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GitHub Repository | Product Reference | REST Documentation | RPC Documentation |
Service Description: AutoML Server API.
The resource names are assigned by the server. The server never reuses names that it has created after the resources with those names are deleted.
An ID of a resource is the last element of the item's resource name. For
projects/{project_id}/locations/{location_id}/datasets/{dataset_id}
, then the id for the item
is {dataset_id}
.
Currently the only supported location_id
is "us-central1".
On any input that is documented to expect a string parameter in snake_case or dash-case, either of those cases is accepted.
This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
Dataset response = autoMlClient.getDataset(name);
}
Note: close() needs to be called on the AutoMlClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().
Method | Description | Method Variants |
---|---|---|
CreateDataset |
Creates a dataset. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
GetDataset |
Gets a dataset. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
ListDatasets |
Lists datasets in a project. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
UpdateDataset |
Updates a dataset. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
DeleteDataset |
Deletes a dataset and all of its contents. Returns empty response in the response field when it completes, and |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
ImportData |
Imports data into a dataset. For Tables this method can only be called on an empty Dataset. For Tables:
|
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
ExportData |
Exports dataset's data to the provided output location. Returns an empty response in the response field when it completes. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
GetAnnotationSpec |
Gets an annotation spec. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
CreateModel |
Creates a model. Returns a Model in the response field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
GetModel |
Gets a model. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
ListModels |
Lists models. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
DeleteModel |
Deletes a model. Returns |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
UpdateModel |
Updates a model. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
DeployModel |
Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing node_number) will reset the deployment state without pausing the model's availability. Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage deployment automatically. Returns an empty response in the response field when it completes. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
UndeployModel |
Undeploys a model. If the model is not deployed this method has no effect. Only applicable for Text Classification, Image Object Detection and Tables; all other domains manage deployment automatically. Returns an empty response in the response field when it completes. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
ExportModel |
Exports a trained, "export-able", model to a user specified Google Cloud Storage location. A model is considered export-able if and only if it has an export format defined for it in ModelExportOutputConfig. Returns an empty response in the response field when it completes. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
GetModelEvaluation |
Gets a model evaluation. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
ListModelEvaluations |
Lists model evaluations. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return 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 and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
AutoMlSettings autoMlSettings =
AutoMlSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);
To customize the endpoint:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
AutoMlSettings autoMlSettings = AutoMlSettings.newBuilder().setEndpoint(myEndpoint).build();
AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);
To use REST (HTTP1.1/JSON) transport (instead of gRPC) for sending and receiving requests over the wire:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
AutoMlSettings autoMlSettings = AutoMlSettings.newHttpJsonBuilder().build();
AutoMlClient autoMlClient = AutoMlClient.create(autoMlSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
Static Methods
create()
public static final AutoMlClient create()
Constructs an instance of AutoMlClient with default settings.
Returns | |
---|---|
Type | Description |
AutoMlClient |
Exceptions | |
---|---|
Type | Description |
IOException |
create(AutoMlSettings settings)
public static final AutoMlClient create(AutoMlSettings settings)
Constructs an instance of AutoMlClient, using the given settings. The channels are created based on the settings passed in, or defaults for any settings that are not set.
Parameter | |
---|---|
Name | Description |
settings |
AutoMlSettings |
Returns | |
---|---|
Type | Description |
AutoMlClient |
Exceptions | |
---|---|
Type | Description |
IOException |
create(AutoMlStub stub)
public static final AutoMlClient create(AutoMlStub stub)
Constructs an instance of AutoMlClient, using the given stub for making calls. This is for advanced usage - prefer using create(AutoMlSettings).
Parameter | |
---|---|
Name | Description |
stub |
AutoMlStub |
Returns | |
---|---|
Type | Description |
AutoMlClient |
Constructors
AutoMlClient(AutoMlSettings settings)
protected AutoMlClient(AutoMlSettings settings)
Constructs an instance of AutoMlClient, using the given settings. This is protected so that it is easy to make a subclass, but otherwise, the static factory methods should be preferred.
Parameter | |
---|---|
Name | Description |
settings |
AutoMlSettings |
AutoMlClient(AutoMlStub stub)
protected AutoMlClient(AutoMlStub stub)
Parameter | |
---|---|
Name | Description |
stub |
AutoMlStub |
Methods
awaitTermination(long duration, TimeUnit unit)
public boolean awaitTermination(long duration, TimeUnit unit)
Parameters | |
---|---|
Name | Description |
duration |
long |
unit |
TimeUnit |
Returns | |
---|---|
Type | Description |
boolean |
Exceptions | |
---|---|
Type | Description |
InterruptedException |
close()
public final void close()
createDatasetAsync(CreateDatasetRequest request)
public final OperationFuture<Dataset,OperationMetadata> createDatasetAsync(CreateDatasetRequest request)
Creates a dataset.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
CreateDatasetRequest request =
CreateDatasetRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setDataset(Dataset.newBuilder().build())
.build();
Dataset response = autoMlClient.createDatasetAsync(request).get();
}
Parameter | |
---|---|
Name | Description |
request |
CreateDatasetRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
OperationFuture<Dataset,OperationMetadata> |
createDatasetAsync(LocationName parent, Dataset dataset)
public final OperationFuture<Dataset,OperationMetadata> createDatasetAsync(LocationName parent, Dataset dataset)
Creates a dataset.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
Dataset dataset = Dataset.newBuilder().build();
Dataset response = autoMlClient.createDatasetAsync(parent, dataset).get();
}
Parameters | |
---|---|
Name | Description |
parent |
LocationName Required. The resource name of the project to create the dataset for. |
dataset |
Dataset Required. The dataset to create. |
Returns | |
---|---|
Type | Description |
OperationFuture<Dataset,OperationMetadata> |
createDatasetAsync(String parent, Dataset dataset)
public final OperationFuture<Dataset,OperationMetadata> createDatasetAsync(String parent, Dataset dataset)
Creates a dataset.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
Dataset dataset = Dataset.newBuilder().build();
Dataset response = autoMlClient.createDatasetAsync(parent, dataset).get();
}
Parameters | |
---|---|
Name | Description |
parent |
String Required. The resource name of the project to create the dataset for. |
dataset |
Dataset Required. The dataset to create. |
Returns | |
---|---|
Type | Description |
OperationFuture<Dataset,OperationMetadata> |
createDatasetCallable()
public final UnaryCallable<CreateDatasetRequest,Operation> createDatasetCallable()
Creates a dataset.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
CreateDatasetRequest request =
CreateDatasetRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setDataset(Dataset.newBuilder().build())
.build();
ApiFuture<Operation> future = autoMlClient.createDatasetCallable().futureCall(request);
// Do something.
Operation response = future.get();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<CreateDatasetRequest,Operation> |
createDatasetOperationCallable()
public final OperationCallable<CreateDatasetRequest,Dataset,OperationMetadata> createDatasetOperationCallable()
Creates a dataset.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
CreateDatasetRequest request =
CreateDatasetRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setDataset(Dataset.newBuilder().build())
.build();
OperationFuture<Dataset, OperationMetadata> future =
autoMlClient.createDatasetOperationCallable().futureCall(request);
// Do something.
Dataset response = future.get();
}
Returns | |
---|---|
Type | Description |
OperationCallable<CreateDatasetRequest,Dataset,OperationMetadata> |
createModelAsync(CreateModelRequest request)
public final OperationFuture<Model,OperationMetadata> createModelAsync(CreateModelRequest request)
Creates a model. Returns a Model in the response field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
CreateModelRequest request =
CreateModelRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setModel(Model.newBuilder().build())
.build();
Model response = autoMlClient.createModelAsync(request).get();
}
Parameter | |
---|---|
Name | Description |
request |
CreateModelRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
OperationFuture<Model,OperationMetadata> |
createModelAsync(LocationName parent, Model model)
public final OperationFuture<Model,OperationMetadata> createModelAsync(LocationName parent, Model model)
Creates a model. Returns a Model in the response field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
LocationName parent = LocationName.of("[PROJECT]", "[LOCATION]");
Model model = Model.newBuilder().build();
Model response = autoMlClient.createModelAsync(parent, model).get();
}
Parameters | |
---|---|
Name | Description |
parent |
LocationName Required. Resource name of the parent project where the model is being created. |
model |
Model Required. The model to create. |
Returns | |
---|---|
Type | Description |
OperationFuture<Model,OperationMetadata> |
createModelAsync(String parent, Model model)
public final OperationFuture<Model,OperationMetadata> createModelAsync(String parent, Model model)
Creates a model. Returns a Model in the response field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String parent = LocationName.of("[PROJECT]", "[LOCATION]").toString();
Model model = Model.newBuilder().build();
Model response = autoMlClient.createModelAsync(parent, model).get();
}
Parameters | |
---|---|
Name | Description |
parent |
String Required. Resource name of the parent project where the model is being created. |
model |
Model Required. The model to create. |
Returns | |
---|---|
Type | Description |
OperationFuture<Model,OperationMetadata> |
createModelCallable()
public final UnaryCallable<CreateModelRequest,Operation> createModelCallable()
Creates a model. Returns a Model in the response field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
CreateModelRequest request =
CreateModelRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setModel(Model.newBuilder().build())
.build();
ApiFuture<Operation> future = autoMlClient.createModelCallable().futureCall(request);
// Do something.
Operation response = future.get();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<CreateModelRequest,Operation> |
createModelOperationCallable()
public final OperationCallable<CreateModelRequest,Model,OperationMetadata> createModelOperationCallable()
Creates a model. Returns a Model in the response field when it completes. When you create a model, several model evaluations are created for it: a global evaluation, and one evaluation for each annotation spec.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
CreateModelRequest request =
CreateModelRequest.newBuilder()
.setParent(LocationName.of("[PROJECT]", "[LOCATION]").toString())
.setModel(Model.newBuilder().build())
.build();
OperationFuture<Model, OperationMetadata> future =
autoMlClient.createModelOperationCallable().futureCall(request);
// Do something.
Model response = future.get();
}
Returns | |
---|---|
Type | Description |
OperationCallable<CreateModelRequest,Model,OperationMetadata> |
deleteDatasetAsync(DatasetName name)
public final OperationFuture<Empty,OperationMetadata> deleteDatasetAsync(DatasetName name)
Deletes a dataset and all of its contents. Returns empty response in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DatasetName name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]");
autoMlClient.deleteDatasetAsync(name).get();
}
Parameter | |
---|---|
Name | Description |
name |
DatasetName Required. The resource name of the dataset to delete. |
Returns | |
---|---|
Type | Description |
OperationFuture<Empty,OperationMetadata> |
deleteDatasetAsync(DeleteDatasetRequest request)
public final OperationFuture<Empty,OperationMetadata> deleteDatasetAsync(DeleteDatasetRequest request)
Deletes a dataset and all of its contents. Returns empty response in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeleteDatasetRequest request =
DeleteDatasetRequest.newBuilder()
.setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
.build();
autoMlClient.deleteDatasetAsync(request).get();
}
Parameter | |
---|---|
Name | Description |
request |
DeleteDatasetRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
OperationFuture<Empty,OperationMetadata> |
deleteDatasetAsync(String name)
public final OperationFuture<Empty,OperationMetadata> deleteDatasetAsync(String name)
Deletes a dataset and all of its contents. Returns empty response in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString();
autoMlClient.deleteDatasetAsync(name).get();
}
Parameter | |
---|---|
Name | Description |
name |
String Required. The resource name of the dataset to delete. |
Returns | |
---|---|
Type | Description |
OperationFuture<Empty,OperationMetadata> |
deleteDatasetCallable()
public final UnaryCallable<DeleteDatasetRequest,Operation> deleteDatasetCallable()
Deletes a dataset and all of its contents. Returns empty response in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeleteDatasetRequest request =
DeleteDatasetRequest.newBuilder()
.setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
.build();
ApiFuture<Operation> future = autoMlClient.deleteDatasetCallable().futureCall(request);
// Do something.
future.get();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<DeleteDatasetRequest,Operation> |
deleteDatasetOperationCallable()
public final OperationCallable<DeleteDatasetRequest,Empty,OperationMetadata> deleteDatasetOperationCallable()
Deletes a dataset and all of its contents. Returns empty response in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeleteDatasetRequest request =
DeleteDatasetRequest.newBuilder()
.setName(DatasetName.of("[PROJECT]", "[LOCATION]", "[DATASET]").toString())
.build();
OperationFuture<Empty, OperationMetadata> future =
autoMlClient.deleteDatasetOperationCallable().futureCall(request);
// Do something.
future.get();
}
Returns | |
---|---|
Type | Description |
OperationCallable<DeleteDatasetRequest,Empty,OperationMetadata> |
deleteModelAsync(DeleteModelRequest request)
public final OperationFuture<Empty,OperationMetadata> deleteModelAsync(DeleteModelRequest request)
Deletes a model. Returns google.protobuf.Empty
in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeleteModelRequest request =
DeleteModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
autoMlClient.deleteModelAsync(request).get();
}
Parameter | |
---|---|
Name | Description |
request |
DeleteModelRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
OperationFuture<Empty,OperationMetadata> |
deleteModelAsync(ModelName name)
public final OperationFuture<Empty,OperationMetadata> deleteModelAsync(ModelName name)
Deletes a model. Returns google.protobuf.Empty
in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
autoMlClient.deleteModelAsync(name).get();
}
Parameter | |
---|---|
Name | Description |
name |
ModelName Required. Resource name of the model being deleted. |
Returns | |
---|---|
Type | Description |
OperationFuture<Empty,OperationMetadata> |
deleteModelAsync(String name)
public final OperationFuture<Empty,OperationMetadata> deleteModelAsync(String name)
Deletes a model. Returns google.protobuf.Empty
in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
String name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
autoMlClient.deleteModelAsync(name).get();
}
Parameter | |
---|---|
Name | Description |
name |
String Required. Resource name of the model being deleted. |
Returns | |
---|---|
Type | Description |
OperationFuture<Empty,OperationMetadata> |
deleteModelCallable()
public final UnaryCallable<DeleteModelRequest,Operation> deleteModelCallable()
Deletes a model. Returns google.protobuf.Empty
in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeleteModelRequest request =
DeleteModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
ApiFuture<Operation> future = autoMlClient.deleteModelCallable().futureCall(request);
// Do something.
future.get();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<DeleteModelRequest,Operation> |
deleteModelOperationCallable()
public final OperationCallable<DeleteModelRequest,Empty,OperationMetadata> deleteModelOperationCallable()
Deletes a model. Returns google.protobuf.Empty
in the
response field when it completes, and delete_details
in the metadata field.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeleteModelRequest request =
DeleteModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
OperationFuture<Empty, OperationMetadata> future =
autoMlClient.deleteModelOperationCallable().futureCall(request);
// Do something.
future.get();
}
Returns | |
---|---|
Type | Description |
OperationCallable<DeleteModelRequest,Empty,OperationMetadata> |
deployModelAsync(DeployModelRequest request)
public final OperationFuture<Empty,OperationMetadata> deployModelAsync(DeployModelRequest request)
Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing node_number) will reset the deployment state without pausing the model's availability.
Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage deployment automatically.
Returns an empty response in the response field when it completes.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
DeployModelRequest request =
DeployModelRequest.newBuilder()
.setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
.build();
autoMlClient.deployModelAsync(request).get();
}
Parameter | |
---|---|
Name | Description |
request |
DeployModelRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
OperationFuture<Empty,OperationMetadata> |
deployModelAsync(ModelName name)
public final OperationFuture<Empty,OperationMetadata> deployModelAsync(ModelName name)
Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing node_number) will reset the deployment state without pausing the model's availability.
Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage deployment automatically.
Returns an empty response in the response field when it completes.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (AutoMlClient autoMlClient = AutoMlClient.create()) {
ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
autoMlClient.deployModelAsync(name).get();
}
Parameter | |
---|---|
Name | Description |
name |
ModelName Required. Resource name of the model to deploy. |
Returns | |
---|---|
Type | Description |
OperationFuture<Empty,OperationMetadata> |
deployModelAsync(String name)
public final OperationFuture<Empty,OperationMetadata> deployModelAsync(String name)
Deploys a model. If a model is already deployed, deploying it with the same parameters has no effect. Deploying with different parametrs (as e.g. changing node_number) will reset the deployment state without pausing the model's availability.
Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage deployment automatically.
Returns an empty response in the response field when it completes.
Sample code:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
try (