code: def get_texts(df, cfg, separator=None):
      if isinstance(cfg.dataset.prompt_column, str):
          # single column dataset
          texts = df[cfg.dataset.prompt_column].astype(str)
          texts = texts.values
      else:
          # multi-column dataset - prepend (if necessary) and join
          columns = list(cfg.dataset.prompt_column)
  
          for column in columns:
              df[column] = df[column].astype(str)
  
          if separator is None:
              separator = getattr(
                  cfg, "_tokenizer_sep_token", TEXT_SEPARATOR
              )
  
          join_str = f" {separator} "
          texts = df[columns].astype(str)
          texts = texts.apply(lambda x: join_str.join(x), axis=1).values
  
      return texts
  
imports: import codecs
  import logging
  import os
  from typing import Any
  from transformers import AutoTokenizer
label_desc: Use image node_id 1 for calling a global function with example usage: get_texts(df, cfg, separator) and returns: texts