code: def check_forward(self, x_data):
      with chainer.using_config("train", not self.test):
          x = chainer.Variable(x_data)
          y = self.link(x)
          self.assertEqual(y.dtype, self.dtype)
  
      sigma_batch = numpy.sqrt(self.var + self.eps)
      running_sigma = numpy.sqrt(self.running_var + self.eps)
      r = numpy.clip(
          sigma_batch / running_sigma, 1.0 / self.rmax, self.rmax
      )
      d = numpy.clip(
          (self.mean - self.running_mean) / running_sigma,
          -self.dmax,
          self.dmax,
      )
      y_expect = _batch_renormalization(
          self.expander,
          self.gamma,
          self.beta,
          self.x,
          self.mean,
          sigma_batch,
          self.test,
          r[self.expander],
          d[self.expander],
      )
  
      testing.assert_allclose(
          y.array, y_expect, **self.check_forward_optionss
      )
  
imports: import unittest
  import numpy
  import six
  import chainer
  from chainer.backends import cuda
  from chainer import links
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 2 for calling the BatchRenormalizationTest obj's underlying member method code with example usage: obj.check_forward(x_data) without return types