feat: adds ValueConverter utility and demo samples

google-cloud-aiplatform/pom.xml

@@ -83,6 +83,10 @@
  <classifier>testlib</classifier>
  <scope>test</scope>
  </dependency>
+ <dependency>
+ <groupId>com.google.protobuf</groupId>
+ <artifactId>protobuf-java-util</artifactId>
+ </dependency>
  </dependencies>
 
  <profiles>

google-cloud-aiplatform/src/main/java/com/google/cloud/aiplatform/v1beta1/utility/ValueConverter.java

@@ -0,0 +1,48 @@
+package com.google.cloud.aiplatform.v1beta1.utility;
+
+import com.google.protobuf.InvalidProtocolBufferException;
+import com.google.protobuf.Message;
+import com.google.protobuf.Value;
+import com.google.protobuf.util.JsonFormat;
+
+/**
+ * Exposes utility methods for converting AI Platform messages to and
+ * from {@com.google.protobuf.Value} objects.
+ */
+public class ValueConverter {
+
+ /**
+ * An empty {@com.google.protobuf.Value} message.
+ */
+ public static final Value EMPTY_VALUE = Value.newBuilder().build();
+
+ /**
+ * Converts a message type to a {@com.google.protobuf.Value}.
+ *
+ * @param message the message to convert
+ * @return the message as a {@com.google.protobuf.Value}
+ * @throws InvalidProtocolBufferException
+ */
+ public static Value toValue(Message message) throws InvalidProtocolBufferException {
+ String jsonString = JsonFormat.printer().print(message);
+ Value.Builder value = Value.newBuilder();
+ JsonFormat.parser().merge(jsonString, value);
+ return value.build();
+ }
+
+ /**
+ * Converts a {@com.google.protobuf.Value} to a {@com.google.protobuf.Message}
+ * of the provided {@com.google.protobuf.Message.Builder}.
+ *
+ * @param messageBuilder a builder for the message type
+ * @param value the Value to convert to a message
+ * @return the value as a message
+ * @throws InvalidProtocolBufferException
+ */
+ public static Message fromValue(Message.Builder messageBuilder, Value value)
+ throws InvalidProtocolBufferException {
+ String valueString = JsonFormat.printer().print(value);
+ JsonFormat.parser().merge(valueString, messageBuilder);
+ return messageBuilder.build();
+ }
+}

samples/snippets/src/main/java/aiplatform/CreateTrainingPipelineImageClassificationSample.java

@@ -38,6 +38,10 @@
 import com.google.cloud.aiplatform.v1beta1.SampledShapleyAttribution;
 import com.google.cloud.aiplatform.v1beta1.TimestampSplit;
 import com.google.cloud.aiplatform.v1beta1.TrainingPipeline;
+import com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs;
+import com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType;
+import com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationMetadata;
+import com.google.cloud.aiplatform.v1beta1.utility.ValueConverter;
 import com.google.protobuf.Any;
 import com.google.protobuf.Value;
 import com.google.protobuf.util.JsonFormat;
@@ -76,11 +80,13 @@ static void createTrainingPipelineImageClassificationSample(
  + "automl_image_classification_1.0.0.yaml";
  LocationName locationName = LocationName.of(project, location);
 
- String jsonString =
- "{\"multiLabel\": false, \"modelType\": \"CLOUD\", \"budgetMilliNodeHours\": 8000,"
- + " \"disableEarlyStopping\": false}";
- Value.Builder trainingTaskInputs = Value.newBuilder();
- JsonFormat.parser().merge(jsonString, trainingTaskInputs);
+ AutoMlImageClassificationInputs autoMlImageClassificationInputs =
+ AutoMlImageClassificationInputs.newBuilder()
+ .setModelType(ModelType.CLOUD)
+ .setMultiLabel(false)
+ .setBudgetMilliNodeHours(8000)
+ .setDisableEarlyStopping(false)
+ .build();
 
  InputDataConfig trainingInputDataConfig =
  InputDataConfig.newBuilder().setDatasetId(datasetId).build();
@@ -89,7 +95,7 @@ static void createTrainingPipelineImageClassificationSample(
  TrainingPipeline.newBuilder()
  .setDisplayName(trainingPipelineDisplayName)
  .setTrainingTaskDefinition(trainingTaskDefinition)
- .setTrainingTaskInputs(trainingTaskInputs)
+ .setTrainingTaskInputs(ValueConverter.toValue(autoMlImageClassificationInputs))
  .setInputDataConfig(trainingInputDataConfig)
  .setModelToUpload(model)
  .build();

samples/snippets/src/main/java/aiplatform/PredictImageClassificationSample.java

@@ -23,6 +23,10 @@
 import com.google.cloud.aiplatform.v1beta1.PredictResponse;
 import com.google.cloud.aiplatform.v1beta1.PredictionServiceClient;
 import com.google.cloud.aiplatform.v1beta1.PredictionServiceSettings;
+import com.google.cloud.aiplatform.v1beta1.schema.predict.instance.ImageClassificationPredictionInstance;
+import com.google.cloud.aiplatform.v1beta1.schema.predict.params.ImageClassificationPredictionParams;
+import com.google.cloud.aiplatform.v1beta1.schema.predict.prediction.ClassificationPredictionResult;
+import com.google.cloud.aiplatform.v1beta1.utility.ValueConverter;
 import com.google.protobuf.Value;
 import com.google.protobuf.util.JsonFormat;
 import java.io.IOException;
@@ -60,23 +64,40 @@ static void predictImageClassification(String project, String fileName, String e
  byte[] contents = Base64.encodeBase64(Files.readAllBytes(Paths.get(fileName)));
  String content = new String(contents, StandardCharsets.UTF_8);
 
- Value parameter = Value.newBuilder().setNumberValue(0).setNumberValue(5).build();
-
- String contentDict = "{\"content\": \"" + content + "\"}";
- Value.Builder instance = Value.newBuilder();
- JsonFormat.parser().merge(contentDict, instance);
+ ImageClassificationPredictionInstance predictionInstance =
+ ImageClassificationPredictionInstance.newBuilder()
+ .setContent(content)
+ .build();
 
  List<Value> instances = new ArrayList<>();
- instances.add(instance.build());
+ instances.add(ValueConverter.toValue(predictionInstance));
+
+ ImageClassificationPredictionParams predictionParams =
+ ImageClassificationPredictionParams.newBuilder()
+ .setConfidenceThreshold((float) 0.5)
+ .setMaxPredictions(5)
+ .build();
 
  PredictResponse predictResponse =
- predictionServiceClient.predict(endpointName, instances, parameter);
+ predictionServiceClient.predict(endpointName, instances, ValueConverter.toValue(predictionParams));
  System.out.println("Predict Image Classification Response");
  System.out.format("\tDeployed Model Id: %s\n", predictResponse.getDeployedModelId());
 
  System.out.println("Predictions");
  for (Value prediction : predictResponse.getPredictionsList()) {
- System.out.format("\tPrediction: %s\n", prediction);
+
+ ClassificationPredictionResult.Builder resultBuilder = ClassificationPredictionResult.newBuilder();
+ // Display names and confidences values correspond to
+ // IDs in the ID list.
+ ClassificationPredictionResult result =
+ (ClassificationPredictionResult)ValueConverter.fromValue(resultBuilder, prediction);
+ int counter = 0;
+ for (Long id : result.getIdsList()) {
+ System.out.printf("Label ID: %d\n", id);
+ System.out.printf("Label: %s\n", result.getDisplayNames(counter));
+ System.out.printf("Confidence: %.4f\n", result.getConfidences(counter));
+ counter++;
+ }
  }
  }
  }

samples/snippets/src/main/java/aiplatform/PredictTextClassificationSingleLabelSample.java

@@ -22,6 +22,9 @@
 import com.google.cloud.aiplatform.v1beta1.PredictResponse;
 import com.google.cloud.aiplatform.v1beta1.PredictionServiceClient;
 import com.google.cloud.aiplatform.v1beta1.PredictionServiceSettings;
+import com.google.cloud.aiplatform.v1beta1.schema.predict.instance.TextClassificationPredictionInstance;
+import com.google.cloud.aiplatform.v1beta1.schema.predict.prediction.ClassificationPredictionResult;
+import com.google.cloud.aiplatform.v1beta1.utility.ValueConverter;
 import com.google.protobuf.Value;
 import com.google.protobuf.util.JsonFormat;
 import java.io.IOException;
@@ -52,25 +55,37 @@ static void predictTextClassificationSingleLabel(
  try (PredictionServiceClient predictionServiceClient =
  PredictionServiceClient.create(predictionServiceSettings)) {
  String location = "us-central1";
- String jsonString = "{\"content\": \"" + content + "\"}";
-
  EndpointName endpointName = EndpointName.of(project, location, endpointId);
 
- Value parameter = Value.newBuilder().setNumberValue(0).setNumberValue(5).build();
- Value.Builder instance = Value.newBuilder();
- JsonFormat.parser().merge(jsonString, instance);
+ TextClassificationPredictionInstance predictionInstance = TextClassificationPredictionInstance
+ .newBuilder()
+ .setContent(content)
+ .build();
 
  List<Value> instances = new ArrayList<>();
- instances.add(instance.build());
+ instances.add(ValueConverter.toValue(predictionInstance));
 
  PredictResponse predictResponse =
- predictionServiceClient.predict(endpointName, instances, parameter);
+ predictionServiceClient.predict(endpointName, instances, ValueConverter.EMPTY_VALUE);
  System.out.println("Predict Text Classification Response");
  System.out.format("\tDeployed Model Id: %s\n", predictResponse.getDeployedModelId());
 
- System.out.println("Predictions");
+ System.out.println("Predictions:\n\n");
  for (Value prediction : predictResponse.getPredictionsList()) {
- System.out.format("\tPrediction: %s\n", prediction);
+
+ ClassificationPredictionResult.Builder resultBuilder = ClassificationPredictionResult.newBuilder();
+
+ // Display names and confidences values correspond to
+ // IDs in the ID list.
+ ClassificationPredictionResult result =
+ (ClassificationPredictionResult)ValueConverter.fromValue(resultBuilder, prediction);
+ int counter = 0;
+ for (Long id : result.getIdsList()) {
+ System.out.printf("Label ID: %d\n", id);
+ System.out.printf("Label: %s\n", result.getDisplayNames(counter));
+ System.out.printf("Confidence: %.4f\n", result.getConfidences(counter));
+ counter++;
+ }
  }
  }
  }