code: def _select_example(curr_arg: Any, index: int, bsz: int) -> Any:
      if curr_arg is None:
          return None
      is_tuple = isinstance(curr_arg, tuple)
      if not is_tuple:
          curr_arg = (curr_arg,)
      selected_arg = []
      for i in range(len(curr_arg)):
          if (
              isinstance(curr_arg[i], (Tensor, list))
              and len(curr_arg[i]) == bsz
          ):
              selected_arg.append(curr_arg[i][index : index + 1])
          else:
              selected_arg.append(curr_arg[i])
      return _format_output(is_tuple, tuple(selected_arg))
  
file_path: captum/captum/attr/_utils/batching.py
imports: import typing
  import warnings
  from typing import Any, Callable, Iterator, Tuple, Union
  import torch
  from captum._utils.common import _format_additional_forward_args, _format_output, _format_tensor_into_tuples, _reduce_list
  from captum._utils.typing import TargetType, TensorOrTupleOfTensorsGeneric, TupleOrTensorOrBoolGeneric
  from captum.attr._utils.approximation_methods import approximation_parameters
  from torch import Tensor
label_desc: Use image node_id 7 for calling a global function with example usage: _select_example(curr_arg, index, bsz) and returns: _format_output, None