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TetyanaYahodskaTetyanaYahodska
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Fixed test
2 parents 90bbb41 + c617f2a commit 4d7c2a6

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-219
lines changed

‎aiplatform/pom.xml‎

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<version>1.7.1</version>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>org.mockito</groupId>
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<artifactId>mockito-core</artifactId>
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<version>5.13.0</version>
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<scope>test</scope>
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</dependency>
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<dependency>
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<groupId>org.junit.jupiter</groupId>
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<artifactId>junit-jupiter</artifactId>

‎aiplatform/resources/roller_skaters.png‎

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‎aiplatform/resources/roller_skaters_mask.png‎

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‎aiplatform/resources/volleyball_game.png‎

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‎aiplatform/resources/volleyball_game_inpainting_remove_mask.png‎

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‎aiplatform/resources/woman.png‎

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‎aiplatform/resources/woman_inpainting_insert_mask.png‎

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‎aiplatform/src/main/java/aiplatform/Gemma2PredictGpu.java‎

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/*
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* Copyright 2024 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package aiplatform;
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// [START generativeaionvertexai_gemma2_predict_gpu]
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import com.google.cloud.aiplatform.v1.EndpointName;
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import com.google.cloud.aiplatform.v1.PredictResponse;
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import com.google.cloud.aiplatform.v1.PredictionServiceClient;
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import com.google.cloud.aiplatform.v1.PredictionServiceSettings;
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import com.google.gson.Gson;
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import com.google.protobuf.InvalidProtocolBufferException;
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import com.google.protobuf.Value;
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import com.google.protobuf.util.JsonFormat;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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public class Gemma2PredictGpu {
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private final PredictionServiceClient predictionServiceClient;
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// Constructor to inject the PredictionServiceClient
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public Gemma2PredictGpu(PredictionServiceClient predictionServiceClient) {
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this.predictionServiceClient = predictionServiceClient;
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}
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public static void main(String[] args) throws IOException {
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// TODO(developer): Replace these variables before running the sample.
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String projectId = "YOUR_PROJECT_ID";
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String endpointRegion = "us-east4";
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String endpointId = "YOUR_ENDPOINT_ID";
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PredictionServiceSettings predictionServiceSettings =
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PredictionServiceSettings.newBuilder()
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.setEndpoint(String.format("%s-aiplatform.googleapis.com:443", endpointRegion))
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.build();
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PredictionServiceClient predictionServiceClient =
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PredictionServiceClient.create(predictionServiceSettings);
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Gemma2PredictGpu creator = new Gemma2PredictGpu(predictionServiceClient);
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creator.gemma2PredictGpu(projectId, endpointRegion, endpointId);
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}
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// Demonstrates how to run inference on a Gemma2 model
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// deployed to a Vertex AI endpoint with GPU accelerators.
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public String gemma2PredictGpu(String projectId, String region,
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String endpointId) throws IOException {
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Map<String, Object> paramsMap = new HashMap<>();
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paramsMap.put("temperature", 0.9);
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paramsMap.put("maxOutputTokens", 1024);
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paramsMap.put("topP", 1.0);
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paramsMap.put("topK", 1);
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Value parameters = mapToValue(paramsMap);
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// Prompt used in the prediction
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String instance = "{ \"inputs\": \"Why is the sky blue?\"}";
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Value.Builder instanceValue = Value.newBuilder();
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JsonFormat.parser().merge(instance, instanceValue);
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// Encapsulate the prompt in a correct format for GPUs
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// Example format: [{'inputs': 'Why is the sky blue?', 'parameters': {'temperature': 0.8}}]
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List<Value> instances = new ArrayList<>();
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instances.add(instanceValue.build());
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EndpointName endpointName = EndpointName.of(projectId, region, endpointId);
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PredictResponse predictResponse = this.predictionServiceClient
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.predict(endpointName, instances, parameters);
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String textResponse = predictResponse.getPredictions(0).getStringValue();
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System.out.println(textResponse);
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return textResponse;
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}
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private static Value mapToValue(Map<String, Object> map) throws InvalidProtocolBufferException {
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Gson gson = new Gson();
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String json = gson.toJson(map);
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Value.Builder builder = Value.newBuilder();
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JsonFormat.parser().merge(json, builder);
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return builder.build();
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}
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}
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// [END generativeaionvertexai_gemma2_predict_gpu]

‎aiplatform/src/main/java/aiplatform/Gemma2PredictTpu.java‎

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/*
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* Copyright 2024 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package aiplatform;
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// [START generativeaionvertexai_gemma2_predict_tpu]
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import com.google.cloud.aiplatform.v1.EndpointName;
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import com.google.cloud.aiplatform.v1.PredictResponse;
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import com.google.cloud.aiplatform.v1.PredictionServiceClient;
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import com.google.cloud.aiplatform.v1.PredictionServiceSettings;
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import com.google.gson.Gson;
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import com.google.protobuf.InvalidProtocolBufferException;
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import com.google.protobuf.Value;
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import com.google.protobuf.util.JsonFormat;
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import java.io.IOException;
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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.List;
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import java.util.Map;
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public class Gemma2PredictTpu {
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private final PredictionServiceClient predictionServiceClient;
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// Constructor to inject the PredictionServiceClient
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public Gemma2PredictTpu(PredictionServiceClient predictionServiceClient) {
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this.predictionServiceClient = predictionServiceClient;
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}
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public static void main(String[] args) throws IOException {
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// TODO(developer): Replace these variables before running the sample.
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String projectId = "YOUR_PROJECT_ID";
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String endpointRegion = "us-west1";
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String endpointId = "YOUR_ENDPOINT_ID";
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PredictionServiceSettings predictionServiceSettings =
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PredictionServiceSettings.newBuilder()
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.setEndpoint(String.format("%s-aiplatform.googleapis.com:443", endpointRegion))
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.build();
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PredictionServiceClient predictionServiceClient =
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PredictionServiceClient.create(predictionServiceSettings);
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Gemma2PredictTpu creator = new Gemma2PredictTpu(predictionServiceClient);
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creator.gemma2PredictTpu(projectId, endpointRegion, endpointId);
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}
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// Demonstrates how to run inference on a Gemma2 model
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// deployed to a Vertex AI endpoint with TPU accelerators.
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public String gemma2PredictTpu(String projectId, String region,
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String endpointId) throws IOException {
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Map<String, Object> paramsMap = new HashMap<>();
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paramsMap.put("temperature", 0.9);
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paramsMap.put("maxOutputTokens", 1024);
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paramsMap.put("topP", 1.0);
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paramsMap.put("topK", 1);
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Value parameters = mapToValue(paramsMap);
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// Prompt used in the prediction
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String instance = "{ \"prompt\": \"Why is the sky blue?\"}";
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Value.Builder instanceValue = Value.newBuilder();
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JsonFormat.parser().merge(instance, instanceValue);
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// Encapsulate the prompt in a correct format for TPUs
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// Example format: [{'prompt': 'Why is the sky blue?', 'temperature': 0.9}]
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List<Value> instances = new ArrayList<>();
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instances.add(instanceValue.build());
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EndpointName endpointName = EndpointName.of(projectId, region, endpointId);
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PredictResponse predictResponse = this.predictionServiceClient
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.predict(endpointName, instances, parameters);
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String textResponse = predictResponse.getPredictions(0).getStringValue();
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System.out.println(textResponse);
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return textResponse;
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}
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private static Value mapToValue(Map<String, Object> map) throws InvalidProtocolBufferException {
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Gson gson = new Gson();
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String json = gson.toJson(map);
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Value.Builder builder = Value.newBuilder();
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JsonFormat.parser().merge(json, builder);
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return builder.build();
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}
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}
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// [END generativeaionvertexai_gemma2_predict_tpu]
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‎aiplatform/src/main/java/aiplatform/imagen/EditImageInpaintingInsertMaskSample.java‎

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/*
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* Copyright 2024 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package aiplatform.imagen;
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// [START generativeaionvertexai_imagen_edit_image_inpainting_insert_mask]
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import com.google.api.gax.rpc.ApiException;
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import com.google.cloud.aiplatform.v1.EndpointName;
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import com.google.cloud.aiplatform.v1.PredictResponse;
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import com.google.cloud.aiplatform.v1.PredictionServiceClient;
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import com.google.cloud.aiplatform.v1.PredictionServiceSettings;
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import com.google.gson.Gson;
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import com.google.protobuf.InvalidProtocolBufferException;
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import com.google.protobuf.Value;
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import com.google.protobuf.util.JsonFormat;
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import java.io.IOException;
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import java.nio.file.Files;
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import java.nio.file.Path;
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import java.nio.file.Paths;
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import java.util.Base64;
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import java.util.Collections;
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import java.util.HashMap;
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import java.util.Map;
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public class EditImageInpaintingInsertMaskSample {
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public static void main(String[] args) throws IOException {
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// TODO(developer): Replace these variables before running the sample.
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String projectId = "my-project-id";
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String location = "us-central1";
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String inputPath = "/path/to/my-input.png";
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String maskPath = "/path/to/my-mask.png";
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String prompt =
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""; // The text prompt describing what you want to see inserted in the mask area.
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editImageInpaintingInsertMask(projectId, location, inputPath, maskPath, prompt);
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}
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// Edit an image using a mask file. Inpainting can insert the object designated by the prompt
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// into the masked area.
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public static PredictResponse editImageInpaintingInsertMask(
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String projectId, String location, String inputPath, String maskPath, String prompt)
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throws ApiException, IOException {
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final String endpoint = String.format("%s-aiplatform.googleapis.com:443", location);
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PredictionServiceSettings predictionServiceSettings =
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PredictionServiceSettings.newBuilder().setEndpoint(endpoint).build();
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// Initialize client that will be used to send requests. This client only needs to be created
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// once, and can be reused for multiple requests.
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try (PredictionServiceClient predictionServiceClient =
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PredictionServiceClient.create(predictionServiceSettings)) {
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final EndpointName endpointName =
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EndpointName.ofProjectLocationPublisherModelName(
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projectId, location, "google", "imagegeneration@006");
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// Encode image and mask to Base64
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String imageBase64 =
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Base64.getEncoder().encodeToString(Files.readAllBytes(Paths.get(inputPath)));
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String maskBase64 =
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Base64.getEncoder().encodeToString(Files.readAllBytes(Paths.get(maskPath)));
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// Create the image and image mask maps
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Map<String, String> imageMap = new HashMap<>();
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imageMap.put("bytesBase64Encoded", imageBase64);
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Map<String, String> maskMap = new HashMap<>();
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maskMap.put("bytesBase64Encoded", maskBase64);
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Map<String, Map> imageMaskMap = new HashMap<>();
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imageMaskMap.put("image", maskMap);
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Map<String, Object> instancesMap = new HashMap<>();
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instancesMap.put("prompt", prompt); // [ "prompt", "<my-prompt>" ]
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instancesMap.put(
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"image", imageMap); // [ "image", [ "bytesBase64Encoded", "iVBORw0KGgo...==" ] ]
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instancesMap.put(
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"mask",
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imageMaskMap); // [ "mask", [ "image", [ "bytesBase64Encoded", "iJKDF0KGpl...==" ] ] ]
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instancesMap.put("editMode", "inpainting-insert"); // [ "editMode", "inpainting-insert" ]
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Value instances = mapToValue(instancesMap);
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// Optional parameters
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Map<String, Object> paramsMap = new HashMap<>();
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paramsMap.put("sampleCount", 1);
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Value parameters = mapToValue(paramsMap);
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PredictResponse predictResponse =
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predictionServiceClient.predict(
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endpointName, Collections.singletonList(instances), parameters);
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for (Value prediction : predictResponse.getPredictionsList()) {
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Map<String, Value> fieldsMap = prediction.getStructValue().getFieldsMap();
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if (fieldsMap.containsKey("bytesBase64Encoded")) {
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String bytesBase64Encoded = fieldsMap.get("bytesBase64Encoded").getStringValue();
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Path tmpPath = Files.createTempFile("imagen-", ".png");
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Files.write(tmpPath, Base64.getDecoder().decode(bytesBase64Encoded));
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System.out.format("Image file written to: %s\n", tmpPath.toUri());
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}
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}
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return predictResponse;
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}
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}
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private static Value mapToValue(Map<String, Object> map) throws InvalidProtocolBufferException {
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Gson gson = new Gson();
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String json = gson.toJson(map);
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Value.Builder builder = Value.newBuilder();
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JsonFormat.parser().merge(json, builder);
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return builder.build();
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}
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}
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// [END generativeaionvertexai_imagen_edit_image_inpainting_insert_mask]

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