use of com.google.cloud.aiplatform.v1.JobServiceSettings in project java-aiplatform by googleapis.
the class CreateBatchPredictionJobTextSentimentAnalysisSample method createBatchPredictionJobTextSentimentAnalysisSample.
static void createBatchPredictionJobTextSentimentAnalysisSample(String project, String location, String displayName, String modelId, String gcsSourceUri, String gcsDestinationOutputUriPrefix) throws IOException {
// The AI Platform services require regional API endpoints.
JobServiceSettings settings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
// the "close" method on the client to safely clean up any remaining background resources.
try (JobServiceClient client = JobServiceClient.create(settings)) {
try {
String modelName = ModelName.of(project, location, modelId).toString();
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).setModel(modelName).setInputConfig(inputConfig).setOutputConfig(outputConfig).build();
LocationName parent = LocationName.of(project, location);
BatchPredictionJob response = client.createBatchPredictionJob(parent, batchPredictionJob);
System.out.format("response: %s\n", response);
} catch (ApiException ex) {
System.out.format("Exception: %s\n", ex.getLocalizedMessage());
}
}
}
use of com.google.cloud.aiplatform.v1.JobServiceSettings in project java-aiplatform by googleapis.
the class CreateBatchPredictionJobVideoClassificationSample method createBatchPredictionJobVideoClassification.
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();
// 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);
VideoClassificationPredictionParams modelParamsObj = VideoClassificationPredictionParams.newBuilder().setConfidenceThreshold(((float) 0.5)).setMaxPredictions(10000).setSegmentClassification(true).setShotClassification(true).setOneSecIntervalClassification(true).build();
Value modelParameters = ValueConverter.toValue(modelParamsObj);
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("\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());
}
}
use of com.google.cloud.aiplatform.v1.JobServiceSettings in project java-aiplatform by googleapis.
the class CreateBatchPredictionJobVideoObjectTrackingSample method batchPredictionJobVideoObjectTracking.
static void batchPredictionJobVideoObjectTracking(String batchPredictionDisplayName, String modelId, String gcsSourceUri, String gcsDestinationOutputUriPrefix, String project) throws IOException {
JobServiceSettings jobServiceSettings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
// 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);
ModelName modelName = ModelName.of(project, location, modelId);
VideoObjectTrackingPredictionParams modelParamsObj = VideoObjectTrackingPredictionParams.newBuilder().setConfidenceThreshold(((float) 0.5)).build();
Value modelParameters = ValueConverter.toValue(modelParamsObj);
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 Object Tracking 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("\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());
}
}
use of com.google.cloud.aiplatform.v1.JobServiceSettings in project java-aiplatform by googleapis.
the class CreateDataLabelingJobActiveLearningSample method createDataLabelingJobActiveLearningSample.
static void createDataLabelingJobActiveLearningSample(String project, String displayName, String dataset, String instructionUri, String inputsSchemaUri, String annotationSpec) throws IOException {
JobServiceSettings settings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
String location = "us-central1";
// the "close" method on the client to safely clean up any remaining background resources.
try (JobServiceClient client = JobServiceClient.create(settings)) {
JsonArray jsonAnnotationSpecs = new JsonArray();
jsonAnnotationSpecs.add(annotationSpec);
JsonObject jsonInputs = new JsonObject();
jsonInputs.add("annotation_specs", jsonAnnotationSpecs);
Value.Builder inputsBuilder = Value.newBuilder();
JsonFormat.parser().merge(jsonInputs.toString(), inputsBuilder);
Value inputs = inputsBuilder.build();
ActiveLearningConfig activeLearningConfig = ActiveLearningConfig.newBuilder().setMaxDataItemCount(1).build();
String datasetName = DatasetName.of(project, location, dataset).toString();
DataLabelingJob dataLabelingJob = DataLabelingJob.newBuilder().setDisplayName(displayName).addDatasets(datasetName).setLabelerCount(1).setInstructionUri(instructionUri).setInputsSchemaUri(inputsSchemaUri).setInputs(inputs).putAnnotationLabels("aiplatform.googleapis.com/annotation_set_name", "data_labeling_job_active_learning").setActiveLearningConfig(activeLearningConfig).build();
LocationName parent = LocationName.of(project, location);
DataLabelingJob response = client.createDataLabelingJob(parent, dataLabelingJob);
System.out.format("response: %s\n", response);
System.out.format("Name: %s\n", response.getName());
}
}
use of com.google.cloud.aiplatform.v1.JobServiceSettings in project java-aiplatform by googleapis.
the class CreateDataLabelingJobImageSample method createDataLabelingJobImage.
static void createDataLabelingJobImage(String project, String displayName, String datasetId, String instructionUri, String annotationSpec) throws IOException {
JobServiceSettings jobServiceSettings = JobServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
// 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 = "{\"annotation_specs\": [ " + annotationSpec + "]}";
Value.Builder annotationSpecValue = Value.newBuilder();
JsonFormat.parser().merge(jsonString, annotationSpecValue);
DatasetName datasetName = DatasetName.of(project, location, datasetId);
DataLabelingJob dataLabelingJob = DataLabelingJob.newBuilder().setDisplayName(displayName).setLabelerCount(1).setInstructionUri(instructionUri).setInputsSchemaUri("gs://google-cloud-aiplatform/schema/datalabelingjob/inputs/" + "image_classification.yaml").addDatasets(datasetName.toString()).setInputs(annotationSpecValue).putAnnotationLabels("aiplatform.googleapis.com/annotation_set_name", "my_test_saved_query").build();
DataLabelingJob dataLabelingJobResponse = jobServiceClient.createDataLabelingJob(locationName, dataLabelingJob);
System.out.println("Create Data Labeling Job Image Response");
System.out.format("\tName: %s\n", dataLabelingJobResponse.getName());
System.out.format("\tDisplay Name: %s\n", dataLabelingJobResponse.getDisplayName());
System.out.format("\tDatasets: %s\n", dataLabelingJobResponse.getDatasetsList());
System.out.format("\tLabeler Count: %s\n", dataLabelingJobResponse.getLabelerCount());
System.out.format("\tInstruction Uri: %s\n", dataLabelingJobResponse.getInstructionUri());
System.out.format("\tInputs Schema Uri: %s\n", dataLabelingJobResponse.getInputsSchemaUri());
System.out.format("\tInputs: %s\n", dataLabelingJobResponse.getInputs());
System.out.format("\tState: %s\n", dataLabelingJobResponse.getState());
System.out.format("\tLabeling Progress: %s\n", dataLabelingJobResponse.getLabelingProgress());
System.out.format("\tCreate Time: %s\n", dataLabelingJobResponse.getCreateTime());
System.out.format("\tUpdate Time: %s\n", dataLabelingJobResponse.getUpdateTime());
System.out.format("\tLabels: %s\n", dataLabelingJobResponse.getLabelsMap());
System.out.format("\tSpecialist Pools: %s\n", dataLabelingJobResponse.getSpecialistPoolsList());
for (Map.Entry<String, String> annotationLabelMap : dataLabelingJobResponse.getAnnotationLabelsMap().entrySet()) {
System.out.println("\tAnnotation Level");
System.out.format("\t\tkey: %s\n", annotationLabelMap.getKey());
System.out.format("\t\tvalue: %s\n", annotationLabelMap.getValue());
}
Money money = dataLabelingJobResponse.getCurrentSpend();
System.out.println("\tCurrent Spend");
System.out.format("\t\tCurrency Code: %s\n", money.getCurrencyCode());
System.out.format("\t\tUnits: %s\n", money.getUnits());
System.out.format("\t\tNanos: %s\n", money.getNanos());
}
}
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