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samples: adds custom model, action recognition samples and tests (#111)
* samples: adds custom mode, action recognition samples and tests * fix: refactor to use Gson
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‎aiplatform/snippets/pom.xml

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<artifactId>protobuf-java-util</artifactId>
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<version>4.0.0-rc-2</version>
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</dependency>
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<dependency>
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<groupId>com.google.code.gson</groupId>
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<artifactId>gson</artifactId>
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<version>2.8.6</version>
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</dependency>
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<dependency>
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<groupId>junit</groupId>
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<artifactId>junit</artifactId>

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

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/*
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* Copyright 2020 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 aiplatform_create_batch_prediction_job_bigquery_sample]
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import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob;
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import com.google.cloud.aiplatform.v1beta1.BigQueryDestination;
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import com.google.cloud.aiplatform.v1beta1.BigQuerySource;
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import com.google.cloud.aiplatform.v1beta1.JobServiceClient;
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import com.google.cloud.aiplatform.v1beta1.JobServiceSettings;
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import com.google.cloud.aiplatform.v1beta1.LocationName;
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import com.google.cloud.aiplatform.v1beta1.ModelName;
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import com.google.gson.JsonObject;
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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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public class CreateBatchPredictionJobBigquerySample {
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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 project = "PROJECT";
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String displayName = "DISPLAY_NAME";
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String modelName = "MODEL_NAME";
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String instancesFormat = "INSTANCES_FORMAT";
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String bigquerySourceInputUri = "BIGQUERY_SOURCE_INPUT_URI";
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String predictionsFormat = "PREDICTIONS_FORMAT";
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String bigqueryDestinationOutputUri = "BIGQUERY_DESTINATION_OUTPUT_URI";
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createBatchPredictionJobBigquerySample(
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project,
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displayName,
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modelName,
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instancesFormat,
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bigquerySourceInputUri,
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predictionsFormat,
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bigqueryDestinationOutputUri);
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}
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static void createBatchPredictionJobBigquerySample(
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String project,
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String displayName,
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String model,
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String instancesFormat,
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String bigquerySourceInputUri,
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String predictionsFormat,
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String bigqueryDestinationOutputUri)
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throws IOException {
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JobServiceSettings settings =
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JobServiceSettings.newBuilder()
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.setEndpoint("us-central1-aiplatform.googleapis.com:443")
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.build();
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String location = "us-central1";
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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. After completing all of your requests, call
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// the "close" method on the client to safely clean up any remaining background resources.
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try (JobServiceClient client = JobServiceClient.create(settings)) {
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JsonObject jsonModelParameters = new JsonObject();
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Value.Builder modelParametersBuilder = Value.newBuilder();
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JsonFormat.parser().merge(jsonModelParameters.toString(), modelParametersBuilder);
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Value modelParameters = modelParametersBuilder.build();
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BigQuerySource bigquerySource =
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BigQuerySource.newBuilder().setInputUri(bigquerySourceInputUri).build();
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BatchPredictionJob.InputConfig inputConfig =
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BatchPredictionJob.InputConfig.newBuilder()
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.setInstancesFormat(instancesFormat)
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.setBigquerySource(bigquerySource)
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.build();
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BigQueryDestination bigqueryDestination =
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BigQueryDestination.newBuilder().setOutputUri(bigqueryDestinationOutputUri).build();
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BatchPredictionJob.OutputConfig outputConfig =
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BatchPredictionJob.OutputConfig.newBuilder()
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.setPredictionsFormat(predictionsFormat)
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.setBigqueryDestination(bigqueryDestination)
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.build();
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String modelName = ModelName.of(project, location, model).toString();
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BatchPredictionJob batchPredictionJob =
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BatchPredictionJob.newBuilder()
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.setDisplayName(displayName)
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.setModel(modelName)
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.setModelParameters(modelParameters)
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.setInputConfig(inputConfig)
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.setOutputConfig(outputConfig)
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// optional
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.setGenerateExplanation(true)
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.build();
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LocationName parent = LocationName.of(project, location);
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BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
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System.out.format("response: %s\n", response);
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System.out.format("\tName: %s\n", response.getName());
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}
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}
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}
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// [END aiplatform_create_batch_prediction_job_bigquery_sample]

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

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/*
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* Copyright 2020 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 aiplatform_create_batch_prediction_job_sample]
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import com.google.cloud.aiplatform.v1beta1.AcceleratorType;
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import com.google.cloud.aiplatform.v1beta1.BatchDedicatedResources;
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import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob;
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import com.google.cloud.aiplatform.v1beta1.GcsDestination;
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import com.google.cloud.aiplatform.v1beta1.GcsSource;
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import com.google.cloud.aiplatform.v1beta1.JobServiceClient;
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import com.google.cloud.aiplatform.v1beta1.JobServiceSettings;
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import com.google.cloud.aiplatform.v1beta1.LocationName;
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import com.google.cloud.aiplatform.v1beta1.MachineSpec;
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import com.google.cloud.aiplatform.v1beta1.ModelName;
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import com.google.gson.JsonObject;
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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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public class CreateBatchPredictionJobSample {
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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 project = "PROJECT";
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String displayName = "DISPLAY_NAME";
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String modelName = "MODEL_NAME";
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String instancesFormat = "INSTANCES_FORMAT";
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String gcsSourceUri = "GCS_SOURCE_URI";
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String predictionsFormat = "PREDICTIONS_FORMAT";
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String gcsDestinationOutputUriPrefix = "GCS_DESTINATION_OUTPUT_URI_PREFIX";
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createBatchPredictionJobSample(
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project,
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displayName,
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modelName,
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instancesFormat,
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gcsSourceUri,
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predictionsFormat,
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gcsDestinationOutputUriPrefix);
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}
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static void createBatchPredictionJobSample(
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String project,
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String displayName,
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String model,
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String instancesFormat,
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String gcsSourceUri,
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String predictionsFormat,
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String gcsDestinationOutputUriPrefix)
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throws IOException {
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JobServiceSettings settings =
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JobServiceSettings.newBuilder()
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.setEndpoint("us-central1-aiplatform.googleapis.com:443")
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.build();
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String location = "us-central1";
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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. After completing all of your requests, call
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// the "close" method on the client to safely clean up any remaining background resources.
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try (JobServiceClient client = JobServiceClient.create(settings)) {
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// Passing in an empty Value object for model parameters
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JsonObject jsonModelParameters = new JsonObject();
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Value.Builder modelParametersBuilder = Value.newBuilder();
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JsonFormat.parser().merge(jsonModelParameters.toString(), modelParametersBuilder);
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Value modelParameters = modelParametersBuilder.build();
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GcsSource gcsSource = GcsSource.newBuilder().addUris(gcsSourceUri).build();
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BatchPredictionJob.InputConfig inputConfig =
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BatchPredictionJob.InputConfig.newBuilder()
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.setInstancesFormat(instancesFormat)
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.setGcsSource(gcsSource)
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.build();
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GcsDestination gcsDestination =
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GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
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BatchPredictionJob.OutputConfig outputConfig =
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BatchPredictionJob.OutputConfig.newBuilder()
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.setPredictionsFormat(predictionsFormat)
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.setGcsDestination(gcsDestination)
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.build();
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MachineSpec machineSpec =
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MachineSpec.newBuilder()
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.setMachineType("n1-standard-2")
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.setAcceleratorType(AcceleratorType.NVIDIA_TESLA_K80)
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.setAcceleratorCount(1)
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.build();
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BatchDedicatedResources dedicatedResources =
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BatchDedicatedResources.newBuilder()
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.setMachineSpec(machineSpec)
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.setStartingReplicaCount(1)
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.setMaxReplicaCount(1)
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.build();
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String modelName = ModelName.of(project, location, model).toString();
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BatchPredictionJob batchPredictionJob =
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BatchPredictionJob.newBuilder()
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.setDisplayName(displayName)
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.setModel(modelName)
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.setModelParameters(modelParameters)
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.setInputConfig(inputConfig)
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.setOutputConfig(outputConfig)
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.setDedicatedResources(dedicatedResources)
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.build();
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LocationName parent = LocationName.of(project, location);
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BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
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System.out.format("response: %s\n", response);
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System.out.format("\tName: %s\n", response.getName());
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}
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}
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}
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// [END aiplatform_create_batch_prediction_job_sample]

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

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/*
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* Copyright 2020 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 aiplatform_create_batch_prediction_job_video_action_recognition_sample]
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import com.google.cloud.aiplatform.v1beta1.BatchPredictionJob;
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import com.google.cloud.aiplatform.v1beta1.GcsDestination;
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import com.google.cloud.aiplatform.v1beta1.GcsSource;
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import com.google.cloud.aiplatform.v1beta1.JobServiceClient;
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import com.google.cloud.aiplatform.v1beta1.JobServiceSettings;
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import com.google.cloud.aiplatform.v1beta1.LocationName;
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import com.google.cloud.aiplatform.v1beta1.ModelName;
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import com.google.gson.JsonObject;
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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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public class CreateBatchPredictionJobVideoActionRecognitionSample {
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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 project = "PROJECT";
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String displayName = "DISPLAY_NAME";
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String model = "MODEL";
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String gcsSourceUri = "GCS_SOURCE_URI";
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String gcsDestinationOutputUriPrefix = "GCS_DESTINATION_OUTPUT_URI_PREFIX";
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createBatchPredictionJobVideoActionRecognitionSample(
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project, displayName, model, gcsSourceUri, gcsDestinationOutputUriPrefix);
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}
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static void createBatchPredictionJobVideoActionRecognitionSample(
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String project,
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String displayName,
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String model,
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String gcsSourceUri,
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String gcsDestinationOutputUriPrefix)
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throws IOException {
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JobServiceSettings settings =
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JobServiceSettings.newBuilder()
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.setEndpoint("us-central1-aiplatform.googleapis.com:443")
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.build();
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String location = "us-central1";
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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. After completing all of your requests, call
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// the "close" method on the client to safely clean up any remaining background resources.
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try (JobServiceClient client = JobServiceClient.create(settings)) {
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JsonObject jsonModelParameters = new JsonObject();
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jsonModelParameters.addProperty("confidenceThreshold", 0.5);
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Value.Builder modelParametersBuilder = Value.newBuilder();
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JsonFormat.parser().merge(jsonModelParameters.toString(), modelParametersBuilder);
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Value modelParameters = modelParametersBuilder.build();
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GcsSource gcsSource = GcsSource.newBuilder().addUris(gcsSourceUri).build();
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BatchPredictionJob.InputConfig inputConfig =
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BatchPredictionJob.InputConfig.newBuilder()
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.setInstancesFormat("jsonl")
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.setGcsSource(gcsSource)
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.build();
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GcsDestination gcsDestination =
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GcsDestination.newBuilder().setOutputUriPrefix(gcsDestinationOutputUriPrefix).build();
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BatchPredictionJob.OutputConfig outputConfig =
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BatchPredictionJob.OutputConfig.newBuilder()
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.setPredictionsFormat("jsonl")
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.setGcsDestination(gcsDestination)
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.build();
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String modelName = ModelName.of(project, location, model).toString();
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BatchPredictionJob batchPredictionJob =
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BatchPredictionJob.newBuilder()
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.setDisplayName(displayName)
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.setModel(modelName)
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.setModelParameters(modelParameters)
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.setInputConfig(inputConfig)
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.setOutputConfig(outputConfig)
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.build();
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LocationName parent = LocationName.of(project, location);
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BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
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System.out.format("response: %s\n", response);
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System.out.format("\tName: %s\n", response.getName());
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}
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}
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}
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// [END aiplatform_create_batch_prediction_job_video_action_recognition_sample]

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