samples: adds custom model, action recognition samples and tests

.kokoro/build.sh

@@ -77,6 +77,11 @@ samples)
             source "${KOKORO_GFILE_DIR}/secret_manager/ucaip_samples_secrets"
         fi
 
+        if [ -f "${KOKORO_GFILE_DIR}/secret_manager/java-aiplatform-samples-secrets" ]
+        then
+            source "${KOKORO_GFILE_DIR}/secret_manager/java-aiplatform-samples-secrets"
+        fi
+
         pushd samples
         mvn -B \
           -Penable-samples \

.kokoro/presubmit/samples.cfg

@@ -29,5 +29,5 @@ env_vars: {
 
 env_vars: {
   key: "SECRET_MANAGER_KEYS"
-  value: "java-docs-samples-service-account,ucaip_samples_secrets"
-}
+  value: "java-docs-samples-service-account,ucaip_samples_secrets,java-aiplatform-samples-secrets"
+}

samples/snippets/pom.xml

@@ -40,6 +40,11 @@
       <artifactId>protobuf-java-util</artifactId>
       <version>4.0.0-rc-2</version>
     </dependency>
+    <dependency>
+      <groupId>com.google.code.gson</groupId>
+      <artifactId>gson</artifactId>
+      <version>2.8.6</version>
+    </dependency>
     <dependency>
       <groupId>junit</groupId>
       <artifactId>junit</artifactId>

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

@@ -0,0 +1,108 @@
+/*
+ * 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 aiplatform;
+
+// [START aiplatform_create_batch_prediction_job_bigquery_sample]
+import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob;
+import com.google.cloud.aiplatform.v1beta1.BigQueryDestination;
+import com.google.cloud.aiplatform.v1beta1.BigQuerySource;
+import com.google.cloud.aiplatform.v1beta1.JobServiceClient;
+import com.google.cloud.aiplatform.v1beta1.JobServiceSettings;
+import com.google.cloud.aiplatform.v1beta1.LocationName;
+import com.google.gson.JsonObject;
+import com.google.protobuf.Value;
+import com.google.protobuf.util.JsonFormat;
+import java.io.IOException;
+
+public class CreateBatchPredictionJobBigquerySample {
+
+  public static void main(String[] args) throws IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String project = "PROJECT";
+    String displayName = "DISPLAY_NAME";
+    String modelName = "MODEL_NAME";
+    String instancesFormat = "INSTANCES_FORMAT";
+    String bigquerySourceInputUri = "BIGQUERY_SOURCE_INPUT_URI";
+    String predictionsFormat = "PREDICTIONS_FORMAT";
+    String bigqueryDestinationOutputUri = "BIGQUERY_DESTINATION_OUTPUT_URI";
+    createBatchPredictionJobBigquerySample(
+        project,
+        displayName,
+        modelName,
+        instancesFormat,
+        bigquerySourceInputUri,
+        predictionsFormat,
+        bigqueryDestinationOutputUri);
+  }
+
+  static void createBatchPredictionJobBigquerySample(
+      String project,
+      String displayName,
+      String modelName,
+      String instancesFormat,
+      String bigquerySourceInputUri,
+      String predictionsFormat,
+      String bigqueryDestinationOutputUri)
+      throws IOException {
+    JobServiceSettings settings =
+        JobServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+    String location = "us-central1";
+
+    // Initialize client that will be used to send requests. This client only needs to be created
+    // once, and can be reused for multiple requests. After completing all of your requests, call
+    // the "close" method on the client to safely clean up any remaining background resources.
+    try (JobServiceClient client = JobServiceClient.create(settings)) {
+      JsonObject jsonModelParameters = new JsonObject();
+      Value.Builder modelParametersBuilder = Value.newBuilder();
+      JsonFormat.parser().merge(jsonModelParameters.toString(), modelParametersBuilder);
+      Value modelParameters = modelParametersBuilder.build();
+      BigQuerySource bigquerySource =
+          BigQuerySource.newBuilder().setInputUri(bigquerySourceInputUri).build();
+      BatchPredictionJob.InputConfig inputConfig =
+          BatchPredictionJob.InputConfig.newBuilder()
+              .setInstancesFormat(instancesFormat)
+              .setBigquerySource(bigquerySource)
+              .build();
+      BigQueryDestination bigqueryDestination =
+          BigQueryDestination.newBuilder().setOutputUri(bigqueryDestinationOutputUri).build();
+      BatchPredictionJob.OutputConfig outputConfig =
+          BatchPredictionJob.OutputConfig.newBuilder()
+              .setPredictionsFormat(predictionsFormat)
+              .setBigqueryDestination(bigqueryDestination)
+              .build();
+      BatchPredictionJob batchPredictionJob =
+          BatchPredictionJob.newBuilder()
+              .setDisplayName(displayName)
+              // Format: 'projects/{project}/locations/{location}/models/{model_id}'
+              .setModel(modelName)
+              .setModelParameters(modelParameters)
+              .setInputConfig(inputConfig)
+              .setOutputConfig(outputConfig)
+              // optional
+              .setGenerateExplanation(true)
+              .build();
+      LocationName parent = LocationName.of(project, location);
+      BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
+      System.out.format("response: %s\n", response);
+      System.out.format("\tName: %s\n", response.getName());
+    }
+  }
+}
+
+// [END aiplatform_create_batch_prediction_job_bigquery_sample]

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

@@ -0,0 +1,124 @@
+/*
+ * 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 aiplatform;
+
+// [START aiplatform_create_batch_prediction_job_sample]
+import com.google.cloud.aiplatform.v1beta1.AcceleratorType;
+import com.google.cloud.aiplatform.v1beta1.BatchDedicatedResources;
+import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob;
+import com.google.cloud.aiplatform.v1beta1.GcsDestination;
+import com.google.cloud.aiplatform.v1beta1.GcsSource;
+import com.google.cloud.aiplatform.v1beta1.JobServiceClient;
+import com.google.cloud.aiplatform.v1beta1.JobServiceSettings;
+import com.google.cloud.aiplatform.v1beta1.LocationName;
+import com.google.cloud.aiplatform.v1beta1.MachineSpec;
+import com.google.gson.JsonObject;
+import com.google.protobuf.Value;
+import com.google.protobuf.util.JsonFormat;
+import java.io.IOException;
+
+public class CreateBatchPredictionJobSample {
+
+  public static void main(String[] args) throws IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String project = "PROJECT";
+    String displayName = "DISPLAY_NAME";
+    String modelName = "MODEL_NAME";
+    String instancesFormat = "INSTANCES_FORMAT";
+    String gcsSourceUri = "GCS_SOURCE_URI";
+    String predictionsFormat = "PREDICTIONS_FORMAT";
+    String gcsDestinationOutputUriPrefix = "GCS_DESTINATION_OUTPUT_URI_PREFIX";
+    createBatchPredictionJobSample(
+        project,
+        displayName,
+        modelName,
+        instancesFormat,
+        gcsSourceUri,
+        predictionsFormat,
+        gcsDestinationOutputUriPrefix);
+  }
+
+  static void createBatchPredictionJobSample(
+      String project,
+      String displayName,
+      String modelName,
+      String instancesFormat,
+      String gcsSourceUri,
+      String predictionsFormat,
+      String gcsDestinationOutputUriPrefix)
+      throws IOException {
+    JobServiceSettings settings =
+        JobServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+    String location = "us-central1";
+
+    // Initialize client that will be used to send requests. This client only needs to be created
+    // once, and can be reused for multiple requests. After completing all of your requests, call
+    // the "close" method on the client to safely clean up any remaining background resources.
+    try (JobServiceClient client = JobServiceClient.create(settings)) {
+
+      // Passing in an empty Value object for model parameters
+      JsonObject jsonModelParameters = new JsonObject();
+      Value.Builder modelParametersBuilder = Value.newBuilder();
+      JsonFormat.parser().merge(jsonModelParameters.toString(), modelParametersBuilder);
+      Value modelParameters = modelParametersBuilder.build();
+
+      GcsSource gcsSource = GcsSource.newBuilder().addUris(gcsSourceUri).build();
+      BatchPredictionJob.InputConfig inputConfig =
+          BatchPredictionJob.InputConfig.newBuilder()
+              .setInstancesFormat(instancesFormat)
+              .setGcsSource(gcsSource)
+              .build();
+      GcsDestination gcsDestination =
+          GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
+      BatchPredictionJob.OutputConfig outputConfig =
+          BatchPredictionJob.OutputConfig.newBuilder()
+              .setPredictionsFormat(predictionsFormat)
+              .setGcsDestination(gcsDestination)
+              .build();
+      MachineSpec machineSpec =
+          MachineSpec.newBuilder()
+              .setMachineType("n1-standard-2")
+              .setAcceleratorType(AcceleratorType.NVIDIA_TESLA_K80)
+              .setAcceleratorCount(1)
+              .build();
+      BatchDedicatedResources dedicatedResources =
+          BatchDedicatedResources.newBuilder()
+              .setMachineSpec(machineSpec)
+              .setStartingReplicaCount(1)
+              .setMaxReplicaCount(1)
+              .build();
+      BatchPredictionJob batchPredictionJob =
+          BatchPredictionJob.newBuilder()
+              .setDisplayName(displayName)
+              // Format: 'projects/{project}/locations/{location}/models/{model_id}'
+              .setModel(modelName)
+              .setModelParameters(modelParameters)
+              .setInputConfig(inputConfig)
+              .setOutputConfig(outputConfig)
+              .setDedicatedResources(dedicatedResources)
+              .build();
+      LocationName parent = LocationName.of(project, location);
+      BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
+      System.out.format("response: %s\n", response);
+      System.out.format("\tName: %s\n", response.getName());
+    }
+  }
+}
+
+// [END aiplatform_create_batch_prediction_job_sample]

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

@@ -0,0 +1,96 @@
+/*
+ * 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 aiplatform;
+
+// [START aiplatform_create_batch_prediction_job_video_action_recognition_sample]
+import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob;
+import com.google.cloud.aiplatform.v1beta1.GcsDestination;
+import com.google.cloud.aiplatform.v1beta1.GcsSource;
+import com.google.cloud.aiplatform.v1beta1.JobServiceClient;
+import com.google.cloud.aiplatform.v1beta1.JobServiceSettings;
+import com.google.cloud.aiplatform.v1beta1.LocationName;
+import com.google.gson.JsonObject;
+import com.google.protobuf.Value;
+import com.google.protobuf.util.JsonFormat;
+import java.io.IOException;
+
+public class CreateBatchPredictionJobVideoActionRecognitionSample {
+
+  public static void main(String[] args) throws IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String project = "PROJECT";
+    String displayName = "DISPLAY_NAME";
+    String model = "MODEL";
+    String gcsSourceUri = "GCS_SOURCE_URI";
+    String gcsDestinationOutputUriPrefix = "GCS_DESTINATION_OUTPUT_URI_PREFIX";
+    createBatchPredictionJobVideoActionRecognitionSample(
+        project, displayName, model, gcsSourceUri, gcsDestinationOutputUriPrefix);
+  }
+
+  static void createBatchPredictionJobVideoActionRecognitionSample(
+      String project,
+      String displayName,
+      String model,
+      String gcsSourceUri,
+      String gcsDestinationOutputUriPrefix)
+      throws IOException {
+    JobServiceSettings settings =
+        JobServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+    String location = "us-central1";
+
+    // Initialize client that will be used to send requests. This client only needs to be created
+    // once, and can be reused for multiple requests. After completing all of your requests, call
+    // the "close" method on the client to safely clean up any remaining background resources.
+    try (JobServiceClient client = JobServiceClient.create(settings)) {
+      JsonObject jsonModelParameters = new JsonObject();
+      jsonModelParameters.addProperty("confidenceThreshold", 0.5);
+      Value.Builder modelParametersBuilder = Value.newBuilder();
+      JsonFormat.parser().merge(jsonModelParameters.toString(), modelParametersBuilder);
+      Value modelParameters = modelParametersBuilder.build();
+      GcsSource gcsSource = GcsSource.newBuilder().addUris(gcsSourceUri).build();
+      BatchPredictionJob.InputConfig inputConfig =
+          BatchPredictionJob.InputConfig.newBuilder()
+              .setInstancesFormat("jsonl")
+              .setGcsSource(gcsSource)
+              .build();
+      GcsDestination gcsDestination =
+          GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
+      BatchPredictionJob.OutputConfig outputConfig =
+          BatchPredictionJob.OutputConfig.newBuilder()
+              .setPredictionsFormat("jsonl")
+              .setGcsDestination(gcsDestination)
+              .build();
+      BatchPredictionJob batchPredictionJob =
+          BatchPredictionJob.newBuilder()
+              .setDisplayName(displayName)
+              // Format: 'projects/{project}/locations/{location}/models/{model_id}'
+              .setModel(model)
+              .setModelParameters(modelParameters)
+              .setInputConfig(inputConfig)
+              .setOutputConfig(outputConfig)
+              .build();
+      LocationName parent = LocationName.of(project, location);
+      BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
+      System.out.format("response: %s\n", response);
+      System.out.format("\tName: %s\n", response.getName());
+    }
+  }
+}
+
+// [END aiplatform_create_batch_prediction_job_video_action_recognition_sample]