code: def recursive_print(name, val, spaces=0):
      # Format the message.
      if name is None:
          msg = None
      else:
          fmt = (
              "." * max(0, spaces - 2)
              + "# {:"
              + str(50 - spaces)
              + "s}"
          )
          msg = fmt.format(name)
  
      # Print and recurse (if needed).
      if isinstance(val, dict):
          if msg is not None:
              print(msg)
          for k in val.keys():
              recursive_print(k, val[k], spaces + 2)
      elif isinstance(val, torch.Tensor):
          print(msg, ":", val.size())
      else:
          print(msg, ":", val)
  
file_path: transformers/src/transformers/models/megatron_gpt2/convert_megatron_gpt2_checkpoint.py
imports: import argparse
  import os
  import re
  import zipfile
  import torch
  from transformers import AutoTokenizer, GPT2Config
label_desc: Use image node_id 1 for calling a global function with example usage: recursive_print(name, val, spaces) without return types