Module gapi_grpc::google::cloud::aiplatform::v1[][src]

Modules

active_learning_config
batch_migrate_resources_operation_metadata
batch_prediction_job
dataset_service_client

Generated client implementations.

deployed_model
endpoint_service_client

Generated client implementations.

export_data_config
export_model_operation_metadata
export_model_request
import_data_config
input_data_config
job_service_client

Generated client implementations.

measurement
migratable_resource
migrate_resource_request
migrate_resource_response
migration_service_client

Generated client implementations.

model
model_evaluation_slice
model_service_client

Generated client implementations.

pipeline_service_client

Generated client implementations.

prediction_service_client

Generated client implementations.

sample_config
schema
specialist_pool_service_client

Generated client implementations.

study_spec
trial
user_action_reference
worker_pool_spec

Structs

ActiveLearningConfig

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

Annotation

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

AnnotationSpec

Identifies a concept with which DataItems may be annotated with.

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.

BatchDedicatedResources

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

BatchMigrateResourcesOperationMetadata

Runtime operation information for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].

BatchMigrateResourcesRequest

Request message for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].

BatchMigrateResourcesResponse

Response message for [MigrationService.BatchMigrateResources][google.cloud.aiplatform.v1.MigrationService.BatchMigrateResources].

BatchPredictionJob

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

BigQueryDestination

The BigQuery location for the output content.

BigQuerySource

The BigQuery location for the input content.

CancelBatchPredictionJobRequest

Request message for [JobService.CancelBatchPredictionJob][google.cloud.aiplatform.v1.JobService.CancelBatchPredictionJob].

CancelCustomJobRequest

Request message for [JobService.CancelCustomJob][google.cloud.aiplatform.v1.JobService.CancelCustomJob].

CancelDataLabelingJobRequest

Request message for [JobService.CancelDataLabelingJob][google.cloud.aiplatform.v1.JobService.CancelDataLabelingJob].

CancelHyperparameterTuningJobRequest

Request message for [JobService.CancelHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.CancelHyperparameterTuningJob].

CancelTrainingPipelineRequest

Request message for [PipelineService.CancelTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CancelTrainingPipeline].

CompletionStats

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

ContainerRegistryDestination

The Container Registry location for the container image.

ContainerSpec

The spec of a Container.

CreateBatchPredictionJobRequest

Request message for [JobService.CreateBatchPredictionJob][google.cloud.aiplatform.v1.JobService.CreateBatchPredictionJob].

CreateCustomJobRequest

Request message for [JobService.CreateCustomJob][google.cloud.aiplatform.v1.JobService.CreateCustomJob].

CreateDataLabelingJobRequest

Request message for [JobService.CreateDataLabelingJob][google.cloud.aiplatform.v1.JobService.CreateDataLabelingJob].

CreateDatasetOperationMetadata

Runtime operation information for [DatasetService.CreateDataset][google.cloud.aiplatform.v1.DatasetService.CreateDataset].

CreateDatasetRequest

Request message for [DatasetService.CreateDataset][google.cloud.aiplatform.v1.DatasetService.CreateDataset].

CreateEndpointOperationMetadata

Runtime operation information for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1.EndpointService.CreateEndpoint].

CreateEndpointRequest

Request message for [EndpointService.CreateEndpoint][google.cloud.aiplatform.v1.EndpointService.CreateEndpoint].

CreateHyperparameterTuningJobRequest

Request message for [JobService.CreateHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.CreateHyperparameterTuningJob].

CreateSpecialistPoolOperationMetadata

Runtime operation information for [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.CreateSpecialistPool].

CreateSpecialistPoolRequest

Request message for [SpecialistPoolService.CreateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.CreateSpecialistPool].

CreateTrainingPipelineRequest

Request message for [PipelineService.CreateTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.CreateTrainingPipeline].

CustomJob

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

CustomJobSpec

Represents the spec of a CustomJob.

DataItem

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

DataLabelingJob

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

Dataset

A collection of DataItems and Annotations on them.

DedicatedResources

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

DeleteBatchPredictionJobRequest

Request message for [JobService.DeleteBatchPredictionJob][google.cloud.aiplatform.v1.JobService.DeleteBatchPredictionJob].

DeleteCustomJobRequest

Request message for [JobService.DeleteCustomJob][google.cloud.aiplatform.v1.JobService.DeleteCustomJob].

DeleteDataLabelingJobRequest

Request message for [JobService.DeleteDataLabelingJob][google.cloud.aiplatform.v1.JobService.DeleteDataLabelingJob].

DeleteDatasetRequest

Request message for [DatasetService.DeleteDataset][google.cloud.aiplatform.v1.DatasetService.DeleteDataset].

DeleteEndpointRequest

Request message for [EndpointService.DeleteEndpoint][google.cloud.aiplatform.v1.EndpointService.DeleteEndpoint].

DeleteHyperparameterTuningJobRequest

Request message for [JobService.DeleteHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.DeleteHyperparameterTuningJob].

DeleteModelRequest

Request message for [ModelService.DeleteModel][google.cloud.aiplatform.v1.ModelService.DeleteModel].

DeleteOperationMetadata

Details of operations that perform deletes of any entities.

DeleteSpecialistPoolRequest

Request message for [SpecialistPoolService.DeleteSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.DeleteSpecialistPool].

DeleteTrainingPipelineRequest

Request message for [PipelineService.DeleteTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.DeleteTrainingPipeline].

DeployModelOperationMetadata

Runtime operation information for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].

DeployModelRequest

Request message for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].

DeployModelResponse

Response message for [EndpointService.DeployModel][google.cloud.aiplatform.v1.EndpointService.DeployModel].

DeployedModel

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

DeployedModelRef

Points to a DeployedModel.

DiskSpec

Represents the spec of disk options.

EncryptionSpec

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

Endpoint

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

EnvVar

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

ExportDataConfig

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

ExportDataOperationMetadata

Runtime operation information for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].

ExportDataRequest

Request message for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].

ExportDataResponse

Response message for [DatasetService.ExportData][google.cloud.aiplatform.v1.DatasetService.ExportData].

ExportModelOperationMetadata

Details of [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel] operation.

ExportModelRequest

Request message for [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel].

ExportModelResponse

Response message of [ModelService.ExportModel][google.cloud.aiplatform.v1.ModelService.ExportModel] operation.

FilterSplit

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

FractionSplit

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

GcsDestination

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

GcsSource

The Google Cloud Storage location for the input content.

GenericOperationMetadata

Generic Metadata shared by all operations.

GetAnnotationSpecRequest

Request message for [DatasetService.GetAnnotationSpec][google.cloud.aiplatform.v1.DatasetService.GetAnnotationSpec].

GetBatchPredictionJobRequest

Request message for [JobService.GetBatchPredictionJob][google.cloud.aiplatform.v1.JobService.GetBatchPredictionJob].

GetCustomJobRequest

Request message for [JobService.GetCustomJob][google.cloud.aiplatform.v1.JobService.GetCustomJob].

GetDataLabelingJobRequest

Request message for [JobService.GetDataLabelingJob][google.cloud.aiplatform.v1.JobService.GetDataLabelingJob].

GetDatasetRequest

Request message for [DatasetService.GetDataset][google.cloud.aiplatform.v1.DatasetService.GetDataset].

GetEndpointRequest

Request message for [EndpointService.GetEndpoint][google.cloud.aiplatform.v1.EndpointService.GetEndpoint]

GetHyperparameterTuningJobRequest

Request message for [JobService.GetHyperparameterTuningJob][google.cloud.aiplatform.v1.JobService.GetHyperparameterTuningJob].

GetModelEvaluationRequest

Request message for [ModelService.GetModelEvaluation][google.cloud.aiplatform.v1.ModelService.GetModelEvaluation].

GetModelEvaluationSliceRequest

Request message for [ModelService.GetModelEvaluationSlice][google.cloud.aiplatform.v1.ModelService.GetModelEvaluationSlice].

GetModelRequest

Request message for [ModelService.GetModel][google.cloud.aiplatform.v1.ModelService.GetModel].

GetSpecialistPoolRequest

Request message for [SpecialistPoolService.GetSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.GetSpecialistPool].

GetTrainingPipelineRequest

Request message for [PipelineService.GetTrainingPipeline][google.cloud.aiplatform.v1.PipelineService.GetTrainingPipeline].

HyperparameterTuningJob

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

ImportDataConfig

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

ImportDataOperationMetadata

Runtime operation information for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].

ImportDataRequest

Request message for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].

ImportDataResponse

Response message for [DatasetService.ImportData][google.cloud.aiplatform.v1.DatasetService.ImportData].

InputDataConfig

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

ListAnnotationsRequest

Request message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].

ListAnnotationsResponse

Response message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1.DatasetService.ListAnnotations].

ListBatchPredictionJobsRequest

Request message for [JobService.ListBatchPredictionJobs][google.cloud.aiplatform.v1.JobService.ListBatchPredictionJobs].

ListBatchPredictionJobsResponse

Response message for [JobService.ListBatchPredictionJobs][google.cloud.aiplatform.v1.JobService.ListBatchPredictionJobs]

ListCustomJobsRequest

Request message for [JobService.ListCustomJobs][google.cloud.aiplatform.v1.JobService.ListCustomJobs].

ListCustomJobsResponse

Response message for [JobService.ListCustomJobs][google.cloud.aiplatform.v1.JobService.ListCustomJobs]

ListDataItemsRequest

Request message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems].

ListDataItemsResponse

Response message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1.DatasetService.ListDataItems].

ListDataLabelingJobsRequest

Request message for [JobService.ListDataLabelingJobs][google.cloud.aiplatform.v1.JobService.ListDataLabelingJobs].

ListDataLabelingJobsResponse

Response message for [JobService.ListDataLabelingJobs][google.cloud.aiplatform.v1.JobService.ListDataLabelingJobs].

ListDatasetsRequest

Request message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1.DatasetService.ListDatasets].

ListDatasetsResponse

Response message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1.DatasetService.ListDatasets].

ListEndpointsRequest

Request message for [EndpointService.ListEndpoints][google.cloud.aiplatform.v1.EndpointService.ListEndpoints].

ListEndpointsResponse

Response message for [EndpointService.ListEndpoints][google.cloud.aiplatform.v1.EndpointService.ListEndpoints].

ListHyperparameterTuningJobsRequest

Request message for [JobService.ListHyperparameterTuningJobs][google.cloud.aiplatform.v1.JobService.ListHyperparameterTuningJobs].

ListHyperparameterTuningJobsResponse

Response message for [JobService.ListHyperparameterTuningJobs][google.cloud.aiplatform.v1.JobService.ListHyperparameterTuningJobs]

ListModelEvaluationSlicesRequest

Request message for [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.ListModelEvaluationSlices].

ListModelEvaluationSlicesResponse

Response message for [ModelService.ListModelEvaluationSlices][google.cloud.aiplatform.v1.ModelService.ListModelEvaluationSlices].

ListModelEvaluationsRequest

Request message for [ModelService.ListModelEvaluations][google.cloud.aiplatform.v1.ModelService.ListModelEvaluations].

ListModelEvaluationsResponse

Response message for [ModelService.ListModelEvaluations][google.cloud.aiplatform.v1.ModelService.ListModelEvaluations].

ListModelsRequest

Request message for [ModelService.ListModels][google.cloud.aiplatform.v1.ModelService.ListModels].

ListModelsResponse

Response message for [ModelService.ListModels][google.cloud.aiplatform.v1.ModelService.ListModels]

ListSpecialistPoolsRequest

Request message for [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1.SpecialistPoolService.ListSpecialistPools].

ListSpecialistPoolsResponse

Response message for [SpecialistPoolService.ListSpecialistPools][google.cloud.aiplatform.v1.SpecialistPoolService.ListSpecialistPools].

ListTrainingPipelinesRequest

Request message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines].

ListTrainingPipelinesResponse

Response message for [PipelineService.ListTrainingPipelines][google.cloud.aiplatform.v1.PipelineService.ListTrainingPipelines]

MachineSpec

Specification of a single machine.

ManualBatchTuningParameters

Manual batch tuning parameters.

Measurement

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

MigratableResource

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

MigrateResourceRequest

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

MigrateResourceResponse

Describes a successfully migrated resource.

Model

A trained machine learning Model.

ModelContainerSpec

Specification of a container for serving predictions. Some fields in this message correspond to fields in the Kubernetes Container v1 core specification.

ModelEvaluation

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

ModelEvaluationSlice

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

Port

Represents a network port in a container.

PredefinedSplit

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

PredictRequest

Request message for [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict].

PredictResponse

Response message for [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict].

PredictSchemata

Contains the schemata used in Model’s predictions and explanations via [PredictionService.Predict][google.cloud.aiplatform.v1.PredictionService.Predict], [PredictionService.Explain][] and [BatchPredictionJob][google.cloud.aiplatform.v1.BatchPredictionJob].

PythonPackageSpec

The spec of a Python packaged code.

ResourcesConsumed

Statistics information about resource consumption.

SampleConfig

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

Scheduling

All parameters related to queuing and scheduling of custom jobs.

SearchMigratableResourcesRequest

Request message for [MigrationService.SearchMigratableResources][google.cloud.aiplatform.v1.MigrationService.SearchMigratableResources].

SearchMigratableResourcesResponse

Response message for [MigrationService.SearchMigratableResources][google.cloud.aiplatform.v1.MigrationService.SearchMigratableResources].

SpecialistPool

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

StudySpec

Represents specification of a Study.

TimestampSplit

Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set.

TrainingConfig

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

TrainingPipeline

The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI’s Dataset which becomes the training input, [upload][google.cloud.aiplatform.v1.ModelService.UploadModel] the Model to Vertex AI, and evaluate the Model.

Trial

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

UndeployModelOperationMetadata

Runtime operation information for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].

UndeployModelRequest

Request message for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].

UndeployModelResponse

Response message for [EndpointService.UndeployModel][google.cloud.aiplatform.v1.EndpointService.UndeployModel].

UpdateDatasetRequest

Request message for [DatasetService.UpdateDataset][google.cloud.aiplatform.v1.DatasetService.UpdateDataset].

UpdateEndpointRequest

Request message for [EndpointService.UpdateEndpoint][google.cloud.aiplatform.v1.EndpointService.UpdateEndpoint].

UpdateModelRequest

Request message for [ModelService.UpdateModel][google.cloud.aiplatform.v1.ModelService.UpdateModel].

UpdateSpecialistPoolOperationMetadata

Runtime operation metadata for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.UpdateSpecialistPool].

UpdateSpecialistPoolRequest

Request message for [SpecialistPoolService.UpdateSpecialistPool][google.cloud.aiplatform.v1.SpecialistPoolService.UpdateSpecialistPool].

UploadModelOperationMetadata

Details of [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel] operation.

UploadModelRequest

Request message for [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel].

UploadModelResponse

Response message of [ModelService.UploadModel][google.cloud.aiplatform.v1.ModelService.UploadModel] operation.

UserActionReference

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

WorkerPoolSpec

Represents the spec of a worker pool in a job.

Enums

AcceleratorType

Represents a hardware accelerator type.

JobState

Describes the state of a job.

PipelineState

Describes the state of a pipeline.