Package types (1.16.1)

API documentation for aiplatform_v1.types package.

Classes

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.

This message has oneof_ fields (mutually exclusive fields). For each oneof, at most one member field can be set at the same time. Setting any member of the oneof automatically clears all other members.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

AddContextArtifactsAndExecutionsRequest

Request message for MetadataService.AddContextArtifactsAndExecutions.

AddContextArtifactsAndExecutionsResponse

Response message for MetadataService.AddContextArtifactsAndExecutions.

AddContextChildrenRequest

Request message for MetadataService.AddContextChildren.

AddContextChildrenResponse

Response message for MetadataService.AddContextChildren.

AddExecutionEventsRequest

Request message for MetadataService.AddExecutionEvents.

AddExecutionEventsResponse

Response message for MetadataService.AddExecutionEvents.

AddTrialMeasurementRequest

Request message for 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.

BatchCreateFeaturesResponse

Response message for FeaturestoreService.BatchCreateFeatures.

BatchCreateTensorboardRunsRequest

Request message for TensorboardService.BatchCreateTensorboardRuns.

BatchCreateTensorboardRunsResponse

Response message for TensorboardService.BatchCreateTensorboardRuns.

BatchCreateTensorboardTimeSeriesRequest

Request message for TensorboardService.BatchCreateTensorboardTimeSeries.

BatchCreateTensorboardTimeSeriesResponse

Response message for TensorboardService.BatchCreateTensorboardTimeSeries.

BatchDedicatedResources

A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration.

BatchImportModelEvaluationSlicesRequest

Request message for ModelService.BatchImportModelEvaluationSlices

BatchImportModelEvaluationSlicesResponse

Response message for ModelService.BatchImportModelEvaluationSlices

BatchMigrateResourcesOperationMetadata

Runtime operation information for MigrationService.BatchMigrateResources.

BatchMigrateResourcesRequest

Request message for MigrationService.BatchMigrateResources.

BatchMigrateResourcesResponse

Response message for MigrationService.BatchMigrateResources.

BatchPredictionJob

A job that uses a Model to produce predictions on multiple [input instances][google.cloud.aiplatform.v1.BatchPredictionJob.input_config]. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.

BatchReadFeatureValuesOperationMetadata

Details of operations that batch reads Feature values.

BatchReadFeatureValuesRequest

Request message for FeaturestoreService.BatchReadFeatureValues.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

BatchReadFeatureValuesResponse

Response message for FeaturestoreService.BatchReadFeatureValues.

BatchReadTensorboardTimeSeriesDataRequest

Request message for TensorboardService.BatchReadTensorboardTimeSeriesData.

BatchReadTensorboardTimeSeriesDataResponse

Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.

BigQueryDestination

The BigQuery location for the output content.

BigQuerySource

The BigQuery location for the input content.

BlurBaselineConfig

Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383

BoolArray

A list of boolean values.

CancelBatchPredictionJobRequest

Request message for JobService.CancelBatchPredictionJob.

CancelCustomJobRequest

Request message for JobService.CancelCustomJob.

CancelDataLabelingJobRequest

Request message for JobService.CancelDataLabelingJob.

CancelHyperparameterTuningJobRequest

Request message for JobService.CancelHyperparameterTuningJob.

CancelPipelineJobRequest

Request message for PipelineService.CancelPipelineJob.

CancelTrainingPipelineRequest

Request message for 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.

CheckTrialEarlyStoppingStateResponse

Response message for VizierService.CheckTrialEarlyStoppingState.

CompleteTrialRequest

Request message for 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.

CreateBatchPredictionJobRequest

Request message for JobService.CreateBatchPredictionJob.

CreateContextRequest

Request message for MetadataService.CreateContext.

CreateCustomJobRequest

Request message for JobService.CreateCustomJob.

CreateDataLabelingJobRequest

Request message for JobService.CreateDataLabelingJob.

CreateDatasetOperationMetadata

Runtime operation information for DatasetService.CreateDataset.

CreateDatasetRequest

Request message for DatasetService.CreateDataset.

CreateEndpointOperationMetadata

Runtime operation information for EndpointService.CreateEndpoint.

CreateEndpointRequest

Request message for EndpointService.CreateEndpoint.

CreateEntityTypeOperationMetadata

Details of operations that perform create EntityType.

CreateEntityTypeRequest

Request message for FeaturestoreService.CreateEntityType.

CreateExecutionRequest

Request message for MetadataService.CreateExecution.

CreateFeatureOperationMetadata

Details of operations that perform create Feature.

CreateFeatureRequest

Request message for FeaturestoreService.CreateFeature.

CreateFeaturestoreOperationMetadata

Details of operations that perform create Featurestore.

CreateFeaturestoreRequest

Request message for FeaturestoreService.CreateFeaturestore.

CreateHyperparameterTuningJobRequest

Request message for JobService.CreateHyperparameterTuningJob.

CreateIndexEndpointOperationMetadata

Runtime operation information for IndexEndpointService.CreateIndexEndpoint.

CreateIndexEndpointRequest

Request message for IndexEndpointService.CreateIndexEndpoint.

CreateIndexOperationMetadata

Runtime operation information for IndexService.CreateIndex.

CreateIndexRequest

Request message for IndexService.CreateIndex.

CreateMetadataSchemaRequest

Request message for MetadataService.CreateMetadataSchema.

CreateMetadataStoreOperationMetadata

Details of operations that perform MetadataService.CreateMetadataStore.

CreateMetadataStoreRequest

Request message for MetadataService.CreateMetadataStore.

CreateModelDeploymentMonitoringJobRequest

Request message for JobService.CreateModelDeploymentMonitoringJob.

CreatePipelineJobRequest

Request message for PipelineService.CreatePipelineJob.

CreateSpecialistPoolOperationMetadata

Runtime operation information for SpecialistPoolService.CreateSpecialistPool.

CreateSpecialistPoolRequest

Request message for SpecialistPoolService.CreateSpecialistPool.

CreateStudyRequest

Request message for VizierService.CreateStudy.

CreateTensorboardExperimentRequest

Request message for TensorboardService.CreateTensorboardExperiment.

CreateTensorboardOperationMetadata

Details of operations that perform create Tensorboard.

CreateTensorboardRequest

Request message for TensorboardService.CreateTensorboard.

CreateTensorboardRunRequest

Request message for TensorboardService.CreateTensorboardRun.

CreateTensorboardTimeSeriesRequest

Request message for TensorboardService.CreateTensorboardTimeSeries.

CreateTrainingPipelineRequest

Request message for PipelineService.CreateTrainingPipeline.

CreateTrialRequest

Request message for 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. Next Id: 15

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.

DeleteArtifactRequest

Request message for MetadataService.DeleteArtifact.

DeleteBatchPredictionJobRequest

Request message for JobService.DeleteBatchPredictionJob.

DeleteContextRequest

Request message for MetadataService.DeleteContext.

DeleteCustomJobRequest

Request message for JobService.DeleteCustomJob.

DeleteDataLabelingJobRequest

Request message for JobService.DeleteDataLabelingJob.

DeleteDatasetRequest

Request message for DatasetService.DeleteDataset.

DeleteEndpointRequest

Request message for EndpointService.DeleteEndpoint.

DeleteEntityTypeRequest

Request message for [FeaturestoreService.DeleteEntityTypes][].

DeleteExecutionRequest

Request message for MetadataService.DeleteExecution.

DeleteFeatureRequest

Request message for FeaturestoreService.DeleteFeature.

DeleteFeaturestoreRequest

Request message for FeaturestoreService.DeleteFeaturestore.

DeleteHyperparameterTuningJobRequest

Request message for JobService.DeleteHyperparameterTuningJob.

DeleteIndexEndpointRequest

Request message for IndexEndpointService.DeleteIndexEndpoint.

DeleteIndexRequest

Request message for IndexService.DeleteIndex.

DeleteMetadataStoreOperationMetadata

Details of operations that perform MetadataService.DeleteMetadataStore.

DeleteMetadataStoreRequest

Request message for MetadataService.DeleteMetadataStore.

DeleteModelDeploymentMonitoringJobRequest

Request message for JobService.DeleteModelDeploymentMonitoringJob.

DeleteModelRequest

Request message for ModelService.DeleteModel.

DeleteModelVersionRequest

Request message for ModelService.DeleteModelVersion.

DeleteOperationMetadata

Details of operations that perform deletes of any entities.

DeletePipelineJobRequest

Request message for PipelineService.DeletePipelineJob.

DeleteSpecialistPoolRequest

Request message for SpecialistPoolService.DeleteSpecialistPool.

DeleteStudyRequest

Request message for VizierService.DeleteStudy.

DeleteTensorboardExperimentRequest

Request message for TensorboardService.DeleteTensorboardExperiment.

DeleteTensorboardRequest

Request message for TensorboardService.DeleteTensorboard.

DeleteTensorboardRunRequest

Request message for TensorboardService.DeleteTensorboardRun.

DeleteTensorboardTimeSeriesRequest

Request message for TensorboardService.DeleteTensorboardTimeSeries.

DeleteTrainingPipelineRequest

Request message for PipelineService.DeleteTrainingPipeline.

DeleteTrialRequest

Request message for VizierService.DeleteTrial.

DeployIndexOperationMetadata

Runtime operation information for IndexEndpointService.DeployIndex.

DeployIndexRequest

Request message for IndexEndpointService.DeployIndex.

DeployIndexResponse

Response message for IndexEndpointService.DeployIndex.

DeployModelOperationMetadata

Runtime operation information for EndpointService.DeployModel.

DeployModelRequest

Request message for EndpointService.DeployModel.

DeployModelResponse

Response message for 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.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

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.

ExamplesOverride

Overrides for example-based explanations.

ExamplesRestrictionsNamespace

Restrictions namespace for example-based explanations overrides.

Execution

Instance of a general execution.

ExplainRequest

Request message for PredictionService.Explain.

ExplainResponse

Response message for PredictionService.Explain.

Explanation

Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance.

ExplanationMetadata

Metadata describing the Model's input and output for explanation.

ExplanationMetadataOverride

The ExplanationMetadata entries that can be overridden at [online explanation][google.cloud.aiplatform.v1.PredictionService.Explain] time.

ExplanationParameters

Parameters to configure explaining for Model's predictions.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

ExplanationSpec

Specification of Model explanation.

ExplanationSpecOverride

The ExplanationSpec entries that can be overridden at [online explanation][google.cloud.aiplatform.v1.PredictionService.Explain] time.

ExportDataConfig

Describes what part of the Dataset is to be exported, the destination of the export and how to export.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

ExportDataOperationMetadata

Runtime operation information for DatasetService.ExportData.

ExportDataRequest

Request message for DatasetService.ExportData.

ExportDataResponse

Response message for DatasetService.ExportData.

ExportFeatureValuesOperationMetadata

Details of operations that exports Features values.

ExportFeatureValuesRequest

Request message for FeaturestoreService.ExportFeatureValues.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

ExportFeatureValuesResponse

Response message for FeaturestoreService.ExportFeatureValues.

ExportModelOperationMetadata

Details of ModelService.ExportModel operation.

ExportModelRequest

Request message for ModelService.ExportModel.

ExportModelResponse

Response message of ModelService.ExportModel operation.

ExportTensorboardTimeSeriesDataRequest

Request message for TensorboardService.ExportTensorboardTimeSeriesData.

ExportTensorboardTimeSeriesDataResponse

Response message for 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.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

FeatureValueDestination

A destination location for Feature values and format.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

FeatureValueList

Container for list of values.

Featurestore

Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values.

FeaturestoreMonitoringConfig

Configuration of how features in Featurestore are monitored.

FilterSplit

Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign).

Supported only for unstructured Datasets.

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.

GetArtifactRequest

Request message for MetadataService.GetArtifact.

GetBatchPredictionJobRequest

Request message for JobService.GetBatchPredictionJob.

GetContextRequest

Request message for MetadataService.GetContext.

GetCustomJobRequest

Request message for JobService.GetCustomJob.

GetDataLabelingJobRequest

Request message for JobService.GetDataLabelingJob.

GetDatasetRequest

Request message for DatasetService.GetDataset.

GetEndpointRequest

Request message for EndpointService.GetEndpoint

GetEntityTypeRequest

Request message for FeaturestoreService.GetEntityType.

GetExecutionRequest

Request message for MetadataService.GetExecution.

GetFeatureRequest

Request message for FeaturestoreService.GetFeature.

GetFeaturestoreRequest

Request message for FeaturestoreService.GetFeaturestore.

GetHyperparameterTuningJobRequest

Request message for JobService.GetHyperparameterTuningJob.

GetIndexEndpointRequest

Request message for IndexEndpointService.GetIndexEndpoint

GetIndexRequest

Request message for IndexService.GetIndex

GetMetadataSchemaRequest

Request message for MetadataService.GetMetadataSchema.

GetMetadataStoreRequest

Request message for MetadataService.GetMetadataStore.

GetModelDeploymentMonitoringJobRequest

Request message for JobService.GetModelDeploymentMonitoringJob.

GetModelEvaluationRequest

Request message for ModelService.GetModelEvaluation.

GetModelEvaluationSliceRequest

Request message for ModelService.GetModelEvaluationSlice.

GetModelRequest

Request message for ModelService.GetModel.

GetPipelineJobRequest

Request message for PipelineService.GetPipelineJob.

GetSpecialistPoolRequest

Request message for SpecialistPoolService.GetSpecialistPool.

GetStudyRequest

Request message for VizierService.GetStudy.

GetTensorboardExperimentRequest

Request message for TensorboardService.GetTensorboardExperiment.

GetTensorboardRequest

Request message for TensorboardService.GetTensorboard.

GetTensorboardRunRequest

Request message for TensorboardService.GetTensorboardRun.

GetTensorboardTimeSeriesRequest

Request message for TensorboardService.GetTensorboardTimeSeries.

GetTrainingPipelineRequest

Request message for PipelineService.GetTrainingPipeline.

GetTrialRequest

Request message for 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.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

ImportDataOperationMetadata

Runtime operation information for DatasetService.ImportData.

ImportDataRequest

Request message for DatasetService.ImportData.

ImportDataResponse

Response message for DatasetService.ImportData.

ImportFeatureValuesOperationMetadata

Details of operations that perform import Feature values.

ImportFeatureValuesRequest

Request message for FeaturestoreService.ImportFeatureValues.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

ImportFeatureValuesResponse

Response message for FeaturestoreService.ImportFeatureValues.

ImportModelEvaluationRequest

Request message for ModelService.ImportModelEvaluation

Index

A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search.

IndexEndpoint

Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes.

IndexPrivateEndpoints

IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment.

InputDataConfig

Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

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.

ListAnnotationsResponse

Response message for DatasetService.ListAnnotations.

ListArtifactsRequest

Request message for MetadataService.ListArtifacts.

ListArtifactsResponse

Response message for MetadataService.ListArtifacts.

ListBatchPredictionJobsRequest

Request message for JobService.ListBatchPredictionJobs.

ListBatchPredictionJobsResponse

Response message for JobService.ListBatchPredictionJobs

ListContextsRequest

Request message for MetadataService.ListContexts

ListContextsResponse

Response message for MetadataService.ListContexts.

ListCustomJobsRequest

Request message for JobService.ListCustomJobs.

ListCustomJobsResponse

Response message for JobService.ListCustomJobs

ListDataItemsRequest

Request message for DatasetService.ListDataItems.

ListDataItemsResponse

Response message for DatasetService.ListDataItems.

ListDataLabelingJobsRequest

Request message for JobService.ListDataLabelingJobs.

ListDataLabelingJobsResponse

Response message for JobService.ListDataLabelingJobs.

ListDatasetsRequest

Request message for DatasetService.ListDatasets.

ListDatasetsResponse

Response message for DatasetService.ListDatasets.

ListEndpointsRequest

Request message for EndpointService.ListEndpoints.

ListEndpointsResponse

Response message for EndpointService.ListEndpoints.

ListEntityTypesRequest

Request message for FeaturestoreService.ListEntityTypes.

ListEntityTypesResponse

Response message for FeaturestoreService.ListEntityTypes.

ListExecutionsRequest

Request message for MetadataService.ListExecutions.

ListExecutionsResponse

Response message for MetadataService.ListExecutions.

ListFeaturesRequest

Request message for FeaturestoreService.ListFeatures.

ListFeaturesResponse

Response message for FeaturestoreService.ListFeatures.

ListFeaturestoresRequest

Request message for FeaturestoreService.ListFeaturestores.

ListFeaturestoresResponse

Response message for FeaturestoreService.ListFeaturestores.

ListHyperparameterTuningJobsRequest

Request message for JobService.ListHyperparameterTuningJobs.

ListHyperparameterTuningJobsResponse

Response message for JobService.ListHyperparameterTuningJobs

ListIndexEndpointsRequest

Request message for IndexEndpointService.ListIndexEndpoints.

ListIndexEndpointsResponse

Response message for IndexEndpointService.ListIndexEndpoints.

ListIndexesRequest

Request message for IndexService.ListIndexes.

ListIndexesResponse

Response message for IndexService.ListIndexes.

ListMetadataSchemasRequest

Request message for MetadataService.ListMetadataSchemas.

ListMetadataSchemasResponse

Response message for MetadataService.ListMetadataSchemas.

ListMetadataStoresRequest

Request message for MetadataService.ListMetadataStores.

ListMetadataStoresResponse

Response message for MetadataService.ListMetadataStores.

ListModelDeploymentMonitoringJobsRequest

Request message for JobService.ListModelDeploymentMonitoringJobs.

ListModelDeploymentMonitoringJobsResponse

Response message for JobService.ListModelDeploymentMonitoringJobs.

ListModelEvaluationSlicesRequest

Request message for ModelService.ListModelEvaluationSlices.

ListModelEvaluationSlicesResponse

Response message for ModelService.ListModelEvaluationSlices.

ListModelEvaluationsRequest

Request message for ModelService.ListModelEvaluations.

ListModelEvaluationsResponse

Response message for ModelService.ListModelEvaluations.

ListModelVersionsRequest

Request message for ModelService.ListModelVersions.

ListModelVersionsResponse

Response message for ModelService.ListModelVersions

ListModelsRequest

Request message for ModelService.ListModels.

ListModelsResponse

Response message for ModelService.ListModels

ListOptimalTrialsRequest

Request message for VizierService.ListOptimalTrials.

ListOptimalTrialsResponse

Response message for VizierService.ListOptimalTrials.

ListPipelineJobsRequest

Request message for PipelineService.ListPipelineJobs.

ListPipelineJobsResponse

Response message for PipelineService.ListPipelineJobs

ListSavedQueriesRequest

Request message for DatasetService.ListSavedQueries.

ListSavedQueriesResponse

Response message for DatasetService.ListSavedQueries.

ListSpecialistPoolsRequest

Request message for SpecialistPoolService.ListSpecialistPools.

ListSpecialistPoolsResponse

Response message for SpecialistPoolService.ListSpecialistPools.

ListStudiesRequest

Request message for VizierService.ListStudies.

ListStudiesResponse

Response message for VizierService.ListStudies.

ListTensorboardExperimentsRequest

Request message for TensorboardService.ListTensorboardExperiments.

ListTensorboardExperimentsResponse

Response message for TensorboardService.ListTensorboardExperiments.

ListTensorboardRunsRequest

Request message for TensorboardService.ListTensorboardRuns.

ListTensorboardRunsResponse

Response message for TensorboardService.ListTensorboardRuns.

ListTensorboardTimeSeriesRequest

Request message for TensorboardService.ListTensorboardTimeSeries.

ListTensorboardTimeSeriesResponse

Response message for TensorboardService.ListTensorboardTimeSeries.

ListTensorboardsRequest

Request message for TensorboardService.ListTensorboards.

ListTensorboardsResponse

Response message for TensorboardService.ListTensorboards.

ListTrainingPipelinesRequest

Request message for PipelineService.ListTrainingPipelines.

ListTrainingPipelinesResponse

Response message for PipelineService.ListTrainingPipelines

ListTrialsRequest

Request message for VizierService.ListTrials.

ListTrialsResponse

Response message for VizierService.ListTrials.

LookupStudyRequest

Request message for VizierService.LookupStudy.

MachineSpec

Specification of a single machine.

ManualBatchTuningParameters

Manual batch tuning parameters.

Measurement

A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values.

MergeVersionAliasesRequest

Request message for ModelService.MergeVersionAliases.

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.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

MigrateResourceRequest

Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

MigrateResourceResponse

Describes a successfully migrated resource.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

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 <https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core>__.

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.

ModelDeploymentMonitoringObjectiveType

The Model Monitoring Objective types.

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: 3

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

ModelMonitoringObjectiveConfig

Next ID: 8

ModelMonitoringStatsAnomalies

Statistics and anomalies generated by Model Monitoring.

MutateDeployedIndexOperationMetadata

Runtime operation information for IndexEndpointService.MutateDeployedIndex.

MutateDeployedIndexRequest

Request message for IndexEndpointService.MutateDeployedIndex.

MutateDeployedIndexResponse

Response message for IndexEndpointService.MutateDeployedIndex.

NearestNeighborSearchOperationMetadata

Runtime operation metadata with regard to Matching Engine Index.

Neighbor

Neighbors for example-based explanations.

NfsMount

Represents a mount configuration for Network File System (NFS) to mount.

PauseModelDeploymentMonitoringJobRequest

Request message for 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.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

PipelineTemplateMetadata

Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry.

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.

Supported only for tabular Datasets.

PredictRequest

Request message for PredictionService.Predict.

PredictRequestResponseLoggingConfig

Configuration for logging request-response to a BigQuery table.

PredictResponse

Response message for PredictionService.Predict.

PredictSchemata

Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob.

PrivateEndpoints

PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment.

PurgeArtifactsMetadata

Details of operations that perform MetadataService.PurgeArtifacts.

PurgeArtifactsRequest

Request message for MetadataService.PurgeArtifacts.

PurgeArtifactsResponse

Response message for MetadataService.PurgeArtifacts.

PurgeContextsMetadata

Details of operations that perform MetadataService.PurgeContexts.

PurgeContextsRequest

Request message for MetadataService.PurgeContexts.

PurgeContextsResponse

Response message for MetadataService.PurgeContexts.

PurgeExecutionsMetadata

Details of operations that perform MetadataService.PurgeExecutions.

PurgeExecutionsRequest

Request message for MetadataService.PurgeExecutions.

PurgeExecutionsResponse

Response message for MetadataService.PurgeExecutions.

PythonPackageSpec

The spec of a Python packaged code.

QueryArtifactLineageSubgraphRequest

Request message for MetadataService.QueryArtifactLineageSubgraph.

QueryContextLineageSubgraphRequest

Request message for MetadataService.QueryContextLineageSubgraph.

QueryExecutionInputsAndOutputsRequest

Request message for MetadataService.QueryExecutionInputsAndOutputs.

RawPredictRequest

Request message for PredictionService.RawPredict.

ReadFeatureValuesRequest

Request message for FeaturestoreOnlineServingService.ReadFeatureValues.

ReadFeatureValuesResponse

Response message for FeaturestoreOnlineServingService.ReadFeatureValues.

ReadTensorboardBlobDataRequest

Request message for TensorboardService.ReadTensorboardBlobData.

ReadTensorboardBlobDataResponse

Response message for TensorboardService.ReadTensorboardBlobData.

ReadTensorboardTimeSeriesDataRequest

Request message for TensorboardService.ReadTensorboardTimeSeriesData.

ReadTensorboardTimeSeriesDataResponse

Response message for TensorboardService.ReadTensorboardTimeSeriesData.

ResourcesConsumed

Statistics information about resource consumption.

ResumeModelDeploymentMonitoringJobRequest

Request message for 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.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

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

SavedQuery

A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters.

Scalar

One point viewable on a scalar metric plot.

Scheduling

All parameters related to queuing and scheduling of custom jobs.

SearchFeaturesRequest

Request message for FeaturestoreService.SearchFeatures.

SearchFeaturesResponse

Response message for FeaturestoreService.SearchFeatures.

SearchMigratableResourcesRequest

Request message for MigrationService.SearchMigratableResources.

SearchMigratableResourcesResponse

Response message for MigrationService.SearchMigratableResources.

SearchModelDeploymentMonitoringStatsAnomaliesRequest

Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.

SearchModelDeploymentMonitoringStatsAnomaliesResponse

Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.

SmoothGradConfig

Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

SpecialistPool

SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console.

StopTrialRequest

Request message for VizierService.StopTrial.

StratifiedSplit

Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the key field) is mirrored within each split. The fraction values determine the relative sizes of the splits.

For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C".

Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned.

Supported only for tabular Datasets.

StreamingReadFeatureValuesRequest

Request message for [FeaturestoreOnlineServingService.StreamingFeatureValuesRead][].

StringArray

A list of string values.

Study

A message representing a Study.

StudySpec

Represents specification of a Study.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

SuggestTrialsMetadata

Details of operations that perform Trials suggestion.

SuggestTrialsRequest

Request message for VizierService.SuggestTrials.

SuggestTrialsResponse

Response message for VizierService.SuggestTrials.

TFRecordDestination

The storage details for TFRecord output content.

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

ThresholdConfig

The config for feature monitoring threshold. Next ID: 3

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

TimeSeriesData

All the data stored in a TensorboardTimeSeries.

TimeSeriesDataPoint

A TensorboardTimeSeries data point.

.. _oneof: https://proto-plus-python.readthedocs.io/en/stable/fields.html#oneofs-mutually-exclusive-fields

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. Supported only for tabular Datasets.

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 the Model to Vertex AI, and evaluate the Model.