code: def parse_feature_meta_tabular(
      metadata: dict,
  ) -> Tuple[list, list, dict]:
      """
      parse feature meta data for tabular
      Args:
          metadata: dict contains class information and feature information
  
      Returns:
          feature_names: list of feature names
          categorical_idx: list of index of categorical feature
          categorical_mapping: a dict maps feature column index to a list of encoding text
  
      """
      feature_names = list()
      categorical_idx = list()
      categorical_mapping = dict()
      feature_meta = metadata.get("feature_types", [])
      for idx, feature in enumerate(feature_meta):
          feature_names.append(feature["name"])
          type = feature["type"]
          if type == "categorical":
              categorical_idx.append(idx)
              mapping = feature.get("mapping", None)
              if mapping:
                  categorical_mapping[idx] = mapping
  
      return feature_names, categorical_idx, categorical_mapping
  
label_desc: Use image node_id 1 for calling a global function with example usage: parse_feature_meta_tabular(metadata) and returns: feature_names,  categorical_idx,  categorical_mapping