code: def build_mtl_model(self):
      prediction_tasks = get_mtl_prediction_tasks(
          self.targets, self.args
      )
      model = get_model(self.schema, prediction_tasks, 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 11 for calling the RankingTrainEvalRunner obj's underlying member method code with example usage: obj.build_mtl_model() and returns: model