code: def _get_dtype(
      dtype: Union[str, torch.dtype],
      config: Optional[transformers.AutoConfig] = None,
  ) -> torch.dtype:
      """Converts `dtype` from `str` to torch.dtype when possible."""
      if dtype is None and config is not None:
          _torch_dtype = config.torch_dtype
      elif isinstance(dtype, str) and dtype != "auto":
          # Convert `str` args torch dtype: `float16` -> `torch.float16`
          _torch_dtype = getattr(torch, dtype)
      else:
          _torch_dtype = dtype
      return _torch_dtype
  
imports: import math
  import torch
  import torch.nn.functional
  import transformers
  import peft
  from pathlib import Path
  from typing import List, Mapping, NewType, Optional, Tuple, Union
  from tqdm import tqdm
  from transformers import BatchEncoding
  from lm_eval import utils
  from lm_eval.base import BaseLM
label_desc: Use image node_id 2 for calling a global function with example usage: _get_dtype(dtype, config) and returns: _torch_dtype