code: def test_whitening_normalizer():
      x = np.random.normal(loc=0.2, scale=2.0, size=(1000, 5))
      normalizer = WhiteningNormalizer(shape=(5,))
      normalizer.update(x[:500])
      normalizer.update(x[500:])
  
      assert_allclose(normalizer.mean, np.mean(x, axis=0))
      assert_allclose(normalizer.std, np.std(x, axis=0))
  
      x_norm = normalizer.normalize(x)
      assert_allclose(
          np.mean(x_norm, axis=0),
          np.zeros(5, dtype=normalizer.dtype),
          atol=1e-5,
      )
      assert_allclose(
          np.std(x_norm, axis=0),
          np.ones(5, dtype=normalizer.dtype),
          atol=1e-5,
      )
  
      x_denorm = normalizer.denormalize(x_norm)
      assert_allclose(x_denorm, x)
  
file_path: keras-rl/tests/rl/test_util.py
imports: from __future__ import division
  import pytest
  import numpy
  from numpy.testing import assert_allclose
  from keras.models import Model, Sequential
  from keras.layers import Input, Dense, Concatenate
  from keras.optimizers import SGD
  import keras.backend
  from rl.util import clone_optimizer, clone_model, huber_loss, WhiteningNormalizer
label_desc: Use image node_id 6 for calling a global function with example usage: test_whitening_normalizer() without return types