Examples with OperationMetadata com.google.cloud.documentai.v1beta2.OperationMetadata used on opensource projects

Example 36 with OperationMetadata

use of com.google.cloud.documentai.v1beta2.OperationMetadata 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 37 with OperationMetadata

use of com.google.cloud.documentai.v1beta2.OperationMetadata in project java-automl by googleapis.

the class TablesCreateModel method createModel.

// Create a model
static void createModel(String projectId, String datasetId, String tableSpecId, String columnSpecId, 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");
        // Get the complete path of the column.
        ColumnSpecName columnSpecName = ColumnSpecName.of(projectId, "us-central1", datasetId, tableSpecId, columnSpecId);
        // Build the get column spec.
        ColumnSpec targetColumnSpec = ColumnSpec.newBuilder().setName(columnSpecName.toString()).build();
        // Set model metadata.
        TablesModelMetadata metadata = TablesModelMetadata.newBuilder().setTargetColumnSpec(targetColumnSpec).setTrainBudgetMilliNodeHours(24000).build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTablesModelMetadata(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 38 with OperationMetadata

use of com.google.cloud.documentai.v1beta2.OperationMetadata in project java-automl by googleapis.

the class VideoClassificationCreateModel 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.
        VideoClassificationModelMetadata metadata = VideoClassificationModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setVideoClassificationModelMetadata(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...");
    }
}