code: def _normalize_scale(attr: ndarray, scale_factor: float):
      assert scale_factor != 0, "Cannot normalize by scale factor = 0"
      if abs(scale_factor) < 1e-5:
          warnings.warn(
              "Attempting to normalize by value approximately 0, visualized results"
              "may be misleading. This likely means that attribution values are all"
              "close to 0."
          )
      attr_norm = attr / scale_factor
      return np.clip(attr_norm, -1, 1)
  
imports: import warnings
  from enum import Enum
  from typing import Any, Iterable, List, Optional, Tuple, Union
  import numpy
  from matplotlib import cm, colors, pyplot
  from matplotlib.collections import LineCollection
  from matplotlib.colors import LinearSegmentedColormap
  from matplotlib.figure import Figure
  from matplotlib.pyplot import axis, figure
  from mpl_toolkits.axes_grid1 import make_axes_locatable
  from numpy import ndarray
label_desc: Use image node_id 2 for calling a global function with example usage: _normalize_scale(attr, scale_factor) and returns: np