code: def test_batch_axis(self):
      shape = (2, 3, 4)
      for batch_axis in range(3):
          en = empirical_normalization.EmpiricalNormalization(
              shape=shape[:batch_axis] + shape[batch_axis + 1 :],
              batch_axis=batch_axis,
          )
          for _ in range(10):
              x = np.random.rand(*shape)
              en(torch.tensor(x))
  
file_path: pfrl/tests/nn_tests/test_empirical_normalization.py
imports: import unittest
  import numpy
  import pytest
  import torch
  from pfrl.nn import empirical_normalization
label_desc: Use image node_id 5 for calling the TestEmpiricalNormalization obj's underlying member method code with example usage: obj.test_batch_axis() without return types