Class AutoMlClient

public class AutoMlClient implements BackgroundResource

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 kebab-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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   Dataset dataset = Dataset.newBuilder().build();
   Dataset response = autoMlClient.createDataset(parent, dataset);
 }
 

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().

The surface of this class includes several types of Java methods for each of the API's methods:

  1. A "flattened" method. With this type of method, the fields of the request type have been converted into function parameters. It may be the case that not all fields are available as parameters, and not every API method will have a flattened method entry point.
  2. A "request object" method. This type of method only takes one parameter, a request object, which must be constructed before the call. Not every API method will have a request object method.
  3. A "callable" method. This type of method takes no parameters and returns an immutable API callable object, which can be used to initiate calls to the service.

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:


 AutoMlSettings autoMlSettings =
     AutoMlSettings.newBuilder()
         .setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
         .build();
 AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);
 

To customize the endpoint:


 AutoMlSettings autoMlSettings = AutoMlSettings.newBuilder().setEndpoint(myEndpoint).build();
 AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);
 

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

Inheritance

java.lang.Object > AutoMlClient

Implements

BackgroundResource

Static Methods

create()

public static final AutoMlClient create()

Constructs an instance of AutoMlClient with default settings.

Returns
TypeDescription
AutoMlClient
Exceptions
TypeDescription
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
NameDescription
settingsAutoMlSettings
Returns
TypeDescription
AutoMlClient
Exceptions
TypeDescription
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
NameDescription
stubAutoMlStub
Returns
TypeDescription
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
NameDescription
settingsAutoMlSettings

AutoMlClient(AutoMlStub stub)

protected AutoMlClient(AutoMlStub stub)
Parameter
NameDescription
stubAutoMlStub

Methods

awaitTermination(long duration, TimeUnit unit)

public boolean awaitTermination(long duration, TimeUnit unit)
Parameters
NameDescription
durationlong
unitTimeUnit
Returns
TypeDescription
boolean
Exceptions
TypeDescription
InterruptedException

close()

public final void close()

createDataset(CreateDatasetRequest request)

public final Dataset createDataset(CreateDatasetRequest request)

Creates a dataset.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   CreateDatasetRequest request =
       CreateDatasetRequest.newBuilder()
           .setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
           .setDataset(Dataset.newBuilder().build())
           .build();
   Dataset response = autoMlClient.createDataset(request);
 }
 
Parameter
NameDescription
requestCreateDatasetRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
Dataset

createDataset(LocationName parent, Dataset dataset)

public final Dataset createDataset(LocationName parent, Dataset dataset)

Creates a dataset.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   Dataset dataset = Dataset.newBuilder().build();
   Dataset response = autoMlClient.createDataset(parent, dataset);
 }
 
Parameters
NameDescription
parentLocationName

Required. The resource name of the project to create the dataset for.

datasetDataset

Required. The dataset to create.

Returns
TypeDescription
Dataset

createDataset(String parent, Dataset dataset)

public final Dataset createDataset(String parent, Dataset dataset)

Creates a dataset.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
   Dataset dataset = Dataset.newBuilder().build();
   Dataset response = autoMlClient.createDataset(parent, dataset);
 }
 
Parameters
NameDescription
parentString

Required. The resource name of the project to create the dataset for.

datasetDataset

Required. The dataset to create.

Returns
TypeDescription
Dataset

createDatasetCallable()

public final UnaryCallable<CreateDatasetRequest,Dataset> createDatasetCallable()

Creates a dataset.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   CreateDatasetRequest request =
       CreateDatasetRequest.newBuilder()
           .setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
           .setDataset(Dataset.newBuilder().build())
           .build();
   ApiFuture<Dataset> future = autoMlClient.createDatasetCallable().futureCall(request);
   // Do something.
   Dataset response = future.get();
 }
 
Returns
TypeDescription
UnaryCallable<CreateDatasetRequest,Dataset>

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:


 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
NameDescription
requestCreateModelRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
OperationFuture<Model,OperationMetadata>

createModelAsync(LocationName parent, Model model)

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

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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
   Model model = Model.newBuilder().build();
   Model response = autoMlClient.createModelAsync(parent, model).get();
 }
 
Parameters
NameDescription
parentLocationName

Required. Resource name of the parent project where the model is being created.

modelModel

Required. The model to create.

Returns
TypeDescription
OperationFuture<Model,OperationMetadata>

createModelAsync(String parent, Model model)

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

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:


 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
NameDescription
parentString

Required. Resource name of the parent project where the model is being created.

modelModel

Required. The model to create.

Returns
TypeDescription
OperationFuture<Model,OperationMetadata>

createModelCallable()

public final UnaryCallable<CreateModelRequest,Operation> createModelCallable()

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:


 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
TypeDescription
UnaryCallable<CreateModelRequest,Operation>

createModelOperationCallable()

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

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:


 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
TypeDescription
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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
   autoMlClient.deleteDatasetAsync(name).get();
 }
 
Parameter
NameDescription
nameDatasetName

Required. The resource name of the dataset to delete.

Returns
TypeDescription
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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeleteDatasetRequest request =
       DeleteDatasetRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .build();
   autoMlClient.deleteDatasetAsync(request).get();
 }
 
Parameter
NameDescription
requestDeleteDatasetRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
   autoMlClient.deleteDatasetAsync(name).get();
 }
 
Parameter
NameDescription
nameString

Required. The resource name of the dataset to delete.

Returns
TypeDescription
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:


 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
TypeDescription
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:


 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
TypeDescription
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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeleteModelRequest request =
       DeleteModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   autoMlClient.deleteModelAsync(request).get();
 }
 
Parameter
NameDescription
requestDeleteModelRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   autoMlClient.deleteModelAsync(name).get();
 }
 
Parameter
NameDescription
nameModelName

Required. Resource name of the model being deleted.

Returns
TypeDescription
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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
   autoMlClient.deleteModelAsync(name).get();
 }
 
Parameter
NameDescription
nameString

Required. Resource name of the model being deleted.

Returns
TypeDescription
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:


 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
TypeDescription
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:


 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
TypeDescription
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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeployModelRequest request =
       DeployModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   autoMlClient.deployModelAsync(request).get();
 }
 
Parameter
NameDescription
requestDeployModelRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

deployModelAsync(ModelName name)

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

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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   autoMlClient.deployModelAsync(name).get();
 }
 
Parameter
NameDescription
nameModelName

Required. Resource name of the model to deploy.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

deployModelAsync(String name)

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

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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
   autoMlClient.deployModelAsync(name).get();
 }
 
Parameter
NameDescription
nameString

Required. Resource name of the model to deploy.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

deployModelCallable()

public final UnaryCallable<DeployModelRequest,Operation> deployModelCallable()

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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeployModelRequest request =
       DeployModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   ApiFuture<Operation> future = autoMlClient.deployModelCallable().futureCall(request);
   // Do something.
   future.get();
 }
 
Returns
TypeDescription
UnaryCallable<DeployModelRequest,Operation>

deployModelOperationCallable()

public final OperationCallable<DeployModelRequest,Empty,OperationMetadata> deployModelOperationCallable()

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:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DeployModelRequest request =
       DeployModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   OperationFuture<Empty, OperationMetadata> future =
       autoMlClient.deployModelOperationCallable().futureCall(request);
   // Do something.
   future.get();
 }
 
Returns
TypeDescription
OperationCallable<DeployModelRequest,Empty,OperationMetadata>

exportDataAsync(DatasetName name, OutputConfig outputConfig)

public final OperationFuture<Empty,OperationMetadata> exportDataAsync(DatasetName name, OutputConfig outputConfig)

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

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
   OutputConfig outputConfig = OutputConfig.newBuilder().build();
   autoMlClient.exportDataAsync(name, outputConfig).get();
 }
 
Parameters
NameDescription
nameDatasetName

Required. The resource name of the dataset.

outputConfigOutputConfig

Required. The desired output location.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportDataAsync(ExportDataRequest request)

public final OperationFuture<Empty,OperationMetadata> exportDataAsync(ExportDataRequest request)

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

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportDataRequest request =
       ExportDataRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .setOutputConfig(OutputConfig.newBuilder().build())
           .build();
   autoMlClient.exportDataAsync(request).get();
 }
 
Parameter
NameDescription
requestExportDataRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportDataAsync(String name, OutputConfig outputConfig)

public final OperationFuture<Empty,OperationMetadata> exportDataAsync(String name, OutputConfig outputConfig)

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

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
   OutputConfig outputConfig = OutputConfig.newBuilder().build();
   autoMlClient.exportDataAsync(name, outputConfig).get();
 }
 
Parameters
NameDescription
nameString

Required. The resource name of the dataset.

outputConfigOutputConfig

Required. The desired output location.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportDataCallable()

public final UnaryCallable<ExportDataRequest,Operation> exportDataCallable()

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

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportDataRequest request =
       ExportDataRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .setOutputConfig(OutputConfig.newBuilder().build())
           .build();
   ApiFuture<Operation> future = autoMlClient.exportDataCallable().futureCall(request);
   // Do something.
   future.get();
 }
 
Returns
TypeDescription
UnaryCallable<ExportDataRequest,Operation>

exportDataOperationCallable()

public final OperationCallable<ExportDataRequest,Empty,OperationMetadata> exportDataOperationCallable()

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

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportDataRequest request =
       ExportDataRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .setOutputConfig(OutputConfig.newBuilder().build())
           .build();
   OperationFuture<Empty, OperationMetadata> future =
       autoMlClient.exportDataOperationCallable().futureCall(request);
   // Do something.
   future.get();
 }
 
Returns
TypeDescription
OperationCallable<ExportDataRequest,Empty,OperationMetadata>

exportEvaluatedExamplesAsync(ExportEvaluatedExamplesRequest request)

public final OperationFuture<Empty,OperationMetadata> exportEvaluatedExamplesAsync(ExportEvaluatedExamplesRequest request)

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportEvaluatedExamplesRequest request =
       ExportEvaluatedExamplesRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setOutputConfig(ExportEvaluatedExamplesOutputConfig.newBuilder().build())
           .build();
   autoMlClient.exportEvaluatedExamplesAsync(request).get();
 }
 
Parameter
NameDescription
requestExportEvaluatedExamplesRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportEvaluatedExamplesAsync(ModelName name, ExportEvaluatedExamplesOutputConfig outputConfig)

public final OperationFuture<Empty,OperationMetadata> exportEvaluatedExamplesAsync(ModelName name, ExportEvaluatedExamplesOutputConfig outputConfig)

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   ExportEvaluatedExamplesOutputConfig outputConfig =
       ExportEvaluatedExamplesOutputConfig.newBuilder().build();
   autoMlClient.exportEvaluatedExamplesAsync(name, outputConfig).get();
 }
 
Parameters
NameDescription
nameModelName

Required. The resource name of the model whose evaluated examples are to be exported.

outputConfigExportEvaluatedExamplesOutputConfig

Required. The desired output location and configuration.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportEvaluatedExamplesAsync(String name, ExportEvaluatedExamplesOutputConfig outputConfig)

public final OperationFuture<Empty,OperationMetadata> exportEvaluatedExamplesAsync(String name, ExportEvaluatedExamplesOutputConfig outputConfig)

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
   ExportEvaluatedExamplesOutputConfig outputConfig =
       ExportEvaluatedExamplesOutputConfig.newBuilder().build();
   autoMlClient.exportEvaluatedExamplesAsync(name, outputConfig).get();
 }
 
Parameters
NameDescription
nameString

Required. The resource name of the model whose evaluated examples are to be exported.

outputConfigExportEvaluatedExamplesOutputConfig

Required. The desired output location and configuration.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportEvaluatedExamplesCallable()

public final UnaryCallable<ExportEvaluatedExamplesRequest,Operation> exportEvaluatedExamplesCallable()

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportEvaluatedExamplesRequest request =
       ExportEvaluatedExamplesRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setOutputConfig(ExportEvaluatedExamplesOutputConfig.newBuilder().build())
           .build();
   ApiFuture<Operation> future =
       autoMlClient.exportEvaluatedExamplesCallable().futureCall(request);
   // Do something.
   future.get();
 }
 
Returns
TypeDescription
UnaryCallable<ExportEvaluatedExamplesRequest,Operation>

exportEvaluatedExamplesOperationCallable()

public final OperationCallable<ExportEvaluatedExamplesRequest,Empty,OperationMetadata> exportEvaluatedExamplesOperationCallable()

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportEvaluatedExamplesRequest request =
       ExportEvaluatedExamplesRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setOutputConfig(ExportEvaluatedExamplesOutputConfig.newBuilder().build())
           .build();
   OperationFuture<Empty, OperationMetadata> future =
       autoMlClient.exportEvaluatedExamplesOperationCallable().futureCall(request);
   // Do something.
   future.get();
 }
 
Returns
TypeDescription
OperationCallable<ExportEvaluatedExamplesRequest,Empty,OperationMetadata>

exportModelAsync(ExportModelRequest request)

public final OperationFuture<Empty,OperationMetadata> exportModelAsync(ExportModelRequest request)

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportModelRequest request =
       ExportModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setOutputConfig(ModelExportOutputConfig.newBuilder().build())
           .build();
   autoMlClient.exportModelAsync(request).get();
 }
 
Parameter
NameDescription
requestExportModelRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportModelAsync(ModelName name, ModelExportOutputConfig outputConfig)

public final OperationFuture<Empty,OperationMetadata> exportModelAsync(ModelName name, ModelExportOutputConfig outputConfig)

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   ModelExportOutputConfig outputConfig = ModelExportOutputConfig.newBuilder().build();
   autoMlClient.exportModelAsync(name, outputConfig).get();
 }
 
Parameters
NameDescription
nameModelName

Required. The resource name of the model to export.

outputConfigModelExportOutputConfig

Required. The desired output location and configuration.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportModelAsync(String name, ModelExportOutputConfig outputConfig)

public final OperationFuture<Empty,OperationMetadata> exportModelAsync(String name, ModelExportOutputConfig outputConfig)

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
   ModelExportOutputConfig outputConfig = ModelExportOutputConfig.newBuilder().build();
   autoMlClient.exportModelAsync(name, outputConfig).get();
 }
 
Parameters
NameDescription
nameString

Required. The resource name of the model to export.

outputConfigModelExportOutputConfig

Required. The desired output location and configuration.

Returns
TypeDescription
OperationFuture<Empty,OperationMetadata>

exportModelCallable()

public final UnaryCallable<ExportModelRequest,Operation> exportModelCallable()

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportModelRequest request =
       ExportModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setOutputConfig(ModelExportOutputConfig.newBuilder().build())
           .build();
   ApiFuture<Operation> future = autoMlClient.exportModelCallable().futureCall(request);
   // Do something.
   future.get();
 }
 
Returns
TypeDescription
UnaryCallable<ExportModelRequest,Operation>

exportModelOperationCallable()

public final OperationCallable<ExportModelRequest,Empty,OperationMetadata> exportModelOperationCallable()

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.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ExportModelRequest request =
       ExportModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setOutputConfig(ModelExportOutputConfig.newBuilder().build())
           .build();
   OperationFuture<Empty, OperationMetadata> future =
       autoMlClient.exportModelOperationCallable().futureCall(request);
   // Do something.
   future.get();
 }
 
Returns
TypeDescription
OperationCallable<ExportModelRequest,Empty,OperationMetadata>

getAnnotationSpec(AnnotationSpecName name)

public final AnnotationSpec getAnnotationSpec(AnnotationSpecName name)

Gets an annotation spec.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   AnnotationSpecName name =
       AnnotationSpecName.of("[PROJECT]", "[LOCATION]", "[DATASET]", "[ANNOTATION_SPEC]");
   AnnotationSpec response = autoMlClient.getAnnotationSpec(name);
 }
 
Parameter
NameDescription
nameAnnotationSpecName

Required. The resource name of the annotation spec to retrieve.

Returns
TypeDescription
AnnotationSpec

getAnnotationSpec(GetAnnotationSpecRequest request)

public final AnnotationSpec getAnnotationSpec(GetAnnotationSpecRequest request)

Gets an annotation spec.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetAnnotationSpecRequest request =
       GetAnnotationSpecRequest.newBuilder()
           .setName(
               AnnotationSpecName.of("[PROJECT]", "[LOCATION]", "[DATASET]", "[ANNOTATION_SPEC]")
                   .toString())
           .build();
   AnnotationSpec response = autoMlClient.getAnnotationSpec(request);
 }
 
Parameter
NameDescription
requestGetAnnotationSpecRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
AnnotationSpec

getAnnotationSpec(String name)

public final AnnotationSpec getAnnotationSpec(String name)

Gets an annotation spec.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name =
       AnnotationSpecName.of("[PROJECT]", "[LOCATION]", "[DATASET]", "[ANNOTATION_SPEC]")
           .toString();
   AnnotationSpec response = autoMlClient.getAnnotationSpec(name);
 }
 
Parameter
NameDescription
nameString

Required. The resource name of the annotation spec to retrieve.

Returns
TypeDescription
AnnotationSpec

getAnnotationSpecCallable()

public final UnaryCallable<GetAnnotationSpecRequest,AnnotationSpec> getAnnotationSpecCallable()

Gets an annotation spec.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetAnnotationSpecRequest request =
       GetAnnotationSpecRequest.newBuilder()
           .setName(
               AnnotationSpecName.of("[PROJECT]", "[LOCATION]", "[DATASET]", "[ANNOTATION_SPEC]")
                   .toString())
           .build();
   ApiFuture<AnnotationSpec> future =
       autoMlClient.getAnnotationSpecCallable().futureCall(request);
   // Do something.
   AnnotationSpec response = future.get();
 }
 
Returns
TypeDescription
UnaryCallable<GetAnnotationSpecRequest,AnnotationSpec>

getColumnSpec(ColumnSpecName name)

public final ColumnSpec getColumnSpec(ColumnSpecName name)

Gets a column spec.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ColumnSpecName name =
       ColumnSpecName.of(
           "[PROJECT]", "[LOCATION]", "[DATASET]", "[TABLE_SPEC]", "[COLUMN_SPEC]");
   ColumnSpec response = autoMlClient.getColumnSpec(name);
 }
 
Parameter
NameDescription
nameColumnSpecName

Required. The resource name of the column spec to retrieve.

Returns
TypeDescription
ColumnSpec

getColumnSpec(GetColumnSpecRequest request)

public final ColumnSpec getColumnSpec(GetColumnSpecRequest request)

Gets a column spec.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetColumnSpecRequest request =
       GetColumnSpecRequest.newBuilder()
           .setName(
               ColumnSpecName.of(
                       "[PROJECT]", "[LOCATION]", "[DATASET]", "[TABLE_SPEC]", "[COLUMN_SPEC]")
                   .toString())
           .setFieldMask(FieldMask.newBuilder().build())
           .build();
   ColumnSpec response = autoMlClient.getColumnSpec(request);
 }
 
Parameter
NameDescription
requestGetColumnSpecRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
ColumnSpec

getColumnSpec(String name)

public final ColumnSpec getColumnSpec(String name)

Gets a column spec.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name =
       ColumnSpecName.of("[PROJECT]", "[LOCATION]", "[DATASET]", "[TABLE_SPEC]", "[COLUMN_SPEC]")
           .toString();
   ColumnSpec response = autoMlClient.getColumnSpec(name);
 }
 
Parameter
NameDescription
nameString

Required. The resource name of the column spec to retrieve.

Returns
TypeDescription
ColumnSpec

getColumnSpecCallable()

public final UnaryCallable<GetColumnSpecRequest,ColumnSpec> getColumnSpecCallable()

Gets a column spec.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetColumnSpecRequest request =
       GetColumnSpecRequest.newBuilder()
           .setName(
               ColumnSpecName.of(
                       "[PROJECT]", "[LOCATION]", "[DATASET]", "[TABLE_SPEC]", "[COLUMN_SPEC]")
                   .toString())
           .setFieldMask(FieldMask.newBuilder().build())
           .build();
   ApiFuture<ColumnSpec> future = autoMlClient.getColumnSpecCallable().futureCall(request);
   // Do something.
   ColumnSpec response = future.get();
 }
 
Returns
TypeDescription
UnaryCallable<GetColumnSpecRequest,ColumnSpec>

getDataset(DatasetName name)

public final Dataset getDataset(DatasetName name)

Gets a dataset.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
   Dataset response = autoMlClient.getDataset(name);
 }
 
Parameter
NameDescription
nameDatasetName

Required. The resource name of the dataset to retrieve.

Returns
TypeDescription
Dataset

getDataset(GetDatasetRequest request)

public final Dataset getDataset(GetDatasetRequest request)

Gets a dataset.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetDatasetRequest request =
       GetDatasetRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .build();
   Dataset response = autoMlClient.getDataset(request);
 }
 
Parameter
NameDescription
requestGetDatasetRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
Dataset

getDataset(String name)

public final Dataset getDataset(String name)

Gets a dataset.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
   Dataset response = autoMlClient.getDataset(name);
 }
 
Parameter
NameDescription
nameString

Required. The resource name of the dataset to retrieve.

Returns
TypeDescription
Dataset

getDatasetCallable()

public final UnaryCallable<GetDatasetRequest,Dataset> getDatasetCallable()

Gets a dataset.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetDatasetRequest request =
       GetDatasetRequest.newBuilder()
           .setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
           .build();
   ApiFuture<Dataset> future = autoMlClient.getDatasetCallable().futureCall(request);
   // Do something.
   Dataset response = future.get();
 }
 
Returns
TypeDescription
UnaryCallable<GetDatasetRequest,Dataset>

getModel(GetModelRequest request)

public final Model getModel(GetModelRequest request)

Gets a model.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetModelRequest request =
       GetModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   Model response = autoMlClient.getModel(request);
 }
 
Parameter
NameDescription
requestGetModelRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
Model

getModel(ModelName name)

public final Model getModel(ModelName name)

Gets a model.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   Model response = autoMlClient.getModel(name);
 }
 
Parameter
NameDescription
nameModelName

Required. Resource name of the model.

Returns
TypeDescription
Model

getModel(String name)

public final Model getModel(String name)

Gets a model.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
   Model response = autoMlClient.getModel(name);
 }
 
Parameter
NameDescription
nameString

Required. Resource name of the model.

Returns
TypeDescription
Model

getModelCallable()

public final UnaryCallable<GetModelRequest,Model> getModelCallable()

Gets a model.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetModelRequest request =
       GetModelRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .build();
   ApiFuture<Model> future = autoMlClient.getModelCallable().futureCall(request);
   // Do something.
   Model response = future.get();
 }
 
Returns
TypeDescription
UnaryCallable<GetModelRequest,Model>

getModelEvaluation(GetModelEvaluationRequest request)

public final ModelEvaluation getModelEvaluation(GetModelEvaluationRequest request)

Gets a model evaluation.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetModelEvaluationRequest request =
       GetModelEvaluationRequest.newBuilder()
           .setName(
               ModelEvaluationName.of("[PROJECT]", "[LOCATION]", "[MODEL]", "[MODEL_EVALUATION]")
                   .toString())
           .build();
   ModelEvaluation response = autoMlClient.getModelEvaluation(request);
 }
 
Parameter
NameDescription
requestGetModelEvaluationRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
ModelEvaluation

getModelEvaluation(ModelEvaluationName name)

public final ModelEvaluation getModelEvaluation(ModelEvaluationName name)

Gets a model evaluation.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   ModelEvaluationName name =
       ModelEvaluationName.of("[PROJECT]", "[LOCATION]", "[MODEL]", "[MODEL_EVALUATION]");
   ModelEvaluation response = autoMlClient.getModelEvaluation(name);
 }
 
Parameter
NameDescription
nameModelEvaluationName

Required. Resource name for the model evaluation.

Returns
TypeDescription
ModelEvaluation

getModelEvaluation(String name)

public final ModelEvaluation getModelEvaluation(String name)

Gets a model evaluation.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   String name =
       ModelEvaluationName.of("[PROJECT]", "[LOCATION]", "[MODEL]", "[MODEL_EVALUATION]")
           .toString();
   ModelEvaluation response = autoMlClient.getModelEvaluation(name);
 }
 
Parameter
NameDescription
nameString

Required. Resource name for the model evaluation.

Returns
TypeDescription
ModelEvaluation

getModelEvaluationCallable()

public final UnaryCallable<GetModelEvaluationRequest,ModelEvaluation> getModelEvaluationCallable()

Gets a model evaluation.

Sample code:


 try (AutoMlClient autoMlClient = AutoMlClient.create()) {
   GetModelEvaluationRequest request =
       GetModelEvaluationRequest.newBuilder()
           .setName(
               ModelEvaluationName.of("[PROJECT]", "[LOCATION]", "[MODEL]", "[MODEL_EVALUATION]")
                   .toString())
           .build();
   ApiFuture<ModelEvaluation> future =
       autoMlClient.getModelEvaluationCallable().futureCall(request);
   // Do something.
   ModelEvaluation response = future.get();
 }
 
Returns
TypeDescription
UnaryCallable<GetModelEvaluationRequest,ModelEvaluation>

getOperationsClient()

public final OperationsClient getOperationsClient()

Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.

Returns
TypeDescription
OperationsClient

getSettings()

public final AutoMlSettings getSettings()
Returns
TypeDescription
AutoMlSettings

getStub()

public AutoMlStub getStub()
Returns </
TypeDescription
AutoMlStub