in aiplatform/src/main/java/aiplatform/CreateTrainingPipelineTabularRegressionSample.java [56:319]
static void createTrainingPipelineTableRegression(
String project, String modelDisplayName, String datasetId, String targetColumn)
throws IOException {
PipelineServiceSettings pipelineServiceSettings =
PipelineServiceSettings.newBuilder()
.setEndpoint("us-central1-aiplatform.googleapis.com:443")
.build();
// Initialize client that will be used to send requests. This client only needs to be created
// once, and can be reused for multiple requests. After completing all of your requests, call
// the "close" method on the client to safely clean up any remaining background resources.
try (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
ArrayList<Transformation> tranformations = new ArrayList<>();
tranformations.add(
Transformation.newBuilder()
.setAuto(AutoTransformation.newBuilder().setColumnName("STRING_5000unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(AutoTransformation.newBuilder().setColumnName("INTEGER_5000unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(AutoTransformation.newBuilder().setColumnName("FLOAT_5000unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(AutoTransformation.newBuilder().setColumnName("FLOAT_5000unique_REPEATED"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(AutoTransformation.newBuilder().setColumnName("NUMERIC_5000unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(AutoTransformation.newBuilder().setColumnName("BOOLEAN_2unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setTimestamp(
TimestampTransformation.newBuilder()
.setColumnName("TIMESTAMP_1unique_NULLABLE")
.setInvalidValuesAllowed(true))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(AutoTransformation.newBuilder().setColumnName("DATE_1unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(AutoTransformation.newBuilder().setColumnName("TIME_1unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setTimestamp(
TimestampTransformation.newBuilder()
.setColumnName("DATETIME_1unique_NULLABLE")
.setInvalidValuesAllowed(true))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(
AutoTransformation.newBuilder()
.setColumnName("STRUCT_NULLABLE.STRING_5000unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(
AutoTransformation.newBuilder()
.setColumnName("STRUCT_NULLABLE.INTEGER_5000unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(
AutoTransformation.newBuilder()
.setColumnName("STRUCT_NULLABLE.FLOAT_5000unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(
AutoTransformation.newBuilder()
.setColumnName("STRUCT_NULLABLE.FLOAT_5000unique_REQUIRED"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(
AutoTransformation.newBuilder()
.setColumnName("STRUCT_NULLABLE.FLOAT_5000unique_REPEATED"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(
AutoTransformation.newBuilder()
.setColumnName("STRUCT_NULLABLE.NUMERIC_5000unique_NULLABLE"))
.build());
tranformations.add(
Transformation.newBuilder()
.setAuto(
AutoTransformation.newBuilder()
.setColumnName("STRUCT_NULLABLE.TIMESTAMP_1unique_NULLABLE"))
.build());
AutoMlTablesInputs trainingTaskInputs =
AutoMlTablesInputs.newBuilder()
.addAllTransformations(tranformations)
.setTargetColumn(targetColumn)
.setPredictionType("regression")
.setTrainBudgetMilliNodeHours(8000)
.setDisableEarlyStopping(false)
// supported regression optimisation objectives: minimize-rmse,
// minimize-mae, minimize-rmsle
.setOptimizationObjective("minimize-rmse")
.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(trainingTaskInputs))
.setInputDataConfig(inputDataConfig)
.setModelToUpload(modelToUpload)
.build();
TrainingPipeline trainingPipelineResponse =
pipelineServiceClient.createTrainingPipeline(locationName, trainingPipeline);
System.out.println("Create Training Pipeline Tabular Regression 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());
}
}