code: def test_transform(self):
      # check if transform returns np.ndarrays, makes sums equal
      d1_, d2_, dist_ = _transform(sd1, sd2, None)
      assert isinstance(
          d1_, np.ndarray
      ), f"_transform must return ndarrays, got {type(d1_)}"
      assert isinstance(
          d2_, np.ndarray
      ), f"_transform must return ndarrays, got {type(d2_)}"
      s1, s2 = np.sum(d1_), np.sum(d2_)
      assert (
          abs(s1 - s2) < 1e-6
      ), f"_transform must return arrays with equal sums, got {s1} and {s2}"
      assert (
          np.all(np.abs(dist - dist_)) < 1e-6
      ), "_transform distance matrix not calculated correctly"
  
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 2 for calling the TestNormalizeTransform obj's underlying member method code with example usage: obj.test_transform() without return types