use of com.google.cloud.aiplatform.v1.PipelineServiceClient in project java-aiplatform by googleapis.
the class GetTrainingPipelineSample method getTrainingPipeline.
static void getTrainingPipeline(String project, String trainingPipelineId) throws IOException {
PipelineServiceSettings pipelineServiceSettings = PipelineServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
// the "close" method on the client to safely clean up any remaining background resources.
try (PipelineServiceClient pipelineServiceClient = PipelineServiceClient.create(pipelineServiceSettings)) {
String location = "us-central1";
TrainingPipelineName trainingPipelineName = TrainingPipelineName.of(project, location, trainingPipelineId);
TrainingPipeline trainingPipelineResponse = pipelineServiceClient.getTrainingPipeline(trainingPipelineName);
System.out.println("Get Training Pipeline Response");
System.out.format("\tName: %s\n", trainingPipelineResponse.getName());
System.out.format("\tDisplay Name: %s\n", trainingPipelineResponse.getDisplayName());
System.out.format("\tTraining Task Definition: %s\n", trainingPipelineResponse.getTrainingTaskDefinition());
System.out.format("\tTraining Task Inputs: %s\n", trainingPipelineResponse.getTrainingTaskInputs());
System.out.format("\tTraining Task Metadata: %s\n", trainingPipelineResponse.getTrainingTaskMetadata());
System.out.format("\tState: %s\n", trainingPipelineResponse.getState());
System.out.format("\tCreate Time: %s\n", trainingPipelineResponse.getCreateTime());
System.out.format("\tStart Time: %s\n", trainingPipelineResponse.getStartTime());
System.out.format("\tEnd Time: %s\n", trainingPipelineResponse.getEndTime());
System.out.format("\tUpdate Time: %s\n", trainingPipelineResponse.getUpdateTime());
System.out.format("\tLabels: %s\n", trainingPipelineResponse.getLabelsMap());
InputDataConfig inputDataConfig = trainingPipelineResponse.getInputDataConfig();
System.out.println("\tInput Data Config");
System.out.format("\t\tDataset Id: %s\n", inputDataConfig.getDatasetId());
System.out.format("\t\tAnnotations Filter: %s\n", inputDataConfig.getAnnotationsFilter());
FractionSplit fractionSplit = inputDataConfig.getFractionSplit();
System.out.println("\t\tFraction Split");
System.out.format("\t\t\tTraining Fraction: %s\n", fractionSplit.getTrainingFraction());
System.out.format("\t\t\tValidation Fraction: %s\n", fractionSplit.getValidationFraction());
System.out.format("\t\t\tTest Fraction: %s\n", fractionSplit.getTestFraction());
FilterSplit filterSplit = inputDataConfig.getFilterSplit();
System.out.println("\t\tFilter Split");
System.out.format("\t\t\tTraining Filter: %s\n", filterSplit.getTrainingFilter());
System.out.format("\t\t\tValidation Filter: %s\n", filterSplit.getValidationFilter());
System.out.format("\t\t\tTest Filter: %s\n", filterSplit.getTestFilter());
PredefinedSplit predefinedSplit = inputDataConfig.getPredefinedSplit();
System.out.println("\t\tPredefined Split");
System.out.format("\t\t\tKey: %s\n", predefinedSplit.getKey());
TimestampSplit timestampSplit = inputDataConfig.getTimestampSplit();
System.out.println("\t\tTimestamp Split");
System.out.format("\t\t\tTraining Fraction: %s\n", timestampSplit.getTrainingFraction());
System.out.format("\t\t\tTest Fraction: %s\n", timestampSplit.getTestFraction());
System.out.format("\t\t\tValidation Fraction: %s\n", timestampSplit.getValidationFraction());
System.out.format("\t\t\tKey: %s\n", timestampSplit.getKey());
Model modelResponse = trainingPipelineResponse.getModelToUpload();
System.out.println("\t\tModel to upload");
System.out.format("\t\tName: %s\n", modelResponse.getName());
System.out.format("\t\tDisplay Name: %s\n", modelResponse.getDisplayName());
System.out.format("\t\tDescription: %s\n", modelResponse.getDescription());
System.out.format("\t\tMetadata Schema Uri: %s\n", modelResponse.getMetadataSchemaUri());
System.out.format("\t\tMeta Data: %s\n", modelResponse.getMetadata());
System.out.format("\t\tTraining Pipeline: %s\n", modelResponse.getTrainingPipeline());
System.out.format("\t\tArtifact Uri: %s\n", modelResponse.getArtifactUri());
System.out.format("\t\tSupported Deployment Resources Types: %s\n", modelResponse.getSupportedDeploymentResourcesTypesList().toString());
System.out.format("\t\tSupported Input Storage Formats: %s\n", modelResponse.getSupportedInputStorageFormatsList().toString());
System.out.format("\t\tSupported Output Storage Formats: %s\n", modelResponse.getSupportedOutputStorageFormatsList().toString());
System.out.format("\t\tCreate Time: %s\n", modelResponse.getCreateTime());
System.out.format("\t\tUpdate Time: %s\n", modelResponse.getUpdateTime());
System.out.format("\t\tLabels: %s\n", modelResponse.getLabelsMap());
PredictSchemata predictSchemata = modelResponse.getPredictSchemata();
System.out.println("\tPredict Schemata");
System.out.format("\t\tInstance Schema Uri: %s\n", predictSchemata.getInstanceSchemaUri());
System.out.format("\t\tParameters Schema Uri: %s\n", predictSchemata.getParametersSchemaUri());
System.out.format("\t\tPrediction Schema Uri: %s\n", predictSchemata.getPredictionSchemaUri());
for (Model.ExportFormat supportedExportFormat : modelResponse.getSupportedExportFormatsList()) {
System.out.println("\tSupported Export Format");
System.out.format("\t\tId: %s\n", supportedExportFormat.getId());
}
ModelContainerSpec containerSpec = modelResponse.getContainerSpec();
System.out.println("\tContainer Spec");
System.out.format("\t\tImage Uri: %s\n", containerSpec.getImageUri());
System.out.format("\t\tCommand: %s\n", containerSpec.getCommandList());
System.out.format("\t\tArgs: %s\n", containerSpec.getArgsList());
System.out.format("\t\tPredict Route: %s\n", containerSpec.getPredictRoute());
System.out.format("\t\tHealth Route: %s\n", containerSpec.getHealthRoute());
for (EnvVar envVar : containerSpec.getEnvList()) {
System.out.println("\t\tEnv");
System.out.format("\t\t\tName: %s\n", envVar.getName());
System.out.format("\t\t\tValue: %s\n", envVar.getValue());
}
for (Port port : containerSpec.getPortsList()) {
System.out.println("\t\tPort");
System.out.format("\t\t\tContainer Port: %s\n", port.getContainerPort());
}
for (DeployedModelRef deployedModelRef : modelResponse.getDeployedModelsList()) {
System.out.println("\tDeployed Model");
System.out.format("\t\tEndpoint: %s\n", deployedModelRef.getEndpoint());
System.out.format("\t\tDeployed Model Id: %s\n", deployedModelRef.getDeployedModelId());
}
Status status = trainingPipelineResponse.getError();
System.out.println("\tError");
System.out.format("\t\tCode: %s\n", status.getCode());
System.out.format("\t\tMessage: %s\n", status.getMessage());
}
}
use of com.google.cloud.aiplatform.v1.PipelineServiceClient in project java-aiplatform by googleapis.
the class CreateTrainingPipelineTabularClassificationSampleTest method tearDown.
@After
public void tearDown() throws InterruptedException, ExecutionException, IOException, TimeoutException {
// Cancel the Training Pipeline
CancelTrainingPipelineSample.cancelTrainingPipelineSample(PROJECT, trainingPipelineId);
// Assert
String cancelResponse = bout.toString();
assertThat(cancelResponse).contains("Cancelled the Training Pipeline");
PipelineServiceSettings pipelineServiceSettings = PipelineServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
try (PipelineServiceClient pipelineServiceClient = PipelineServiceClient.create(pipelineServiceSettings)) {
String location = "us-central1";
TrainingPipelineName trainingPipelineName = TrainingPipelineName.of(PROJECT, location, trainingPipelineId);
TrainingPipeline trainingPipelineResponse = pipelineServiceClient.getTrainingPipeline(trainingPipelineName);
while (!trainingPipelineResponse.getState().name().contains("STATE_CANCELLED")) {
TimeUnit.SECONDS.sleep(30);
trainingPipelineResponse = pipelineServiceClient.getTrainingPipeline(trainingPipelineName);
}
}
// Delete the Training Pipeline
DeleteTrainingPipelineSample.deleteTrainingPipelineSample(PROJECT, trainingPipelineId);
// Assert
String deleteResponse = bout.toString();
assertThat(deleteResponse).contains("Deleted Training Pipeline.");
System.out.flush();
System.setOut(originalPrintStream);
}
use of com.google.cloud.aiplatform.v1.PipelineServiceClient in project java-aiplatform by googleapis.
the class CreateTrainingPipelineCustomTrainingManagedDatasetSample method createTrainingPipelineCustomTrainingManagedDatasetSample.
static void createTrainingPipelineCustomTrainingManagedDatasetSample(String project, String displayName, String modelDisplayName, String datasetId, String annotationSchemaUri, String trainingContainerSpecImageUri, String modelContainerSpecImageUri, String baseOutputUriPrefix) throws IOException {
PipelineServiceSettings settings = PipelineServiceSettings.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 (PipelineServiceClient client = PipelineServiceClient.create(settings)) {
JsonArray jsonArgs = new JsonArray();
jsonArgs.add("--model-dir=$(AIP_MODEL_DIR)");
// training_task_inputs
JsonObject jsonTrainingContainerSpec = new JsonObject();
jsonTrainingContainerSpec.addProperty("imageUri", trainingContainerSpecImageUri);
// AIP_MODEL_DIR is set by the service according to baseOutputDirectory.
jsonTrainingContainerSpec.add("args", jsonArgs);
JsonObject jsonMachineSpec = new JsonObject();
jsonMachineSpec.addProperty("machineType", "n1-standard-8");
JsonObject jsonTrainingWorkerPoolSpec = new JsonObject();
jsonTrainingWorkerPoolSpec.addProperty("replicaCount", 1);
jsonTrainingWorkerPoolSpec.add("machineSpec", jsonMachineSpec);
jsonTrainingWorkerPoolSpec.add("containerSpec", jsonTrainingContainerSpec);
JsonArray jsonWorkerPoolSpecs = new JsonArray();
jsonWorkerPoolSpecs.add(jsonTrainingWorkerPoolSpec);
JsonObject jsonBaseOutputDirectory = new JsonObject();
jsonBaseOutputDirectory.addProperty("outputUriPrefix", baseOutputUriPrefix);
JsonObject jsonTrainingTaskInputs = new JsonObject();
jsonTrainingTaskInputs.add("workerPoolSpecs", jsonWorkerPoolSpecs);
jsonTrainingTaskInputs.add("baseOutputDirectory", jsonBaseOutputDirectory);
Value.Builder trainingTaskInputsBuilder = Value.newBuilder();
JsonFormat.parser().merge(jsonTrainingTaskInputs.toString(), trainingTaskInputsBuilder);
Value trainingTaskInputs = trainingTaskInputsBuilder.build();
// model_to_upload
ModelContainerSpec modelContainerSpec = ModelContainerSpec.newBuilder().setImageUri(modelContainerSpecImageUri).build();
Model model = Model.newBuilder().setDisplayName(modelDisplayName).setContainerSpec(modelContainerSpec).build();
GcsDestination gcsDestination = GcsDestination.newBuilder().setOutputUriPrefix(baseOutputUriPrefix).build();
// input_data_config
InputDataConfig inputDataConfig = InputDataConfig.newBuilder().setDatasetId(datasetId).setAnnotationSchemaUri(annotationSchemaUri).setGcsDestination(gcsDestination).build();
// training_task_definition
String customTaskDefinition = "gs://google-cloud-aiplatform/schema/trainingjob/definition/custom_task_1.0.0.yaml";
TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().setDisplayName(displayName).setInputDataConfig(inputDataConfig).setTrainingTaskDefinition(customTaskDefinition).setTrainingTaskInputs(trainingTaskInputs).setModelToUpload(model).build();
LocationName parent = LocationName.of(project, location);
TrainingPipeline response = client.createTrainingPipeline(parent, trainingPipeline);
System.out.format("response: %s\n", response);
System.out.format("Name: %s\n", response.getName());
}
}
use of com.google.cloud.aiplatform.v1.PipelineServiceClient in project java-aiplatform by googleapis.
the class CreateTrainingPipelineImageObjectDetectionSample method createTrainingPipelineImageObjectDetectionSample.
static void createTrainingPipelineImageObjectDetectionSample(String project, String trainingPipelineDisplayName, String datasetId, String modelDisplayName) throws IOException {
PipelineServiceSettings pipelineServiceSettings = PipelineServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
// the "close" method on the client to safely clean up any remaining background resources.
try (PipelineServiceClient pipelineServiceClient = PipelineServiceClient.create(pipelineServiceSettings)) {
String location = "us-central1";
String trainingTaskDefinition = "gs://google-cloud-aiplatform/schema/trainingjob/definition/" + "automl_image_object_detection_1.0.0.yaml";
LocationName locationName = LocationName.of(project, location);
AutoMlImageObjectDetectionInputs autoMlImageObjectDetectionInputs = AutoMlImageObjectDetectionInputs.newBuilder().setModelType(ModelType.CLOUD_HIGH_ACCURACY_1).setBudgetMilliNodeHours(20000).setDisableEarlyStopping(false).build();
InputDataConfig trainingInputDataConfig = InputDataConfig.newBuilder().setDatasetId(datasetId).build();
Model model = Model.newBuilder().setDisplayName(modelDisplayName).build();
TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().setDisplayName(trainingPipelineDisplayName).setTrainingTaskDefinition(trainingTaskDefinition).setTrainingTaskInputs(ValueConverter.toValue(autoMlImageObjectDetectionInputs)).setInputDataConfig(trainingInputDataConfig).setModelToUpload(model).build();
TrainingPipeline trainingPipelineResponse = pipelineServiceClient.createTrainingPipeline(locationName, trainingPipeline);
System.out.println("Create Training Pipeline Image Object Detection Response");
System.out.format("Name: %s\n", trainingPipelineResponse.getName());
System.out.format("Display Name: %s\n", trainingPipelineResponse.getDisplayName());
System.out.format("Training Task Definition %s\n", trainingPipelineResponse.getTrainingTaskDefinition());
System.out.format("Training Task Inputs: %s\n", trainingPipelineResponse.getTrainingTaskInputs());
System.out.format("Training Task Metadata: %s\n", trainingPipelineResponse.getTrainingTaskMetadata());
System.out.format("State: %s\n", trainingPipelineResponse.getState());
System.out.format("Create Time: %s\n", trainingPipelineResponse.getCreateTime());
System.out.format("StartTime %s\n", trainingPipelineResponse.getStartTime());
System.out.format("End Time: %s\n", trainingPipelineResponse.getEndTime());
System.out.format("Update Time: %s\n", trainingPipelineResponse.getUpdateTime());
System.out.format("Labels: %s\n", trainingPipelineResponse.getLabelsMap());
InputDataConfig inputDataConfig = trainingPipelineResponse.getInputDataConfig();
System.out.println("Input Data Config");
System.out.format("Dataset Id: %s", inputDataConfig.getDatasetId());
System.out.format("Annotations Filter: %s\n", inputDataConfig.getAnnotationsFilter());
FractionSplit fractionSplit = inputDataConfig.getFractionSplit();
System.out.println("Fraction Split");
System.out.format("Training Fraction: %s\n", fractionSplit.getTrainingFraction());
System.out.format("Validation Fraction: %s\n", fractionSplit.getValidationFraction());
System.out.format("Test Fraction: %s\n", fractionSplit.getTestFraction());
FilterSplit filterSplit = inputDataConfig.getFilterSplit();
System.out.println("Filter Split");
System.out.format("Training Filter: %s\n", filterSplit.getTrainingFilter());
System.out.format("Validation Filter: %s\n", filterSplit.getValidationFilter());
System.out.format("Test Filter: %s\n", filterSplit.getTestFilter());
PredefinedSplit predefinedSplit = inputDataConfig.getPredefinedSplit();
System.out.println("Predefined Split");
System.out.format("Key: %s\n", predefinedSplit.getKey());
TimestampSplit timestampSplit = inputDataConfig.getTimestampSplit();
System.out.println("Timestamp Split");
System.out.format("Training Fraction: %s\n", timestampSplit.getTrainingFraction());
System.out.format("Validation Fraction: %s\n", timestampSplit.getValidationFraction());
System.out.format("Test Fraction: %s\n", timestampSplit.getTestFraction());
System.out.format("Key: %s\n", timestampSplit.getKey());
Model modelResponse = trainingPipelineResponse.getModelToUpload();
System.out.println("Model To Upload");
System.out.format("Name: %s\n", modelResponse.getName());
System.out.format("Display Name: %s\n", modelResponse.getDisplayName());
System.out.format("Description: %s\n", modelResponse.getDescription());
System.out.format("Metadata Schema Uri: %s\n", modelResponse.getMetadataSchemaUri());
System.out.format("Metadata: %s\n", modelResponse.getMetadata());
System.out.format("Training Pipeline: %s\n", modelResponse.getTrainingPipeline());
System.out.format("Artifact Uri: %s\n", modelResponse.getArtifactUri());
System.out.format("Supported Deployment Resources Types: %s\n", modelResponse.getSupportedDeploymentResourcesTypesList());
System.out.format("Supported Input Storage Formats: %s\n", modelResponse.getSupportedInputStorageFormatsList());
System.out.format("Supported Output Storage Formats: %s\n", modelResponse.getSupportedOutputStorageFormatsList());
System.out.format("Create Time: %s\n", modelResponse.getCreateTime());
System.out.format("Update Time: %s\n", modelResponse.getUpdateTime());
System.out.format("Labels: %sn\n", modelResponse.getLabelsMap());
PredictSchemata predictSchemata = modelResponse.getPredictSchemata();
System.out.println("Predict Schemata");
System.out.format("Instance Schema Uri: %s\n", predictSchemata.getInstanceSchemaUri());
System.out.format("Parameters Schema Uri: %s\n", predictSchemata.getParametersSchemaUri());
System.out.format("Prediction Schema Uri: %s\n", predictSchemata.getPredictionSchemaUri());
for (ExportFormat exportFormat : modelResponse.getSupportedExportFormatsList()) {
System.out.println("Supported Export Format");
System.out.format("Id: %s\n", exportFormat.getId());
}
ModelContainerSpec modelContainerSpec = modelResponse.getContainerSpec();
System.out.println("Container Spec");
System.out.format("Image Uri: %s\n", modelContainerSpec.getImageUri());
System.out.format("Command: %s\n", modelContainerSpec.getCommandList());
System.out.format("Args: %s\n", modelContainerSpec.getArgsList());
System.out.format("Predict Route: %s\n", modelContainerSpec.getPredictRoute());
System.out.format("Health Route: %s\n", modelContainerSpec.getHealthRoute());
for (EnvVar envVar : modelContainerSpec.getEnvList()) {
System.out.println("Env");
System.out.format("Name: %s\n", envVar.getName());
System.out.format("Value: %s\n", envVar.getValue());
}
for (Port port : modelContainerSpec.getPortsList()) {
System.out.println("Port");
System.out.format("Container Port: %s\n", port.getContainerPort());
}
for (DeployedModelRef deployedModelRef : modelResponse.getDeployedModelsList()) {
System.out.println("Deployed Model");
System.out.format("Endpoint: %s\n", deployedModelRef.getEndpoint());
System.out.format("Deployed Model Id: %s\n", deployedModelRef.getDeployedModelId());
}
Status status = trainingPipelineResponse.getError();
System.out.println("Error");
System.out.format("Code: %s\n", status.getCode());
System.out.format("Message: %s\n", status.getMessage());
}
}
use of com.google.cloud.aiplatform.v1.PipelineServiceClient in project java-aiplatform by googleapis.
the class CreateTrainingPipelineTabularClassificationSample method createTrainingPipelineTableClassification.
static void createTrainingPipelineTableClassification(String project, String modelDisplayName, String datasetId, String targetColumn) throws IOException {
PipelineServiceSettings pipelineServiceSettings = PipelineServiceSettings.newBuilder().setEndpoint("us-central1-aiplatform.googleapis.com:443").build();
// the "close" method on the client to safely clean up any remaining background resources.
try (PipelineServiceClient pipelineServiceClient = PipelineServiceClient.create(pipelineServiceSettings)) {
String location = "us-central1";
LocationName locationName = LocationName.of(project, location);
String trainingTaskDefinition = "gs://google-cloud-aiplatform/schema/trainingjob/definition/automl_tables_1.0.0.yaml";
// Set the columns used for training and their data types
Transformation transformation1 = Transformation.newBuilder().setAuto(AutoTransformation.newBuilder().setColumnName("sepal_width").build()).build();
Transformation transformation2 = Transformation.newBuilder().setAuto(AutoTransformation.newBuilder().setColumnName("sepal_length").build()).build();
Transformation transformation3 = Transformation.newBuilder().setAuto(AutoTransformation.newBuilder().setColumnName("petal_length").build()).build();
Transformation transformation4 = Transformation.newBuilder().setAuto(AutoTransformation.newBuilder().setColumnName("petal_width").build()).build();
ArrayList<Transformation> transformationArrayList = new ArrayList<>();
transformationArrayList.add(transformation1);
transformationArrayList.add(transformation2);
transformationArrayList.add(transformation3);
transformationArrayList.add(transformation4);
AutoMlTablesInputs autoMlTablesInputs = AutoMlTablesInputs.newBuilder().setTargetColumn(targetColumn).setPredictionType("classification").addAllTransformations(transformationArrayList).setTrainBudgetMilliNodeHours(8000).build();
FractionSplit fractionSplit = FractionSplit.newBuilder().setTrainingFraction(0.8).setValidationFraction(0.1).setTestFraction(0.1).build();
InputDataConfig inputDataConfig = InputDataConfig.newBuilder().setDatasetId(datasetId).setFractionSplit(fractionSplit).build();
Model modelToUpload = Model.newBuilder().setDisplayName(modelDisplayName).build();
TrainingPipeline trainingPipeline = TrainingPipeline.newBuilder().setDisplayName(modelDisplayName).setTrainingTaskDefinition(trainingTaskDefinition).setTrainingTaskInputs(ValueConverter.toValue(autoMlTablesInputs)).setInputDataConfig(inputDataConfig).setModelToUpload(modelToUpload).build();
TrainingPipeline trainingPipelineResponse = pipelineServiceClient.createTrainingPipeline(locationName, trainingPipeline);
System.out.println("Create Training Pipeline Tabular Classification Response");
System.out.format("\tName: %s\n", trainingPipelineResponse.getName());
System.out.format("\tDisplay Name: %s\n", trainingPipelineResponse.getDisplayName());
System.out.format("\tTraining Task Definition: %s\n", trainingPipelineResponse.getTrainingTaskDefinition());
System.out.format("\tTraining Task Inputs: %s\n", trainingPipelineResponse.getTrainingTaskInputs());
System.out.format("\tTraining Task Metadata: %s\n", trainingPipelineResponse.getTrainingTaskMetadata());
System.out.format("\tState: %s\n", trainingPipelineResponse.getState());
System.out.format("\tCreate Time: %s\n", trainingPipelineResponse.getCreateTime());
System.out.format("\tStart Time: %s\n", trainingPipelineResponse.getStartTime());
System.out.format("\tEnd Time: %s\n", trainingPipelineResponse.getEndTime());
System.out.format("\tUpdate Time: %s\n", trainingPipelineResponse.getUpdateTime());
System.out.format("\tLabels: %s\n", trainingPipelineResponse.getLabelsMap());
InputDataConfig inputDataConfigResponse = trainingPipelineResponse.getInputDataConfig();
System.out.println("\tInput Data Config");
System.out.format("\t\tDataset Id: %s\n", inputDataConfigResponse.getDatasetId());
System.out.format("\t\tAnnotations Filter: %s\n", inputDataConfigResponse.getAnnotationsFilter());
FractionSplit fractionSplitResponse = inputDataConfigResponse.getFractionSplit();
System.out.println("\t\tFraction Split");
System.out.format("\t\t\tTraining Fraction: %s\n", fractionSplitResponse.getTrainingFraction());
System.out.format("\t\t\tValidation Fraction: %s\n", fractionSplitResponse.getValidationFraction());
System.out.format("\t\t\tTest Fraction: %s\n", fractionSplitResponse.getTestFraction());
FilterSplit filterSplit = inputDataConfigResponse.getFilterSplit();
System.out.println("\t\tFilter Split");
System.out.format("\t\t\tTraining Fraction: %s\n", filterSplit.getTrainingFilter());
System.out.format("\t\t\tValidation Fraction: %s\n", filterSplit.getValidationFilter());
System.out.format("\t\t\tTest Fraction: %s\n", filterSplit.getTestFilter());
PredefinedSplit predefinedSplit = inputDataConfigResponse.getPredefinedSplit();
System.out.println("\t\tPredefined Split");
System.out.format("\t\t\tKey: %s\n", predefinedSplit.getKey());
TimestampSplit timestampSplit = inputDataConfigResponse.getTimestampSplit();
System.out.println("\t\tTimestamp Split");
System.out.format("\t\t\tTraining Fraction: %s\n", timestampSplit.getTrainingFraction());
System.out.format("\t\t\tValidation Fraction: %s\n", timestampSplit.getValidationFraction());
System.out.format("\t\t\tTest Fraction: %s\n", timestampSplit.getTestFraction());
System.out.format("\t\t\tKey: %s\n", timestampSplit.getKey());
Model modelResponse = trainingPipelineResponse.getModelToUpload();
System.out.println("\tModel To Upload");
System.out.format("\t\tName: %s\n", modelResponse.getName());
System.out.format("\t\tDisplay Name: %s\n", modelResponse.getDisplayName());
System.out.format("\t\tDescription: %s\n", modelResponse.getDescription());
System.out.format("\t\tMetadata Schema Uri: %s\n", modelResponse.getMetadataSchemaUri());
System.out.format("\t\tMeta Data: %s\n", modelResponse.getMetadata());
System.out.format("\t\tTraining Pipeline: %s\n", modelResponse.getTrainingPipeline());
System.out.format("\t\tArtifact Uri: %s\n", modelResponse.getArtifactUri());
System.out.format("\t\tSupported Deployment Resources Types: %s\n", modelResponse.getSupportedDeploymentResourcesTypesList().toString());
System.out.format("\t\tSupported Input Storage Formats: %s\n", modelResponse.getSupportedInputStorageFormatsList().toString());
System.out.format("\t\tSupported Output Storage Formats: %s\n", modelResponse.getSupportedOutputStorageFormatsList().toString());
System.out.format("\t\tCreate Time: %s\n", modelResponse.getCreateTime());
System.out.format("\t\tUpdate Time: %s\n", modelResponse.getUpdateTime());
System.out.format("\t\tLables: %s\n", modelResponse.getLabelsMap());
PredictSchemata predictSchemata = modelResponse.getPredictSchemata();
System.out.println("\tPredict Schemata");
System.out.format("\t\tInstance Schema Uri: %s\n", predictSchemata.getInstanceSchemaUri());
System.out.format("\t\tParameters Schema Uri: %s\n", predictSchemata.getParametersSchemaUri());
System.out.format("\t\tPrediction Schema Uri: %s\n", predictSchemata.getPredictionSchemaUri());
for (Model.ExportFormat supportedExportFormat : modelResponse.getSupportedExportFormatsList()) {
System.out.println("\tSupported Export Format");
System.out.format("\t\tId: %s\n", supportedExportFormat.getId());
}
ModelContainerSpec containerSpec = modelResponse.getContainerSpec();
System.out.println("\tContainer Spec");
System.out.format("\t\tImage Uri: %s\n", containerSpec.getImageUri());
System.out.format("\t\tCommand: %s\n", containerSpec.getCommandList());
System.out.format("\t\tArgs: %s\n", containerSpec.getArgsList());
System.out.format("\t\tPredict Route: %s\n", containerSpec.getPredictRoute());
System.out.format("\t\tHealth Route: %s\n", containerSpec.getHealthRoute());
for (EnvVar envVar : containerSpec.getEnvList()) {
System.out.println("\t\tEnv");
System.out.format("\t\t\tName: %s\n", envVar.getName());
System.out.format("\t\t\tValue: %s\n", envVar.getValue());
}
for (Port port : containerSpec.getPortsList()) {
System.out.println("\t\tPort");
System.out.format("\t\t\tContainer Port: %s\n", port.getContainerPort());
}
for (DeployedModelRef deployedModelRef : modelResponse.getDeployedModelsList()) {
System.out.println("\tDeployed Model");
System.out.format("\t\tEndpoint: %s\n", deployedModelRef.getEndpoint());
System.out.format("\t\tDeployed Model Id: %s\n", deployedModelRef.getDeployedModelId());
}
Status status = trainingPipelineResponse.getError();
System.out.println("\tError");
System.out.format("\t\tCode: %s\n", status.getCode());
System.out.format("\t\tMessage: %s\n", status.getMessage());
}
}
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