Module gapi_grpc::google::cloud::aiplatform::v1beta1[−][src]

Modules

active_learning_config
artifact
batch_migrate_resources_operation_metadata
batch_prediction_job
batch_read_feature_values_request
dataset_service_client	Generated client implementations.
deployed_index_auth_config
deployed_model
endpoint_service_client	Generated client implementations.
event
execution
explanation_metadata
explanation_metadata_override
explanation_parameters
export_data_config
export_feature_values_request
export_model_operation_metadata
export_model_request
feature
feature_noise_sigma
feature_value
feature_value_destination
featurestore
featurestore_monitoring_config
featurestore_online_serving_service_client	Generated client implementations.
featurestore_service_client	Generated client implementations.
import_data_config
import_feature_values_request
index_endpoint_service_client	Generated client implementations.
index_service_client	Generated client implementations.
input_data_config
job_service_client	Generated client implementations.
measurement
metadata_schema
metadata_service_client	Generated client implementations.
metadata_store
migratable_resource
migrate_resource_request
migrate_resource_response
migration_service_client	Generated client implementations.
model
model_deployment_monitoring_big_query_table
model_deployment_monitoring_job
model_evaluation
model_evaluation_slice
model_monitoring_alert_config
model_monitoring_objective_config
model_monitoring_stats_anomalies
model_service_client	Generated client implementations.
nearest_neighbor_search_operation_metadata
pipeline_job
pipeline_service_client	Generated client implementations.
pipeline_task_detail
pipeline_task_executor_detail
prediction_service_client	Generated client implementations.
read_feature_values_response
sample_config
sampling_strategy
schema
search_model_deployment_monitoring_stats_anomalies_request
smooth_grad_config
specialist_pool_service_client	Generated client implementations.
study
study_spec
tensorboard_service_client	Generated client implementations.
tensorboard_time_series
threshold_config
time_series_data_point
trial
user_action_reference
value
vizier_service_client	Generated client implementations.
worker_pool_spec

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.v1beta1.MetadataService.AddContextArtifactsAndExecutions].
AddContextArtifactsAndExecutionsResponse	Response message for [MetadataService.AddContextArtifactsAndExecutions][google.cloud.aiplatform.v1beta1.MetadataService.AddContextArtifactsAndExecutions].
AddContextChildrenRequest	Request message for [MetadataService.AddContextChildren][google.cloud.aiplatform.v1beta1.MetadataService.AddContextChildren].
AddContextChildrenResponse	Response message for [MetadataService.AddContextChildren][google.cloud.aiplatform.v1beta1.MetadataService.AddContextChildren].
AddExecutionEventsRequest	Request message for [MetadataService.AddExecutionEvents][google.cloud.aiplatform.v1beta1.MetadataService.AddExecutionEvents].
AddExecutionEventsResponse	Response message for [MetadataService.AddExecutionEvents][google.cloud.aiplatform.v1beta1.MetadataService.AddExecutionEvents].
AddTrialMeasurementRequest	Request message for [VizierService.AddTrialMeasurement][google.cloud.aiplatform.v1beta1.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.
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.
BatchCreateFeaturesOperationMetadata	Details of operations that perform batch create Features.
BatchCreateFeaturesRequest	Request message for [FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.BatchCreateFeatures].
BatchCreateFeaturesResponse	Response message for [FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.BatchCreateFeatures].
BatchDedicatedResources	A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.
BatchMigrateResourcesOperationMetadata	Runtime operation information for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1beta1.MigrationService.BatchMigrateResources].
BatchMigrateResourcesRequest	Request message for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1beta1.MigrationService.BatchMigrateResources].
BatchMigrateResourcesResponse	Response message for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1beta1.MigrationService.BatchMigrateResources].
BatchPredictionJob	A job that uses a [Model][google.cloud.aiplatform.v1beta1.BatchPredictionJob.model] to produce predictions on multiple [input instances][google.cloud.aiplatform.v1beta1.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.v1beta1.FeaturestoreService.BatchReadFeatureValues]. (- Next Id: 6 -)
BatchReadFeatureValuesResponse	Response message for [FeaturestoreService.BatchReadFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.BatchReadFeatureValues].
BigQueryDestination	The BigQuery location for the output content.
BigQuerySource	The BigQuery location for the input content.
BoolArray	A list of boolean values.
CancelBatchPredictionJobRequest	Request message for [JobService.CancelBatchPredictionJob][google.cloud.aiplatform.v1beta1.JobService.CancelBatchPredictionJob].
CancelCustomJobRequest	Request message for [JobService.CancelCustomJob][google.cloud.aiplatform.v1beta1.JobService.CancelCustomJob].
CancelDataLabelingJobRequest	Request message for [JobService.CancelDataLabelingJob][google.cloud.aiplatform.v1beta1.JobService.CancelDataLabelingJob].
CancelHyperparameterTuningJobRequest	Request message for [JobService.CancelHyperparameterTuningJob][google.cloud.aiplatform.v1beta1.JobService.CancelHyperparameterTuningJob].
CancelPipelineJobRequest	Request message for [PipelineService.CancelPipelineJob][google.cloud.aiplatform.v1beta1.PipelineService.CancelPipelineJob].
CancelTrainingPipelineRequest	Request message for [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.CancelTrainingPipeline].
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.v1beta1.VizierService.CheckTrialEarlyStoppingState].
CheckTrialEarlyStoppingStateResponse	Response message for [VizierService.CheckTrialEarlyStoppingState][google.cloud.aiplatform.v1beta1.VizierService.CheckTrialEarlyStoppingState].
CompleteTrialRequest	Request message for [VizierService.CompleteTrial][google.cloud.aiplatform.v1beta1.VizierService.CompleteTrial].
CompletionStats	Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
ContainerRegistryDestination	The Container Registry location for the container image.
ContainerSpec	The spec of a Container.
Context	Instance of a general context.
CreateArtifactRequest	Request message for [MetadataService.CreateArtifact][google.cloud.aiplatform.v1beta1.MetadataService.CreateArtifact].
CreateBatchPredictionJobRequest	Request message for [JobService.CreateBatchPredictionJob][google.cloud.aiplatform.v1beta1.JobService.CreateBatchPredictionJob].
CreateContextRequest	Request message for [MetadataService.CreateContext][google.cloud.aiplatform.v1beta1.MetadataService.CreateContext].
CreateCustomJobRequest	Request message for [JobService.CreateCustomJob][google.cloud.aiplatform.v1beta1.JobService.CreateCustomJob].
CreateDataLabelingJobRequest	Request message for [JobService.CreateDataLabelingJob][google.cloud.aiplatform.v1beta1.JobService.CreateDataLabelingJob].
CreateDatasetOperationMetadata	Runtime operation information for [DatasetService.CreateDataset][google.cloud.aiplatform.v1beta1.DatasetService.CreateDataset].
CreateDatasetRequest	Request message for [DatasetService.CreateDataset][google.cloud.aiplatform.v1beta1.DatasetService.CreateDataset].
CreateEndpointOperationMetadata	Runtime operation information for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1beta1.EndpointService.CreateEndpoint].
CreateEndpointRequest	Request message for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1beta1.EndpointService.CreateEndpoint].
CreateEntityTypeOperationMetadata	Details of operations that perform create EntityType.
CreateEntityTypeRequest	Request message for [FeaturestoreService.CreateEntityType][google.cloud.aiplatform.v1beta1.FeaturestoreService.CreateEntityType].
CreateExecutionRequest	Request message for [MetadataService.CreateExecution][google.cloud.aiplatform.v1beta1.MetadataService.CreateExecution].
CreateFeatureOperationMetadata	Details of operations that perform create Feature.
CreateFeatureRequest	Request message for [FeaturestoreService.CreateFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.CreateFeature].
CreateFeaturestoreOperationMetadata	Details of operations that perform create Featurestore.
CreateFeaturestoreRequest	Request message for [FeaturestoreService.CreateFeaturestore][google.cloud.aiplatform.v1beta1.FeaturestoreService.CreateFeaturestore].
CreateHyperparameterTuningJobRequest	Request message for [JobService.CreateHyperparameterTuningJob][google.cloud.aiplatform.v1beta1.JobService.CreateHyperparameterTuningJob].
CreateIndexEndpointOperationMetadata	Runtime operation information for [IndexEndpointService.CreateIndexEndpoint][google.cloud.aiplatform.v1beta1.IndexEndpointService.CreateIndexEndpoint].
CreateIndexEndpointRequest	Request message for [IndexEndpointService.CreateIndexEndpoint][google.cloud.aiplatform.v1beta1.IndexEndpointService.CreateIndexEndpoint].
CreateIndexOperationMetadata	Runtime operation information for [IndexService.CreateIndex][google.cloud.aiplatform.v1beta1.IndexService.CreateIndex].
CreateIndexRequest	Request message for [IndexService.CreateIndex][google.cloud.aiplatform.v1beta1.IndexService.CreateIndex].
CreateMetadataSchemaRequest	Request message for [MetadataService.CreateMetadataSchema][google.cloud.aiplatform.v1beta1.MetadataService.CreateMetadataSchema].
CreateMetadataStoreOperationMetadata	Details of operations that perform [MetadataService.CreateMetadataStore][google.cloud.aiplatform.v1beta1.MetadataService.CreateMetadataStore].
CreateMetadataStoreRequest	Request message for [MetadataService.CreateMetadataStore][google.cloud.aiplatform.v1beta1.MetadataService.CreateMetadataStore].
CreateModelDeploymentMonitoringJobRequest	Request message for [JobService.CreateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1beta1.JobService.CreateModelDeploymentMonitoringJob].
CreatePipelineJobRequest	Request message for [PipelineService.CreatePipelineJob][google.cloud.aiplatform.v1beta1.PipelineService.CreatePipelineJob].
CreateSpecialistPoolOperationMetadata	Runtime operation information for [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.CreateSpecialistPool].
CreateSpecialistPoolRequest	Request message for [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.CreateSpecialistPool].
CreateStudyRequest	Request message for [VizierService.CreateStudy][google.cloud.aiplatform.v1beta1.VizierService.CreateStudy].
CreateTensorboardExperimentRequest	Request message for [TensorboardService.CreateTensorboardExperiment][google.cloud.aiplatform.v1beta1.TensorboardService.CreateTensorboardExperiment].
CreateTensorboardOperationMetadata	Details of operations that perform create Tensorboard.
CreateTensorboardRequest	Request message for [TensorboardService.CreateTensorboard][google.cloud.aiplatform.v1beta1.TensorboardService.CreateTensorboard].
CreateTensorboardRunRequest	Request message for [TensorboardService.CreateTensorboardRun][google.cloud.aiplatform.v1beta1.TensorboardService.CreateTensorboardRun].
CreateTensorboardTimeSeriesRequest	Request message for [TensorboardService.CreateTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.CreateTensorboardTimeSeries].
CreateTrainingPipelineRequest	Request message for [PipelineService.CreateTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.CreateTrainingPipeline].
CreateTrialRequest	Request message for [VizierService.CreateTrial][google.cloud.aiplatform.v1beta1.VizierService.CreateTrial].
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.
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.
DedicatedResources	A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.
DeleteBatchPredictionJobRequest	Request message for [JobService.DeleteBatchPredictionJob][google.cloud.aiplatform.v1beta1.JobService.DeleteBatchPredictionJob].
DeleteContextRequest	Request message for [MetadataService.DeleteContext][google.cloud.aiplatform.v1beta1.MetadataService.DeleteContext].
DeleteCustomJobRequest	Request message for [JobService.DeleteCustomJob][google.cloud.aiplatform.v1beta1.JobService.DeleteCustomJob].
DeleteDataLabelingJobRequest	Request message for [JobService.DeleteDataLabelingJob][google.cloud.aiplatform.v1beta1.JobService.DeleteDataLabelingJob].
DeleteDatasetRequest	Request message for [DatasetService.DeleteDataset][google.cloud.aiplatform.v1beta1.DatasetService.DeleteDataset].
DeleteEndpointRequest	Request message for [EndpointService.DeleteEndpoint][google.cloud.aiplatform.v1beta1.EndpointService.DeleteEndpoint].
DeleteEntityTypeRequest	Request message for [FeaturestoreService.DeleteEntityTypes][].
DeleteFeatureRequest	Request message for [FeaturestoreService.DeleteFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.DeleteFeature].
DeleteFeaturestoreRequest	Request message for [FeaturestoreService.DeleteFeaturestore][google.cloud.aiplatform.v1beta1.FeaturestoreService.DeleteFeaturestore].
DeleteHyperparameterTuningJobRequest	Request message for [JobService.DeleteHyperparameterTuningJob][google.cloud.aiplatform.v1beta1.JobService.DeleteHyperparameterTuningJob].
DeleteIndexEndpointRequest	Request message for [IndexEndpointService.DeleteIndexEndpoint][google.cloud.aiplatform.v1beta1.IndexEndpointService.DeleteIndexEndpoint].
DeleteIndexRequest	Request message for [IndexService.DeleteIndex][google.cloud.aiplatform.v1beta1.IndexService.DeleteIndex].
DeleteMetadataStoreOperationMetadata	Details of operations that perform [MetadataService.DeleteMetadataStore][google.cloud.aiplatform.v1beta1.MetadataService.DeleteMetadataStore].
DeleteMetadataStoreRequest	Request message for [MetadataService.DeleteMetadataStore][google.cloud.aiplatform.v1beta1.MetadataService.DeleteMetadataStore].
DeleteModelDeploymentMonitoringJobRequest	Request message for [JobService.DeleteModelDeploymentMonitoringJob][google.cloud.aiplatform.v1beta1.JobService.DeleteModelDeploymentMonitoringJob].
DeleteModelRequest	Request message for [ModelService.DeleteModel][google.cloud.aiplatform.v1beta1.ModelService.DeleteModel].
DeleteOperationMetadata	Details of operations that perform deletes of any entities.
DeletePipelineJobRequest	Request message for [PipelineService.DeletePipelineJob][google.cloud.aiplatform.v1beta1.PipelineService.DeletePipelineJob].
DeleteSpecialistPoolRequest	Request message for [SpecialistPoolService.DeleteSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.DeleteSpecialistPool].
DeleteStudyRequest	Request message for [VizierService.DeleteStudy][google.cloud.aiplatform.v1beta1.VizierService.DeleteStudy].
DeleteTensorboardExperimentRequest	Request message for [TensorboardService.DeleteTensorboardExperiment][google.cloud.aiplatform.v1beta1.TensorboardService.DeleteTensorboardExperiment].
DeleteTensorboardRequest	Request message for [TensorboardService.DeleteTensorboard][google.cloud.aiplatform.v1beta1.TensorboardService.DeleteTensorboard].
DeleteTensorboardRunRequest	Request message for [TensorboardService.DeleteTensorboardRun][google.cloud.aiplatform.v1beta1.TensorboardService.DeleteTensorboardRun].
DeleteTensorboardTimeSeriesRequest	Request message for [TensorboardService.DeleteTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.DeleteTensorboardTimeSeries].
DeleteTrainingPipelineRequest	Request message for [PipelineService.DeleteTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.DeleteTrainingPipeline].
DeleteTrialRequest	Request message for [VizierService.DeleteTrial][google.cloud.aiplatform.v1beta1.VizierService.DeleteTrial].
DeployIndexOperationMetadata	Runtime operation information for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1beta1.IndexEndpointService.DeployIndex].
DeployIndexRequest	Request message for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1beta1.IndexEndpointService.DeployIndex].
DeployIndexResponse	Response message for [IndexEndpointService.DeployIndex][google.cloud.aiplatform.v1beta1.IndexEndpointService.DeployIndex].
DeployModelOperationMetadata	Runtime operation information for [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel].
DeployModelRequest	Request message for [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.EndpointService.DeployModel].
DeployModelResponse	Response message for [EndpointService.DeployModel][google.cloud.aiplatform.v1beta1.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.
DestinationFeatureSetting
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.
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.
Event	An edge describing the relationship between an Artifact and an Execution in a lineage graph.
Execution	Instance of a general execution.
ExplainRequest	Request message for [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
ExplainResponse	Response message for [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain].
Explanation	Explanation of a prediction (provided in [PredictResponse.predictions][google.cloud.aiplatform.v1beta1.PredictResponse.predictions]) produced by the Model on a given [instance][google.cloud.aiplatform.v1beta1.ExplainRequest.instances].
ExplanationMetadata	Metadata describing the Model’s input and output for explanation.
ExplanationMetadataOverride	The [ExplanationMetadata][google.cloud.aiplatform.v1beta1.ExplanationMetadata] entries that can be overridden at [online explanation][google.cloud.aiplatform.v1beta1.PredictionService.Explain] time.
ExplanationParameters	Parameters to configure explaining for Model’s predictions.
ExplanationSpec	Specification of Model explanation.
ExplanationSpecOverride	The [ExplanationSpec][google.cloud.aiplatform.v1beta1.ExplanationSpec] entries that can be overridden at [online explanation][PredictionService.Explain][google.cloud.aiplatform.v1beta1.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.v1beta1.DatasetService.ExportData].
ExportDataRequest	Request message for [DatasetService.ExportData][google.cloud.aiplatform.v1beta1.DatasetService.ExportData].
ExportDataResponse	Response message for [DatasetService.ExportData][google.cloud.aiplatform.v1beta1.DatasetService.ExportData].
ExportFeatureValuesOperationMetadata	Details of operations that exports Features values.
ExportFeatureValuesRequest	Request message for [FeaturestoreService.ExportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ExportFeatureValues].
ExportFeatureValuesResponse	Response message for [FeaturestoreService.ExportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ExportFeatureValues].
ExportModelOperationMetadata	Details of [ModelService.ExportModel][google.cloud.aiplatform.v1beta1.ModelService.ExportModel] operation.
ExportModelRequest	Request message for [ModelService.ExportModel][google.cloud.aiplatform.v1beta1.ModelService.ExportModel].
ExportModelResponse	Response message of [ModelService.ExportModel][google.cloud.aiplatform.v1beta1.ModelService.ExportModel] operation.
ExportTensorboardTimeSeriesDataRequest	Request message for [TensorboardService.ExportTensorboardTimeSeriesData][google.cloud.aiplatform.v1beta1.TensorboardService.ExportTensorboardTimeSeriesData].
ExportTensorboardTimeSeriesDataResponse	Response message for [TensorboardService.ExportTensorboardTimeSeriesData][google.cloud.aiplatform.v1beta1.TensorboardService.ExportTensorboardTimeSeriesData].
Feature	Feature Metadata information that describes an attribute of an entity type. For example, apple is an entity type, and color is a feature that describes apple.
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.
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. NEXT ID: 15
FeatureValueDestination	A destination location for Feature values and format.
FeatureValueList	Container for list of values.
Featurestore	Featurestore configuration information on how the Featurestore is configured.
FeaturestoreMonitoringConfig	Configuration of how features in Featurestore are monitored.
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).
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.
GcsDestination	The Google Cloud Storage location where the output is to be written to.
GcsSource	The Google Cloud Storage location for the input content.
GenericOperationMetadata	Generic Metadata shared by all operations.
GetAnnotationSpecRequest	Request message for [DatasetService.GetAnnotationSpec][google.cloud.aiplatform.v1beta1.DatasetService.GetAnnotationSpec].
GetArtifactRequest	Request message for [MetadataService.GetArtifact][google.cloud.aiplatform.v1beta1.MetadataService.GetArtifact].
GetBatchPredictionJobRequest	Request message for [JobService.GetBatchPredictionJob][google.cloud.aiplatform.v1beta1.JobService.GetBatchPredictionJob].
GetContextRequest	Request message for [MetadataService.GetContext][google.cloud.aiplatform.v1beta1.MetadataService.GetContext].
GetCustomJobRequest	Request message for [JobService.GetCustomJob][google.cloud.aiplatform.v1beta1.JobService.GetCustomJob].
GetDataLabelingJobRequest	Request message for [JobService.GetDataLabelingJob][google.cloud.aiplatform.v1beta1.JobService.GetDataLabelingJob].
GetDatasetRequest	Request message for [DatasetService.GetDataset][google.cloud.aiplatform.v1beta1.DatasetService.GetDataset].
GetEndpointRequest	Request message for [EndpointService.GetEndpoint][google.cloud.aiplatform.v1beta1.EndpointService.GetEndpoint]
GetEntityTypeRequest	Request message for [FeaturestoreService.GetEntityType][google.cloud.aiplatform.v1beta1.FeaturestoreService.GetEntityType].
GetExecutionRequest	Request message for [MetadataService.GetExecution][google.cloud.aiplatform.v1beta1.MetadataService.GetExecution].
GetFeatureRequest	Request message for [FeaturestoreService.GetFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.GetFeature].
GetFeaturestoreRequest	Request message for [FeaturestoreService.GetFeaturestore][google.cloud.aiplatform.v1beta1.FeaturestoreService.GetFeaturestore].
GetHyperparameterTuningJobRequest	Request message for [JobService.GetHyperparameterTuningJob][google.cloud.aiplatform.v1beta1.JobService.GetHyperparameterTuningJob].
GetIndexEndpointRequest	Request message for [IndexEndpointService.GetIndexEndpoint][google.cloud.aiplatform.v1beta1.IndexEndpointService.GetIndexEndpoint]
GetIndexRequest	Request message for [IndexService.GetIndex][google.cloud.aiplatform.v1beta1.IndexService.GetIndex]
GetMetadataSchemaRequest	Request message for [MetadataService.GetMetadataSchema][google.cloud.aiplatform.v1beta1.MetadataService.GetMetadataSchema].
GetMetadataStoreRequest	Request message for [MetadataService.GetMetadataStore][google.cloud.aiplatform.v1beta1.MetadataService.GetMetadataStore].
GetModelDeploymentMonitoringJobRequest	Request message for [JobService.GetModelDeploymentMonitoringJob][google.cloud.aiplatform.v1beta1.JobService.GetModelDeploymentMonitoringJob].
GetModelEvaluationRequest	Request message for [ModelService.GetModelEvaluation][google.cloud.aiplatform.v1beta1.ModelService.GetModelEvaluation].
GetModelEvaluationSliceRequest	Request message for [ModelService.GetModelEvaluationSlice][google.cloud.aiplatform.v1beta1.ModelService.GetModelEvaluationSlice].
GetModelRequest	Request message for [ModelService.GetModel][google.cloud.aiplatform.v1beta1.ModelService.GetModel].
GetPipelineJobRequest	Request message for [PipelineService.GetPipelineJob][google.cloud.aiplatform.v1beta1.PipelineService.GetPipelineJob].
GetSpecialistPoolRequest	Request message for [SpecialistPoolService.GetSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.GetSpecialistPool].
GetStudyRequest	Request message for [VizierService.GetStudy][google.cloud.aiplatform.v1beta1.VizierService.GetStudy].
GetTensorboardExperimentRequest	Request message for [TensorboardService.GetTensorboardExperiment][google.cloud.aiplatform.v1beta1.TensorboardService.GetTensorboardExperiment].
GetTensorboardRequest	Request message for [TensorboardService.GetTensorboard][google.cloud.aiplatform.v1beta1.TensorboardService.GetTensorboard].
GetTensorboardRunRequest	Request message for [TensorboardService.GetTensorboardRun][google.cloud.aiplatform.v1beta1.TensorboardService.GetTensorboardRun].
GetTensorboardTimeSeriesRequest	Request message for [TensorboardService.GetTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.GetTensorboardTimeSeries].
GetTrainingPipelineRequest	Request message for [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1beta1.PipelineService.GetTrainingPipeline].
GetTrialRequest	Request message for [VizierService.GetTrial][google.cloud.aiplatform.v1beta1.VizierService.GetTrial].
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.v1beta1.DatasetService.ImportData].
ImportDataRequest	Request message for [DatasetService.ImportData][google.cloud.aiplatform.v1beta1.DatasetService.ImportData].
ImportDataResponse	Response message for [DatasetService.ImportData][google.cloud.aiplatform.v1beta1.DatasetService.ImportData].
ImportFeatureValuesOperationMetadata	Details of operations that perform import feature values.
ImportFeatureValuesRequest	Request message for [FeaturestoreService.ImportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ImportFeatureValues].
ImportFeatureValuesResponse	Response message for [FeaturestoreService.ImportFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreService.ImportFeatureValues].
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.
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 services access.
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
LineageSubgraph	A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.
ListAnnotationsRequest	Request message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1beta1.DatasetService.ListAnnotations].
ListAnnotationsResponse	Response message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1beta1.DatasetService.ListAnnotations].
ListArtifactsRequest	Request message for [MetadataService.ListArtifacts][google.cloud.aiplatform.v1beta1.MetadataService.ListArtifacts].
ListArtifactsResponse	Response message for [MetadataService.ListArtifacts][google.cloud.aiplatform.v1beta1.MetadataService.ListArtifacts].
ListBatchPredictionJobsRequest	Request message for [JobService.ListBatchPredictionJobs][google.cloud.aiplatform.v1beta1.JobService.ListBatchPredictionJobs].
ListBatchPredictionJobsResponse	Response message for [JobService.ListBatchPredictionJobs][google.cloud.aiplatform.v1beta1.JobService.ListBatchPredictionJobs]
ListContextsRequest	Request message for [MetadataService.ListContexts][google.cloud.aiplatform.v1beta1.MetadataService.ListContexts]
ListContextsResponse	Response message for [MetadataService.ListContexts][google.cloud.aiplatform.v1beta1.MetadataService.ListContexts].
ListCustomJobsRequest	Request message for [JobService.ListCustomJobs][google.cloud.aiplatform.v1beta1.JobService.ListCustomJobs].
ListCustomJobsResponse	Response message for [JobService.ListCustomJobs][google.cloud.aiplatform.v1beta1.JobService.ListCustomJobs]
ListDataItemsRequest	Request message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1beta1.DatasetService.ListDataItems].
ListDataItemsResponse	Response message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1beta1.DatasetService.ListDataItems].
ListDataLabelingJobsRequest	Request message for [JobService.ListDataLabelingJobs][google.cloud.aiplatform.v1beta1.JobService.ListDataLabelingJobs].
ListDataLabelingJobsResponse	Response message for [JobService.ListDataLabelingJobs][google.cloud.aiplatform.v1beta1.JobService.ListDataLabelingJobs].
ListDatasetsRequest	Request message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasets].
ListDatasetsResponse	Response message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasets].
ListEndpointsRequest	Request message for [EndpointService.ListEndpoints][google.cloud.aiplatform.v1beta1.EndpointService.ListEndpoints].
ListEndpointsResponse	Response message for [EndpointService.ListEndpoints][google.cloud.aiplatform.v1beta1.EndpointService.ListEndpoints].
ListEntityTypesRequest	Request message for [FeaturestoreService.ListEntityTypes][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListEntityTypes].
ListEntityTypesResponse	Response message for [FeaturestoreService.ListEntityTypes][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListEntityTypes].
ListExecutionsRequest	Request message for [MetadataService.ListExecutions][google.cloud.aiplatform.v1beta1.MetadataService.ListExecutions].
ListExecutionsResponse	Response message for [MetadataService.ListExecutions][google.cloud.aiplatform.v1beta1.MetadataService.ListExecutions].
ListFeaturesRequest	Request message for [FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeatures].
ListFeaturesResponse	Response message for [FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeatures].
ListFeaturestoresRequest	Request message for [FeaturestoreService.ListFeaturestores][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeaturestores].
ListFeaturestoresResponse	Response message for [FeaturestoreService.ListFeaturestores][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeaturestores].
ListHyperparameterTuningJobsRequest	Request message for [JobService.ListHyperparameterTuningJobs][google.cloud.aiplatform.v1beta1.JobService.ListHyperparameterTuningJobs].
ListHyperparameterTuningJobsResponse	Response message for [JobService.ListHyperparameterTuningJobs][google.cloud.aiplatform.v1beta1.JobService.ListHyperparameterTuningJobs]
ListIndexEndpointsRequest	Request message for [IndexEndpointService.ListIndexEndpoints][google.cloud.aiplatform.v1beta1.IndexEndpointService.ListIndexEndpoints].
ListIndexEndpointsResponse	Response message for [IndexEndpointService.ListIndexEndpoints][google.cloud.aiplatform.v1beta1.IndexEndpointService.ListIndexEndpoints].
ListIndexesRequest	Request message for [IndexService.ListIndexes][google.cloud.aiplatform.v1beta1.IndexService.ListIndexes].
ListIndexesResponse	Response message for [IndexService.ListIndexes][google.cloud.aiplatform.v1beta1.IndexService.ListIndexes].
ListMetadataSchemasRequest	Request message for [MetadataService.ListMetadataSchemas][google.cloud.aiplatform.v1beta1.MetadataService.ListMetadataSchemas].
ListMetadataSchemasResponse	Response message for [MetadataService.ListMetadataSchemas][google.cloud.aiplatform.v1beta1.MetadataService.ListMetadataSchemas].
ListMetadataStoresRequest	Request message for [MetadataService.ListMetadataStores][google.cloud.aiplatform.v1beta1.MetadataService.ListMetadataStores].
ListMetadataStoresResponse	Response message for [MetadataService.ListMetadataStores][google.cloud.aiplatform.v1beta1.MetadataService.ListMetadataStores].
ListModelDeploymentMonitoringJobsRequest	Request message for [JobService.ListModelDeploymentMonitoringJobs][google.cloud.aiplatform.v1beta1.JobService.ListModelDeploymentMonitoringJobs].
ListModelDeploymentMonitoringJobsResponse	Response message for [JobService.ListModelDeploymentMonitoringJobs][google.cloud.aiplatform.v1beta1.JobService.ListModelDeploymentMonitoringJobs].
ListModelEvaluationSlicesRequest	Request message for [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1beta1.ModelService.ListModelEvaluationSlices].
ListModelEvaluationSlicesResponse	Response message for [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1beta1.ModelService.ListModelEvaluationSlices].
ListModelEvaluationsRequest	Request message for [ModelService.ListModelEvaluations][google.cloud.aiplatform.v1beta1.ModelService.ListModelEvaluations].
ListModelEvaluationsResponse	Response message for [ModelService.ListModelEvaluations][google.cloud.aiplatform.v1beta1.ModelService.ListModelEvaluations].
ListModelsRequest	Request message for [ModelService.ListModels][google.cloud.aiplatform.v1beta1.ModelService.ListModels].
ListModelsResponse	Response message for [ModelService.ListModels][google.cloud.aiplatform.v1beta1.ModelService.ListModels]
ListOptimalTrialsRequest	Request message for [VizierService.ListOptimalTrials][google.cloud.aiplatform.v1beta1.VizierService.ListOptimalTrials].
ListOptimalTrialsResponse	Response message for [VizierService.ListOptimalTrials][google.cloud.aiplatform.v1beta1.VizierService.ListOptimalTrials].
ListPipelineJobsRequest	Request message for [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1beta1.PipelineService.ListPipelineJobs].
ListPipelineJobsResponse	Response message for [PipelineService.ListPipelineJobs][google.cloud.aiplatform.v1beta1.PipelineService.ListPipelineJobs]
ListSpecialistPoolsRequest	Request message for [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1beta1.SpecialistPoolService.ListSpecialistPools].
ListSpecialistPoolsResponse	Response message for [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1beta1.SpecialistPoolService.ListSpecialistPools].
ListStudiesRequest	Request message for [VizierService.ListStudies][google.cloud.aiplatform.v1beta1.VizierService.ListStudies].
ListStudiesResponse	Response message for [VizierService.ListStudies][google.cloud.aiplatform.v1beta1.VizierService.ListStudies].
ListTensorboardExperimentsRequest	Request message for [TensorboardService.ListTensorboardExperiments][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardExperiments].
ListTensorboardExperimentsResponse	Response message for [TensorboardService.ListTensorboardExperiments][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardExperiments].
ListTensorboardRunsRequest	Request message for [TensorboardService.ListTensorboardRuns][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardRuns].
ListTensorboardRunsResponse	Response message for [TensorboardService.ListTensorboardRuns][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardRuns].
ListTensorboardTimeSeriesRequest	Request message for [TensorboardService.ListTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardTimeSeries].
ListTensorboardTimeSeriesResponse	Response message for [TensorboardService.ListTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardTimeSeries].
ListTensorboardsRequest	Request message for [TensorboardService.ListTensorboards][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboards].
ListTensorboardsResponse	Response message for [TensorboardService.ListTensorboards][google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboards].
ListTrainingPipelinesRequest	Request message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1beta1.PipelineService.ListTrainingPipelines].
ListTrainingPipelinesResponse	Response message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1beta1.PipelineService.ListTrainingPipelines]
ListTrialsRequest	Request message for [VizierService.ListTrials][google.cloud.aiplatform.v1beta1.VizierService.ListTrials].
ListTrialsResponse	Response message for [VizierService.ListTrials][google.cloud.aiplatform.v1beta1.VizierService.ListTrials].
LookupStudyRequest	Request message for [VizierService.LookupStudy][google.cloud.aiplatform.v1beta1.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.
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.
ModelMonitoringAlertConfig	Next ID: 2
ModelMonitoringObjectiveConfig	Next ID: 6
ModelMonitoringStatsAnomalies	Statistics and anomalies generated by Model Monitoring.
NearestNeighborSearchOperationMetadata	Runtime operation metadata with regard to Matching Engine Index.
PauseModelDeploymentMonitoringJobRequest	Request message for [JobService.PauseModelDeploymentMonitoringJob][google.cloud.aiplatform.v1beta1.JobService.PauseModelDeploymentMonitoringJob].
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.
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.v1beta1.PredictionService.Predict].
PredictResponse	Response message for [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict].
PredictSchemata	Contains the schemata used in Model’s predictions and explanations via [PredictionService.Predict][google.cloud.aiplatform.v1beta1.PredictionService.Predict], [PredictionService.Explain][google.cloud.aiplatform.v1beta1.PredictionService.Explain] and [BatchPredictionJob][google.cloud.aiplatform.v1beta1.BatchPredictionJob].
PythonPackageSpec	The spec of a Python packaged code.
QueryArtifactLineageSubgraphRequest	Request message for [MetadataService.QueryArtifactLineageSubgraph][google.cloud.aiplatform.v1beta1.MetadataService.QueryArtifactLineageSubgraph].
QueryContextLineageSubgraphRequest	Request message for [MetadataService.QueryContextLineageSubgraph][google.cloud.aiplatform.v1beta1.MetadataService.QueryContextLineageSubgraph].
QueryExecutionInputsAndOutputsRequest	Request message for [MetadataService.QueryExecutionInputsAndOutputs][google.cloud.aiplatform.v1beta1.MetadataService.QueryExecutionInputsAndOutputs].
ReadFeatureValuesRequest	Request message for [FeaturestoreOnlineServingService.ReadFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreOnlineServingService.ReadFeatureValues].
ReadFeatureValuesResponse	Response message for [FeaturestoreOnlineServingService.ReadFeatureValues][google.cloud.aiplatform.v1beta1.FeaturestoreOnlineServingService.ReadFeatureValues].
ReadTensorboardBlobDataRequest	Request message for [TensorboardService.ReadTensorboardBlobData][google.cloud.aiplatform.v1beta1.TensorboardService.ReadTensorboardBlobData].
ReadTensorboardBlobDataResponse	Response message for [TensorboardService.ReadTensorboardBlobData][google.cloud.aiplatform.v1beta1.TensorboardService.ReadTensorboardBlobData].
ReadTensorboardTimeSeriesDataRequest	Request message for [TensorboardService.ReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1beta1.TensorboardService.ReadTensorboardTimeSeriesData].
ReadTensorboardTimeSeriesDataResponse	Response message for [TensorboardService.ReadTensorboardTimeSeriesData][google.cloud.aiplatform.v1beta1.TensorboardService.ReadTensorboardTimeSeriesData].
ResourcesConsumed	Statistics information about resource consumption.
ResumeModelDeploymentMonitoringJobRequest	Request message for [JobService.ResumeModelDeploymentMonitoringJob][google.cloud.aiplatform.v1beta1.JobService.ResumeModelDeploymentMonitoringJob].
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. Next ID: 2
Scalar	One point viewable on a scalar metric plot.
Scheduling	All parameters related to queuing and scheduling of custom jobs.
SearchFeaturesRequest	Request message for [FeaturestoreService.SearchFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.SearchFeatures].
SearchFeaturesResponse	Response message for [FeaturestoreService.SearchFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.SearchFeatures].
SearchMigratableResourcesRequest	Request message for [MigrationService.SearchMigratableResources][google.cloud.aiplatform.v1beta1.MigrationService.SearchMigratableResources].
SearchMigratableResourcesResponse	Response message for [MigrationService.SearchMigratableResources][google.cloud.aiplatform.v1beta1.MigrationService.SearchMigratableResources].
SearchModelDeploymentMonitoringStatsAnomaliesRequest	Request message for [JobService.SearchModelDeploymentMonitoringStatsAnomalies][google.cloud.aiplatform.v1beta1.JobService.SearchModelDeploymentMonitoringStatsAnomalies].
SearchModelDeploymentMonitoringStatsAnomaliesResponse	Response message for [JobService.SearchModelDeploymentMonitoringStatsAnomalies][google.cloud.aiplatform.v1beta1.JobService.SearchModelDeploymentMonitoringStatsAnomalies].
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 who are responsible for managing the labelers 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 labelers work with the jobs using CrowdCompute console.
StopTrialRequest	Request message for [VizierService.StopTrial][google.cloud.aiplatform.v1beta1.VizierService.StopTrial].
StreamingReadFeatureValuesRequest	Request message for [FeaturestoreOnlineServingService.StreamingFeatureValuesRead][].
StringArray	A list of string values.
Study	A message representing a Study.
StudySpec	Represents specification of a Study.
SuggestTrialsMetadata	Details of operations that perform Trials suggestion.
SuggestTrialsRequest	Request message for [VizierService.SuggestTrials][google.cloud.aiplatform.v1beta1.VizierService.SuggestTrials].
SuggestTrialsResponse	Response message for [VizierService.SuggestTrials][google.cloud.aiplatform.v1beta1.VizierService.SuggestTrials].
Tensorboard	Tensorboard is a physical database that stores users’ training metrics. A default Tensorboard is provided in each region of a GCP 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. Next ID: 3
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.
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.v1beta1.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.
UndeployIndexOperationMetadata	Runtime operation information for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1beta1.IndexEndpointService.UndeployIndex].
UndeployIndexRequest	Request message for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1beta1.IndexEndpointService.UndeployIndex].
UndeployIndexResponse	Response message for [IndexEndpointService.UndeployIndex][google.cloud.aiplatform.v1beta1.IndexEndpointService.UndeployIndex].
UndeployModelOperationMetadata	Runtime operation information for [EndpointService.UndeployModel][google.cloud.aiplatform.v1beta1.EndpointService.UndeployModel].
UndeployModelRequest	Request message for [EndpointService.UndeployModel][google.cloud.aiplatform.v1beta1.EndpointService.UndeployModel].
UndeployModelResponse	Response message for [EndpointService.UndeployModel][google.cloud.aiplatform.v1beta1.EndpointService.UndeployModel].
UpdateArtifactRequest	Request message for [MetadataService.UpdateArtifact][google.cloud.aiplatform.v1beta1.MetadataService.UpdateArtifact].
UpdateContextRequest	Request message for [MetadataService.UpdateContext][google.cloud.aiplatform.v1beta1.MetadataService.UpdateContext].
UpdateDatasetRequest	Request message for [DatasetService.UpdateDataset][google.cloud.aiplatform.v1beta1.DatasetService.UpdateDataset].
UpdateEndpointRequest	Request message for [EndpointService.UpdateEndpoint][google.cloud.aiplatform.v1beta1.EndpointService.UpdateEndpoint].
UpdateEntityTypeRequest	Request message for [FeaturestoreService.UpdateEntityType][google.cloud.aiplatform.v1beta1.FeaturestoreService.UpdateEntityType].
UpdateExecutionRequest	Request message for [MetadataService.UpdateExecution][google.cloud.aiplatform.v1beta1.MetadataService.UpdateExecution].
UpdateFeatureRequest	Request message for [FeaturestoreService.UpdateFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.UpdateFeature].
UpdateFeaturestoreOperationMetadata	Details of operations that perform update Featurestore.
UpdateFeaturestoreRequest	Request message for [FeaturestoreService.UpdateFeaturestore][google.cloud.aiplatform.v1beta1.FeaturestoreService.UpdateFeaturestore].
UpdateIndexEndpointRequest	Request message for [IndexEndpointService.UpdateIndexEndpoint][google.cloud.aiplatform.v1beta1.IndexEndpointService.UpdateIndexEndpoint].
UpdateIndexOperationMetadata	Runtime operation information for [IndexService.UpdateIndex][google.cloud.aiplatform.v1beta1.IndexService.UpdateIndex].
UpdateIndexRequest	Request message for [IndexService.UpdateIndex][google.cloud.aiplatform.v1beta1.IndexService.UpdateIndex].
UpdateModelDeploymentMonitoringJobOperationMetadata	Runtime operation information for [JobService.UpdateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1beta1.JobService.UpdateModelDeploymentMonitoringJob].
UpdateModelDeploymentMonitoringJobRequest	Request message for [JobService.UpdateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1beta1.JobService.UpdateModelDeploymentMonitoringJob].
UpdateModelRequest	Request message for [ModelService.UpdateModel][google.cloud.aiplatform.v1beta1.ModelService.UpdateModel].
UpdateSpecialistPoolOperationMetadata	Runtime operation metadata for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.UpdateSpecialistPool].
UpdateSpecialistPoolRequest	Request message for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1beta1.SpecialistPoolService.UpdateSpecialistPool].
UpdateTensorboardExperimentRequest	Request message for [TensorboardService.UpdateTensorboardExperiment][google.cloud.aiplatform.v1beta1.TensorboardService.UpdateTensorboardExperiment].
UpdateTensorboardOperationMetadata	Details of operations that perform update Tensorboard.
UpdateTensorboardRequest	Request message for [TensorboardService.UpdateTensorboard][google.cloud.aiplatform.v1beta1.TensorboardService.UpdateTensorboard].
UpdateTensorboardRunRequest	Request message for [TensorboardService.UpdateTensorboardRun][google.cloud.aiplatform.v1beta1.TensorboardService.UpdateTensorboardRun].
UpdateTensorboardTimeSeriesRequest	Request message for [TensorboardService.UpdateTensorboardTimeSeries][google.cloud.aiplatform.v1beta1.TensorboardService.UpdateTensorboardTimeSeries].
UploadModelOperationMetadata	Details of [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel] operation.
UploadModelRequest	Request message for [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel].
UploadModelResponse	Response message of [ModelService.UploadModel][google.cloud.aiplatform.v1beta1.ModelService.UploadModel] operation.
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.
WorkerPoolSpec	Represents the spec of a worker pool in a job.
WriteTensorboardRunDataRequest	Request message for [TensorboardService.WriteTensorboardRunData][google.cloud.aiplatform.v1beta1.TensorboardService.WriteTensorboardRunData].
WriteTensorboardRunDataResponse	Response message for [TensorboardService.WriteTensorboardRunData][google.cloud.aiplatform.v1beta1.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.
JobState	Describes the state of a job.
ModelDeploymentMonitoringObjectiveType	The Model Monitoring Objective types.
PipelineState	Describes the state of a pipeline.