code: def _format_and_verify_strides(
      strides: Union[
          None,
          int,
          Tuple[int, ...],
          Tuple[Union[int, Tuple[int, ...]], ...],
      ],
      inputs: Tuple[Tensor, ...],
  ) -> Tuple[Union[int, Tuple[int, ...]], ...]:
      # Formats strides, which are necessary for occlusion
      # Assumes inputs are already formatted (in tuple)
      if strides is None:
          strides = tuple(1 for input in inputs)
      if len(inputs) == 1 and not (
          isinstance(strides, tuple) and len(strides) == 1
      ):
          strides = (strides,)  # type: ignore
      assert isinstance(strides, tuple) and len(strides) == len(
          inputs
      ), "Strides must be provided for each input tensor."
      for i in range(len(inputs)):
          assert isinstance(strides[i], int) or (
              isinstance(strides[i], tuple)
              and len(strides[i]) == len(inputs[i].shape) - 1  # type: ignore
          ), (
              "Stride for input index {} is {}, which is invalid for input with "
              "shape {}. It must be either an int or a tuple with length equal to "
              "len(input_shape) - 1."
          ).format(
              i, strides[i], inputs[i].shape
          )
  
      return strides
  
imports: import typing
  from inspect import signature
  from typing import Any, Callable, List, Tuple, TYPE_CHECKING, Union
  import torch
  from captum._utils.common import _format_baseline, _format_output, _format_tensor_into_tuples, _validate_input
  from captum._utils.typing import BaselineType, Literal, TargetType, TensorOrTupleOfTensorsGeneric
  from captum.attr._utils.approximation_methods import SUPPORTED_METHODS
  from torch import Tensor
label_desc: Use image node_id 11 for calling a global function with example usage: _format_and_verify_strides(strides, inputs) and returns: strides