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API documentation for aiplatform_v1beta1.types
package.
Classes
ActiveLearningConfig
Paramaters that configure 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.
Attribution
Attribution that explains a particular prediction output.
AutomaticResources
A description of resources that to large degree are decided by AI Platform, 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
.
BatchMigrateResourcesRequest
Request message for
MigrationService.BatchMigrateResources
.
BatchMigrateResourcesResponse
Response message for
MigrationService.BatchMigrateResources
.
BatchPredictionJob
A job that uses a
Model
to
produce predictions on multiple [input
instances][google.cloud.aiplatform.v1beta1.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
.
CancelCustomJobRequest
Request message for
JobService.CancelCustomJob
.
CancelDataLabelingJobRequest
Request message for [DataLabelingJobService.CancelDataLabelingJob][].
CancelHyperparameterTuningJobRequest
Request message for
JobService.CancelHyperparameterTuningJob
.
CancelTrainingPipelineRequest
Request message for
PipelineService.CancelTrainingPipeline
.
CompletionStats
Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch.
ContainerRegistryDestination
The Container Regsitry location for the container image.
ContainerSpec
The spec of a Container.
CreateBatchPredictionJobRequest
Request message for
JobService.CreateBatchPredictionJob
.
CreateCustomJobRequest
Request message for
JobService.CreateCustomJob
.
CreateDataLabelingJobRequest
Request message for [DataLabelingJobService.CreateDataLabelingJob][].
CreateDatasetOperationMetadata
Runtime operation information for
DatasetService.CreateDataset
.
CreateDatasetRequest
Request message for
DatasetService.CreateDataset
.
CreateEndpointOperationMetadata
Runtime operation information for
EndpointService.CreateEndpoint
.
CreateEndpointRequest
Request message for
EndpointService.CreateEndpoint
.
CreateHyperparameterTuningJobRequest
Request message for
JobService.CreateHyperparameterTuningJob
.
CreateSpecialistPoolOperationMetadata
Runtime operation information for
SpecialistPoolService.CreateSpecialistPool
.
CreateSpecialistPoolRequest
Request message for
SpecialistPoolService.CreateSpecialistPool
.
CreateTrainingPipelineRequest
Request message for
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
.
DeleteCustomJobRequest
Request message for
JobService.DeleteCustomJob
.
DeleteDataLabelingJobRequest
Request message for
JobService.DeleteDataLabelingJob
.
DeleteDatasetRequest
Request message for
DatasetService.DeleteDataset
.
DeleteEndpointRequest
Request message for
EndpointService.DeleteEndpoint
.
DeleteHyperparameterTuningJobRequest
Request message for
JobService.DeleteHyperparameterTuningJob
.
DeleteModelRequest
Request message for
ModelService.DeleteModel
.
DeleteOperationMetadata
Details of operations that perform deletes of any entities.
DeleteSpecialistPoolRequest
Request message for
SpecialistPoolService.DeleteSpecialistPool
.
DeleteTrainingPipelineRequest
Request message for
PipelineService.DeleteTrainingPipeline
.
DeployModelOperationMetadata
Runtime operation information for
EndpointService.DeployModel
.
DeployModelRequest
Request message for
EndpointService.DeployModel
.
DeployModelResponse
Response message for
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.
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.
ExplainRequest
Request message for
PredictionService.Explain
.
ExplainResponse
Response message for
PredictionService.Explain
.
Explanation
Explanation of a prediction (provided in
PredictResponse.predictions
)
produced by the Model on a given
instance
.
ExplanationMetadata
Metadata describing the Model's input and output for explanation.
ExplanationParameters
Parameters to configure explaining for Model's predictions.
ExplanationSpec
Specification of Model explanation.
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
.
ExportDataRequest
Request message for
DatasetService.ExportData
.
ExportDataResponse
Response message for
DatasetService.ExportData
.
ExportModelOperationMetadata
Details of
ModelService.ExportModel
operation.
ExportModelRequest
Request message for
ModelService.ExportModel
.
ExportModelResponse
Response message of
ModelService.ExportModel
operation.
FeatureNoiseSigma
Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients.
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 AI Platform.
If none of the fractions are set, by default roughly 80% of data
will be 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
.
GetBatchPredictionJobRequest
Request message for
JobService.GetBatchPredictionJob
.
GetCustomJobRequest
Request message for
JobService.GetCustomJob
.
GetDataLabelingJobRequest
Request message for [DataLabelingJobService.GetDataLabelingJob][].
GetDatasetRequest
Request message for
DatasetService.GetDataset
.
GetEndpointRequest
Request message for
EndpointService.GetEndpoint
GetHyperparameterTuningJobRequest
Request message for
JobService.GetHyperparameterTuningJob
.
GetModelEvaluationRequest
Request message for
ModelService.GetModelEvaluation
.
GetModelEvaluationSliceRequest
Request message for
ModelService.GetModelEvaluationSlice
.
GetModelRequest
Request message for
ModelService.GetModel
.
GetSpecialistPoolRequest
Request message for
SpecialistPoolService.GetSpecialistPool
.
GetTrainingPipelineRequest
Request message for
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
.
ImportDataRequest
Request message for
DatasetService.ImportData
.
ImportDataResponse
Response message for
DatasetService.ImportData
.
InputDataConfig
Specifies AI Platform owned input data to be used for training, and possibly evaluating, the Model.
IntegratedGradientsAttribution
An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365
ListAnnotationsRequest
Request message for
DatasetService.ListAnnotations
.
ListAnnotationsResponse
Response message for
DatasetService.ListAnnotations
.
ListBatchPredictionJobsRequest
Request message for
JobService.ListBatchPredictionJobs
.
ListBatchPredictionJobsResponse
Response message for
JobService.ListBatchPredictionJobs
ListCustomJobsRequest
Request message for
JobService.ListCustomJobs
.
ListCustomJobsResponse
Response message for
JobService.ListCustomJobs
ListDataItemsRequest
Request message for
DatasetService.ListDataItems
.
ListDataItemsResponse
Response message for
DatasetService.ListDataItems
.
ListDataLabelingJobsRequest
Request message for [DataLabelingJobService.ListDataLabelingJobs][].
ListDataLabelingJobsResponse
Response message for
JobService.ListDataLabelingJobs
.
ListDatasetsRequest
Request message for
DatasetService.ListDatasets
.
ListDatasetsResponse
Response message for
DatasetService.ListDatasets
.
ListEndpointsRequest
Request message for
EndpointService.ListEndpoints
.
ListEndpointsResponse
Response message for
EndpointService.ListEndpoints
.
ListHyperparameterTuningJobsRequest
Request message for
JobService.ListHyperparameterTuningJobs
.
ListHyperparameterTuningJobsResponse
Response message for
JobService.ListHyperparameterTuningJobs
ListModelEvaluationSlicesRequest
Request message for
ModelService.ListModelEvaluationSlices
.
ListModelEvaluationSlicesResponse
Response message for
ModelService.ListModelEvaluationSlices
.
ListModelEvaluationsRequest
Request message for
ModelService.ListModelEvaluations
.
ListModelEvaluationsResponse
Response message for
ModelService.ListModelEvaluations
.
ListModelsRequest
Request message for
ModelService.ListModels
.
ListModelsResponse
Response message for
ModelService.ListModels
ListSpecialistPoolsRequest
Request message for
SpecialistPoolService.ListSpecialistPools
.
ListSpecialistPoolsResponse
Response message for
SpecialistPoolService.ListSpecialistPools
.
ListTrainingPipelinesRequest
Request message for
PipelineService.ListTrainingPipelines
.
ListTrainingPipelinesResponse
Response message for
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 AI Platform.
MigrateResourceResponse
Describes a successfully migrated resource.
Model
A trained machine learning Model.
ModelContainerSpec
Specification of a container for serving predictions. This message
is a subset of the Kubernetes Container v1 core
specification <https://tinyurl.com/k8s-io-api/v1.18/#container-v1-core>
__.
ModelEvaluation
A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.
ModelEvaluationSlice
A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.
ModelExplanation
Aggregated explanation metrics for a Model over a set of instances.
Port
Represents a network port in a container.
PredefinedSplit
Assigns input data to training, validation, and test sets based on the value of a provided key.
Supported only for tabular Datasets.
PredictRequest
Request message for
PredictionService.Predict
.
PredictResponse
Response message for
PredictionService.Predict
.
PredictSchemata
Contains the schemata used in Model's predictions and explanations
via
PredictionService.Predict
,
PredictionService.Explain
and
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.
SampledShapleyAttribution
An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features.
Scheduling
All parameters related to queuing and scheduling of custom jobs.
SearchMigratableResourcesRequest
Request message for
MigrationService.SearchMigratableResources
.
SearchMigratableResourcesResponse
Response message for
MigrationService.SearchMigratableResources
.
SmoothGradConfig
Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf
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. Supported only for tabular Datasets.
TrainingConfig
CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.
TrainingPipeline
The TrainingPipeline orchestrates tasks associated with training a
Model. It always executes the training task, and optionally may also
export data from AI Platform's Dataset which becomes the training
input,
upload
the Model to AI Platform, 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
.
UndeployModelRequest
Request message for
EndpointService.UndeployModel
.
UndeployModelResponse
Response message for
EndpointService.UndeployModel
.
UpdateDatasetRequest
Request message for
DatasetService.UpdateDataset
.
UpdateEndpointRequest
Request message for
EndpointService.UpdateEndpoint
.
UpdateModelRequest
Request message for
ModelService.UpdateModel
.
UpdateSpecialistPoolOperationMetadata
Runtime operation metadata for
SpecialistPoolService.UpdateSpecialistPool
.
UpdateSpecialistPoolRequest
Request message for
SpecialistPoolService.UpdateSpecialistPool
.
UploadModelOperationMetadata
Details of
ModelService.UploadModel
operation.
UploadModelRequest
Request message for
ModelService.UploadModel
.
UploadModelResponse
Response message of
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.
XraiAttribution
An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825
Only supports image Models (modality
is
IMAGE).