code: def save_model(self, model, path):
      logging.info(f"Saving model to {path}")
      model.save(path)
  
      # Saving the model targets
      output_targets_path = os.path.join(path, "targets.json")
      logging.info(
          f"Saving model targets metadata to {output_targets_path}"
      )
      json_object = json.dumps(self.targets, indent=4)
      with open(output_targets_path, "w") as outfile:
          outfile.write(json_object)
  
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 16 for calling the RankingTrainEvalRunner obj's underlying member method code with example usage: obj.save_model(model, path) without return types