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...");
}
}
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...");
}
}
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...");
}
}
use of com.google.cloud.documentai.v1beta2.OperationMetadata in project java-automl by googleapis.
the class LanguageTextClassificationCreateDataset method createDataset.
// Create a dataset
static void createDataset(String projectId, 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");
// Specify the classification type
// Types:
// MultiLabel: Multiple labels are allowed for one example.
// MultiClass: At most one label is allowed per example.
ClassificationType classificationType = ClassificationType.MULTILABEL;
// Specify the text classification type for the dataset.
TextClassificationDatasetMetadata metadata = TextClassificationDatasetMetadata.newBuilder().setClassificationType(classificationType).build();
Dataset dataset = Dataset.newBuilder().setDisplayName(displayName).setTextClassificationDatasetMetadata(metadata).build();
OperationFuture<Dataset, OperationMetadata> future = client.createDatasetAsync(projectLocation, dataset);
Dataset createdDataset = future.get();
// Display the dataset information.
System.out.format("Dataset name: %s\n", createdDataset.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 = createdDataset.getName().split("/");
String datasetId = names[names.length - 1];
System.out.format("Dataset id: %s\n", datasetId);
}
}
use of com.google.cloud.documentai.v1beta2.OperationMetadata in project java-automl by googleapis.
the class VideoObjectTrackingCreateModel 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.
VideoObjectTrackingModelMetadata metadata = VideoObjectTrackingModelMetadata.newBuilder().build();
Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setVideoObjectTrackingModelMetadata(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...");
}
}
Aggregations