Examples with Model com.google.cloud.automl.v1beta1.Model used on opensource projects

Example 91 with Model

use of com.google.cloud.automl.v1beta1.Model in project java-automl by googleapis.

the class GetModel method getModel.

// Get a model
static void getModel(String projectId, String modelId) throws IOException {
    // 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);
        Model model = client.getModel(modelFullId);
        // Display the model information.
        System.out.format("Model name: %s\n", model.getName());
        // To get the model id, you have to parse it out of the `name` field. As models Ids are
        // required for other methods.
        // Name Format: `projects/{project_id}/locations/{location_id}/models/{model_id}`
        String[] names = model.getName().split("/");
        String retrievedModelId = names[names.length - 1];
        System.out.format("Model id: %s\n", retrievedModelId);
        System.out.format("Model display name: %s\n", model.getDisplayName());
        System.out.println("Model create time:");
        System.out.format("\tseconds: %s\n", model.getCreateTime().getSeconds());
        System.out.format("\tnanos: %s\n", model.getCreateTime().getNanos());
        System.out.format("Model deployment state: %s\n", model.getDeploymentState());
    }
}

Example 92 with Model

use of com.google.cloud.automl.v1beta1.Model in project java-automl by googleapis.

the class LanguageSentimentAnalysisCreateModel 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");
        // Set model metadata.
        System.out.println(datasetId);
        TextSentimentModelMetadata metadata = TextSentimentModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextSentimentModelMetadata(metadata).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...");
    }
}

Example 93 with Model

use of com.google.cloud.automl.v1beta1.Model in project java-automl by googleapis.

the class LanguageEntityExtractionPredictTest 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);
}

Example 94 with Model

use of com.google.cloud.automl.v1beta1.Model in project java-automl by googleapis.

the class LanguageTextClassificationPredictTest 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);
}

Example 95 with Model

use of com.google.cloud.automl.v1beta1.Model in project java-automl by googleapis.

the class VisionClassificationPredictTest 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);
}