code: def convert(
      src_path: str,
      map_location: str = "cpu",
      save_path: Union[str, None] = None,
  ) -> None:
      """Convert a pytorch_model.bin or model.pt file to torch.float16 for faster downloads, less disk space."""
      state_dict = torch.load(src_path, map_location=map_location)
      for k, v in tqdm(state_dict.items()):
          if not isinstance(v, torch.Tensor):
              raise TypeError(
                  "FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"
              )
          state_dict[k] = v.half()
      if save_path is None:  # overwrite src_path
          save_path = src_path
      torch.save(state_dict, save_path)
  
imports: from typing import Union
  import fire
  import torch
  from tqdm import tqdm
label_desc: Use image node_id 1 for calling a global function with example usage: convert(src_path, map_location, save_path) without return types