code: def _test_small(self, gpu):
      en = empirical_normalization.EmpiricalNormalization(10)
      if gpu >= 0:
          chainer.cuda.get_device_from_id(gpu).use()
          en.to_gpu()
  
      xp = en.xp
  
      xs = []
      for t in range(10):
          x = xp.random.normal(loc=4, scale=2, size=(t + 3, 10))
          en(x)
          xs.extend(list(x))
      xs = xp.stack(xs)
      true_mean = xp.mean(xs, axis=0)
      true_std = xp.std(xs, axis=0)
      xp.testing.assert_allclose(en.mean, true_mean, rtol=1e-4)
      xp.testing.assert_allclose(en.std, true_std, rtol=1e-4)
  
file_path: chainerrl/tests/links_tests/test_empirical_normalization.py
imports: import unittest
  import chainer
  from chainer import testing
  import numpy
  from chainerrl.links import empirical_normalization
label_desc: Use image node_id 3 for calling the TestEmpiricalNormalization obj's underlying member method code with example usage: obj._test_small(gpu) without return types