use of com.google.cloud.aiplatform.v1.LocationName in project java-automl by googleapis.
the class LanguageSentimentAnalysisCreateDataset 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 text classification type for the dataset.
TextSentimentDatasetMetadata metadata = TextSentimentDatasetMetadata.newBuilder().setSentimentMax(// Possible max sentiment score: 1-10
4).build();
Dataset dataset = Dataset.newBuilder().setDisplayName(displayName).setTextSentimentDatasetMetadata(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.aiplatform.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...");
}
}
use of com.google.cloud.aiplatform.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();
}
}
use of com.google.cloud.aiplatform.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...");
}
}
use of com.google.cloud.aiplatform.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()));
}
}
}
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