use of com.google.cloud.automl.v1.Model in project java-automl by googleapis.
the class DeployModel method deployModel.
// Deploy a model for prediction
static void deployModel(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// Get the full path of the model.
ModelName modelFullId = ModelName.of(projectId, "us-central1", modelId);
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
future.get();
System.out.println("Model deployment finished");
}
}
use of com.google.cloud.automl.v1.Model in project java-automl by googleapis.
the class TranslateCreateModel method createModel.
// Create a model
static void createModel(String projectId, String datasetId, String displayName) throws IOException, ExecutionException, InterruptedException {
// the "close" method on the client to safely clean up any remaining background resources.
try (AutoMlClient client = AutoMlClient.create()) {
// A resource that represents Google Cloud Platform location.
LocationName projectLocation = LocationName.of(projectId, "us-central1");
TranslationModelMetadata translationModelMetadata = TranslationModelMetadata.newBuilder().build();
Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTranslationModelMetadata(translationModelMetadata).build();
// Create a model with the model metadata in the region.
OperationFuture<Model, OperationMetadata> future = client.createModelAsync(projectLocation, model);
// OperationFuture.get() will block until the model is created, which may take several hours.
// You can use OperationFuture.getInitialFuture to get a future representing the initial
// response to the request, which contains information while the operation is in progress.
System.out.format("Training operation name: %s\n", future.getInitialFuture().get().getName());
System.out.println("Training started...");
}
}
use of com.google.cloud.automl.v1.Model in project java-automl by googleapis.
the class TablesPredictTest method setUp.
@Before
public void setUp() throws IOException, ExecutionException, InterruptedException {
// Verify that the model is deployed for prediction
try (AutoMlClient client = AutoMlClient.create()) {
ModelName modelFullId = ModelName.of(PROJECT_ID, "us-central1", MODEL_ID);
Model model = client.getModel(modelFullId);
if (model.getDeploymentState() == Model.DeploymentState.UNDEPLOYED) {
// Deploy the model if not deployed
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
client.deployModelAsync(request).get();
}
}
bout = new ByteArrayOutputStream();
out = new PrintStream(bout);
originalPrintStream = System.out;
System.setOut(out);
}
use of com.google.cloud.automl.v1.Model in project java-automl by googleapis.
the class LanguageSentimentAnalysisPredictTest method setUp.
@Before
public void setUp() throws IOException, ExecutionException, InterruptedException {
// Verify that the model is deployed for prediction
try (AutoMlClient client = AutoMlClient.create()) {
ModelName modelFullId = ModelName.of(PROJECT_ID, "us-central1", MODEL_ID);
Model model = client.getModel(modelFullId);
if (model.getDeploymentState() == Model.DeploymentState.UNDEPLOYED) {
// Deploy the model if not deployed
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
client.deployModelAsync(request).get();
}
}
bout = new ByteArrayOutputStream();
out = new PrintStream(bout);
originalPrintStream = System.out;
System.setOut(out);
}
use of com.google.cloud.automl.v1.Model in project java-automl by googleapis.
the class VisionObjectDetectionPredictTest method setUp.
@Before
public void setUp() throws IOException, ExecutionException, InterruptedException {
// Verify that the model is deployed for prediction
try (AutoMlClient client = AutoMlClient.create()) {
ModelName modelFullId = ModelName.of(PROJECT_ID, "us-central1", MODEL_ID);
Model model = client.getModel(modelFullId);
if (model.getDeploymentState() == Model.DeploymentState.UNDEPLOYED) {
// Deploy the model if not deployed
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
client.deployModelAsync(request).get();
}
}
bout = new ByteArrayOutputStream();
out = new PrintStream(bout);
originalPrintStream = System.out;
System.setOut(out);
}
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