code: def get_dtype_size(dtype):
      if dtype == torch.bool:
          return 1 / 8
      bit_search = re.search("[^\d](\d+)$", str(dtype))
      if bit_search is None:
          raise ValueError(f"`dtype` is not a valid dtype: {dtype}.")
      bit_size = int(bit_search.groups()[0])
      return bit_size // 8
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/src/transformers/models/bloom/convert_bloom_original_checkpoint_to_pytorch.py
imports: import argparse
  import json
  import os
  import re
  import torch
  from transformers import BloomConfig, BloomModel
  from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
  from transformers.utils import logging
label_desc: Use image node_id 2 for calling a global function with example usage: get_dtype_size(dtype) and returns: unknown, unknown