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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 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 for illustrative purposes only.
// It may require modifications to work in your environment.
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().
The surface of this class includes several types of Java methods for each of the API's methods:
- 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.
- 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.
- 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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
AutoMlSettings autoMlSettings =
AutoMlSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);
To customize the endpoint:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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 for illustrative purposes only.
// It may require modifications to work in your environment.
AutoMlSettings autoMlSettings =
AutoMlSettings.newBuilder()
.setTransportChannelProvider(
AutoMlSettings.defaultHttpJsonTransportProviderBuilder().build())
.build();
AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
Implements
BackgroundResourceStatic Methods
create()
public static final AutoMlClient create()
Constructs an instance of AutoMlClient with default settings.
Type | Description |
AutoMlClient |
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.
Name | Description |
settings | AutoMlSettings |
Type | Description |
AutoMlClient |
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).
Name | Description |
stub | AutoMlStub |
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.
Name | Description |
settings | AutoMlSettings |
AutoMlClient(AutoMlStub stub)
protected AutoMlClient(AutoMlStub stub)
Name | Description |
stub | AutoMlStub |
Methods
awaitTermination(long duration, TimeUnit unit)
public boolean awaitTermination(long duration, TimeUnit unit)
Name | Description |
duration | long |
unit | TimeUnit |
Type | Description |
boolean |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Name | Description |
request | CreateDatasetRequest The request object containing all of the parameters for the API call. |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
Dataset dataset = Dataset.newBuilder().build();
Dataset response = autoMlClient.createDatasetAsync(parent, dataset).get();
}
Name | Description |
parent | LocationName Required. The resource name of the project to create the dataset for. |
dataset | Dataset Required. The dataset to create. |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
Dataset dataset = Dataset.newBuilder().build();
Dataset response = autoMlClient.createDatasetAsync(parent, dataset).get();
}
Name | Description |
parent | String Required. The resource name of the project to create the dataset for. |
dataset | Dataset Required. The dataset to create. |
Type | Description |
OperationFuture<Dataset,OperationMetadata> |
createDatasetCallable()
public final UnaryCallable<CreateDatasetRequest,Operation> createDatasetCallable()
Creates a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
UnaryCallable<CreateDatasetRequest,Operation> |
createDatasetOperationCallable()
public final OperationCallable<CreateDatasetRequest,Dataset,OperationMetadata> createDatasetOperationCallable()
Creates a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
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 for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Name | Description |
request | CreateModelRequest The request object containing all of the parameters for the API call. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
Model model = Model.newBuilder().build();
Model response = autoMlClient.createModelAsync(parent, model).get();
}
Name | Description |
parent | LocationName Required. Resource name of the parent project where the model is being created. |
model | Model Required. The model to create. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
Model model = Model.newBuilder().build();
Model response = autoMlClient.createModelAsync(parent, model).get();
}
Name | Description |
parent | String Required. Resource name of the parent project where the model is being created. |
model | Model Required. The model to create. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
autoMlClient.deleteDatasetAsync(name).get();
}
Name | Description |
name | DatasetName Required. The resource name of the dataset to delete. |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeleteDatasetRequest request =
DeleteDatasetRequest.newBuilder()
.setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
.build();
autoMlClient.deleteDatasetAsync(request).get();
}
Name | Description |
request | DeleteDatasetRequest The request object containing all of the parameters for the API call. |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
autoMlClient.deleteDatasetAsync(name).get();
}
Name | Description |
name | String Required. The resource name of the dataset to delete. |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
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 for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeleteModelRequest request =
DeleteModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
autoMlClient.deleteModelAsync(request).get();
}
Name | Description |
request | DeleteModelRequest The request object containing all of the parameters for the API call. |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
autoMlClient.deleteModelAsync(name).get();
}
Name | Description |
name | ModelName Required. Resource name of the model being deleted. |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
autoMlClient.deleteModelAsync(name).get();
}
Name | Description |
name | String Required. Resource name of the model being deleted. |
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 for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
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 for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
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 for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeployModelRequest request =
DeployModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
autoMlClient.deployModelAsync(request).get();
}
Name | Description |
request | DeployModelRequest The request object containing all of the parameters for the API call. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
autoMlClient.deployModelAsync(name).get();
}
Name | Description |
name | ModelName Required. Resource name of the model to deploy. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
autoMlClient.deployModelAsync(name).get();
}
Name | Description |
name | String Required. Resource name of the model to deploy. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
OutputConfig outputConfig = OutputConfig.newBuilder().build();
autoMlClient.exportDataAsync(name, outputConfig).get();
}
Name | Description |
name | DatasetName Required. The resource name of the dataset. |
outputConfig | OutputConfig Required. The desired output location. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Name | Description |
request | ExportDataRequest The request object containing all of the parameters for the API call. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
OutputConfig outputConfig = OutputConfig.newBuilder().build();
autoMlClient.exportDataAsync(name, outputConfig).get();
}
Name | Description |
name | String Required. The resource name of the dataset. |
outputConfig | OutputConfig Required. The desired output location. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
OperationCallable<ExportDataRequest,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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Name | Description |
request | ExportModelRequest The request object containing all of the parameters for the API call. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
ModelExportOutputConfig outputConfig = ModelExportOutputConfig.newBuilder().build();
autoMlClient.exportModelAsync(name, outputConfig).get();
}
Name | Description |
name | ModelName Required. The resource name of the model to export. |
outputConfig | ModelExportOutputConfig Required. The desired output location and configuration. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
ModelExportOutputConfig outputConfig = ModelExportOutputConfig.newBuilder().build();
autoMlClient.exportModelAsync(name, outputConfig).get();
}
Name | Description |
name | String Required. The resource name of the model to export. |
outputConfig | ModelExportOutputConfig Required. The desired output location and configuration. |
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
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:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
OperationCallable<ExportModelRequest,Empty,OperationMetadata> |
getAnnotationSpec(AnnotationSpecName name)
public final AnnotationSpec getAnnotationSpec(AnnotationSpecName name)
Gets an annotation spec.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
AnnotationSpecName name =
AnnotationSpecName.of("[PROJECT]", "[LOCATION]", "[DATASET]", "[ANNOTATION_SPEC]");
AnnotationSpec response = autoMlClient.getAnnotationSpec(name);
}
Name | Description |
name | AnnotationSpecName Required. The resource name of the annotation spec to retrieve. |
Type | Description |
AnnotationSpec |
getAnnotationSpec(GetAnnotationSpecRequest request)
public final AnnotationSpec getAnnotationSpec(GetAnnotationSpecRequest request)
Gets an annotation spec.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
GetAnnotationSpecRequest request =
GetAnnotationSpecRequest.newBuilder()
.setName(
AnnotationSpecName.of("[PROJECT]", "[LOCATION]", "[DATASET]", "[ANNOTATION_SPEC]")
.toString())
.build();
AnnotationSpec response = autoMlClient.getAnnotationSpec(request);
}
Name | Description |
request | GetAnnotationSpecRequest The request object containing all of the parameters for the API call. |
Type | Description |
AnnotationSpec |
getAnnotationSpec(String name)
public final AnnotationSpec getAnnotationSpec(String name)
Gets an annotation spec.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name =
AnnotationSpecName.of("[PROJECT]", "[LOCATION]", "[DATASET]", "[ANNOTATION_SPEC]")
.toString();
AnnotationSpec response = autoMlClient.getAnnotationSpec(name);
}
Name | Description |
name | String Required. The resource name of the annotation spec to retrieve. |
Type | Description |
AnnotationSpec |
getAnnotationSpecCallable()
public final UnaryCallable<GetAnnotationSpecRequest,AnnotationSpec> getAnnotationSpecCallable()
Gets an annotation spec.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
UnaryCallable<GetAnnotationSpecRequest,AnnotationSpec> |
getDataset(DatasetName name)
public final Dataset getDataset(DatasetName name)
Gets a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
Dataset response = autoMlClient.getDataset(name);
}
Name | Description |
name | DatasetName Required. The resource name of the dataset to retrieve. |
Type | Description |
Dataset |
getDataset(GetDatasetRequest request)
public final Dataset getDataset(GetDatasetRequest request)
Gets a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
GetDatasetRequest request =
GetDatasetRequest.newBuilder()
.setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
.build();
Dataset response = autoMlClient.getDataset(request);
}
Name | Description |
request | GetDatasetRequest The request object containing all of the parameters for the API call. |
Type | Description |
Dataset |
getDataset(String name)
public final Dataset getDataset(String name)
Gets a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
Dataset response = autoMlClient.getDataset(name);
}
Name | Description |
name | String Required. The resource name of the dataset to retrieve. |
Type | Description |
Dataset |
getDatasetCallable()
public final UnaryCallable<GetDatasetRequest,Dataset> getDatasetCallable()
Gets a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
UnaryCallable<GetDatasetRequest,Dataset> |
getHttpJsonOperationsClient()
public final OperationsClient getHttpJsonOperationsClient()
Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.
Type | Description |
OperationsClient |
getModel(GetModelRequest request)
public final Model getModel(GetModelRequest request)
Gets a model.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
GetModelRequest request =
GetModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
Model response = autoMlClient.getModel(request);
}
Name | Description |
request | GetModelRequest The request object containing all of the parameters for the API call. |
Type | Description |
Model |
getModel(ModelName name)
public final Model getModel(ModelName name)
Gets a model.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
Model response = autoMlClient.getModel(name);
}
Name | Description |
name | ModelName Required. Resource name of the model. |
Type | Description |
Model |
getModel(String name)
public final Model getModel(String name)
Gets a model.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
Model response = autoMlClient.getModel(name);
}
Name | Description |
name | String Required. Resource name of the model. |
Type | Description |
Model |
getModelCallable()
public final UnaryCallable<GetModelRequest,Model> getModelCallable()
Gets a model.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
UnaryCallable<GetModelRequest,Model> |
getModelEvaluation(GetModelEvaluationRequest request)
public final ModelEvaluation getModelEvaluation(GetModelEvaluationRequest request)
Gets a model evaluation.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
GetModelEvaluationRequest request =
GetModelEvaluationRequest.newBuilder()
.setName(
ModelEvaluationName.of("[PROJECT]", "[LOCATION]", "[MODEL]", "[MODEL_EVALUATION]")
.toString())
.build();
ModelEvaluation response = autoMlClient.getModelEvaluation(request);
}
Name | Description |
request | GetModelEvaluationRequest The request object containing all of the parameters for the API call. |
Type | Description |
ModelEvaluation |
getModelEvaluation(ModelEvaluationName name)
public final ModelEvaluation getModelEvaluation(ModelEvaluationName name)
Gets a model evaluation.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelEvaluationName name =
ModelEvaluationName.of("[PROJECT]", "[LOCATION]", "[MODEL]", "[MODEL_EVALUATION]");
ModelEvaluation response = autoMlClient.getModelEvaluation(name);
}
Name | Description |
name | ModelEvaluationName Required. Resource name for the model evaluation. |
Type | Description |
ModelEvaluation |
getModelEvaluation(String name)
public final ModelEvaluation getModelEvaluation(String name)
Gets a model evaluation.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name =
ModelEvaluationName.of("[PROJECT]", "[LOCATION]", "[MODEL]", "[MODEL_EVALUATION]")
.toString();
ModelEvaluation response = autoMlClient.getModelEvaluation(name);
}
Name | Description |
name | String Required. Resource name for the model evaluation. |
Type | Description |
ModelEvaluation |
getModelEvaluationCallable()
public final UnaryCallable<GetModelEvaluationRequest,ModelEvaluation> getModelEvaluationCallable()
Gets a model evaluation.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
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();
}
Type | Description |
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.
Type | Description |
OperationsClient |
getSettings()
public final AutoMlSettings getSettings()
Type | Description |
AutoMlSettings |
getStub()
public AutoMlStub getStub()
Type | Description |
AutoMlStub |
importDataAsync(DatasetName name, InputConfig inputConfig)
public final OperationFuture<Empty,OperationMetadata> importDataAsync(DatasetName name, InputConfig inputConfig)
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
InputConfig inputConfig = InputConfig.newBuilder().build();
autoMlClient.importDataAsync(name, inputConfig).get();
}
Name | Description |
name | DatasetName Required. Dataset name. Dataset must already exist. All imported annotations and examples will be added. |
inputConfig | InputConfig Required. The desired input location and its domain specific semantics, if any. |
Type | Description |
OperationFuture<Empty,OperationMetadata> |
importDataAsync(ImportDataRequest request)
public final OperationFuture<Empty,OperationMetadata> importDataAsync(ImportDataRequest request)
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ImportDataRequest request =
ImportDataRequest.newBuilder()
.setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
.setInputConfig(InputConfig.newBuilder().build())
.build();
autoMlClient.importDataAsync(request).get();
}
Name | Description |
request | ImportDataRequest The request object containing all of the parameters for the API call. |
Type | Description |
OperationFuture<Empty,OperationMetadata> |
importDataAsync(String name, InputConfig inputConfig)
public final OperationFuture<Empty,OperationMetadata> importDataAsync(String name, InputConfig inputConfig)
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
InputConfig inputConfig = InputConfig.newBuilder().build();
autoMlClient.importDataAsync(name, inputConfig).get();
}
Name | Description |
name | String Required. Dataset name. Dataset must already exist. All imported annotations and examples will be added. |
inputConfig | InputConfig Required. The desired input location and its domain specific semantics, if any. |
Type | Description |
OperationFuture<Empty,OperationMetadata> |
importDataCallable()
public final UnaryCallable<ImportDataRequest,Operation> importDataCallable()
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ImportDataRequest request =
ImportDataRequest.newBuilder()
.setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
.setInputConfig(InputConfig.newBuilder().build())
.build();
ApiFuture<Operation> future = autoMlClient.importDataCallable().futureCall(request);
// Do something.
future.get();
}
Type | Description |
UnaryCallable<ImportDataRequest,Operation> |
importDataOperationCallable()
public final OperationCallable<ImportDataRequest,Empty,OperationMetadata> importDataOperationCallable()
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ImportDataRequest request =
ImportDataRequest.newBuilder()
.setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
.setInputConfig(InputConfig.newBuilder().build())
.build();
OperationFuture<Empty, OperationMetadata> future =
autoMlClient.importDataOperationCallable().futureCall(request);
// Do something.
future.get();
}
Type | Description |
OperationCallable<ImportDataRequest,Empty,OperationMetadata> |
isShutdown()
public boolean isShutdown()
Type | Description |
boolean |
isTerminated()
public boolean isTerminated()
Type | Description |
boolean |
listDatasets(ListDatasetsRequest request)
public final AutoMlClient.ListDatasetsPagedResponse listDatasets(ListDatasetsRequest request)
Lists datasets in a project.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListDatasetsRequest request =
ListDatasetsRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
for (Dataset element : autoMlClient.listDatasets(request).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
request | ListDatasetsRequest The request object containing all of the parameters for the API call. |
Type | Description |
AutoMlClient.ListDatasetsPagedResponse |
listDatasets(LocationName parent)
public final AutoMlClient.ListDatasetsPagedResponse listDatasets(LocationName parent)
Lists datasets in a project.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
for (Dataset element : autoMlClient.listDatasets(parent).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
parent | LocationName Required. The resource name of the project from which to list datasets. |
Type | Description |
AutoMlClient.ListDatasetsPagedResponse |
listDatasets(String parent)
public final AutoMlClient.ListDatasetsPagedResponse listDatasets(String parent)
Lists datasets in a project.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
for (Dataset element : autoMlClient.listDatasets(parent).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
parent | String Required. The resource name of the project from which to list datasets. |
Type | Description |
AutoMlClient.ListDatasetsPagedResponse |
listDatasetsCallable()
public final UnaryCallable<ListDatasetsRequest,ListDatasetsResponse> listDatasetsCallable()
Lists datasets in a project.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListDatasetsRequest request =
ListDatasetsRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
while (true) {
ListDatasetsResponse response = autoMlClient.listDatasetsCallable().call(request);
for (Dataset element : response.getDatasetsList()) {
// doThingsWith(element);
}
String nextPageToken = response.getNextPageToken();
if (!Strings.isNullOrEmpty(nextPageToken)) {
request = request.toBuilder().setPageToken(nextPageToken).build();
} else {
break;
}
}
}
Type | Description |
UnaryCallable<ListDatasetsRequest,ListDatasetsResponse> |
listDatasetsPagedCallable()
public final UnaryCallable<ListDatasetsRequest,AutoMlClient.ListDatasetsPagedResponse> listDatasetsPagedCallable()
Lists datasets in a project.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListDatasetsRequest request =
ListDatasetsRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
ApiFuture<Dataset> future = autoMlClient.listDatasetsPagedCallable().futureCall(request);
// Do something.
for (Dataset element : future.get().iterateAll()) {
// doThingsWith(element);
}
}
Type | Description |
UnaryCallable<ListDatasetsRequest,ListDatasetsPagedResponse> |
listModelEvaluations(ListModelEvaluationsRequest request)
public final AutoMlClient.ListModelEvaluationsPagedResponse listModelEvaluations(ListModelEvaluationsRequest request)
Lists model evaluations.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListModelEvaluationsRequest request =
ListModelEvaluationsRequest.newBuilder()
.setParent(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
for (ModelEvaluation element : autoMlClient.listModelEvaluations(request).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
request | ListModelEvaluationsRequest The request object containing all of the parameters for the API call. |
Type | Description |
AutoMlClient.ListModelEvaluationsPagedResponse |
listModelEvaluations(ModelName parent, String filter)
public final AutoMlClient.ListModelEvaluationsPagedResponse listModelEvaluations(ModelName parent, String filter)
Lists model evaluations.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelName parent = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
String filter = "filter-1274492040";
for (ModelEvaluation element :
autoMlClient.listModelEvaluations(parent, filter).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
parent | ModelName Required. Resource name of the model to list the model evaluations for. If modelId is set as "-", this will list model evaluations from across all models of the parent location. |
filter | String Required. An expression for filtering the results of the request. * Some examples of using the filter are: * |
Type | Description |
AutoMlClient.ListModelEvaluationsPagedResponse |
listModelEvaluations(String parent, String filter)
public final AutoMlClient.ListModelEvaluationsPagedResponse listModelEvaluations(String parent, String filter)
Lists model evaluations.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String parent = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
String filter = "filter-1274492040";
for (ModelEvaluation element :
autoMlClient.listModelEvaluations(parent, filter).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
parent | String Required. Resource name of the model to list the model evaluations for. If modelId is set as "-", this will list model evaluations from across all models of the parent location. |
filter | String Required. An expression for filtering the results of the request. * Some examples of using the filter are: * |
Type | Description |
AutoMlClient.ListModelEvaluationsPagedResponse |
listModelEvaluationsCallable()
public final UnaryCallable<ListModelEvaluationsRequest,ListModelEvaluationsResponse> listModelEvaluationsCallable()
Lists model evaluations.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListModelEvaluationsRequest request =
ListModelEvaluationsRequest.newBuilder()
.setParent(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
while (true) {
ListModelEvaluationsResponse response =
autoMlClient.listModelEvaluationsCallable().call(request);
for (ModelEvaluation element : response.getModelEvaluationList()) {
// doThingsWith(element);
}
String nextPageToken = response.getNextPageToken();
if (!Strings.isNullOrEmpty(nextPageToken)) {
request = request.toBuilder().setPageToken(nextPageToken).build();
} else {
break;
}
}
}
Type | Description |
UnaryCallable<ListModelEvaluationsRequest,ListModelEvaluationsResponse> |
listModelEvaluationsPagedCallable()
public final UnaryCallable<ListModelEvaluationsRequest,AutoMlClient.ListModelEvaluationsPagedResponse> listModelEvaluationsPagedCallable()
Lists model evaluations.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListModelEvaluationsRequest request =
ListModelEvaluationsRequest.newBuilder()
.setParent(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
ApiFuture<ModelEvaluation> future =
autoMlClient.listModelEvaluationsPagedCallable().futureCall(request);
// Do something.
for (ModelEvaluation element : future.get().iterateAll()) {
// doThingsWith(element);
}
}
Type | Description |
UnaryCallable<ListModelEvaluationsRequest,ListModelEvaluationsPagedResponse> |
listModels(ListModelsRequest request)
public final AutoMlClient.ListModelsPagedResponse listModels(ListModelsRequest request)
Lists models.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListModelsRequest request =
ListModelsRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
for (Model element : autoMlClient.listModels(request).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
request | ListModelsRequest The request object containing all of the parameters for the API call. |
Type | Description |
AutoMlClient.ListModelsPagedResponse |
listModels(LocationName parent)
public final AutoMlClient.ListModelsPagedResponse listModels(LocationName parent)
Lists models.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
for (Model element : autoMlClient.listModels(parent).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
parent | LocationName Required. Resource name of the project, from which to list the models. |
Type | Description |
AutoMlClient.ListModelsPagedResponse |
listModels(String parent)
public final AutoMlClient.ListModelsPagedResponse listModels(String parent)
Lists models.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
for (Model element : autoMlClient.listModels(parent).iterateAll()) {
// doThingsWith(element);
}
}
Name | Description |
parent | String Required. Resource name of the project, from which to list the models. |
Type | Description |
AutoMlClient.ListModelsPagedResponse |
listModelsCallable()
public final UnaryCallable<ListModelsRequest,ListModelsResponse> listModelsCallable()
Lists models.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListModelsRequest request =
ListModelsRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
while (true) {
ListModelsResponse response = autoMlClient.listModelsCallable().call(request);
for (Model element : response.getModelList()) {
// doThingsWith(element);
}
String nextPageToken = response.getNextPageToken();
if (!Strings.isNullOrEmpty(nextPageToken)) {
request = request.toBuilder().setPageToken(nextPageToken).build();
} else {
break;
}
}
}
Type | Description |
UnaryCallable<ListModelsRequest,ListModelsResponse> |
listModelsPagedCallable()
public final UnaryCallable<ListModelsRequest,AutoMlClient.ListModelsPagedResponse> listModelsPagedCallable()
Lists models.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ListModelsRequest request =
ListModelsRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
ApiFuture<Model> future = autoMlClient.listModelsPagedCallable().futureCall(request);
// Do something.
for (Model element : future.get().iterateAll()) {
// doThingsWith(element);
}
}
Type | Description |
UnaryCallable<ListModelsRequest,ListModelsPagedResponse> |
shutdown()
public void shutdown()
shutdownNow()
public void shutdownNow()
undeployModelAsync(ModelName name)
public final OperationFuture<Empty,OperationMetadata> undeployModelAsync(ModelName name)
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
autoMlClient.undeployModelAsync(name).get();
}
Name | Description |
name | ModelName Required. Resource name of the model to undeploy. |
Type | Description |
OperationFuture<Empty,OperationMetadata> |
undeployModelAsync(UndeployModelRequest request)
public final OperationFuture<Empty,OperationMetadata> undeployModelAsync(UndeployModelRequest request)
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
UndeployModelRequest request =
UndeployModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
autoMlClient.undeployModelAsync(request).get();
}
Name | Description |
request | UndeployModelRequest The request object containing all of the parameters for the API call. |
Type | Description |
OperationFuture<Empty,OperationMetadata> |
undeployModelAsync(String name)
public final OperationFuture<Empty,OperationMetadata> undeployModelAsync(String name)
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
autoMlClient.undeployModelAsync(name).get();
}
Name | Description |
name | String Required. Resource name of the model to undeploy. |
Type | Description |
OperationFuture<Empty,OperationMetadata> |
undeployModelCallable()
public final UnaryCallable<UndeployModelRequest,Operation> undeployModelCallable()
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
UndeployModelRequest request =
UndeployModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
ApiFuture<Operation> future = autoMlClient.undeployModelCallable().futureCall(request);
// Do something.
future.get();
}
Type | Description |
UnaryCallable<UndeployModelRequest,Operation> |
undeployModelOperationCallable()
public final OperationCallable<UndeployModelRequest,Empty,OperationMetadata> undeployModelOperationCallable()
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.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
UndeployModelRequest request =
UndeployModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
OperationFuture<Empty, OperationMetadata> future =
autoMlClient.undeployModelOperationCallable().futureCall(request);
// Do something.
future.get();
}
Type | Description |
OperationCallable<UndeployModelRequest,Empty,OperationMetadata> |
updateDataset(Dataset dataset, FieldMask updateMask)
public final Dataset updateDataset(Dataset dataset, FieldMask updateMask)
Updates a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
Dataset dataset = Dataset.newBuilder().build();
FieldMask updateMask = FieldMask.newBuilder().build();
Dataset response = autoMlClient.updateDataset(dataset, updateMask);
}
Name | Description |
dataset | Dataset Required. The dataset which replaces the resource on the server. |
updateMask | FieldMask Required. The update mask applies to the resource. |
Type | Description |
Dataset |
updateDataset(UpdateDatasetRequest request)
public final Dataset updateDataset(UpdateDatasetRequest request)
Updates a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
UpdateDatasetRequest request =
UpdateDatasetRequest.newBuilder()
.setDataset(Dataset.newBuilder().build())
.setUpdateMask(FieldMask.newBuilder().build())
.build();
Dataset response = autoMlClient.updateDataset(request);
}
Name | Description |
request | UpdateDatasetRequest The request object containing all of the parameters for the API call. |
Type | Description |
Dataset |
updateDatasetCallable()
public final UnaryCallable<UpdateDatasetRequest,Dataset> updateDatasetCallable()
Updates a dataset.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
UpdateDatasetRequest request =
UpdateDatasetRequest.newBuilder()
.setDataset(Dataset.newBuilder().build())
.setUpdateMask(FieldMask.newBuilder().build())
.build();
ApiFuture<Dataset> future = autoMlClient.updateDatasetCallable().futureCall(request);
// Do something.
Dataset response = future.get();
}
Type | Description |
UnaryCallable<UpdateDatasetRequest,Dataset> |
updateModel(Model model, FieldMask updateMask)
public final Model updateModel(Model model, FieldMask updateMask)
Updates a model.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
Model model = Model.newBuilder().build();
FieldMask updateMask = FieldMask.newBuilder().build();
Model response = autoMlClient.updateModel(model, updateMask);
}
Name | Description |
model | Model Required. The model which replaces the resource on the server. |
updateMask | FieldMask Required. The update mask applies to the resource. |
Type | Description |
Model |
updateModel(UpdateModelRequest request)
public final Model updateModel(UpdateModelRequest request)
Updates a model.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
UpdateModelRequest request =
UpdateModelRequest.newBuilder()
.setModel(Model.newBuilder().build())
.setUpdateMask(FieldMask.newBuilder().build())
.build();
Model response = autoMlClient.updateModel(request);
}
Name | Description |
request | UpdateModelRequest The request object containing all of the parameters for the API call. |
Type | Description |
Model |
updateModelCallable()
public final UnaryCallable<UpdateModelRequest,Model> updateModelCallable()
Updates a model.
Sample code:
// This snippet has been automatically generated for illustrative purposes only.
// It may require modifications to work in your environment.
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
UpdateModelRequest request =
UpdateModelRequest.newBuilder()
.setModel(Model.newBuilder().build())
.setUpdateMask(FieldMask.newBuilder().build())
.build();
ApiFuture<Model> future = autoMlClient.updateModelCallable().futureCall(request);
// Do something.
Model response = future.get();
}
Type | Description |
UnaryCallable<UpdateModelRequest,Model> |