code: def _tuple_splice_range(
      inputs: Union[None, Tuple], start: int, end: int
  ) -> Union[None, Tuple]:
      """
      Splices each tensor element of given tuple (inputs) from range start
      (inclusive) to end (non-inclusive) on its first dimension. If element
      is not a Tensor, it is left unchanged. It is assumed that all tensor elements
      have the same first dimension (corresponding to number of examples).
      The returned value is a tuple with the same length as inputs, with Tensors
      spliced appropriately.
      """
      assert (
          start < end
      ), "Start point must precede end point for batch splicing."
      if inputs is None:
          return None
      return tuple(
          inp[start:end] if isinstance(inp, torch.Tensor) else inp
          for inp in inputs
      )
  
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 4 for calling a global function with example usage: _tuple_splice_range(inputs, start, end) and returns: tuple, None