code: def get_fill_columns(cfg: Any) -> List[str]:
      if hasattr(cfg.dataset, "prompt_column"):
          if isinstance(cfg.dataset.prompt_column, (list, tuple)):
              return list(cfg.dataset.prompt_column)
          return [cfg.dataset.prompt_column]
  
      return []
  
imports: import logging
  import math
  import os
  from typing import Any, DefaultDict, Dict, List, Optional, Tuple, Union, no_type_check
  import networkx
  import numpy
  import pandas
  import pyarrow.parquet
  import torch
  from sklearn.model_selection import GroupShuffleSplit, train_test_split
  from torch import distributed
  from torch.utils.data import DataLoader, Sampler, SequentialSampler
  from llm_studio.src.datasets.conversation_chain_handler import ConversationChainHandler
  from llm_studio.src.utils.exceptions import LLMDataException
  from llm_studio.src.utils.utils import PatchedAttribute, set_seed
label_desc: Use image node_id 2 for calling a global function with example usage: get_fill_columns(cfg) and returns: list, list, list