code: def test_normalize(self):
      # test normalization: must make every value non-negative
      _normalize(d1, d2)
      assert isinstance(
          d1, np.ndarray
      ), f"_normalize must keep inputs as ndarray, got {type(d1)}"
      assert isinstance(
          d2, np.ndarray
      ), f"_normalize must keep inputs as ndarray, got {type(d2)}"
      assert np.all(
          d1 >= 0
      ), "_normalize: negatives present in distribution 1"
      assert np.all(
          d2 >= 0
      ), "_normalize: negatives present in distribution 2"
      assert (
          abs(np.sum(d1) - 1) < 1e-6
      ), "_normalize: distribution 1 must sum to 1"
      assert (
          abs(np.sum(d2) - 1) < 1e-6
      ), "_normalize: distribution 2 must sum to 1"
  
imports: import numpy
  import pandas
  from aif360.metrics.ot_metric import _normalize, _transform, _evaluate
  from aif360.sklearn.metrics import ot_distance
  from ot import emd2
  import unittest
  from unittest import TestCase
label_desc: Use image node_id 1 for calling the TestNormalizeTransform obj's underlying member method code with example usage: obj.test_normalize() without return types