code: def convert_gpt2(args):
      if not os.path.exists(args.save_dir):
          os.makedirs(args.save_dir)
  
      tf_ckpt_path = os.path.join(args.tf_model_path, "model.ckpt")
      tf_params = read_tf_ckpt(tf_ckpt_path)
      with open(
          os.path.join(args.tf_model_path, "hparams.json"), "r"
      ) as hf:
          tf_cfg = json.load(hf)
  
      vocab_size = convert_vocab(args)
      gluon_backbone_cfg = convert_config(tf_cfg, vocab_size)
      with open(os.path.join(args.save_dir, "model.yml"), "w") as of:
          of.write(gluon_backbone_cfg.dump())
  
      gluon_gpt2forlm_model = GPT2ForLM(gluon_backbone_cfg)
      gluon_gpt2forlm_model.initialize(ctx=mx.cpu())
      gluon_gpt2forlm_model.hybridize()
      gluon_backbone_model = gluon_gpt2forlm_model._backbone_model
      convert_backbone_params(tf_params, gluon_backbone_model)
  
      if args.test:
          test_model(args.tf_model_path, gluon_gpt2forlm_model)
  
      gluon_gpt2forlm_model.save_parameters(
          os.path.join(args.save_dir, "model_lm.params"),
          deduplicate=True,
      )
      logging.info(
          "Convert the GPT2 LM model in {} to {}".format(
              os.path.join(args.tf_model_path, "model.ckpt"),
              os.path.join(args.save_dir, "model_lm.params"),
          )
      )
      gluon_backbone_model.save_parameters(
          os.path.join(args.save_dir, "model.params"), deduplicate=True
      )
      logging.info(
          "Convert the GPT2 backbone model in {} to {}".format(
              os.path.join(args.tf_model_path, "model.ckpt"),
              os.path.join(args.save_dir, "model.params"),
          )
      )
  
      logging.info("Conversion finished!")
      logging.info("Statistics:")
      old_names = os.listdir(args.save_dir)
      for old_name in old_names:
          new_name, long_hash = naming_convention(
              args.save_dir, old_name
          )
          old_path = os.path.join(args.save_dir, old_name)
          new_path = os.path.join(args.save_dir, new_name)
          shutil.move(old_path, new_path)
          file_size = os.path.getsize(new_path)
          logging.info(
              "\t{}/{} {} {}".format(
                  args.save_dir, new_name, long_hash, file_size
              )
          )
  
imports: import os
  import re
  import json
  import shutil
  import logging
  import argparse
  import tensorflow
  from tensorflow.contrib.training import HParams
  from gpt_2.src import model
  import mxnet
  import numpy
  from numpy.testing import assert_allclose
  from gluonnlp.data.vocab import Vocab
  from gluonnlp.utils.misc import sha1sum, logging_config, naming_convention
  from gluonnlp.models.gpt2 import GPT2Model, GPT2ForLM
label_desc: Use image node_id 8 for calling a global function with example usage: convert_gpt2(args) without return types