code: def test_normalize_signed_saliency(self):
      # Test the case when the magnitude of positive numbers is higher.
      a = np.linspace(-10, 100, num=101, endpoint=True)
      a_norm = image_utils.normalize_signed_saliency(a)
      self.assertAlmostEqual(a_norm.max(), 1.0)
      self.assertAlmostEqual(a_norm.min(), 0.45)
  
      # Test the case when the magnitude of negative numbers is higher.
      a = np.linspace(-100, 10, num=101, endpoint=True)
      a_norm = image_utils.normalize_signed_saliency(a)
      self.assertAlmostEqual(a_norm.max(), 0.55)
      self.assertAlmostEqual(a_norm.min(), 0.0)
  
file_path: lit/lit_nlp/lib/image_utils_test.py
imports: from absl.testing import absltest
  from absl.testing import parameterized
  from lit_nlp.lib import image_utils
  import numpy
  from PIL import Image
label_desc: Use image node_id 7 for calling the ImageUtilsTest obj's underlying member method code with example usage: obj.test_normalize_signed_saliency() without return types