code: def from_framework_format(
      cls, dtype: Union[torch.dtype, tf.dtypes.DType, np.dtype]
  ):
      if isinstance(dtype, torch.dtype):
          framework = "torch"
      elif isinstance(dtype, tf.dtypes.DType):
          framework = "tensorflow"
      else:
          framework = "numpy"
          dtype = dtype.type
      return FRAMEWORK_TO_DATA_TYPE_CONVERSION_DICT[framework][dtype]
  
imports: import subprocess
  from dataclasses import dataclass
  from enum import Enum
  from functools import cached_property
  from typing import Optional, Any, Union, Tuple, List, Dict
  import numpy
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch
label_desc: Use image node_id 1 for calling the DataType obj's underlying member method code with example usage: obj.from_framework_format(cls, dtype) and returns: FRAMEWORK_TO_DATA_TYPE_CONVERSION_DICT