Examples with Model com.google.cloud.aiplatform.v1.Model used on opensource projects

Example 61 with Model

use of com.google.cloud.aiplatform.v1.Model in project java-automl by googleapis.

the class TablesGetModel method getModel.

// Demonstrates using the AutoML client to get model details.
public static void getModel(String projectId, String computeRegion, String modelId) throws IOException, StatusRuntimeException {
    // 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, computeRegion, modelId);
        // Get complete detail of the model.
        Model model = client.getModel(modelFullId);
        // Display the model information.
        System.out.format("Model name: %s%n", model.getName());
        System.out.format("Model Id: %s\n", model.getName().split("/")[model.getName().split("/").length - 1]);
        System.out.format("Model display name: %s%n", model.getDisplayName());
        System.out.format("Dataset Id: %s%n", model.getDatasetId());
        System.out.println("Tables Model Metadata: ");
        System.out.format("\tTraining budget: %s%n", model.getTablesModelMetadata().getTrainBudgetMilliNodeHours());
        System.out.format("\tTraining cost: %s%n", model.getTablesModelMetadata().getTrainBudgetMilliNodeHours());
        DateFormat dateFormat = new SimpleDateFormat("yyyy-MM-dd'T'HH:mm:ss.SSSZ");
        String createTime = dateFormat.format(new java.util.Date(model.getCreateTime().getSeconds() * 1000));
        System.out.format("Model create time: %s%n", createTime);
        System.out.format("Model deployment state: %s%n", model.getDeploymentState());
        // Get features of top importance
        for (TablesModelColumnInfo info : model.getTablesModelMetadata().getTablesModelColumnInfoList()) {
            System.out.format("Column: %s - Importance: %.2f%n", info.getColumnDisplayName(), info.getFeatureImportance());
        }
    }
}

Example 62 with Model

use of com.google.cloud.aiplatform.v1.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 63 with Model

use of com.google.cloud.aiplatform.v1.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 64 with Model

use of com.google.cloud.aiplatform.v1.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();
    }
}

Example 65 with Model

use of com.google.cloud.aiplatform.v1.Model in project java-automl by googleapis.

the class VisionObjectDetectionCreateModel 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.
        ImageObjectDetectionModelMetadata metadata = ImageObjectDetectionModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setImageObjectDetectionModelMetadata(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...");
    }
}