code: def parse_param(cfg, prompt):
      prompt = prompt.replace("--", "")
      parts = prompt.split(" ")
      args = [
          " ".join(parts[i : i + 2]) for i in range(0, len(parts), 2)
      ]
      for arg in args:
          splitted_arg = arg.split(" ")
          setattr(
              cfg.prediction,
              splitted_arg[0],
              type(getattr(cfg.prediction, splitted_arg[0]))(
                  splitted_arg[1]
              ),
          )
          print(
              f"Permanently changed {splitted_arg[0]} to",
              getattr(cfg.prediction, splitted_arg[0]),
          )
      return cfg
  
imports: import os
  from llm_studio.src.utils.config_utils import load_config_yaml
  import argparse
  import numpy
  import torch
  from llm_studio.src.datasets.text_utils import get_tokenizer
  from llm_studio.src.utils.modeling_utils import load_checkpoint
label_desc: Use image node_id 1 for calling a global function with example usage: parse_param(cfg, prompt) and returns: cfg