use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class UndeployModel method undeployModel.
// Undeploy a model from prediction
static void undeployModel(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);
UndeployModelRequest request = UndeployModelRequest.newBuilder().setName(modelFullId.toString()).build();
OperationFuture<Empty, OperationMetadata> future = client.undeployModelAsync(request);
future.get();
System.out.println("Model undeployment finished");
}
}
use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class VisionClassificationDeployModelNodeCount method visionClassificationDeployModelNodeCount.
// Deploy a model for prediction with a specified node count (can be used to redeploy a model)
static void visionClassificationDeployModelNodeCount(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);
ImageClassificationModelDeploymentMetadata metadata = ImageClassificationModelDeploymentMetadata.newBuilder().setNodeCount(2).build();
DeployModelRequest request = DeployModelRequest.newBuilder().setName(modelFullId.toString()).setImageClassificationModelDeploymentMetadata(metadata).build();
OperationFuture<Empty, OperationMetadata> future = client.deployModelAsync(request);
future.get();
System.out.println("Model deployment finished");
}
}
use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class TablesPredict method predict.
static void predict(String projectId, String modelId, List<Value> values) throws IOException {
// the "close" method on the client to safely clean up any remaining background resources.
try (PredictionServiceClient client = PredictionServiceClient.create()) {
// Get the full path of the model.
ModelName name = ModelName.of(projectId, "us-central1", modelId);
Row row = Row.newBuilder().addAllValues(values).build();
ExamplePayload payload = ExamplePayload.newBuilder().setRow(row).build();
// Feature importance gives you visibility into how the features in a specific prediction
// request informed the resulting prediction. For more info, see:
// https://cloud.google.com/automl-tables/docs/features#local
PredictRequest request = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).putParams("feature_importance", "true").build();
PredictResponse response = client.predict(request);
System.out.println("Prediction results:");
for (AnnotationPayload annotationPayload : response.getPayloadList()) {
TablesAnnotation tablesAnnotation = annotationPayload.getTables();
System.out.format("Classification label: %s%n", tablesAnnotation.getValue().getStringValue());
System.out.format("Classification score: %.3f%n", tablesAnnotation.getScore());
// Get features of top importance
tablesAnnotation.getTablesModelColumnInfoList().forEach(info -> System.out.format("\tColumn: %s - Importance: %.2f%n", info.getColumnDisplayName(), info.getFeatureImportance()));
}
}
}
use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class LanguageTextClassificationPredict method predict.
static void predict(String projectId, String modelId, String content) throws IOException {
// the "close" method on the client to safely clean up any remaining background resources.
try (PredictionServiceClient client = PredictionServiceClient.create()) {
// Get the full path of the model.
ModelName name = ModelName.of(projectId, "us-central1", modelId);
// For available mime types, see:
// https://cloud.google.com/automl/docs/reference/rest/v1/projects.locations.models/predict#textsnippet
TextSnippet textSnippet = TextSnippet.newBuilder().setContent(content).setMimeType(// Types: text/plain, text/html
"text/plain").build();
ExamplePayload payload = ExamplePayload.newBuilder().setTextSnippet(textSnippet).build();
PredictRequest predictRequest = PredictRequest.newBuilder().setName(name.toString()).setPayload(payload).build();
PredictResponse response = client.predict(predictRequest);
for (AnnotationPayload annotationPayload : response.getPayloadList()) {
System.out.format("Predicted class name: %s\n", annotationPayload.getDisplayName());
System.out.format("Predicted sentiment score: %.2f\n\n", annotationPayload.getClassification().getScore());
}
}
}
use of com.google.cloud.aiplatform.v1.ModelName in project java-automl by googleapis.
the class DeleteModel method deleteModel.
// Delete a model
static void deleteModel(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);
// Delete a model.
Empty response = client.deleteModelAsync(modelFullId).get();
System.out.println("Model deletion started...");
System.out.println(String.format("Model deleted. %s", response));
}
}
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