code: def prepare_ctrl_input(args, _, tokenizer, prompt_text):
      if args.temperature > 0.7:
          logger.info(
              "CTRL typically works better with lower temperatures (and lower top_k)."
          )
  
      encoded_prompt = tokenizer.encode(
          prompt_text, add_special_tokens=False
      )
      if not any(
          encoded_prompt[0] == x
          for x in tokenizer.control_codes.values()
      ):
          logger.info(
              "WARNING! You are not starting your generation from a control code so you won't get good results"
          )
      return prompt_text
  
imports: import argparse
  import inspect
  import logging
  from typing import Tuple
  import torch
  from accelerate import PartialState
  from accelerate.utils import set_seed
  from transformers import AutoTokenizer, BloomForCausalLM, BloomTokenizerFast, CTRLLMHeadModel, CTRLTokenizer, GenerationMixin, GPT2LMHeadModel, GPT2Tokenizer, GPTJForCausalLM, LlamaForCausalLM, LlamaTokenizer, OpenAIGPTLMHeadModel, OpenAIGPTTokenizer, OPTForCausalLM, TransfoXLLMHeadModel, TransfoXLTokenizer, XLMTokenizer, XLMWithLMHeadModel, XLNetLMHeadModel, XLNetTokenizer
  from transformers.modeling_outputs import CausalLMOutputWithPast
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_ctrl_input(args, _, tokenizer, prompt_text) and returns: prompt_text