Class AutoMlClient (2.51.0)

Service Description: 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 dash-case, either of those cases is accepted.

This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
   Dataset response = autoMlClient.getDataset(name);
 }

Note: close() needs to be called on the AutoMlClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().

Methods
Method	Description	Method Variants
CreateDataset	Creates a dataset.	Request object method variants only take one parameter, a request object, which must be constructed before the call. createDatasetAsync(CreateDatasetRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. createDatasetAsync(LocationName parent, Dataset dataset) createDatasetAsync(String parent, Dataset dataset) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. createDatasetOperationCallable() createDatasetCallable()
GetDataset	Gets a dataset.	Request object method variants only take one parameter, a request object, which must be constructed before the call. getDataset(GetDatasetRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. getDataset(DatasetName name) getDataset(String name) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. getDatasetCallable()
ListDatasets	Lists datasets in a project.	Request object method variants only take one parameter, a request object, which must be constructed before the call. listDatasets(ListDatasetsRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. listDatasets(LocationName parent) listDatasets(String parent) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. listDatasetsPagedCallable() listDatasetsCallable()
UpdateDataset	Updates a dataset.	Request object method variants only take one parameter, a request object, which must be constructed before the call. updateDataset(UpdateDatasetRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. updateDataset(Dataset dataset, FieldMask updateMask) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. updateDatasetCallable()
DeleteDataset	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.	Request object method variants only take one parameter, a request object, which must be constructed before the call. deleteDatasetAsync(DeleteDatasetRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. deleteDatasetAsync(DatasetName name) deleteDatasetAsync(String name) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. deleteDatasetOperationCallable() deleteDatasetCallable()
ImportData	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.	Request object method variants only take one parameter, a request object, which must be constructed before the call. importDataAsync(ImportDataRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. importDataAsync(DatasetName name, InputConfig inputConfig) importDataAsync(String name, InputConfig inputConfig) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. importDataOperationCallable() importDataCallable()
ExportData	Exports dataset's data to the provided output location. Returns an empty response in the response field when it completes.	Request object method variants only take one parameter, a request object, which must be constructed before the call. exportDataAsync(ExportDataRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. exportDataAsync(DatasetName name, OutputConfig outputConfig) exportDataAsync(String name, OutputConfig outputConfig) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. exportDataOperationCallable() exportDataCallable()
GetAnnotationSpec	Gets an annotation spec.	Request object method variants only take one parameter, a request object, which must be constructed before the call. getAnnotationSpec(GetAnnotationSpecRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. getAnnotationSpec(AnnotationSpecName name) getAnnotationSpec(String name) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. getAnnotationSpecCallable()
CreateModel	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.	Request object method variants only take one parameter, a request object, which must be constructed before the call. createModelAsync(CreateModelRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. createModelAsync(LocationName parent, Model model) createModelAsync(String parent, Model model) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. createModelOperationCallable() createModelCallable()
GetModel	Gets a model.	Request object method variants only take one parameter, a request object, which must be constructed before the call. getModel(GetModelRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. getModel(ModelName name) getModel(String name) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. getModelCallable()
ListModels	Lists models.	Request object method variants only take one parameter, a request object, which must be constructed before the call. listModels(ListModelsRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. listModels(LocationName parent) listModels(String parent) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. listModelsPagedCallable() listModelsCallable()
DeleteModel	Deletes a model. Returns `google.protobuf.Empty` in the response field when it completes, and `delete_details` in the metadata field.	Request object method variants only take one parameter, a request object, which must be constructed before the call. deleteModelAsync(DeleteModelRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. deleteModelAsync(ModelName name) deleteModelAsync(String name) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. deleteModelOperationCallable() deleteModelCallable()
UpdateModel	Updates a model.	Request object method variants only take one parameter, a request object, which must be constructed before the call. updateModel(UpdateModelRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. updateModel(Model model, FieldMask updateMask) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. updateModelCallable()
DeployModel	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.	Request object method variants only take one parameter, a request object, which must be constructed before the call. deployModelAsync(DeployModelRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. deployModelAsync(ModelName name) deployModelAsync(String name) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. deployModelOperationCallable() deployModelCallable()
UndeployModel	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.	Request object method variants only take one parameter, a request object, which must be constructed before the call. undeployModelAsync(UndeployModelRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. undeployModelAsync(ModelName name) undeployModelAsync(String name) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. undeployModelOperationCallable() undeployModelCallable()
ExportModel	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.	Request object method variants only take one parameter, a request object, which must be constructed before the call. exportModelAsync(ExportModelRequest request) Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service. exportModelAsync(ModelName name, ModelExportOutputConfig outputConfig) exportModelAsync(String name, ModelExportOutputConfig outputConfig) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. exportModelOperationCallable() exportModelCallable()
GetModelEvaluation	Gets a model evaluation.	Request object method variants only take one parameter, a request object, which must be constructed before the call. getModelEvaluation(GetModelEvaluationRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. getModelEvaluation(ModelEvaluationName name) getModelEvaluation(String name) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. getModelEvaluationCallable()
ListModelEvaluations	Lists model evaluations.	Request object method variants only take one parameter, a request object, which must be constructed before the call. listModelEvaluations(ListModelEvaluationsRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. listModelEvaluations(ModelName parent, String filter) listModelEvaluations(String parent, String filter) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. listModelEvaluationsPagedCallable() listModelEvaluationsCallable()

See the individual methods for example code.

Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.

This class can be customized by passing in a custom instance of AutoMlSettings to create(). For example:

To customize credentials:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 AutoMlSettings autoMlSettings =
     AutoMlSettings.newBuilder()
         .setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
         .build();
 AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);

To customize the endpoint:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 AutoMlSettings autoMlSettings = AutoMlSettings.newBuilder().setEndpoint(myEndpoint).build();
 AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);

To use REST (HTTP1.1/JSON) transport (instead of gRPC) for sending and receiving requests over the wire:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 AutoMlSettings autoMlSettings = AutoMlSettings.newHttpJsonBuilder().build();
 AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);

Please refer to the GitHub repository's samples for more quickstart code snippets.

Inheritance

java.lang.Object > AutoMlClient

Static Methods

create()

public static final AutoMlClient create()

Constructs an instance of AutoMlClient with default settings.

Returns
Type	Description
`AutoMlClient`

Exceptions
Type	Description
`IOException`

create(AutoMlSettings settings)

public static final AutoMlClient create(AutoMlSettings settings)

Constructs an instance of AutoMlClient, using the given settings. The channels are created based on the settings passed in, or defaults for any settings that are not set.

Parameter
Name	Description
`settings`	`AutoMlSettings`

Returns
Type	Description
`AutoMlClient`

Exceptions
Type	Description
`IOException`

create(AutoMlStub stub)

public static final AutoMlClient create(AutoMlStub stub)

Constructs an instance of AutoMlClient, using the given stub for making calls. This is for advanced usage - prefer using create(AutoMlSettings).

Parameter
Name	Description
`stub`	`AutoMlStub`

Returns
Type	Description
`AutoMlClient`

Constructors

AutoMlClient(AutoMlSettings settings)

protected AutoMlClient(AutoMlSettings settings)

Constructs an instance of AutoMlClient, using the given settings. This is protected so that it is easy to make a subclass, but otherwise, the static factory methods should be preferred.

Parameter
Name	Description
`settings`	`AutoMlSettings`

AutoMlClient(AutoMlStub stub)

protected AutoMlClient(AutoMlStub stub)

Parameter
Name	Description
`stub`	`AutoMlStub`

Methods

awaitTermination(long duration, TimeUnit unit)

public boolean awaitTermination(long duration, TimeUnit unit)

Parameters
Name	Description
`duration`	`long`
`unit`	`TimeUnit`

Returns
Type	Description
`boolean`

Exceptions
Type	Description
`InterruptedException`

close()

public final void close()

createDatasetAsync(CreateDatasetRequest request)

public final OperationFuture<Dataset,OperationMetadata> createDatasetAsync(CreateDatasetRequest request)

Creates a dataset.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   CreateDatasetRequest request =
       CreateDatasetRequest.newBuilder()
           .setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
           .setDataset(Dataset.newBuilder().build())
           .build();
   Dataset response = autoMlClient.createDatasetAsync(request).get();
 }

Parameter
Name	Description
`request`	`CreateDatasetRequest` The request object containing all of the parameters for the API call.

Returns
Type	Description
`OperationFuture<Dataset,OperationMetadata>`

createDatasetAsync(LocationName parent, Dataset dataset)

public final OperationFuture<Dataset,OperationMetadata> createDatasetAsync(LocationName parent, Dataset dataset)

Creates a dataset.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   Dataset dataset = Dataset.newBuilder().build();
   Dataset response = autoMlClient.createDatasetAsync(parent, dataset).get();
 }

Parameters
Name	Description
`parent`	`LocationName` Required. The resource name of the project to create the dataset for.
`dataset`	`Dataset` Required. The dataset to create.

Returns
Type	Description
`OperationFuture<Dataset,OperationMetadata>`

createDatasetAsync(String parent, Dataset dataset)

public final OperationFuture<Dataset,OperationMetadata> createDatasetAsync(String parent, Dataset dataset)

Creates a dataset.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
   Dataset dataset = Dataset.newBuilder().build();
   Dataset response = autoMlClient.createDatasetAsync(parent, dataset).get();
 }

Parameters
Name	Description
`parent`	`String` Required. The resource name of the project to create the dataset for.
`dataset`	`Dataset` Required. The dataset to create.

Returns
Type	Description
`OperationFuture<Dataset,OperationMetadata>`

createDatasetCallable()

public final UnaryCallable<CreateDatasetRequest,Operation> createDatasetCallable()

Creates a dataset.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   CreateDatasetRequest request =
       CreateDatasetRequest.newBuilder()
           .setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
           .setDataset(Dataset.newBuilder().build())
           .build();
   ApiFuture<Operation> future = autoMlClient.createDatasetCallable().futureCall(request);
   // Do something.
   Operation response = future.get();
 }

Returns
Type	Description
`UnaryCallable<CreateDatasetRequest,Operation>`

createDatasetOperationCallable()

public final OperationCallable<CreateDatasetRequest,Dataset,OperationMetadata> createDatasetOperationCallable()

Creates a dataset.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   CreateDatasetRequest request =
       CreateDatasetRequest.newBuilder()
           .setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
           .setDataset(Dataset.newBuilder().build())
           .build();
   OperationFuture<Dataset, OperationMetadata> future =
       autoMlClient.createDatasetOperationCallable().futureCall(request);
   // Do something.
   Dataset response = future.get();
 }

Returns
Type	Description
`OperationCallable<CreateDatasetRequest,Dataset,OperationMetadata>`

createModelAsync(CreateModelRequest request)

public final OperationFuture<Model,OperationMetadata> createModelAsync(CreateModelRequest request)

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   CreateModelRequest request =
       CreateModelRequest.newBuilder()
           .setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
           .setModel(Model.newBuilder().build())
           .build();
   Model response = autoMlClient.createModelAsync(request).get();
 }

Parameter
Name	Description
`request`	`CreateModelRequest` The request object containing all of the parameters for the API call.

Returns
Type	Description
`OperationFuture<Model,OperationMetadata>`

createModelAsync(LocationName parent, Model model)

public final OperationFuture<Model,OperationMetadata> createModelAsync(LocationName parent, Model model)

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   Model model = Model.newBuilder().build();
   Model response = autoMlClient.createModelAsync(parent, model).get();
 }

Parameters
Name	Description
`parent`	`LocationName` Required. Resource name of the parent project where the model is being created.
`model`	`Model` Required. The model to create.

Returns
Type	Description
`OperationFuture<Model,OperationMetadata>`

createModelAsync(String parent, Model model)

public final OperationFuture<Model,OperationMetadata> createModelAsync(String parent, Model model)

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
   Model model = Model.newBuilder().build();
   Model response = autoMlClient.createModelAsync(parent, model).get();
 }

Parameters
Name	Description
`parent`	`String` Required. Resource name of the parent project where the model is being created.
`model`	`Model` Required. The model to create.

Returns
Type	Description
`OperationFuture<Model,OperationMetadata>`

createModelCallable()

public final UnaryCallable<CreateModelRequest,Operation> createModelCallable()

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   CreateModelRequest request =
       CreateModelRequest.newBuilder()
           .setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
           .setModel(Model.newBuilder().build())
           .build();
   ApiFuture<Operation> future = autoMlClient.createModelCallable().futureCall(request);
   // Do something.
   Operation response = future.get();
 }

Returns
Type	Description
`UnaryCallable<CreateModelRequest,Operation>`

createModelOperationCallable()

public final OperationCallable<CreateModelRequest,Model,OperationMetadata> createModelOperationCallable()

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   CreateModelRequest request =
       CreateModelRequest.newBuilder()
           .setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
           .setModel(Model.newBuilder().build())
           .build();
   OperationFuture<Model, OperationMetadata> future =
       autoMlClient.createModelOperationCallable().futureCall(request);
   // Do something.
   Model response = future.get();
 }

Returns
Type	Description
`OperationCallable<CreateModelRequest,Model,OperationMetadata>`

deleteDatasetAsync(DatasetName name)

public final OperationFuture<Empty,OperationMetadata> deleteDatasetAsync(DatasetName name)

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
   autoMlClient.deleteDatasetAsync(name).get();
 }

Parameter
Name	Description
`name`	`DatasetName` Required. The resource name of the dataset to delete.

Returns
Type	Description
`OperationFuture<Empty,OperationMetadata>`

deleteDatasetAsync(DeleteDatasetRequest request)

public final OperationFuture<Empty,OperationMetadata> deleteDatasetAsync(DeleteDatasetRequest request)

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeleteDatasetRequest request =
       DeleteDatasetRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .build();
   autoMlClient.deleteDatasetAsync(request).get();
 }

Parameter
Name	Description
`request`	`DeleteDatasetRequest` The request object containing all of the parameters for the API call.

Returns
Type	Description
`OperationFuture<Empty,OperationMetadata>`

deleteDatasetAsync(String name)

public final OperationFuture<Empty,OperationMetadata> deleteDatasetAsync(String name)

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
   autoMlClient.deleteDatasetAsync(name).get();
 }

Parameter
Name	Description
`name`	`String` Required. The resource name of the dataset to delete.

Returns
Type	Description
`OperationFuture<Empty,OperationMetadata>`

deleteDatasetCallable()

public final UnaryCallable<DeleteDatasetRequest,Operation> deleteDatasetCallable()

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeleteDatasetRequest request =
       DeleteDatasetRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .build();
   ApiFuture<Operation> future = autoMlClient.deleteDatasetCallable().futureCall(request);
   // Do something.
   future.get();
 }

Returns
Type	Description
`UnaryCallable<DeleteDatasetRequest,Operation>`

deleteDatasetOperationCallable()

public final OperationCallable<DeleteDatasetRequest,Empty,OperationMetadata> deleteDatasetOperationCallable()

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeleteDatasetRequest request =
       DeleteDatasetRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .build();
   OperationFuture<Empty, OperationMetadata> future =
       autoMlClient.deleteDatasetOperationCallable().futureCall(request);
   // Do something.
   future.get();
 }

Returns
Type	Description
`OperationCallable<DeleteDatasetRequest,Empty,OperationMetadata>`

deleteModelAsync(DeleteModelRequest request)

public final OperationFuture<Empty,OperationMetadata> deleteModelAsync(DeleteModelRequest request)

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

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeleteModelRequest request =
       DeleteModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   autoMlClient.deleteModelAsync(request).get();
 }

Parameter
Name	Description
`request`	`DeleteModelRequest` The request object containing all of the parameters for the API call.

Returns
Type	Description
`OperationFuture<Empty,OperationMetadata>`

deleteModelAsync(ModelName name)

public final OperationFuture<Empty,OperationMetadata> deleteModelAsync(ModelName name)

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

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   autoMlClient.deleteModelAsync(name).get();
 }

Parameter
Name	Description
`name`	`ModelName` Required. Resource name of the model being deleted.

Returns
Type	Description
`OperationFuture<Empty,OperationMetadata>`

deleteModelAsync(String name)

public final OperationFuture<Empty,OperationMetadata> deleteModelAsync(String name)

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

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
   autoMlClient.deleteModelAsync(name).get();
 }

Parameter
Name	Description
`name`	`String` Required. Resource name of the model being deleted.

Returns
Type	Description
`OperationFuture<Empty,OperationMetadata>`

deleteModelCallable()

public final UnaryCallable<DeleteModelRequest,Operation> deleteModelCallable()

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

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeleteModelRequest request =
       DeleteModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   ApiFuture<Operation> future = autoMlClient.deleteModelCallable().futureCall(request);
   // Do something.
   future.get();
 }

Returns
Type	Description
`UnaryCallable<DeleteModelRequest,Operation>`

deleteModelOperationCallable()

public final OperationCallable<DeleteModelRequest,Empty,OperationMetadata> deleteModelOperationCallable()

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

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeleteModelRequest request =
       DeleteModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   OperationFuture<Empty, OperationMetadata> future =
       autoMlClient.deleteModelOperationCallable().futureCall(request);
   // Do something.
   future.get();
 }

Returns
Type	Description
`OperationCallable<DeleteModelRequest,Empty,OperationMetadata>`

deployModelAsync(DeployModelRequest request)

public final OperationFuture<Empty,OperationMetadata> deployModelAsync(DeployModelRequest request)

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeployModelRequest request =
       DeployModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   autoMlClient.deployModelAsync(request).get();
 }

Parameter
Name	Description
`request`	`DeployModelRequest` The request object containing all of the parameters for the API call.

Returns
Type	Description
`OperationFuture<Empty,OperationMetadata>`

deployModelAsync(ModelName name)

public final OperationFuture<Empty,OperationMetadata> deployModelAsync(ModelName name)

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   autoMlClient.deployModelAsync(name).get();
 }

Parameter
Name	Description
`name`	`ModelName` Required. Resource name of the model to deploy.

Returns
Type	Description
`OperationFuture<Empty,OperationMetadata>`

deployModelAsync(String name)

public final OperationFuture<Empty,OperationMetadata> deployModelAsync(String name)

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.

Sample code:


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (