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Example 56 with Model

use of com.google.cloud.automl.v1beta1.Model in project java-automl by googleapis.

the class ObjectDetectionDeployModelNodeCount method objectDetectionDeployModelNodeCount.

static void objectDetectionDeployModelNodeCount(String projectId, String modelId) throws IOException, ExecutionException, InterruptedException {
    // 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, "us-central1", modelId);
        // Set how many nodes the model is deployed on
        ImageObjectDetectionModelDeploymentMetadata deploymentMetadata = ImageObjectDetectionModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
        DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).setImageObjectDetectionModelDeploymentMetadata(deploymentMetadata).build();
        // Deploy the model
        OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
        future.get();
        System.out.println("Model deployment on 2 nodes finished");
    }
}
Also used : DeployModelRequest(com.google.cloud.automl.v1beta1.DeployModelRequest) Empty(com.google.protobuf.Empty) ModelName(com.google.cloud.automl.v1beta1.ModelName) ImageObjectDetectionModelDeploymentMetadata(com.google.cloud.automl.v1beta1.ImageObjectDetectionModelDeploymentMetadata) OperationMetadata(com.google.cloud.automl.v1beta1.OperationMetadata) AutoMlClient(com.google.cloud.automl.v1beta1.AutoMlClient)

Example 57 with Model

use of com.google.cloud.automl.v1beta1.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...");
    }
}
Also used : Model(com.google.cloud.automl.v1.Model) OperationMetadata(com.google.cloud.automl.v1.OperationMetadata) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient) LocationName(com.google.cloud.automl.v1.LocationName) ImageObjectDetectionModelMetadata(com.google.cloud.automl.v1.ImageObjectDetectionModelMetadata)

Example 58 with Model

use of com.google.cloud.automl.v1beta1.Model 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()));
        }
    }
}
Also used : Model(com.google.cloud.automl.v1.Model) ListModelsRequest(com.google.cloud.automl.v1.ListModelsRequest) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient) LocationName(com.google.cloud.automl.v1.LocationName)

Example 59 with Model

use of com.google.cloud.automl.v1beta1.Model in project java-automl by googleapis.

the class TranslateCreateModel 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");
        TranslationModelMetadata translationModelMetadata = TranslationModelMetadata.newBuilder().build();
        Model model = Model.newBuilder().setDisplayName(displayName).setDatasetId(datasetId).setTranslationModelMetadata(translationModelMetadata).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...");
    }
}
Also used : Model(com.google.cloud.automl.v1.Model) TranslationModelMetadata(com.google.cloud.automl.v1.TranslationModelMetadata) OperationMetadata(com.google.cloud.automl.v1.OperationMetadata) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient) LocationName(com.google.cloud.automl.v1.LocationName)

Example 60 with Model

use of com.google.cloud.automl.v1beta1.Model in project java-automl by googleapis.

the class TablesPredictTest method setUp.

@Before
public void setUp() throws IOException, ExecutionException, InterruptedException {
    // Verify that the model is deployed for prediction
    try (AutoMlClient client = AutoMlClient.create()) {
        ModelName modelFullId = ModelName.of(PROJECT_ID, "us-central1", MODEL_ID);
        Model model = client.getModel(modelFullId);
        if (model.getDeploymentState() == Model.DeploymentState.UNDEPLOYED) {
            // Deploy the model if not deployed
            DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
            client.deployModelAsync(request).get();
        }
    }
    bout = new ByteArrayOutputStream();
    out = new PrintStream(bout);
    originalPrintStream = System.out;
    System.setOut(out);
}
Also used : DeployModelRequest(com.google.cloud.automl.v1.DeployModelRequest) PrintStream(java.io.PrintStream) ModelName(com.google.cloud.automl.v1.ModelName) Model(com.google.cloud.automl.v1.Model) ByteArrayOutputStream(java.io.ByteArrayOutputStream) AutoMlClient(com.google.cloud.automl.v1.AutoMlClient) Before(org.junit.Before)

Aggregations

Test (org.junit.Test)51 Model (org.eclipse.xtext.valueconverter.bug250313.Model)30 AutoMlClient (com.google.cloud.automl.v1beta1.AutoMlClient)17 Model (com.google.cloud.aiplatform.v1.Model)16 AutoMlClient (com.google.cloud.automl.v1.AutoMlClient)16 Model (com.google.cloud.automl.v1.Model)16 ICompositeNode (org.eclipse.xtext.nodemodel.ICompositeNode)16 ModelName (com.google.cloud.automl.v1beta1.ModelName)15 LocationName (com.google.cloud.aiplatform.v1.LocationName)14 PipelineServiceClient (com.google.cloud.aiplatform.v1.PipelineServiceClient)14 PipelineServiceSettings (com.google.cloud.aiplatform.v1.PipelineServiceSettings)14 TrainingPipeline (com.google.cloud.aiplatform.v1.TrainingPipeline)14 InputDataConfig (com.google.cloud.aiplatform.v1.InputDataConfig)13 ModelContainerSpec (com.google.cloud.aiplatform.v1.ModelContainerSpec)13 OperationMetadata (com.google.cloud.automl.v1beta1.OperationMetadata)12 FilterSplit (com.google.cloud.aiplatform.v1.FilterSplit)11 FractionSplit (com.google.cloud.aiplatform.v1.FractionSplit)11 PredefinedSplit (com.google.cloud.aiplatform.v1.PredefinedSplit)11 TimestampSplit (com.google.cloud.aiplatform.v1.TimestampSplit)11 Status (com.google.rpc.Status)11