feat: adds ValueConverter utility and demo samples

google-cloud-aiplatform/pom.xml

@@ -83,6 +83,15 @@
       <classifier>testlib</classifier>
       <scope>test</scope>
     </dependency>
+    <dependency>
+      <groupId>com.google.protobuf</groupId>
+      <artifactId>protobuf-java-util</artifactId>
+    </dependency>
+    <dependency>
+      <groupId>com.google.code.gson</groupId>
+      <artifactId>gson</artifactId>
+      <scope>test</scope>
+    </dependency>
   </dependencies>
 
   <profiles>

google-cloud-aiplatform/src/main/java/com/google/cloud/aiplatform/util/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.util;
+
+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/util/ValueConverterTest.java

@@ -0,0 +1,123 @@
+/*
+ * 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.util;
+
+import static org.junit.Assert.assertEquals;
+import static org.junit.Assert.assertThrows;
+
+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 org.junit.Test;
+import org.junit.function.ThrowingRunnable;
+
+public class ValueConverterTest {
+
+  @Test
+  public void testValueConverterToValue() throws InvalidProtocolBufferException {
+    AutoMlImageClassificationInputs testObjectInputs =
+        AutoMlImageClassificationInputs.newBuilder()
+            .setModelType(ModelType.CLOUD)
+            .setBudgetMilliNodeHours(8000)
+            .setMultiLabel(true)
+            .setDisableEarlyStopping(false)
+            .build();
+
+    Value actualConvertedValue = ValueConverter.toValue(testObjectInputs);
+
+    Struct actualStruct = actualConvertedValue.getStructValue();
+    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.equals("multiLabel")) {
+        actualBoolValueEntry = entry;
+      } else if (key.equals("modelType")) {
+        actualStringValueEntry = entry;
+      } else if (key.equals("budgetMilliNodeHours")) {
+        actualNumberValueEntry = entry;
+      }
+    }
+
+    Value actualBoolValue = (Value) actualBoolValueEntry.getValue();
+    assertEquals(testObjectInputs.getMultiLabel(), actualBoolValue.getBoolValue());
+
+    Value actualStringValue = (Value) actualStringValueEntry.getValue();
+    assertEquals("CLOUD", actualStringValue.getStringValue());
+
+    Value actualNumberValue = (Value) actualNumberValueEntry.getValue();
+    // protobuf stores int64 values as strings rather than numbers
+    long actualNumber = Long.parseLong(actualNumberValue.getStringValue());
+    assertEquals(testObjectInputs.getBudgetMilliNodeHours(), actualNumber);
+  }
+
+  @Test
+  public void testValueConverterFromValue() throws InvalidProtocolBufferException {
+
+    JsonObject 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);
+    Value testValueInputs = valueBuilder.build();
+
+    AutoMlImageClassificationInputs actualInputs =
+        (AutoMlImageClassificationInputs)
+            ValueConverter.fromValue(AutoMlImageClassificationInputs.newBuilder(), testValueInputs);
+
+    assertEquals(8000, actualInputs.getBudgetMilliNodeHours());
+    assertEquals(true, actualInputs.getMultiLabel());
+    assertEquals(ModelType.CLOUD, actualInputs.getModelType());
+  }
+
+  @Test
+  public void testValueConverterFromValueWithBadInputs() throws InvalidProtocolBufferException {
+    JsonObject testBadJsonInputs = new JsonObject();
+    testBadJsonInputs.addProperty("wrong_key", "some_value");
+
+    Value.Builder badValueBuilder = Value.newBuilder();
+    JsonFormat.parser().merge(testBadJsonInputs.toString(), badValueBuilder);
+    final Value testBadValueInputs = badValueBuilder.build();
+
+    assertThrows(
+        InvalidProtocolBufferException.class,
+        new ThrowingRunnable() {
+          @Override
+          public void run() throws Throwable {
+            AutoMlImageClassificationInputs actualBadInput =
+                (AutoMlImageClassificationInputs)
+                    ValueConverter.fromValue(
+                        AutoMlImageClassificationInputs.newBuilder(), testBadValueInputs);
+          }
+        });
+  }
+}

samples/snippets/pom.xml

@@ -27,7 +27,7 @@
     <dependency>
       <groupId>com.google.cloud</groupId>
       <artifactId>google-cloud-aiplatform</artifactId>
-      <version>0.1.0</version>
+      <version>0.1.1-SNAPSHOT</version>
     </dependency>
     <!-- [END aiplatform_install_with_bom] -->
     <dependency>

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

@@ -17,7 +17,7 @@
 package aiplatform;
 
 // [START aiplatform_create_training_pipeline_image_classification_sample]
-
+import com.google.cloud.aiplatform.util.ValueConverter;
 import com.google.cloud.aiplatform.v1beta1.DeployedModelRef;
 import com.google.cloud.aiplatform.v1beta1.EnvVar;
 import com.google.cloud.aiplatform.v1beta1.ExplanationMetadata;
@@ -38,8 +38,8 @@
 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.rpc.Status;
 import java.io.IOException;
 
@@ -74,11 +74,13 @@ 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 +89,7 @@ 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

@@ -19,12 +19,15 @@
 // [START aiplatform_predict_image_classification_sample]
 
 import com.google.api.client.util.Base64;
+import com.google.cloud.aiplatform.util.ValueConverter;
 import com.google.cloud.aiplatform.v1beta1.EndpointName;
 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.protobuf.Value;
-import com.google.protobuf.util.JsonFormat;
 import java.io.IOException;
 import java.nio.charset.StandardCharsets;
 import java.nio.file.Files;
@@ -60,23 +63,42 @@ 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

@@ -17,13 +17,14 @@
 package aiplatform;
 
 // [START aiplatform_predict_text_classification_sample]
-
+import com.google.cloud.aiplatform.util.ValueConverter;
 import com.google.cloud.aiplatform.v1beta1.EndpointName;
 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.protobuf.Value;
-import com.google.protobuf.util.JsonFormat;
 import java.io.IOException;
 import java.util.ArrayList;
 import java.util.List;
@@ -52,25 +53,38 @@ 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++;
+        }
       }
     }
   }