code: def save_model(model, dirpath):
      # save results
      if os.path.exists(dirpath):
          if os.path.exists(
              os.path.join(dirpath, "config.json")
          ) and os.path.isfile(os.path.join(dirpath, "config.json")):
              os.remove(os.path.join(dirpath, "config.json"))
          if os.path.exists(
              os.path.join(dirpath, "pytorch_model.bin")
          ) and os.path.isfile(
              os.path.join(dirpath, "pytorch_model.bin")
          ):
              os.remove(os.path.join(dirpath, "pytorch_model.bin"))
      else:
          os.makedirs(dirpath)
      model.save_pretrained(dirpath)
  
file_path: transformers/examples/research_projects/bertology/run_prune_gpt.py
imports: import argparse
  import logging
  import os
  from datetime import datetime
  import numpy
  import torch
  from torch import nn
  from torch.utils.data import DataLoader, RandomSampler, TensorDataset
  from tqdm import tqdm
  from transformers import GPT2LMHeadModel
label_desc: Use image node_id 1 for calling a global function with example usage: save_model(model, dirpath) without return types