code: def get_size_recursively(
      tensor_tuple: Union[torch.Tensor, tf.Tensor, Tuple]
  ) -> List[int]:
      if isinstance(tensor_tuple[0], (torch.Tensor, tf.Tensor)):
          return [len(tensor_tuple)]
      else:
          inner_size = get_size_recursively(tensor_tuple[0])
          return [len(tensor_tuple), *inner_size]
  
file_path: nebuly/optimization/nebullvm/nebullvm/tools/huggingface.py
imports: from collections import OrderedDict
  from typing import Union, Iterable, List, Dict, Tuple, Type, Any
  import numpy
  from nebullvm.core.models import Device, DeviceType
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch, Module
label_desc: Use image node_id 2 for calling a global function with example usage: get_size_recursively(tensor_tuple) and returns: list, list