code: def main():
      """Converts saved checkpoint to the expected format for detoxify."""
      checkpoint = torch.load(ARGS.checkpoint, map_location=ARGS.device)
  
      new_state_dict = {
          "state_dict": OrderedDict(),
          "config": checkpoint["hyper_parameters"]["config"],
      }
      for k, v in checkpoint["state_dict"].items():
          if k.startswith("model."):
              k = k[6:]  # remove `model.`
          new_state_dict["state_dict"][k] = v
  
      torch.save(new_state_dict, ARGS.save_to)
  
      if ARGS.hash:
          with open(ARGS.save_to, "rb") as f:
              bytes = f.read()  # read entire file as bytes
              readable_hash = hashlib.sha256(bytes).hexdigest()
              print("Hash: ", readable_hash)
  
          torch.save(
              new_state_dict,
              ARGS.save_to[:-5] + f"-{readable_hash[:8]}.ckpt",
          )
  
imports: import argparse
  import hashlib
  from collections import OrderedDict
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: main() without return types