Package types (1.59.0)

Represents a hardware accelerator type.

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

Request message for MetadataService.AddContextArtifactsAndExecutions.

Response message for MetadataService.AddContextArtifactsAndExecutions.

Request message for MetadataService.AddContextChildren.

Response message for MetadataService.AddContextChildren.

Request message for MetadataService.AddExecutionEvents.

Response message for MetadataService.AddExecutionEvents.

Request message for VizierService.AddTrialMeasurement.

Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem.

Identifies a concept with which DataItems may be annotated with.

Instance of a general artifact.

Metadata information for NotebookService.AssignNotebookRuntime.

Request message for NotebookService.AssignNotebookRuntime.

Attribution that explains a particular prediction output.

A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines.

The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count.

The storage details for Avro input content.

Runtime operation information for PipelineService.BatchCancelPipelineJobs.

Request message for PipelineService.BatchCancelPipelineJobs.

Response message for PipelineService.BatchCancelPipelineJobs.

Details of operations that perform batch create Features.

Request message for FeaturestoreService.BatchCreateFeatures.

Response message for FeaturestoreService.BatchCreateFeatures.

Request message for TensorboardService.BatchCreateTensorboardRuns.

Response message for TensorboardService.BatchCreateTensorboardRuns.

Request message for TensorboardService.BatchCreateTensorboardTimeSeries.

Response message for TensorboardService.BatchCreateTensorboardTimeSeries.

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

Request message for PipelineService.BatchDeletePipelineJobs.

Response message for PipelineService.BatchDeletePipelineJobs.

Request message for ModelService.BatchImportEvaluatedAnnotations

Response message for ModelService.BatchImportEvaluatedAnnotations

Request message for ModelService.BatchImportModelEvaluationSlices

Response message for ModelService.BatchImportModelEvaluationSlices

Runtime operation information for MigrationService.BatchMigrateResources.

Request message for MigrationService.BatchMigrateResources.

Response message for MigrationService.BatchMigrateResources.

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.

Details of operations that batch reads Feature values.

Request message for FeaturestoreService.BatchReadFeatureValues.

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

Response message for FeaturestoreService.BatchReadFeatureValues.

Request message for TensorboardService.BatchReadTensorboardTimeSeriesData.

Response message for TensorboardService.BatchReadTensorboardTimeSeriesData.

The BigQuery location for the output content.

The BigQuery location for the input content.

Content blob.

It's preferred to send as text directly rather than raw bytes.

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

A list of boolean values.

Request message for JobService.CancelBatchPredictionJob.

Request message for JobService.CancelCustomJob.

Request message for JobService.CancelDataLabelingJob.

Request message for JobService.CancelHyperparameterTuningJob.

Request message for JobService.CancelNasJob.

Request message for PipelineService.CancelPipelineJob.

Request message for PipelineService.CancelTrainingPipeline.

Request message for GenAiTuningService.CancelTuningJob.

A response candidate generated from the model.

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

This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request.

Request message for VizierService.CheckTrialEarlyStoppingState.

Response message for VizierService.CheckTrialEarlyStoppingState.

Source attributions for content.

A collection of source attributions for a piece of content.

Request message for VizierService.CompleteTrial.

Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.

Request message for ComputeTokens RPC call.

Response message for ComputeTokens RPC call.

The Container Registry location for the container image.

The spec of a Container.

The base structured datatype containing multi-part content of a message.

A Content includes a role field designating the producer of the Content and a parts field containing multi-part data that contains the content of the message turn.

Instance of a general context.

Details of ModelService.CopyModel operation.

Request message for ModelService.CopyModel.

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

Response message of ModelService.CopyModel operation.

Request message for [PredictionService.CountTokens][].

Response message for [PredictionService.CountTokens][].

Request message for MetadataService.CreateArtifact.

Request message for JobService.CreateBatchPredictionJob.

Request message for MetadataService.CreateContext.

Request message for JobService.CreateCustomJob.

Request message for JobService.CreateDataLabelingJob.

Runtime operation information for DatasetService.CreateDataset.

Request message for DatasetService.CreateDataset.

Runtime operation information for DatasetService.CreateDatasetVersion.

Request message for DatasetService.CreateDatasetVersion.

Runtime operation information for CreateDeploymentResourcePool method.

Request message for CreateDeploymentResourcePool method.

Runtime operation information for EndpointService.CreateEndpoint.

Request message for EndpointService.CreateEndpoint.

Details of operations that perform create EntityType.

Request message for FeaturestoreService.CreateEntityType.

Request message for MetadataService.CreateExecution.

Details of operations that perform create FeatureGroup.

Request message for FeatureRegistryService.CreateFeatureGroup.

Details of operations that perform create FeatureOnlineStore.

Request message for FeatureOnlineStoreAdminService.CreateFeatureOnlineStore.

Details of operations that perform create Feature.

Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature.

Details of operations that perform create FeatureView.

Request message for FeatureOnlineStoreAdminService.CreateFeatureView.

Details of operations that perform create Featurestore.

Request message for FeaturestoreService.CreateFeaturestore.

Request message for JobService.CreateHyperparameterTuningJob.

Runtime operation information for IndexEndpointService.CreateIndexEndpoint.

Request message for IndexEndpointService.CreateIndexEndpoint.

Runtime operation information for IndexService.CreateIndex.

Request message for IndexService.CreateIndex.

Request message for MetadataService.CreateMetadataSchema.

Details of operations that perform MetadataService.CreateMetadataStore.

Request message for MetadataService.CreateMetadataStore.

Request message for JobService.CreateModelDeploymentMonitoringJob.

Request message for JobService.CreateNasJob.

Metadata information for NotebookService.CreateNotebookRuntimeTemplate.

Request message for NotebookService.CreateNotebookRuntimeTemplate.

Details of operations that perform create PersistentResource.

Request message for PersistentResourceService.CreatePersistentResource.

Request message for PipelineService.CreatePipelineJob.

Details of operations that perform create FeatureGroup.

Request message for ScheduleService.CreateSchedule.

Runtime operation information for SpecialistPoolService.CreateSpecialistPool.

Request message for SpecialistPoolService.CreateSpecialistPool.

Request message for VizierService.CreateStudy.

Request message for TensorboardService.CreateTensorboardExperiment.

Details of operations that perform create Tensorboard.

Request message for TensorboardService.CreateTensorboard.

Request message for TensorboardService.CreateTensorboardRun.

Request message for TensorboardService.CreateTensorboardTimeSeries.

Request message for PipelineService.CreateTrainingPipeline.

Request message for VizierService.CreateTrial.

Request message for GenAiTuningService.CreateTuningJob.

The storage details for CSV output content.

The storage details for CSV input content.

Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded).

Represents the spec of a CustomJob.

A piece of data in a Dataset. Could be an image, a video, a document or plain text.

A container for a single DataItem and Annotations on it.

DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset:

A collection of DataItems and Annotations on them.

Describes the dataset version.

A description of resources that are dedicated to a DeployedModel, and that need a higher degree of manual configuration.

Request message for MetadataService.DeleteArtifact.

Request message for JobService.DeleteBatchPredictionJob.

Request message for MetadataService.DeleteContext.

Request message for JobService.DeleteCustomJob.

Request message for JobService.DeleteDataLabelingJob.

Request message for DatasetService.DeleteDataset.

Request message for DatasetService.DeleteDatasetVersion.

Request message for DeleteDeploymentResourcePool method.

Request message for EndpointService.DeleteEndpoint.

Request message for [FeaturestoreService.DeleteEntityTypes][].

Request message for MetadataService.DeleteExecution.

Request message for FeatureRegistryService.DeleteFeatureGroup.

Request message for FeatureOnlineStoreAdminService.DeleteFeatureOnlineStore.

Request message for FeaturestoreService.DeleteFeature. Request message for FeatureRegistryService.DeleteFeature.

Details of operations that delete Feature values.

Request message for FeaturestoreService.DeleteFeatureValues.

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

Response message for FeaturestoreService.DeleteFeatureValues.

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

Request message for [FeatureOnlineStoreAdminService.DeleteFeatureViews][].

Request message for FeaturestoreService.DeleteFeaturestore.

Request message for JobService.DeleteHyperparameterTuningJob.

Request message for IndexEndpointService.DeleteIndexEndpoint.

Request message for IndexService.DeleteIndex.

Details of operations that perform MetadataService.DeleteMetadataStore.

Request message for MetadataService.DeleteMetadataStore.

Request message for JobService.DeleteModelDeploymentMonitoringJob.

Request message for ModelService.DeleteModel.

Request message for ModelService.DeleteModelVersion.

Request message for JobService.DeleteNasJob.

Request message for NotebookService.DeleteNotebookRuntime.

Request message for NotebookService.DeleteNotebookRuntimeTemplate.

Details of operations that perform deletes of any entities.

Request message for PersistentResourceService.DeletePersistentResource.

Request message for PipelineService.DeletePipelineJob.

Request message for DatasetService.DeleteSavedQuery.

Request message for ScheduleService.DeleteSchedule.

Request message for SpecialistPoolService.DeleteSpecialistPool.

Request message for VizierService.DeleteStudy.

Request message for TensorboardService.DeleteTensorboardExperiment.

Request message for TensorboardService.DeleteTensorboard.

Request message for TensorboardService.DeleteTensorboardRun.

Request message for TensorboardService.DeleteTensorboardTimeSeries.

Request message for PipelineService.DeleteTrainingPipeline.

Request message for VizierService.DeleteTrial.

Runtime operation information for IndexEndpointService.DeployIndex.

Request message for IndexEndpointService.DeployIndex.

Response message for IndexEndpointService.DeployIndex.

Runtime operation information for EndpointService.DeployModel.

Request message for EndpointService.DeployModel.

Response message for EndpointService.DeployModel.

A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes.

Used to set up the auth on the DeployedIndex's private endpoint.

Points to a DeployedIndex.

A deployment of a Model. Endpoints contain one or more DeployedModels.

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

Points to a DeployedModel.

A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources.

Request message for PredictionService.DirectPredict.

Response message for PredictionService.DirectPredict.

Request message for PredictionService.DirectRawPredict.

Response message for PredictionService.DirectRawPredict.

Represents the spec of disk options.

A list of double values.

Represents a customer-managed encryption key spec that can be applied to a top-level resource.

Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.

Selector for entityId. Getting ids from the given source.

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

An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver.

Represents an environment variable present in a Container or Python Module.

Model error analysis for each annotation.

True positive, false positive, or false negative.

EvaluatedAnnotation is only available under ModelEvaluationSlice with slice of annotationSpec dimension.

Explanation result of the prediction produced by the Model.

An edge describing the relationship between an Artifact and an Execution in a lineage graph.

Example-based explainability that returns the nearest neighbors from the provided dataset.

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

Overrides for example-based explanations.

Restrictions namespace for example-based explanations overrides.

Instance of a general execution.

Request message for PredictionService.Explain.

Response message for PredictionService.Explain.

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

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

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

Parameters to configure explaining for Model's predictions.

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

Specification of Model explanation.

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

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

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

Runtime operation information for DatasetService.ExportData.

Request message for DatasetService.ExportData.

Response message for DatasetService.ExportData.

Details of operations that exports Features values.

Request message for FeaturestoreService.ExportFeatureValues.

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

Response message for FeaturestoreService.ExportFeatureValues.

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

Supported only for unstructured Datasets.

Assigns the input data to training, validation, and test sets as per the given fractions. Any of training_fraction, validation_fraction and test_fraction may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.

Details of ModelService.ExportModel operation.

Request message for ModelService.ExportModel.

Response message of ModelService.ExportModel operation.

Request message for TensorboardService.ExportTensorboardTimeSeriesData.

Response message for TensorboardService.ExportTensorboardTimeSeriesData.

Feature Metadata information. For example, color is a feature that describes an apple.

Vertex AI Feature Group.

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

Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.

Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container.

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

Selector for Features of an EntityType.

Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display.

Value for a feature.

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

A destination location for Feature values and format.

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

Container for list of values.

FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig.

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

Format of the data in the Feature View.

Lookup key for a feature view.

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

FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store.

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

Configuration of how features in Featurestore are monitored.

Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned.

Response message for FeatureOnlineStoreService.FetchFeatureValues

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

URI based data.

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

Supported only for unstructured Datasets.

The request message for MatchService.FindNeighbors.

The response message for MatchService.FindNeighbors.

Assigns the input data to training, validation, and test sets as per the given fractions. Any of training_fraction, validation_fraction and test_fraction may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test.

A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values.

Function calling config.

Structured representation of a function declaration as defined by the OpenAPI 3.0 specification <https://spec.openapis.org/oas/v3.0.3>__. Included in this declaration are the function name and parameters. This FunctionDeclaration is a representation of a block of code that can be used as a Tool by the model and executed by the client.

The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction.

The Google Cloud Storage location where the output is to be written to.

The Google Cloud Storage location for the input content.

Request message for [PredictionService.GenerateContent].

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

Response message for [PredictionService.GenerateContent].

Generation config.

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

Generic Metadata shared by all operations.

Contains information about the source of the models generated from Generative AI Studio.

Request message for DatasetService.GetAnnotationSpec.

Request message for MetadataService.GetArtifact.

Request message for JobService.GetBatchPredictionJob.

Request message for MetadataService.GetContext.

Request message for JobService.GetCustomJob.

Request message for JobService.GetDataLabelingJob.

Request message for DatasetService.GetDataset.

Request message for DatasetService.GetDatasetVersion.

Request message for GetDeploymentResourcePool method.

Request message for EndpointService.GetEndpoint

Request message for FeaturestoreService.GetEntityType.

Request message for MetadataService.GetExecution.

Request message for FeatureRegistryService.GetFeatureGroup.

Request message for FeatureOnlineStoreAdminService.GetFeatureOnlineStore.

Request message for FeaturestoreService.GetFeature. Request message for FeatureRegistryService.GetFeature.

Request message for FeatureOnlineStoreAdminService.GetFeatureView.

Request message for FeatureOnlineStoreAdminService.GetFeatureViewSync.

Request message for FeaturestoreService.GetFeaturestore.

Request message for JobService.GetHyperparameterTuningJob.

Request message for IndexEndpointService.GetIndexEndpoint

Request message for IndexService.GetIndex

Request message for MetadataService.GetMetadataSchema.

Request message for MetadataService.GetMetadataStore.

Request message for JobService.GetModelDeploymentMonitoringJob.

Request message for ModelService.GetModelEvaluation.

Request message for ModelService.GetModelEvaluationSlice.

Request message for ModelService.GetModel.

Request message for JobService.GetNasJob.

Request message for JobService.GetNasTrialDetail.

Request message for NotebookService.GetNotebookRuntime

Request message for NotebookService.GetNotebookRuntimeTemplate

Request message for PersistentResourceService.GetPersistentResource.

Request message for PipelineService.GetPipelineJob.

Request message for ModelGardenService.GetPublisherModel

Request message for ScheduleService.GetSchedule.

Request message for SpecialistPoolService.GetSpecialistPool.

Request message for VizierService.GetStudy.

Request message for TensorboardService.GetTensorboardExperiment.

Request message for TensorboardService.GetTensorboard.

Request message for TensorboardService.GetTensorboardRun.

Request message for TensorboardService.GetTensorboardTimeSeries.

Request message for PipelineService.GetTrainingPipeline.

Request message for VizierService.GetTrial.

Request message for GenAiTuningService.GetTuningJob.

Tool to retrieve public web data for grounding, powered by Google.

Metadata returned to client when grounding is enabled.

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

Harm categories that will block the content.

Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification.

Matcher for Features of an EntityType by Feature ID.

Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations.

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

Runtime operation information for DatasetService.ImportData.

Request message for DatasetService.ImportData.

Response message for DatasetService.ImportData.

Details of operations that perform import Feature values.

Request message for FeaturestoreService.ImportFeatureValues.

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

Response message for FeaturestoreService.ImportFeatureValues.

Request message for ModelService.ImportModelEvaluation

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

A datapoint of Index.

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

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

Stats of the Index.

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

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

A list of int64 values.

An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365

Describes the state of a job.

Contains information about the Large Model.

A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes.

Request message for DatasetService.ListAnnotations.

Response message for DatasetService.ListAnnotations.

Request message for MetadataService.ListArtifacts.

Response message for MetadataService.ListArtifacts.

Request message for JobService.ListBatchPredictionJobs.

Response message for JobService.ListBatchPredictionJobs

Request message for MetadataService.ListContexts

Response message for MetadataService.ListContexts.

Request message for JobService.ListCustomJobs.

Response message for JobService.ListCustomJobs

Request message for DatasetService.ListDataItems.

Response message for DatasetService.ListDataItems.

Request message for JobService.ListDataLabelingJobs.

Response message for JobService.ListDataLabelingJobs.

Request message for DatasetService.ListDatasetVersions.

Response message for DatasetService.ListDatasetVersions.

Request message for DatasetService.ListDatasets.

Response message for DatasetService.ListDatasets.

Request message for ListDeploymentResourcePools method.

Response message for ListDeploymentResourcePools method.

Request message for EndpointService.ListEndpoints.

Response message for EndpointService.ListEndpoints.

Request message for FeaturestoreService.ListEntityTypes.

Response message for FeaturestoreService.ListEntityTypes.

Request message for MetadataService.ListExecutions.

Response message for MetadataService.ListExecutions.

Request message for FeatureRegistryService.ListFeatureGroups.

Response message for FeatureRegistryService.ListFeatureGroups.

Request message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.

Response message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores.

Request message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs.

Response message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs.

Request message for FeatureOnlineStoreAdminService.ListFeatureViews.

Response message for FeatureOnlineStoreAdminService.ListFeatureViews.

Request message for FeaturestoreService.ListFeatures. Request message for FeatureRegistryService.ListFeatures.

Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures.

Request message for FeaturestoreService.ListFeaturestores.

Response message for FeaturestoreService.ListFeaturestores.

Request message for JobService.ListHyperparameterTuningJobs.

Response message for JobService.ListHyperparameterTuningJobs

Request message for IndexEndpointService.ListIndexEndpoints.

Response message for IndexEndpointService.ListIndexEndpoints.

Request message for IndexService.ListIndexes.

Response message for IndexService.ListIndexes.

Request message for MetadataService.ListMetadataSchemas.

Response message for MetadataService.ListMetadataSchemas.

Request message for MetadataService.ListMetadataStores.

Response message for MetadataService.ListMetadataStores.

Request message for JobService.ListModelDeploymentMonitoringJobs.

Response message for JobService.ListModelDeploymentMonitoringJobs.

Request message for ModelService.ListModelEvaluationSlices.

Response message for ModelService.ListModelEvaluationSlices.

Request message for ModelService.ListModelEvaluations.

Response message for ModelService.ListModelEvaluations.

Request message for ModelService.ListModelVersions.

Response message for ModelService.ListModelVersions

Request message for ModelService.ListModels.

Response message for ModelService.ListModels

Request message for JobService.ListNasJobs.

Response message for JobService.ListNasJobs

Request message for JobService.ListNasTrialDetails.

Response message for JobService.ListNasTrialDetails

Request message for NotebookService.ListNotebookRuntimeTemplates.

Response message for NotebookService.ListNotebookRuntimeTemplates.

Request message for NotebookService.ListNotebookRuntimes.

Response message for NotebookService.ListNotebookRuntimes.

Request message for VizierService.ListOptimalTrials.

Response message for VizierService.ListOptimalTrials.

Request message for [PersistentResourceService.ListPersistentResource][].

Response message for PersistentResourceService.ListPersistentResources

Request message for PipelineService.ListPipelineJobs.

Response message for PipelineService.ListPipelineJobs

Request message for DatasetService.ListSavedQueries.

Response message for DatasetService.ListSavedQueries.

Request message for ScheduleService.ListSchedules.

Response message for ScheduleService.ListSchedules

Request message for SpecialistPoolService.ListSpecialistPools.

Response message for SpecialistPoolService.ListSpecialistPools.

Request message for VizierService.ListStudies.

Response message for VizierService.ListStudies.

Request message for TensorboardService.ListTensorboardExperiments.

Response message for TensorboardService.ListTensorboardExperiments.

Request message for TensorboardService.ListTensorboardRuns.

Response message for TensorboardService.ListTensorboardRuns.

Request message for TensorboardService.ListTensorboardTimeSeries.

Response message for TensorboardService.ListTensorboardTimeSeries.

Request message for TensorboardService.ListTensorboards.

Response message for TensorboardService.ListTensorboards.

Request message for PipelineService.ListTrainingPipelines.

Response message for PipelineService.ListTrainingPipelines

Request message for VizierService.ListTrials.

Response message for VizierService.ListTrials.

Request message for GenAiTuningService.ListTuningJobs.

Response message for GenAiTuningService.ListTuningJobs

Request message for VizierService.LookupStudy.

Specification of a single machine.

Manual batch tuning parameters.

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

Request message for ModelService.MergeVersionAliases.

Instance of a general MetadataSchema.

Instance of a metadata store. Contains a set of metadata that can be queried.

Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com.

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

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

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

Describes a successfully migrated resource.

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

A trained machine learning Model.

Specification of a container for serving predictions. Some fields in this message correspond to fields in the Kubernetes Container v1 core specification <https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.23/#container-v1-core>__.

ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table.

Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors.

ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig.

The Model Monitoring Objective types.

The config for scheduling monitoring job.

A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.

A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.

Aggregated explanation metrics for a Model over a set of instances.

Contains information about the source of the models generated from Model Garden.

The alert config for model monitoring.

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

The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model.

Statistics and anomalies generated by Model Monitoring.

Detail description of the source information of the model.

Runtime operation information for IndexEndpointService.MutateDeployedIndex.

Request message for IndexEndpointService.MutateDeployedIndex.

Response message for IndexEndpointService.MutateDeployedIndex.

Runtime operation information for EndpointService.MutateDeployedModel.

Request message for EndpointService.MutateDeployedModel.

Response message for EndpointService.MutateDeployedModel.

Represents a Neural Architecture Search (NAS) job.

Represents a uCAIP NasJob output.

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

Represents the spec of a NasJob.

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

Represents a uCAIP NasJob trial.

Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned.

A query to find a number of similar entities.

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

Runtime operation metadata with regard to Matching Engine Index.

Nearest neighbors for one query.

Neighbors for example-based explanations.

Network spec.

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

The euc configuration of NotebookRuntimeTemplate.

The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field.

A runtime is a virtual machine allocated to a particular user for a particular Notebook file on temporary basis with lifetime limited to 24 hours.

A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template.

Points to a NotebookRuntimeTemplateRef.

Represents a notebook runtime type.

A datatype containing media that is part of a multi-part Content message.

A Part consists of data which has an associated datatype. A Part can only contain one of the accepted types in Part.data.

A Part must have a fixed IANA MIME type identifying the type and subtype of the media if inline_data or file_data field is filled with raw bytes.

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

Request message for JobService.PauseModelDeploymentMonitoringJob.

Request message for ScheduleService.PauseSchedule.

Represents the spec of [persistent disk][https://cloud.google.com/compute/docs/disks/persistent-disks] options.

Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec.

Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion.

An instance of a machine learning PipelineJob.

The runtime detail of PipelineJob.

Describes the state of a pipeline.

The runtime detail of a task execution.

The runtime detail of a pipeline executor.

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

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

Represents a network port in a container.

Assigns input data to training, validation, and test sets based on the value of a provided key.

Supported only for tabular Datasets.

Request message for PredictionService.Predict.

Configuration for logging request-response to a BigQuery table.

Response message for PredictionService.Predict.

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

Preset configuration for example-based explanations

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

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

Represents configuration for private service connect.

Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic.

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

PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig.

A Model Garden Publisher Model.

View enumeration of PublisherModel.

Details of operations that perform MetadataService.PurgeArtifacts.

Request message for MetadataService.PurgeArtifacts.

Response message for MetadataService.PurgeArtifacts.

Details of operations that perform MetadataService.PurgeContexts.

Request message for MetadataService.PurgeContexts.

Response message for MetadataService.PurgeContexts.

Details of operations that perform MetadataService.PurgeExecutions.

Request message for MetadataService.PurgeExecutions.

Response message for MetadataService.PurgeExecutions.

The spec of a Python packaged code.

Request message for MetadataService.QueryArtifactLineageSubgraph.

Request message for MetadataService.QueryContextLineageSubgraph.

Request message for QueryDeployedModels method.

Response message for QueryDeployedModels method.

Request message for MetadataService.QueryExecutionInputsAndOutputs.

Request message for PredictionService.RawPredict.

Configuration for the Ray metrics.

Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes.

Request message for FeaturestoreOnlineServingService.ReadFeatureValues.

Response message for FeaturestoreOnlineServingService.ReadFeatureValues.

The request message for MatchService.ReadIndexDatapoints.

The response message for MatchService.ReadIndexDatapoints.

Request message for TensorboardService.ReadTensorboardBlobData.

Response message for TensorboardService.ReadTensorboardBlobData.

Request message for TensorboardService.ReadTensorboardSize.

Response message for TensorboardService.ReadTensorboardSize.

Request message for TensorboardService.ReadTensorboardTimeSeriesData.

Response message for TensorboardService.ReadTensorboardTimeSeriesData.

Request message for TensorboardService.ReadTensorboardUsage.

Response message for TensorboardService.ReadTensorboardUsage.

Details of operations that perform reboot PersistentResource.

Request message for PersistentResourceService.RebootPersistentResource.

Request message for [MetadataService.DeleteContextChildrenRequest][].

Response message for MetadataService.RemoveContextChildren.

Request message for IndexService.RemoveDatapoints

Response message for IndexService.RemoveDatapoints

Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource.

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

Persistent Cluster runtime information as output

Configuration for the runtime on a PersistentResource instance, including but not limited to:

• Service accounts used to run the workloads.
• Whether to make it a dedicated Ray Cluster.

Statistics information about resource consumption.

Runtime operation information for DatasetService.RestoreDatasetVersion.

Request message for DatasetService.RestoreDatasetVersion.

Request message for JobService.ResumeModelDeploymentMonitoringJob.

Request message for ScheduleService.ResumeSchedule.

Defines a retrieval tool that model can call to access external knowledge.

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

Safety rating corresponding to the generated content.

Safety settings.

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

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

An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.

Sampling Strategy for logging, can be for both training and prediction dataset.

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

One point viewable on a scalar metric plot.

An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type.

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

All parameters related to queuing and scheduling of custom jobs.

Schema is used to define the format of input/output data. Represents a select subset of an OpenAPI 3.0 schema object <https://spec.openapis.org/oas/v3.0.3#schema>__. More fields may be added in the future as needed.

Request message for DatasetService.SearchDataItems.

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

Response message for DatasetService.SearchDataItems.

Google search entry point.

Request message for FeaturestoreService.SearchFeatures.

Response message for FeaturestoreService.SearchFeatures.

Request message for MigrationService.SearchMigratableResources.

Response message for MigrationService.SearchMigratableResources.

Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.

Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies.

The request message for FeatureOnlineStoreService.SearchNearestEntities.

Response message for FeatureOnlineStoreService.SearchNearestEntities

Configuration for the use of custom service account to run the workloads.

A set of Shielded Instance options. See Images using supported Shielded VM features <https://cloud.google.com/compute/docs/instances/modifying-shielded-vm>__.

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

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

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

Metadata information for NotebookService.StartNotebookRuntime.

Request message for NotebookService.StartNotebookRuntime.

Response message for NotebookService.StartNotebookRuntime.

Request message for VizierService.StopTrial.

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

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.

Request message for PredictionService.StreamDirectPredict.

The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].

Response message for PredictionService.StreamDirectPredict.

Request message for PredictionService.StreamDirectRawPredict.

The first message must contain endpoint and method_name fields and optionally input. The subsequent messages must contain input. method_name in the subsequent messages have no effect.

Response message for PredictionService.StreamDirectRawPredict.

Request message for PredictionService.StreamRawPredict.

Request message for PredictionService.StreamingPredict.

The first message must contain endpoint field and optionally [input][]. The subsequent messages must contain [input][].

Response message for PredictionService.StreamingPredict.

Request message for PredictionService.StreamingRawPredict.

The first message must contain endpoint and method_name fields and optionally input. The subsequent messages must contain input. method_name in the subsequent messages have no effect.

Response message for PredictionService.StreamingRawPredict.

Request message for [FeaturestoreOnlineServingService.StreamingFeatureValuesRead][].

A list of string values.

One field of a Struct (or object) type feature value.

Struct (or object) type feature value.

A message representing a Study.

Represents specification of a Study.

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

Time-based Constraint for Study

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

Details of operations that perform Trials suggestion.

Request message for VizierService.SuggestTrials.

Response message for VizierService.SuggestTrials.

Hyperparameters for SFT.

Tuning data statistics for Supervised Tuning.

Dataset distribution for Supervised Tuning.

Tuning Spec for Supervised Tuning.

Request message for FeatureOnlineStoreAdminService.SyncFeatureView.

Respose message for FeatureOnlineStoreAdminService.SyncFeatureView.

The storage details for TFRecord output content.

A tensor value type.

Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a Google Cloud project. If needed users can also create extra Tensorboards in their projects.

One blob (e.g, image, graph) viewable on a blob metric plot.

One point viewable on a blob metric plot, but mostly just a wrapper message to work around repeated fields can't be used directly within oneof fields.

A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard.

TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc

One point viewable on a tensor metric plot.

TensorboardTimeSeries maps to times series produced in training runs

The config for feature monitoring threshold.

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

All the data stored in a TensorboardTimeSeries.

A TensorboardTimeSeries data point.

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

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.

Tokens info with a list of tokens and the corresponding list of token ids.

Tool details that the model may use to generate response.

A Tool is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).

Tool config. This config is shared for all tools provided in the request.

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.

A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial.

Next ID: 3

The Model Registry Model and Online Prediction Endpoint assiociated with this TuningJob.

The tuning data statistic values for TuningJob.

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

Represents a TuningJob that runs with Google owned models.

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

Type contains the list of OpenAPI data types as defined by https://swagger.io/docs/specification/data-models/data-types/

Runtime operation information for IndexEndpointService.UndeployIndex.

Request message for IndexEndpointService.UndeployIndex.

Response message for IndexEndpointService.UndeployIndex.

Runtime operation information for EndpointService.UndeployModel.

Request message for EndpointService.UndeployModel.

Response message for EndpointService.UndeployModel.

Contains model information necessary to perform batch prediction without requiring a full model import.

Request message for MetadataService.UpdateArtifact.

Request message for MetadataService.UpdateContext.

Request message for DatasetService.UpdateDataset.

Request message for DatasetService.UpdateDatasetVersion.

Runtime operation information for UpdateDeploymentResourcePool method.

Request message for UpdateDeploymentResourcePool method.

Request message for EndpointService.UpdateEndpoint.

Request message for FeaturestoreService.UpdateEntityType.

Request message for MetadataService.UpdateExecution.

Runtime operation information for ModelService.UpdateExplanationDataset.

Request message for ModelService.UpdateExplanationDataset.

Response message of ModelService.UpdateExplanationDataset operation.

Details of operations that perform update FeatureGroup.

Request message for FeatureRegistryService.UpdateFeatureGroup.

Details of operations that perform update FeatureOnlineStore.

Request message for FeatureOnlineStoreAdminService.UpdateFeatureOnlineStore.

Details of operations that perform update Feature.

Request message for FeaturestoreService.UpdateFeature. Request message for FeatureRegistryService.UpdateFeature.

Details of operations that perform update FeatureView.

Request message for FeatureOnlineStoreAdminService.UpdateFeatureView.

Details of operations that perform update Featurestore.

Request message for FeaturestoreService.UpdateFeaturestore.

Request message for IndexEndpointService.UpdateIndexEndpoint.

Runtime operation information for IndexService.UpdateIndex.

Request message for IndexService.UpdateIndex.

Runtime operation information for JobService.UpdateModelDeploymentMonitoringJob.

Request message for JobService.UpdateModelDeploymentMonitoringJob.

Request message for ModelService.UpdateModel.

Request message for NotebookService.UpdateNotebookRuntimeTemplate.

Details of operations that perform update PersistentResource.

Request message for UpdatePersistentResource method.

Request message for ScheduleService.UpdateSchedule.

Runtime operation metadata for SpecialistPoolService.UpdateSpecialistPool.

Request message for SpecialistPoolService.UpdateSpecialistPool.

Request message for TensorboardService.UpdateTensorboardExperiment.

Details of operations that perform update Tensorboard.

Request message for TensorboardService.UpdateTensorboard.

Request message for TensorboardService.UpdateTensorboardRun.

Request message for TensorboardService.UpdateTensorboardTimeSeries.

Metadata information for NotebookService.UpgradeNotebookRuntime.

Request message for NotebookService.UpgradeNotebookRuntime.

Response message for NotebookService.UpgradeNotebookRuntime.

Details of ModelService.UploadModel operation.

Request message for ModelService.UploadModel.

Response message of ModelService.UploadModel operation.

Request message for IndexService.UpsertDatapoints

Response message for IndexService.UpsertDatapoints

References an API call. It contains more information about long running operation and Jobs that are triggered by the API call.

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

Value is the value of the field.

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

Retrieve from Vertex AI Search datastore for grounding. See https://cloud.google.com/vertex-ai-search-and-conversation

Metadata describes the input video content.

Represents the spec of a worker pool in a job.

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

Contains Feature values to be written for a specific entity.

Request message for FeaturestoreOnlineServingService.WriteFeatureValues.

Response message for FeaturestoreOnlineServingService.WriteFeatureValues.

Request message for TensorboardService.WriteTensorboardExperimentData.

Response message for TensorboardService.WriteTensorboardExperimentData.

Request message for TensorboardService.WriteTensorboardRunData.

Response message for TensorboardService.WriteTensorboardRunData.

An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details:

https://arxiv.org/abs/1906.02825

Supported only by image Models.