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

Example 51 with Model

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

the class UndeployModel method undeployModel.

// Undeploy a model from prediction
static void undeployModel(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);
        UndeployModelRequest request = UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
        OperationFuture<Empty, OperationMetadata> future = client.undeployModelAsync(request);
        future.get();
        System.out.println("Model undeployment finished");
    }
}

Example 52 with Model

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

the class LanguageEntityExtractionCreateModel 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.
        TextExtractionModelMetadata metadata = TextExtractionModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextExtractionModelMetadata(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 53 with Model

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

the class LanguageTextClassificationCreateModel 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.
        TextClassificationModelMetadata metadata = TextClassificationModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTextClassificationModelMetadata(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 54 with Model

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

the class ClassificationUndeployModel method classificationUndeployModel.

// Deploy a model
static void classificationUndeployModel(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);
        // Build deploy model request.
        UndeployModelRequest undeployModelRequest = UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
        // Deploy a model with the deploy model request.
        OperationFuture<Empty, OperationMetadata> future = client.undeployModelAsync(undeployModelRequest);
        future.get();
        // Display the deployment details of model.
        System.out.println("Model undeploy finished");
    }
}

Example 55 with Model

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

the class ModelApi method createModel.

// [START automl_vision_create_model]
/**
 * Demonstrates using the AutoML client to create a model.
 *
 * @param projectId the Id of the project.
 * @param computeRegion the Region name.
 * @param dataSetId the Id of the dataset to which model is created.
 * @param modelName the Name of the model.
 * @param trainBudget the Budget for training the model.
 */
static void createModel(String projectId, String computeRegion, String dataSetId, String modelName, String trainBudget) {
    // Instantiates a client
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, computeRegion);
        // Set model metadata.
        ImageClassificationModelMetadata imageClassificationModelMetadata = Long.valueOf(trainBudget) == 0 ? ImageClassificationModelMetadata.newBuilder().build() : ImageClassificationModelMetadata.newBuilder().setTrainBudget(Long.valueOf(trainBudget)).build();
        // Set model name and model metadata for the image dataset.
        Model myModel = Model.newBuilder().setDisplayName(modelName).setDatasetId(dataSetId).setImageClassificationModelMetadata(imageClassificationModelMetadata).build();
        // Create a model with the model metadata in the region.
        OperationFuture<Model, OperationMetadata> response = client.createModelAsync(projectLocation, myModel);
        System.out.println(String.format("Training operation name: %s", response.getInitialFuture().get().getName()));
        System.out.println("Training started...");
    } catch (IOException | ExecutionException | InterruptedException e) {
        e.printStackTrace();
    }
}