samples: ucaip sample batch 2 of 6 (#15)

batch 2 of 6

aiplatform/snippets/format.sh

@@ -0,0 +1,6 @@
+touch format.sh
+ chmod +rx format.sh
+
+git add .
+git reset HEAD format.sh
+./format.sh

aiplatform/snippets/pom.xml

@@ -30,16 +30,6 @@
       <version>0.0.1-SNAPSHOT</version>
     </dependency>
     <!-- [END aiplatform_install_with_bom] -->
-    <dependency>
-      <groupId>com.google.protobuf</groupId>
-      <artifactId>protobuf-java-util</artifactId>
-      <version>4.0.0-rc-1</version>
-    </dependency>
-    <dependency>
-      <groupId>com.google.cloud</groupId>
-      <artifactId>google-cloud-storage</artifactId>
-      <version>1.111.0</version>
-    </dependency>
     <dependency>
       <groupId>com.google.cloud</groupId>
       <artifactId>google-cloud-storage</artifactId>
@@ -50,8 +40,6 @@
       <artifactId>protobuf-java-util</artifactId>
       <version>4.0.0-rc-1</version>
     </dependency>
-
-
     <dependency>
       <groupId>junit</groupId>
       <artifactId>junit</artifactId>

aiplatform/snippets/src/main/java/aiplatform/CancelBatchPredictionJobSample.java

@@ -0,0 +1,56 @@
+/*
+ * 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_cancel_batch_prediction_job_sample]
+
+import com.google.cloud.aiplatform.v1beta1.BatchPredictionJobName;
+import com.google.cloud.aiplatform.v1beta1.JobServiceClient;
+import com.google.cloud.aiplatform.v1beta1.JobServiceSettings;
+import java.io.IOException;
+
+public class CancelBatchPredictionJobSample {
+
+  public static void main(String[] args) throws IOException {
+    // TODO(developer): Replace these variables before running the sample.
+    String project = "YOUR_PROJECT_ID";
+    String batchPredictionJobId = "YOUR_BATCH_PREDICTION_JOB_ID";
+    cancelBatchPredictionJobSample(project, batchPredictionJobId);
+  }
+
+  static void cancelBatchPredictionJobSample(String project, String batchPredictionJobId)
+      throws IOException {
+    JobServiceSettings jobServiceSettings =
+        JobServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+
+    // 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 jobServiceClient = JobServiceClient.create(jobServiceSettings)) {
+      String location = "us-central1";
+      BatchPredictionJobName batchPredictionJobName =
+          BatchPredictionJobName.of(project, location, batchPredictionJobId);
+
+      jobServiceClient.cancelBatchPredictionJob(batchPredictionJobName);
+
+      System.out.println("Cancelled the Batch Prediction Job");
+    }
+  }
+}
+// [END aiplatform_cancel_batch_prediction_job_sample]

aiplatform/snippets/src/main/java/aiplatform/CreateBatchPredictionJobVideoClassificationSample.java

@@ -0,0 +1,200 @@
+/*
+ * 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_classification_sample]
+
+import com.google.cloud.aiplatform.v1beta1.BatchDedicatedResources;
+import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob;
+import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob.InputConfig;
+import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputConfig;
+import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob.OutputInfo;
+import com.google.cloud.aiplatform.v1beta1.BigQueryDestination;
+import com.google.cloud.aiplatform.v1beta1.BigQuerySource;
+import com.google.cloud.aiplatform.v1beta1.CompletionStats;
+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.cloud.aiplatform.v1beta1.ManualBatchTuningParameters;
+import com.google.cloud.aiplatform.v1beta1.ModelName;
+import com.google.cloud.aiplatform.v1beta1.ResourcesConsumed;
+import com.google.protobuf.Any;
+import com.google.protobuf.Value;
+import com.google.protobuf.util.JsonFormat;
+import com.google.rpc.Status;
+import java.io.IOException;
+import java.util.List;
+
+public class CreateBatchPredictionJobVideoClassificationSample {
+
+  public static void main(String[] args) throws IOException {
+    String batchPredictionDisplayName = "YOUR_VIDEO_CLASSIFICATION_DISPLAY_NAME";
+    String modelId = "YOUR_MODEL_ID";
+    String gcsSourceUri =
+        "gs://YOUR_GCS_SOURCE_BUCKET/path_to_your_video_source/[file.csv/file.jsonl]";
+    String gcsDestinationOutputUriPrefix =
+        "gs://YOUR_GCS_SOURCE_BUCKET/destination_output_uri_prefix/";
+    String project = "YOUR_PROJECT_ID";
+    createBatchPredictionJobVideoClassification(
+        batchPredictionDisplayName, modelId, gcsSourceUri, gcsDestinationOutputUriPrefix, project);
+  }
+
+  static void createBatchPredictionJobVideoClassification(
+      String batchPredictionDisplayName,
+      String modelId,
+      String gcsSourceUri,
+      String gcsDestinationOutputUriPrefix,
+      String project)
+      throws IOException {
+    JobServiceSettings jobServiceSettings =
+        JobServiceSettings.newBuilder()
+            .setEndpoint("us-central1-aiplatform.googleapis.com:443")
+            .build();
+
+    // 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 jobServiceClient = JobServiceClient.create(jobServiceSettings)) {
+      String location = "us-central1";
+      LocationName locationName = LocationName.of(project, location);
+
+      String jsonString =
+          "{\"confidenceThreshold\": 0.5,\"maxPredictions\": 10000,\"segmentClassification\":"
+              + " True,\"shotClassification\": True,\"oneSecIntervalClassification\": True}";
+      Value.Builder modelParameters = Value.newBuilder();
+      JsonFormat.parser().merge(jsonString, modelParameters);
+
+      ModelName modelName = ModelName.of(project, location, modelId);
+      GcsSource.Builder gcsSource = GcsSource.newBuilder();
+      gcsSource.addUris(gcsSourceUri);
+      InputConfig inputConfig =
+          InputConfig.newBuilder().setInstancesFormat("jsonl").setGcsSource(gcsSource).build();
+
+      GcsDestination gcsDestination =
+          GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
+      OutputConfig outputConfig =
+          OutputConfig.newBuilder()
+              .setPredictionsFormat("jsonl")
+              .setGcsDestination(gcsDestination)
+              .build();
+
+      BatchPredictionJob batchPredictionJob =
+          BatchPredictionJob.newBuilder()
+              .setDisplayName(batchPredictionDisplayName)
+              .setModel(modelName.toString())
+              .setModelParameters(modelParameters)
+              .setInputConfig(inputConfig)
+              .setOutputConfig(outputConfig)
+              .build();
+      BatchPredictionJob batchPredictionJobResponse =
+          jobServiceClient.createBatchPredictionJob(locationName, batchPredictionJob);
+
+      System.out.println("Create Batch Prediction Job Video Classification Response");
+      System.out.format("\tName: %s\n", batchPredictionJobResponse.getName());
+      System.out.format("\tDisplay Name: %s\n", batchPredictionJobResponse.getDisplayName());
+      System.out.format("\tModel %s\n", batchPredictionJobResponse.getModel());
+      System.out.format(
+          "\tModel Parameters: %s\n", batchPredictionJobResponse.getModelParameters());
+      System.out.format(
+          "\tGenerate Explanation: %s\n", batchPredictionJobResponse.getGenerateExplanation());
+
+      System.out.format("\tState: %s\n", batchPredictionJobResponse.getState());
+      System.out.format("\tCreate Time: %s\n", batchPredictionJobResponse.getCreateTime());
+      System.out.format("\tStart Time: %s\n", batchPredictionJobResponse.getStartTime());
+      System.out.format("\tEnd Time: %s\n", batchPredictionJobResponse.getEndTime());
+      System.out.format("\tUpdate Time: %s\n", batchPredictionJobResponse.getUpdateTime());
+      System.out.format("\tLabels: %s\n", batchPredictionJobResponse.getLabelsMap());
+
+      InputConfig inputConfigResponse = batchPredictionJobResponse.getInputConfig();
+      System.out.println("\tInput Config");
+      System.out.format("\t\tInstances Format: %s\n", inputConfigResponse.getInstancesFormat());
+
+      GcsSource gcsSourceResponse = inputConfigResponse.getGcsSource();
+      System.out.println("\t\tGcs Source");
+      System.out.format("\t\t\tUris %s\n", gcsSourceResponse.getUrisList());
+
+      BigQuerySource bigQuerySource = inputConfigResponse.getBigquerySource();
+      System.out.println("\t\tBigquery Source");
+      System.out.format("\t\t\tInput_uri: %s\n", bigQuerySource.getInputUri());
+
+      OutputConfig outputConfigResponse = batchPredictionJobResponse.getOutputConfig();
+      System.out.println("\tOutput Config");
+      System.out.format(
+          "\t\tPredictions Format: %s\n", outputConfigResponse.getPredictionsFormat());
+
+      GcsDestination gcsDestinationResponse = outputConfigResponse.getGcsDestination();
+      System.out.println("\t\tGcs Destination");
+      System.out.format(
+          "\t\t\tOutput Uri Prefix: %s\n", gcsDestinationResponse.getOutputUriPrefix());
+
+      BigQueryDestination bigQueryDestination = outputConfigResponse.getBigqueryDestination();
+      System.out.println("\t\tBig Query Destination");
+      System.out.format("\t\t\tOutput Uri: %s\n", bigQueryDestination.getOutputUri());
+
+      BatchDedicatedResources batchDedicatedResources =
+          batchPredictionJobResponse.getDedicatedResources();
+      System.out.println("\tBatch Dedicated Resources");
+      System.out.format(
+          "\t\tStarting Replica Count: %s\n", batchDedicatedResources.getStartingReplicaCount());
+      System.out.format(
+          "\t\tMax Replica Count: %s\n", batchDedicatedResources.getMaxReplicaCount());
+
+      MachineSpec machineSpec = batchDedicatedResources.getMachineSpec();
+      System.out.println("\t\tMachine Spec");
+      System.out.format("\t\t\tMachine Type: %s\n", machineSpec.getMachineType());
+      System.out.format("\t\t\tAccelerator Type: %s\n", machineSpec.getAcceleratorType());
+      System.out.format("\t\t\tAccelerator Count: %s\n", machineSpec.getAcceleratorCount());
+
+      ManualBatchTuningParameters manualBatchTuningParameters =
+          batchPredictionJobResponse.getManualBatchTuningParameters();
+      System.out.println("\tManual Batch Tuning Parameters");
+      System.out.format("\t\tBatch Size: %s\n", manualBatchTuningParameters.getBatchSize());
+
+      OutputInfo outputInfo = batchPredictionJobResponse.getOutputInfo();
+      System.out.println("\tOutput Info");
+      System.out.format("\t\tGcs Output Directory: %s\n", outputInfo.getGcsOutputDirectory());
+      System.out.format("\t\tBigquery Output Dataset: %s\n", outputInfo.getBigqueryOutputDataset());
+
+      Status status = batchPredictionJobResponse.getError();
+      System.out.println("\tError");
+      System.out.format("\t\tCode: %s\n", status.getCode());
+      System.out.format("\t\tMessage: %s\n", status.getMessage());
+      List<Any> details = status.getDetailsList();
+
+      for (Status partialFailure : batchPredictionJobResponse.getPartialFailuresList()) {
+        System.out.println("\tPartial Failure");
+        System.out.format("\t\tCode: %s\n", partialFailure.getCode());
+        System.out.format("\t\tMessage: %s\n", partialFailure.getMessage());
+        List<Any> partialFailureDetailsList = partialFailure.getDetailsList();
+      }
+
+      ResourcesConsumed resourcesConsumed = batchPredictionJobResponse.getResourcesConsumed();
+      System.out.println("\tResources Consumed");
+      System.out.format("\t\tReplica Hours: %s\n", resourcesConsumed.getReplicaHours());
+
+      CompletionStats completionStats = batchPredictionJobResponse.getCompletionStats();
+      System.out.println("\tCompletion Stats");
+      System.out.format("\t\tSuccessful Count: %s\n", completionStats.getSuccessfulCount());
+      System.out.format("\t\tFailed Count: %s\n", completionStats.getFailedCount());
+      System.out.format("\t\tIncomplete Count: %s\n", completionStats.getIncompleteCount());
+    }
+  }
+}
+// [END aiplatform_create_batch_prediction_job_video_classification_sample]