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samples: adds custom model, action recognition samples and tests (#111)
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* samples: adds custom mode, action recognition samples and tests

* fix: refactor to use Gson
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telpirion authored Dec 16, 2020
1 parent fc550d9 commit d6602ce
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5 changes: 5 additions & 0 deletions aiplatform/snippets/pom.xml
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<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>
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/*
* 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.cloud.aiplatform.v1beta1.ModelName;
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 model,
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();
String modelName = ModelName.of(project, location, model).toString();
BatchPredictionJob batchPredictionJob =
BatchPredictionJob.newBuilder()
.setDisplayName(displayName)
.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]
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/*
* 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.cloud.aiplatform.v1beta1.ModelName;
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 model,
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();
String modelName = ModelName.of(project, location, model).toString();
BatchPredictionJob batchPredictionJob =
BatchPredictionJob.newBuilder()
.setDisplayName(displayName)
.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]
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/*
* 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.cloud.aiplatform.v1beta1.ModelName;
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();

String modelName = ModelName.of(project, location, model).toString();

BatchPredictionJob batchPredictionJob =
BatchPredictionJob.newBuilder()
.setDisplayName(displayName)
.setModel(modelName)
.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]
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