code: def flat_config(config):
      """Flat config loaded from a yaml file to a flat dict.
  
      Args:
          config (dict): Configuration loaded from a yaml file.
  
      Returns:
          dict: Configuration dictionary.
      """
      f_config = {}
      category = config.keys()
      for cate in category:
          for key, val in config[cate].items():
              f_config[key] = val
      return f_config
  
imports: import os
  from sklearn.metrics import roc_auc_score, log_loss, mean_squared_error, accuracy_score, f1_score
  import numpy
  import yaml
  import zipfile
  import pickle
  from recommenders.datasets.download_utils import maybe_download
label_desc: Use image node_id 1 for calling a global function with example usage: flat_config(config) and returns: f_config