code: def build_stl_model(self):
      if Task.BINARY_CLASSIFICATION.value in self.targets:
          prediction_task = mm.BinaryOutput(
              self.targets[Task.BINARY_CLASSIFICATION.value][0]
          )
      elif Task.REGRESSION in self.targets:
          prediction_task = mm.RegressionOutput(
              self.targets[Task.REGRESSION.value][0]
          )
      else:
          raise ValueError(f"Unrecognized task: {self.targets}")
  
      model = get_model(self.schema, prediction_task, self.args)
      return model
  
imports: import json
  import logging
  import os
  from datetime import datetime
  import merlin.models.tf
  import numpy
  import tensorflow
  from merlin.io.dataset import Dataset
  from merlin.models.tf.logging.callbacks import ExamplesPerSecondCallback, WandbLogger
  from merlin.models.tf.transforms.negative_sampling import InBatchNegatives
  from merlin.schema.tags import Tags
  from .args_parsing import Task, parse_arguments
  from .mtl import get_mtl_loss_weights, get_mtl_prediction_tasks
  from .ranking_models import get_model
label_desc: Use image node_id 9 for calling the RankingTrainEvalRunner obj's underlying member method code with example usage: obj.build_stl_model() and returns: model