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/utility/ValueConverter.java

@@ -0,0 +1,62 @@
+/*
+ * Copyright 2020 Google LLC
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package com.google.cloud.aiplatform.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();
+ }
+}

google-cloud-aiplatform/src/test/java/com/google/cloud/aiplatform/utility/ValueConverterTest.java

@@ -0,0 +1,107 @@
+/*
+ * Copyright 2020 Google LLC
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package com.google.cloud.aiplatform.utility;
+
+import com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs;
+import com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageClassificationInputs.ModelType;
+import com.google.gson.JsonObject;
+import com.google.protobuf.InvalidProtocolBufferException;
+import com.google.protobuf.MapEntry;
+import com.google.protobuf.Struct;
+import com.google.protobuf.Value;
+import com.google.protobuf.util.JsonFormat;
+import java.util.Collection;
+import java.util.stream.Collectors;
+import org.junit.Assert;
+import org.junit.Before;
+import org.junit.Test;
+
+public class ValueConverterTest {
+
+ private static JsonObject testJsonInputs;
+ private static Value testValueInputs;
+ private static AutoMlImageClassificationInputs testObjectInputs;
+
+ @Before
+ public void setUp() throws InvalidProtocolBufferException {
+ testJsonInputs = new JsonObject();
+ testJsonInputs.addProperty("multi_label", true);
+ testJsonInputs.addProperty("model_type", "CLOUD");
+ testJsonInputs.addProperty("budget_milli_node_hours", 8000);
+
+ Value.Builder valueBuilder = Value.newBuilder();
+ JsonFormat.parser().merge(testJsonInputs.toString(), valueBuilder);
+ testValueInputs = valueBuilder.build();
+
+ testObjectInputs =
+ AutoMlImageClassificationInputs.newBuilder()
+ .setModelType(ModelType.CLOUD)
+ .setBudgetMilliNodeHours(8000)
+ .setMultiLabel(true)
+ .setDisableEarlyStopping(false)
+ .build();
+ }
+
+ @Test
+ public void testValueConverterToValue() throws InvalidProtocolBufferException {
+ Value actualConvertedValue = ValueConverter.toValue(testObjectInputs);
+
+ Struct actualStruct = actualConvertedValue.getStructValue();
+ Assert.assertEquals(3, actualStruct.getFieldsCount());
+
+ Collection<Object> innerFields = actualStruct.getAllFields().values();
+ Collection<MapEntry> fieldEntries = (Collection<MapEntry>) innerFields.toArray()[0];
+
+ MapEntry actualBoolValueEntry = null;
+ MapEntry actualStringValueEntry = null;
+ MapEntry actualNumberValueEntry = null;
+
+ for (MapEntry entry : fieldEntries) {
+ String key = entry.getKey().toString();
+ if (key.contains("multiLabel")) {
+ actualBoolValueEntry = entry;
+ } else if (key.contains("modelType")) {
+ actualStringValueEntry = entry;
+ } else if (key.contains("budgetMilliNodeHours")) {
+ actualNumberValueEntry = entry;
+ }
+ }
+
+
+ Value actualBoolValue = (Value) actualBoolValueEntry.getValue();
+ Assert.assertEquals(testObjectInputs.getMultiLabel(), actualBoolValue.getBoolValue());
+
+ Value actualStringValue = (Value) actualStringValueEntry.getValue();
+ Assert.assertEquals("CLOUD", actualStringValue.getStringValue());
+
+ Value actualNumberValue = (Value) actualNumberValueEntry.getValue();
+ // protobuf stores int64 values as strings rather than numbers
+ long actualNumber = Long.parseLong(actualNumberValue.getStringValue());
+ Assert.assertEquals(testObjectInputs.getBudgetMilliNodeHours(), actualNumber);
+ }
+
+ @Test
+ public void testValueConverterFromValue() throws InvalidProtocolBufferException {
+ AutoMlImageClassificationInputs actualInputs =
+ (AutoMlImageClassificationInputs)
+ ValueConverter.fromValue(AutoMlImageClassificationInputs.newBuilder(), testValueInputs);
+
+ Assert.assertEquals(8000, actualInputs.getBudgetMilliNodeHours());
+ Assert.assertEquals(true, actualInputs.getMultiLabel());
+ Assert.assertEquals(ModelType.CLOUD, actualInputs.getModelType());
+ }
+}

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

@@ -38,8 +38,9 @@
 import com.google.cloud.aiplatform.v1beta1.SampledShapleyAttribution;
 import com.google.cloud.aiplatform.v1beta1.TimestampSplit;
 import com.google.cloud.aiplatform.v1beta1.TrainingPipeline;
-import com.google.protobuf.Value;
-import com.google.protobuf.util.JsonFormat;
+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.utility.ValueConverter;
 import com.google.rpc.Status;
 import java.io.IOException;
 
@@ -74,11 +75,13 @@ 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();
@@ -87,7 +90,7 @@ 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

@@ -23,8 +23,11 @@
 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.utility.ValueConverter;
 import com.google.protobuf.Value;
-import com.google.protobuf.util.JsonFormat;
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
 import java.nio.file.Files;
@@ -60,23 +63,40 @@ 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

@@ -22,8 +22,10 @@
 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.TextClassificationPredictionInstance;
+import com.google.cloud.aiplatform.v1beta1.schema.predict.prediction.ClassificationPredictionResult;
+import com.google.cloud.aiplatform.utility.ValueConverter;
 import com.google.protobuf.Value;
-import com.google.protobuf.util.JsonFormat;
 import java.io.IOException;
 import java.util.ArrayList;
 import java.util.List;
@@ -52,25 +54,37 @@ 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++;
+ }
  }
  }
  }