code: def normalize_unsigned_saliency(saliency: np.ndarray) -> np.ndarray:
      """Normalizes positive only saliency map to range [0, 1]."""
      assert saliency.min() >= 0
      saliency = saliency.astype(np.float32)
      saliency = saliency - saliency.min()
      max_val = saliency.max()
      if max_val > 0:
          return saliency / max_val
      else:
          return saliency
  
file_path: lit/lit_nlp/lib/image_utils.py
imports: import base64
  import io
  from typing import Optional
  import matplotlib.cm
  import numpy
  from PIL import Image
  from PIL import ImageEnhance
label_desc: Use image node_id 5 for calling a global function with example usage: normalize_unsigned_saliency(saliency) and returns: unknown, saliency