code: def get_features_in_step(
      max_steps_per_input: int, input_shape: Tuple[int, ...]
  ):
      """
      Get the number of features in the iteration.
  
      Parameters
      ----------
      max_steps_per_input: integer
          The number of repeated iterations on an image.
      input_shape: tuple
          Input shape.
  
      Returns
      -------
      float
          Product of the input shape divided by the maximum number of steps.
      """
      return int(np.prod(input_shape) / max_steps_per_input)
  
imports: import copy
  import re
  from importlib import util
  from typing import Any, Dict, Optional, Sequence, Tuple, Union, List, TypeVar
  import numpy
  from skimage.segmentation import slic, felzenszwalb
  from quantus.helpers import asserts
  from quantus.helpers.model.model_interface import ModelInterface
label_desc: Use image node_id 5 for calling a global function with example usage: get_features_in_step(max_steps_per_input, input_shape) and returns: int