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Example 56 with Model

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");
    }
}
Also used : DeployModelRequest(com.google.cloud.automl.v1.DeployModelRequest) Empty(com.google.protobuf.Empty) ModelName(com.google.cloud.automl.v1.ModelName) OperationMetadata(com.google.cloud.automl.v1.OperationMetadata) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient)

Example 57 with Model

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...");
    }
}
Also used : Model(com.google.cloud.automl.v1.Model) TranslationModelMetadata(com.google.cloud.automl.v1.TranslationModelMetadata) OperationMetadata(com.google.cloud.automl.v1.OperationMetadata) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient) LocationName(com.google.cloud.automl.v1.LocationName)

Example 58 with Model

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);
}
Also used : DeployModelRequest(com.google.cloud.automl.v1.DeployModelRequest) PrintStream(java.io.PrintStream) ModelName(com.google.cloud.automl.v1.ModelName) Model(com.google.cloud.automl.v1.Model) ByteArrayOutputStream(java.io.ByteArrayOutputStream) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient) Before(org.junit.Before)

Example 59 with Model

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);
}
Also used : DeployModelRequest(com.google.cloud.automl.v1.DeployModelRequest) PrintStream(java.io.PrintStream) ModelName(com.google.cloud.automl.v1.ModelName) Model(com.google.cloud.automl.v1.Model) ByteArrayOutputStream(java.io.ByteArrayOutputStream) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient) Before(org.junit.Before)

Example 60 with Model

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);
}
Also used : DeployModelRequest(com.google.cloud.automl.v1.DeployModelRequest) PrintStream(java.io.PrintStream) ModelName(com.google.cloud.automl.v1.ModelName) Model(com.google.cloud.automl.v1.Model) ByteArrayOutputStream(java.io.ByteArrayOutputStream) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient) Before(org.junit.Before)

Aggregations

Test (org.junit.Test)51 Model (org.eclipse.xtext.valueconverter.bug250313.Model)30 AutoMlClient (com.google.cloud.automl.v1.AutoMlClient)25 ModelName (com.google.cloud.automl.v1.ModelName)24 Model (com.google.cloud.aiplatform.v1.Model)16 Model (com.google.cloud.automl.v1.Model)16 ICompositeNode (org.eclipse.xtext.nodemodel.ICompositeNode)16 LocationName (com.google.cloud.aiplatform.v1.LocationName)14 PipelineServiceClient (com.google.cloud.aiplatform.v1.PipelineServiceClient)14 PipelineServiceSettings (com.google.cloud.aiplatform.v1.PipelineServiceSettings)14 TrainingPipeline (com.google.cloud.aiplatform.v1.TrainingPipeline)14 InputDataConfig (com.google.cloud.aiplatform.v1.InputDataConfig)13 ModelContainerSpec (com.google.cloud.aiplatform.v1.ModelContainerSpec)13 OperationMetadata (com.google.cloud.automl.v1.OperationMetadata)12 FilterSplit (com.google.cloud.aiplatform.v1.FilterSplit)11 FractionSplit (com.google.cloud.aiplatform.v1.FractionSplit)11 PredefinedSplit (com.google.cloud.aiplatform.v1.PredefinedSplit)11 TimestampSplit (com.google.cloud.aiplatform.v1.TimestampSplit)11 Status (com.google.rpc.Status)11 Model (com.microsoft.z3.Model)11