Examples with LocationName com.google.cloud.bigquery.connection.v1.LocationName used on opensource projects

Example 61 with LocationName

use of com.google.cloud.bigquery.connection.v1.LocationName 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 62 with LocationName

use of com.google.cloud.bigquery.connection.v1.LocationName 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 63 with LocationName

use of com.google.cloud.bigquery.connection.v1.LocationName 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...");
    }
}

Example 64 with LocationName

use of com.google.cloud.bigquery.connection.v1.LocationName in project java-automl by googleapis.

the class ModelApi method listModels.

// [START automl_translate_list_models]
/**
 * Demonstrates using the AutoML client to list all models.
 *
 * @param projectId the Id of the project.
 * @param computeRegion the Region name.
 * @param filter the filter expression.
 * @throws IOException on Input/Output errors.
 */
public static void listModels(String projectId, String computeRegion, String filter) throws IOException {
    // Instantiates a client
    try (AutoMlClient client = AutoMlClient.create()) {
        // A resource that represents Google Cloud Platform location.
        LocationName projectLocation = LocationName.of(projectId, computeRegion);
        // Create list models request.
        ListModelsRequest listModlesRequest = ListModelsRequest.newBuilder().setParent(projectLocation.toString()).setFilter(filter).build();
        // List all the models available in the region by applying filter.
        System.out.println("List of models:");
        for (Model model : client.listModels(listModlesRequest).iterateAll()) {
            // Display the model information.
            System.out.println(String.format("Model name: %s", model.getName()));
            System.out.println(String.format("Model id: %s", model.getName().split("/")[model.getName().split("/").length - 1]));
            System.out.println(String.format("Model display name: %s", model.getDisplayName()));
            System.out.println("Model create time:");
            System.out.println(String.format("\tseconds: %s", model.getCreateTime().getSeconds()));
            System.out.println(String.format("\tnanos: %s", model.getCreateTime().getNanos()));
            System.out.println(String.format("Model deployment state: %s", model.getDeploymentState()));
        }
    }
}

Example 65 with LocationName

use of com.google.cloud.bigquery.connection.v1.LocationName in project java-automl by googleapis.

the class ListDatasets method listDatasets.

// List the datasets
static void listDatasets(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");
        ListDatasetsRequest request = ListDatasetsRequest.newBuilder().setParent(projectLocation.toString()).build();
        // List all the datasets available in the region by applying filter.
        System.out.println("List of datasets:");
        for (Dataset dataset : client.listDatasets(request).iterateAll()) {
            // Display the dataset information
            System.out.format("\nDataset name: %s\n", dataset.getName());
            // To get the dataset id, you have to parse it out of the `name` field. As dataset Ids are
            // required for other methods.
            // Name Form: `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`
            String[] names = dataset.getName().split("/");
            String retrievedDatasetId = names[names.length - 1];
            System.out.format("Dataset id: %s\n", retrievedDatasetId);
            System.out.format("Dataset display name: %s\n", dataset.getDisplayName());
            System.out.println("Dataset create time:");
            System.out.format("\tseconds: %s\n", dataset.getCreateTime().getSeconds());
            System.out.format("\tnanos: %s\n", dataset.getCreateTime().getNanos());
            // [END automl_language_sentiment_analysis_list_datasets]
            // [END automl_language_text_classification_list_datasets]
            // [END automl_translate_list_datasets]
            // [END automl_vision_classification_list_datasets]
            // [END automl_vision_object_detection_list_datasets]
            System.out.format("Text extraction dataset metadata: %s\n", dataset.getTextExtractionDatasetMetadata());
            // [END automl_language_entity_extraction_list_datasets]
            // [START automl_language_sentiment_analysis_list_datasets]
            System.out.format("Text sentiment dataset metadata: %s\n", dataset.getTextSentimentDatasetMetadata());
            // [END automl_language_sentiment_analysis_list_datasets]
            // [START automl_language_text_classification_list_datasets]
            System.out.format("Text classification dataset metadata: %s\n", dataset.getTextClassificationDatasetMetadata());
            // [END automl_language_text_classification_list_datasets]
            // [START automl_translate_list_datasets]
            System.out.println("Translation dataset metadata:");
            System.out.format("\tSource language code: %s\n", dataset.getTranslationDatasetMetadata().getSourceLanguageCode());
            System.out.format("\tTarget language code: %s\n", dataset.getTranslationDatasetMetadata().getTargetLanguageCode());
            // [END automl_translate_list_datasets]
            // [START automl_vision_classification_list_datasets]
            System.out.format("Image classification dataset metadata: %s\n", dataset.getImageClassificationDatasetMetadata());
            // [END automl_vision_classification_list_datasets]
            // [START automl_vision_object_detection_list_datasets]
            System.out.format("Image object detection dataset metadata: %s\n", dataset.getImageObjectDetectionDatasetMetadata());
        // [START automl_language_entity_extraction_list_datasets]
        // [START automl_language_sentiment_analysis_list_datasets]
        // [START automl_language_text_classification_list_datasets]
        // [START automl_translate_list_datasets]
        // [START automl_vision_classification_list_datasets]
        }
    }
}