Interface AutoMlGrpc.AsyncService (2.43.0)

AutoML Server API. The resource names are assigned by the server. The server never reuses names that it has created after the resources with those names are deleted. An ID of a resource is the last element of the item's resource name. For projects/{project_id}/locations/{location_id}/datasets/{dataset_id}, then the id for the item is {dataset_id}. Currently the only supported location_id is "us-central1". On any input that is documented to expect a string parameter in snake_case or kebab-case, either of those cases is accepted.

Creates a dataset.

Creates a model. Returns a Model in the response field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec.

Deletes a dataset and all of its contents. Returns empty response in the response field when it completes, and delete_details in the metadata field.

Deletes a model. Returns google.protobuf.Empty in the response field when it completes, and delete_details in the metadata field.

Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing node_number) will reset the deployment state without pausing the model's availability. Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage deployment automatically. Returns an empty response in the response field when it completes.

Exports dataset's data to the provided output location. Returns an empty response in the response field when it completes.

Exports examples on which the model was evaluated (i.e. which were in the TEST set of the dataset the model was created from), together with their ground truth annotations and the annotations created (predicted) by the model. The examples, ground truth and predictions are exported in the state they were at the moment the model was evaluated. This export is available only for 30 days since the model evaluation is created. Currently only available for Tables. Returns an empty response in the response field when it completes.

Exports a trained, "export-able", model to a user specified Google Cloud Storage location. A model is considered export-able if and only if it has an export format defined for it in ModelExportOutputConfig. Returns an empty response in the response field when it completes.

Gets an annotation spec.

Gets a column spec.

Gets a dataset.

Gets a model.

Gets a model evaluation.

Gets a table spec.

Imports data into a dataset. For Tables this method can only be called on an empty Dataset. For Tables:

• A schema_inference_version parameter must be explicitly set. Returns an empty response in the response field when it completes.

Lists column specs in a table spec.

Lists datasets in a project.

Lists model evaluations.

Lists models.

Lists table specs in a dataset.

Undeploys a model. If the model is not deployed this method has no effect. Only applicable for Text Classification, Image Object Detection and Tables; all other domains manage deployment automatically. Returns an empty response in the response field when it completes.

Updates a column spec.

Updates a dataset.

Updates a table spec.