code: def get_expected_scaling_method(training_config):
      """
      get expected scaling method from the parsed training configuration (description.json)
      """
      dataset_props = training_config.get("dataset_props")
      if not dataset_props:
          return
      preprocess_options = dataset_props.get("preprocess")
      if not preprocess_options:
          return
      scaling_options = preprocess_options.get("scale")
      if not scaling_options:
          return
      return scaling_options.get("method")
  
file_path: igel/igel/utils.py
imports: import json
  import logging
  import joblib
  import pandas
  import yaml
  from igel.configs import configs
  from igel.data import metrics_dict, models_dict
label_desc: Use image node_id 8 for calling a global function with example usage: get_expected_scaling_method(training_config) and returns: scaling_options