BatchCreateFeaturesRequest
  Request message for [FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1.FeaturestoreService.BatchCreateFeatures].
• BatchCreateFeaturesResponse
  Response message for [FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1.FeaturestoreService.BatchCreateFeatures].
• BatchCreateTensorboardRunsRequest
  Request message for [TensorboardService.BatchCreateTensorboardRuns][google.cloud.aiplatform.v1.TensorboardService.BatchCreateTensorboardRuns].
• BatchCreateTensorboardRunsResponse
  Response message for [TensorboardService.BatchCreateTensorboardRuns][google.cloud.aiplatform.v1.TensorboardService.BatchCreateTensorboardRuns].
• BatchCreateTensorboardTimeSeriesRequest
  Request message for [TensorboardService.BatchCreateTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.BatchCreateTensorboardTimeSeries].
• BatchCreateTensorboardTimeSeriesResponse
  Response message for [TensorboardService.BatchCreateTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.BatchCreateTensorboardTimeSeries].
• BatchDedicatedResources
  A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.
• BatchDeletePipelineJobsRequest
  Request message for [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].
• BatchDeletePipelineJobsResponse
  Response message for [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].
• BatchImportEvaluatedAnnotationsRequest
  Request message for [ModelService.BatchImportEvaluatedAnnotations][google.cloud.aiplatform.v1.ModelService.BatchImportEvaluatedAnnotations]
• BatchImportEvaluatedAnnotationsResponse
  Response message for [ModelService.BatchImportEvaluatedAnnotations][google.cloud.aiplatform.v1.ModelService.BatchImportEvaluatedAnnotations]
• BatchImportModelEvaluationSlicesRequest
  Request message for [ModelService.BatchImportModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.BatchImportModelEvaluationSlices]
• BatchImportModelEvaluationSlicesResponse
  Response message for [ModelService.BatchImportModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.BatchImportModelEvaluationSlices]
• BatchMigrateResourcesOperationMetadata
  Runtime operation information for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
• BatchMigrateResourcesRequest
  Request message for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
• BatchMigrateResourcesResponse
  Response message for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
• BatchPredictionJob
  A job that uses a [Model][google.cloud.aiplatform.v1.BatchPredictionJob.model] to produce predictions on multiple [input instances][google.cloud.aiplatform.v1.BatchPredictionJob.input_config]. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.
• BatchReadFeatureValuesOperationMetadata
  Details of operations that batch reads Feature values.
• BatchReadFeatureValuesRequest
  Request message for [FeaturestoreService.BatchReadFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.BatchReadFeatureValues].
• BatchReadFeatureValuesResponse
  Response message for [FeaturestoreService.BatchReadFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.BatchReadFeatureValues].
• BatchReadTensorboardTimeSeriesDataRequest
  Request message for [TensorboardService.BatchReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.BatchReadTensorboardTimeSeriesData].
• BatchReadTensorboardTimeSeriesDataResponse
  Response message for [TensorboardService.BatchReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.BatchReadTensorboardTimeSeriesData].
• BigQueryDestination
  The BigQuery location for the output content.
• BigQuerySource
  The BigQuery location for the input content.
• BleuInput
  Input for bleu metric.
• BleuInstance
  Spec for bleu instance.
• BleuMetricValue
  Bleu metric value for an instance.
• BleuResults
  Results for bleu metric.
• BleuSpec
  Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1.
• Blob
  Content blob.
• BlurBaselineConfig
  Config for blur baseline.
• BoolArray
  A list of boolean values.
• CancelBatchPredictionJobRequest
  Request message for [JobService.CancelBatchPredictionJob][google.cloud.aiplatform.v1.JobService.CancelBatchPredictionJob].
• CancelCustomJobRequest
  Request message for [JobService.CancelCustomJob][google.cloud.aiplatform.v1.JobService.CancelCustomJob].
• CancelDataLabelingJobRequest
  Request message for [JobService.CancelDataLabelingJob][google.cloud.aiplatform.v1.JobService.CancelDataLabelingJob].
• CancelHyperparameterTuningJobRequest
  Request message for [JobService.CancelHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.CancelHyperparameterTuningJob].
• CancelNasJobRequest
  Request message for [JobService.CancelNasJob][google.cloud.aiplatform.v1.JobService.CancelNasJob].
• CancelPipelineJobRequest
  Request message for [PipelineService.CancelPipelineJob][google.cloud.aiplatform.v1.PipelineService.CancelPipelineJob].
• CancelTrainingPipelineRequest
  Request message for [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CancelTrainingPipeline].
• CancelTuningJobRequest
  Request message for [GenAiTuningService.CancelTuningJob][google.cloud.aiplatform.v1.GenAiTuningService.CancelTuningJob].
• Candidate
  A response candidate generated from the model.
• CheckTrialEarlyStoppingStateMetatdata
  This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
• CheckTrialEarlyStoppingStateRequest
  Request message for [VizierService.CheckTrialEarlyStoppingState][google.cloud.aiplatform.v1.VizierService.CheckTrialEarlyStoppingState].
• CheckTrialEarlyStoppingStateResponse
  Response message for [VizierService.CheckTrialEarlyStoppingState][google.cloud.aiplatform.v1.VizierService.CheckTrialEarlyStoppingState].
• Citation
  Source attributions for content.
• CitationMetadata
  A collection of source attributions for a piece of content.
• CoherenceInput
  Input for coherence metric.
• CoherenceInstance
  Spec for coherence instance.
• CoherenceResult
  Spec for coherence result.
• CoherenceSpec
  Spec for coherence score metric.
• CompleteTrialRequest
  Request message for [VizierService.CompleteTrial][google.cloud.aiplatform.v1.VizierService.CompleteTrial].
• CompletionStats
  Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
• ComputeTokensRequest
  Request message for ComputeTokens RPC call.
• ComputeTokensResponse
  Response message for ComputeTokens RPC call.
• ContainerRegistryDestination
  The Container Registry location for the container image.
• ContainerSpec
  The spec of a Container.
• Content
  The base structured datatype containing multi-part content of a message.
• Context
  Instance of a general context.
• CopyModelOperationMetadata
  Details of [ModelService.CopyModel][google.cloud.aiplatform.v1.ModelService.CopyModel] operation.
• CopyModelRequest
  Request message for [ModelService.CopyModel][google.cloud.aiplatform.v1.ModelService.CopyModel].
• CopyModelResponse
  Response message of [ModelService.CopyModel][google.cloud.aiplatform.v1.ModelService.CopyModel] operation.
• CountTokensRequest
  Request message for [PredictionService.CountTokens][].
• CountTokensResponse
  Response message for [PredictionService.CountTokens][].
• CreateArtifactRequest
  Request message for [MetadataService.CreateArtifact][google.cloud.aiplatform.v1.MetadataService.CreateArtifact].
• CreateBatchPredictionJobRequest
  Request message for [JobService.CreateBatchPredictionJob][google.cloud.aiplatform.v1.JobService.CreateBatchPredictionJob].
• CreateContextRequest
  Request message for [MetadataService.CreateContext][google.cloud.aiplatform.v1.MetadataService.CreateContext].
• CreateCustomJobRequest
  Request message for [JobService.CreateCustomJob][google.cloud.aiplatform.v1.JobService.CreateCustomJob].
• CreateDataLabelingJobRequest
  Request message for [JobService.CreateDataLabelingJob][google.cloud.aiplatform.v1.JobService.CreateDataLabelingJob].
• CreateDatasetOperationMetadata
  Runtime operation information for [DatasetService.CreateDataset][google.cloud.aiplatform.v1.DatasetService.CreateDataset].
• CreateDatasetRequest
  Request message for [DatasetService.CreateDataset][google.cloud.aiplatform.v1.DatasetService.CreateDataset].
• CreateDatasetVersionOperationMetadata
  Runtime operation information for [DatasetService.CreateDatasetVersion][google.cloud.aiplatform.v1.DatasetService.CreateDatasetVersion].
• CreateDatasetVersionRequest
  Request message for [DatasetService.CreateDatasetVersion][google.cloud.aiplatform.v1.DatasetService.CreateDatasetVersion].
• CreateDeploymentResourcePoolOperationMetadata
  Runtime operation information for CreateDeploymentResourcePool method.
• CreateDeploymentResourcePoolRequest
  Request message for CreateDeploymentResourcePool method.
• CreateEndpointOperationMetadata
  Runtime operation information for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1.EndpointService.CreateEndpoint].
• CreateEndpointRequest
  Request message for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1.EndpointService.CreateEndpoint].
• CreateEntityTypeOperationMetadata
  Details of operations that perform create EntityType.
• CreateEntityTypeRequest
  Request message for [FeaturestoreService.CreateEntityType][google.cloud.aiplatform.v1.FeaturestoreService.CreateEntityType].
• CreateExecutionRequest
  Request message for [MetadataService.CreateExecution][google.cloud.aiplatform.v1.MetadataService.CreateExecution].
• CreateFeatureGroupOperationMetadata
  Details of operations that perform create FeatureGroup.
• CreateFeatureGroupRequest
  Request message for [FeatureRegistryService.CreateFeatureGroup][google.cloud.aiplatform.v1.FeatureRegistryService.CreateFeatureGroup].
• CreateFeatureOnlineStoreOperationMetadata
  Details of operations that perform create FeatureOnlineStore.
• CreateFeatureOnlineStoreRequest
  Request message for [FeatureOnlineStoreAdminService.CreateFeatureOnlineStore][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.CreateFeatureOnlineStore].
• CreateFeatureOperationMetadata
  Details of operations that perform create Feature.
• CreateFeatureRequest
  Request message for [FeaturestoreService.CreateFeature][google.cloud.aiplatform.v1.FeaturestoreService.CreateFeature]. Request message for [FeatureRegistryService.CreateFeature][google.cloud.aiplatform.v1.FeatureRegistryService.CreateFeature].
• CreateFeatureViewOperationMetadata
  Details of operations that perform create FeatureView.
• CreateFeatureViewRequest
  Request message for [FeatureOnlineStoreAdminService.CreateFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.CreateFeatureView].
• CreateFeaturestoreOperationMetadata
  Details of operations that perform create Featurestore.
• CreateFeaturestoreRequest
  Request message for [FeaturestoreService.CreateFeaturestore][google.cloud.aiplatform.v1.FeaturestoreService.CreateFeaturestore].
• CreateHyperparameterTuningJobRequest
  Request message for [JobService.CreateHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.CreateHyperparameterTuningJob].
• CreateIndexEndpointOperationMetadata
  Runtime operation information for [IndexEndpointService.CreateIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.CreateIndexEndpoint].
• CreateIndexEndpointRequest
  Request message for [IndexEndpointService.CreateIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.CreateIndexEndpoint].
• CreateIndexOperationMetadata
  Runtime operation information for [IndexService.CreateIndex][google.cloud.aiplatform.v1.IndexService.CreateIndex].
• CreateIndexRequest
  Request message for [IndexService.CreateIndex][google.cloud.aiplatform.v1.IndexService.CreateIndex].
• CreateMetadataSchemaRequest
  Request message for [MetadataService.CreateMetadataSchema][google.cloud.aiplatform.v1.MetadataService.CreateMetadataSchema].
• CreateMetadataStoreOperationMetadata
  Details of operations that perform [MetadataService.CreateMetadataStore][google.cloud.aiplatform.v1.MetadataService.CreateMetadataStore].
• CreateMetadataStoreRequest
  Request message for [MetadataService.CreateMetadataStore][google.cloud.aiplatform.v1.MetadataService.CreateMetadataStore].
• CreateModelDeploymentMonitoringJobRequest
  Request message for [JobService.CreateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.CreateModelDeploymentMonitoringJob].
• CreateNasJobRequest
  Request message for [JobService.CreateNasJob][google.cloud.aiplatform.v1.JobService.CreateNasJob].
• CreateNotebookExecutionJobOperationMetadata
  Metadata information for [NotebookService.CreateNotebookExecutionJob][google.cloud.aiplatform.v1.NotebookService.CreateNotebookExecutionJob].
• CreateNotebookExecutionJobRequest
  Request message for [NotebookService.CreateNotebookExecutionJob]
• CreateNotebookRuntimeTemplateOperationMetadata
  Metadata information for [NotebookService.CreateNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.CreateNotebookRuntimeTemplate].
• CreateNotebookRuntimeTemplateRequest
  Request message for [NotebookService.CreateNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.CreateNotebookRuntimeTemplate].
• CreatePersistentResourceOperationMetadata
  Details of operations that perform create PersistentResource.
• CreatePersistentResourceRequest
  Request message for [PersistentResourceService.CreatePersistentResource][google.cloud.aiplatform.v1.PersistentResourceService.CreatePersistentResource].
• CreatePipelineJobRequest
  Request message for [PipelineService.CreatePipelineJob][google.cloud.aiplatform.v1.PipelineService.CreatePipelineJob].
• CreateRegistryFeatureOperationMetadata
  Details of operations that perform create FeatureGroup.
• CreateScheduleRequest
  Request message for [ScheduleService.CreateSchedule][google.cloud.aiplatform.v1.ScheduleService.CreateSchedule].
• CreateSpecialistPoolOperationMetadata
  Runtime operation information for [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.CreateSpecialistPool].
• CreateSpecialistPoolRequest
  Request message for [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.CreateSpecialistPool].
• CreateStudyRequest
  Request message for [VizierService.CreateStudy][google.cloud.aiplatform.v1.VizierService.CreateStudy].
• CreateTensorboardExperimentRequest
  Request message for [TensorboardService.CreateTensorboardExperiment][google.cloud.aiplatform.v1.TensorboardService.CreateTensorboardExperiment].
• CreateTensorboardOperationMetadata
  Details of operations that perform create Tensorboard.
• CreateTensorboardRequest
  Request message for [TensorboardService.CreateTensorboard][google.cloud.aiplatform.v1.TensorboardService.CreateTensorboard].
• CreateTensorboardRunRequest
  Request message for [TensorboardService.CreateTensorboardRun][google.cloud.aiplatform.v1.TensorboardService.CreateTensorboardRun].
• CreateTensorboardTimeSeriesRequest
  Request message for [TensorboardService.CreateTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.CreateTensorboardTimeSeries].
• CreateTrainingPipelineRequest
  Request message for [PipelineService.CreateTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CreateTrainingPipeline].
• CreateTrialRequest
  Request message for [VizierService.CreateTrial][google.cloud.aiplatform.v1.VizierService.CreateTrial].
• CreateTuningJobRequest
  Request message for [GenAiTuningService.CreateTuningJob][google.cloud.aiplatform.v1.GenAiTuningService.CreateTuningJob].
• CsvDestination
  The storage details for CSV output content.
• CsvSource
  The storage details for CSV input content.
• 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).
• CustomJobSpec
  Represents the spec of a CustomJob.
• DataItem
  A piece of data in a Dataset. Could be an image, a video, a document or plain text.
• DataItemView
  A container for a single DataItem and Annotations on it.
• DataLabelingJob
  DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:
• Dataset
  A collection of DataItems and Annotations on them.
• DatasetVersion
  Describes the dataset version.
• DedicatedResources
  A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.
• DeleteArtifactRequest
  Request message for [MetadataService.DeleteArtifact][google.cloud.aiplatform.v1.MetadataService.DeleteArtifact].
• DeleteBatchPredictionJobRequest
  Request message for [JobService.DeleteBatchPredictionJob][google.cloud.aiplatform.v1.JobService.DeleteBatchPredictionJob].
• DeleteContextRequest
  Request message for [MetadataService.DeleteContext][google.cloud.aiplatform.v1.MetadataService.DeleteContext].
• DeleteCustomJobRequest
  Request message for [JobService.DeleteCustomJob][google.cloud.aiplatform.v1.JobService.DeleteCustomJob].
• DeleteDataLabelingJobRequest
  Request message for [JobService.DeleteDataLabelingJob][google.cloud.aiplatform.v1.JobService.DeleteDataLabelingJob].
• DeleteDatasetRequest
  Request message for [DatasetService.DeleteDataset][google.cloud.aiplatform.v1.DatasetService.DeleteDataset].
• DeleteDatasetVersionRequest
  Request message for [DatasetService.DeleteDatasetVersion][google.cloud.aiplatform.v1.DatasetService.DeleteDatasetVersion].
• DeleteDeploymentResourcePoolRequest
  Request message for DeleteDeploymentResourcePool method.
• DeleteEndpointRequest
  Request message for [EndpointService.DeleteEndpoint][google.cloud.aiplatform.v1.EndpointService.DeleteEndpoint].
• DeleteEntityTypeRequest
  Request message for [FeaturestoreService.DeleteEntityTypes][].
• DeleteExecutionRequest
  Request message for [MetadataService.DeleteExecution][google.cloud.aiplatform.v1.MetadataService.DeleteExecution].
• DeleteFeatureGroupRequest
  Request message for [FeatureRegistryService.DeleteFeatureGroup][google.cloud.aiplatform.v1.FeatureRegistryService.DeleteFeatureGroup].
• DeleteFeatureOnlineStoreRequest
  Request message for [FeatureOnlineStoreAdminService.DeleteFeatureOnlineStore][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.DeleteFeatureOnlineStore].
• DeleteFeatureRequest
  Request message for [FeaturestoreService.DeleteFeature][google.cloud.aiplatform.v1.FeaturestoreService.DeleteFeature]. Request message for [FeatureRegistryService.DeleteFeature][google.cloud.aiplatform.v1.FeatureRegistryService.DeleteFeature].
• DeleteFeatureValuesOperationMetadata
  Details of operations that delete Feature values.
• DeleteFeatureValuesRequest
  Request message for [FeaturestoreService.DeleteFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.DeleteFeatureValues].
• DeleteFeatureValuesResponse
  Response message for [FeaturestoreService.DeleteFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.DeleteFeatureValues].
• DeleteFeatureViewRequest
  Request message for [FeatureOnlineStoreAdminService.DeleteFeatureViews][].
• DeleteFeaturestoreRequest
  Request message for [FeaturestoreService.DeleteFeaturestore][google.cloud.aiplatform.v1.FeaturestoreService.DeleteFeaturestore].
• DeleteHyperparameterTuningJobRequest
  Request message for [JobService.DeleteHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.DeleteHyperparameterTuningJob].
• DeleteIndexEndpointRequest
  Request message for [IndexEndpointService.DeleteIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.DeleteIndexEndpoint].
• DeleteIndexRequest
  Request message for [IndexService.DeleteIndex][google.cloud.aiplatform.v1.IndexService.DeleteIndex].
• DeleteMetadataStoreOperationMetadata
  Details of operations that perform [MetadataService.DeleteMetadataStore][google.cloud.aiplatform.v1.MetadataService.DeleteMetadataStore].
• DeleteMetadataStoreRequest
  Request message for [MetadataService.DeleteMetadataStore][google.cloud.aiplatform.v1.MetadataService.DeleteMetadataStore].
• DeleteModelDeploymentMonitoringJobRequest
  Request message for [JobService.DeleteModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.DeleteModelDeploymentMonitoringJob].
• DeleteModelRequest
  Request message for [ModelService.DeleteModel][google.cloud.aiplatform.v1.ModelService.DeleteModel].
• DeleteModelVersionRequest
  Request message for [ModelService.DeleteModelVersion][google.cloud.aiplatform.v1.ModelService.DeleteModelVersion].
• DeleteNasJobRequest
  Request message for [JobService.DeleteNasJob][google.cloud.aiplatform.v1.JobService.DeleteNasJob].
• DeleteNotebookExecutionJobRequest
  Request message for [NotebookService.DeleteNotebookExecutionJob]
• DeleteNotebookRuntimeRequest
  Request message for [NotebookService.DeleteNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.DeleteNotebookRuntime].
• DeleteNotebookRuntimeTemplateRequest
  Request message for [NotebookService.DeleteNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.DeleteNotebookRuntimeTemplate].
• DeleteOperationMetadata
  Details of operations that perform deletes of any entities.
• DeletePersistentResourceRequest
  Request message for [PersistentResourceService.DeletePersistentResource][google.cloud.aiplatform.v1.PersistentResourceService.DeletePersistentResource].
• DeletePipelineJobRequest
  Request message for [PipelineService.DeletePipelineJob][google.cloud.aiplatform.v1.PipelineService.DeletePipelineJob].
• DeleteSavedQueryRequest
  Request message for [DatasetService.DeleteSavedQuery][google.cloud.aiplatform.v1.DatasetService.DeleteSavedQuery].
• DeleteScheduleRequest
  Request message for [ScheduleService.DeleteSchedule][google.cloud.aiplatform.v1.ScheduleService.DeleteSchedule].
• DeleteSpecialistPoolRequest
  Request message for [SpecialistPoolService.DeleteSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.DeleteSpecialistPool].
• DeleteStudyRequest
  Request message for [VizierService.DeleteStudy][google.cloud.aiplatform.v1.VizierService.DeleteStudy].
• DeleteTensorboardExperimentRequest
  Request message for [TensorboardService.DeleteTensorboardExperiment][google.cloud.aiplatform.v1.TensorboardService.DeleteTensorboardExperiment].
• DeleteTensorboardRequest
  Request message for [TensorboardService.DeleteTensorboard][google.cloud.aiplatform.v1.TensorboardService.DeleteTensorboard].
• DeleteTensorboardRunRequest
  Request message for [TensorboardService.DeleteTensorboardRun][google.cloud.aiplatform.v1.TensorboardService.DeleteTensorboardRun].
• DeleteTensorboardTimeSeriesRequest
  Request message for [TensorboardService.DeleteTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.DeleteTensorboardTimeSeries].
• DeleteTrainingPipelineRequest
  Request message for [PipelineService.DeleteTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.DeleteTrainingPipeline].
• DeleteTrialRequest
  Request message for [VizierService.DeleteTrial][google.cloud.aiplatform.v1.VizierService.DeleteTrial].
• DeployIndexOperationMetadata
  Runtime operation information for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.DeployIndex].
• DeployIndexRequest
  Request message for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.DeployIndex].
• DeployIndexResponse
  Response message for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.DeployIndex].
• DeployModelOperationMetadata
  Runtime operation information for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].
• DeployModelRequest
  Request message for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].
• DeployModelResponse
  Response message for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].
• DeployedIndex
  A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.
• DeployedIndexAuthConfig
  Used to set up the auth on the DeployedIndex’s private endpoint.
• DeployedIndexRef
  Points to a DeployedIndex.
• DeployedModel
  A deployment of a Model. Endpoints contain one or more DeployedModels.
• DeployedModelRef
  Points to a DeployedModel.
• DeploymentResourcePool
  A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.
• DestinationFeatureSetting
• DirectPredictRequest
  Request message for [PredictionService.DirectPredict][google.cloud.aiplatform.v1.PredictionService.DirectPredict].
• DirectPredictResponse
  Response message for [PredictionService.DirectPredict][google.cloud.aiplatform.v1.PredictionService.DirectPredict].
• DirectRawPredictRequest
  Request message for [PredictionService.DirectRawPredict][google.cloud.aiplatform.v1.PredictionService.DirectRawPredict].
• DirectRawPredictResponse
  Response message for [PredictionService.DirectRawPredict][google.cloud.aiplatform.v1.PredictionService.DirectRawPredict].
• DiskSpec
  Represents the spec of disk options.
• DoubleArray
  A list of double values.
• EncryptionSpec
  Represents a customer-managed encryption key spec that can be applied to a top-level resource.
• Endpoint
  Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.
• EntityIdSelector
  Selector for entityId. Getting ids from the given source.
• 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.
• EnvVar
  Represents an environment variable present in a Container or Python Module.
• ErrorAnalysisAnnotation
  Model error analysis for each annotation.
• EvaluateInstancesRequest
  Request message for EvaluationService.EvaluateInstances.
• EvaluateInstancesResponse
  Response message for EvaluationService.EvaluateInstances.
• EvaluatedAnnotation
  True positive, false positive, or false negative.
• EvaluatedAnnotationExplanation
  Explanation result of the prediction produced by the Model.
• Event
  An edge describing the relationship between an Artifact and an Execution in a lineage graph.
• ExactMatchInput
  Input for exact match metric.
• ExactMatchInstance
  Spec for exact match instance.
• ExactMatchMetricValue
  Exact match metric value for an instance.
• ExactMatchResults
  Results for exact match metric.
• ExactMatchSpec
  Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0.
• Examples
  Example-based explainability that returns the nearest neighbors from the provided dataset.
• ExamplesOverride
  Overrides for example-based explanations.
• ExamplesRestrictionsNamespace
  Restrictions namespace for example-based explanations overrides.
• Execution
  Instance of a general execution.
• ExplainRequest
  Request message for [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
• ExplainResponse
  Response message for [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
• Explanation
  Explanation of a prediction (provided in [PredictResponse.predictions][google.cloud.aiplatform.v1.PredictResponse.predictions]) produced by the Model on a given [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
• ExplanationMetadata
  Metadata describing the Model’s input and output for explanation.
• ExplanationMetadataOverride
  The [ExplanationMetadata][google.cloud.aiplatform.v1.ExplanationMetadata] entries that can be overridden at [online explanation][google.cloud.aiplatform.v1.PredictionService.Explain] time.
• ExplanationParameters
  Parameters to configure explaining for Model’s predictions.
• ExplanationSpec
  Specification of Model explanation.
• ExplanationSpecOverride
  The [ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec] entries that can be overridden at [online explanation][google.cloud.aiplatform.v1.PredictionService.Explain] time.
• ExportDataConfig
  Describes what part of the Dataset is to be exported, the destination of the export and how to export.
• ExportDataOperationMetadata
  Runtime operation information for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].
• ExportDataRequest
  Request message for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].
• ExportDataResponse
  Response message for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].
• ExportFeatureValuesOperationMetadata
  Details of operations that exports Features values.
• ExportFeatureValuesRequest
  Request message for [FeaturestoreService.ExportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ExportFeatureValues].
• ExportFeatureValuesResponse
  Response message for [FeaturestoreService.ExportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ExportFeatureValues].
• ExportFilterSplit
  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).
• 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.
• ExportModelOperationMetadata
  Details of [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel] operation.
• ExportModelRequest
  Request message for [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel].
• ExportModelResponse
  Response message of [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel] operation.
• ExportTensorboardTimeSeriesDataRequest
  Request message for [TensorboardService.ExportTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.ExportTensorboardTimeSeriesData].
• ExportTensorboardTimeSeriesDataResponse
  Response message for [TensorboardService.ExportTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.ExportTensorboardTimeSeriesData].
• Feature
  Feature Metadata information. For example, color is a feature that describes an apple.
• FeatureGroup
  Vertex AI Feature Group.
• 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.
• FeatureOnlineStore
  Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container.
• FeatureSelector
  Selector for Features of an EntityType.
• 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.
• FeatureValue
  Value for a feature.
• FeatureValueDestination
  A destination location for Feature values and format.
• FeatureValueList
  Container for list of values.
• FeatureView
  FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
• FeatureViewDataKey
  Lookup key for a feature view.
• FeatureViewSync
  FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store.
• 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.
• FeaturestoreMonitoringConfig
  Configuration of how features in Featurestore are monitored.
• FetchFeatureValuesRequest
  Request message for [FeatureOnlineStoreService.FetchFeatureValues][google.cloud.aiplatform.v1.FeatureOnlineStoreService.FetchFeatureValues]. All the features under the requested feature view will be returned.
• FetchFeatureValuesResponse
  Response message for [FeatureOnlineStoreService.FetchFeatureValues][google.cloud.aiplatform.v1.FeatureOnlineStoreService.FetchFeatureValues]
• FileData
  URI based data.
• 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).
• FindNeighborsRequest
  The request message for [MatchService.FindNeighbors][google.cloud.aiplatform.v1.MatchService.FindNeighbors].
• FindNeighborsResponse
  The response message for [MatchService.FindNeighbors][google.cloud.aiplatform.v1.MatchService.FindNeighbors].
• FluencyInput
  Input for fluency metric.
• FluencyInstance
  Spec for fluency instance.
• FluencyResult
  Spec for fluency result.
• FluencySpec
  Spec for fluency score metric.
• 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.
• FulfillmentInput
  Input for fulfillment metric.
• FulfillmentInstance
  Spec for fulfillment instance.
• FulfillmentResult
  Spec for fulfillment result.
• FulfillmentSpec
  Spec for fulfillment metric.
• FunctionCall
  A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values.
• FunctionCallingConfig
  Function calling config.
• FunctionDeclaration
  Structured representation of a function declaration as defined by the OpenAPI 3.0 specification. Included in this declaration are the function name and parameters. This FunctionDeclaration is a representation of a block of code that can be used as a Tool by the model and executed by the client.
• FunctionResponse
  The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction.
• GcsDestination
  The Google Cloud Storage location where the output is to be written to.
• GcsSource
  The Google Cloud Storage location for the input content.
• GenerateContentRequest
  Request message for [PredictionService.GenerateContent].
• GenerateContentResponse
  Response message for [PredictionService.GenerateContent].
• GenerationConfig
  Generation config.
• GenericOperationMetadata
  Generic Metadata shared by all operations.
• GenieSource
  Contains information about the source of the models generated from Generative AI Studio.
• GetAnnotationSpecRequest
  Request message for [DatasetService.GetAnnotationSpec][google.cloud.aiplatform.v1.DatasetService.GetAnnotationSpec].
• GetArtifactRequest
  Request message for [MetadataService.GetArtifact][google.cloud.aiplatform.v1.MetadataService.GetArtifact].
• GetBatchPredictionJobRequest
  Request message for [JobService.GetBatchPredictionJob][google.cloud.aiplatform.v1.JobService.GetBatchPredictionJob].
• GetContextRequest
  Request message for [MetadataService.GetContext][google.cloud.aiplatform.v1.MetadataService.GetContext].
• GetCustomJobRequest
  Request message for [JobService.GetCustomJob][google.cloud.aiplatform.v1.JobService.GetCustomJob].
• GetDataLabelingJobRequest
  Request message for [JobService.GetDataLabelingJob][google.cloud.aiplatform.v1.JobService.GetDataLabelingJob].
• GetDatasetRequest
  Request message for [DatasetService.GetDataset][google.cloud.aiplatform.v1.DatasetService.GetDataset].
• GetDatasetVersionRequest
  Request message for [DatasetService.GetDatasetVersion][google.cloud.aiplatform.v1.DatasetService.GetDatasetVersion].
• GetDeploymentResourcePoolRequest
  Request message for GetDeploymentResourcePool method.
• GetEndpointRequest
  Request message for [EndpointService.GetEndpoint][google.cloud.aiplatform.v1.EndpointService.GetEndpoint]
• GetEntityTypeRequest
  Request message for [FeaturestoreService.GetEntityType][google.cloud.aiplatform.v1.FeaturestoreService.GetEntityType].
• GetExecutionRequest
  Request message for [MetadataService.GetExecution][google.cloud.aiplatform.v1.MetadataService.GetExecution].
• GetFeatureGroupRequest
  Request message for [FeatureRegistryService.GetFeatureGroup][google.cloud.aiplatform.v1.FeatureRegistryService.GetFeatureGroup].
• GetFeatureOnlineStoreRequest
  Request message for [FeatureOnlineStoreAdminService.GetFeatureOnlineStore][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.GetFeatureOnlineStore].
• GetFeatureRequest
  Request message for [FeaturestoreService.GetFeature][google.cloud.aiplatform.v1.FeaturestoreService.GetFeature]. Request message for [FeatureRegistryService.GetFeature][google.cloud.aiplatform.v1.FeatureRegistryService.GetFeature].
• GetFeatureViewRequest
  Request message for [FeatureOnlineStoreAdminService.GetFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.GetFeatureView].
• GetFeatureViewSyncRequest
  Request message for [FeatureOnlineStoreAdminService.GetFeatureViewSync][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.GetFeatureViewSync].
• GetFeaturestoreRequest
  Request message for [FeaturestoreService.GetFeaturestore][google.cloud.aiplatform.v1.FeaturestoreService.GetFeaturestore].
• GetHyperparameterTuningJobRequest
  Request message for [JobService.GetHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.GetHyperparameterTuningJob].
• GetIndexEndpointRequest
  Request message for [IndexEndpointService.GetIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.GetIndexEndpoint]
• GetIndexRequest
  Request message for [IndexService.GetIndex][google.cloud.aiplatform.v1.IndexService.GetIndex]
• GetMetadataSchemaRequest
  Request message for [MetadataService.GetMetadataSchema][google.cloud.aiplatform.v1.MetadataService.GetMetadataSchema].
• GetMetadataStoreRequest
  Request message for [MetadataService.GetMetadataStore][google.cloud.aiplatform.v1.MetadataService.GetMetadataStore].
• GetModelDeploymentMonitoringJobRequest
  Request message for [JobService.GetModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.GetModelDeploymentMonitoringJob].
• GetModelEvaluationRequest
  Request message for [ModelService.GetModelEvaluation][google.cloud.aiplatform.v1.ModelService.GetModelEvaluation].
• GetModelEvaluationSliceRequest
  Request message for [ModelService.GetModelEvaluationSlice][google.cloud.aiplatform.v1.ModelService.GetModelEvaluationSlice].
• GetModelRequest
  Request message for [ModelService.GetModel][google.cloud.aiplatform.v1.ModelService.GetModel].
• GetNasJobRequest
  Request message for [JobService.GetNasJob][google.cloud.aiplatform.v1.JobService.GetNasJob].
• GetNasTrialDetailRequest
  Request message for [JobService.GetNasTrialDetail][google.cloud.aiplatform.v1.JobService.GetNasTrialDetail].
• GetNotebookExecutionJobRequest
  Request message for [NotebookService.GetNotebookExecutionJob]
• GetNotebookRuntimeRequest
  Request message for [NotebookService.GetNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.GetNotebookRuntime]
• GetNotebookRuntimeTemplateRequest
  Request message for [NotebookService.GetNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.GetNotebookRuntimeTemplate]
• GetPersistentResourceRequest
  Request message for [PersistentResourceService.GetPersistentResource][google.cloud.aiplatform.v1.PersistentResourceService.GetPersistentResource].
• GetPipelineJobRequest
  Request message for [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1.PipelineService.GetPipelineJob].
• GetPublisherModelRequest
  Request message for [ModelGardenService.GetPublisherModel][google.cloud.aiplatform.v1.ModelGardenService.GetPublisherModel]
• GetScheduleRequest
  Request message for [ScheduleService.GetSchedule][google.cloud.aiplatform.v1.ScheduleService.GetSchedule].
• GetSpecialistPoolRequest
  Request message for [SpecialistPoolService.GetSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.GetSpecialistPool].
• GetStudyRequest
  Request message for [VizierService.GetStudy][google.cloud.aiplatform.v1.VizierService.GetStudy].
• GetTensorboardExperimentRequest
  Request message for [TensorboardService.GetTensorboardExperiment][google.cloud.aiplatform.v1.TensorboardService.GetTensorboardExperiment].
• GetTensorboardRequest
  Request message for [TensorboardService.GetTensorboard][google.cloud.aiplatform.v1.TensorboardService.GetTensorboard].
• GetTensorboardRunRequest
  Request message for [TensorboardService.GetTensorboardRun][google.cloud.aiplatform.v1.TensorboardService.GetTensorboardRun].
• GetTensorboardTimeSeriesRequest
  Request message for [TensorboardService.GetTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.GetTensorboardTimeSeries].
• GetTrainingPipelineRequest
  Request message for [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.GetTrainingPipeline].
• GetTrialRequest
  Request message for [VizierService.GetTrial][google.cloud.aiplatform.v1.VizierService.GetTrial].
• GetTuningJobRequest
  Request message for [GenAiTuningService.GetTuningJob][google.cloud.aiplatform.v1.GenAiTuningService.GetTuningJob].
• GoogleSearchRetrieval
  Tool to retrieve public web data for grounding, powered by Google.
• GroundednessInput
  Input for groundedness metric.
• GroundednessInstance
  Spec for groundedness instance.
• GroundednessResult
  Spec for groundedness result.
• GroundednessSpec
  Spec for groundedness metric.
• GroundingChunk
  Grounding chunk.
• GroundingMetadata
  Metadata returned to client when grounding is enabled.
• GroundingSupport
  Grounding support.
• HyperparameterTuningJob
  Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.
• IdMatcher
  Matcher for Features of an EntityType by Feature ID.
• 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.
• ImportDataOperationMetadata
  Runtime operation information for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].
• ImportDataRequest
  Request message for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].
• ImportDataResponse
  Response message for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].
• ImportFeatureValuesOperationMetadata
  Details of operations that perform import Feature values.
• ImportFeatureValuesRequest
  Request message for [FeaturestoreService.ImportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ImportFeatureValues].
• ImportFeatureValuesResponse
  Response message for [FeaturestoreService.ImportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ImportFeatureValues].
• ImportModelEvaluationRequest
  Request message for [ModelService.ImportModelEvaluation][google.cloud.aiplatform.v1.ModelService.ImportModelEvaluation]
• 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.
• IndexDatapoint
  A datapoint of Index.
• IndexEndpoint
  Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.
• 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.
• IndexStats
  Stats of the Index.
• InputDataConfig
  Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.
• Int64Array
  A list of int64 values.
• 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
• LargeModelReference
  Contains information about the Large Model.
• LineageSubgraph
  A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.
• ListAnnotationsRequest
  Request message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].
• ListAnnotationsResponse
  Response message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].
• ListArtifactsRequest
  Request message for [MetadataService.ListArtifacts][google.cloud.aiplatform.v1.MetadataService.ListArtifacts].
• ListArtifactsResponse
  Response message for [MetadataService.ListArtifacts][google.cloud.aiplatform.v1.MetadataService.ListArtifacts].
• ListBatchPredictionJobsRequest
  Request message for [JobService.ListBatchPredictionJobs][google.cloud.aiplatform.v1.JobService.ListBatchPredictionJobs].
• ListBatchPredictionJobsResponse
  Response message for [JobService.ListBatchPredictionJobs][google.cloud.aiplatform.v1.JobService.ListBatchPredictionJobs]
• ListContextsRequest
  Request message for [MetadataService.ListContexts][google.cloud.aiplatform.v1.MetadataService.ListContexts]
• ListContextsResponse
  Response message for [MetadataService.ListContexts][google.cloud.aiplatform.v1.MetadataService.ListContexts].
• ListCustomJobsRequest
  Request message for [JobService.ListCustomJobs][google.cloud.aiplatform.v1.JobService.ListCustomJobs].
• ListCustomJobsResponse
  Response message for [JobService.ListCustomJobs][google.cloud.aiplatform.v1.JobService.ListCustomJobs]
• ListDataItemsRequest
  Request message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems].
• ListDataItemsResponse
  Response message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems].
• ListDataLabelingJobsRequest
  Request message for [JobService.ListDataLabelingJobs][google.cloud.aiplatform.v1.JobService.ListDataLabelingJobs].
• ListDataLabelingJobsResponse
  Response message for [JobService.ListDataLabelingJobs][google.cloud.aiplatform.v1.JobService.ListDataLabelingJobs].
• ListDatasetVersionsRequest
  Request message for [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1.DatasetService.ListDatasetVersions].
• ListDatasetVersionsResponse
  Response message for [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1.DatasetService.ListDatasetVersions].
• ListDatasetsRequest
  Request message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1.DatasetService.ListDatasets].
• ListDatasetsResponse
  Response message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1.DatasetService.ListDatasets].
• ListDeploymentResourcePoolsRequest
  Request message for ListDeploymentResourcePools method.
• ListDeploymentResourcePoolsResponse
  Response message for ListDeploymentResourcePools method.
• ListEndpointsRequest
  Request message for [EndpointService.ListEndpoints][google.cloud.aiplatform.v1.EndpointService.ListEndpoints].
• ListEndpointsResponse
  Response message for [EndpointService.ListEndpoints][google.cloud.aiplatform.v1.EndpointService.ListEndpoints].
• ListEntityTypesRequest
  Request message for [FeaturestoreService.ListEntityTypes][google.cloud.aiplatform.v1.FeaturestoreService.ListEntityTypes].
• ListEntityTypesResponse
  Response message for [FeaturestoreService.ListEntityTypes][google.cloud.aiplatform.v1.FeaturestoreService.ListEntityTypes].
• ListExecutionsRequest
  Request message for [MetadataService.ListExecutions][google.cloud.aiplatform.v1.MetadataService.ListExecutions].
• ListExecutionsResponse
  Response message for [MetadataService.ListExecutions][google.cloud.aiplatform.v1.MetadataService.ListExecutions].
• ListFeatureGroupsRequest
  Request message for [FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatureGroups].
• ListFeatureGroupsResponse
  Response message for [FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatureGroups].
• ListFeatureOnlineStoresRequest
  Request message for [FeatureOnlineStoreAdminService.ListFeatureOnlineStores][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureOnlineStores].
• ListFeatureOnlineStoresResponse
  Response message for [FeatureOnlineStoreAdminService.ListFeatureOnlineStores][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureOnlineStores].
• ListFeatureViewSyncsRequest
  Request message for [FeatureOnlineStoreAdminService.ListFeatureViewSyncs][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureViewSyncs].
• ListFeatureViewSyncsResponse
  Response message for [FeatureOnlineStoreAdminService.ListFeatureViewSyncs][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureViewSyncs].
• ListFeatureViewsRequest
  Request message for [FeatureOnlineStoreAdminService.ListFeatureViews][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureViews].
• ListFeatureViewsResponse
  Response message for [FeatureOnlineStoreAdminService.ListFeatureViews][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureViews].
• ListFeaturesRequest
  Request message for [FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures]. Request message for [FeatureRegistryService.ListFeatures][google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatures].
• ListFeaturesResponse
  Response message for [FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures]. Response message for [FeatureRegistryService.ListFeatures][google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatures].
• ListFeaturestoresRequest
  Request message for [FeaturestoreService.ListFeaturestores][google.cloud.aiplatform.v1.FeaturestoreService.ListFeaturestores].
• ListFeaturestoresResponse
  Response message for [FeaturestoreService.ListFeaturestores][google.cloud.aiplatform.v1.FeaturestoreService.ListFeaturestores].
• ListHyperparameterTuningJobsRequest
  Request message for [JobService.ListHyperparameterTuningJobs][google.cloud.aiplatform.v1.JobService.ListHyperparameterTuningJobs].
• ListHyperparameterTuningJobsResponse
  Response message for [JobService.ListHyperparameterTuningJobs][google.cloud.aiplatform.v1.JobService.ListHyperparameterTuningJobs]
• ListIndexEndpointsRequest
  Request message for [IndexEndpointService.ListIndexEndpoints][google.cloud.aiplatform.v1.IndexEndpointService.ListIndexEndpoints].
• ListIndexEndpointsResponse
  Response message for [IndexEndpointService.ListIndexEndpoints][google.cloud.aiplatform.v1.IndexEndpointService.ListIndexEndpoints].
• ListIndexesRequest
  Request message for [IndexService.ListIndexes][google.cloud.aiplatform.v1.IndexService.ListIndexes].
• ListIndexesResponse
  Response message for [IndexService.ListIndexes][google.cloud.aiplatform.v1.IndexService.ListIndexes].
• ListMetadataSchemasRequest
  Request message for [MetadataService.ListMetadataSchemas][google.cloud.aiplatform.v1.MetadataService.ListMetadataSchemas].
• ListMetadataSchemasResponse
  Response message for [MetadataService.ListMetadataSchemas][google.cloud.aiplatform.v1.MetadataService.ListMetadataSchemas].
• ListMetadataStoresRequest
  Request message for [MetadataService.ListMetadataStores][google.cloud.aiplatform.v1.MetadataService.ListMetadataStores].
• ListMetadataStoresResponse
  Response message for [MetadataService.ListMetadataStores][google.cloud.aiplatform.v1.MetadataService.ListMetadataStores].
• ListModelDeploymentMonitoringJobsRequest
  Request message for [JobService.ListModelDeploymentMonitoringJobs][google.cloud.aiplatform.v1.JobService.ListModelDeploymentMonitoringJobs].
• ListModelDeploymentMonitoringJobsResponse
  Response message for [JobService.ListModelDeploymentMonitoringJobs][google.cloud.aiplatform.v1.JobService.ListModelDeploymentMonitoringJobs].
• ListModelEvaluationSlicesRequest
  Request message for [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.ListModelEvaluationSlices].
• ListModelEvaluationSlicesResponse
  Response message for [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.ListModelEvaluationSlices].
• ListModelEvaluationsRequest
  Request message for [ModelService.ListModelEvaluations][google.cloud.aiplatform.v1.ModelService.ListModelEvaluations].
• ListModelEvaluationsResponse
  Response message for [ModelService.ListModelEvaluations][google.cloud.aiplatform.v1.ModelService.ListModelEvaluations].
• ListModelVersionsRequest
  Request message for [ModelService.ListModelVersions][google.cloud.aiplatform.v1.ModelService.ListModelVersions].
• ListModelVersionsResponse
  Response message for [ModelService.ListModelVersions][google.cloud.aiplatform.v1.ModelService.ListModelVersions]
• ListModelsRequest
  Request message for [ModelService.ListModels][google.cloud.aiplatform.v1.ModelService.ListModels].
• ListModelsResponse
  Response message for [ModelService.ListModels][google.cloud.aiplatform.v1.ModelService.ListModels]
• ListNasJobsRequest
  Request message for [JobService.ListNasJobs][google.cloud.aiplatform.v1.JobService.ListNasJobs].
• ListNasJobsResponse
  Response message for [JobService.ListNasJobs][google.cloud.aiplatform.v1.JobService.ListNasJobs]
• ListNasTrialDetailsRequest
  Request message for [JobService.ListNasTrialDetails][google.cloud.aiplatform.v1.JobService.ListNasTrialDetails].
• ListNasTrialDetailsResponse
  Response message for [JobService.ListNasTrialDetails][google.cloud.aiplatform.v1.JobService.ListNasTrialDetails]
• ListNotebookExecutionJobsRequest
  Request message for [NotebookService.ListNotebookExecutionJobs]
• ListNotebookExecutionJobsResponse
  Response message for [NotebookService.CreateNotebookExecutionJob]
• ListNotebookRuntimeTemplatesRequest
  Request message for [NotebookService.ListNotebookRuntimeTemplates][google.cloud.aiplatform.v1.NotebookService.ListNotebookRuntimeTemplates].
• ListNotebookRuntimeTemplatesResponse
  Response message for [NotebookService.ListNotebookRuntimeTemplates][google.cloud.aiplatform.v1.NotebookService.ListNotebookRuntimeTemplates].
• ListNotebookRuntimesRequest
  Request message for [NotebookService.ListNotebookRuntimes][google.cloud.aiplatform.v1.NotebookService.ListNotebookRuntimes].
• ListNotebookRuntimesResponse
  Response message for [NotebookService.ListNotebookRuntimes][google.cloud.aiplatform.v1.NotebookService.ListNotebookRuntimes].
• ListOptimalTrialsRequest
  Request message for [VizierService.ListOptimalTrials][google.cloud.aiplatform.v1.VizierService.ListOptimalTrials].
• ListOptimalTrialsResponse
  Response message for [VizierService.ListOptimalTrials][google.cloud.aiplatform.v1.VizierService.ListOptimalTrials].
• ListPersistentResourcesRequest
  Request message for [PersistentResourceService.ListPersistentResource][].
• ListPersistentResourcesResponse
  Response message for [PersistentResourceService.ListPersistentResources][google.cloud.aiplatform.v1.PersistentResourceService.ListPersistentResources]
• ListPipelineJobsRequest
  Request message for [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1.PipelineService.ListPipelineJobs].
• ListPipelineJobsResponse
  Response message for [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1.PipelineService.ListPipelineJobs]
• ListSavedQueriesRequest
  Request message for [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1.DatasetService.ListSavedQueries].
• ListSavedQueriesResponse
  Response message for [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1.DatasetService.ListSavedQueries].
• ListSchedulesRequest
  Request message for [ScheduleService.ListSchedules][google.cloud.aiplatform.v1.ScheduleService.ListSchedules].
• ListSchedulesResponse
  Response message for [ScheduleService.ListSchedules][google.cloud.aiplatform.v1.ScheduleService.ListSchedules]
• ListSpecialistPoolsRequest
  Request message for [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1.SpecialistPoolService.ListSpecialistPools].
• ListSpecialistPoolsResponse
  Response message for [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1.SpecialistPoolService.ListSpecialistPools].
• ListStudiesRequest
  Request message for [VizierService.ListStudies][google.cloud.aiplatform.v1.VizierService.ListStudies].
• ListStudiesResponse
  Response message for [VizierService.ListStudies][google.cloud.aiplatform.v1.VizierService.ListStudies].
• ListTensorboardExperimentsRequest
  Request message for [TensorboardService.ListTensorboardExperiments][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardExperiments].
• ListTensorboardExperimentsResponse
  Response message for [TensorboardService.ListTensorboardExperiments][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardExperiments].
• ListTensorboardRunsRequest
  Request message for [TensorboardService.ListTensorboardRuns][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardRuns].
• ListTensorboardRunsResponse
  Response message for [TensorboardService.ListTensorboardRuns][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardRuns].
• ListTensorboardTimeSeriesRequest
  Request message for [TensorboardService.ListTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardTimeSeries].
• ListTensorboardTimeSeriesResponse
  Response message for [TensorboardService.ListTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardTimeSeries].
• ListTensorboardsRequest
  Request message for [TensorboardService.ListTensorboards][google.cloud.aiplatform.v1.TensorboardService.ListTensorboards].
• ListTensorboardsResponse
  Response message for [TensorboardService.ListTensorboards][google.cloud.aiplatform.v1.TensorboardService.ListTensorboards].
• ListTrainingPipelinesRequest
  Request message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines].
• ListTrainingPipelinesResponse
  Response message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines]
• ListTrialsRequest
  Request message for [VizierService.ListTrials][google.cloud.aiplatform.v1.VizierService.ListTrials].
• ListTrialsResponse
  Response message for [VizierService.ListTrials][google.cloud.aiplatform.v1.VizierService.ListTrials].
• ListTuningJobsRequest
  Request message for [GenAiTuningService.ListTuningJobs][google.cloud.aiplatform.v1.GenAiTuningService.ListTuningJobs].
• ListTuningJobsResponse
  Response message for [GenAiTuningService.ListTuningJobs][google.cloud.aiplatform.v1.GenAiTuningService.ListTuningJobs]
• LookupStudyRequest
  Request message for [VizierService.LookupStudy][google.cloud.aiplatform.v1.VizierService.LookupStudy].
• MachineSpec
  Specification of a single machine.
• ManualBatchTuningParameters
  Manual batch tuning parameters.
• Measurement
  A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.
• MergeVersionAliasesRequest
  Request message for [ModelService.MergeVersionAliases][google.cloud.aiplatform.v1.ModelService.MergeVersionAliases].
• MetadataSchema
  Instance of a general MetadataSchema.
• MetadataStore
  Instance of a metadata store. Contains a set of metadata that can be queried.
• MigratableResource
  Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.
• MigrateResourceRequest
  Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
• MigrateResourceResponse
  Describes a successfully migrated resource.
• Model
  A trained machine learning Model.
• ModelContainerSpec
  Specification of a container for serving predictions. Some fields in this message correspond to fields in the Kubernetes Container v1 core specification.
• ModelDeploymentMonitoringBigQueryTable
  ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.
• ModelDeploymentMonitoringJob
  Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.
• ModelDeploymentMonitoringObjectiveConfig
  ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.
• ModelDeploymentMonitoringScheduleConfig
  The config for scheduling monitoring job.
• ModelEvaluation
  A collection of metrics calculated by comparing Model’s predictions on all of the test data against annotations from the test data.
• ModelEvaluationSlice
  A collection of metrics calculated by comparing Model’s predictions on a slice of the test data against ground truth annotations.
• ModelExplanation
  Aggregated explanation metrics for a Model over a set of instances.
• ModelGardenSource
  Contains information about the source of the models generated from Model Garden.
• ModelMonitoringAlertConfig
  The alert config for model monitoring.
• ModelMonitoringObjectiveConfig
  The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.
• ModelMonitoringStatsAnomalies
  Statistics and anomalies generated by Model Monitoring.
• ModelSourceInfo
  Detail description of the source information of the model.
• MutateDeployedIndexOperationMetadata
  Runtime operation information for [IndexEndpointService.MutateDeployedIndex][google.cloud.aiplatform.v1.IndexEndpointService.MutateDeployedIndex].
• MutateDeployedIndexRequest
  Request message for [IndexEndpointService.MutateDeployedIndex][google.cloud.aiplatform.v1.IndexEndpointService.MutateDeployedIndex].
• MutateDeployedIndexResponse
  Response message for [IndexEndpointService.MutateDeployedIndex][google.cloud.aiplatform.v1.IndexEndpointService.MutateDeployedIndex].
• MutateDeployedModelOperationMetadata
  Runtime operation information for [EndpointService.MutateDeployedModel][google.cloud.aiplatform.v1.EndpointService.MutateDeployedModel].
• MutateDeployedModelRequest
  Request message for [EndpointService.MutateDeployedModel][google.cloud.aiplatform.v1.EndpointService.MutateDeployedModel].
• MutateDeployedModelResponse
  Response message for [EndpointService.MutateDeployedModel][google.cloud.aiplatform.v1.EndpointService.MutateDeployedModel].
• NasJob
  Represents a Neural Architecture Search (NAS) job.
• NasJobOutput
  Represents a uCAIP NasJob output.
• NasJobSpec
  Represents the spec of a NasJob.
• NasTrial
  Represents a uCAIP NasJob trial.
• NasTrialDetail
  Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.
• NearestNeighborQuery
  A query to find a number of similar entities.
• NearestNeighborSearchOperationMetadata
  Runtime operation metadata with regard to Matching Engine Index.
• NearestNeighbors
  Nearest neighbors for one query.
• Neighbor
  Neighbors for example-based explanations.
• NetworkSpec
  Network spec.
• NfsMount
  Represents a mount configuration for Network File System (NFS) to mount.
• NotebookEucConfig
  The euc configuration of NotebookRuntimeTemplate.
• NotebookExecutionJob
  NotebookExecutionJob represents an instance of a notebook execution.
• NotebookIdleShutdownConfig
  The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.
• NotebookRuntime
  A runtime is a virtual machine allocated to a particular user for a particular Notebook file on temporary basis with lifetime limited to 24 hours.
• NotebookRuntimeTemplate
  A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template.
• NotebookRuntimeTemplateRef
  Points to a NotebookRuntimeTemplateRef.
• PairwiseMetricInput
  Input for pairwise metric.
• PairwiseMetricInstance
  Pairwise metric instance. Usually one instance corresponds to one row in an evaluation dataset.
• PairwiseMetricResult
  Spec for pairwise metric result.
• PairwiseMetricSpec
  Spec for pairwise metric.
• PairwiseQuestionAnsweringQualityInput
  Input for pairwise question answering quality metric.
• PairwiseQuestionAnsweringQualityInstance
  Spec for pairwise question answering quality instance.
• PairwiseQuestionAnsweringQualityResult
  Spec for pairwise question answering quality result.
• PairwiseQuestionAnsweringQualitySpec
  Spec for pairwise question answering quality score metric.
• PairwiseSummarizationQualityInput
  Input for pairwise summarization quality metric.
• PairwiseSummarizationQualityInstance
  Spec for pairwise summarization quality instance.
• PairwiseSummarizationQualityResult
  Spec for pairwise summarization quality result.
• PairwiseSummarizationQualitySpec
  Spec for pairwise summarization quality score metric.
• Part
  A datatype containing media that is part of a multi-part Content message.
• PauseModelDeploymentMonitoringJobRequest
  Request message for [JobService.PauseModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.PauseModelDeploymentMonitoringJob].
• PauseScheduleRequest
  Request message for [ScheduleService.PauseSchedule][google.cloud.aiplatform.v1.ScheduleService.PauseSchedule].
• PersistentDiskSpec
  Represents the spec of [persistent disk][https://cloud.google.com/compute/docs/disks/persistent-disks] options.
• PersistentResource
  Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec.
• PipelineJob
  An instance of a machine learning PipelineJob.
• PipelineJobDetail
  The runtime detail of PipelineJob.
• PipelineTaskDetail
  The runtime detail of a task execution.
• PipelineTaskExecutorDetail
  The runtime detail of a pipeline executor.
• PipelineTemplateMetadata
  Pipeline template metadata if [PipelineJob.template_uri][google.cloud.aiplatform.v1.PipelineJob.template_uri] is from supported template registry. Currently, the only supported registry is Artifact Registry.
• PointwiseMetricInput
  Input for pointwise metric.
• PointwiseMetricInstance
  Pointwise metric instance. Usually one instance corresponds to one row in an evaluation dataset.
• PointwiseMetricResult
  Spec for pointwise metric result.
• PointwiseMetricSpec
  Spec for pointwise metric.
• Port
  Represents a network port in a container.
• PredefinedSplit
  Assigns input data to training, validation, and test sets based on the value of a provided key.
• PredictRequest
  Request message for [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict].
• PredictRequestResponseLoggingConfig
  Configuration for logging request-response to a BigQuery table.
• PredictResponse
  Response message for [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict].
• PredictSchemata
  Contains the schemata used in Model’s predictions and explanations via [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict], [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain] and [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].
• Presets
  Preset configuration for example-based explanations
• PrivateEndpoints
  PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.
• PrivateServiceConnectConfig
  Represents configuration for private service connect.
• Probe
  Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.
• PscAutomatedEndpoints
  PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig.
• PublisherModel
  A Model Garden Publisher Model.
• PurgeArtifactsMetadata
  Details of operations that perform [MetadataService.PurgeArtifacts][google.cloud.aiplatform.v1.MetadataService.PurgeArtifacts].
• PurgeArtifactsRequest
  Request message for [MetadataService.PurgeArtifacts][google.cloud.aiplatform.v1.MetadataService.PurgeArtifacts].
• PurgeArtifactsResponse
  Response message for [MetadataService.PurgeArtifacts][google.cloud.aiplatform.v1.MetadataService.PurgeArtifacts].
• PurgeContextsMetadata
  Details of operations that perform [MetadataService.PurgeContexts][google.cloud.aiplatform.v1.MetadataService.PurgeContexts].
• PurgeContextsRequest
  Request message for [MetadataService.PurgeContexts][google.cloud.aiplatform.v1.MetadataService.PurgeContexts].
• PurgeContextsResponse
  Response message for [MetadataService.PurgeContexts][google.cloud.aiplatform.v1.MetadataService.PurgeContexts].
• PurgeExecutionsMetadata
  Details of operations that perform [MetadataService.PurgeExecutions][google.cloud.aiplatform.v1.MetadataService.PurgeExecutions].
• PurgeExecutionsRequest
  Request message for [MetadataService.PurgeExecutions][google.cloud.aiplatform.v1.MetadataService.PurgeExecutions].
• PurgeExecutionsResponse
  Response message for [MetadataService.PurgeExecutions][google.cloud.aiplatform.v1.MetadataService.PurgeExecutions].
• PythonPackageSpec
  The spec of a Python packaged code.
• QueryArtifactLineageSubgraphRequest
  Request message for [MetadataService.QueryArtifactLineageSubgraph][google.cloud.aiplatform.v1.MetadataService.QueryArtifactLineageSubgraph].
• QueryContextLineageSubgraphRequest
  Request message for [MetadataService.QueryContextLineageSubgraph][google.cloud.aiplatform.v1.MetadataService.QueryContextLineageSubgraph].
• QueryDeployedModelsRequest
  Request message for QueryDeployedModels method.
• QueryDeployedModelsResponse
  Response message for QueryDeployedModels method.
• QueryExecutionInputsAndOutputsRequest
  Request message for [MetadataService.QueryExecutionInputsAndOutputs][google.cloud.aiplatform.v1.MetadataService.QueryExecutionInputsAndOutputs].
• QuestionAnsweringCorrectnessInput
  Input for question answering correctness metric.
• QuestionAnsweringCorrectnessInstance
  Spec for question answering correctness instance.
• QuestionAnsweringCorrectnessResult
  Spec for question answering correctness result.
• QuestionAnsweringCorrectnessSpec
  Spec for question answering correctness metric.
• QuestionAnsweringHelpfulnessInput
  Input for question answering helpfulness metric.
• QuestionAnsweringHelpfulnessInstance
  Spec for question answering helpfulness instance.
• QuestionAnsweringHelpfulnessResult
  Spec for question answering helpfulness result.
• QuestionAnsweringHelpfulnessSpec
  Spec for question answering helpfulness metric.
• QuestionAnsweringQualityInput
  Input for question answering quality metric.
• QuestionAnsweringQualityInstance
  Spec for question answering quality instance.
• QuestionAnsweringQualityResult
  Spec for question answering quality result.
• QuestionAnsweringQualitySpec
  Spec for question answering quality score metric.
• QuestionAnsweringRelevanceInput
  Input for question answering relevance metric.
• QuestionAnsweringRelevanceInstance
  Spec for question answering relevance instance.
• QuestionAnsweringRelevanceResult
  Spec for question answering relevance result.
• QuestionAnsweringRelevanceSpec
  Spec for question answering relevance metric.
• RawPredictRequest
  Request message for [PredictionService.RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict].
• RayLogsSpec
  Configuration for the Ray OSS Logs.
• RayMetricSpec
  Configuration for the Ray metrics.
• RaySpec
  Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes.
• ReadFeatureValuesRequest
  Request message for [FeaturestoreOnlineServingService.ReadFeatureValues][google.cloud.aiplatform.v1.FeaturestoreOnlineServingService.ReadFeatureValues].
• ReadFeatureValuesResponse
  Response message for [FeaturestoreOnlineServingService.ReadFeatureValues][google.cloud.aiplatform.v1.FeaturestoreOnlineServingService.ReadFeatureValues].
• ReadIndexDatapointsRequest
  The request message for [MatchService.ReadIndexDatapoints][google.cloud.aiplatform.v1.MatchService.ReadIndexDatapoints].
• ReadIndexDatapointsResponse
  The response message for [MatchService.ReadIndexDatapoints][google.cloud.aiplatform.v1.MatchService.ReadIndexDatapoints].
• ReadTensorboardBlobDataRequest
  Request message for [TensorboardService.ReadTensorboardBlobData][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardBlobData].
• ReadTensorboardBlobDataResponse
  Response message for [TensorboardService.ReadTensorboardBlobData][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardBlobData].
• ReadTensorboardSizeRequest
  Request message for [TensorboardService.ReadTensorboardSize][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardSize].
• ReadTensorboardSizeResponse
  Response message for [TensorboardService.ReadTensorboardSize][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardSize].
• ReadTensorboardTimeSeriesDataRequest
  Request message for [TensorboardService.ReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardTimeSeriesData].
• ReadTensorboardTimeSeriesDataResponse
  Response message for [TensorboardService.ReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardTimeSeriesData].
• ReadTensorboardUsageRequest
  Request message for [TensorboardService.ReadTensorboardUsage][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardUsage].
• ReadTensorboardUsageResponse
  Response message for [TensorboardService.ReadTensorboardUsage][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardUsage].
• RebootPersistentResourceOperationMetadata
  Details of operations that perform reboot PersistentResource.
• RebootPersistentResourceRequest
  Request message for [PersistentResourceService.RebootPersistentResource][google.cloud.aiplatform.v1.PersistentResourceService.RebootPersistentResource].
• RemoveContextChildrenRequest
  Request message for [MetadataService.DeleteContextChildrenRequest][].
• RemoveContextChildrenResponse
  Response message for [MetadataService.RemoveContextChildren][google.cloud.aiplatform.v1.MetadataService.RemoveContextChildren].
• RemoveDatapointsRequest
  Request message for [IndexService.RemoveDatapoints][google.cloud.aiplatform.v1.IndexService.RemoveDatapoints]
• RemoveDatapointsResponse
  Response message for [IndexService.RemoveDatapoints][google.cloud.aiplatform.v1.IndexService.RemoveDatapoints]
• ReservationAffinity
  A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity.
• ResourcePool
  Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource.
• ResourceRuntime
  Persistent Cluster runtime information as output
• ResourceRuntimeSpec
  Configuration for the runtime on a PersistentResource instance, including but not limited to:
• ResourcesConsumed
  Statistics information about resource consumption.
• RestoreDatasetVersionOperationMetadata
  Runtime operation information for [DatasetService.RestoreDatasetVersion][google.cloud.aiplatform.v1.DatasetService.RestoreDatasetVersion].
• RestoreDatasetVersionRequest
  Request message for [DatasetService.RestoreDatasetVersion][google.cloud.aiplatform.v1.DatasetService.RestoreDatasetVersion].
• ResumeModelDeploymentMonitoringJobRequest
  Request message for [JobService.ResumeModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.ResumeModelDeploymentMonitoringJob].
• ResumeScheduleRequest
  Request message for [ScheduleService.ResumeSchedule][google.cloud.aiplatform.v1.ScheduleService.ResumeSchedule].
• Retrieval
  Defines a retrieval tool that model can call to access external knowledge.
• RougeInput
  Input for rouge metric.
• RougeInstance
  Spec for rouge instance.
• RougeMetricValue
  Rouge metric value for an instance.
• RougeResults
  Results for rouge metric.
• RougeSpec
  Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1.
• SafetyInput
  Input for safety metric.
• SafetyInstance
  Spec for safety instance.
• SafetyRating
  Safety rating corresponding to the generated content.
• SafetyResult
  Spec for safety result.
• SafetySetting
  Safety settings.
• SafetySpec
  Spec for safety metric.
• SampleConfig
  Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
• SampledShapleyAttribution
  An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.
• SamplingStrategy
  Sampling Strategy for logging, can be for both training and prediction dataset.
• SavedQuery
  A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
• Scalar
  One point viewable on a scalar metric plot.
• Schedule
  An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
• Scheduling
  All parameters related to queuing and scheduling of custom jobs.
• Schema
  Schema is used to define the format of input/output data. Represents a select subset of an OpenAPI 3.0 schema object. More fields may be added in the future as needed.
• SearchDataItemsRequest
  Request message for [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
• SearchDataItemsResponse
  Response message for [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
• SearchEntryPoint
  Google search entry point.
• SearchFeaturesRequest
  Request message for [FeaturestoreService.SearchFeatures][google.cloud.aiplatform.v1.FeaturestoreService.SearchFeatures].
• SearchFeaturesResponse
  Response message for [FeaturestoreService.SearchFeatures][google.cloud.aiplatform.v1.FeaturestoreService.SearchFeatures].
• SearchMigratableResourcesRequest
  Request message for [MigrationService.SearchMigratableResources][google.cloud.aiplatform.v1.MigrationService.SearchMigratableResources].
• SearchMigratableResourcesResponse
  Response message for [MigrationService.SearchMigratableResources][google.cloud.aiplatform.v1.MigrationService.SearchMigratableResources].
• SearchModelDeploymentMonitoringStatsAnomaliesRequest
  Request message for [JobService.SearchModelDeploymentMonitoringStatsAnomalies][google.cloud.aiplatform.v1.JobService.SearchModelDeploymentMonitoringStatsAnomalies].
• SearchModelDeploymentMonitoringStatsAnomaliesResponse
  Response message for [JobService.SearchModelDeploymentMonitoringStatsAnomalies][google.cloud.aiplatform.v1.JobService.SearchModelDeploymentMonitoringStatsAnomalies].
• SearchNearestEntitiesRequest
  The request message for [FeatureOnlineStoreService.SearchNearestEntities][google.cloud.aiplatform.v1.FeatureOnlineStoreService.SearchNearestEntities].
• SearchNearestEntitiesResponse
  Response message for [FeatureOnlineStoreService.SearchNearestEntities][google.cloud.aiplatform.v1.FeatureOnlineStoreService.SearchNearestEntities]
• Segment
  Segment of the content.
• ServiceAccountSpec
  Configuration for the use of custom service account to run the workloads.
• ShieldedVmConfig
  A set of Shielded Instance options. See Images using supported Shielded VM features.
• SmoothGradConfig
  Config for SmoothGrad approximation of gradients.
• SpecialistPool
  SpecialistPool represents customers’ own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers’ data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console.
• StartNotebookRuntimeOperationMetadata
  Metadata information for [NotebookService.StartNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.StartNotebookRuntime].
• StartNotebookRuntimeRequest
  Request message for [NotebookService.StartNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.StartNotebookRuntime].
• StartNotebookRuntimeResponse
  Response message for [NotebookService.StartNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.StartNotebookRuntime].
• StopTrialRequest
  Request message for [VizierService.StopTrial][google.cloud.aiplatform.v1.VizierService.StopTrial].
• StratifiedSplit
  Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the key field) is mirrored within each split. The fraction values determine the relative sizes of the splits.
• StreamDirectPredictRequest
  Request message for [PredictionService.StreamDirectPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectPredict].
• StreamDirectPredictResponse
  Response message for [PredictionService.StreamDirectPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectPredict].
• StreamDirectRawPredictRequest
  Request message for [PredictionService.StreamDirectRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectRawPredict].
• StreamDirectRawPredictResponse
  Response message for [PredictionService.StreamDirectRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectRawPredict].
• StreamRawPredictRequest
  Request message for [PredictionService.StreamRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamRawPredict].
• StreamingPredictRequest
  Request message for [PredictionService.StreamingPredict][google.cloud.aiplatform.v1.PredictionService.StreamingPredict].
• StreamingPredictResponse
  Response message for [PredictionService.StreamingPredict][google.cloud.aiplatform.v1.PredictionService.StreamingPredict].
• StreamingRawPredictRequest
  Request message for [PredictionService.StreamingRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamingRawPredict].
• StreamingRawPredictResponse
  Response message for [PredictionService.StreamingRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamingRawPredict].
• StreamingReadFeatureValuesRequest
  Request message for [FeaturestoreOnlineServingService.StreamingFeatureValuesRead][].
• StringArray
  A list of string values.
• StructFieldValue
  One field of a Struct (or object) type feature value.
• StructValue
  Struct (or object) type feature value.
• Study
  A message representing a Study.
• StudySpec
  Represents specification of a Study.
• StudyTimeConstraint
  Time-based Constraint for Study
• SuggestTrialsMetadata
  Details of operations that perform Trials suggestion.
• SuggestTrialsRequest
  Request message for [VizierService.SuggestTrials][google.cloud.aiplatform.v1.VizierService.SuggestTrials].
• SuggestTrialsResponse
  Response message for [VizierService.SuggestTrials][google.cloud.aiplatform.v1.VizierService.SuggestTrials].
• SummarizationHelpfulnessInput
  Input for summarization helpfulness metric.
• SummarizationHelpfulnessInstance
  Spec for summarization helpfulness instance.
• SummarizationHelpfulnessResult
  Spec for summarization helpfulness result.
• SummarizationHelpfulnessSpec
  Spec for summarization helpfulness score metric.
• SummarizationQualityInput
  Input for summarization quality metric.
• SummarizationQualityInstance
  Spec for summarization quality instance.
• SummarizationQualityResult
  Spec for summarization quality result.
• SummarizationQualitySpec
  Spec for summarization quality score metric.
• SummarizationVerbosityInput
  Input for summarization verbosity metric.
• SummarizationVerbosityInstance
  Spec for summarization verbosity instance.
• SummarizationVerbosityResult
  Spec for summarization verbosity result.
• SummarizationVerbositySpec
  Spec for summarization verbosity score metric.
• SupervisedHyperParameters
  Hyperparameters for SFT.
• SupervisedTuningDataStats
  Tuning data statistics for Supervised Tuning.
• SupervisedTuningDatasetDistribution
  Dataset distribution for Supervised Tuning.
• SupervisedTuningSpec
  Tuning Spec for Supervised Tuning.
• SyncFeatureViewRequest
  Request message for [FeatureOnlineStoreAdminService.SyncFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.SyncFeatureView].
• SyncFeatureViewResponse
  Respose message for [FeatureOnlineStoreAdminService.SyncFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.SyncFeatureView].
• Tensor
  A tensor value type.
• Tensorboard
  Tensorboard is a physical database that stores users’ training metrics. A default Tensorboard is provided in each region of a Google Cloud project. If needed users can also create extra Tensorboards in their projects.
• TensorboardBlob
  One blob (e.g, image, graph) viewable on a blob metric plot.
• TensorboardBlobSequence
  One point viewable on a blob metric plot, but mostly just a wrapper message to work around repeated fields can’t be used directly within oneof fields.
• TensorboardExperiment
  A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.
• TensorboardRun
  TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
• TensorboardTensor
  One point viewable on a tensor metric plot.
• TensorboardTimeSeries
  TensorboardTimeSeries maps to times series produced in training runs
• TfRecordDestination
  The storage details for TFRecord output content.
• ThresholdConfig
  The config for feature monitoring threshold.
• TimeSeriesData
  All the data stored in a TensorboardTimeSeries.
• TimeSeriesDataPoint
  A TensorboardTimeSeries data point.
• TimestampSplit
  Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set.
• TokensInfo
  Tokens info with a list of tokens and the corresponding list of token ids.
• Tool
  Tool details that the model may use to generate response.
• ToolCallValidInput
  Input for tool call valid metric.
• ToolCallValidInstance
  Spec for tool call valid instance.
• ToolCallValidMetricValue
  Tool call valid metric value for an instance.
• ToolCallValidResults
  Results for tool call valid metric.
• ToolCallValidSpec
  Spec for tool call valid metric.
• ToolConfig
  Tool config. This config is shared for all tools provided in the request.
• ToolNameMatchInput
  Input for tool name match metric.
• ToolNameMatchInstance
  Spec for tool name match instance.
• ToolNameMatchMetricValue
  Tool name match metric value for an instance.
• ToolNameMatchResults
  Results for tool name match metric.
• ToolNameMatchSpec
  Spec for tool name match metric.
• ToolParameterKeyMatchInput
  Input for tool parameter key match metric.
• ToolParameterKeyMatchInstance
  Spec for tool parameter key match instance.
• ToolParameterKeyMatchMetricValue
  Tool parameter key match metric value for an instance.
• ToolParameterKeyMatchResults
  Results for tool parameter key match metric.
• ToolParameterKeyMatchSpec
  Spec for tool parameter key match metric.
• ToolParameterKvMatchInput
  Input for tool parameter key value match metric.
• ToolParameterKvMatchInstance
  Spec for tool parameter key value match instance.
• ToolParameterKvMatchMetricValue
  Tool parameter key value match metric value for an instance.
• ToolParameterKvMatchResults
  Results for tool parameter key value match metric.
• ToolParameterKvMatchSpec
  Spec for tool parameter key value match metric.
• TrainingConfig
  CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
• TrainingPipeline
  The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI’s Dataset which becomes the training input, [upload][google.cloud.aiplatform.v1.ModelService.UploadModel] the Model to Vertex AI, and evaluate the Model.
• Trial
  A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.
• TrialContext
• TunedModel
  The Model Registry Model and Online Prediction Endpoint assiociated with this [TuningJob][google.cloud.aiplatform.v1.TuningJob].
• TuningDataStats
  The tuning data statistic values for [TuningJob][google.cloud.aiplatform.v1.TuningJob].
• TuningJob
  Represents a TuningJob that runs with Google owned models.
• UndeployIndexOperationMetadata
  Runtime operation information for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.UndeployIndex].
• UndeployIndexRequest
  Request message for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.UndeployIndex].
• UndeployIndexResponse
  Response message for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.UndeployIndex].
• UndeployModelOperationMetadata
  Runtime operation information for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].
• UndeployModelRequest
  Request message for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].
• UndeployModelResponse
  Response message for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].
• UnmanagedContainerModel
  Contains model information necessary to perform batch prediction without requiring a full model import.
• UpdateArtifactRequest
  Request message for [MetadataService.UpdateArtifact][google.cloud.aiplatform.v1.MetadataService.UpdateArtifact].
• UpdateContextRequest
  Request message for [MetadataService.UpdateContext][google.cloud.aiplatform.v1.MetadataService.UpdateContext].
• UpdateDatasetRequest
  Request message for [DatasetService.UpdateDataset][google.cloud.aiplatform.v1.DatasetService.UpdateDataset].
• UpdateDatasetVersionRequest
  Request message for [DatasetService.UpdateDatasetVersion][google.cloud.aiplatform.v1.DatasetService.UpdateDatasetVersion].
• UpdateDeploymentResourcePoolOperationMetadata
  Runtime operation information for UpdateDeploymentResourcePool method.
• UpdateDeploymentResourcePoolRequest
  Request message for UpdateDeploymentResourcePool method.
• UpdateEndpointRequest
  Request message for [EndpointService.UpdateEndpoint][google.cloud.aiplatform.v1.EndpointService.UpdateEndpoint].
• UpdateEntityTypeRequest
  Request message for [FeaturestoreService.UpdateEntityType][google.cloud.aiplatform.v1.FeaturestoreService.UpdateEntityType].
• UpdateExecutionRequest
  Request message for [MetadataService.UpdateExecution][google.cloud.aiplatform.v1.MetadataService.UpdateExecution].
• UpdateExplanationDatasetOperationMetadata
  Runtime operation information for [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset].
• UpdateExplanationDatasetRequest
  Request message for [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset].
• UpdateExplanationDatasetResponse
  Response message of [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset] operation.
• UpdateFeatureGroupOperationMetadata
  Details of operations that perform update FeatureGroup.
• UpdateFeatureGroupRequest
  Request message for [FeatureRegistryService.UpdateFeatureGroup][google.cloud.aiplatform.v1.FeatureRegistryService.UpdateFeatureGroup].
• UpdateFeatureOnlineStoreOperationMetadata
  Details of operations that perform update FeatureOnlineStore.
• UpdateFeatureOnlineStoreRequest
  Request message for [FeatureOnlineStoreAdminService.UpdateFeatureOnlineStore][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.UpdateFeatureOnlineStore].
• UpdateFeatureOperationMetadata
  Details of operations that perform update Feature.
• UpdateFeatureRequest
  Request message for [FeaturestoreService.UpdateFeature][google.cloud.aiplatform.v1.FeaturestoreService.UpdateFeature]. Request message for [FeatureRegistryService.UpdateFeature][google.cloud.aiplatform.v1.FeatureRegistryService.UpdateFeature].
• UpdateFeatureViewOperationMetadata
  Details of operations that perform update FeatureView.
• UpdateFeatureViewRequest
  Request message for [FeatureOnlineStoreAdminService.UpdateFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.UpdateFeatureView].
• UpdateFeaturestoreOperationMetadata
  Details of operations that perform update Featurestore.
• UpdateFeaturestoreRequest
  Request message for [FeaturestoreService.UpdateFeaturestore][google.cloud.aiplatform.v1.FeaturestoreService.UpdateFeaturestore].
• UpdateIndexEndpointRequest
  Request message for [IndexEndpointService.UpdateIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.UpdateIndexEndpoint].
• UpdateIndexOperationMetadata
  Runtime operation information for [IndexService.UpdateIndex][google.cloud.aiplatform.v1.IndexService.UpdateIndex].
• UpdateIndexRequest
  Request message for [IndexService.UpdateIndex][google.cloud.aiplatform.v1.IndexService.UpdateIndex].
• UpdateModelDeploymentMonitoringJobOperationMetadata
  Runtime operation information for [JobService.UpdateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.UpdateModelDeploymentMonitoringJob].
• UpdateModelDeploymentMonitoringJobRequest
  Request message for [JobService.UpdateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.UpdateModelDeploymentMonitoringJob].
• UpdateModelRequest
  Request message for [ModelService.UpdateModel][google.cloud.aiplatform.v1.ModelService.UpdateModel].
• UpdateNotebookRuntimeTemplateRequest
  Request message for [NotebookService.UpdateNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.UpdateNotebookRuntimeTemplate].
• UpdatePersistentResourceOperationMetadata
  Details of operations that perform update PersistentResource.
• UpdatePersistentResourceRequest
  Request message for UpdatePersistentResource method.
• UpdateScheduleRequest
  Request message for [ScheduleService.UpdateSchedule][google.cloud.aiplatform.v1.ScheduleService.UpdateSchedule].
• UpdateSpecialistPoolOperationMetadata
  Runtime operation metadata for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.UpdateSpecialistPool].
• UpdateSpecialistPoolRequest
  Request message for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.UpdateSpecialistPool].
• UpdateTensorboardExperimentRequest
  Request message for [TensorboardService.UpdateTensorboardExperiment][google.cloud.aiplatform.v1.TensorboardService.UpdateTensorboardExperiment].
• UpdateTensorboardOperationMetadata
  Details of operations that perform update Tensorboard.
• UpdateTensorboardRequest
  Request message for [TensorboardService.UpdateTensorboard][google.cloud.aiplatform.v1.TensorboardService.UpdateTensorboard].
• UpdateTensorboardRunRequest
  Request message for [TensorboardService.UpdateTensorboardRun][google.cloud.aiplatform.v1.TensorboardService.UpdateTensorboardRun].
• UpdateTensorboardTimeSeriesRequest
  Request message for [TensorboardService.UpdateTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.UpdateTensorboardTimeSeries].
• UpgradeNotebookRuntimeOperationMetadata
  Metadata information for [NotebookService.UpgradeNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.UpgradeNotebookRuntime].
• UpgradeNotebookRuntimeRequest
  Request message for [NotebookService.UpgradeNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.UpgradeNotebookRuntime].
• UpgradeNotebookRuntimeResponse
  Response message for [NotebookService.UpgradeNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.UpgradeNotebookRuntime].
• UploadModelOperationMetadata
  Details of [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel] operation.
• UploadModelRequest
  Request message for [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel].
• UploadModelResponse
  Response message of [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel] operation.
• UpsertDatapointsRequest
  Request message for [IndexService.UpsertDatapoints][google.cloud.aiplatform.v1.IndexService.UpsertDatapoints]
• UpsertDatapointsResponse
  Response message for [IndexService.UpsertDatapoints][google.cloud.aiplatform.v1.IndexService.UpsertDatapoints]
• UserActionReference
  References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.
• Value
  Value is the value of the field.
• VertexAiSearch
  Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation
• VideoMetadata
  Metadata describes the input video content.
• WorkerPoolSpec
  Represents the spec of a worker pool in a job.
• WriteFeatureValuesPayload
  Contains Feature values to be written for a specific entity.
• WriteFeatureValuesRequest
  Request message for [FeaturestoreOnlineServingService.WriteFeatureValues][google.cloud.aiplatform.v1.FeaturestoreOnlineServingService.WriteFeatureValues].
• WriteFeatureValuesResponse
  Response message for [FeaturestoreOnlineServingService.WriteFeatureValues][google.cloud.aiplatform.v1.FeaturestoreOnlineServingService.WriteFeatureValues].
• WriteTensorboardExperimentDataRequest
  Request message for [TensorboardService.WriteTensorboardExperimentData][google.cloud.aiplatform.v1.TensorboardService.WriteTensorboardExperimentData].
• WriteTensorboardExperimentDataResponse
  Response message for [TensorboardService.WriteTensorboardExperimentData][google.cloud.aiplatform.v1.TensorboardService.WriteTensorboardExperimentData].
• WriteTensorboardRunDataRequest
  Request message for [TensorboardService.WriteTensorboardRunData][google.cloud.aiplatform.v1.TensorboardService.WriteTensorboardRunData].
• WriteTensorboardRunDataResponse
  Response message for [TensorboardService.WriteTensorboardRunData][google.cloud.aiplatform.v1.TensorboardService.WriteTensorboardRunData].
• XraiAttribution
  An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model’s fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825

Enums

• AcceleratorType
  Represents a hardware accelerator type.
• FeatureViewDataFormat
  Format of the data in the Feature View.
• HarmCategory
  Harm categories that will block the content.
• JobState
  Describes the state of a job.
• ModelDeploymentMonitoringObjectiveType
  The Model Monitoring Objective types.
• NotebookExecutionJobView
  Views for Get/List NotebookExecutionJob
• NotebookRuntimeType
  Represents a notebook runtime type.
• PairwiseChoice
  Pairwise prediction autorater preference.
• PipelineFailurePolicy
  Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.
• PipelineState
  Describes the state of a pipeline.
• PublisherModelView
  View enumeration of PublisherModel.
• Type
  Type contains the list of OpenAPI data types as defined by https://swagger.io/docs/specification/data-models/data-types/