class_docstr: Dataset for Causal Language modeling.
code: def parse_prompt(cfg: Any, prompt: str):
      prompt = f"{codecs.decode(cfg.dataset.text_prompt_start, 'unicode_escape')}{prompt}"
      if cfg.dataset.add_eos_token_to_prompt:
          prompt += cfg._tokenizer_eos_token
      prompt = (
          f"{prompt}"
          f"{codecs.decode(cfg.dataset.text_answer_separator, 'unicode_escape')}"
      )
      return prompt
  
imports: import codecs
  import collections.abc
  import logging
  from typing import Any, Dict, List, Tuple, Union
  import numpy
  import pandas
  import torch
  from torch.utils.data import Dataset
  from llm_studio.src.datasets.conversation_chain_handler import ConversationChainHandler
  from llm_studio.src.datasets.text_utils import get_tokenizer
label_desc: Use image node_id 4 for calling the CustomDataset obj's underlying member method code with example usage: obj.parse_prompt(cfg, prompt) and returns: prompt