Modules§

Structs§

  • 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.
  • Request message for [MetadataService.AddContextArtifactsAndExecutions][google.cloud.aiplatform.v1.MetadataService.AddContextArtifactsAndExecutions].
  • Response message for [MetadataService.AddContextArtifactsAndExecutions][google.cloud.aiplatform.v1.MetadataService.AddContextArtifactsAndExecutions].
  • Request message for [MetadataService.AddContextChildren][google.cloud.aiplatform.v1.MetadataService.AddContextChildren].
  • Response message for [MetadataService.AddContextChildren][google.cloud.aiplatform.v1.MetadataService.AddContextChildren].
  • Request message for [MetadataService.AddExecutionEvents][google.cloud.aiplatform.v1.MetadataService.AddExecutionEvents].
  • Response message for [MetadataService.AddExecutionEvents][google.cloud.aiplatform.v1.MetadataService.AddExecutionEvents].
  • Request message for [VizierService.AddTrialMeasurement][google.cloud.aiplatform.v1.VizierService.AddTrialMeasurement].
  • Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.
  • Identifies a concept with which DataItems may be annotated with.
  • Instance of a general artifact.
  • Metadata information for [NotebookService.AssignNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.AssignNotebookRuntime].
  • Request message for [NotebookService.AssignNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.AssignNotebookRuntime].
  • Attribution that explains a particular prediction output.
  • 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.
  • The metric specification that defines the target resource utilization (CPU utilization, accelerator’s duty cycle, and so on) for calculating the desired replica count.
  • The storage details for Avro input content.
  • Runtime operation information for [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].
  • Request message for [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].
  • Response message for [PipelineService.BatchCancelPipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchCancelPipelineJobs].
  • Details of operations that perform batch create Features.
  • Request message for [FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1.FeaturestoreService.BatchCreateFeatures].
  • Response message for [FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1.FeaturestoreService.BatchCreateFeatures].
  • Request message for [TensorboardService.BatchCreateTensorboardRuns][google.cloud.aiplatform.v1.TensorboardService.BatchCreateTensorboardRuns].
  • Response message for [TensorboardService.BatchCreateTensorboardRuns][google.cloud.aiplatform.v1.TensorboardService.BatchCreateTensorboardRuns].
  • Request message for [TensorboardService.BatchCreateTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.BatchCreateTensorboardTimeSeries].
  • Response message for [TensorboardService.BatchCreateTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.BatchCreateTensorboardTimeSeries].
  • A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.
  • Request message for [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].
  • Response message for [PipelineService.BatchDeletePipelineJobs][google.cloud.aiplatform.v1.PipelineService.BatchDeletePipelineJobs].
  • Request message for [ModelService.BatchImportEvaluatedAnnotations][google.cloud.aiplatform.v1.ModelService.BatchImportEvaluatedAnnotations]
  • Response message for [ModelService.BatchImportEvaluatedAnnotations][google.cloud.aiplatform.v1.ModelService.BatchImportEvaluatedAnnotations]
  • Request message for [ModelService.BatchImportModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.BatchImportModelEvaluationSlices]
  • Response message for [ModelService.BatchImportModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.BatchImportModelEvaluationSlices]
  • Runtime operation information for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
  • Request message for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
  • Response message for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].
  • 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.
  • Details of operations that batch reads Feature values.
  • Request message for [FeaturestoreService.BatchReadFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.BatchReadFeatureValues].
  • Response message for [FeaturestoreService.BatchReadFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.BatchReadFeatureValues].
  • Request message for [TensorboardService.BatchReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.BatchReadTensorboardTimeSeriesData].
  • Response message for [TensorboardService.BatchReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.BatchReadTensorboardTimeSeriesData].
  • The BigQuery location for the output content.
  • The BigQuery location for the input content.
  • Content blob.
  • Config for blur baseline.
  • A list of boolean values.
  • Request message for [JobService.CancelBatchPredictionJob][google.cloud.aiplatform.v1.JobService.CancelBatchPredictionJob].
  • Request message for [JobService.CancelCustomJob][google.cloud.aiplatform.v1.JobService.CancelCustomJob].
  • Request message for [JobService.CancelDataLabelingJob][google.cloud.aiplatform.v1.JobService.CancelDataLabelingJob].
  • Request message for [JobService.CancelHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.CancelHyperparameterTuningJob].
  • Request message for [JobService.CancelNasJob][google.cloud.aiplatform.v1.JobService.CancelNasJob].
  • Request message for [PipelineService.CancelPipelineJob][google.cloud.aiplatform.v1.PipelineService.CancelPipelineJob].
  • Request message for [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CancelTrainingPipeline].
  • Request message for [GenAiTuningService.CancelTuningJob][google.cloud.aiplatform.v1.GenAiTuningService.CancelTuningJob].
  • A response candidate generated from the model.
  • This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.
  • Request message for [VizierService.CheckTrialEarlyStoppingState][google.cloud.aiplatform.v1.VizierService.CheckTrialEarlyStoppingState].
  • Response message for [VizierService.CheckTrialEarlyStoppingState][google.cloud.aiplatform.v1.VizierService.CheckTrialEarlyStoppingState].
  • Source attributions for content.
  • A collection of source attributions for a piece of content.
  • Request message for [VizierService.CompleteTrial][google.cloud.aiplatform.v1.VizierService.CompleteTrial].
  • Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
  • Request message for ComputeTokens RPC call.
  • Response message for ComputeTokens RPC call.
  • The Container Registry location for the container image.
  • The spec of a Container.
  • The base structured datatype containing multi-part content of a message.
  • Instance of a general context.
  • Details of [ModelService.CopyModel][google.cloud.aiplatform.v1.ModelService.CopyModel] operation.
  • Request message for [ModelService.CopyModel][google.cloud.aiplatform.v1.ModelService.CopyModel].
  • Response message of [ModelService.CopyModel][google.cloud.aiplatform.v1.ModelService.CopyModel] operation.
  • Request message for [PredictionService.CountTokens][].
  • Response message for [PredictionService.CountTokens][].
  • Request message for [MetadataService.CreateArtifact][google.cloud.aiplatform.v1.MetadataService.CreateArtifact].
  • Request message for [JobService.CreateBatchPredictionJob][google.cloud.aiplatform.v1.JobService.CreateBatchPredictionJob].
  • Request message for [MetadataService.CreateContext][google.cloud.aiplatform.v1.MetadataService.CreateContext].
  • Request message for [JobService.CreateCustomJob][google.cloud.aiplatform.v1.JobService.CreateCustomJob].
  • Request message for [JobService.CreateDataLabelingJob][google.cloud.aiplatform.v1.JobService.CreateDataLabelingJob].
  • Runtime operation information for [DatasetService.CreateDataset][google.cloud.aiplatform.v1.DatasetService.CreateDataset].
  • Request message for [DatasetService.CreateDataset][google.cloud.aiplatform.v1.DatasetService.CreateDataset].
  • Runtime operation information for [DatasetService.CreateDatasetVersion][google.cloud.aiplatform.v1.DatasetService.CreateDatasetVersion].
  • Request message for [DatasetService.CreateDatasetVersion][google.cloud.aiplatform.v1.DatasetService.CreateDatasetVersion].
  • Runtime operation information for CreateDeploymentResourcePool method.
  • Request message for CreateDeploymentResourcePool method.
  • Runtime operation information for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1.EndpointService.CreateEndpoint].
  • Request message for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1.EndpointService.CreateEndpoint].
  • Details of operations that perform create EntityType.
  • Request message for [FeaturestoreService.CreateEntityType][google.cloud.aiplatform.v1.FeaturestoreService.CreateEntityType].
  • Request message for [MetadataService.CreateExecution][google.cloud.aiplatform.v1.MetadataService.CreateExecution].
  • Details of operations that perform create FeatureGroup.
  • Request message for [FeatureRegistryService.CreateFeatureGroup][google.cloud.aiplatform.v1.FeatureRegistryService.CreateFeatureGroup].
  • Details of operations that perform create FeatureOnlineStore.
  • Request message for [FeatureOnlineStoreAdminService.CreateFeatureOnlineStore][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.CreateFeatureOnlineStore].
  • Details of operations that perform create Feature.
  • Request message for [FeaturestoreService.CreateFeature][google.cloud.aiplatform.v1.FeaturestoreService.CreateFeature]. Request message for [FeatureRegistryService.CreateFeature][google.cloud.aiplatform.v1.FeatureRegistryService.CreateFeature].
  • Details of operations that perform create FeatureView.
  • Request message for [FeatureOnlineStoreAdminService.CreateFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.CreateFeatureView].
  • Details of operations that perform create Featurestore.
  • Request message for [FeaturestoreService.CreateFeaturestore][google.cloud.aiplatform.v1.FeaturestoreService.CreateFeaturestore].
  • Request message for [JobService.CreateHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.CreateHyperparameterTuningJob].
  • Runtime operation information for [IndexEndpointService.CreateIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.CreateIndexEndpoint].
  • Request message for [IndexEndpointService.CreateIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.CreateIndexEndpoint].
  • Runtime operation information for [IndexService.CreateIndex][google.cloud.aiplatform.v1.IndexService.CreateIndex].
  • Request message for [IndexService.CreateIndex][google.cloud.aiplatform.v1.IndexService.CreateIndex].
  • Request message for [MetadataService.CreateMetadataSchema][google.cloud.aiplatform.v1.MetadataService.CreateMetadataSchema].
  • Details of operations that perform [MetadataService.CreateMetadataStore][google.cloud.aiplatform.v1.MetadataService.CreateMetadataStore].
  • Request message for [MetadataService.CreateMetadataStore][google.cloud.aiplatform.v1.MetadataService.CreateMetadataStore].
  • Request message for [JobService.CreateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.CreateModelDeploymentMonitoringJob].
  • Request message for [JobService.CreateNasJob][google.cloud.aiplatform.v1.JobService.CreateNasJob].
  • Metadata information for [NotebookService.CreateNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.CreateNotebookRuntimeTemplate].
  • Request message for [NotebookService.CreateNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.CreateNotebookRuntimeTemplate].
  • Details of operations that perform create PersistentResource.
  • Request message for [PersistentResourceService.CreatePersistentResource][google.cloud.aiplatform.v1.PersistentResourceService.CreatePersistentResource].
  • Request message for [PipelineService.CreatePipelineJob][google.cloud.aiplatform.v1.PipelineService.CreatePipelineJob].
  • Details of operations that perform create FeatureGroup.
  • Request message for [ScheduleService.CreateSchedule][google.cloud.aiplatform.v1.ScheduleService.CreateSchedule].
  • Runtime operation information for [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.CreateSpecialistPool].
  • Request message for [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.CreateSpecialistPool].
  • Request message for [VizierService.CreateStudy][google.cloud.aiplatform.v1.VizierService.CreateStudy].
  • Request message for [TensorboardService.CreateTensorboardExperiment][google.cloud.aiplatform.v1.TensorboardService.CreateTensorboardExperiment].
  • Details of operations that perform create Tensorboard.
  • Request message for [TensorboardService.CreateTensorboard][google.cloud.aiplatform.v1.TensorboardService.CreateTensorboard].
  • Request message for [TensorboardService.CreateTensorboardRun][google.cloud.aiplatform.v1.TensorboardService.CreateTensorboardRun].
  • Request message for [TensorboardService.CreateTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.CreateTensorboardTimeSeries].
  • Request message for [PipelineService.CreateTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CreateTrainingPipeline].
  • Request message for [VizierService.CreateTrial][google.cloud.aiplatform.v1.VizierService.CreateTrial].
  • Request message for [GenAiTuningService.CreateTuningJob][google.cloud.aiplatform.v1.GenAiTuningService.CreateTuningJob].
  • The storage details for CSV output content.
  • The storage details for CSV input content.
  • 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).
  • Represents the spec of a CustomJob.
  • A piece of data in a Dataset. Could be an image, a video, a document or plain text.
  • A container for a single DataItem and Annotations on it.
  • DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:
  • A collection of DataItems and Annotations on them.
  • Describes the dataset version.
  • A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.
  • Request message for [MetadataService.DeleteArtifact][google.cloud.aiplatform.v1.MetadataService.DeleteArtifact].
  • Request message for [JobService.DeleteBatchPredictionJob][google.cloud.aiplatform.v1.JobService.DeleteBatchPredictionJob].
  • Request message for [MetadataService.DeleteContext][google.cloud.aiplatform.v1.MetadataService.DeleteContext].
  • Request message for [JobService.DeleteCustomJob][google.cloud.aiplatform.v1.JobService.DeleteCustomJob].
  • Request message for [JobService.DeleteDataLabelingJob][google.cloud.aiplatform.v1.JobService.DeleteDataLabelingJob].
  • Request message for [DatasetService.DeleteDataset][google.cloud.aiplatform.v1.DatasetService.DeleteDataset].
  • Request message for [DatasetService.DeleteDatasetVersion][google.cloud.aiplatform.v1.DatasetService.DeleteDatasetVersion].
  • Request message for DeleteDeploymentResourcePool method.
  • Request message for [EndpointService.DeleteEndpoint][google.cloud.aiplatform.v1.EndpointService.DeleteEndpoint].
  • Request message for [FeaturestoreService.DeleteEntityTypes][].
  • Request message for [MetadataService.DeleteExecution][google.cloud.aiplatform.v1.MetadataService.DeleteExecution].
  • Request message for [FeatureRegistryService.DeleteFeatureGroup][google.cloud.aiplatform.v1.FeatureRegistryService.DeleteFeatureGroup].
  • Request message for [FeatureOnlineStoreAdminService.DeleteFeatureOnlineStore][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.DeleteFeatureOnlineStore].
  • Request message for [FeaturestoreService.DeleteFeature][google.cloud.aiplatform.v1.FeaturestoreService.DeleteFeature]. Request message for [FeatureRegistryService.DeleteFeature][google.cloud.aiplatform.v1.FeatureRegistryService.DeleteFeature].
  • Details of operations that delete Feature values.
  • Request message for [FeaturestoreService.DeleteFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.DeleteFeatureValues].
  • Response message for [FeaturestoreService.DeleteFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.DeleteFeatureValues].
  • Request message for [FeatureOnlineStoreAdminService.DeleteFeatureViews][].
  • Request message for [FeaturestoreService.DeleteFeaturestore][google.cloud.aiplatform.v1.FeaturestoreService.DeleteFeaturestore].
  • Request message for [JobService.DeleteHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.DeleteHyperparameterTuningJob].
  • Request message for [IndexEndpointService.DeleteIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.DeleteIndexEndpoint].
  • Request message for [IndexService.DeleteIndex][google.cloud.aiplatform.v1.IndexService.DeleteIndex].
  • Details of operations that perform [MetadataService.DeleteMetadataStore][google.cloud.aiplatform.v1.MetadataService.DeleteMetadataStore].
  • Request message for [MetadataService.DeleteMetadataStore][google.cloud.aiplatform.v1.MetadataService.DeleteMetadataStore].
  • Request message for [JobService.DeleteModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.DeleteModelDeploymentMonitoringJob].
  • Request message for [ModelService.DeleteModel][google.cloud.aiplatform.v1.ModelService.DeleteModel].
  • Request message for [ModelService.DeleteModelVersion][google.cloud.aiplatform.v1.ModelService.DeleteModelVersion].
  • Request message for [JobService.DeleteNasJob][google.cloud.aiplatform.v1.JobService.DeleteNasJob].
  • Request message for [NotebookService.DeleteNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.DeleteNotebookRuntime].
  • Request message for [NotebookService.DeleteNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.DeleteNotebookRuntimeTemplate].
  • Details of operations that perform deletes of any entities.
  • Request message for [PersistentResourceService.DeletePersistentResource][google.cloud.aiplatform.v1.PersistentResourceService.DeletePersistentResource].
  • Request message for [PipelineService.DeletePipelineJob][google.cloud.aiplatform.v1.PipelineService.DeletePipelineJob].
  • Request message for [DatasetService.DeleteSavedQuery][google.cloud.aiplatform.v1.DatasetService.DeleteSavedQuery].
  • Request message for [ScheduleService.DeleteSchedule][google.cloud.aiplatform.v1.ScheduleService.DeleteSchedule].
  • Request message for [SpecialistPoolService.DeleteSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.DeleteSpecialistPool].
  • Request message for [VizierService.DeleteStudy][google.cloud.aiplatform.v1.VizierService.DeleteStudy].
  • Request message for [TensorboardService.DeleteTensorboardExperiment][google.cloud.aiplatform.v1.TensorboardService.DeleteTensorboardExperiment].
  • Request message for [TensorboardService.DeleteTensorboard][google.cloud.aiplatform.v1.TensorboardService.DeleteTensorboard].
  • Request message for [TensorboardService.DeleteTensorboardRun][google.cloud.aiplatform.v1.TensorboardService.DeleteTensorboardRun].
  • Request message for [TensorboardService.DeleteTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.DeleteTensorboardTimeSeries].
  • Request message for [PipelineService.DeleteTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.DeleteTrainingPipeline].
  • Request message for [VizierService.DeleteTrial][google.cloud.aiplatform.v1.VizierService.DeleteTrial].
  • Runtime operation information for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.DeployIndex].
  • Request message for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.DeployIndex].
  • Response message for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.DeployIndex].
  • Runtime operation information for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].
  • Request message for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].
  • Response message for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].
  • A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.
  • Used to set up the auth on the DeployedIndex’s private endpoint.
  • Points to a DeployedIndex.
  • A deployment of a Model. Endpoints contain one or more DeployedModels.
  • Points to a DeployedModel.
  • A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.
  • Request message for [PredictionService.DirectPredict][google.cloud.aiplatform.v1.PredictionService.DirectPredict].
  • Response message for [PredictionService.DirectPredict][google.cloud.aiplatform.v1.PredictionService.DirectPredict].
  • Request message for [PredictionService.DirectRawPredict][google.cloud.aiplatform.v1.PredictionService.DirectRawPredict].
  • Response message for [PredictionService.DirectRawPredict][google.cloud.aiplatform.v1.PredictionService.DirectRawPredict].
  • Represents the spec of disk options.
  • A list of double values.
  • Represents a customer-managed encryption key spec that can be applied to a top-level resource.
  • Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.
  • Selector for entityId. Getting ids from the given source.
  • 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.
  • Represents an environment variable present in a Container or Python Module.
  • Model error analysis for each annotation.
  • True positive, false positive, or false negative.
  • Explanation result of the prediction produced by the Model.
  • An edge describing the relationship between an Artifact and an Execution in a lineage graph.
  • Example-based explainability that returns the nearest neighbors from the provided dataset.
  • Overrides for example-based explanations.
  • Restrictions namespace for example-based explanations overrides.
  • Instance of a general execution.
  • Request message for [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
  • Response message for [PredictionService.Explain][google.cloud.aiplatform.v1.PredictionService.Explain].
  • 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].
  • Metadata describing the Model’s input and output for explanation.
  • The [ExplanationMetadata][google.cloud.aiplatform.v1.ExplanationMetadata] entries that can be overridden at [online explanation][google.cloud.aiplatform.v1.PredictionService.Explain] time.
  • Parameters to configure explaining for Model’s predictions.
  • Specification of Model explanation.
  • The [ExplanationSpec][google.cloud.aiplatform.v1.ExplanationSpec] entries that can be overridden at [online explanation][google.cloud.aiplatform.v1.PredictionService.Explain] time.
  • Describes what part of the Dataset is to be exported, the destination of the export and how to export.
  • Runtime operation information for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].
  • Request message for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].
  • Response message for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].
  • Details of operations that exports Features values.
  • Request message for [FeaturestoreService.ExportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ExportFeatureValues].
  • Response message for [FeaturestoreService.ExportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ExportFeatureValues].
  • 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).
  • 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.
  • Details of [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel] operation.
  • Request message for [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel].
  • Response message of [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel] operation.
  • Request message for [TensorboardService.ExportTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.ExportTensorboardTimeSeriesData].
  • Response message for [TensorboardService.ExportTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.ExportTensorboardTimeSeriesData].
  • Feature Metadata information. For example, color is a feature that describes an apple.
  • Vertex AI Feature Group.
  • 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.
  • 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.
  • Selector for Features of an EntityType.
  • 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.
  • Value for a feature.
  • A destination location for Feature values and format.
  • Container for list of values.
  • FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.
  • Lookup key for a feature view.
  • FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store.
  • 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.
  • Configuration of how features in Featurestore are monitored.
  • Request message for [FeatureOnlineStoreService.FetchFeatureValues][google.cloud.aiplatform.v1.FeatureOnlineStoreService.FetchFeatureValues]. All the features under the requested feature view will be returned.
  • Response message for [FeatureOnlineStoreService.FetchFeatureValues][google.cloud.aiplatform.v1.FeatureOnlineStoreService.FetchFeatureValues]
  • URI based data.
  • 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).
  • The request message for [MatchService.FindNeighbors][google.cloud.aiplatform.v1.MatchService.FindNeighbors].
  • The response message for [MatchService.FindNeighbors][google.cloud.aiplatform.v1.MatchService.FindNeighbors].
  • 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.
  • 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.
  • 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.
  • 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.
  • The Google Cloud Storage location where the output is to be written to.
  • The Google Cloud Storage location for the input content.
  • Request message for [PredictionService.GenerateContent].
  • Response message for [PredictionService.GenerateContent].
  • Generation config.
  • Generic Metadata shared by all operations.
  • Contains information about the source of the models generated from Generative AI Studio.
  • Request message for [DatasetService.GetAnnotationSpec][google.cloud.aiplatform.v1.DatasetService.GetAnnotationSpec].
  • Request message for [MetadataService.GetArtifact][google.cloud.aiplatform.v1.MetadataService.GetArtifact].
  • Request message for [JobService.GetBatchPredictionJob][google.cloud.aiplatform.v1.JobService.GetBatchPredictionJob].
  • Request message for [MetadataService.GetContext][google.cloud.aiplatform.v1.MetadataService.GetContext].
  • Request message for [JobService.GetCustomJob][google.cloud.aiplatform.v1.JobService.GetCustomJob].
  • Request message for [JobService.GetDataLabelingJob][google.cloud.aiplatform.v1.JobService.GetDataLabelingJob].
  • Request message for [DatasetService.GetDataset][google.cloud.aiplatform.v1.DatasetService.GetDataset].
  • Request message for [DatasetService.GetDatasetVersion][google.cloud.aiplatform.v1.DatasetService.GetDatasetVersion].
  • Request message for GetDeploymentResourcePool method.
  • Request message for [EndpointService.GetEndpoint][google.cloud.aiplatform.v1.EndpointService.GetEndpoint]
  • Request message for [FeaturestoreService.GetEntityType][google.cloud.aiplatform.v1.FeaturestoreService.GetEntityType].
  • Request message for [MetadataService.GetExecution][google.cloud.aiplatform.v1.MetadataService.GetExecution].
  • Request message for [FeatureRegistryService.GetFeatureGroup][google.cloud.aiplatform.v1.FeatureRegistryService.GetFeatureGroup].
  • Request message for [FeatureOnlineStoreAdminService.GetFeatureOnlineStore][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.GetFeatureOnlineStore].
  • Request message for [FeaturestoreService.GetFeature][google.cloud.aiplatform.v1.FeaturestoreService.GetFeature]. Request message for [FeatureRegistryService.GetFeature][google.cloud.aiplatform.v1.FeatureRegistryService.GetFeature].
  • Request message for [FeatureOnlineStoreAdminService.GetFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.GetFeatureView].
  • Request message for [FeatureOnlineStoreAdminService.GetFeatureViewSync][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.GetFeatureViewSync].
  • Request message for [FeaturestoreService.GetFeaturestore][google.cloud.aiplatform.v1.FeaturestoreService.GetFeaturestore].
  • Request message for [JobService.GetHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.GetHyperparameterTuningJob].
  • Request message for [IndexEndpointService.GetIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.GetIndexEndpoint]
  • Request message for [IndexService.GetIndex][google.cloud.aiplatform.v1.IndexService.GetIndex]
  • Request message for [MetadataService.GetMetadataSchema][google.cloud.aiplatform.v1.MetadataService.GetMetadataSchema].
  • Request message for [MetadataService.GetMetadataStore][google.cloud.aiplatform.v1.MetadataService.GetMetadataStore].
  • Request message for [JobService.GetModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.GetModelDeploymentMonitoringJob].
  • Request message for [ModelService.GetModelEvaluation][google.cloud.aiplatform.v1.ModelService.GetModelEvaluation].
  • Request message for [ModelService.GetModelEvaluationSlice][google.cloud.aiplatform.v1.ModelService.GetModelEvaluationSlice].
  • Request message for [ModelService.GetModel][google.cloud.aiplatform.v1.ModelService.GetModel].
  • Request message for [JobService.GetNasJob][google.cloud.aiplatform.v1.JobService.GetNasJob].
  • Request message for [JobService.GetNasTrialDetail][google.cloud.aiplatform.v1.JobService.GetNasTrialDetail].
  • Request message for [NotebookService.GetNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.GetNotebookRuntime]
  • Request message for [NotebookService.GetNotebookRuntimeTemplate][google.cloud.aiplatform.v1.NotebookService.GetNotebookRuntimeTemplate]
  • Request message for [PersistentResourceService.GetPersistentResource][google.cloud.aiplatform.v1.PersistentResourceService.GetPersistentResource].
  • Request message for [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1.PipelineService.GetPipelineJob].
  • Request message for [ModelGardenService.GetPublisherModel][google.cloud.aiplatform.v1.ModelGardenService.GetPublisherModel]
  • Request message for [ScheduleService.GetSchedule][google.cloud.aiplatform.v1.ScheduleService.GetSchedule].
  • Request message for [SpecialistPoolService.GetSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.GetSpecialistPool].
  • Request message for [VizierService.GetStudy][google.cloud.aiplatform.v1.VizierService.GetStudy].
  • Request message for [TensorboardService.GetTensorboardExperiment][google.cloud.aiplatform.v1.TensorboardService.GetTensorboardExperiment].
  • Request message for [TensorboardService.GetTensorboard][google.cloud.aiplatform.v1.TensorboardService.GetTensorboard].
  • Request message for [TensorboardService.GetTensorboardRun][google.cloud.aiplatform.v1.TensorboardService.GetTensorboardRun].
  • Request message for [TensorboardService.GetTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.GetTensorboardTimeSeries].
  • Request message for [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.GetTrainingPipeline].
  • Request message for [VizierService.GetTrial][google.cloud.aiplatform.v1.VizierService.GetTrial].
  • Request message for [GenAiTuningService.GetTuningJob][google.cloud.aiplatform.v1.GenAiTuningService.GetTuningJob].
  • Tool to retrieve public web data for grounding, powered by Google.
  • Grounding attribution.
  • Metadata returned to client when grounding is enabled.
  • Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.
  • Matcher for Features of an EntityType by Feature ID.
  • 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.
  • Runtime operation information for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].
  • Request message for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].
  • Response message for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].
  • Details of operations that perform import Feature values.
  • Request message for [FeaturestoreService.ImportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ImportFeatureValues].
  • Response message for [FeaturestoreService.ImportFeatureValues][google.cloud.aiplatform.v1.FeaturestoreService.ImportFeatureValues].
  • Request message for [ModelService.ImportModelEvaluation][google.cloud.aiplatform.v1.ModelService.ImportModelEvaluation]
  • A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.
  • A datapoint of Index.
  • Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.
  • 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.
  • Stats of the Index.
  • Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.
  • A list of int64 values.
  • 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
  • Contains information about the Large Model.
  • A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.
  • Request message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].
  • Response message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].
  • Request message for [MetadataService.ListArtifacts][google.cloud.aiplatform.v1.MetadataService.ListArtifacts].
  • Response message for [MetadataService.ListArtifacts][google.cloud.aiplatform.v1.MetadataService.ListArtifacts].
  • Request message for [JobService.ListBatchPredictionJobs][google.cloud.aiplatform.v1.JobService.ListBatchPredictionJobs].
  • Response message for [JobService.ListBatchPredictionJobs][google.cloud.aiplatform.v1.JobService.ListBatchPredictionJobs]
  • Request message for [MetadataService.ListContexts][google.cloud.aiplatform.v1.MetadataService.ListContexts]
  • Response message for [MetadataService.ListContexts][google.cloud.aiplatform.v1.MetadataService.ListContexts].
  • Request message for [JobService.ListCustomJobs][google.cloud.aiplatform.v1.JobService.ListCustomJobs].
  • Response message for [JobService.ListCustomJobs][google.cloud.aiplatform.v1.JobService.ListCustomJobs]
  • Request message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems].
  • Response message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems].
  • Request message for [JobService.ListDataLabelingJobs][google.cloud.aiplatform.v1.JobService.ListDataLabelingJobs].
  • Response message for [JobService.ListDataLabelingJobs][google.cloud.aiplatform.v1.JobService.ListDataLabelingJobs].
  • Request message for [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1.DatasetService.ListDatasetVersions].
  • Response message for [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1.DatasetService.ListDatasetVersions].
  • Request message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1.DatasetService.ListDatasets].
  • Response message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1.DatasetService.ListDatasets].
  • Request message for ListDeploymentResourcePools method.
  • Response message for ListDeploymentResourcePools method.
  • Request message for [EndpointService.ListEndpoints][google.cloud.aiplatform.v1.EndpointService.ListEndpoints].
  • Response message for [EndpointService.ListEndpoints][google.cloud.aiplatform.v1.EndpointService.ListEndpoints].
  • Request message for [FeaturestoreService.ListEntityTypes][google.cloud.aiplatform.v1.FeaturestoreService.ListEntityTypes].
  • Response message for [FeaturestoreService.ListEntityTypes][google.cloud.aiplatform.v1.FeaturestoreService.ListEntityTypes].
  • Request message for [MetadataService.ListExecutions][google.cloud.aiplatform.v1.MetadataService.ListExecutions].
  • Response message for [MetadataService.ListExecutions][google.cloud.aiplatform.v1.MetadataService.ListExecutions].
  • Request message for [FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatureGroups].
  • Response message for [FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatureGroups].
  • Request message for [FeatureOnlineStoreAdminService.ListFeatureOnlineStores][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureOnlineStores].
  • Response message for [FeatureOnlineStoreAdminService.ListFeatureOnlineStores][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureOnlineStores].
  • Request message for [FeatureOnlineStoreAdminService.ListFeatureViewSyncs][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureViewSyncs].
  • Response message for [FeatureOnlineStoreAdminService.ListFeatureViewSyncs][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureViewSyncs].
  • Request message for [FeatureOnlineStoreAdminService.ListFeatureViews][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureViews].
  • Response message for [FeatureOnlineStoreAdminService.ListFeatureViews][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.ListFeatureViews].
  • Request message for [FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures]. Request message for [FeatureRegistryService.ListFeatures][google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatures].
  • Response message for [FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1.FeaturestoreService.ListFeatures]. Response message for [FeatureRegistryService.ListFeatures][google.cloud.aiplatform.v1.FeatureRegistryService.ListFeatures].
  • Request message for [FeaturestoreService.ListFeaturestores][google.cloud.aiplatform.v1.FeaturestoreService.ListFeaturestores].
  • Response message for [FeaturestoreService.ListFeaturestores][google.cloud.aiplatform.v1.FeaturestoreService.ListFeaturestores].
  • Request message for [JobService.ListHyperparameterTuningJobs][google.cloud.aiplatform.v1.JobService.ListHyperparameterTuningJobs].
  • Response message for [JobService.ListHyperparameterTuningJobs][google.cloud.aiplatform.v1.JobService.ListHyperparameterTuningJobs]
  • Request message for [IndexEndpointService.ListIndexEndpoints][google.cloud.aiplatform.v1.IndexEndpointService.ListIndexEndpoints].
  • Response message for [IndexEndpointService.ListIndexEndpoints][google.cloud.aiplatform.v1.IndexEndpointService.ListIndexEndpoints].
  • Request message for [IndexService.ListIndexes][google.cloud.aiplatform.v1.IndexService.ListIndexes].
  • Response message for [IndexService.ListIndexes][google.cloud.aiplatform.v1.IndexService.ListIndexes].
  • Request message for [MetadataService.ListMetadataSchemas][google.cloud.aiplatform.v1.MetadataService.ListMetadataSchemas].
  • Response message for [MetadataService.ListMetadataSchemas][google.cloud.aiplatform.v1.MetadataService.ListMetadataSchemas].
  • Request message for [MetadataService.ListMetadataStores][google.cloud.aiplatform.v1.MetadataService.ListMetadataStores].
  • Response message for [MetadataService.ListMetadataStores][google.cloud.aiplatform.v1.MetadataService.ListMetadataStores].
  • Request message for [JobService.ListModelDeploymentMonitoringJobs][google.cloud.aiplatform.v1.JobService.ListModelDeploymentMonitoringJobs].
  • Response message for [JobService.ListModelDeploymentMonitoringJobs][google.cloud.aiplatform.v1.JobService.ListModelDeploymentMonitoringJobs].
  • Request message for [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.ListModelEvaluationSlices].
  • Response message for [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.ListModelEvaluationSlices].
  • Request message for [ModelService.ListModelEvaluations][google.cloud.aiplatform.v1.ModelService.ListModelEvaluations].
  • Response message for [ModelService.ListModelEvaluations][google.cloud.aiplatform.v1.ModelService.ListModelEvaluations].
  • Request message for [ModelService.ListModelVersions][google.cloud.aiplatform.v1.ModelService.ListModelVersions].
  • Response message for [ModelService.ListModelVersions][google.cloud.aiplatform.v1.ModelService.ListModelVersions]
  • Request message for [ModelService.ListModels][google.cloud.aiplatform.v1.ModelService.ListModels].
  • Response message for [ModelService.ListModels][google.cloud.aiplatform.v1.ModelService.ListModels]
  • Request message for [JobService.ListNasJobs][google.cloud.aiplatform.v1.JobService.ListNasJobs].
  • Response message for [JobService.ListNasJobs][google.cloud.aiplatform.v1.JobService.ListNasJobs]
  • Request message for [JobService.ListNasTrialDetails][google.cloud.aiplatform.v1.JobService.ListNasTrialDetails].
  • Response message for [JobService.ListNasTrialDetails][google.cloud.aiplatform.v1.JobService.ListNasTrialDetails]
  • Request message for [NotebookService.ListNotebookRuntimeTemplates][google.cloud.aiplatform.v1.NotebookService.ListNotebookRuntimeTemplates].
  • Response message for [NotebookService.ListNotebookRuntimeTemplates][google.cloud.aiplatform.v1.NotebookService.ListNotebookRuntimeTemplates].
  • Request message for [NotebookService.ListNotebookRuntimes][google.cloud.aiplatform.v1.NotebookService.ListNotebookRuntimes].
  • Response message for [NotebookService.ListNotebookRuntimes][google.cloud.aiplatform.v1.NotebookService.ListNotebookRuntimes].
  • Request message for [VizierService.ListOptimalTrials][google.cloud.aiplatform.v1.VizierService.ListOptimalTrials].
  • Response message for [VizierService.ListOptimalTrials][google.cloud.aiplatform.v1.VizierService.ListOptimalTrials].
  • Request message for [PersistentResourceService.ListPersistentResource][].
  • Response message for [PersistentResourceService.ListPersistentResources][google.cloud.aiplatform.v1.PersistentResourceService.ListPersistentResources]
  • Request message for [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1.PipelineService.ListPipelineJobs].
  • Response message for [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1.PipelineService.ListPipelineJobs]
  • Request message for [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1.DatasetService.ListSavedQueries].
  • Response message for [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1.DatasetService.ListSavedQueries].
  • Request message for [ScheduleService.ListSchedules][google.cloud.aiplatform.v1.ScheduleService.ListSchedules].
  • Response message for [ScheduleService.ListSchedules][google.cloud.aiplatform.v1.ScheduleService.ListSchedules]
  • Request message for [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1.SpecialistPoolService.ListSpecialistPools].
  • Response message for [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1.SpecialistPoolService.ListSpecialistPools].
  • Request message for [VizierService.ListStudies][google.cloud.aiplatform.v1.VizierService.ListStudies].
  • Response message for [VizierService.ListStudies][google.cloud.aiplatform.v1.VizierService.ListStudies].
  • Request message for [TensorboardService.ListTensorboardExperiments][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardExperiments].
  • Response message for [TensorboardService.ListTensorboardExperiments][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardExperiments].
  • Request message for [TensorboardService.ListTensorboardRuns][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardRuns].
  • Response message for [TensorboardService.ListTensorboardRuns][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardRuns].
  • Request message for [TensorboardService.ListTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardTimeSeries].
  • Response message for [TensorboardService.ListTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.ListTensorboardTimeSeries].
  • Request message for [TensorboardService.ListTensorboards][google.cloud.aiplatform.v1.TensorboardService.ListTensorboards].
  • Response message for [TensorboardService.ListTensorboards][google.cloud.aiplatform.v1.TensorboardService.ListTensorboards].
  • Request message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines].
  • Response message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines]
  • Request message for [VizierService.ListTrials][google.cloud.aiplatform.v1.VizierService.ListTrials].
  • Response message for [VizierService.ListTrials][google.cloud.aiplatform.v1.VizierService.ListTrials].
  • Request message for [GenAiTuningService.ListTuningJobs][google.cloud.aiplatform.v1.GenAiTuningService.ListTuningJobs].
  • Response message for [GenAiTuningService.ListTuningJobs][google.cloud.aiplatform.v1.GenAiTuningService.ListTuningJobs]
  • Request message for [VizierService.LookupStudy][google.cloud.aiplatform.v1.VizierService.LookupStudy].
  • Specification of a single machine.
  • Manual batch tuning parameters.
  • A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.
  • Request message for [ModelService.MergeVersionAliases][google.cloud.aiplatform.v1.ModelService.MergeVersionAliases].
  • Instance of a general MetadataSchema.
  • Instance of a metadata store. Contains a set of metadata that can be queried.
  • Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.
  • Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.
  • Describes a successfully migrated resource.
  • A trained machine learning Model.
  • Specification of a container for serving predictions. Some fields in this message correspond to fields in the Kubernetes Container v1 core specification.
  • ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.
  • 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 contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.
  • The config for scheduling monitoring job.
  • A collection of metrics calculated by comparing Model’s predictions on all of the test data against annotations from the test data.
  • A collection of metrics calculated by comparing Model’s predictions on a slice of the test data against ground truth annotations.
  • Aggregated explanation metrics for a Model over a set of instances.
  • Contains information about the source of the models generated from Model Garden.
  • The alert config for model monitoring.
  • The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.
  • Statistics and anomalies generated by Model Monitoring.
  • Detail description of the source information of the model.
  • Runtime operation information for [IndexEndpointService.MutateDeployedIndex][google.cloud.aiplatform.v1.IndexEndpointService.MutateDeployedIndex].
  • Request message for [IndexEndpointService.MutateDeployedIndex][google.cloud.aiplatform.v1.IndexEndpointService.MutateDeployedIndex].
  • Response message for [IndexEndpointService.MutateDeployedIndex][google.cloud.aiplatform.v1.IndexEndpointService.MutateDeployedIndex].
  • Runtime operation information for [EndpointService.MutateDeployedModel][google.cloud.aiplatform.v1.EndpointService.MutateDeployedModel].
  • Request message for [EndpointService.MutateDeployedModel][google.cloud.aiplatform.v1.EndpointService.MutateDeployedModel].
  • Response message for [EndpointService.MutateDeployedModel][google.cloud.aiplatform.v1.EndpointService.MutateDeployedModel].
  • Represents a Neural Architecture Search (NAS) job.
  • Represents a uCAIP NasJob output.
  • Represents the spec of a NasJob.
  • Represents a uCAIP NasJob trial.
  • Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.
  • A query to find a number of similar entities.
  • Runtime operation metadata with regard to Matching Engine Index.
  • Nearest neighbors for one query.
  • Neighbors for example-based explanations.
  • Network spec.
  • Represents a mount configuration for Network File System (NFS) to mount.
  • The euc configuration of NotebookRuntimeTemplate.
  • The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.
  • 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.
  • A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template.
  • Points to a NotebookRuntimeTemplateRef.
  • A datatype containing media that is part of a multi-part Content message.
  • Request message for [JobService.PauseModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.PauseModelDeploymentMonitoringJob].
  • Request message for [ScheduleService.PauseSchedule][google.cloud.aiplatform.v1.ScheduleService.PauseSchedule].
  • Represents the spec of [persistent disk][https://cloud.google.com/compute/docs/disks/persistent-disks] options.
  • 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.
  • An instance of a machine learning PipelineJob.
  • The runtime detail of PipelineJob.
  • The runtime detail of a task execution.
  • The runtime detail of a pipeline executor.
  • 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.
  • Represents a network port in a container.
  • Assigns input data to training, validation, and test sets based on the value of a provided key.
  • Request message for [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict].
  • Configuration for logging request-response to a BigQuery table.
  • Response message for [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict].
  • 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].
  • Preset configuration for example-based explanations
  • 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.
  • Represents configuration for private service connect.
  • Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.
  • PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig.
  • A Model Garden Publisher Model.
  • Details of operations that perform [MetadataService.PurgeArtifacts][google.cloud.aiplatform.v1.MetadataService.PurgeArtifacts].
  • Request message for [MetadataService.PurgeArtifacts][google.cloud.aiplatform.v1.MetadataService.PurgeArtifacts].
  • Response message for [MetadataService.PurgeArtifacts][google.cloud.aiplatform.v1.MetadataService.PurgeArtifacts].
  • Details of operations that perform [MetadataService.PurgeContexts][google.cloud.aiplatform.v1.MetadataService.PurgeContexts].
  • Request message for [MetadataService.PurgeContexts][google.cloud.aiplatform.v1.MetadataService.PurgeContexts].
  • Response message for [MetadataService.PurgeContexts][google.cloud.aiplatform.v1.MetadataService.PurgeContexts].
  • Details of operations that perform [MetadataService.PurgeExecutions][google.cloud.aiplatform.v1.MetadataService.PurgeExecutions].
  • Request message for [MetadataService.PurgeExecutions][google.cloud.aiplatform.v1.MetadataService.PurgeExecutions].
  • Response message for [MetadataService.PurgeExecutions][google.cloud.aiplatform.v1.MetadataService.PurgeExecutions].
  • The spec of a Python packaged code.
  • Request message for [MetadataService.QueryArtifactLineageSubgraph][google.cloud.aiplatform.v1.MetadataService.QueryArtifactLineageSubgraph].
  • Request message for [MetadataService.QueryContextLineageSubgraph][google.cloud.aiplatform.v1.MetadataService.QueryContextLineageSubgraph].
  • Request message for QueryDeployedModels method.
  • Response message for QueryDeployedModels method.
  • Request message for [MetadataService.QueryExecutionInputsAndOutputs][google.cloud.aiplatform.v1.MetadataService.QueryExecutionInputsAndOutputs].
  • Request message for [PredictionService.RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict].
  • 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.
  • Request message for [FeaturestoreOnlineServingService.ReadFeatureValues][google.cloud.aiplatform.v1.FeaturestoreOnlineServingService.ReadFeatureValues].
  • Response message for [FeaturestoreOnlineServingService.ReadFeatureValues][google.cloud.aiplatform.v1.FeaturestoreOnlineServingService.ReadFeatureValues].
  • The request message for [MatchService.ReadIndexDatapoints][google.cloud.aiplatform.v1.MatchService.ReadIndexDatapoints].
  • The response message for [MatchService.ReadIndexDatapoints][google.cloud.aiplatform.v1.MatchService.ReadIndexDatapoints].
  • Request message for [TensorboardService.ReadTensorboardBlobData][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardBlobData].
  • Response message for [TensorboardService.ReadTensorboardBlobData][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardBlobData].
  • Request message for [TensorboardService.ReadTensorboardSize][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardSize].
  • Response message for [TensorboardService.ReadTensorboardSize][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardSize].
  • Request message for [TensorboardService.ReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardTimeSeriesData].
  • Response message for [TensorboardService.ReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardTimeSeriesData].
  • Request message for [TensorboardService.ReadTensorboardUsage][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardUsage].
  • Response message for [TensorboardService.ReadTensorboardUsage][google.cloud.aiplatform.v1.TensorboardService.ReadTensorboardUsage].
  • Details of operations that perform reboot PersistentResource.
  • Request message for [PersistentResourceService.RebootPersistentResource][google.cloud.aiplatform.v1.PersistentResourceService.RebootPersistentResource].
  • Request message for [MetadataService.DeleteContextChildrenRequest][].
  • Response message for [MetadataService.RemoveContextChildren][google.cloud.aiplatform.v1.MetadataService.RemoveContextChildren].
  • Request message for [IndexService.RemoveDatapoints][google.cloud.aiplatform.v1.IndexService.RemoveDatapoints]
  • Response message for [IndexService.RemoveDatapoints][google.cloud.aiplatform.v1.IndexService.RemoveDatapoints]
  • Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource.
  • Persistent Cluster runtime information as output
  • Configuration for the runtime on a PersistentResource instance, including but not limited to:
  • Statistics information about resource consumption.
  • Runtime operation information for [DatasetService.RestoreDatasetVersion][google.cloud.aiplatform.v1.DatasetService.RestoreDatasetVersion].
  • Request message for [DatasetService.RestoreDatasetVersion][google.cloud.aiplatform.v1.DatasetService.RestoreDatasetVersion].
  • Request message for [JobService.ResumeModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.ResumeModelDeploymentMonitoringJob].
  • Request message for [ScheduleService.ResumeSchedule][google.cloud.aiplatform.v1.ScheduleService.ResumeSchedule].
  • Defines a retrieval tool that model can call to access external knowledge.
  • Safety rating corresponding to the generated content.
  • Safety settings.
  • Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.
  • 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.
  • Sampling Strategy for logging, can be for both training and prediction dataset.
  • A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.
  • One point viewable on a scalar metric plot.
  • An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.
  • All parameters related to queuing and scheduling of custom jobs.
  • 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.
  • Request message for [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
  • Response message for [DatasetService.SearchDataItems][google.cloud.aiplatform.v1.DatasetService.SearchDataItems].
  • Google search entry point.
  • Request message for [FeaturestoreService.SearchFeatures][google.cloud.aiplatform.v1.FeaturestoreService.SearchFeatures].
  • Response message for [FeaturestoreService.SearchFeatures][google.cloud.aiplatform.v1.FeaturestoreService.SearchFeatures].
  • Request message for [MigrationService.SearchMigratableResources][google.cloud.aiplatform.v1.MigrationService.SearchMigratableResources].
  • Response message for [MigrationService.SearchMigratableResources][google.cloud.aiplatform.v1.MigrationService.SearchMigratableResources].
  • Request message for [JobService.SearchModelDeploymentMonitoringStatsAnomalies][google.cloud.aiplatform.v1.JobService.SearchModelDeploymentMonitoringStatsAnomalies].
  • Response message for [JobService.SearchModelDeploymentMonitoringStatsAnomalies][google.cloud.aiplatform.v1.JobService.SearchModelDeploymentMonitoringStatsAnomalies].
  • The request message for [FeatureOnlineStoreService.SearchNearestEntities][google.cloud.aiplatform.v1.FeatureOnlineStoreService.SearchNearestEntities].
  • Response message for [FeatureOnlineStoreService.SearchNearestEntities][google.cloud.aiplatform.v1.FeatureOnlineStoreService.SearchNearestEntities]
  • Segment of the content.
  • Configuration for the use of custom service account to run the workloads.
  • A set of Shielded Instance options. See Images using supported Shielded VM features.
  • Config for SmoothGrad approximation of gradients.
  • 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.
  • Metadata information for [NotebookService.StartNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.StartNotebookRuntime].
  • Request message for [NotebookService.StartNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.StartNotebookRuntime].
  • Response message for [NotebookService.StartNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.StartNotebookRuntime].
  • Request message for [VizierService.StopTrial][google.cloud.aiplatform.v1.VizierService.StopTrial].
  • 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.
  • Request message for [PredictionService.StreamDirectPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectPredict].
  • Response message for [PredictionService.StreamDirectPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectPredict].
  • Request message for [PredictionService.StreamDirectRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectRawPredict].
  • Response message for [PredictionService.StreamDirectRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamDirectRawPredict].
  • Request message for [PredictionService.StreamRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamRawPredict].
  • Request message for [PredictionService.StreamingPredict][google.cloud.aiplatform.v1.PredictionService.StreamingPredict].
  • Response message for [PredictionService.StreamingPredict][google.cloud.aiplatform.v1.PredictionService.StreamingPredict].
  • Request message for [PredictionService.StreamingRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamingRawPredict].
  • Response message for [PredictionService.StreamingRawPredict][google.cloud.aiplatform.v1.PredictionService.StreamingRawPredict].
  • Request message for [FeaturestoreOnlineServingService.StreamingFeatureValuesRead][].
  • A list of string values.
  • A message representing a Study.
  • Represents specification of a Study.
  • Time-based Constraint for Study
  • Details of operations that perform Trials suggestion.
  • Request message for [VizierService.SuggestTrials][google.cloud.aiplatform.v1.VizierService.SuggestTrials].
  • Response message for [VizierService.SuggestTrials][google.cloud.aiplatform.v1.VizierService.SuggestTrials].
  • Hyperparameters for SFT.
  • Tuning data statistics for Supervised Tuning.
  • Dataset distribution for Supervised Tuning.
  • Tuning Spec for Supervised Tuning.
  • Request message for [FeatureOnlineStoreAdminService.SyncFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.SyncFeatureView].
  • Respose message for [FeatureOnlineStoreAdminService.SyncFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.SyncFeatureView].
  • A tensor value type.
  • 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.
  • One blob (e.g, image, graph) viewable on a blob metric plot.
  • 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.
  • A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.
  • TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc
  • One point viewable on a tensor metric plot.
  • TensorboardTimeSeries maps to times series produced in training runs
  • The storage details for TFRecord output content.
  • The config for feature monitoring threshold.
  • All the data stored in a TensorboardTimeSeries.
  • A TensorboardTimeSeries data point.
  • 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.
  • Tokens info with a list of tokens and the corresponding list of token ids.
  • Tool details that the model may use to generate response.
  • 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.
  • 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.
  • 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.
  • Next ID: 3
  • The Model Registry Model and Online Prediction Endpoint assiociated with this [TuningJob][google.cloud.aiplatform.v1.TuningJob].
  • The tuning data statistic values for [TuningJob][google.cloud.aiplatform.v1.TuningJob].
  • Represents a TuningJob that runs with Google owned models.
  • Runtime operation information for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.UndeployIndex].
  • Request message for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.UndeployIndex].
  • Response message for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1.IndexEndpointService.UndeployIndex].
  • Runtime operation information for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].
  • Request message for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].
  • Response message for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].
  • Contains model information necessary to perform batch prediction without requiring a full model import.
  • Request message for [MetadataService.UpdateArtifact][google.cloud.aiplatform.v1.MetadataService.UpdateArtifact].
  • Request message for [MetadataService.UpdateContext][google.cloud.aiplatform.v1.MetadataService.UpdateContext].
  • Request message for [DatasetService.UpdateDataset][google.cloud.aiplatform.v1.DatasetService.UpdateDataset].
  • Runtime operation information for UpdateDeploymentResourcePool method.
  • Request message for [EndpointService.UpdateEndpoint][google.cloud.aiplatform.v1.EndpointService.UpdateEndpoint].
  • Request message for [FeaturestoreService.UpdateEntityType][google.cloud.aiplatform.v1.FeaturestoreService.UpdateEntityType].
  • Request message for [MetadataService.UpdateExecution][google.cloud.aiplatform.v1.MetadataService.UpdateExecution].
  • Runtime operation information for [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset].
  • Request message for [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset].
  • Response message of [ModelService.UpdateExplanationDataset][google.cloud.aiplatform.v1.ModelService.UpdateExplanationDataset] operation.
  • Details of operations that perform update FeatureGroup.
  • Request message for [FeatureRegistryService.UpdateFeatureGroup][google.cloud.aiplatform.v1.FeatureRegistryService.UpdateFeatureGroup].
  • Details of operations that perform update FeatureOnlineStore.
  • Request message for [FeatureOnlineStoreAdminService.UpdateFeatureOnlineStore][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.UpdateFeatureOnlineStore].
  • Details of operations that perform update Feature.
  • Request message for [FeaturestoreService.UpdateFeature][google.cloud.aiplatform.v1.FeaturestoreService.UpdateFeature]. Request message for [FeatureRegistryService.UpdateFeature][google.cloud.aiplatform.v1.FeatureRegistryService.UpdateFeature].
  • Details of operations that perform update FeatureView.
  • Request message for [FeatureOnlineStoreAdminService.UpdateFeatureView][google.cloud.aiplatform.v1.FeatureOnlineStoreAdminService.UpdateFeatureView].
  • Details of operations that perform update Featurestore.
  • Request message for [FeaturestoreService.UpdateFeaturestore][google.cloud.aiplatform.v1.FeaturestoreService.UpdateFeaturestore].
  • Request message for [IndexEndpointService.UpdateIndexEndpoint][google.cloud.aiplatform.v1.IndexEndpointService.UpdateIndexEndpoint].
  • Runtime operation information for [IndexService.UpdateIndex][google.cloud.aiplatform.v1.IndexService.UpdateIndex].
  • Request message for [IndexService.UpdateIndex][google.cloud.aiplatform.v1.IndexService.UpdateIndex].
  • Runtime operation information for [JobService.UpdateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.UpdateModelDeploymentMonitoringJob].
  • Request message for [JobService.UpdateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1.JobService.UpdateModelDeploymentMonitoringJob].
  • Request message for [ModelService.UpdateModel][google.cloud.aiplatform.v1.ModelService.UpdateModel].
  • Details of operations that perform update PersistentResource.
  • Request message for UpdatePersistentResource method.
  • Request message for [ScheduleService.UpdateSchedule][google.cloud.aiplatform.v1.ScheduleService.UpdateSchedule].
  • Runtime operation metadata for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.UpdateSpecialistPool].
  • Request message for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.UpdateSpecialistPool].
  • Request message for [TensorboardService.UpdateTensorboardExperiment][google.cloud.aiplatform.v1.TensorboardService.UpdateTensorboardExperiment].
  • Details of operations that perform update Tensorboard.
  • Request message for [TensorboardService.UpdateTensorboard][google.cloud.aiplatform.v1.TensorboardService.UpdateTensorboard].
  • Request message for [TensorboardService.UpdateTensorboardRun][google.cloud.aiplatform.v1.TensorboardService.UpdateTensorboardRun].
  • Request message for [TensorboardService.UpdateTensorboardTimeSeries][google.cloud.aiplatform.v1.TensorboardService.UpdateTensorboardTimeSeries].
  • Metadata information for [NotebookService.UpgradeNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.UpgradeNotebookRuntime].
  • Request message for [NotebookService.UpgradeNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.UpgradeNotebookRuntime].
  • Response message for [NotebookService.UpgradeNotebookRuntime][google.cloud.aiplatform.v1.NotebookService.UpgradeNotebookRuntime].
  • Details of [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel] operation.
  • Request message for [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel].
  • Response message of [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel] operation.
  • Request message for [IndexService.UpsertDatapoints][google.cloud.aiplatform.v1.IndexService.UpsertDatapoints]
  • Response message for [IndexService.UpsertDatapoints][google.cloud.aiplatform.v1.IndexService.UpsertDatapoints]
  • References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.
  • Value is the value of the field.
  • Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation
  • Metadata describes the input video content.
  • Represents the spec of a worker pool in a job.
  • Contains Feature values to be written for a specific entity.
  • Request message for [FeaturestoreOnlineServingService.WriteFeatureValues][google.cloud.aiplatform.v1.FeaturestoreOnlineServingService.WriteFeatureValues].
  • Response message for [FeaturestoreOnlineServingService.WriteFeatureValues][google.cloud.aiplatform.v1.FeaturestoreOnlineServingService.WriteFeatureValues].
  • Request message for [TensorboardService.WriteTensorboardExperimentData][google.cloud.aiplatform.v1.TensorboardService.WriteTensorboardExperimentData].
  • Response message for [TensorboardService.WriteTensorboardExperimentData][google.cloud.aiplatform.v1.TensorboardService.WriteTensorboardExperimentData].
  • Request message for [TensorboardService.WriteTensorboardRunData][google.cloud.aiplatform.v1.TensorboardService.WriteTensorboardRunData].
  • Response message for [TensorboardService.WriteTensorboardRunData][google.cloud.aiplatform.v1.TensorboardService.WriteTensorboardRunData].
  • 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

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