Package google.cloud.aiplatform.v1

Index

DatasetService

The service that handles the CRUD of Vertex AI Dataset and its child resources.

CreateDataset

rpc CreateDataset(CreateDatasetRequest) returns (Operation)

Creates a Dataset.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.datasets.create

For more information, see the IAM documentation.

DeleteDataset

rpc DeleteDataset(DeleteDatasetRequest) returns (Operation)

Deletes a Dataset.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.datasets.delete

For more information, see the IAM documentation.

ExportData

rpc ExportData(ExportDataRequest) returns (Operation)

Exports data from a Dataset.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.datasets.export

For more information, see the IAM documentation.

GetAnnotationSpec

rpc GetAnnotationSpec(GetAnnotationSpecRequest) returns (AnnotationSpec)

Gets an AnnotationSpec.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.annotationSpecs.get

For more information, see the IAM documentation.

GetDataset

rpc GetDataset(GetDatasetRequest) returns (Dataset)

Gets a Dataset.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.datasets.get

For more information, see the IAM documentation.

ImportData

rpc ImportData(ImportDataRequest) returns (Operation)

Imports data into a Dataset.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.datasets.import

For more information, see the IAM documentation.

ListAnnotations

rpc ListAnnotations(ListAnnotationsRequest) returns (ListAnnotationsResponse)

Lists Annotations belongs to a dataitem

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.annotations.list

For more information, see the IAM documentation.

ListDataItems

rpc ListDataItems(ListDataItemsRequest) returns (ListDataItemsResponse)

Lists DataItems in a Dataset.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.dataItems.list

For more information, see the IAM documentation.

ListDatasets

rpc ListDatasets(ListDatasetsRequest) returns (ListDatasetsResponse)

Lists Datasets in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.datasets.list

For more information, see the IAM documentation.

UpdateDataset

rpc UpdateDataset(UpdateDatasetRequest) returns (Dataset)

Updates a Dataset.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.datasets.update

For more information, see the IAM documentation.

EndpointService

A service for managing Vertex AI's Endpoints.

CreateEndpoint

rpc CreateEndpoint(CreateEndpointRequest) returns (Operation)

Creates an Endpoint.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.endpoints.create

For more information, see the IAM documentation.

DeleteEndpoint

rpc DeleteEndpoint(DeleteEndpointRequest) returns (Operation)

Deletes an Endpoint.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.endpoints.delete

For more information, see the IAM documentation.

DeployModel

rpc DeployModel(DeployModelRequest) returns (Operation)

Deploys a Model into this Endpoint, creating a DeployedModel within it.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the endpoint resource:

  • aiplatform.endpoints.deploy

For more information, see the IAM documentation.

GetEndpoint

rpc GetEndpoint(GetEndpointRequest) returns (Endpoint)

Gets an Endpoint.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.endpoints.get

For more information, see the IAM documentation.

ListEndpoints

rpc ListEndpoints(ListEndpointsRequest) returns (ListEndpointsResponse)

Lists Endpoints in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.endpoints.list

For more information, see the IAM documentation.

UndeployModel

rpc UndeployModel(UndeployModelRequest) returns (Operation)

Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all resources it's using.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the endpoint resource:

  • aiplatform.endpoints.undeploy

For more information, see the IAM documentation.

UpdateEndpoint

rpc UpdateEndpoint(UpdateEndpointRequest) returns (Endpoint)

Updates an Endpoint.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.endpoints.update

For more information, see the IAM documentation.

JobService

A service for creating and managing Vertex AI's jobs.

CancelBatchPredictionJob

rpc CancelBatchPredictionJob(CancelBatchPredictionJobRequest) returns (Empty)

Cancels a BatchPredictionJob.

Starts asynchronous cancellation on the BatchPredictionJob. The server makes the best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetBatchPredictionJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On a successful cancellation, the BatchPredictionJob is not deleted;instead its BatchPredictionJob.state is set to CANCELLED. Any files already outputted by the job are not deleted.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.batchPredictionJobs.cancel

For more information, see the IAM documentation.

CancelCustomJob

rpc CancelCustomJob(CancelCustomJobRequest) returns (Empty)

Cancels a CustomJob. Starts asynchronous cancellation on the CustomJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetCustomJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the CustomJob is not deleted; instead it becomes a job with a CustomJob.error value with a google.rpc.Status.code of 1, corresponding to Code.CANCELLED, and CustomJob.state is set to CANCELLED.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.customJobs.cancel

For more information, see the IAM documentation.

CancelDataLabelingJob

rpc CancelDataLabelingJob(CancelDataLabelingJobRequest) returns (Empty)

Cancels a DataLabelingJob. Success of cancellation is not guaranteed.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.dataLabelingJobs.cancel

For more information, see the IAM documentation.

CancelHyperparameterTuningJob

rpc CancelHyperparameterTuningJob(CancelHyperparameterTuningJobRequest) returns (Empty)

Cancels a HyperparameterTuningJob. Starts asynchronous cancellation on the HyperparameterTuningJob. The server makes a best effort to cancel the job, but success is not guaranteed. Clients can use JobService.GetHyperparameterTuningJob or other methods to check whether the cancellation succeeded or whether the job completed despite cancellation. On successful cancellation, the HyperparameterTuningJob is not deleted; instead it becomes a job with a HyperparameterTuningJob.error value with a google.rpc.Status.code of 1, corresponding to Code.CANCELLED, and HyperparameterTuningJob.state is set to CANCELLED.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.hyperparameterTuningJobs.cancel

For more information, see the IAM documentation.

CreateBatchPredictionJob

rpc CreateBatchPredictionJob(CreateBatchPredictionJobRequest) returns (BatchPredictionJob)

Creates a BatchPredictionJob. A BatchPredictionJob once created will right away be attempted to start.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.batchPredictionJobs.create

For more information, see the IAM documentation.

CreateCustomJob

rpc CreateCustomJob(CreateCustomJobRequest) returns (CustomJob)

Creates a CustomJob. A created CustomJob right away will be attempted to be run.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.customJobs.create

For more information, see the IAM documentation.

CreateDataLabelingJob

rpc CreateDataLabelingJob(CreateDataLabelingJobRequest) returns (DataLabelingJob)

Creates a DataLabelingJob.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.dataLabelingJobs.create

For more information, see the IAM documentation.

CreateHyperparameterTuningJob

rpc CreateHyperparameterTuningJob(CreateHyperparameterTuningJobRequest) returns (HyperparameterTuningJob)

Creates a HyperparameterTuningJob

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.hyperparameterTuningJobs.create

For more information, see the IAM documentation.

DeleteBatchPredictionJob

rpc DeleteBatchPredictionJob(DeleteBatchPredictionJobRequest) returns (Operation)

Deletes a BatchPredictionJob. Can only be called on jobs that already finished.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.batchPredictionJobs.delete

For more information, see the IAM documentation.

DeleteCustomJob

rpc DeleteCustomJob(DeleteCustomJobRequest) returns (Operation)

Deletes a CustomJob.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.customJobs.delete

For more information, see the IAM documentation.

DeleteDataLabelingJob

rpc DeleteDataLabelingJob(DeleteDataLabelingJobRequest) returns (Operation)

Deletes a DataLabelingJob.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.dataLabelingJobs.delete

For more information, see the IAM documentation.

DeleteHyperparameterTuningJob

rpc DeleteHyperparameterTuningJob(DeleteHyperparameterTuningJobRequest) returns (Operation)

Deletes a HyperparameterTuningJob.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.hyperparameterTuningJobs.delete

For more information, see the IAM documentation.

GetBatchPredictionJob

rpc GetBatchPredictionJob(GetBatchPredictionJobRequest) returns (BatchPredictionJob)

Gets a BatchPredictionJob

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.batchPredictionJobs.get

For more information, see the IAM documentation.

GetCustomJob

rpc GetCustomJob(GetCustomJobRequest) returns (CustomJob)

Gets a CustomJob.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.customJobs.get

For more information, see the IAM documentation.

GetDataLabelingJob

rpc GetDataLabelingJob(GetDataLabelingJobRequest) returns (DataLabelingJob)

Gets a DataLabelingJob.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.dataLabelingJobs.get

For more information, see the IAM documentation.

GetHyperparameterTuningJob

rpc GetHyperparameterTuningJob(GetHyperparameterTuningJobRequest) returns (HyperparameterTuningJob)

Gets a HyperparameterTuningJob

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.hyperparameterTuningJobs.get

For more information, see the IAM documentation.

ListBatchPredictionJobs

rpc ListBatchPredictionJobs(ListBatchPredictionJobsRequest) returns (ListBatchPredictionJobsResponse)

Lists BatchPredictionJobs in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.batchPredictionJobs.list

For more information, see the IAM documentation.

ListCustomJobs

rpc ListCustomJobs(ListCustomJobsRequest) returns (ListCustomJobsResponse)

Lists CustomJobs in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.customJobs.list

For more information, see the IAM documentation.

ListDataLabelingJobs

rpc ListDataLabelingJobs(ListDataLabelingJobsRequest) returns (ListDataLabelingJobsResponse)

Lists DataLabelingJobs in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.dataLabelingJobs.list

For more information, see the IAM documentation.

ListHyperparameterTuningJobs

rpc ListHyperparameterTuningJobs(ListHyperparameterTuningJobsRequest) returns (ListHyperparameterTuningJobsResponse)

Lists HyperparameterTuningJobs in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.hyperparameterTuningJobs.list

For more information, see the IAM documentation.

MigrationService

A service that migrates resources from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI.

BatchMigrateResources

rpc BatchMigrateResources(BatchMigrateResourcesRequest) returns (Operation)

Batch migrates resources from ml.googleapis.com, automl.googleapis.com, and datalabeling.googleapis.com to Vertex AI.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.migratableResources.migrate

For more information, see the IAM documentation.

SearchMigratableResources

rpc SearchMigratableResources(SearchMigratableResourcesRequest) returns (SearchMigratableResourcesResponse)

Searches all of the resources in automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com that can be migrated to Vertex AI's given location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.migratableResources.search

For more information, see the IAM documentation.

ModelService

A service for managing Vertex AI's machine learning Models.

DeleteModel

rpc DeleteModel(DeleteModelRequest) returns (Operation)

Deletes a Model. Note: Model can only be deleted if there are no DeployedModels created from it.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.models.delete

For more information, see the IAM documentation.

ExportModel

rpc ExportModel(ExportModelRequest) returns (Operation)

Exports a trained, exportable, Model to a location specified by the user. A Model is considered to be exportable if it has at least one supported export format.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.models.export

For more information, see the IAM documentation.

GetModel

rpc GetModel(GetModelRequest) returns (Model)

Gets a Model.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.models.get

For more information, see the IAM documentation.

GetModelEvaluation

rpc GetModelEvaluation(GetModelEvaluationRequest) returns (ModelEvaluation)

Gets a ModelEvaluation.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.modelEvaluations.get

For more information, see the IAM documentation.

GetModelEvaluationSlice

rpc GetModelEvaluationSlice(GetModelEvaluationSliceRequest) returns (ModelEvaluationSlice)

Gets a ModelEvaluationSlice.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.modelEvaluationSlices.get

For more information, see the IAM documentation.

ListModelEvaluationSlices

rpc ListModelEvaluationSlices(ListModelEvaluationSlicesRequest) returns (ListModelEvaluationSlicesResponse)

Lists ModelEvaluationSlices in a ModelEvaluation.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.modelEvaluationSlices.list

For more information, see the IAM documentation.

ListModelEvaluations

rpc ListModelEvaluations(ListModelEvaluationsRequest) returns (ListModelEvaluationsResponse)

Lists ModelEvaluations in a Model.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.modelEvaluations.list

For more information, see the IAM documentation.

ListModels

rpc ListModels(ListModelsRequest) returns (ListModelsResponse)

Lists Models in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.models.list

For more information, see the IAM documentation.

UpdateModel

rpc UpdateModel(UpdateModelRequest) returns (Model)

Updates a Model.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.models.update

For more information, see the IAM documentation.

UploadModel

rpc UploadModel(UploadModelRequest) returns (Operation)

Uploads a Model artifact into Vertex AI.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.models.upload

For more information, see the IAM documentation.

PipelineService

A service for creating and managing Vertex AI's pipelines. This includes both TrainingPipeline resources (used for AutoML and custom training) and PipelineJob resources (used for Vertex Pipelines).

CancelPipelineJob

rpc CancelPipelineJob(CancelPipelineJobRequest) returns (Empty)

Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetPipelineJob or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a PipelineJob.error value with a google.rpc.Status.code of 1, corresponding to Code.CANCELLED, and PipelineJob.state is set to CANCELLED.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.pipelineJobs.cancel

For more information, see the IAM documentation.

CancelTrainingPipeline

rpc CancelTrainingPipeline(CancelTrainingPipelineRequest) returns (Empty)

Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use PipelineService.GetTrainingPipeline or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a TrainingPipeline.error value with a google.rpc.Status.code of 1, corresponding to Code.CANCELLED, and TrainingPipeline.state is set to CANCELLED.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.trainingPipelines.cancel

For more information, see the IAM documentation.

CreatePipelineJob

rpc CreatePipelineJob(CreatePipelineJobRequest) returns (PipelineJob)

Creates a PipelineJob. A PipelineJob will run immediately when created.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.pipelineJobs.create

For more information, see the IAM documentation.

CreateTrainingPipeline

rpc CreateTrainingPipeline(CreateTrainingPipelineRequest) returns (TrainingPipeline)

Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.trainingPipelines.create

For more information, see the IAM documentation.

DeletePipelineJob

rpc DeletePipelineJob(DeletePipelineJobRequest) returns (Operation)

Deletes a PipelineJob.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.pipelineJobs.delete

For more information, see the IAM documentation.

DeleteTrainingPipeline

rpc DeleteTrainingPipeline(DeleteTrainingPipelineRequest) returns (Operation)

Deletes a TrainingPipeline.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.trainingPipelines.delete

For more information, see the IAM documentation.

GetPipelineJob

rpc GetPipelineJob(GetPipelineJobRequest) returns (PipelineJob)

Gets a PipelineJob.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.pipelineJobs.get

For more information, see the IAM documentation.

GetTrainingPipeline

rpc GetTrainingPipeline(GetTrainingPipelineRequest) returns (TrainingPipeline)

Gets a TrainingPipeline.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.trainingPipelines.get

For more information, see the IAM documentation.

ListPipelineJobs

rpc ListPipelineJobs(ListPipelineJobsRequest) returns (ListPipelineJobsResponse)

Lists PipelineJobs in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.pipelineJobs.list

For more information, see the IAM documentation.

ListTrainingPipelines

rpc ListTrainingPipelines(ListTrainingPipelinesRequest) returns (ListTrainingPipelinesResponse)

Lists TrainingPipelines in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.trainingPipelines.list

For more information, see the IAM documentation.

PredictionService

A service for online predictions and explanations.

Explain

rpc Explain(ExplainRequest) returns (ExplainResponse)

Perform an online explanation.

If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated. Only deployed AutoML tabular Models have explanation_spec.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the endpoint resource:

  • aiplatform.endpoints.explain

For more information, see the IAM documentation.

Predict

rpc Predict(PredictRequest) returns (PredictResponse)

Perform an online prediction.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the endpoint resource:

  • aiplatform.endpoints.predict

For more information, see the IAM documentation.

SpecialistPoolService

A service for creating and managing Customer SpecialistPools. When customers start Data Labeling jobs, they can reuse/create Specialist Pools to bring their own Specialists to label the data. Customers can add/remove Managers for the Specialist Pool on Cloud console, then Managers will get email notifications to manage Specialists and tasks on CrowdCompute console.

CreateSpecialistPool

rpc CreateSpecialistPool(CreateSpecialistPoolRequest) returns (Operation)

Creates a SpecialistPool.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.specialistPools.create

For more information, see the IAM documentation.

DeleteSpecialistPool

rpc DeleteSpecialistPool(DeleteSpecialistPoolRequest) returns (Operation)

Deletes a SpecialistPool as well as all Specialists in the pool.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.specialistPools.delete

For more information, see the IAM documentation.

GetSpecialistPool

rpc GetSpecialistPool(GetSpecialistPoolRequest) returns (SpecialistPool)

Gets a SpecialistPool.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.specialistPools.get

For more information, see the IAM documentation.

ListSpecialistPools

rpc ListSpecialistPools(ListSpecialistPoolsRequest) returns (ListSpecialistPoolsResponse)

Lists SpecialistPools in a Location.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the parent resource:

  • aiplatform.specialistPools.list

For more information, see the IAM documentation.

UpdateSpecialistPool

rpc UpdateSpecialistPool(UpdateSpecialistPoolRequest) returns (Operation)

Updates a SpecialistPool.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.

IAM Permissions

Requires the following IAM permission on the name resource:

  • aiplatform.specialistPools.update

For more information, see the IAM documentation.

AcceleratorType

Represents a hardware accelerator type.

Enums
ACCELERATOR_TYPE_UNSPECIFIED Unspecified accelerator type, which means no accelerator.
NVIDIA_TESLA_K80 Nvidia Tesla K80 GPU.
NVIDIA_TESLA_P100 Nvidia Tesla P100 GPU.
NVIDIA_TESLA_V100 Nvidia Tesla V100 GPU.
NVIDIA_TESLA_P4 Nvidia Tesla P4 GPU.
NVIDIA_TESLA_T4 Nvidia Tesla T4 GPU.
NVIDIA_TESLA_A100 Nvidia Tesla A100 GPU.

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.

Fields
sample_config

SampleConfig

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

training_config

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.

Union field human_labeling_budget. Required. Max human labeling DataItems. The rest part will be labeled by machine. human_labeling_budget can be only one of the following:
max_data_item_count

int64

Max number of human labeled DataItems.

max_data_item_percentage

int32

Max percent of total DataItems for human labeling.

Annotation

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

Fields
name

string

Output only. Resource name of the Annotation.

payload_schema_uri

string

Required. Google Cloud Storage URI points to a YAML file describing payload. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/annotation/, note that the chosen schema must be consistent with the parent Dataset's metadata.

payload

Value

Required. The schema of the payload can be found in payload_schema.

create_time

Timestamp

Output only. Timestamp when this Annotation was created.

update_time

Timestamp

Output only. Timestamp when this Annotation was last updated.

etag

string

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

annotation_source

UserActionReference

Output only. The source of the Annotation.

labels

map<string, string>

Optional. The labels with user-defined metadata to organize your Annotations.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Annotation(System labels are excluded).

See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Annotation:

  • "aiplatform.googleapis.com/annotation_set_name": optional, name of the UI's annotation set this Annotation belongs to. If not set, the Annotation is not visible in the UI.

  • "aiplatform.googleapis.com/payload_schema": output only, its value is the payload_schema's title.

AnnotationSpec

Identifies a concept with which DataItems may be annotated with.

Fields
name

string

Output only. Resource name of the AnnotationSpec.

display_name

string

Required. The user-defined name of the AnnotationSpec. The name can be up to 128 characters long and can be consist of any UTF-8 characters.

create_time

Timestamp

Output only. Timestamp when this AnnotationSpec was created.

update_time

Timestamp

Output only. Timestamp when AnnotationSpec was last updated.

etag

string

Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

Artifact

Instance of a general artifact.

Fields
name

string

Output only. The resource name of the Artifact.

display_name

string

User provided display name of the Artifact. May be up to 128 Unicode characters.

uri

string

The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.

etag

string

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

labels

map<string, string>

The labels with user-defined metadata to organize your Artifacts.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded).

create_time

Timestamp

Output only. Timestamp when this Artifact was created.

update_time

Timestamp

Output only. Timestamp when this Artifact was last updated.

state

State

The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex Pipelines), and the system does not prescribe or check the validity of state transitions.

State

Describes the state of the Artifact.

Enums
STATE_UNSPECIFIED Unspecified state for the Artifact.
PENDING A state used by systems like Vertex Pipelines to indicate that the underlying data item represented by this Artifact is being created.
LIVE A state indicating that the Artifact should exist, unless something external to the system deletes it.

Attribution

Attribution that explains a particular prediction output.

Fields
baseline_output_value

double

Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in ExplanationMetadata.inputs. The field name of the output is determined by the key in ExplanationMetadata.outputs.

If the Model's predicted output has multiple dimensions (rank > 1), this is the value in the output located by output_index.

If there are multiple baselines, their output values are averaged.

instance_output_value

double

Output only. Model predicted output on the corresponding [explanation instance][ExplainRequest.instances]. The field name of the output is determined by the key in ExplanationMetadata.outputs.

If the Model predicted output has multiple dimensions, this is the value in the output located by output_index.

feature_attributions

Value

Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs.

The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance contributed to the predicted result.

The format of the value is determined by the feature's input format:

  • If the feature is a scalar value, the attribution value is a floating number.

  • If the feature is an array of scalar values, the attribution value is an array.

  • If the feature is a struct, the attribution value is a struct. The keys in the attribution value struct are the same as the keys in the feature struct. The formats of the values in the attribution struct are determined by the formats of the values in the feature struct.

The ExplanationMetadata.feature_attributions_schema_uri field, pointed to by the ExplanationSpec field of the Endpoint.deployed_models object, points to the schema file that describes the features and their attribution values (if it is populated).

output_index[]

int32

Output only. The index that locates the explained prediction output.

If the prediction output is a scalar value, output_index is not populated. If the prediction output has multiple dimensions, the length of the output_index list is the same as the number of dimensions of the output. The i-th element in output_index is the element index of the i-th dimension of the output vector. Indices start from 0.

output_display_name

string

Output only. The display name of the output identified by output_index. For example, the predicted class name by a multi-classification Model.

This field is only populated iff the Model predicts display names as a separate field along with the explained output. The predicted display name must has the same shape of the explained output, and can be located using output_index.

approximation_error

double

Output only. Error of feature_attributions caused by approximation used in the explanation method. Lower value means more precise attributions.

See this introduction for more information.

output_name

string

Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs.

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.

Fields
min_replica_count

int32

Immutable. The minimum number of replicas this DeployedModel will be always deployed on. If traffic against it increases, it may dynamically be deployed onto more replicas up to max_replica_count, and as traffic decreases, some of these extra replicas may be freed. If the requested value is too large, the deployment will error.

max_replica_count

int32

Immutable. The maximum number of replicas this DeployedModel may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale the model to that many replicas is guaranteed (barring service outages). If traffic against the DeployedModel increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, a no upper bound for scaling under heavy traffic will be assume, though Vertex AI may be unable to scale beyond certain replica number.

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.

Fields
metric_name

string

Required. The resource metric name. Supported metrics:

  • For Online Prediction:
  • aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle
  • aiplatform.googleapis.com/prediction/online/cpu/utilization
target

int32

The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided.

BatchDedicatedResources

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

Fields
machine_spec

MachineSpec

Required. Immutable. The specification of a single machine.

starting_replica_count

int32

Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count

max_replica_count

int32

Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10.

BatchMigrateResourcesOperationMetadata

Runtime operation information for MigrationService.BatchMigrateResources.

Fields
generic_metadata

GenericOperationMetadata

The common part of the operation metadata.

partial_results[]

PartialResult

Partial results that reflect the latest migration operation progress.

PartialResult

Represents a partial result in batch migration operation for one MigrateResourceRequest.

Fields
request

MigrateResourceRequest

It's the same as the value in [MigrateResourceRequest.migrate_resource_requests][].

Union field result. If the resource's migration is ongoing, none of the result will be set. If the resource's migration is finished, either error or one of the migrated resource name will be filled. result can be only one of the following:
error

Status

The error result of the migration request in case of failure.

model

string

Migrated model resource name.

dataset

string

Migrated dataset resource name.

BatchMigrateResourcesRequest

Request message for MigrationService.BatchMigrateResources.

Fields
parent

string

Required. The location of the migrated resource will live in. Format: projects/{project}/locations/{location}

migrate_resource_requests[]

MigrateResourceRequest

Required. The request messages specifying the resources to migrate. They must be in the same location as the destination. Up to 50 resources can be migrated in one batch.

BatchMigrateResourcesResponse

Response message for MigrationService.BatchMigrateResources.

Fields
migrate_resource_responses[]

MigrateResourceResponse

Successfully migrated resources.

BatchPredictionJob

A job that uses a Model to produce predictions on multiple input instances. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances.

Fields
name

string

Output only. Resource name of the BatchPredictionJob.

display_name

string

Required. The user-defined name of this BatchPredictionJob.

model

string

Required. The name of the Model that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources.

input_config

InputConfig

Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri.

model_parameters

Value

The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.

output_config

OutputConfig

Required. The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri.

dedicated_resources

BatchDedicatedResources

The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided.

manual_batch_tuning_parameters

ManualBatchTuningParameters

Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself).

generate_explanation

bool

Generate explanation with the batch prediction results.

When set to true, the batch prediction output changes based on the predictions_format field of the BatchPredictionJob.output_config object:

  • bigquery: output includes a column named explanation. The value is a struct that conforms to the Explanation object.
  • jsonl: The JSON objects on each line include an additional entry keyed explanation. The value of the entry is a JSON object that conforms to the Explanation object.
  • csv: Generating explanations for CSV format is not supported.

If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated.

explanation_spec

ExplanationSpec

Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to true.

This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited.

output_info

OutputInfo

Output only. Information further describing the output of this job.

state

JobState

Output only. The detailed state of the job.

error

Status

Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED.

partial_failures[]

Status

Output only. Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard GCP error details.

resources_consumed

ResourcesConsumed

Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes.

Note: This field currently may be not populated for batch predictions that use AutoML Models.

completion_stats

CompletionStats

Output only. Statistics on completed and failed prediction instances.

create_time

Timestamp

Output only. Time when the BatchPredictionJob was created.

start_time

Timestamp

Output only. Time when the BatchPredictionJob for the first time entered the JOB_STATE_RUNNING state.

end_time

Timestamp

Output only. Time when the BatchPredictionJob entered any of the following states: JOB_STATE_SUCCEEDED, JOB_STATE_FAILED, JOB_STATE_CANCELLED.

update_time

Timestamp

Output only. Time when the BatchPredictionJob was most recently updated.

labels

map<string, string>

The labels with user-defined metadata to organize BatchPredictionJobs.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed.

See https://goo.gl/xmQnxf for more information and examples of labels.

encryption_spec

EncryptionSpec

Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key.

InputConfig

Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them.

Fields
instances_format

string

Required. The format in which instances are given, must be one of the Model's supported_input_storage_formats.

Union field source. Required. The source of the input. source can be only one of the following:
gcs_source

GcsSource

The Cloud Storage location for the input instances.

bigquery_source

BigQuerySource

The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored.

OutputConfig

Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them.

Fields
predictions_format

string

Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats.

Union field destination. Required. The destination of the output. destination can be only one of the following:
gcs_destination

GcsDestination

The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is prediction-<model-display-name>-<job-create-time>, where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files predictions_0001.<extension>, predictions_0002.<extension>, ..., predictions_N.<extension> are created where <extension> depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional errors_0001.<extension>, errors_0002.<extension>,..., errors_N.<extension> files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional error field which as value has google.rpc.Status containing only code and message fields.

bigquery_destination

BigQueryDestination

The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name prediction_<model-display-name>_<job-create-time> where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, predictions, and errors. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The predictions table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The errors table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only code and message.

OutputInfo

Further describes this job's output. Supplements output_config.

Fields
bigquery_output_table

string

Output only. The name of the BigQuery table created, in predictions_<timestamp> format, into which the prediction output is written. Can be used by UI to generate the BigQuery output path, for example.

Union field output_location. The output location into which prediction output is written. output_location can be only one of the following:
gcs_output_directory

string

Output only. The full path of the Cloud Storage directory created, into which the prediction output is written.

bigquery_output_dataset

string

Output only. The path of the BigQuery dataset created, in bq://projectId.bqDatasetId format, into which the prediction output is written.

BigQueryDestination

The BigQuery location for the output content.

Fields
output_uri

string

Required. BigQuery URI to a project or table, up to 2000 characters long.

When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist.

Accepted forms:

  • BigQuery path. For example: bq://projectId or bq://projectId.bqDatasetId or bq://projectId.bqDatasetId.bqTableId.

BigQuerySource

The BigQuery location for the input content.

Fields
input_uri

string

Required. BigQuery URI to a table, up to 2000 characters long. Accepted forms:

  • BigQuery path. For example: bq://projectId.bqDatasetId.bqTableId.

CancelBatchPredictionJobRequest

Request message for JobService.CancelBatchPredictionJob.

Fields
name

string

Required. The name of the BatchPredictionJob to cancel. Format: projects/{project}/locations/{location}/batchPredictionJobs/{batch_prediction_job}

CancelCustomJobRequest

Request message for JobService.CancelCustomJob.

Fields
name

string

Required. The name of the CustomJob to cancel. Format: projects/{project}/locations/{location}/customJobs/{custom_job}

CancelDataLabelingJobRequest

Request message for JobService.CancelDataLabelingJob.

Fields
name

string

Required. The name of the DataLabelingJob. Format: projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}

CancelHyperparameterTuningJobRequest

Request message for JobService.CancelHyperparameterTuningJob.

Fields
name

string

Required. The name of the HyperparameterTuningJob to cancel. Format: projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyperparameter_tuning_job}

CancelPipelineJobRequest

Request message for PipelineService.CancelPipelineJob.

Fields
name

string

Required. The name of the PipelineJob to cancel. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}

CancelTrainingPipelineRequest

Request message for PipelineService.CancelTrainingPipeline.

Fields
name

string

Required. The name of the TrainingPipeline to cancel. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline}

CompletionStats

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

Fields
successful_count

int64

Output only. The number of entities that had been processed successfully.

failed_count

int64

Output only. The number of entities for which any error was encountered.

incomplete_count

int64

Output only. In cases when enough errors are encountered a job, pipeline, or operation may be failed as a whole. Below is the number of entities for which the processing had not been finished (either in successful or failed state). Set to -1 if the number is unknown (for example, the operation failed before the total entity number could be collected).

ContainerRegistryDestination

The Container Registry location for the container image.

Fields
output_uri

string

Required. Container Registry URI of a container image. Only Google Container Registry and Artifact Registry are supported now. Accepted forms:

  • Google Container Registry path. For example: gcr.io/projectId/imageName:tag.

  • Artifact Registry path. For example: us-central1-docker.pkg.dev/projectId/repoName/imageName:tag.

If a tag is not specified, "latest" will be used as the default tag.

ContainerSpec

The spec of a Container.

Fields
image_uri

string

Required. The URI of a container image in the Container Registry that is to be run on each worker replica.

command[]

string

The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided.

args[]

string

The arguments to be passed when starting the container.

env[]

EnvVar

Environment variables to be passed to the container.

Context

Instance of a general context.

Fields
name

string

Output only. The resource name of the Context.

display_name

string

User provided display name of the Context. May be up to 128 Unicode characters.

etag

string

An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.

labels

map<string, string>

The labels with user-defined metadata to organize your Contexts.

Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded).

create_time

Timestamp

Output only. Timestamp when this Context was created.

update_time

Timestamp

Output only. Timestamp when this Context was last updated.

parent_contexts[]

string

Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts.

CreateBatchPredictionJobRequest

Request message for JobService.CreateBatchPredictionJob.

Fields
parent

string

Required. The resource name of the Location to create the BatchPredictionJob in. Format: projects/{project}/locations/{location}

batch_prediction_job

BatchPredictionJob

Required. The BatchPredictionJob to create.

CreateCustomJobRequest

Request message for JobService.CreateCustomJob.

Fields
parent

string

Required. The resource name of the Location to create the CustomJob in. Format: projects/{project}/locations/{location}

custom_job

CustomJob

Required. The CustomJob to create.

CreateDataLabelingJobRequest

Request message for JobService.CreateDataLabelingJob.

Fields
parent

string

Required. The parent of the DataLabelingJob. Format: projects/{project}/locations/{location}

data_labeling_job

DataLabelingJob

Required. The DataLabelingJob to create.

CreateDatasetOperationMetadata

Runtime operation information for DatasetService.CreateDataset.

Fields
generic_metadata

GenericOperationMetadata

The operation generic information.

CreateDatasetRequest

Request message for DatasetService.CreateDataset.

Fields
parent

string

Required. The resource name of the Location to create the Dataset in. Format: projects/{project}/locations/{location}

dataset

Dataset

Required. The Dataset to create.

CreateEndpointOperationMetadata

Runtime operation information for EndpointService.CreateEndpoint.

Fields
generic_metadata

GenericOperationMetadata

The operation generic information.

CreateEndpointRequest

Request message for EndpointService.CreateEndpoint.

Fields
parent

string

Required. The resource name of the Location to create the Endpoint in. Format: projects/{project}/locations/{location}

endpoint

Endpoint

Required. The Endpoint to create.

CreateHyperparameterTuningJobRequest

Request message for JobService.CreateHyperparameterTuningJob.

Fields
parent

string

Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: projects/{project}/locations/{location}

hyperparameter_tuning_job

HyperparameterTuningJob

Required. The HyperparameterTuningJob to create.

CreatePipelineJobRequest

Request message for PipelineService.CreatePipelineJob.

Fields
parent

string

Required. The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location}

pipeline_job

PipelineJob

Required. The PipelineJob to create.

pipeline_job_id

string

The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated.

This value should be less than 128 characters, and valid characters are /[a-z][0-9]-/.

CreateSpecialistPoolOperationMetadata

Runtime operation information for SpecialistPoolService.CreateSpecialistPool.

Fields
generic_metadata

GenericOperationMetadata

The operation generic information.

CreateSpecialistPoolRequest

Request message for SpecialistPoolService.CreateSpecialistPool.

Fields
parent

string

Required. The parent Project name for the new SpecialistPool. The form is projects/{project}/locations/{location}.

specialist_pool

SpecialistPool

Required. The SpecialistPool to create.

CreateTrainingPipelineRequest

Request message for PipelineService.CreateTrainingPipeline.

Fields
parent

string

Required. The resource name of the Location to create the TrainingPipeline in. Format: projects/{project}/locations/{location}

training_pipeline

TrainingPipeline

Required. The TrainingPipeline to create.

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).

Fields
name

string

Output only. Resource name of a CustomJob.

display_name

string

Required. The display name of the CustomJob. The name can be up to 128 characters long and can be consist of any UTF-8 characters.

job_spec

CustomJobSpec

Required. Job spec.

state

JobState

Output only. The detailed state of the job.

create_time

Timestamp

Output only. Time when the CustomJob was created.

start_time

Timestamp

Output only. Time when the CustomJob for the first time entered the JOB_STATE_RUNNING state.

end_time