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

Example 36 with AutoMlClient

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

the class ListOperationStatus method listOperationStatus.

// Get the status of an operation
static void listOperationStatus(String projectId) throws IOException {
    // 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");
        // Create list operations request.
        ListOperationsRequest listrequest = ListOperationsRequest.newBuilder().setName(projectLocation.toString()).build();
        // List all the operations names available in the region by applying filter.
        for (Operation operation : client.getOperationsClient().listOperations(listrequest).iterateAll()) {
            System.out.println("Operation details:");
            System.out.format("\tName: %s\n", operation.getName());
            System.out.format("\tMetadata Type Url: %s\n", operation.getMetadata().getTypeUrl());
            System.out.format("\tDone: %s\n", operation.getDone());
            if (operation.hasResponse()) {
                System.out.format("\tResponse Type Url: %s\n", operation.getResponse().getTypeUrl());
            }
            if (operation.hasError()) {
                System.out.println("\tResponse:");
                System.out.format("\t\tError code: %s\n", operation.getError().getCode());
                System.out.format("\t\tError message: %s\n\n", operation.getError().getMessage());
            }
        }
    }
}

Example 37 with AutoMlClient

use of com.google.cloud.automl.v1beta1.AutoMlClient 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 38 with AutoMlClient

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

the class VisionClassificationCreateModel 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.
        ImageClassificationModelMetadata metadata = ImageClassificationModelMetadata.newBuilder().setTrainBudgetMilliNodeHours(24000).build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setImageClassificationModelMetadata(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 39 with AutoMlClient

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

the class ModelApi method getOperationStatus.

// [END automl_translate_list_models]
// [START automl_translate_get_operation_status]
/**
 * Demonstrates using the AutoML client to get operation status.
 *
 * @param operationFullId Full name of a operation. For example, the name of your operation is
 *     projects/[projectId]/locations/us-central1/operations/[operationId].
 * @throws IOException on Input/Output errors.
 */
private static void getOperationStatus(String operationFullId) throws IOException {
    // Instantiates a client
    try (AutoMlClient client = AutoMlClient.create()) {
        // Get the latest state of a long-running operation.
        Operation response = client.getOperationsClient().getOperation(operationFullId);
        System.out.println(String.format("Operation status: %s", response));
    }
}

Example 40 with AutoMlClient

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

the class ClassificationDeployModelNodeCount method classificationDeployModelNodeCount.

// Deploy a model with a specified node count
static void classificationDeployModelNodeCount(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);
        // Set how many nodes the model is deployed on
        ImageClassificationModelDeploymentMetadata deploymentMetadata = ImageClassificationModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
        DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).setImageClassificationModelDeploymentMetadata(deploymentMetadata).build();
        // Deploy the model
        OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
        future.get();
        System.out.println("Model deployment on 2 nodes finished");
    }
}