code: def get_config_foldername(config: dict) -> str:
      def shorten_key(key: str) -> str:
          return "".join(word[0] for word in key.split("_"))
  
      def shorten_value(value) -> str:
          if isinstance(value, bool):
              return "1" if value else "0"
          elif isinstance(value, str):
              value = value.split("/")[-1]
              if "_" in value:
                  return "_".join(word[:4] for word in value.split("_"))
              else:
                  return value
          else:
              return str(value)
  
      return "-".join(
          f"{shorten_key(k)}={shorten_value(v)}"
          for k, v in sorted(config.items())
      )
  
file_path: weak-to-strong/train_simple.py
imports: import json
  import os
  import random
  import subprocess
  from typing import Dict, List, Optional
  import fire
  import numpy
  import torch
  from datasets import load_dataset, load_from_disk
  import weak_to_strong.logger
  from weak_to_strong.common import get_tokenizer
  from weak_to_strong.datasets import VALID_DATASETS, load_dataset, tokenize_dataset
  from weak_to_strong.loss import logconf_loss_fn, product_loss_fn, xent_loss
  from weak_to_strong.train import ModelConfig, train_and_save_model
label_desc: Use image node_id 1 for calling a global function with example usage: get_config_foldername(config) and returns: str, str, unknown, str, str, value